SPAWAR

Systems Center

San Diego

Ex-ORISKANY Artificial Reef Project

January 2006 

FINAL REPORT

Prospective Risk Assessment Model (PRAM)

Version 1.4C
Ex-ORISKANY 

Artificial Reef Project

Prospective Risk 

Assessment Model 

(PRAM) Version 1.4c

FINAL REPORT

Prepared for:

Program Executive Office Ships (PMS 333)

Prepared by:

Navy Environmental Health Center

URS Corporation

SPAWAR Systems Center, San Diego
TABLE OF CONTENTS

SSC-SD/NEHC/URS i 

Acronyms and Abbreviations ............................................................................vi 

Section 1. Introduction to Prospective Risk Assessment Model (PRAM).................. 1

1.1 Model Background and Development............................................................................. 1

1.2 Generalized Description of PRAM.................................................................................. 3

1.2.1 Introduction............................................................................................................. 3 

1.2.2 Generalized Model Construct ................................................................................. 4 

1.2.3 Rationale for PRAM Development......................................................................... 5 

1.2.4 Constructing the PRAM.......................................................................................... 5 

1.2.5 PRAM Format and User Interface .......................................................................... 7 

1.2.6 Empirical Data Used in PRAM............................................................................... 7 

1.3 Versions of the PRAM Model .......................................................................................... 8

1.4 Purpose of the Document ................................................................................................. 9

1.4.1 Model Objectives.................................................................................................... 9 

Section 2. Model Assumptions .............................................................................................. 1

2.1 Model Construct: Basic Concept.................................................................................... 1

2.2 Physical and Chemical Processes of PCBs ..................................................................... 3

2.2.1 PCB Release from Shipboard Materials: Normalized Release Rates..................... 3 

2.2.2 Physical Transport Mechanisms ............................................................................. 7 

2.2.2.1 Diffusion .................................................................................................. 7 

2.2.2.2 Dispersion ................................................................................................ 9 

2.2.2.3 Advection............................................................................................... 11 

2.2.3 Partitioning Coefficients ....................................................................................... 12 

2.2.4 Transformation...................................................................................................... 14 

2.3 Abiotic Model Selection of PCB Fate and Transport.................................................. 15

2.3.1 The Fugacity Multimedia Approach..................................................................... 15 

2.3.1.1 Level I Fugacity Model.......................................................................... 16 

2.3.1.2 Level II Fugacity Model ........................................................................ 20 

2.3.1.3 Level III Fugacity Model....................................................................... 21 

2.3.1.4 Model IV Fugacity Model ..................................................................... 23 

2.3.2 PRAM Level III Fugacity Model and Algorithms................................................ 23 

2.3.2.1 Non-Diffusive Transport Within the PRAM ......................................... 25 

2.3.2.2 Diffusive Transport Within the PRAM.................................................. 28 
TABLE OF CONTENTS

SSC-SD/NEHC/URS ii 

2.3.2.3 Surface Water and Air Diffusive Boundary........................................... 29 

2.3.2.4 Lower Water Column and Upper Water Column Diffusive Boundary . 34 

2.3.2.5 Lower Water Column and Sediment Bed Diffusive Boundary ............. 35 

2.3.2.6 Compartmental Fugacities and Media PCB Concentrations ................. 37 

2.4 The PRAM Food Web and Trophic Transfers of PCBs ............................................. 42

2.4.1 Food Web Communities Considered Within the PRAM...................................... 43 

2.4.2 PRAM Food Web Community Structure.............................................................. 45 

2.4.2.1 Representative Herbivores..................................................................... 45 

2.4.2.2 Representative Detritivores.................................................................... 49 

2.4.2.3 Representative Omnivores..................................................................... 51 

2.4.2.4 Representative Primary Carnivores ...................................................... 52 

2.4.2.5 Representative Top Carnivores.............................................................. 53 

2.4.3 Generalized Representative Dietary and Water Exposures for Use in Modeling 

PCB Food Web Transfers ..................................................................................................... 54 

2.4.3.1 Pelagic Community................................................................................ 54 

2.4.3.2 Reef Community.................................................................................... 56 

2.4.3.3 Benthic Community............................................................................... 58 

2.5 PRAM PCB Trophic Transfer Methods and Algorithms........................................... 60

2.5.1 Equations that Describe Food Transfers of PCBs ................................................ 64 

2.5.1.1 Bioconcentration Factors ....................................................................... 64 

2.5.1.2 Tissue Concentrations............................................................................ 66 

2.5.1.3 Bioaccumulation Factors ....................................................................... 67 

2.5.2 Derivation of Rate Constants................................................................................ 68 

2.5.2.1 Oxygen Consumption Rates, Dietary Ingestion Rates, and Bioenergetics

 68 

2.5.2.2 Total Energy Consumption and Ingestion Rates ................................... 72 

2.5.2.3 Assimilation Efficiencies Across Gastrointestinal Tracts ..................... 74 

2.5.2.4 Uptake Rate Constants and Assimilation Efficiencies Across Respiratory 

Tissues 76 

2.5.2.5 Depuration Rates (Elimination and Metabolism) .................................. 78 

2.5.2.6 Derivation of Growth Rates from Bioenergetic Budget ........................ 79 

2.6 Sensitivity Analyses......................................................................................................... 80

2.6.1 PRAM Version 1.1 Testing .................................................................................. 80 

2.6.2 PRAM Version 1.2 Testing .................................................................................. 80 

2.6.3 PRAM Version 1.4c Testing................................................................................. 83 
TABLE OF CONTENTS

SSC-SD/NEHC/URS iii 

2.7 Model Uncertainties and Limitations ........................................................................... 91

2.7.1 Strength................................................................................................................. 91 

2.7.2 Limitations ............................................................................................................ 92

Section. References .................................................................................................................. 1

TABLES 

Table 1 Summary of Analysis of PCB Release Rate (Leachate) Data for Materials Found 

Onboard Ex-US Navy Vessels (Adapted from R. George, SSC-SD, 2004) 

Table 2 Physical-Chemical Parameters for PCB Homologs Used in PRAM 

Table 3 Example PCB Degradation Rates in Surface Water 

Table 4 Fugacity-Based PCB Transport Coefficients Used in PRAM 

Table 5 Food Web Diet Compositions Assumed for PRAM and the ex-ORISKANY 

Memorial Reef 

Table 6 Food Web Water Exposure Values Assumed for PRAM and the ex-ORISKANY 

Memorial Reef (Modified with Comments from Biology Technical Working 

Group; Revised, 12/31/04) 

Table 7 Biological Parameters for Food Web Components Within PRAM 

Table 8 Temperature and Body Weight Dependent Oxygen Consumption Regressions for 

the Biological Components Within PRAM 

Table 9 Physical Boundaries and Conditions for the ex-ORISKANY Memorial Reef Site 

Table 10 Summary of Statistical Analysis of PCB Concentrations in Materials Onboard the 

ex-ORISKANY 

Table 11 Mass Estimates of PCB-Containing Materials Onboard the ex-ORISKANY 

FIGURES 

Figure 1 Flow Diagram for the Development of an Environmental Fate and Transport 

(Adapted from Mackay et al., 1995) 

Figure 2 PRAM: Modules, Input and Outputs 

Figure 3 Abiotic and Biotic-Food Web Modules in PRAM 

Figure 4 Compartment Identification for PCB Transport in PRAM

Figure 5 Example PCB Leach Rate Study Results: Pentachlorobiphenyl (CL5) in 

Bulkhead Insulation and Ventilation Gaskets (Adapted from R. George, 

SPAWAR, 2004) 

Figure 6 Transport Coefficients and Conceptual Design for PCB Transport in PRAM 

Figure 7 Fugacity-Based Transport and Transfers of PCBs in PRAM 

Figure 8 Depiction of Food Web Used in PRAM

Figure 9 Assimilation Efficiencies Across Gastro-Intestinal Tracts as Function of 

Chemical-Specific Kow in the Food Web Module of PRAM 

Figure 10 Relationship Between Kow and Elimination Rates (Ke) of PCB in Aquatic 

Animals 
TABLE OF CONTENTS

SSC-SD/NEHC/URS iv 

FIGURES (Continued) 

Figure 11 Logic Diagram for Statistical Estimation of Reasonable Maximum PCB 

Concentration and Central Tendency Concentration in Source Material Onboard 

the ex-ORISKANY 

Figure 12 PCB Concentrations Presented as Box-Whisker Plots for Materials Found 

Onboard the ex-ORISKANY 

Figure 13 Zone of Influence (ZOI) Ellipse Area Calculations 

Figure 14 Risk Characterization Module in PRAM 

Figure 15 Site Conceptual Exposure Model (SCEM) 
TABLE OF CONTENTS

SSC-SD/NEHC/URS v 

APPENDICES 

Appendix A Regression Analyses: PCB Leach Rates and Material Fractions 

Appendix B Calculation of Homolog-Specific Kows 

Appendix C Calculation of Homolog-Specific Vapor Pressures 

Appendix D Fugacity Equation Substitutions 

Appendix E Organism Respiration Regressions 

Appendix F Zone of Influence 

Appendix G Clarifications/Additions and Responses to Biology TWG Comments on Navy 

Environmental Health Center (NEHC) Proposed Food Web Diet – Water 

Exposure Matrix 

Appendix H Example PRAM Output 

Appendix I Response to EPA Comments on Ex-ORISKANY Artificial Reef Project: 

Prospective Risk Assessment Model (PRAM). June 2005 (Draft Final) 

Appendix J Response to EPA’s December 2, 2005 Second Round of Comments on ExORISKANY Artificial Reef Project: Prospective Risk Assessment Model 

(PRAM). June 2005 (Draft Final). 

Appendix K An Evaluation of the Prospective Risk Assessment Model (PRAM Version 1.4c) 

to Predict the Bioaccumulation of PCBs in the Food Chain of a Sunken Ship 

Artificial Reef. 
TABLE OF CONTENTS

SSC-SD/NEHC/URS vi 

ACRONYMS AND ABBREVIATIONS 

ATSDR Agency for Toxic Substances and Disease Registry 

BAF biological accumulation factor 

BCF bioconcentration factor 

CB Chlorobiphenyl 

CalTOX California EPA Multimedia Total Exposure Model for Hazardous Waste Sites 

CFR Code of Federal Regulations 

cm Centimeters 

CNO Chief of Naval Operations 

COC constituent of concern 

CTE central tendency exposure 

d day 

deca-CBs PCB congeners with 10 of 10 possible chlorine substitutions 

DO dissolved oxygen 

DOC dissolved organic carbon 

ECETOC European Centre for Ecotoxicology and Toxicology of Chemicals 

f fugacity 

FI fraction of fish ingested 

FWCC Florida Fish and Wildlife Conservation Commission 

FWR Final Weight Report 

g gram 

GUI Graphical User Interface 

hexa-CBs PCB congeners with 6 of 10 possible chlorine substitutions 

hr hour 

IR ingestion rate 

IRIS Integrated Risk Information System 

kg kilogram 

Koc water to particulate organic carbon partitioning coefficient 

Kdoc water to dissolved organic carbon partitioning coefficient 

Kow octanol to water partitioning coefficient 

L Liters 

LAARS large area artificial reef site 

LLNL Lawrence Livermore National Laboratory 

m meter 

MAMES Mississippi-Alabama Marine Ecosystem Study 

mg milligram 
TABLE OF CONTENTS

SSC-SD/NEHC/URS vii 

ACRONYMS AND ABBREVIATIONS (Continued)

MMS Minerals Management Service 

mol mole 

mono-CBs PCB congeners with 1 of 10 possible chlorine substitutions 

NAVSEA Naval Sea Systems Command 

NDBC National Data Buoy Center 

NEHC Navy Environmental Health Center 

ng nanogram 

NMFS National Marine Fisheries Service 

NOAA National Oceanic and Atmospheric Administration 

nona-CBs PCB congeners with 9 of 10 possible chlorine substitutions 

Pa Pascals 

PCB Polychlorinated Biphenyl 

PRAM Prospective Risk Assessment Model 

QSAR Quantitative structure activity relationship 

RAGS Risk Assessment Guidance for Superfund 

REEFEX Reef Exercise (Sunken Vessels Used to Construct Artificial Reefs on the 

Continental Shelf of the US) 

RfD reference dose 

RISC Risk-Integrated Software for Clean-ups 

RME reasonable maximum exposure 

s seconds 

SCEM Site Conceptual Exposure Model 

SF slope factor 

SHHRA Supplemental Human Health Risk Assessment 

SSC-SD Space and Naval Warfare Systems Center (SPAWARSYSCEN) San Diego, an 

organization of the Space and Naval Warfare Systems Command (SPAWAR) 

SPAWAR Space and Naval Warfare 

TDM Time-dynamic model 

TL Trophic Level 

TWG Technical Working Group 

UCD University of California – Davis 

UCL Upper confidence limit 

USEPA U.S. Environmental Protection Agency 

USGS United States Geological Survey 
TABLE OF CONTENTS

SSC-SD/NEHC/URS viii 

ACRONYMS AND ABBREVIATIONS (Continued) 

ZOI Zone of Influence 
SECTIONONE Introduction to Prospective Risk Assessment 

Model (PRAM) 

SSC-SD/NEHC/URS 1 

1. Section 1 ONE Introduction to Prospective Risk Assessment Model (PRAM) 

This document describes a predictive model, Prospective Risk Assessment Model (PRAM), 

initially developed under the technical direction of the Navy Environmental Health Center 

(NEHC), Portsmouth, Virginia and more recently under the technical direction of SPACE 

and NAVAL WARFARE SYSTEMS CENTER – San Diego (SSC-SD). Its application 

supports the environmental evaluation of a decommissioned Navy vessel (ex-ORISKANY) 

proposed for sinking and use as a potential artificial reef. 

The purpose of PRAM is to predict concentrations of PCBs in abiotic media, predict 

concentrations of PCBs in tissue of marine organisms on or near the sunken ex-ORISKANY, 

and estimate human health risks for use in a human health risk assessment (Ex-Oriskany 

Artificial Reef Project Human Health Risk Assessment) and ecological risk assessment (ExOriskany Artificial Reef Project Ecological Risk Assessment). 

These predictions reflect the incremental exposure to PCBs associated with the presence of 

the sunken vessel after its colonization as an artificial reef under steady state assumptions. A 

companion model, the Time Dynamic Model (TDM), predicts the abiotic concentrations 

during the first two years after sinking, a period that we assume is non-steady state 

(NEHC/SSC-SD. 2005). 

These incremental estimates of exposure associated with sinking the ex-ORISKANY do not 

include or estimate background1

 concentrations of PCBs in the local marine environment. 

1.1 MODEL BACKGROUND AND DEVELOPMENT 

The PRAM predictions apply to a proposed future environmental condition, the biological 

colonization of a sunken ship to form an artificial reef. Therefore, we characterized the risk 

assessments as prospective. An interagency Technical Working Group (TWG)2

 first 

entertained the concept of such a prospective risk assessment at a 1999 meeting. The concept 

was briefed to the Navy as: 

 

1

 Background referring to the in-situ concentration of PCBs within the system prior to the deployment of a 

vessel for artificial reef building. 2

 The REEFEX interagency Technical Working Group (TWG) was comprised of U.S. Environmental 

Protection Agency (USEPA) representatives from the Office of Pollution Prevention and Toxics (USEPA 

OPPT), the Office of Water (USEPA OW), the state of Florida (Florida Fish and Wildlife Commission, 

Escambia County Marine Resources Division), Navy representatives, and contractors to the Navy. 
SECTIONONE Introduction to Prospective Risk Assessment 

Model (PRAM) 

SSC-SD/NEHC/URS 2 

“An assessment of risk that is based on known/estimated contaminant 

source values, modeled fate and transport values, and assumptions about 

exposure pathways and extent of exposure” (A. Lunsford, NEHC – 

RDML L.C. Baucom Briefing, February 23, 2000).

Steps in Model Development 

The history of PRAM development included: 

2000 

An initial demonstration program, with all of the relevant equations considered at that time, 

presented to the REEFEX TWG; 

Late 2000 to 2001 

NEHC reviewed the modeling algorithms and mathematical assumptions in PRAM; 

2001 

Formal sensitivity analysis on the list of variables within the PRAM; 

Late 2001 

Incorporation of draft leachate rates of PCB-containing bulk product materials developed by 

the SSC-SD Marine Environmental Support Office 

Research Triangle Institute (RTI) provided review that resulted in, among other things, the 

incorporation of a compartment, interior to the sunken vessel, into which PCBs are initially 

released; 

The Navy addressed comments from external reviewers (non-Navy TWG representatives); 

2003 

The Navy tested PRAM using data obtained from the ex-AGERHOLM (a Gearing class 

destroyer [DD-826], deployed in deep water off the coast of California); and published the 

results (Goodrich et al., 2003). 
SECTIONONE Introduction to Prospective Risk Assessment 

Model (PRAM) 

SSC-SD/NEHC/URS 3 

July 2004 

The Navy provided PRAM (Version 1.3) to the USEPA3

 and State of Florida representatives 

for review in July 2004. The Navy incorporated experimentally derived leach rates for PCB 

homologs into PRAM and changed various parameters (e.g. vessel dimensions, PCB source 

material amounts, and water column height) to make the model specifically applicable to the 

proposed ex-ORISKANY4

 Memorial Reef. 

This document addresses PRAM Version 1.4c. Subsection 1.3 describes the technical 

enhancements added to PRAM Version 1.3 to develop Version 1.4c. 

1.2 GENERALIZED DESCRIPTION OF PRAM 

This section provides a generalized description of PRAM. Sections 2, 3, and 4 of this 

document provide more scientific and detailed descriptions of the model’s construct, 

algorithms, and assumptions. 

1.2.1 Introduction 

Within PRAM there are three modules (Figure 2): a multimedia, environmental chemical 

fate module, a biotic food web module, and a risk characterization module. These three 

modules are directly linked within PRAM, such that the model begins with a known quantity 

of a chemical, or known quantities of several chemicals (chemical source terms), simulates 

how these chemicals will be distributed within a marine environment, simulates how the 

chemicals will be taken up and bioaccumulated in living organisms, and finally, calculates 

the human health risks (carcinogenic risks and non-cancer hazards) that would be associated 

with consuming fish that have accumulated those chemicals. It also provides estimates of 

exposure point concentrations to assess impacts to survival, growth, and reproduction of 

representative receptors from pelagic, benthic, and reef communities associated with the 

artificial reef . 

 

3

 The PRAM (Version 1.3) was provided to EPA Region 4, EPA Headquarters, EPA OPPT, and EPA National 

Exposure Research Laboratory (NERL) representatives for review. 4

 Ex-ORISKANY (CVA-34) is the last Essex class aircraft carrier that served the Navy fleet for more than 25 

years, maintaining a powerful presence during the Korean War and the Vietnam conflict. The vessel was 

launched on October 13, 1945 and was commissioned on September 25, 1950. It was decommissioned in 

1976. 
SECTIONONE Introduction to Prospective Risk Assessment 

Model (PRAM) 

SSC-SD/NEHC/URS 4 

1.2.2 Generalized Model Construct 

The following illustration shows the general relationship among the three PRAM modules. 

In the illustration: 

• Inputs to the PRAM are the chemical source terms specific to a particular 

sunken vessel. For the ex-ORISKANY risk assessment, the primary chemical 

of concern is PCBs. The amount of each PCB homolog (mono- through decachlorobiphenyl) remaining in materials onboard the ex-ORISKANY when it is 

deployed as an artificial reef are the source terms (inputs) to PRAM for this 

assessment. 

• Module 1 is the multimedia environmental chemical fate module. It 

incorporates the equations and physical parameters that govern the processes 

by which PCB homologs are released and dispersed in the marine 

environment surrounding the sunken vessel, and distributed into the various 

abiotic media (water, suspended solids, dissolved organic carbon, sediment, 

and air) within a defined volume around the sunken vessel. 

• Module 2 is the PRAM biotic-food web module. It incorporates the equations 

and parameters that govern the processes by which the PCB homologs in the 

abiotic media accumulate through the food web and into the tissues of marine 

biota. 

• Module 3 is the risk characterization model. It incorporates the equations and 

parameters for assessing human health risks from ingestion of PCB 

contaminated fish. 

PRAM

INPUTS Module OUTPUTS 

(1)

Module 

(2)

Module 

(3) (PCB source terms) (Abiotic media concentrations) 

(Fish tissue concentrations) 

(Human health risks) 
SECTIONONE Introduction to Prospective Risk Assessment 

Model (PRAM) 

SSC-SD/NEHC/URS 5 

• Outputs of the PRAM are abiotic media concentrations from the multimedia 

environmental model of chemical fate; tissue concentrations from the biotic 

food web module; and cancer risk and non-cancer hazard estimates for adults 

and children that are associated with chronic ingestion of representative reef 

fish. 

Section 2 of this document expands upon these descriptions. 

1.2.3 Rationale for PRAM Development 

The PRAM was developed in order to be able to assess the potential risks, to human health 

and the environment, that could be associated with leaving PCBs of greater than or equal to 

50 ppm on decommissioned ships that will be deployed as artificial reefs. 

1.2.4 Constructing the PRAM 

A marine model must consider that there are few, if any, physical boundaries in an ocean 

environment (e.g., no nearby walls, stream banks, or other barriers). Fate and transport 

models must address physical processes such as ocean currents, tides, the large volume of 

water into which chemicals are released; chemical/physical properties such as the solubilities 

of different chemicals; diffusion limitations; and the capacities of the various media within 

the marine environment to adsorb or absorb the chemicals. 

Eventually, the dissolved chemicals that have not been absorbed into the sediment or other 

media compartments will be distributed over such a large volume of water that the 

concentrations will become very low. Thus, for a marine chemical fate and transport model, 

one must define a relevant exposure zone around the point of release, within which marine 

organisms may be assumed to be exposed to higher-than-background levels of the chemical. 

This exposure zone is referred to as a Zone of Influence (ZOI) throughout this report. 

Multimedia Environmental Chemical Fate Module – A Fugacity Approach 

The PRAM multimedia environmental chemical fate module is a fugacity model (Mackay, 

2001). 

The fugacity model is a compartment model that has the advantage of allowing the user to 

select or specify the compartments and the reactions within them. Therefore, one is able to 
SECTIONONE Introduction to Prospective Risk Assessment 

Model (PRAM) 

SSC-SD/NEHC/URS 6 

use the fugacity model to predict the partitioning of PCBs among abiotic media only, and 

then use this output (abiotic media concentrations) as input to a separate calculation in the 

biotic food web module. The underlying assumption in doing so is that the partitioning to 

biota or biological degradation will not substantially affect abiotic partitioning. This 

assumption likely increases the predicted concentrations in the abiotic media that are then 

input to the biotic food web module. 

Biotic Food Web Module 

While the biotic food web module is a de novo construction, it uses well known and accepted 

equations to estimate biological uptake and bioaccumulation in representative species at four 

trophic levels within each of three different communities associated with artificial reefs 

(pelagic community, reef-associated community, and benthic community). 

This module required a great deal of information from the literature about: 

• the energy budgets of representative marine fish species (i.e. respiration, growth and 

reproduction, excretion) 

• the biological makeup (average adult body weight, fraction of lipid content, fraction 

of water content, average caloric intake, fraction of metabolizable energy relative to 

gross energy). 

• their diets (e.g., fraction of suspended solids in diet, fraction of phytoplankton in diet, 

fraction of zooplankton in diet, fraction of sessile filter feeders, and fractions of 

infaunal and epifaunal benthos in diet, fractions of benthic foragers and reef/vessel 

foragers in diet). 

In many cases, the values of specific parameters, such as diet fraction or respiration rates, 

were the result of a consensus among members of the TWG. 

Risk Characterization Module 

The equations used in the risk characterization module to estimate human health risk are 

from the U.S. EPA publication “Risk Assessment Guidance for Superfund” (RAGS, 1989). 

Other U.S. EPA guidance documents such as the Exposure Factors Handbook (1997) 

provided input parameters such as the average and upper bound fish ingestion rates for the 

Gulf States. 
SECTIONONE Introduction to Prospective Risk Assessment 

Model (PRAM) 

SSC-SD/NEHC/URS 7 

1.2.5 PRAM Format and User Interface 

PRAM was developed with Microsoft ExcelTM software, and Visual Basic++TM. All of the 

equations and input parameters used in the model are resident in an Excel database that is 

supported by a Graphical User Interface (GUI). The database and GUI are bundled in an 

electronic file, PRAM, Version 1.4c. Electronic copies of the model have been provided to 

personnel at the U.S. EPA, the State of Florida, and the U.S. Navy. 

The GUI of PRAM provides users with many options. The opening screen allows the user to 

either: 

• Run the program (using default values) to estimate PCB concentrations in abiotic and 

biotic media, and estimate human health risks; or 

• View the individual modules that comprise the PRAM, and the various equations, 

parameters, and values that are used in each of the modules. 

The user can change input parameter values such as lipid fraction of a representative 

organism or mass of PCB source material. Users can reset input parameters to the default 

values. 

1.2.6 Empirical Data Used in PRAM 

The PRAM relied on data from published scientific literature and three significant sources: 

• The December 7, 2004 CACI report, “Final Report, Revision 4, 

Polychlorinated biphenyls (PCB) Source Term Estimates for ex-ORISKANY 

(CVA-34)” 

• The October, 2004 SSC-SD report, “Draft Final Report: Investigation of 

Polychlorinated Biphenyl (PCB) Release-Rates from Selected Shipboard 

Solid Materials Under Laboratory-Simulated Shallow Ocean (Artificial Reef) 

Environments” 

• The June, 2004 Escambia County, FL report, “Escambia County Fish 

Consumption Survey” 
SECTIONONE Introduction to Prospective Risk Assessment 

Model (PRAM) 

SSC-SD/NEHC/URS 8 

1.3 VERSIONS OF THE PRAM MODEL 

This document presents the technical details of PRAM 1.4c. 

Changes made from PRAM Version 1.3 (July 2004) to Version 1.3c (September 2004) 

included: 

1. Incorporating a child receptor into the risk characterization module. 

2. Updating default values, to reflect ex-ORISKANY-specific exposure scenario. 

3. Fixing typographical errors in PRAM Version 1.3 modules for solving to non-risk 

PCB load onboard and risk estimates for range of PCB loads onboard. 

4. Reprogramming PRAM to provide additional outputs from the model, including: 

bioaccumulation factors calculated for each trophic level for each homolog series; 

feeding rates calculated for each trophic level; and growth rates calculated for each 

trophic level. 

5. Incorporating revised leachate rate data (from SSC-SD, 2004) into the model. 

6. Adding a factor to account for metabolizable energy, versus gross energy, of dietary 

items. 

Changes made from PRAM Version 1.3c (September 2004) to Version 1.4c (May 2005) 

included: 

1. Revising fish respiration parameters to reflect marine species. 

2. Incorporating gill efficiency correction for PCB uptake rates in fish. 

3. Refining algorithms to achieve Level III fugacity, versus using a Level II fugacity 

approach. 

4. Incorporating a pycnocline boundary condition that divides the external water column 

into two layers (i.e., into upper, epilimnion layer and lower, hypolimnion layer). 

5. Revising the biotic-food web module for the lower epilimnion layer and designing a 

new biotic-food web module for the upper epilimnion layer (Appendix G), per dietwater exposure matrix table developed with TWG. 
SECTIONONE Introduction to Prospective Risk Assessment 

Model (PRAM) 

SSC-SD/NEHC/URS 9 

6. Constructing an interface or macro to receive TDM abiotic media concentration 

output to estimate biota concentrations in water column (Time Dynamic Model 

Documentation, January 2006). 

7. Incorporating multiple zones of influence according to a negotiated agreement 

established in the TWG based on feeding behavior, range and habitat of relevant fish 

species of concern. 

8. Modifying the GUI to provide default input values for parameters and to generate 

output from the model, based on the above structural modifications. 

9. Conducting a preliminary quality assurance check, testing, and sensitivity analysis 

(Appendix K). 

1.4 PURPOSE OF THE DOCUMENT 

The purpose of this document is to provide background and technical information to USEPA, 

State of Florida, and external reviewers on PRAM Version 1.4c as revised from versions 1.3 

and 1.3c in response to comments and resolution of issues by the TWG. 

It provides PRAM version 1.4c objectives and background information, and details the 

scientific basis, model structure, assumptions, input parameters, output, findings of limited 

testing and sensitivity analysis, and uncertainties/limitations. PRAM Version 1.4c, in 

conjunction with the Time Dynamic Model (TDM) (NEHC/SSC-SD, 2006) supports both a 

Human Health Risk Assessment and an Ecologcial Risk Assessment 

1.4.1 Model Objectives 

PRAM Version 1.4c has two objectives: 

• Predict human health risks from the fish ingestion pathway of anglers at or 

near the ex-ORISKANY artificial reef under steady-state (i.e., chronicexposure) conditions. 

• Estimate PCB concentrations in a variety of representative biological species 

that reside on or near the artificial reef during the first two years post sinking 

under an assumption of a changing leach rate. 
SECTIONONE Introduction to Prospective Risk Assessment 

Model (PRAM) 

SSC-SD/NEHC/URS 10 

Comments or questions relating to this document should be sent to: 

Bill Wild, Project Technical Lead - REEFEX 

Space and Naval Warfare Systems Center - San Diego 

Environmental Sciences and Applied Systems Branch (2375) 

Bldg 111, RM 218 

53475 Strothe Rd. 

San Diego, CA 92152-6 

Phone: 619 55-32781 

Email: bill.wild@navy.mil 

 
SECTIONTWO Model Assumptions 

SSC-SD/NEHC/URS 1 

2. Section 2 TWO Model Assumptions 

This section describes PRAM’s modules and their governing equations, describes how the 

model algorithm works, and points out its strengths and limitations. Figure 3 presents the 

modules. 

2.1 MODEL CONSTRUCT: BASIC CONCEPT 

The PRAM is a compartmental model that spatially and biologically defines an environment 

into which PCBs are released. Compartmental models consist of interconnected 

compartments (Figure 4). The arrows represent the PCB exchanges, or fluxes, that occur 

between the compartments. The initial source of PCBs within the system is from the sunken 

ship compartment (Compartment 5). 

The PRAM is an open system5

 model where some material will leave the modeled 

environment due to processes such as a current flowing through the water compartments, a 

current flowing through the air compartment, and possible sediment burial. 

The model assumes that each of the compartments: 

• is homogeneously mixed 

• exchanges chemical substances and energy following thermodynamic processes that 

can be described mathematically 

• has a defined geometry, volume, density, and mass. 

PRAM contains 11 categories of abiotic environmental compartments outside the sunken 

vessel (air, aerosols in air, an upper water column and lower water column separated by a 

pycnocline, suspended solids in the upper and lower water columns, dissolved organic 

carbon in the upper and lower water columns, sediment on the ocean floor, sediment pore 

water, and dissolved organic carbon in pore water). 

PRAM has five basic assumptions for the exposure modeling6

 (adapted from Trapp and 

Matthies 1996): 

 

5

 Closed compartmental systems only interact with each other and are analogous to a closed bottle or jar 

containing a liquid and air space. PRAM is an open compartmental system where, for example, water flows 

into and out of the modeled environment and is analogous to water flowing through an open trough with its 

inlet and outlet. 6

 In the context here, exposure modeling refers to the estimation of PCB chemical concentrations in abiotic 

media to which biota (plants and animals) can be directly exposed. 
SECTIONTWO Model Assumptions 

SSC-SD/NEHC/URS 2 

1. The environmental compartments can be defined to represent phases or mixtures of 

phases in a thermodynamic sense (a phase is a physical stage of a chemical). 

2. Rules and laws of chemical equilibrium and kinetics can be applied to describe PCB 

movement and/or fate. 

3. Feedback of effects due to biota on PCB fate can be neglected. 

4. Interactions among the various PCB homolog groups can be neglected, in the context 

of modeling PCB fate and transport. 

5. Each PCB homolog series can be considered as a single phase in each compartment. 

As Trapp and Matthies (1996) indicate, these assumptions are not trivial. For example, 

“sediment” is actually a mixture of minerals, organic components, water, and biota. The 

simplifying assumption of using a single compartment for sediment in the model represents a 

general level of resolution. A finer level of resolution could be achieved by adding more 

compartments within the sediment bed. However the development of PRAM followed the 

cautions of: 

• Trapp and Matthies (1996) that “The model should only include the considerably 

important processes. It should also require a minimum of data and be comparable 

with environmental results;” and, 

• Mackay et al. (1995) that “To select the appropriate model complexity, it is important 

to remember not to make the model more complex than the data set available.... 

Models should not be too complex, because it is then hard to obtain the data needed 

for calibration and validation.” 

Thus, developing the PRAM required: 

• an appropriate balance, or level of resolution, considering the complexity of the realworld environment it attempted to characterize; 

• the level of resolution in data that was available and/or obtainable; 

• the level of resolution needed in the PRAM outputs. 

The goal was to provide decision makers with additional information about the potential 

exposure conditions and human health risks associated with leaving regulated PCBs on the 

ex-ORISKANY so they can determine whether the ex-ORISKANY artificial reef would 

present an unacceptable risk to human health or the environment. 
SECTIONTWO Model Assumptions 

SSC-SD/NEHC/URS 3 

To keep the model minimally complex and more likely to overestimate than underestimate 

risk, the PRAM was designed as a steady-state model. Steady-state in environmental 

modeling refers to the state where fluxes among compartments and across boundaries (i.e., 

between sources and sinks) are balanced, i.e., the concentrations of PCBs in various 

compartments remain the same as inflows to compartments balance outflows. The 

assumption of steady-state has a number of mathematical advantages in the context of risk 

assessments. These include, but are not limited to: 

• Within the mathematical algorithms, under an assumption of thermodynamic 

steady-state, the time-dependent differential terms for the algorithms can be 

set to zero, resulting in computationally easy solutions. 

• A thermodynamic steady-state allows for the incorporation of empiric 

methods/results to define the highly complex interactions that result in 

environmental partitioning among various phases within the environment 

(e.g., it allows the use of empirically-derived partitioning coefficients such as 

Koc, Kdoc, Kow, etc.). 

• A thermodynamic steady-state represents the long-term overall condition of 

the system. This condition fits well with evaluations of chronic exposure 

regimes for potential receptors of concern (e.g., humans and long-lived 

ecologically relevant predators). 

2.2 PHYSICAL AND CHEMICAL PROCESSES OF PCBS 

Modeling the fate and transport of PCBs requires an understanding of those processes that 

functionally control or determine fate and transport (Mackay et al. 1995). PRAM considers 

four physical processes/mechanisms: release, transport, partitioning, and transformation. 

2.2.1 PCB Release from Shipboard Materials: Normalized Release Rates 

This subsection describes the rationale for using a two-year constant release rate in PRAM. 
SECTIONTWO Model Assumptions 

SSC-SD/NEHC/URS 4 

Release in environmental modeling represents the input of PCBs into the environment from 

bulk product materials within the vessel that contain PCBs. PRAM handles PCB release 

with an empiric method7 (Trapp and Matthies, 1996). 

The Navy developed a release rate for each PCB homolog leaching from each shipboard 

PCB containing material by: 

• Measuring release rate for various homologs from each material in a laboratory; 

• Comparing the time scales of these experiments to human exposure durations; 

• Demonstrating a statistical relationship between release rates and time; 

• Normalizing the release rates to PCB mass in each shipboard material; 

• Selecting a steady state constant rate based on the comparison between the two-year 

release and predicted release rates over 30 years. 

Laboratory Measurement of PCB Homolog Release Rates 

SSC-SD (2004) provides the results of a laboratory investigation of the release of PCBs from 

a variety of PCB-containing bulk product materials from decommissioned US Navy vessels. 

PRAM does not model the mechanisms that control PCB release from these shipboard 

materials because these processes are very complex. It uses the PCB releases rates for 

specific shipboard materials. A companion volume (SSC-SD, 2004) provides the PCB 

homolog release rates, with units of nanogram of PCB homolog per gram of PCB-containing 

material per day (ngPCB⋅gmaterial

-1⋅d-1). 

The experiments used nine PCB-containing bulk product materials, seven of which were 

collected from ex-US Navy vessels: felt gaskets (2 types – inner and outer gasket material), 

rubber pipe hanger/liner material, bulkhead insulation, electrical cable, foam rubber material, 

aluminized paint, and standard samples of Aroclor© 1254, and Aroclor© 1268. Based on the 

leachate rate of PCBs from a known quantity of each material, the distribution of each 

homolog8

 series was determined and the release rates were adjusted to reflect release of the 

homolog series, as a total, on a per gram material per day basis (e.g., ngPCB⋅gmaterial

-1⋅d-1). 

Additionally, a subset of PCB congener masses per unit mass material per day was calculated 

(SSC-SD 2004). Initially PCB leached from the shipboard materials on the order of days, 

 

7

 The empiric method is generally applied for those systems and processes that are too complex or too little 

understood for a physicochemical mathematical description (modified definition from Trap and Matthies 

1996, Mackay et al., 1995). 8

 As PCBs represent a mixture of 209 congeners that exhibit differences in environmental fate and effects, 

subsequent analysis utilized the grouping of the congeners by homolog series (the number of chlorines within 

the conger defines the homolog series or grouping, e.g., see Eisler and Belisle, 1996). 
SECTIONTWO Model Assumptions 

SSC-SD/NEHC/URS 5 

with an increase in rate followed by a decrease in rate over a longer period of time (Figure 

5). 

Experimental Time Scales and Exposure Durations 

The leachate experiments show a decrease in release over the experimental period of 

approximately 18 months, which is about 5% of the 30-year chronic exposure period used in 

the human health risk assessment (NHEC (SHHRA), 2004). 

Demonstrate a Statistical Relationship Between Release Rate and Time 

Integration of the release rates over a 30-year period is not possible using the existing data. 

To further characterize these data, they were statistically evaluated for the potential 

development of a functional relationship between homolog-specific release rate and time 

using regression analysis (Appendix A). This analysis was for only those data that represent 

detections9

 and was based on the natural log transformed PCB release rate in nanograms of 

PCB (by homolog) per gram of total PCB (sum total of all homologs) within the material per 

day (Appendix A). The reported rates from SSC-SD (2004) within the PRAM were 

normalized, by material, to the observed concentration of PCBs within the material used in 

the experimentation, before the statistical analysis. 

PCB Normalized Release Rate 

The rationale for the adjustment of units is to account for the potential variation in PCB 

concentrations within materials collected from a ship being evaluated for disposal and those 

used in the laboratory measurements. This adjustment assumes that the relationship between 

release rate and PCB concentration is linear. For example, suppose that one vessel has 1,000 

kilograms (kg) of an onboard material containing 100 milligrams (mg) of PCB per kg and the 

laboratory-observed release rate for this material is 1 nanogram (ng) PCB per gram (g) PCB 

per day. The total release (flux) from the material would be 100 ng PCB per day ([100 mg 

PCB/kg material * 1,000 kg material]/1,000 mg PCB/g PCB * 1 ng PCB/g PCB-day). 

Suppose another vessel, with the same 1,000 kg of onboard material contains a concentration 

of 50 mg PCB per kg. The total release or flux would be 50 ng PCB per day based on the 1 

ng PCB per g PCB per day rate. Thus, by using the normalized release rates, variable 

material concentrations can be addressed. 

The release rate regression format would be as follows, assuming exponential decay: 

 

9

 As the objective of the statistical evaluation was to establish a functional relationship, it was believed 

appropriate to rely solely on detected and quantified values and not use surrogate values for non-detect 

samples that may skew or bias the statistical analysis. 
SECTIONTWO Model Assumptions 

SSC-SD/NEHC/URS 6 

(1) a b ( ) timee

gPCB

ngPCB release + ⋅ln ⎥ =

⎦

⎤ ⎢

⎣

⎡

where: 

release = PCB homolog series mass release per unit time 

a = the intercept of the regression 

b = the exponential slope of the regression 

ln(time) = natural log of time 

The decrease in release, based on those SSC-SD experimental data sets that could be 

regressed, is highly significant over a 30-year period. For example, the release rate of 

pentachlorobiphenyl from bulkhead insulation material peaks at 73 days after immersion into 

seawater. However, at 1 year the PCB release rate is predicted (based on the regression 

analysis) to be 37% of the peak rate; at 5 years to be 14% of the peak rate; and at 15 years 

and 30 years to be 7% and 4%, respectively, of the peak rate. 

Not all of the leachate rate data sets (homolog series and material) revealed a statistically 

significant regression; some data sets contained only one or two detections for the homolog 

series while others contained only non-detects for the PCB homolog series. 

Selecting a Steady State Constant Release Rate 

Incorporating decay in the PCB release rate from the vessel is problematic because PRAM is 

designed as a steady-state model. Modification to a non-steady state scheme to account for 

these release patterns was also considered problematic because: 

• The existing data are insufficient to establish decay curves for all of the 

homolog series within the various PCB-containing shipboard materials. 

• The approach would complicate the model; that is, other empiric approaches, 

for example, partitioning of the released PCBs into sediment, would no longer 

be appropriate. 

• The resultant exposure levels would need to be integrated over time to 

calculate a reasonable maximum exposure level for human health risk 

calculations. 
SECTIONTWO Model Assumptions 

SSC-SD/NEHC/URS 7 

Therefore, PRAM uses a constant release rate that probably overestimates release over a 30-

year exposure period. The model assumes that the colonization of an artificial reef will take 

two years. Additionally, the maximum bioaccumulation of PCBs, via the food web, into top 

sports fish taken for human consumption from the reef can require as much or more than two 

years time for the heavier homolog groups. Therefore, PRAM uses a two-year release rate 

for modeling a steady-state condition. This rate is higher than the predicted release rate over 

the 30-year exposure period assumed for risk characterization. For example, the predicted 

two-year release rate for pentachlorobiphenyl from bulkhead insulation material is 5 times 

the predicted 30-year release rate. Therefore, the two-year release rate probably 

overestimates PCB release during a 30-year period. 

When there were only one or two detections within the release rate data set (as obtained from 

SSC-SD 2004) or where the statistical analysis failed to produce a significant regression, the 

maximum reported rate was used in the PRAM. This approach decreases the probability of 

underestimating the exposure levels to humans and relevant ecological receptors of concern. 

Table 1 shows the material-specific PCB homolog release rates incorporated into the PRAM. 

2.2.2 Physical Transport Mechanisms 

Diffusion, dispersion, and advection are the three physical forcing functions10 within the 

PRAM. These three mechanisms drive the transport of PCBs within the modeled 

environment and are applied to the released PCBs within and outside the sunken vessel. 

2.2.2.1 Diffusion 

The molecules of a solute are in a state of continuous motion due to their kinetic energy. 

This motion, also called the Brownian motion, moves mass from regions of higher 

concentration (more molecules) to regions of lower concentration (less molecules). This 

gradual mixing or transport that occurs even in the absence of the bulk movement 

(advection) of fluid is called molecular diffusion. PCB molecules will show a net flux from 

places of higher concentrations to lower concentrations via molecular diffusion (e.g., see 

Trapp and Matthies, 1996). In one direction, diffusional flux is dependant on the area the 

flux is occurring across, the thickness of the layer it is occurring across, and the 

 

10 Forcing functions are variables of an external nature that affect the state of the system (abbreviated definition 

from Mackay et al., 1995). 
SECTIONTWO Model Assumptions 

SSC-SD/NEHC/URS 8 

concentration gradient (e.g., Trapp and Matthies, 1996; USEPA, 1982). The driving force 

for diffusion is the concentration gradient. 

Diffusion is mathematically described by Fick’s First Law, which assumes, (1) the medium 

within which it occurs and the direction in which it occurs remain constant, (2) the flux is 

perpendicular to the cross-sectional area of the boundary, and (3) the concentration gradient 

is constant (e.g., Trapp and Matthies, 1996; USEPA, 1982). Mathematically, molecular 

diffusion in one direction can be described as follows: 

(2) [ ] [ ] ⎟

⎟

⎟

⎟

⎟

⎠

⎞

⎜

⎜

⎜

⎜

⎜

⎝

⎛

⎟

⎟

⎠

⎞ ⎜

⎜

⎝

⎛

⎥

⎦

⎤ ⎢

⎣

⎡ −⎥

⎦

⎤ ⎢

⎣

⎡ ×

∆

⎥

⎦

⎤ ⎢

⎣

⎡

= ×

⎥

⎦

⎤ ⎢

⎣

⎡ 2 3 1 3

2

2

m

mol C

m

mol C

m

d

m D

N A m

d

mol diff

where: 

N = net substance flux due to diffusion (mol⋅d-1) 

A = the surface area 

D = the diffusion coefficient 

C2 – C1 = the concentration gradient 

∆ = the “thickness” of the diffusion gradient 

In reality, diffusion occurs in three directions simultaneously. Diffusion in the context of 

PCB transport within the environment is very slow compared to dispersion and advection. 

According to Lyman (1995), if advective water flow (i.e., current) is greater than 2 x 10-3 cm⋅

s

-1 (4 x 10-5 knots), molecular diffusion can probably be ignored. 

The importance of molecular diffusion within PRAM concerns “resistance” across media 

boundaries such as a pycnocline, surface water, and air interface, or the sediment bed – 

surface water interface (e.g., see Mackay et al., 1985; Mackay and Paterson, 1991; Trapp and 

Matthies, 1996). For this one-dimensional flux scenario Equation 2 (above) is appropriate. 

The quotient between the diffusion coefficient and diffusion length is termed “conductance” 

(m⋅d-1), a measure of the exchange velocity and termed the “transport parameter” for 

exchange of PCBs across a boundary. The inverse of conductance is resistance, which can 

impede the partitioning of PCBs to sediments, for example, within a steady-state modeling 

scheme such as that used for the PRAM. This potential impedance is why diffusion is 

considered a relevant and important forcing function within the PRAM. 
SECTIONTWO Model Assumptions 

SSC-SD/NEHC/URS 9 

The area, concentration gradient, and thickness of the boundary are model variables within 

the PRAM whereas the diffusion coefficient is a chemical parameter. Mackay and Paterson 

(1991) present a single diffusion coefficient for hexa-CBs in water (4 x 10-4

 m

2

⋅hr-1), which 

was not considered appropriate as the PRAM attempts to model all ten PCB homolog series 

that differ among themselves regarding physicochemical properties, such as diffusion 

coefficients. Diffusion coefficients are proportional to temperature and inversely proportional 

to molar volume, which is related to the square root of the chemical molar mass (e.g., see 

USEPA, 1982; Trapp and Matthies, 1996), such that: 

(3) 

i

j

j

i

M

M

D

D =

where: 

Di / Dj = the ratio between the diffusion coefficients for chemicals i and j

Mi and Mj = molar mass (g⋅mol-1) for chemicals i and j, respectively 

This relationship leads to an estimation method that is functional for PCB homolog series. 

Using oxygen as a reference chemical, the diffusion coefficient in water, based on the mean 

molecular mass for each series, is estimated as follows (Baumgarten et al., 1996, USEPA, 

1982): 

(4) 

PCB series

PCB series M

D

−

− − = × × 32 1.728 10 4

and for air (using steam as the reference chemical) is estimated as follows: 

(5) 

PCB series

PCB series M

D

− − = × 18 2.22

2.2.2.2 Dispersion 

Molecular diffusion, in this context, occurs in perfectly quiescent media (water, air, 

sediment), which is rare in the environment. Turbulence occurs in open surface waters due 

to currents, in sediment beds via bioturbation by sediment-associated organisms and sheer 

stress from overlying water currents. Turbulent diffusion is the dominant forcing function in 

actual situations. Random turbulence (random physical movement in one or all directions) in 
SECTIONTWO Model Assumptions 

SSC-SD/NEHC/URS 10 

the environment increases the apparent diffusion across physical boundaries such as those in 

the PRAM. Molecular diffusion, when supplemented by turbulence, is termed dispersion11

(see Trapp and Matthies, 1996; USEPA, 1982). In effect, the additional physical movement 

to that of molecular diffusion leads into a greater velocity for the equilibration of chemical 

concentrations in space (i.e., increases the exchange velocity and thus impacts the transport 

parameter for exchange of PCBs across a physical boundary). 

The physical movement component of dispersion differs from molecular diffusion; it almost 

always acts as a directional component associated with boundaries – for example, the water 

flow direction over a sediment bed where the turbulence is a consequence of the water 

current direction. Again, what is relevant for the PRAM is the exchange velocity of PCBs 

across the model boundaries where the velocities of media parallel to these boundaries 

(water-air, pycnocline, surface water-sediment bed) are much higher than the perpendicular 

exchange velocities across the boundary. In one dimension, dispersion can be described by 

the same equation (Equation 6) as that for molecular diffusion where: 

(6) [ ] [ ] ⎟

⎟

⎟

⎟

⎟

⎠

⎞

⎜

⎜

⎜

⎜

⎜

⎝

⎛

⎟

⎟

⎠

⎞ ⎜

⎜

⎝

⎛

⎥

⎦

⎤ ⎢

⎣

⎡ −⎥

⎦

⎤ ⎢

⎣

⎡ ×

∆

⎥

⎦

⎤ ⎢

⎣

⎡

= × 2 3 1 3

2

2

m

mol C

m

mol C

m

d

m D

Ndisp A m

where: 

Ndisp = net substance flux due to dispersion (mol⋅d-1) 

A = the surface area 

D = the dispersion coefficient 

C2 – C1 = the concentration gradient 

∆ = the “thickness” of the boundary or diffusion gradient 

However, D in Equation 6 is a dispersion coefficient, which is the sum of the diffusion 

coefficient as described in the previous Diffusion subsection (Section 2.2.2.1), and dispersion 

(m2

⋅d-1) due to turbulence, which within the PRAM is a function of environmental setting 

and derived from empiric estimation techniques. 

 

11 In meteorology the term “eddy diffusion” is used. 
SECTIONTWO Model Assumptions 

SSC-SD/NEHC/URS 11 

2.2.2.3 Advection 

By flowing movement of media such as water and/or air, PCBs contained within the media 

will be co-transported. This process is generally called advection (see Trapp and Matthies, 

1996; Mackay et al., 1995; USEPA, 1982). Because volume and mass are conserved within 

each compartment of the PRAM, inputs of media (e.g., water) into a compartment must be 

balanced with output from the compartment either into another compartment or out of the 

model boundaries. The major advective flows within the PRAM include water current and 

air current. These currents are considered as overall averages since the PRAM is designed as 

a chronic exposure, steady-state model. Similarly, as long-term averages, these currents are 

considered to be unidirectional. Current within the sunken vessel is estimated based on the 

prevailing current within the surrounding water column, as a fraction of that current (e.g., 

1%). Sunken vessels are known to “breathe” where water flows in and out of the open 

conduits. However, the PRAM assumes that, on average, there is a net advective flux of the 

PCBs from the interior of the vessel that is a consequence of the prevailing current exterior to 

the vessel. 

The advection processes explicitly included in the PRAM are: 

• Water currents that carry dissolved PCBs as well as PCBs absorbed onto 

suspended solids and PCBs bound to dissolved organic carbon within the 

water column. 

• Air currents (wind) that carry PCBs that have volatilized into the air column 

above the surface of the water. 

• Wet and dry PCB deposits from the air column. 

The advection processes for particulate deposition from the water column onto the sediment 

bed and resuspension from the sediment into the water column are implicitly included in the 

PRAM (i.e., processes included within the model algorithms), but assumed to be balanced 

(where input and output of PCBs is equal or net flux equals zero). This assumption results in 

no burial or sequestration of PCBs within the sediment bed, which probably overestimates 

exposure. 
SECTIONTWO Model Assumptions 

SSC-SD/NEHC/URS 12 

2.2.3 Partitioning Coefficients 

Within each of the PRAM compartments are phases, which refer to the ability of the material 

to mix with another (e.g., since water and oil do not mix completely, each is considered a 

“phase”). At a thermodynamic steady-state, PCBs will exhibit predictable relative 

concentrations between phases or media. Given an adequate amount of time, the relative 

concentrations in water and organic carbon, for example, will reveal a constant ratio, 

regardless of the relative concentrations of PCBs in that water and organic carbon. The 

physicochemical processes associated with the phenomena are highly complex. As discussed 

above, the complexity of these partitioning processes is part of the rationale for the use of a 

steady-state model. These values have been measured and derived by numerous authors 

using various methods within the scientific literature. These partitioning coefficients have 

many sources, so a process was developed to select or derive the coefficients that are 

incorporated into the PRAM. Three partitioning coefficients are used within the PRAM, the 

octanol-to- water partitioning coefficient (Kow), the water-to-particulate organic carbon 

partitioning coefficient (Koc), and the water-to-dissolved organic carbon partitioning 

coefficient (Kdoc). The following scheme was used to select or derive the coefficients that are 

incorporated into the PRAM: 

• Measured values as reported in reputable (peer-reviewed) documents from 

regulatory agencies (i.e., USEPA, US Fish and Wildlife, Agency for Toxic 

Substances and Disease Registry [ATSDR], and scientific journals) were 

preferred, 

• Empirically validated estimation methods obtained from reputable (peerreviewed) documents from regulatory agencies were used when no measured 

values were obtained, 

• Quantitative structure activity relationship (QSAR) estimation methods as 

described by reputable and/or regulatory agencies were used when no 

measured values or empirically validated estimation methods were obtained. 

This approach is consistent with the approach used in USEPA’s Draft Dioxin Reassessment 

Documents (USEPA, 2003). This reassessment included evaluation of dioxin-like 

compounds, which included PCB congeners. USEPA developed a ranking system to 

evaluate the degree of confidence in reported values of physical parameters (including 

partitioning coefficients) used in the reassessment. A property value with a ranking of one is 
SECTIONTWO Model Assumptions 

SSC-SD/NEHC/URS 13 

considered to have the highest level of confidence. These ranks continue down to a ranking 

of five, which is the lowest level of confidence. The ranking scheme is based on the premise 

that measured values are more definitive than estimated values. USEPA specifically 

indicates that ranking five includes values derived by QSAR methods. 

The octanol-to-water partitioning coefficients (Kow) used within the PRAM are derived from 

the congener values presented within Eisler and Belisle (1996). Eisler and Belisle (1996) 

present the most complete set for PCBs based on a comprehensive review of data in the peerreviewed scientific literature. The congener values were subjected to statistical analysis to 

derive a mean value to represent each homolog group (Appendix B). Too few data are 

available for formal statistical analysis of the Kow values for mono-CBs (3 values), nona-CBs 

(3 values), and deca-CB (single value). For both the mono-CB and nona-CB series, a simple 

average of the values presented by Eisler and Belisle (1996) was used. Deca-CB is 

represented by the value reported by Eisler and Belisle (1996). Table 2 shows the derived 

homolog-specific Kows used in the PRAM. 

The Koc values used in the PRAM were derived in two ways. For the mono-CB through 

hexa-CB homolog series, Koc measurements existed in the literature for congeners in these 

homolog series from which to calculate a Koc value to use in the PRAM. For the PRAM, we 

select the Koc values from Chou and Griffin (1986)12 to calculate the representative Koc

values for each of these homolog groups. The Koc values used for these homolog groups 

correspond to the geometric mean of the Koc values measured for the individual congeners 

within a homologous series. Insufficient measurements of Koc were found in the literature to 

allow determination of representative values for Koc for the hepta- octa-CB, nona-CB and 

deca-CB homologous series. Therefore, a QSAR approach was taken to estimating these 

values. Equation 7 from Lyman (1995) estimates Koc . 

(7) log 0.779 log 0.46 10 10 = × + Koc Kow

The values for Kow used in this calculation of Koc for the hepta-, octa-, nona-, and deca-CBs 

are the geometric means of the Kow values for all congeners within a given homologous 

series reported by Eisler and Belisle (1996) and are included on Table 2. 

Partitioning of PCBs to dissolved organic carbon (Kdoc) in water was related to the Kow of the 

chemical by USEPA (2002). USEPA reported a ratio between Kdoc and Kow of 0.074, which 
SECTIONTWO Model Assumptions 

SSC-SD/NEHC/URS 14 

is used to derive the Kdoc for use in the PRAM. These derived Kdoc values are presented in 

Table 2. 

Note: Kow listed for PCB-126 in Appendix B (6.897) is slightly higher than Kow used in 

PRAM for pentachlorobiphenyls (6.4951). We mention this because the ERA analysis of 

dioxin-like congeners assumes that PCB-126 behaves like its homolog group (i.e. 

pentachlorobiphenyls). 

2.2.4 Transformation 

PCBs, as xenobiotics, may be subject to certain enzymatically-mediated biotransformation 

processes to form metabolites, which may be different in physicochemical properties from 

the parent compounds (Kleinow and Goodrich, 1993). 

Transformations of PCBs depend on the degree of chlorination; the more chlorinated forms 

are much more resistant to transformations than the lesser-chlorinated forms (Safe, 1990)13. 

Photolysis can occur for some forms in air and/or water, e.g., sunlight may react directly with 

many organic contaminants and dissolved organic carbon to produce photoreactant 

intermediates (Cooper, 1989). For PCBs, the importance of this transformation 

(dechlorination) is not suggested to be overly important in the context of PCB fate and 

transport mechanisms (ATSDR, 2000). Similarly hydrolysis and oxidation appear to be 

insignificant processes for PCB fate and transport (ATSDR, 2000). 

PCB transformations mediated though biological processes (bio-degradation) are cited as the 

most important processes for PCB fate and transport in the environment (ATSDR, 2000). 

Table 3 presents a sampling of the reported biodegradation rates from the peer-reviewed 

scientific literature. Biodegradation rates for PCBs are highly variable among the congeners 

due to the degree of chlorination and structural characteristics of the PCB molecule. 

Variable biodegradation rates for the same congener are also expressed in the scientific 

literature, which has been linked to microbial pre-exposure to PCBs or other PCB-like 

compounds, bioavailability, microbial exposure concentrations, temperature, available 

nutrients, and the presence of inhibitory compounds (ATSDR, 2000). 

 12 These data are reproduced in Appendix B. 

13 Safe (1990) showed that 2,4,5,2’,4’,5’-hexachlorinated biphenyl is recalcitrant to metabolism and very 

persistent in the environment. While with only 2 chlorines less than this compound, 3,4,3’4’-tetrachlorinated 

biphenyl is metabolized and less persistent in the environment. The net effect is that with time, both in the 

environment and in organisms, the predominant PCB congeners available for and contributed to 

bioaccumulation are those which resist degradation/transformation. 
SECTIONTWO Model Assumptions 

SSC-SD/NEHC/URS 15 

While biodegradation may be an important process for PCB fate and transport in the 

environment, this importance is limited to lesser-chlorinated forms and difficult to predict for 

any specific environmental setting such as that of an artificial reef. Therefore, within the 

PRAM, biodegradation is recognized and the model provides for rate inputs for each 

homolog series. The default condition of no biodegradation (or other transformation) is 

assumed to assure that the final exposure levels within the environment are not underestimated. 

2.3 ABIOTIC MODEL SELECTION OF PCB FATE AND TRANSPORT 

This subsection describes the fugacity approach, the four levels of fugacity modeling, and the 

reasons for using fugacity level III in PRAM. 

The Navy selected fugacity modeling for PRAM because it offers a steady state solution, is 

widely accepted in multimedia applications (Cowan et al., 1995), and there is regulatory 

precedent for its application. Level III Fugacity models are used by: 

• California Environmental Protection Agency (Cal/EPA) to assist in assessing 

contaminated sites within the state (CalTOX, UC-Davis [UCD] and Lawrence 

Livermore National Laboratory [LLNL], 1994; McKone et al., 1997); 

• USEPA in developing the ambient water criteria for the Great Lakes Water Quality 

Initiative (USEPA, 1995; Gobas, 1993); 

• Health Canada to assist in evaluating regional pollutant issues within Canada; 

• European Union Member States (European Centre for Ecotoxicology and Toxicology 

of Chemicals [ECETOC], 1994) for examining and evaluating pollutant risks. 

What follows is a general description of the various fugacity modeling “levels” and the 

specific structure of the PRAM fugacity module that is based on the Level III fugacity 

construct.14

2.3.1 The Fugacity Multimedia Approach 

Fugacity (f) is the “escaping tendency” of a chemical from a particular phase (Mackay and 

Paterson, 1981) with units of pressure (Pascals [Pa]). This fugacity can be related to the 

 

14 Version 1.3 of the PRAM used a level II fugacity modeling approach, while Version 1.4c of PRAM uses a 

level III fugacity modeling approach. 
SECTIONTWO Model Assumptions 

SSC-SD/NEHC/URS 16 

phase (e.g. environmental media) physically as the partial pressure or “escaping” potential 

exerted by a chemical in one compartment (physical phase such as water, sediment, air) on 

another. When a chemical is at equilibrium between two phases, the escaping tendency or 

“fugacity,” of the chemical is the same for the two phases. 

There are four levels of fugacity modeling: 

• Level I – a closed system at equilibrium (common fugacity) and at 

thermodynamic steady-state, with no chemical reactions. 

• Level II – an open system at equilibrium (common fugacity), and at 

thermodynamic steady-state, with chemical reactions. 

• Level III – an open system not at equilibrium (no common fugacity, except 

within compartments) while at thermodynamic steady-state, with chemical 

reactions. 

• Level IV – an open system not at equilibrium (no common fugacity, except 

within compartments) and not at thermodynamic steady-state, with chemical 

reactions. 

2.3.1.1 Level I Fugacity Model 

This subsection discusses Fugacity Level I because it illustrates the basic underpinnings of 

the fugacity concept and escaping tendency. However, it is not adequate for modeling PCBs 

being released from a sunken vessel because: (1) the sunken vessel is an open system, (2) no 

common fugacity occurs within the system except within compartments, and (3) chemical 

reactions may occur within the compartment (such as dechlorination/degradation). 

Level I fugacity model is akin to a closed jar containing chemical and media (e.g., water, 

sediment, air). No inputs or outputs occur within the system aside from the starting 

conditions. A Level I fugacity model predicts the distribution of the chemical within these 

media at equilibrium, under steady-state conditions. This model, when used for a system that 

has only two media or phases (such as organic carbon and water), will result in a partition 

coefficient that is equal to the Koc as described previously, albeit derived differently. Using 

the fugacity concept and a common fugacity (f), which assumes equilibrium, this situation 

can be expressed mathematically as: 
SECTIONTWO Model Assumptions 

SSC-SD/NEHC/URS 17 

ij

j

i

j

i

j

i K

Z

Z

fZ

fZ

C

C = = =

Where C is the concentration of the chemical (mol⋅m-3) in phase i or j, f is the common 

fugacity (Pa), Z is the fugacity “capacity” of phase i or j, with units of (mols ⋅m-3⋅ Pa-1), and 

Kij equals the partitioning coefficient for the chemical and the respective phases of i and j. 

(see also Equation 17). Using fugacity capacities, the partitioning of multiple phases within 

the system is highly simplified. Consider, for example (per Mackay and Paterson, 1981), a 

10-phase system in which potentially 90 partitioning coefficients may be defined 

independently (e.g., Koc). As the ratios of the fugacity capacities are equivalent to the 

partition coefficients, the solution can be obtained with far greater ease. The dissection of 

equilibrium constants into individual fugacity capacities is a convenient method that 

facilitates calculation of a chemical’s quantities via partitioning within variable multi-media 

systems regardless of whether it is a closed or open system. 

The fugacity capacity for vapors, as discussed by Mackay and Paterson (1981), assuming 

standard atmospheric pressure, can be related back to the partial pressure and the ideal gas 

law. Thus, Z for air is represented as: 

(8) ( ) R T Zair × = 1

where: 

R = Universal Gas Constant (8.31 Joules⋅mol-1⋅°K-1) 

T = temperature (°K) 

Particulate matter within the air column are considered to be aerosols (per Mackay and 

Paterson, 1991) with a fugacity capacity of: 

(9) ( ) VP R T Zaerosols × × = × 6 6 10

where: 

VP = liquid vapor pressure (Pa) 

R = Universal Gas Constant (8.31 Joules⋅mol-1⋅°K-1) 

T = temperature (°K) 
SECTIONTWO Model Assumptions 

SSC-SD/NEHC/URS 18 

6 x 106 = a constant as derived by Mackay and Paterson (1991) (Pa) 

In PRAM, vapor pressures for individual PCB congeners were obtained from Fiedler, 2001; 

Oberg, 2001; and the ATSDR Toxicological Profile for PCBs, 2000. Where possible (i.e., 

sufficient number of values) statistical analysis was performed to derive a homolog-specific 

vapor pressure (Appendix C). The homolog vapor pressures used in the PRAM are presented 

in Table 2. 

The fugacity capacity for water (as a pure phase), assuming a non-ionizable molecule (like 

PCBs), and invoking “infinite dilution” (see Mackay and Paterson, 1981), reduces to the 

reciprocal of the chemical’s Henry’s Law Constant (Pa ⋅ m3

⋅mol-1). 

(10) H Zwater = 1

Freshwater solubility is necessary to estimate the Henry’s Law Constant per Mackay and 

Paterson (1981, 1991). Solubility of PCBs in freshwater were obtained from Chou and 

Griffin (1986). When solubility data were unavailable, the following estimation method 

presented by Lyman (1995) was used: 

(11) log = −1.16× log + 0.79 ⎥

⎦

⎤ ⎢

⎣

⎡ Kow L

mol S

This equation was used to estimate the water solubility of octa-CB, nona-CB, and deca-CB. 

The solubility values used within the PRAM are presented in Table 2. 

The vapor pressures and solubilities for the respective PCB homolog series were used to 

estimate the Henry’s Law Constant (H) per equation 21 within Lyman (1995): 

(12) [ ]

⎥

⎦

⎤ ⎢

⎣

⎡ =⎥

⎦

⎤ ⎢

⎣

⎡ ⋅

3

3

m

mol S

VP Pa

mol

Pa m H

The Henry’s Law Constant values for each PCB homolog series as used within the PRAM 

are presented in Table 2. 
SECTIONTWO Model Assumptions 

SSC-SD/NEHC/URS 19 

As pointed out above, partitioning coefficients can be related to the ratio of chemical 

fugacity capacities (for sorbed phases such as sediment, total suspended solids), and 

dissolved organic carbon (Mackay and Paterson, 1981, 1991): 

(13) H

K f Z oc oc TSS TSS

TSS

× × ρ = − ( )

(14) H

f Z Koc oc-sediment sediment

sediment

( × ) × ρ =

(15) 

H

K

Z DOC DOC

DOC

× ρ =

where: 

TSS = total suspended solids 

DOC = dissolved organic carbon 

H = Henry’s Constant (Pa ⋅m3⋅mol-1) 

Koc = the organic carbon to water partitioning coefficient for PCBs (L⋅kg-1-oc) 

KDOC = the dissolved organic carbon to water partitioning coefficient for PCBs 

(L⋅kg-1-DOC) 

foc-TSS or sediment = the fraction of organic carbon within the suspended solids or 

sediment (unitness) 

ρmedia (TSS, sediment, or DOC) = bulk density of the media (g⋅cm-3) 

Using these fugacity capacities, partitioning within a system containing air, water, sediment, 

total suspended solids, and dissolved organic carbon can be predicted with a minimal amount 

of data requirements. This partitioning is relative in concentration such that volumes and 

mass are required to solve for absolute concentrations, which is derived from the total mass 

of chemical present and a common fugacity where: 

(16) ∑=

i i

T

Z V

M

f

Where f is the common fugacity (equilibrium), MT is the total mass (mols) introduced into 

the closed system, Zi is the fugacity capacity for system phase or compartment i, and Vi is the 
SECTIONTWO Model Assumptions 

SSC-SD/NEHC/URS 20 

volume of the phase in m3. The relationship between fugacity, fugacity capacity and 

chemical concentration, C [mols⋅m-3], is defined by: 

(17) C = Zf

2.3.1.2 Level II Fugacity Model 

This subsection discusses Fugacity Level II because PRAM version 1.3 used it. However, 

reviewers criticized this level for its lack of refinement and the possible underestimation of 

water concentration and overestimation of other phase concentrations (e.g., sediment, DOC, 

and air). 

Very few closed systems exist in the environment whereby there are no exchanges with the 

outside of the model construct (outside of the model boundaries). Level II fugacity models, 

like Level I models, assume system equilibrium and steady conditions. However, they are 

used to represent “open” systems where inputs to and outputs from the system compartments 

are included. This type of system has a chemical input into the system (e.g., emission or 

release), which is balanced by the system media trapping the chemical, reactive losses, and 

chemical output from the system. Thus, all of the inputs to and losses from the system are 

balanced (steady-state) as well as exchanges between the compartments (equilibrium). The 

Level II model is simplistic because it assumes a common fugacity (equilibrium) such that 

the exchanges between the compartments (e.g., water and sediment) are not subject to any 

transfer resistances. The advantage of this system is limited data requirements and a simple 

algebraic solution. The driving forces within such a system are limited to fate and transport 

between compartments, i.e., advection and chemical reactions in the sunken vessel 

environment. Advection in and out of the system compartments can be introduced into the 

Level II model as a first-order constant; as advective flow with units of m3

⋅d-1 divided by the 

phase volume, e.g., water (V in m3) with resultant units of d-1. Additionally, other rate 

constants for reactive processes such as dechlorination/degradation can be included. By 

assuming equilibrium among compartment (phases) and steady-state conditions where input, 

output, and transfers among phases are balanced, a common fugacity can be calculated based 

on emission (mol⋅d-1) into the system (Mackay and Paterson, 1981): 

(18) ∑

= Vi ZiKi

N f
SECTIONTWO Model Assumptions 

SSC-SD/NEHC/URS 21 

Where, as in the Level I fugacity model, f is the common fugacity, N is the mass emission 

(mols⋅d-1) introduced into the system, Z is the fugacity capacity for the system phase or 

compartment i, Vi is the volume of the phase in m3

, and Ki is the advection and any 

additional first-order reactive rate constant occurring within the respective phase or 

compartment. 

This equation can be rewritten to explicitly describe rates and transport using a D value to 

more explicitly represent transport mechanisms (Mackay and Paterson, 1991; Mackay et al., 

1995): 

(19) = ( ) ∑ ∑ DAi + DRi N f

Here ΣDA is the sum of all advective processes and ΣDR is the sum of all reaction processes. 

Although this model can be used to simulate the release of PCBs from a sunken vessel, 

without accounting for the potential resistances associated with media transfers from water, 

the water concentration may be under-estimated while other phase concentrations (e.g., 

sediment, DOC, and air) may be over-estimated. Because of this and USEPA review 

comments on PRAM Version 1.3, the Level II modeling approach was not considered to be 

sufficiently refined. Therefore, PRAM Version 1.4c was developed based on the Level III 

fugacity modeling approach (PRAM Version 1.3 used a Level II fugacity modeling 

approach, e.g., see Goodrich et al., 2003). 

2.3.1.3 Level III Fugacity Model 

PRAM version 1.4c uses a Level III fugacity model because: 

• Unlike the Level II model, the Level III model does not assume equilibrium (a 

common fugacity) between the phases or compartments within the system; 

• Transfer resistances control the exchange between the compartments within the 

system 

• The model considers advection, reactive processes, and diffusion/dispersive 

processes; 

• It is more refined for environmental modeling as true equilibrium among phases is 

considered rare within the real world and diffusive resistance can affect intermedia 

transfers at the respective boundaries. 
SECTIONTWO Model Assumptions 

SSC-SD/NEHC/URS 22 

Intermedia mass transfers can occur through advective processes and diffusive processes in 

Level III modeling. PCB transfers can be expressed as Dijf where the diffusivity Dij term 

includes those processes affecting diffusion, including resistance and f is the compartmental 

fugacity (see Mackay et al., 1985; Mackay and Paterson, 1991). The nomenclature for the D 

(transport) term within the Level III, as used here, is represented by DA and DR, which are 

advective and reactive transport terms, respectively, while Dij refers to total (advective and 

diffusive) transport terms between media (phases and/or compartments) within the system. 

By invoking system steady-state conditions, a mass balance using the fugacity approach can 

be illustrated for each system compartment where inputs are balanced by outputs. This 

approach results in no net gain or loss of the chemical within the system, despite varied 

exchanges or non-common fugacities or “escape tendencies” between compartments 

(common fugacities are assumed to occur within individual compartments). This approach is 

represented by the following equation for delineating the transport mechanism in terms of 

mass emission, N [mol⋅d-1], across the entire system (see Mackay, 1985; Mackay and 

Paterson, 1991): 

(20) − (∑ + + )+ ∑ ( ) = 0 j ji j i j ij Ai Ri N f D D D D f

where: 

i = compartment or phase i

fi = the fugacity of phase / compartment i

fj = the fugacity of phase / compartment j

Dji = the transport coefficient(s) from compartment j into compartment i

The foregoing equation is easily rearranged to solve for the compartmental fugacity (fi): 

(21) 

( )

∑ ( )

∑

+ +

+

=

j ij Ai Ri

j ji j

i D D D

N D f

f

Compartmental concentrations can then be calculated using the compartmental fugacity and 

Z value for the media just as previously described for the Level II model. Figure 6 shows the 

transport terms, which include diffusive transport, for the PRAM system coupled to the 

exchanges they represent. 
SECTIONTWO Model Assumptions 

SSC-SD/NEHC/URS 23 

2.3.1.4 Model IV Fugacity Model 

A Level IV fugacity model is a true dynamic model in that both space and time are modeled 

dynamically. The model system is not considered to be at equilibrium. Nor is it considered 

to be at steady-state. The exchanges are not assumed to balance because fluxes to and from 

compartments are not balanced. This is reflected in the fugacity equation where: 

(22) 

( ( )) ( )

= − (∑ ( + + ))+ ∑ ( ) ∂

∂

− ∑ + + + ∑ ≠

j j f ji j D Ri D Ai D ij D i

f t N

t

f

i Zi V

j j f ji j D Ri D Ai D ij D i N f

and assuch :

0

where t = time 

Solutions for the fugacity terms within Level IV cannot be made through simple algebra as 

for model Levels I, II, and III. The Level IV fugacity model requires significantly more data 

inputs than any of the preceding structures to describe fluxes within the system. While 

empiric equilibrium constants such as organic carbon partitioning coefficients (Kocs) are 

functional in lower levels of fugacity modeling, time specific rates of for such processes are 

required for this model (e.g., rate of absorption and desorption). The Level IV model is 

mathematically and data intensive but does not appear to significantly differ from Level III in 

the model’s ability to account for pollutant inventories (Hertwich, 2001). Further, in a direct 

comparison between a steady-state Level III and non-steady-state Level IV fugacity 

modeling approach, Hertwich (2001) concluded the important properties such as a dose, 

persistence and spatial distribution can be equally derived from the Level III as with the 

Level IV model. Based on such information, the additional data requirements, and the desire 

to, as stated by many (e.g., Trapp and Matthies, 1996; Mackay et al., 1995; and others) 

minimize model development complexity to assure confidence in data inputs and future 

validation, the Level IV model was not considered the most appropriate for the PRAM. 

2.3.2 PRAM Level III Fugacity Model and Algorithms 

In the PRAM Level III fugacity construct, PCB exchange occurs among five compartments 

(Figure 6): 
SECTIONTWO Model Assumptions 

SSC-SD/NEHC/URS 24 

• An air body bounded vertically by the atmosphere to water surface and 

laterally by a user input value15

• A water body above the pycnocline bounded by the water surface and laterally 

by a user input value 

• A water compartment within the vessel interior 

• A water compartment outside of the vessel bounded by a respective lateral 

user input value and vertically by the pycnocline,16

• A sediment bed bounded in depth and laterally by a user input value 

PRAM treats these five compartments as bulk compartments within which there are subcompartments of particles, water, and dissolved organic carbon, as appropriate (Section 2.1). 

These compartments are treated as bulk phases (e.g., see Mackay and Paterson, 1991), and as 

such, the fugacity capacity (Z value) of each phase is weighted by the fractional portion of 

the sub-compartments. For example, compartment 2 (upper water column) consists of water, 

suspended particles, and dissolved organic carbon. The fugacity capacity for the upper water 

column as a bulk phase is represented by the following equation: 

(23) 2 water suspended sediment dissolved organic carbon Z φZ + φZ + φZ = −

Where φ is the volume fraction of the specific media within compartment 2 (the upper water 

column) and the Z is the respective fugacity capacity for the media listed. 

A nomenclature using the compartment numbers can be used to simplify the description of 

this weighting process where the first subscript for the Z value represents the compartment 

and the second represents the media within that compartment17 (A = air, W = water, SS = 

suspended particles, AE = aerosols, SD = sediment, and DOC = dissolved organic carbon). 

 

15 This lateral input value defines the lateral “zone of influence or ZOI” for the artificial reef created by the 

sunken vessel. 16 Per the November 17/18, 2004 TWG meeting, EPA recommended pycnocline to be used as the vertical 

boundary. 17 Not all media listed are present in all compartments, e.g., no air is present in the sediment bed, etc. 
SECTIONTWO Model Assumptions 

SSC-SD/NEHC/URS 25 

Air Compartment 

(24) Z1 = φ1AZ A + φ1AE Z AE

Upper Water Column Compartment 

(25) Z2 = φ2W ZW +φ2SSZSS +φ2DOCZ DOC

Lower Water Column Compartment 

(26) Z3 = φ3W ZW +φ3SSZSS +φ3DOCZDOC

Sediment Bed Compartment 

(27) Z4 = φ4SDZSD +φ4W ZW +φ4DOCZDOC 

Sunken Vessel Interior Compartment 

(28) Z5 = φ5W ZW + φ5SSZSS + φ5DOC Z DOC

Transfers of PCBs can occur between these compartments and through these compartments 

to the outside of the system (Level III fugacity model is an open system). Additionally, the 

sub-compartments can also carry PCBs into adjacent compartments via advection. Table 4 

and Figure 6 show the mass transfers or exchanges of PCBs considered relevant for the 

PRAM. 

2.3.2.1 Non-Diffusive Transport Within the PRAM 

The compartmental exchanges/transfers or “intermedia transfer parameters” are defined as 

transfer coefficients or D terms as described above. Non-diffusive transports (advective and 

reactive [biodegradation]) are described below for the PRAM compartments: 

Compartment 1 – Air compartment 

Non-diffusive transport within this compartment is enabled by precipitation, specifically: 

 

Rain; 

(29) DQW = A12 ×UQ × ZW
SECTIONTWO Model Assumptions 

SSC-SD/NEHC/URS 26 

Wet particle deposition; 

(30) DDW = A12 ×UQ ×φ1AEZ AE

Dry particle deposition; 

(31) DPW = A12 ×U P ×φ1AE Z AE

Physical advection out of the compartment; 

(32) DA1 = GA × Z1

where: 

A12 = the surface area of the water – air interface (m2

) 

UQ = the rain rate (m3

 rain⋅m

-2⋅d-1) 

UP = dry deposition velocity (m⋅d-1) 

GA = air flow through the air compartment (m3

⋅d-1) 

 = [air current x cross-sectional area] 

φ = the volume fraction of the specific media within compartment 1 and Z values 

as previously defined 

Compartment 2 – Upper water column compartment

Physical advection out of the compartment; 

(33) DA2 = GW 2 ×Z2

Biodegradation; 

(34) DR2 = KW ×V2W ×φ 2wZW

where: 

GW2 = water flow through the upper water column compartment (m3

⋅d-1) 

 = [current x cross-sectional area] 

Kw = rate of biodegradation of PCB in water (d-1) 

V2W = the volume of pure water in compartment 2 (m3

) 

φ = the volume fraction of the specific media within compartment 2 and Z values 

as previously defined 

Compartment 3 – Lower water column compartment

Physical advection out of the compartment; 
SECTIONTWO Model Assumptions 

SSC-SD/NEHC/URS 27 

(35) DA3 = GW 3 × Z3

Biodegradation; 

(36) DR3 = KW ×V3W ×φ3wZW

where: 

GW3 = water flow through the lower water column compartment (m3

⋅d-1) 

 = [current x cross-sectional area] 

Kw = rate of biodegradation of PCB in water (d-1) 

V3W = the volume of pure water in compartment 3 (m3

) 

φ = the volume fraction of the specific media within compartment 3 and Z values as 

previously defined 

Compartment 4 – Sediment bed compartment

Particulate deposition; 

(37) DDX = A34 ×UDX ×φ3ssZSS

Particulate resuspension; 

(38) DRX = A34 ×URX ×φ 4SDZSD

Sediment burial; 

(39) DB = A4 ×UB ×φ4SDZSD

Biodegradation; 

(40) DR4 = KW ×V4W ×φ 4sd ZW

where: 

A34 = surface area for sediment bed – water column interface (m2

) 

UDX = suspended solid deposition velocity (m⋅d-1) 

URX = sediment re-suspension solid velocity (m⋅d-1) 

A4 = surface area for sediment bed (m2

) 

UB = sediment burial velocity (m⋅d-1) 

Kw = rate of biodegradation of PCB in water (d-1) 

V4W = the volume of pure water in sediment bed - compartment 4 (m3

) 

φ = the volume fraction of the specific media within compartment 4 and Z values as 

previously defined 
SECTIONTWO Model Assumptions 

SSC-SD/NEHC/URS 28 

Compartment 5 – Sunken vessel interior compartment

Physical advection out of the compartment; 

(41) DA5 = GW5 × Z5

Biodegradation; 

(42) DR5 = KW ×V5W ×φ5W ZW

where: 

GW5 = total flux from the interior vessel compartment (m3

⋅d-1) 

 = [current x cross-sectional area] 

Kw = rate of biodegradation of PCB in water (d-1) 

V5W = the volume of pure water in compartment 5 (m3) 

φ = the volume fraction of the specific media within compartment 5 and Z values as 

previously defined 

These non-diffusive transport coefficients are combined with the diffusive transport 

coefficients defined below to quantify total transport between compartments and ultimately 

the compartmental fugacities required to calculate each phase PCB concentration. 

2.3.2.2 Diffusive Transport Within the PRAM 

Three diffusive exchanges are considered within the PRAM: 

• PCB exchange between the upper water column (compartment 2) and air 

(compartment 1) across the water–air boundary layer, 

• PCB exchange between the lower water column (compartment 3) and the 

upper water column (compartment 2) across the pycnocline, and 

• PCB exchange between the lower water column (compartment 3) and the pore 

water within the sediment bed (compartment 4) across the sediment bed–

surface water boundary layer. 

These exchanges are bi-directional but the net flux of PCBs is based on the concentration 

gradient between the exchanging compartments. Exchange of PCBs between compartments 

involves both molecular diffusion and turbulent diffusion (dispersion). As described 

previously, the forcing process for diffusive flux across a boundary layer is the concentration 

gradient, which can be described as: 
SECTIONTWO Model Assumptions 

SSC-SD/NEHC/URS 29 

(6) [ ] [ ] ⎟

⎟

⎟

⎟

⎟

⎠

⎞

⎜

⎜

⎜

⎜

⎜

⎝

⎛

⎟

⎟

⎠

⎞ ⎜

⎜

⎝

⎛

⎥

⎦

⎤ ⎢

⎣

⎡ −⎥

⎦

⎤ ⎢

⎣

⎡ ×

∆

⎥

⎦

⎤ ⎢

⎣

⎡

= × 2 3 1 3

2

2

m

mol C

m

mol C

m

d

m D

Ndiff A m

where: 

N = net substance diffusive flux due to diffusion and turbulence (mol⋅d-1) 

A = the surface area 

D = the diffusion coefficient 

C2 – C1 = the concentration gradient 

∆ = the “thickness” of the boundary or diffusion gradient 

Salient for the modeling scheme here is a mass transfer coefficient (MTC), which is dissected 

from the above equation as D/∆ across a concentration gradient, and working at a level of 

flux per unit area where: 

(43) ( )( ) 2 C2 C1 U C2 C1

D

m d

mol N − = − ∆ =⎥

⎦

⎤ ⎢

⎣

⎡

⋅

where: 

 U = MTC = D/∆ 

2.3.2.3 Surface Water and Air Diffusive Boundary 

An illustration of the boundary condition between upper water column (compartment 2) and 

air (compartment 1) is presented below (adapted from UCD and LLNL, 1994): 
SECTIONTWO Model Assumptions 

SSC-SD/NEHC/URS 30 

 

The air concentration above the laminar layer (represented by the dotted line above the water 

surface) is assumed to be well-mixed and homogenous in concentration. Similarly, the water 

concentration below the laminar layer just below the water surface is represented by a single 

concentration. These two well-mixed compartmental concentrations are related to the 

fugacity capacities of the compartments where diffusive processes are considered such that: 

(44) ( ) f [] [] Pa f Pa

m Pa d

mol Y

m d

mol N aw ⎥ air − water ⎦

⎤ ⎢

⎣

⎡

⋅ ⋅ =⎥

⎦

⎤ ⎢

⎣

⎡

⋅ 2 2

where Yaw is the overall fugacity mass transfer coefficient per day 

Considering that diffusive flux will occur in two directions at a boundary layer using the air–

water boundary, the flux to the airside of the boundary from the water and from the air to 

waterside of the boundary must balance or: 

( )

w ( ) water water

a air air

N U C C

and

N U C C

− −

− −

= −

= −

2 1

2 1

(46) 

(45) 

where C1-air, C2-air, C1-water, and C2-water are concentrations near the boundary layer 

as shown above. 

C 2-

C1-

C2-

C 1-

fugacity -

fugacit -

∆-

AIR

WATER

∆-

increasing concentration increasing fugacity 
SECTIONTWO Model Assumptions 

SSC-SD/NEHC/URS 31 

Noting that at the surface the partitioning between water and air can be expressed in terms of 

their Z values: 

(47) 

W

A

water

air

Z

Z

C

C =

−

−

1

1

and also noting that C = fZ1 within each compartment, the foregoing equations can be 

manipulated to replace the concentration terms with Z values (see UCD and LLNL, 1994 for 

the specific algebraic manipulations): 

(48) 

1

1 1 −

⎟

⎟

⎠

⎞

⎜

⎜

⎝

⎛

×

+

× =

A a W w

aw Z U Z U

Y

This overall fugacity mass transfer coefficient is related to the airside and waterside mass 

transfer coefficients where: 

airside; 

(49) ⎟

⎟

⎠

⎞

⎜

⎜

⎝

⎛

∆ = =

a

a A a A a

aw

D

Y Z U Z

waterside; 

(50) ⎟

⎟

⎠

⎞

⎜

⎜

⎝

⎛

∆ = =

w

w W w W w

aw

D

Y Z U Z

The CalTOX model (UCD and LLNL, 1994) as well as the CemoS Model (Baumgarten et 

al., 1996) use an empiric method to estimate D/∆ based on the laboratory results of 

Southworth (1979). However, the data used by Southworth (1979) was specific to a large 

freshwater river (see Trapp and Harland, 1995). The approach suggested for open ocean is 

that of Liss and Slater (1974), which is specific to the air–ocean interface. Liss and Slater 

(1974) determined that the average transfer velocity (the combination of diffusion velocity 

and turbulence) for water across the seawater – air interface was 30 [m⋅hr-1]. 

Two other methods in addition to the Southworth and Liss and Slater methods were 

compared to field observations by Trapp and Harlan (1995), that of Mackay and Yeun (1983) 

which was developed for lake environments, and the method presented as the Langbein–

Durum method (Tapp and Harland, 1995) for a river backwater situation. For perspective, in 
SECTIONTWO Model Assumptions 

SSC-SD/NEHC/URS 32 

the seminal papers of Mackay (Mackay et al., 1985; Mackay and Paterson, 1991) a mass 

transport coefficient (U) of 3 m⋅hr-1 (72 m⋅d-1) for the airside U coefficient and 0.03 m⋅hr-1

(0.72 m⋅d-1) for the waterside U coefficient were used in modeling hexa-CB. According to 

Mackay and Paterson (1991), these values were selected based on best professional judgment 

without any further justification. 

Given that the PRAM is attempting to model all ten homolog series with significantly 

different diffusion coefficients (D), the use of a single U for all seems too simplistic while 

the development of ten values based on best professional judgment seems too much of a task. 

It seems appropriate that the methods that could account for the variable chemical 

diffusivities of the PCBs as well as potentially, wind speed and water current, be considered 

as part of the PRAM development. 

Trapp and Harland (1995) evaluated the aforementioned four estimation methods for a large 

river and a ship channel. Although neither situation is similar to the open ocean application 

anticipated for the PRAM, reference to the relative performances of the models is useful. 

The Liss and Slater method over-estimated the observed transport velocities for both 

situations (Trapp and Hartland, 1995). The Southworth and Langbein–Durum methods 

significantly under-estimated the velocities for the ship channel scenario but were accurate 

predictors of the river scenario. The Mackay and Yeun method significantly under-estimated 

the transport velocity for the river scenario and significantly over-estimated the velocity for 

the ship channel (Trapp and Hartland, 1995). The lone method for oceans appears to produce 

non-conservative results based on the limited attempt by Trapp and Hartland (1995) to 

validate the model. Although, as pointed out by Trapp and Hartland (1995), “It is unlikely 

that one universal empirical model is applicable to all cases and consequently no exact 

simulation can be expected,” it is believed that a conservative algorithm can be deduced. 

The Southworth method was consistently conservative or accurate in the validation scenarios 

reported by Trapp and Hartland, although overly conservative under certain situations of 

very low current speeds (Trapp and Hartland, 1995). 

PRAM adopted the Southworth method because it apparently will tend to overestimate 

exposure and it has previously been used within CemoS and CalTOX. One perhaps 

significant uncertainty for the application of this approach is that the method was derived 

with chemicals with Henry’s Law Constants between 1 and 100 Pa- M3

⋅mol-1 and some of 

the more chlorinated PCB homolog series have much higher Henry’s Law constants. The 

impact of this is unclear at this time. 
SECTIONTWO Model Assumptions 

SSC-SD/NEHC/URS 33 

Using the Southworth method, as described by UCD and LLNL (1994), the mass transfer 

coefficient on the waterside (Uw) is calculated as follows: 

[ ]

[ ]

0.526( ) 1.9

0.673

0.969

0.673

0.969

0.67

32

water depth 

current 

(53) 5.64

where (51)is not true and where wind 1.9

32

water depth 

current 

(52) 5.64

where (51)is not true and where wind 1.9 (3.7 knots);

(51) where current 0.04 wind ; 0.24

−

−

−

× ×

⎟

⎟

⎟

⎟

⎟

⎠

⎞

⎜

⎜

⎜

⎜

⎜

⎝

⎛

⎥

⎦

⎤ ⎢

⎣

⎡

=⎥

⎦

⎤ ⎢

⎣

⎡

⎥

⎦

⎤ ⎢

⎣

⎡ >⎥

⎦

⎤ ⎢

⎣

⎡

×

⎟

⎟

⎟

⎟

⎟

⎠

⎞

⎜

⎜

⎜

⎜

⎜

⎝

⎛

⎥

⎦

⎤ ⎢

⎣

⎡

=⎥

⎦

⎤ ⎢

⎣

⎡

⎥

⎦

⎤ ⎢

⎣

⎡ <⎥

⎦

⎤ ⎢

⎣

⎡

⎥

⎦

⎤ ⎢

⎣

⎡ = ⎥

⎦

⎤ ⎢

⎣

⎡ < × ⎥

⎦

⎤ ⎢

⎣

⎡

wind

PCB series

w

PCB series

w

w

e

m MW

s

m

d

m U

s

m

s

m

m MW

s

m

d

m U

s

m

s

m

d

m U

s

m

s

m

Water depth in the context of the PRAM is the depth to the pycnocline, which represents a 

second boundary layer. MWPCB-series is the molecular weight for a particular homolog series. 

For the airside mass transfer coefficient (Ua) according to Southworth (1979, as cited in UCD 

and LLNL, 1994): 

(54) where current wind 0 .5 (0.97 knots); ⎥

⎦

⎤ ⎢

⎣

⎡ < ⎥

⎦

⎤ ⎢

⎣

⎡ + ⎥

⎦

⎤ ⎢

⎣

⎡

s

m

s

m

s

m

(55) 

PCB series

a d MW

m U

−

=⎥

⎦

⎤ ⎢

⎣

⎡ 18 140
SECTIONTWO Model Assumptions 

SSC-SD/NEHC/URS 34 

PCB series

a s MW

m

s

m

d

m U

s

m

s

m

s

m

−

⎟

⎟

⎠

⎞ ⎜

⎜

⎝

⎛

⎥

⎦

⎤ ⎢

⎣

⎡ +⎥

⎦

⎤ ⎢

⎣

⎡ =⎥

⎦

⎤ ⎢

⎣

⎡

⎥

⎦

⎤ ⎢

⎣

⎡ >⎥

⎦

⎤ ⎢

⎣

⎡ +⎥

⎦

⎤ ⎢

⎣

⎡

18 (56) 273 wind current 

where current wind 0.5 ;

Diffusive transport across the air–surface water boundary in terms of the fugacity D value 

(Dv, in mol⋅Pa-1⋅d-1) requires a surface area for the interface (m2

) and is calculated as, using 

the nomenclature within the PRAM for compartmental exchanges: 

(57) 

( ) ( )⎥⎦

⎤ ⎢⎣⎡ +

=

12 12 21 12

1 1

1

U Z A U Z A

D

A W

v

where U12 is the airside mass transfer coefficient for the air-to-surface water boundary and 

U21 is the waterside mass transfer coefficient for the surface water-to-air boundary. 

2.3.2.4 Lower Water Column and Upper Water Column Diffusive Boundary 

No empiric method is available for estimating the mass transfer coefficients for the diffusive 

exchange of PCBs between the upper water column and lower water column across the 

pycnocline (PRAM compartments 2 and 3, respectively). There is, however, enough 

evidence for the transport of nutrients across the pycnocline that an effective diffusive value 

of 0.1 cm2

⋅s

-1 (0.864 m2

⋅d-1) has been suggested. Additionally the thickness of the 

pycnocline is assumed to equal 1 meter and as such, the diffusion path for each side of this 

boundary is 0.5 m. The foregoing assumptions simplify the overall fugacity mass transport 

coefficient and D values to: 

(58)

( ) ( )⎥

⎥

⎥

⎥

⎥

⎦

⎤

⎢

⎢

⎢

⎢

⎢

⎣

⎡

⎟

⎟

⎠

⎞

⎜

⎜

⎝

⎛

⎥

⎦

⎤ ⎢

⎣

⎡ ⎥ ×

⎦

⎤ ⎢

⎣

⎡ +

⎟

⎟

⎠

⎞

⎜

⎜

⎝

⎛

⎥

⎦

⎤ ⎢

⎣

⎡ ⎥ ×

⎦

⎤ ⎢

⎣

⎡

=

23

2

23

2 1

0.5

1 0.864

1

1

0.5

1 0.864

1

1

Z A

d m

m Z A

d m

m

D

W W

w
SECTIONTWO Model Assumptions 

SSC-SD/NEHC/URS 35 

2.3.2.5 Lower Water Column and Sediment Bed Diffusive Boundary 

The last boundary considered within the PRAM is that between the lower water column and 

the sediment bed (PRAM compartments 3 and 4, respectively). Diffusion will occur within 

the water phase within the sediment bed, which is affected by the void space within the 

sediment bed. Mackay and Paterson (1991) do not take into account any impact due to the 

presence of solids along the diffusion pathway. The CalTOX model does include a 

correction of the presence of particles within the sediment bed based on the work of 

Millington and Quirk (1961) that would reduce the efficiency of the diffusion process along a 

path where the effective diffusion (Deff) is defined as: 

(59) Deff ⎟Dw ⎟

⎠

⎞ ⎜

⎜

⎝

⎛ = 2

3

10

φ

ω

where: 

ω = the void fraction of the media occupied by the liquid18 

φ = the total void fraction within the media 

In sediment, the entire void fraction is occupied by water such that the equation within the 

PRAM is stated as: 

(60) DS Dw 3 DW

4

2

3

10

φ φ

φ = ⎟

⎟

⎟

⎠

⎞

⎜

⎜

⎜

⎝

⎛

=

where DS is the effective diffusion within the sediment pore water. 

The waterside and sediment-side mass transfer coefficients are then expressed as: 

waterside; 

 (61) ⎟

⎟

⎠

⎞

⎜

⎜

⎝

⎛

∆ = =

34

34

W

W W wws

D

Y Z U Z

 

sediment – side; 

 

18 The original equation is designed to account for the presence of additional liquids and air within the void 

space. 
SECTIONTWO Model Assumptions 

SSC-SD/NEHC/URS 36 

 (62) ⎟

⎟

⎠

⎞

⎜

⎜

⎝

⎛

∆ = =

34

34

W

W W wws

D

Y Z U Z

The interface between sediment and surface water can be diffuse where the thickness of the 

waterside boundary layer is difficult to define. The CalTOX model (UCD and LLNL, 1994) 

used a static value of 0.020 m, based on a study of radon transfers in the Hudson River 

(Hammond et al., 1975, as cited in UCD and LLNL, 1994). The use of a static value can 

constrain the analysis and as the value is based on a river study where sediment bed stability 

and currents above the bed may be quite different than that of an artificial reef environment, 

the CalTOX default value may not be applicable. Mackay et al. (1985) and Mackay and 

Paterson (1991) did not explicitly set the boundary thickness and used a transport coefficient 

(equivalent to U34 here) of 0.01 m⋅hr-1. As with the CalTOX approach, this is a static value 

and while believed to be functional, it is less desirable as it will not account for the 

differences in diffusion coefficients for the ten PCB homolog series evaluated by the PRAM. 

Additionally, comments from the TWG suggest that the boundary thickness along the 

seafloor in the area of the ex-ORISKANY Memorial Reef would be just a few centimeters. 

Until more relevant data become available, the 0.020 m (2 cm) as used by the CalTOX model 

is assumed to be functional for the PRAM. 

As for the sediment-side boundary layer thickness, Mackay and Paterson (1991) used half of 

the depth of the defined active sediment bed (i.e., the bioturburation zone, see Bosworth and 

Thibodeaux, 1990), which is a common practice (e.g., see USEPA, 1982; Trapp and 

Matthies, 1996). 

The CalTOX model approached this issue differently where a functional relationship 

between outputs from the Jury et al. (1983) modeling approach for soils were regressed 

against a range of effective diffusion coefficients for chemicals with a wide range of Kocs and 

Henry’s constants (UCD and LLNL, 1994). The following relationship was established and 

is used by CalTOX to estimate the sediment-side boundary thickness: 

(63) 0.683 ∆43[m] = 318 × DS 

There is some uncertainty associated with this approach because model results are used as 

inputs to a subsequent modeling scheme and the applicability of predicted soil results for 

sediment may not be valid. The appropriateness of this approach within the PRAM is 

unclear, as it would suggest the diffusion path length varies for each PCB homolog series. 
SECTIONTWO Model Assumptions 

SSC-SD/NEHC/URS 37 

Because of this, and given the uncertainties associated with the use of a soil-based model 

result, the CalTOX model was rejected for this purpose. The approach used by Mackay et al. 

(1985) and many others, where the diffusion path length or boundary thickness for sediment 

is set as half of the active sediment layer, is used within the PRAM. 

Diffusive transport across the surface water – sediment bed boundary in terms of the fugacity 

D value (Dv, in mol⋅Pa-1⋅d-1) requires a surface area for the interface (m2

) and is calculated as 

follows, using the nomenclature with PRAM for compartmental exchanges: 

(64) 

( ) ( )⎥⎦

⎤ ⎢⎣⎡ +

=

34 34 43 43

1 1

1

U Z A U Z A

D

W W

Y

where U34 is the waterside mass transfer coefficient for the surface water to sediment bed 

boundary and U43 is the sediment-side mass transfer coefficient for the sediment bed to 

surface water. 

2.3.2.6 Compartmental Fugacities and Media PCB Concentrations 

By invoking steady-state conditions, a mass balance using the fugacity Level III approach 

can be illustrated (Figure 7) for each compartment where inputs are balanced by outputs as 

follows (see Mackay, 1985; Mackay and Paterson, 1991): 

(65) − ∑ ( + + )+∑ ( ) = 0 j ji j i j ij Ai Ri N f D D D D f

Algebraic rearrangement results in a solution for the compartmental fugacity: 

(66) ( )

∑ ( )

∑

+ +

+

=

j ij Ai Ri

j ji j

i D D D

N D f

f

Where there is no direct emission into the compartment19 except for those transfers from 

adjacent compartments, the foregoing simplifies to: 

 

19 Compartment 5 (the vessel interior) is the only compartment within the PRAM that receives direct emissions 

of PCBs. 
SECTIONTWO Model Assumptions 

SSC-SD/NEHC/URS 38 

(67) ( )

∑ ( )

∑

+ + =

j ij Ai Ri

j ji j

i D D D

D f

f

Thus, using Table 4, the individual fugacity (f) for each compartment (as a bulk media) can 

be calculated: 

(68) [ ]

⎥

⎦

⎤ ⎢

⎣

⎡

•

⎥

⎦

⎤ ⎢

⎣

⎡

=

Pa hr

mol

hr

mol

Pa

5

5

5

DA

N

f

Advection (DA) is considered to be the sole driving force for transporting the released PCBs 

from the interior of the vessel bulk water compartment (compartment 5) into the surrounding 

water column. It is notable that the advection term is for bulk water leaving the compartment 

that includes PCBs attached to suspended solids and dissolved organic carbon. 

The lower water column (compartment 3, the bulk water below the pycnocline) receives the 

discharge of PCBs from the vessel interior: 

(69) 32 34 3 3

53 5 23 2 43 4

3 D D DA DR

D f D f D f f

+ + +

+ + =

The release of PCBs from the interior of the vessel into the lower water column is an 

advection term for a physical/mass input into the lower water column. This water 

compartment loses and gains PCBs from the upper water column (water above the 

pycnocline) and the sediment bed via diffusion and dispersion and loses PCBs through 

advection and degradation. 

The lower water compartment has functional20 boundaries with the sediment bed and the 

upper water column such that diffusive transport into these compartments is a salient issue. 

The fugacity of the sediment bed compartment, in recognition of its connection with the 

lower column, is as follows: 
SECTIONTWO Model Assumptions 

SSC-SD/NEHC/URS 39 

(70) D DR DBs

D f f

+ + =

43 4

34 3

4

The bulk sediment bed (compartment 4) gains and loses PCBs via dispersive processes from 

the lower water column and loses PCBs through degradation and sediment burial. 

PCBs, based on this model, are transported into the upper water column (compartment 2) 

from the lower water column via dispersive process across the pycnocline (2-way process) 

and across the boundary with bulk air (compartment 1) such that the fugacity of the upper 

bulk water column is algebraically described as: 

(71) 

21 23 2 2

32 3 12 1

2 D D DA DR

D f D f f

+ + +

+ =

For bulk air (compartment 1) the compartmental fugacity is: 

(72) 

12 1

21 2

1 D DA

D f f

+ =

No reactive processes are assumed to occur in the atmosphere, which conserves PCBs. 

While the forgoing algebraic solutions are correct they are circular solutions such that 

extensive substitution is required to mathematically solve the equations.21 The substitutions 

are provided in Appendix D and the solutions are as follows: 

(73) 

4

34 43

1 2 12 21

23 32 1

3

53 5

3

DT

D D

DT DT D D

D D DT DT

D f f

− − −

=

(74) 4

34 3

4 DT

D f f =

 20 No diffusive boundary is considered to be present between the vessel interior water compartment and the 

lower water column compartment. 21 Matrix solutions are possible within the code of the program given the absolute values for the input 

parameters using Gaussian elimination matrix techniques, what is presented here and in Appendix D is a pure 

algebraic solution. 
SECTIONTWO Model Assumptions 

SSC-SD/NEHC/URS 40 

(75) 

1

12 21

2

32 3

2

DT

D D

DT

D f f

−

=

(76) 

1

1

12 21

2

32 3

21

1 DT

DT

D D

DT

D f D

f

−

×

=

Given the fugacity for each compartmental phase (air, upper water column, lower water 

column, sediment, and vessel interior water), the bulk concentrations and intracompartmental 

media concentrations can be calculated. Bulk compartmental concentrations are calculated 

per equation 17, where concentration (mols⋅m-3) is defined by: C = Zf. Thus, in the context 

of the bulk concentrations for each compartment and each PCB homolog series: 

⎥

⎦

⎤ ⎢

⎣

⎡ = × × ⎥

⎦

⎤ ⎢

⎣

⎡

⎥

⎦

⎤ ⎢

⎣

⎡ = × × ⎥

⎦

⎤ ⎢

⎣

⎡

⎥

⎦

⎤ ⎢

⎣

⎡ = × × ⎥

⎦

⎤ ⎢

⎣

⎡

⎥

⎦

⎤ ⎢

⎣

⎡ = × × ⎥

⎦

⎤ ⎢

⎣

⎡

⎥

⎦

⎤ ⎢

⎣

⎡ = × × ⎥

⎦

⎤ ⎢

⎣

⎡

−

−

− −

− −

−

mol

g Z f Lmg

mol

g Z f Lmg

mol

g Z f Lmg

mol

g Z f Lmg

mol

g Z f Lmg

l

(81) PCB PCB Molecular weight

(80) PCB PCB Molecular weight

(79) PCB PCB Molecular weight

(78) PCB PCB Molecular weight

(77) PCB PCB Molecular weight

5 vessel-interior 5 5

4 sedimentbed 4 4

3 ower water 3 3

2 upper water 2 2

1 air 1 1

The specific media concentrations within each compartment are calculated using the 

compartmental fugacity, the media fugacity capacities, and densities (ρ in g⋅mol-1) of the 

media where: 

In compartment 1 (the air compartment) 
SECTIONTWO Model Assumptions 

SSC-SD/NEHC/URS 41 

(82) ⎥

⎦

⎤ ⎢

⎣

⎡ = × × ⎥

⎦

⎤ ⎢

⎣

⎡

mol

g Z f

m

g PCBair A PCB Molecular weight 3 1

(83) 

⎥

⎦

⎤ ⎢

⎣

⎡

⎟

⎟

⎠

⎞ ⎜

⎜

⎝

⎛

⎥

⎦

⎤ ⎢

⎣

⎡ ×

=⎥

⎦

⎤ ⎢

⎣

⎡

3

1 PCB Molecular weight

PCB

cm

g

mol

g Z f

kg

mg

aerosols

AE

aerosols

ρ

In compartment 2 (the upper water column) 

(84) ⎥

⎦

⎤ ⎢

⎣

⎡ = × × ⎥

⎦

⎤ ⎢

⎣

⎡

mol

g Z f Lmg PCBWater W PCB Molecular weight 2

(85) 

⎥

⎦

⎤ ⎢

⎣

⎡

⎟

⎟

⎠

⎞ ⎜

⎜

⎝

⎛

⎥

⎦

⎤ ⎢

⎣

⎡ × ×

=⎥

⎦

⎤ ⎢

⎣

⎡

SS 3

2

Suspended Solids

PCB Molecular weight

PCB

cm

g

mol

g Z f

kg

mg SS

ρ

(86)

⎥

⎦

⎤ ⎢

⎣

⎡

⎟

⎟

⎠

⎞ ⎜

⎜

⎝

⎛

⎥

⎦

⎤ ⎢

⎣

⎡ × ×

=⎥

⎦

⎤ ⎢

⎣

⎡

DC 3

2

DissolveOrganicCarbon

PCB Molecular weight

PCB

cm

g

mol

g Z f

kg

mg DC

ρ

The formats for the media concentrations in compartment 3 (the lower water column) are the 

same as those for the upper water column (compartment 2) except that the fugacity used is 

specific to compartment 3 (f3). For compartment 4 (the sediment bed), the media 

concentrations are calculated as: 

(87) 

⎥

⎦

⎤ ⎢

⎣

⎡

⎥

⎦

⎤ ⎢

⎣

⎡ × ×

=⎥

⎦

⎤ ⎢

⎣

⎡

Sediment 3

4

Sediment

PCB Molecular weight

PCB

cm

g

mol

g Z f

kg

mg SD

ρ

(88) ⎥

⎦

⎤ ⎢

⎣

⎡ = × × ⎥

⎦

⎤ ⎢

⎣

⎡ − mol

g Z f Lmg PCBPore water W PCB Molecular weight 4
SECTIONTWO Model Assumptions 

SSC-SD/NEHC/URS 42 

(89) 

⎥

⎦

⎤ ⎢

⎣

⎡

⎟

⎟

⎠

⎞ ⎜

⎜

⎝

⎛

⎥

⎦

⎤ ⎢

⎣

⎡ × ×

=⎥

⎦

⎤ ⎢

⎣

⎡

DC 3

4

DOCin pore water

PCB Molecular weight

PCB

cm

g

mol

g Z f

kg

mg DC

ρ

and within the sunken vessel (compartment 5) 

(90) ⎥

⎦

⎤ ⎢

⎣

⎡ = × × ⎥

⎦

⎤ ⎢

⎣

⎡

mol

g Z f Lmg PCBWater W PCB Molecular weight 5

*(91) 

⎥

⎦

⎤ ⎢

⎣

⎡

⎟

⎟

⎠

⎞ ⎜

⎜

⎝

⎛

⎥

⎦

⎤ ⎢

⎣

⎡ × ×

=⎥

⎦

⎤ ⎢

⎣

⎡

SS 3

5

Suspended Solids

PCB Molecular weight

PCB

cm

g

mol

g Z f

kg

mg SS

ρ

(92) 

⎥

⎦

⎤ ⎢

⎣

⎡

⎟

⎟

⎠

⎞ ⎜

⎜

⎝

⎛

⎥

⎦

⎤ ⎢

⎣

⎡ × ×

=⎥

⎦

⎤ ⎢

⎣

⎡

DOC 3

5

Dissolved OrganicCarbon

PCB Molecular weight

PCB

cm

g

mol

g Z f

kg

mg DOC

ρ

2.4 THE PRAM FOOD WEB AND TROPHIC TRANSFERS OF PCBS 

The PRAM models the transfer of PCBs from abiotic media into biota mechanistically. The 

structure of the food web within which the released PCBs are transferred is treated as a 

closed system. That is, all of the components (organisms) are assumed to be resident within 

the model construct, and do not spend any time or obtain any food outside the influence of 

the sunken vessel. For sessile organisms and less mobile organisms associated with the reef 

structure and nearby sediment bed, this assumption is probably accurate. However, for 

mobile organisms such as fish, this approach overestimates their exposure because many fish 

move from reef to reef and undergo seasonal and/or life-stage migrations. This is especially 

true for pelagic organisms, a major community modeled by PRAM, where the vast majority 

of such species undergo large oceanic movements over their lifetime. 
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2.4.1 Food Web Communities Considered Within the PRAM 

PRAM models three biological communities: a reef community, a benthic community, and a 

pelagic community. Inclusion of these communities in the model accounts for differences in 

habitat and dietary exposure anticipated among different groups of marine organisms near an 

artificial reef. They also include the apparent distribution of sport fish found at artificial 

reefs such as the ex-VERMILION.22

The literature on local hard bottom communities (Thompson et al., 1999) and the broader 

area (e.g., Bortone et al., 1997) indicates substantial variability in biotic community 

composition with depth and shape of submerged structures. The reviewed literature (Svane 

and Petersen, 2001) indicates that it is difficult to predict the exact biological structure of 

artificial reef communities. PRAM assumes that the sunken vessel will host a range of 

transient and resident fishes. 

A Trophic Level Approach 

Each of the three communities within the PRAM has four trophic levels: 

• Trophic Level I includes the primary producers 

• Trophic Level II are animals that feed directly on the primary producers; 

• Trophic Level III animals are those that feed upon Trophic Level II animals; 

• Trophic Level IV animals are those that feed on Trophic Level III animals. 

PRAM used this construct because it is well recognized as a method to describe the flow of 

energy within the food web (e.g., see Parsons et al., 1977), and the exchange and “flow” of 

PCBs within the system follows the same pathways as energy (e.g., see Newman, 1998). 

Figure 8 shows the organizational structure of the food web within the PRAM using the 

organism types from the following matrix. 

Pelagic Community Reef Community Benthjic Community 

Trophic 

Level 

General 

Group 

Examples General 

Group 

Examples General Group Examples 

 

22 In performing the human health risk assessment for the ex-VERMILION artificial reef off the coast of South 

Carolina, the Navy, assisted by the Marine Resources Division/Department of Natural Resources (SCDNR), 

conducted a fish consumption survey of local anglers, and estimated the fraction ingested (FI) term that 

relates to the potential fraction of fish caught from the ex-VERMILION that the anglers may ingest out of the 

total amount of fish they may consume per year (NEHC, 2004). 
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SSC-SD/NEHC/URS 44 

I Phytoplankton Attached 

Algae 

 None due to depth 

II Zooplankton Copepods, 

Krill 

Sessile Filter 

Feeders 

Invertebrate 

Omnivores 

Barnacles, 

Bivalves 

Echinoderms 

Infaunal 

Macroinvertebrates 

Epifaunal 

Macroinvertebrates 

Polychaetes 

Amphipods, 

Echinoderms 

III Planktivorous 

Fish 

Herring, 

Snappers 

Mobile 

Invertebrates 

Vertebrate 

Foragers 

Crustaceans, 

Echinoderms 

Trigger Fish 

Foragers Crabs, 

Lobsters 

IV Piscivorous 

Fish 

Jacks Predators Groupers, 

Barracuda, 

Morays, 

Sharks 

Predators Flounder, 

Flatfish, 

Skates, Rays, 

Sea Basses 

As with any classification scheme, not all organisms will fit neatly into the trophic scheme. 

The model accounts for the progression of diets over the life stage within a given species, 

resulting in a change of trophic status as the animal ages. 

PCB Transfer and Trophic Level Approach 

It is important to note that the PRAM does not attempt to describe the explicit reef trophic 

structure. Rather, it uses representative species at various trophic levels and from various 

feeding types to represent the major functional aspects of a pelagic community, reef 

community, and benthic community. It describes and tracks the accumulation and transfers 

of PCBs along trophic pathways. 

The PRAM food web construct is simplistic relative to the true trophic structure of an 

artificial reef and its associated communities, but fully functional for illustrating the 

movement and potential accumulation of PCBs in those organisms that may be consumed by 

people or relevant ecological receptors (i.e., functional for its end purpose–risk assessment). 

By focusing on the PCBs, the chemical-physical properties that control PCB environmental 

fate, and the subsequent potential exposure pathways, the community food web structure can 

be simplified without loss of the detail required to make risk estimates that probably 

overestimate exposure. For example, certain parasites can be considered predators, some at 

the trophic level IV, but they probably do not represent a significant PCB transport 

mechanism. 
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A more significant example involves the reef-associated trophic level III consumers. There 

are many fish within this trophic level. Those species that feed extensively on the epifaunal 

reef organisms, such as the trigger fish, would be expected to be more exposed to the PCBs 

as they leach out of the vessel and accumulate into the encrusted reef organisms. In contrast, 

the more mobile and generalist trophic level III organisms that forage away from the vessel 

(e.g., bigeye) would be less exposed, and as such, not as relevant as a more closely 

associated species such as the triggerfish. 

Thus, not all species or even species assemblages need be modeled in the PRAM to assure 

it’s utility as a risk assessment tool. The artificial reef community is illustrated conceptually 

in the context of potential PCB exposures in Figure 8. 

2.4.2 PRAM Food Web Community Structure 

PRAM uses a representative species approach within each trophic level to attempt to capture 

the structural and functional complexity of each community. PRAM attempts to represent 

several feeding types within each community. These feeding types include: 

• Herbivores; 

• Detritivores; 

• Omnivores; 

• Primary Carbivores; 

• Top Carnivores. 

2.4.2.1 Representative Herbivores 

Herbivores are those animals that consume only plants. Most marine herbivores are 

invertebrates. The following matrix (adapted from Adey and Loveland, 1991) shows the 

major groups of herbivorous invertebrates that may or may not be present within the 

communities modeled within the PRAM. 

The feeding behaviors are the key element shown in the matrix, for modeling purposes. 

Selective filtering, rasping and “cell sucking” appear to be the most representative for the 

entire group of invertebrates. In pelagic forms, selective filtering is the most common 
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SSC-SD/NEHC/URS 46 

feeding behavior. Rasping and filtering best represent the likely reef dwelling animals. The 

benthic invertebrates seem to focus on rasping and cell sucking. In terms of PCB transfers, 

the protozoans are thought to behave much like the algae (see Spacie et al., 1995; Connolly, 

1991). 

General Representative Marine Invertebrate Herbivores 

Phylum 

Class or 

Order 

Frequency of 

Herbivory 

within Group 

Example 

Common 

name 

Example 

Species23

Example of 

Tissue Eaten 

Mode of 

Feeding 

Predominant 

Community 

Protozoa Several Many Amoeba Amoeba dudia Diatoms Cytoplastic 

engulfing 

All 

Nematoda Several Many Nematodes Dorylaimida Algae Sucking of 

cell contents 

Benthic 

 

23 The examples may or may not be applicable to a specific reef community, but are presented as+ 

representative for the taxa, as adapted from Adey and Loveland (1991). 
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Phylum 

Class or 

Order 

Frequency of 

Herbivory 

within Group 

Example 

Common 

name 

Example 

Species23

Example of 

Tissue Eaten 

Mode of 

Feeding 

Predominant 

Community 

Echinodermata Echinoidea Many Sea-urchins Echinus 

esculentus 

Seaweeds Rasping Reef and 

Benthic 

Mollusca Amphineura Virtually all Chitons Ischnochiton 

ruber 

Algal turfs, 

corallines 

Rasping Reef and 

Benthic 

Arthopoda Copepoda Most Copepods Calanus Phytoplankton Selective 

filtering 

Pelagic 

 Isopoda Some Slaters Ligia oceanica Seaweed Chewing Benthic 

 Euphausiace

a 

Most Krill Euphausia 

superba 

Phytoplankton Selective 

filtering 

Pelagic, Reef 

This matrix suggests that the significant pathways for PCB transfers within the: 

• Pelagic invertebrate community will come from the filtering of algae from the water; 

• Reef invertebrates will come from the rasping of attached algae on the sunken vessel; 

• Benthic community will come from rasping of benthic algae and/or consumption of 

algae falling out of the water column onto the sediment bed. 

Pelagic Herbivores 

Larval fish that feed on phytoplankton, and some smaller adult fishes such as herring, who 

also feed heavily on zooplankton, are examples of fish herbivores within the pelagic 

community. Most pelagic planktivores and larval fish snatch or grab individual planktors, 

but some species, such as herrings, are true filter feeders. In all cases, the algae diet occurs 

only during some of the fish’s life history, or represents only a part of its diet. These fish are 

better classified as omnivores (an animal that consumes both plant and animal tissues). 

The primary point of PCB entry into the biological food web from a sunken vessel is through 

the release to water and adsorption onto suspended particles and algae. The vast majority of 

fish within the pelagic zone that exhibit some herbivory do so as larvae. At this stage in life, 

many consider these fish as part of the macroplankton, or in the context of modeling PCB 

transfers, zooplankton. The inclusion of these fish within Trophic Level II is not necessary 

to trace the transfer(s) of PCBs from primary producers to, or through, Trophic Level II of 

the pelagic community food web, because they are accounted for within the zooplankton 

compartment of the PCB transfer model. Adult filter-feeding or particle-grabbing fishes, 

such as herring, are best characterized as omnivorous because they prey primarily on 

zooplankton and secondarily on algae. The foregoing suggests that, in the pelagic 

community, the zooplankton are the most appropriate group of organisms to trace PCB 

transfers from the primary producers into the pelagic food web. 
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Reef Herbivores 

The most significant primary producers directly associated with the reef community would 

be attached algae. While floating algae may be present, water currents would relegate these 

organisms to more of a pelagic environment, such that the relevant PCB exposure would be 

associated with pelagic waters rather than reef waters, where the attached algae would reside. 

Within the reef community, the parrot fish (Scarids), tangs (Acanthurids), and to a lesser 

extent, the damselfish (Pomacentrids), are thought to represent the vertebrate herbivores. 

Parrot fish are true grazers, while the tangs are better classified as browsers. The damselfish 

that are primarily herbivores tend to browse mostly on benthic algae attached to rocky 

outcrops. While the parrot fish eats a significant amount of attached algae, its diet also 

includes a large amount of coral. While coral contains a significant amount of symbiotic 

zooxanthellae cells (i.e., algae), the majority of coral tissue consists of animal tissue (i.e., 

Coelenterata). In this sense the parrot fish is not a “true” herbivore, but rather, is more akin 

to an omnivore. 

Transfers from the reef community primary producers directly to true vertebrate herbivores 

are limited to species like the tangs. Tangs are poorly represented in the assemblages of reef 

fishes observed in and near the location of the proposed ex-ORISKANY Memorial Reef 

(Bortone et al., 1997). Of the reported 564 sampling events, Acanthurins (tangs) were 

observed 10 times (i.e., not quite 2% of the total number of samples) (Bortone et al., 1997). 

Only 20 individual fish were actually observed on and around the artificial reefs (Bortone et 

al., 1997). This suggests that while a true vertebrate herbivore population may be present at 

low density, the contribution towards any significant PCB transfer up to Trophic Level III or 

IV due to predation is unlikely. Those predators present on the artificial reef would not 

receive a significant loading of PCBs from preying on a very small population of herbivorous 

vertebrates. 

The most significant pathway for PCBs from the primary producers directly associated with 

the reef community would be through the grazing/foraging (mobile) invertebrate herbivores, 

such as urchins and mollusks. 

Benthic Herbivores 

There will be no benthic herbivores at the ex-ORISKANY site because the sandy bottom and 

the depth of the ex-ORISKANY Memorial Reef site location prevents the growth of plants. 
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2.4.2.2 Representative Detritivores 

Detritivores are animals that primarily consume dead biological tissue or excreta. Most of 

these are benthic animals, but filter feeders on a reef feeding on suspended particles could be 

classified as detritivores. Some macroinvertebrates like annelid worms, mollusks, and 

arthropods can be classified as detritivores. To a certain extent, scavenging organisms such 

as many crabs, shrimp, and some fish (e.g., hagfish, sharks, etc.) can also be classified as 

detritivores. 

Detritivores that fall into the Trophic Level II or III position within the food web are relevant 

for the PRAM. Large carrion feeders, in the context of PCB modeling, effectively act as top 

predators, as their diet generally includes many Trophic Level III/IV animals. On the other 

extreme are the very small carrion feeders such as bacteria and other micro/macro 

invertebrates. Here in the context of PCB modeling, the biomass associated with the carrion 

of larger Trophic Level III/IV organisms is small relative to Trophic Level I or II biomass 

(e.g., see Parsons et al., 1977). This carrion PCB transfer pathway should be considered at 

the trophic III level to assure that the pathway is not “missed” in the model. Detritivores that 

fall within the Trophic Level II position must also be considered, and are best represented by 

deposit feeder and filter feeder guilds, in the sense of food web dynamics and biomass (e.g., 

Parsons et al., 1977; Adey and Loveland, 1991). In a general sense, many filter feeders are 

not true detritivores, given that they consume a significant amount of living material. 

However, for evaluating PCB transfers, given that part of their diets are known to include 

fecal pellets and seston, filter feeders can be used to represent the PCB transfers from detritus 

derived from lower trophic level carrion. It is important to note that the greatest mass of 

detritus/carrion is derived from Trophic Levels I and II biomass (e.g., see Parsons et al., 

1977). 

Pelagic Detritivores 

Within the pelagic community the detrital pathway can/should be accounted for utilizing 

zooplankton and/or planktivorous fish by adjusting their diets to include some detritus (as 

suspended particles representing Trophic Level I/II carrion) within their matrix. 

Reef Detritivores 

Within the reef community the sessile filter feeders such as bivalves and barnacles would be 

expected to consume organic-rich suspended particles such as phytoplankton/zooplankton 

carrion along with live plankton. Mobile epifaunal species, such as crabs and shrimps, feed 
SECTIONTWO Model Assumptions 

SSC-SD/NEHC/URS 50 

on carrion. Such crustaceans are known to forage opportunistically, commonly ingesting 

carrion, living organisms, and even plant material. These crustaceans are probably more 

appropriately classified as omnivores than detritivores, and the next subsections reconsider 

them as omnivores or 1st order carnivores. The most significant consumers of detritus 

derived from Trophic Level I and II organisms are the filter/ deposit feeders on the reef, as 

represented by bivalves and barnacles. 

Benthic Detritvores 

Within the benthic community the detritivores represent the largest biomass relative to all 

other guilds. Most of these detritivores are bacteria, fungi, microbenthos (<0.1 mm), 

meiobenthos (0.1 mm to 0.5 mm) and macrobenthos (>0.5 mm).24 However, in the context 

of the transfers into the food web, other larger forms (the macrobenthos or 

macroinvertebrates with the micro and meiobenthos, hereafter referred to as 

microinvertebrates) represent the major predators or consumers of their community. These 

macroinvertebrates represent the transfer pathway out of the sediment bed and into the food 

web to top predator fish consumed by humans and/or relevant ecological receptors. 

Although microinvertebrates are far more numerous than macroinvertebrates per unit area, 

typically the biomass of macroinvertebrates is far greater than that of the microinvertebrates 

per unit area. For example, Parsons et al. (1977) report a study that revealed an overall 

abundance ratio of 1:70 for macrobenthos and meiobenthos, respectively in number of 

individuals, but a biomass ratio of 24:1 by fresh weight. Additional data collected from the 

scientific literature at that time (Parsons et al., 1977, Table 34) showed a consistently higher 

biomass for the macrobenthos, even if ciliates were considered over a significant range of 

geographical areas and sediment bed types in the ocean. 

Two types of benthic (sediment-associated) macroinvertebrates are considered within the 

PRAM, infaunal and epifaunal forms. Infaunal refers to those macroinvertebrates that live 

within the sediment bed itself, whereas the epifaunal forms live upon the sediment bed (e.g., 

see Parsons et al., 1977). There is significant overlap among the many species at issue here. 

Some species build tubes within the bed but feed from the sediment bed surface, while other 

tube builders will migrate into the water column to feed and return to their tubes for shelter 

from predation. Many of the epifaunal forms such as shrimp and scallops make extensive 

movements into the water column (e.g., see Parsons et al., 1977). By considering where 

maximum PCB exposure would or could occur, the relevant invertebrate forms can be 

identified. 

 

24 Benthos classification after Levinton (1982) as cited in Adey and Loveland (1991). 
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Certain infaunal benthic forms, such as the true worms (annelids, i.e., the burrowing 

polychaete worms), do not build tubes nor do they migrate out of the sediment bed to any 

significant degree. They consume organic-rich sediment particles (detritus) that are coated 

with the bacteria and microinvertebrates, as discussed above. Clearly these benthic 

macroinvertebrate forms are significant in the context of PCB transfers from the sediment 

into the food web, as these organisms also represent a significant forage base for higher 

trophic level animals. To capture the transfer of PCBs into the detrital food web, infaunal 

macroinvertebrate worms are the best representative group of infaunal benthic organisms. 

Epifaunal benthos include both macro- and mega-invertebrates, such as nudibrancs, 

echinoderms, mollusks, and crustaceans. The majority of these mega-invertebrates are 

predators and thus not relevant to detrital pathways, although many of the mollusks are filter 

or deposit feeders. As noted previously, the greatest input of biomass and energy into the 

detrital food web is derived from the pelagic primary producers and pelagic primary 

consumers. Thus, the most significant pathway to trace in order to follow the trophic 

transfers of PCBs is to identify the major consumers of this type of detritus. The epifaunal 

deposit and filter feeders represent the primary consumer guild in this context and as such, 

the relevant guild for tracing PCB transfers. Typical representatives include nematodes, 

polychaetes (deposit feeders) and bivalves (filter feeders). 

2.4.2.3 Representative Omnivores 

Omnivores are animals that consume plant and animal tissue, generally in a fresh state. For 

purposes of modeling the PCB transfers within the food web, however, consumption of 

carrion and detritus is considered relevant for them. There are many taxonomic 

representatives among omnivores for invertebrates and vertebrates. Omnivores are between 

Trophic Level II (primary consumers) and Trophic Level III (secondary consumers). 

Pelagic Omnivores 

As discussed above on the pelagic community, planktivores such as herring will consume 

floating algae as part of their diet. Additionally, there are invertebrates in the pelagic water 

column, such as species of shrimp that consume both algae and zooplankton. Consumption 

of dead algae and zooplankton has been identified as a potentially relevant and significant 
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SSC-SD/NEHC/URS 52 

transfer pathway for PCBs. However, PRAM does not incorporate the pelagic omnivore 

pathway. 

Reef Omnivores 

Within the reef community there are numerous examples of vertebrate and invertebrate 

omnivores. The parrot fish, discussed previously, can be classified as an omnivore. Sea 

urchins, also mentioned earlier, consume significant quantities of algae, but also consume 

animal tissues. Many shrimps are also omnivorous. The representative detritivores 

identified as important in the context of PCB transfers, the filter feeders, are also omnivores. 

These filter feeders however, do not feed upon any attached algae directly associated with 

the sunken vessel, whereas organisms such as urchins and some crustaceans would. Sea 

urchins are an appropriate representative of reef omnivores because they capture the transfer 

of PCBs from attached algae, and hydroids. 

2.4.2.4 Representative Primary Carnivores 

First order carnivores consume animals that are primarily herbivorous or in the case of the 

detrital food web, those detritivores that consume primarily detritus derived from algae and 

zooplankton. Organisms within this guild are considered to represent Trophic Level III 

within the PRAM. 

Pelagic Primary Carnivores 

Planktivorous fish are the primary group for consideration in modeling PCB transfers from 

Trophic Level II within the pelagic community. These animals consume mostly 

zooplankton, which represent the primarily consumers within the community, and represent a 

significant food source for higher trophic level predators. 

Reef Primary Carnivores 

While planktivorous fish would be expected to reside in the reef community as well, uptake 

into organisms such as filter feeders and urchins would be expected to represent the major 

PCB uptake pathway from lower trophic levels (filter feeders – see the discussion of 

detritivores, e.g., bivalves and rasping echinoderms such as urchins, see discussion of 

herbivores and omnivores). Both fish and other invertebrates will prey upon these 

organisms. Fish such triggerfish, and invertebrates such as crabs, are typical representatives 

for the predators of sessile filter feeders and crawling invertebrates such as urchins. Both of 

these types of predators forage along the reef. In addition, crabs will consume carrion, which 

was identified as a potentially relevant pathway for PCB transfers. 
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Benthic Primary Carnivores

The infaunal and epifaunal macroinvertebrate detritivores, in the context of the PRAM 

benthic community food web (detrital food web), occupy Trophic Level II as primary 

consumers of detritus. Many organisms, both vertebrates and larger invertebrates, will prey 

upon these detritivores. Those predators close to the sediment bed that probe or sieve the 

sediment for these organisms would be expected to have a higher PCB exposure than those 

predators that capture the organisms as they move out of the sediment. Sediment probing 

and sieving predators of the macroinvertebrate detritivores include nudibrancs, crustaceans 

(e.g., crabs and lobsters), echinoderms, and skates, drums, and hogfish. Most fish, including 

those mentioned move extensively in the water column. The invertebrates, such as the 

nudibrancs, crabs, lobsters, and echinoderms, are in much closer contact with the sediment, 

and as such, are more likely to receive a higher exposure to any PCBs directly associated 

with the sediment than the more mobile fish or invertebrates such as squid. 

Thus, the most relevant first-order predators for tracing PCBs within the benthic community 

are those foraging invertebrates that probe or sieve the sediment for macroinvertebrate 

detritivores, such as the crustaceans. 

2.4.2.5 Representative Top Carnivores 

Top carnivores consume herbivores, carnivores, and omnivores. These are Trophic Level IV 

organisms. 

The PRAM has been designed as a tool for human health risk assessment and as such, sports 

fish (primarily top predators-finfish and shellfish) sought after and consumed by humans are 

the focus. The approach used in PRAM, as discussed above, has been taken to increase the 

probability of overestimating the transfer of PCBs into sports fish. 

Pelagic Top Carnivores 

Within the pelagic food web, this trophic level is dominated by fish such as jacks, tuna, and 

sharks. Although some invertebrates, such as squid, could be considered to be at this level, 

they are generally not taken by recreational anglers. Of the typical pelagic fish taken by 

anglers, the jacks are perhaps the most representative given their, albeit slight, fidelity to 

structure. 
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SSC-SD/NEHC/URS 54 

Reef Top Carnivores

Certain top predators on the artificial reef, such as eels and barracuda, are not commonly 

considered sports fish. Groupers are among the more popular sports fish on artificial reefs, 

and are top predators (Trophic Level IV). 

Benthic Top Carnivores

A similar situation is present in the context of the benthic top carnivores, where organisms 

such as toadfish, skates, and sharks are true top carnivores; top carnivores such as the flatfish 

(e.g., flounder) are commonly sought and consumed by anglers. Other sport fish such as 

some snappers and sea bass forage extensively within the benthic community, but return to 

the reef for shelter when not foraging. This will reduce their direct exposure levels to the 

sediment bed and in the context of PCB transfers decrease their overall exposure level, at 

least to the sediment-associated PCBs. These carnivores are not presently considered viable 

representatives because their exposure is mitigated by this migration on and off the reef. 

2.4.3 Generalized Representative Dietary and Water Exposures for Use in Modeling PCB 

Food Web Transfers 

This subsection summarizes the dietary and water exposures of the pelagic, reef, and benthic 

communities. Each discussion presents a representative organism and its generalized diet 

and exposure profile. 

The PRAM does not attempt to model the trophic dynamics within and among the three 

biological communities but rather calculates PCB accumulation along the most efficient 

pathways within each community separately. Such calculations probably overestimate 

exposure within each community because the implicit assumption is that each community 

has access to all the PCBs in the abiotic media even though these PCBs will be distributed 

among all three communities in reality. 

2.4.3.1 Pelagic Community 

Phytoplankton 

The primary producers (Trophic Level I) within the pelagic community are the 

phytoplankton. The PRAM accounts for the fact that a pycnocline forms within the water 

column that will affect the dissolved PCB water concentrations. While algae may sink 
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SSC-SD/NEHC/URS 55 

through this boundary, they are not expected to remain as living cells but rather as falling 

particles, as the light attenuation with depth would limit algal growth and survival at depth. 

Water column Exposure: For algae, the relevant water exposure to PCBs is that concentration 

above the pycnocline, in well-lit waters. 

Zooplankton 

The crustacean zooplankton represents the largest group, in terms of feeding habits and 

biomass, in most ocean waters (e.g., see Parsons et al., 1977), and as such, are the most 

relevant in considering the potential for accumulation of PCBs. Most of these zooplankton 

are selective filter feeders that graze on the phytoplankton (e.g., Parsons et al., 1977). The 

dietary makeup for most of these zooplankton is most often characterized by particle size 

rather than prey type (e.g.algae, bacteria, and/or particulate organic carbon). 

Dietary Exposure: Considering PCB accumulation, bacteria, algae, and organic particulates 

are modeled as simple sorption materials (see Spacie et al., 1995; Connolly, 1991). The 

dietary breakout is not overly significant, except in the context of the relative sorption 

capacity of these dietary components. Within the PRAM this simplifies the available diet for 

this trophic level to suspended particles, which includes bacteria and suspended organic 

solids. 

Water Column Exposure: Zooplankton are expected to migrate across the pycnocline and be 

exposed to PCB concentrations above and below it. Feeding is expected to occur primarily 

in the upper water column where the phytoplankton are expected to be concentrated. Below 

the pycnocline only minimal feeding on suspended solids is predicted (Table 5). 

Planktivores 

Planktivores (modeled as a herring-like fish) are assumed to feed exclusively on the 

zooplankton (Table 5). 

Dietary Exposure: The assumption of 100% zooplankton diet is used to assure that the 

planktivore PCB concentration is not underestimated. 

Water Column Exposure: Predation on the zooplankton will occur for most planktivores 

visually and assumes a limited foray into the lower water column (time breakout, 80:20, 

Table 6). 
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Top Carnivore

Dietary Exposure: The top carnivore (modeled as a jack-like fish) is assumed to feed almost 

exclusively (90%) on the planktivores with a small fraction of the diet consisting of 

zooplankton (10%) to account for the changes in diet over the fish’s life stages (Table 5). 

This diet is in keeping with what has been reported for jacks (e.g., see Weaver et al., 2001). 

Water Column Exposure: These predators are expected to follow the planktivores through 

the pycnocline so that their water exposure regime mirrors the planktivores (80:20, Table 6). 

2.4.3.2 Reef Community 

Primary Producers 

The primary producers directly associated with the artificial reef are attached algae. Given 

the depth of the ex-ORISKANY Memorial Reef, the algae will likely be limited to the upper 

portions of the prospective reef due to their light requirement. Nevertheless, these waters are 

predicted to be below the pycnocline. 

Water Column Exposure: The water exposure level for attached algae is set as such (Table 

6). 

Primary Consumers - Filter Feeders and Rasping Echinoderms 

PRAM uses two groups of primary consumers to estimate PCB uptake through the reef 

community food web. The first group is the filter feeders, which are modeled as bivalves. 

Although Trophic Level II organisms are generally herbivores, PRAM used an omnivorous 

diet to provide a higher estimate of exposure than a purely herbivorous diet offers. 

Dietary Exposure: Bivalve mollusks and barnacles mostly feed upon algae with some 

suspended solids, but other filter-feeders on the prospective reef would feed on zooplankton 

(e.g., hydroids, etc.) as well. To reflect this fact, the filter feeder diet includes floating algae 

(80%), a fraction of zooplankton (10%), with a relatively small fraction of suspended solids 

(10%). This diet is not specific to any bivalve species, but rather, reflects the filter feeding 

community expected to occur on the artificial reef. 

Dietary Exposure: The second group of primary consumers modeld in PRAM are 

omnivorous rasping echinoderms (modeled as an urchin). A generalized diet for these 

echinoderms emphasizes the herbivorous forms to reflect a Trophic Level II position and 
SECTIONTWO Model Assumptions 

SSC-SD/NEHC/URS 57 

importance of the PCB transfer from attached algae into the reef food web (80% of diet), but 

also sessile organisms such as the hydroids (20% of diet, Table 5). 

Water Column Exposure: Exposure of these organisms is limited to the lower water column 

because the reef is not expected to extend above the pycnocline nor are the urchins expected 

to migrate across it. Therefore these organisms would be exposed to PCB concentrations in 

the lower water column of the model system, and potentially waters within the vessel if the 

organism(s) used the vessel interior. The sessile filterers are unlikely to extend into the 

vessel interior because it is assumed to have low oxygen and low food availability. 

However, the mobile animals, such as the echinoderms, may use the vessel interior as a place 

of shelter from predation. PRAM assumes that these animals are exposed 20% of the time in 

the vessel interior and 80% of the time in the lower water column (Table 6). 

Foraging Invertebrates and Fish 

Carnivorous crustaceans (modeled as crabs) were identified as a relevant pathway for tracing 

PCB transfers within the reef community. Foraging crustaceans within the reef community 

would be highly opportunistic in their dietary preferences. 

Dietary Exposure: PRAM assumes a diet of 50% echinoderms, 35% bivalve filter feeders, 

and to account for a limited input from the pelagic community as infrequent visitation and/or 

as carrion 5% zooplankton, 5% pelagic planktivorous fish, and 5% suspended solids 

(sorption materials, including bacteria, organic matters, and detached algae). 

Dietary Exposure: The fish forager within the reef community would have a diet again of the 

sessile filter feeders (modeled as bivalves) and invertebrate omnivorous foragers (modeled as 

urchins). For this type of fish (modeled as trigger fish), the dietary components include some 

planktivorous fish (19%), reef carnivorous invertebrate foragers (22%), modeled as a crab, 

omnivorous echinoderms (15%), modeled as an urchin, sessile filter feeders (19%), modeled 

as bivalves, epifaunal benthos (12.5%), and infaunal benthos (12.5%) (Table 5). This dietary 

breakout is in keeping with reports for the gray trigger fish (e.g., see Nelson and Bortone, 

1996), and the TWG recommendations. 

Water Column Exposure: Both the foragers are assumed to be present only within the reef 

community and as the prospective reef will be below pycnocline, water exposure would be of 

the water PCB concentration within the lower water column and/or water interior to the 

sunken vessel as used for potential shelter from predation (Table 6). The percentage of 

vessel interior respired waters (30%) is slightly higher than that for the echinoderm 
SECTIONTWO Model Assumptions 

SSC-SD/NEHC/URS 58 

omnivores (20%) due to the behavior associated with these predators (i.e., more time spent 

resting in nooks and crannies along the artificial reef than foraging omnivores such as 

urchins). 

Top Carnivore 

A top reef carnivore consumes primarily Trophic Level III organisms from the reef. Not all 

top carnivores that reside on the reef prey exclusively on reef organisms. For example, the 

gag grouper, while considered to be a reef resident, preys heavily on pelagic planktivorous 

fish. 

Dietary Exposure: The top reef carnivore is assumed to prey primarily (60%) on reef Trophic 

Level III fish (modeled as trigger fish) and Trophic Level III invertebrates (15%) (modeled 

as crabs) (Table 5). 

Water Column Exposure: PRAM assumes that these top carnivores have less need for shelter 

within the vessel, remain on the reef, and have no exposure to the PCB water concentrations 

in the upper water column (Table 6). 

2.4.3.3 Benthic Community 

No primary producers are expected to occur along the sediment bed associated with the exORISKANY Memorial Reef due to the depth of the water and light attenuation at that depth. 

Detritivores 

The infaunal organisms (modeled as polychaetes) that burrow into and reside within the 

sediment bed are assumed to consume sediment that is coated with bacteria and 

microbenthos associated with the sediment particles. 

Dietary Exposure: The diet of these organisms is represented in Table 5 where the animals 

consume 50% sediment particles, 30% algal cells and 20% zooplankton that have fallen from 

the water column. 

The epifaunal macroinvertebrates (modeled as nematodes) are represented as primarily 

deposit feeders with representative predators (e.g., Euncida and Phyllodocida) of other 

worms and small infaunal organisms with a fractionated diet made up of 25% sediment, 30% 

deposited algae, 20% deposited zooplankton, and 25% infaunal macroinvertebrates to reflect 

benthic predators within this guild (Table 5). 
SECTIONTWO Model Assumptions 

SSC-SD/NEHC/URS 59 

Water Column Exposure: Infaunal and epifaunal macroinvertebrates exposure to sediment 

pore water is germane. The sediment pore water concentrations of PCBs may be higher than 

the concentration in the overlying water due to desorption for the sediment particles and 

diffusive impedance from the pore water into the overlying waters. In modeling the transport 

of PCBs, the infaunal macroinvertebrate, for the most part, rarely move into the overlying 

water but this is not to say they do not respire overlying waters (e.g., see Chapman et al., 

2002). 

PRAM assumes that the water exposures for infaunal invertebrates is 80% pore water and 

20% overlying surface water below the pycnocline (Table 6). The epifaunal 

macroinvertebrates live at the interface between the surface water and the sediment such that 

they respire predominantly overlying water. Nevertheless during feeding and disturbing the 

sediment bed, they would have a significant potential for pore water exposure. For epifauna, 

the fractional water exposure for PCB accumulation via respiration is 50% pore water PCB 

concentrations and 50% surface water (below the pycnocline; see Table 6). 

Primary Carnivores 

The relevant first order carnivores within the benthic community in the context of maximal 

exposure levels are those that forage directly on the sediment and dig, probe or sieve the 

sediment for their prey. Among this group are organisms that are directly consumed by 

humans such as crabs and lobsters. Recognizing this and the objective for the PRAM 

(human health risk assessment), the lobster is a logical representative species. 

The diet of lobsters includes mostly epifaunal macroinvertebrates such as gastropods, 

echinoderms, and bivalves (e.g., see FMRI, 2003). 

Dietary Exposure: PRAM assumed the lobster’s diet (Table 5) is approximately an equal 

distribution of infaunal (50%) and epifaunal (45%) organisms and that the animal will 

incidentally consume sediment as it digs or probes into the sediment for these prey items 

(5%). Exposure to pore water concentrations of the PCBs would also be expected because 

the lobster forages along the sediment bed. 

Water Column Exposure: To account for this exposure while recognizing that most of the 

water respired by an animal above the sediment will be of overlying water, the fraction of 

pore water respired is 25% of the total with 75% of the water respired being at the PCB 

concentration of the lower water column (Table 6). 
SECTIONTWO Model Assumptions 

SSC-SD/NEHC/URS 60 

Top Carnivores 

Top carnivores within the benthic community include rays or skates, sharks, flatfish, 

toadfish, certain species of snappers, and others. Of note here are the sports fish that may be 

sought after and consumed by humans. Those organisms that feed heavily on Trophic Level 

III benthic animals (modeled as the lobster) would be exposed to the highest concentration of 

PCBs. The more common sports fish are flat fish (e.g., flounders). 

Dietary Exposure: A dietary makeup of 58% Trophic Level III carnivores, 20% epifaunal 

macroinvertebrates, and 20% infaunal macroinvertebrates represents a diet that probably 

does not underestimate PCB exposure. PRAM assumes an incidental sediment ingestion of 

2% (Table 5). 

Water Column Exposure: As these fish (modeled as a flounder) would be expected to be in 

close contact with the sediment while feeding and resting, they would be expected to be 

exposed to some level of higher PCB concentrations in the water. To account for these 

increased exposure concentrations the top benthic carnivores are assumed to respire 10% 

sediment pore water and 90% water below the pycnocline (Table 6). 

2.5 PRAM PCB TROPHIC TRANSFER METHODS AND ALGORITHMS 

Bioconcentration of PCBs by aquatic organisms from water can be described as a onecompartment, first-order kinetics model (e.g., see Equation 10 in Spacie and Hamelink, 1995; 

Equation 3.19 in Newman, 1998):25

(93) ⎪⎭

⎪

⎬

⎫

⎪⎩

⎪

⎨

⎧

⎥

⎥

⎦

⎤

⎢

⎢

⎣

⎡

×⎟⎟

⎠

⎞ ⎜

⎜

⎝

⎛

⎥

⎦

⎤ ⎢

⎣

⎡ +⎥

⎦

⎤ ⎢

⎣

⎡ −

⎟

⎟

⎠

⎞

⎜

⎜

⎝

⎛

⎥

⎦

⎤ ⎢

⎣

⎡ ×

⎥

⎥

⎦

⎤

⎢

⎢

⎣

⎡

⋅ = = ∆

∆

lp

t

w i i i

lp

i

i

kg

mg C

d

G

d

Ke

L

mg C

kg d

L Ku

t

C 1 1 uptake - loss

where: 

∆Ci = change in tissue concentration for organism i [mg⋅kglp

-1] 

∆t = change in time [d] 

Kui = uptake rate constant for water in organism i

Cw = concentration of PCB in water (surface water and/or sediment pore water) 

 

25 Spacie and Hamelink (1995) combine the two loss terms (Ke and G) as a first order rate constant for 

depuration denoted as Kd. 
SECTIONTWO Model Assumptions 

SSC-SD/NEHC/URS 61 

Kei = elimination rate constant (sum of elimination and metabolism) for 

organism i

Gi = growth rate for organism i

Ci

t

 = PCB concentration in organism i at time t 

kg = kilogram 

mg = milligram 

L = liter 

d = day 

lp = lipid 26

Uptake and accumulation of PCBs by aquatic organisms from food can also be described 

with a simple one-compartment, first-order kinetics model (e.g., see equation 34 in Spacie 

and Hamelink, 1995; equation 3.24 in Newman, 1998): 

(94) ⎪⎭

⎪

⎬

⎫

⎪⎩

⎪

⎨

⎧

⎥

⎥

⎦

⎤

⎢

⎢

⎣

⎡ ×⎟

⎟

⎠

⎞

⎜

⎜

⎝

⎛

⎥

⎦

⎤ ⎢

⎣

⎡ +⎥

⎦

⎤ ⎢

⎣

⎡ −

⎥

⎥

⎦

⎤

⎢

⎢

⎣

⎡

⎥

⎦

⎤ ⎢

⎣

⎡ = ∆

∆

lp

t i i i

lp

i j j

i

kg

mg C

d

G

d

Ke

kg

mg C

d

I

t

C 1 1 1

α ,

where: 

∆Ci = change in tissue concentration for organism i [mg⋅kglp

-1] 

∆t = change in time [d] 

α = assimilation efficiency of COC across digestive tract of organism i

[fraction] 

Ii,j = ingestion rate of dietary item j for organisms i 

kglp·j/kglp·i = kilogram lipid of dietary item j consumed per kilogram lipid of organism 

i

Cj = COC concentration in the dietary item j

Kei = elimination rate constant (sum of elimination and metabolism) for 

organism i

Gi = growth rate for organism i

Ci

t

 = COC concentration in organism i at time t

Equation 94 can be combined with Equation 93 to estimate tissue concentrations of aquatic 

organisms contributed via water, sediment, and food assuming that a steady-state27 condition 

 

26 All concentrations are normalized by lipid content in keeping with the approach presented by Thomann 

(1981) and others. 
SECTIONTWO Model Assumptions 

SSC-SD/NEHC/URS 62 

has been reached and, as such, the change in chemical concentration (lipid-based) over time 

becomes zero. At equilibrium, the rate at which the chemical enters the organism and the rate 

at which the chemical is eliminated or metabolized are balanced. Equation 94 assumes only 

one dietary item, which for the aquatic animals within the PRAM is not appropriate. To 

account for multiple dietary items, Equation 94 is modified and combined with Equation 93 

as follows: 

(95) ( ) ( ) [( ) ] ss

i i i

n

j

ss

i w i j j

i Ku C I C Ke G C

t

C = = × + − + ×

∆

∆ ∑=1

, 0 α

where: 

∆Ci = change in tissue concentration for organism i

∆t = change in time [d] 

Kui = uptake rate constant for water in organism i

Cw = concentration of PCB in water (surface water and/or sediment pore water) 

α = assimilation efficiency of PCB in dietary item j across digestive tract of 

organism i 

Ii,j = ingestion rate of dietary item j by organism i

Css

j = concentration of PCB in dietary item j at thermodynamic steady-state 

Kei = elimination rate constant (sum of elimination and metabolism) for 

organism i

Gi = growth rate for organism i

Css

i = concentration of PCB in organism i at thermodynamic steady-state 

n = number of dietary items 

j = specific dietary item j

Equation 95 is equivalent to the governing equation(s) used by Gobas (1993), Connolly 

(1991), and Thomann et al. (1992). As described above, the first term represents the direct 

uptake of PCB by the animal from water, the second term represents the flux of PCB into the 

animal through feeding, and the third term is the loss of PCB due to metabolism and 

excretion plus the change in concentration due to growth. 

 27 Thermodynamic equilibrium, or “steady-state,” is defined as when uptake and loss are balanced such that the 

change in tissue concentration is zero, as depicted in Equation 95. 
SECTIONTWO Model Assumptions 

SSC-SD/NEHC/URS 63 

According to Spacie et al. (1995) and others, the uptake of chemicals (i.e., PCBs) into 

aquatic animals should be based on the “freely dissolved”28 fraction of the chemical in water. 

Given the organic carbon (oc) fraction and the particulate organic carbon content in the water 

column (foc), dissolved organic carbon can be calculated. Spacie et al. (1995, Equation 9) 

provides the following equation from which a freely dissolved water concentration can be 

derived: 

(96) 

oc oc doc doc

tw

dw f K f K

C C

+ × + × = 1

where: 

Cdw = freely dissolved COC concentration in water 

Ctw = total COC concentration in water 

foc = fraction of particulate organic carbon within the water column 

Koc = organic carbon-water partition coefficient 

fdoc = fraction of dissolved organic carbon within the water column 

Kdoc = dissolved organic carbon-water partition coefficient 

The fraction freely dissolved PCB concentration = 

tw

fd dw

C

C f =

Therefore, 

(97) 

⎟

⎟

⎠

⎞ ⎜

⎜

⎝

⎛

×⎥

⎦

⎤ ⎢

⎣

⎡ +⎟

⎟

⎠

⎞ ⎜

⎜

⎝

⎛

×⎥

⎦

⎤ ⎢

⎣

⎡ +

=

oc oc doc doc

fd

K

L

kg K f L

kg f

f

1

1

where: 

f fd = fraction of PCB concentration that is freely dissolved 

foc = fraction of particulate organic carbon within the water column 

fdoc = fraction of dissolved organic carbon within the water column 

Koc = organic carbon – water partition coefficient 

Kdoc = dissolved organic carbon – water partition coefficient 

 

28 Freely dissolved refers to the total concentration of a PCB in surface water minus that fraction adsorbed to 

suspended particulate organic carbon and dissolved organic carbon (see Spacie et al., 1995; USEPA, 1995). 
SECTIONTWO Model Assumptions 

SSC-SD/NEHC/URS 64 

2.5.1 Equations that Describe Food Transfers of PCBs 

Estimates of uptake and accumulation of PCBs from the diet of aquatic animals requires a 

description of the food web or food chain within which the PCBs are interacting. As 

described above, the food web within the PRAM consists of three inter-related communities: 

the benthic (sediment bed-associated), reef-associated (vessel-associated), and pelagic (water 

column-associated) communities. 

As previously described, PCBs will enter the food web via uptake across the respiratory 

tissues of aquatic animals and across the digestive tract of those animals that consume 

organic carbon within the sediment (bedded or suspended in the water column) as an energy 

source. These PCBs can then be transferred within the food web via consumption of aquatic 

biota (e.g., from aquatic worms feeding on sediment into bottom foraging fish or other 

invertebrates). If the accumulation of PCBs is highly efficient, but the depuration rate is low 

(i.e., not readily excreted or metabolized), the relative concentrations of the PCB among the 

trophic levels depicted above can become significantly elevated along the food chain. This 

phenomenon is commonly referred to as biomagnification (e.g., see Newman, 1998). 

Biomagnification is quantified within PRAM by the calculation of two separate factors, the 

bioconcentration factor (BCF) and the bioaccumulation factor (BAF). Both factors represent 

the ratio between the PCB concentration in the organism’s tissues and the PCB concentration 

in the water. The difference between the factors is in the source of the PCBs; the BCF 

represents only the PCBs collected directly from the water, while the BAF represents PCBs 

collected from water plus PCBs collected from food (and therefore includes an organism’s 

BCF as one of its components). 

The governing equation (Equation 95) was developed specifically to describe the movement 

of organic chemicals such as PCBs within an aquatic food chain (Thomann, 1981, 1989; 

Connolly, 1991; Thomann et al., 1992). The following sections describe how Equation 95 

was adapted to describe the movement of PCBs in the PRAM by extension to the exORISKANY Memorial Reef. 

2.5.1.1 Bioconcentration Factors 

BCFs represent the PCBs taken by an organism directly from the water, and therefore do not 

include food sources. Restating equation 95 without the food sources, we have the steadystate concentration of PCBs contributed directly from the water: 
SECTIONTWO Model Assumptions 

SSC-SD/NEHC/URS 65 

(98) ( )( ) [ ] ss

i w i i i

i Ku C Ke G C

t

C = = × − + ×

∆

∆ 0

We can then solve for the BCF as follows: 

(99) 

⎥

⎦

⎤ ⎢

⎣

⎡ +⎥

⎦

⎤ ⎢

⎣

⎡

⎥

⎥

⎦

⎤

⎢

⎢

⎣

⎡

⋅ = =

⎥

⎥

⎦

⎤

⎢

⎢

⎣

⎡

d

G

d

Ke

kg d

L Ku

C

C

kg

L BCF

i i

lp

i

w

ss

i

lp

i 1 1

PRAM uses equation 99 to calculate the BCF of all organisms except the algae. Algae (free 

floating or attached to the sunken vessel) are assumed to act primarily as sorption material 

for PCBs freely dissolved in the water column. As such, the concentration within algae is 

dependent on the adsorbent (lipid) concentration within the algae, which can be directly 

related back to the PCB’s octanol-water partition coefficient (Kow – e.g., see Thomann, 

1989). However, for chemicals with a logKow greater than 5.0, the algal BCF becomes 

constant (see Spacie et al., 1995; Connolly, 1991): 

(100) 

5 10

;

log 5.0

;

 log 5.0

=

⎥

⎥

⎦

⎤

⎢

⎢

⎣

⎡

>

=

⎥

⎥

⎦

⎤

⎢

⎢

⎣

⎡

≤

lp

ag

ow

ow

lp

ag

ow

kg

L BCF

then

if K

K

kg

L BCF

then

if K

where: 

BCFag = bioconcentration factor for algae (ag) exposed to freely dissolved PCB 

water concentrations 

Kow = octanol-water partition coefficient 
SECTIONTWO Model Assumptions 

SSC-SD/NEHC/URS 66 

The floating algae are considered to be solely exposed to PCBs dissolved in the water above 

the pycnocline (Cwu) whereas attached algae on the sunken vessel are assumed to be exposed 

solely to PCBs dissolved in the water below the pycnocline (Cwl). 

2.5.1.2 Tissue Concentrations 

The concentration of PCBs in an organism’s tissue is derived from Equation 95 and utilizes 

the BCF term calculated in Equation 99. First, Equation 95 is solved for the steady-state 

concentration of PCBs in tissue: 

(101) 

( )

i i

n

j

ss

i j j

i i

ss i w

i Ke G

I C

Ke G

Ku C C

+

+

+

× =

∑=1

α ,

Substituting the BCF from Equation 99 into Equation 101 we have the governing equation 

for calculation of tissue concentrations in PRAM: 

(102) [ ] ∑= ⎟

⎟

⎠

⎞

⎜

⎜

⎝

⎛

⎥

⎥

⎦

⎤

⎢

⎢

⎣

⎡

⎥

⎦

⎤ ⎢

⎣

⎡

⎟

⎟

⎠

⎞ ⎜

⎜

⎝

⎛

⎥

⎦

⎤ ⎢

⎣

⎡ +⎥

⎦

⎤ ⎢

⎣

⎡ +⎥

⎦

⎤ ⎢

⎣

⎡

×

⎥

⎥

⎦

⎤

⎢

⎢

⎣

⎡ =

⎥

⎥

⎦

⎤

⎢

⎢

⎣

⎡ n

j lp

ss PCB

i j j

i i

PCB

w i

lp

i

lp

ss PCB

i kg

mg C

d

I

d

G

d

Ke

unitless

L

mg C

kg

L BCF

kg

mg C 1

, ,

1

1 1

α

where: 

Cw,i = weighted average of all water concentrations to which organism i is 

exposed 

For Trophic Level I primary producers, who consume no other organisms (n = 0), this 

equation is a function of only the water concentration and the BCFag term presented in 

equation 100. For all other organisms, the tissue concentrations of the prey organisms they 

consume must be computed first and entered into equation 102. 

In Equation 102, it is necessary to utilize a weighted average of all PCB water concentrations 

to which an organism is exposed since most species spend their time in multiple 

compartments with different water concentrations. For example, most pelagic species spend 

time both above and below the pycnocline. The weighted average is calculated from the 

fraction of time spent in each compartment as follows: 
SECTIONTWO Model Assumptions 

SSC-SD/NEHC/URS 67 

(103) ∑ [ ] = ⎟

⎟

⎠

⎞

⎜

⎜

⎝

⎛

⎥

⎦

⎤ ⎢

⎣

⎡ = × ⎥

⎦

⎤ ⎢

⎣

⎡ n

c

PCB

c i w c

PCB

w i L

mg f unitless C

L

mg C

1

, , ,

where: 

c = compartment of unique water concentration (above pycnocline, below 

pycnocline, inside vessel or sediment pore water) 

n = number of compartments to which an organism is exposed 

f c,i = fraction of time organism i spends in compartment c

C w,c = concentration of PCBs in water of compartment c 

Since all tissue concentrations in PRAM are calculated on a lipid-normalized basis, the 

concentrations of the PCB homologs in the whole organism are calculated from equation 102 

as follows: 

(104) ( ) ⎥

⎦

⎤ ⎢

⎣

⎡ ⎥ × −

⎦

⎤ ⎢

⎣

⎡

×

⎥

⎥

⎦

⎤

⎢

⎢

⎣

⎡

⎥ =

⎦

⎤ ⎢

⎣

⎡

ww

dw

moist i

dw

lp

lp i

lp

ss PCB

lp i

ww

ss PCB

ww i kg

kg f kg

kg f kg

mg C

kg

mg C , , , 1 ,

where: 

Css ww,i = steady-state concentration of PCBs in whole organism i

Css lp,i = steady-state concentration of PCBs in lipid tissue of organism i (Css i term 

from equation 102) 

flp,i = fraction of lipids in dry tissue of organism i (see Table 7) 

fmoist,i = fraction of water in organism i (see Table 7) 

2.5.1.3 Bioaccumulation Factors 

BAFs are similar to BCFs since they both represent the ratio between the PCB concentration 

in the organism’s tissue and the PCB concentration in the surrounding water; however, the 

BAFs represent the PCBs contributed to the organism’s tissues by both the surrounding 

water and the food eaten by the organism. By including both major PCB sources, the BAF 

term serves as an indicator of the total PCB accumulation in the organism’s tissues. PRAM 

calculates BAFs directly by utilizing the lipid-based tissue concentrations from Equation 102 

and the average water concentrations from Equation 103: 
SECTIONTWO Model Assumptions 

SSC-SD/NEHC/URS 68 

(105) 

⎥

⎦

⎤ ⎢

⎣

⎡

⎥

⎥

⎦

⎤

⎢

⎢

⎣

⎡

=

⎥

⎥

⎦

⎤

⎢

⎢

⎣

⎡

L

mg C

kg

mg C

kg

L BAF

PCB

w i

lp

ss PCB

i

lp

i

,

2.5.2 Derivation of Rate Constants 

The concentrations of the various food web components described above are all based on 

either a wet-weight or lipid-weight basis. To convert to either a lipid-based or a dry weightweight basis, values presented in Table 7 are used. 

The algorithms previously described are based on thermodynamic kinetics and, as such, 

require rate constants. Specifically these rate constants include: 

• Ingestion rates and dietary assimilation efficiencies. 

• Growth rates. 

• Uptake rate constants and assimilation efficiencies for water exposure. 

• Elimination and metabolism rate constants. 

2.5.2.1 Oxygen Consumption Rates, Dietary Ingestion Rates, and Bioenergetics 

To estimate the dietary ingestion rates and growth rates for the animals within the PRAM, 

daily energy (calorie) requirements are calculated based on oxygen consumption. The total 

energy consumption, or maintenance energy budget (energy in = energy out), of an organism 

is described by the following relationship (e.g., see Jobling, 1994 and Welch, 1968): 

(106) ⎥

⎦

⎤ ⎢

⎣

⎡ +⎥

⎦

⎤ ⎢

⎣

⎡ +⎥

⎦

⎤ ⎢

⎣

⎡ +⎥

⎦

⎤ ⎢

⎣

⎡ =⎥

⎦

⎤ ⎢

⎣

⎡

d

kcal U

d

kcal F

d

kcal R

d

kcal G

d

kcal Cn

where: 

Cn = metabolic energy consumption of the organism 

G = metabolic energy usage for production (i.e., growth and reproduction) – not 

to be confused with the growth rate (G) term presented in Equations 93 – 95 

R = metabolic energy usage by tissues (derived from respiration) 

F = energy loss due to fecal excretion 
SECTIONTWO Model Assumptions 

SSC-SD/NEHC/URS 69 

U = energy loss due to urinary excretion 

d = day 

kcal = kilocalories 

The ingestion rate of an aquatic animal must meet these energy requirements to survive. 

Welch (1968) and Parsons et al. (1977) provide the energy budgets for aquatic animals [note 

that Welch (1968) combined energy loss due to fecal (F) and urinary (U) excretion as total 

excretion (EX)] as presented in Table 7. Using the energy budget, oxygen consumption rates 

can be used to estimate metabolic rates, which in turn can be used to estimate food ingestion 

rates (e.g., see USEPA, 1993). 

Oxygen consumption rates are temperature-dependent and weight-dependent in aquatic 

animals, and can be calculated using allometric regressions derived from experimental data 

(see Connolly, 1991; Altman and Dittmer, 1971; Hewett and Johnson, 1992; USEPA, 1993, 

Barber, 2003; Thurston and Gehrke, 1993; and Kline, 2004). PRAM respiration rates are 

based upon the equation presented by Connolly (1991, Equation 10), which calculates 

respiration as a metabolic rate with units of (d-1). Except for benthic foraging invertebrates, 

represented by the lobster, respiration for all invertebrate compartments in the food web is 

based solely on temperature and normalized to body weight. For these species the β1 term in 

Equation 107 is zero. All of the vertebrate compartments within the food web, and the 

benthic foraging invertebrate, are represented by a regression that includes a weight as well 

as temperature component. For these species the β1 term in Equation 107 is non-zero. The 

governing equation for respiration of all species is: 

(107) [ ]β β ( ) T [ ] C

o

αW g e

d

r 1 2 1 =⎥

⎦

⎤ ⎢

⎣

⎡

where: 

r = oxygen consumption rate [d-1] 

W = organism body wet weight in grams [g] 

T = temperature [o

C] 

α = allometric intercept 

e = the base of the natural logarithm 

β1, β2 = allometric slopes for body weight and temperature, respectively 
SECTIONTWO Model Assumptions 

SSC-SD/NEHC/URS 70 

PRAM uses direct respiration rates with units of gO2⋅kglp

-1⋅d-1; therefore, the rate provided by 

Equation 107 must be converted from a metabolic rate. The conversion is done by using the 

three factors presented in Equation 108: aoc, ac, and f. Values for aoc and ac have been 

obtained from Thomann (1989). The conversion has been calculated in PRAM as follows 

where the subscript i represents organism i: 

(108) 

⎥

⎦

⎤ ⎢

⎣

⎡

⎟

⎟

⎠

⎞

⎜

⎜

⎝

⎛

⎥×

⎦

⎤ ⎢

⎣

⎡

×⎥

⎦

⎤ ⎢

⎣

⎡

×⎥

⎦

⎤ ⎢

⎣

⎡ =

⎥

⎥

⎦

⎤

⎢

⎢

⎣

⎡

⋅

dw

lp

lp i

lp

lp

dw

oc c

lp

i

g

g f

kg

g

g

gC a

gC

gO a

d

r

kg d

gO r

,

2

2

1000

1 '

where: 

r’i = oxygen consumption rate [gO2⋅kglp

-1⋅d-1] 

gO2 = oxygen [g] 

kglp = mass of lipids in fish (kg) 

aoc = stoichiometric oxygen/carbon ratio (2.67 gO2⋅gC

-1for all species) 

ac = fraction of carbon in dry weight (0.45 gC⋅gdw

-1for all species) 

flp,i = fraction lipids in dry tissue of organism i (see Table 7) 

Table 8 and Appendix E provide allometric intercepts and slopes compiled or derived from 

the peer-reviewed scientific literature for the food web compartments. 

Rather than calculating metabolic energy consumption rates or food ingestion rates directly 

from Equation 106, they can instead be estimated from respiration metabolic rates based on 

kilocalories. The oxygen consumption rates developed from Equation 108 are converted to a 

kilocalories basis (Equation 109) using: (1) the molar volume of oxygen under average site 

conditions,29 and (2) an approximate conversion factor of 4.8 calories = 1 mL of O2

(USEPA, 1993). The overall metabolic energy consumption rate is then estimated from the 

respiration metabolic rate by dividing by the fraction of metabolism dedicated to respiration: 

 

29 At standard ambient temperature and pressure (SATP; 25°C and 1atm), the molar volume of an ideal gas 

equals 24.47L. Therefore, there are 4.087x10-5 moles per mL of an ideal gas at SATP. Given the molecular 

weight of O2 (~32g/mol), there are 0.00131g of O2 per mL O2 at SATP. 
SECTIONTWO Model Assumptions 

SSC-SD/NEHC/URS 71 

(109) 

resp i

lp

i

lp

i f

mLO

kcal

gO

mLO

kg d

gO r

kg d

kcal Cn

,

2 2

' 2 2

1

0.0048

0.00131

1

× ×

⎥

⎥

⎦

⎤

⎢

⎢

⎣

⎡

⋅ =

⎥

⎥

⎦

⎤

⎢

⎢

⎣

⎡

⋅

where: 

fresp,i = fraction of organism’s energy budget devoted to respiration (see Table 7). 

Per Welch (1968), the energy budget (Equation 106) can be thought of as 

fractions where Cn = 1 and each energy component is less than 1. 

To calculate the respective oxygen consumption rates for each of the food chain organisms, 

temperature and body weights are required. Additionally, since the goal is to first estimate 

the ingestion rates of the animals within the food chain model on a mass basis, caloric 

densities of prey organisms are required and are presented along with body weights in Table 

7. 

For example, assuming a lower water column temperature of 19.5°C, the following 

respiration rates and total energy consumption estimates are calculated for flounder: 

(110) 

( )

⎥

⎥

⎦

⎤

⎢

⎢

⎣

⎡

⋅ =

× ⋅ =

⎥

⎥

⎦

⎤

⎢

⎢

⎣

⎡

⋅ = × ×

×⎥

⎦

⎤ ⎢

⎣

⎡ =

⎥

⎥

⎦

⎤

⎢

⎢

⎣

⎡

⋅

⎥

⎦

⎤ ⎢

⎣

⎡ = = ⎥

⎦

⎤ ⎢

⎣

⎡ − ×

kg d

kcal

.

.

.

kg d

. gO

Cn

kg d

gO . .

. .

d . kg d

gO r '

d . e . d

 r

lp

lp

flounder

lp lp

flounder

. . .

flounder

82.9

0 6

0 00131

1358 0 0048

1358

0 22

1 2 67 0 45 1000 0 00249

1 0 0046(3000) 0 00249 1

2

2 2

0 24 0 067 19 5
SECTIONTWO Model Assumptions 

SSC-SD/NEHC/URS 72 

2.5.2.2 Total Energy Consumption and Ingestion Rates 

To convert energy consumption to a mass ingestion rate requires converting food calories to 

food mass: 

(111)

⎟

⎟

⎠

⎞

⎜

⎜

⎝

⎛ ×

⎥

⎥

⎦

⎤

⎢

⎢

⎣

⎡

⎥

⎥

⎦

⎤

⎢

⎢

⎣

⎡

⋅ =

⎥

⎥

⎦

⎤

⎢

⎢

⎣

⎡

⋅

AE

kg

kcal

kg d

kcal Cn

kg d

kg

I

lp

lp

lp

lp

λ

where: 

I = mass ingestion rate (i.e., [kglp(food)⋅kglp(body)

-1⋅d-1]) 

Cn = caloric ingestion rate 

λ = caloric density of food item 

AE = assimilation efficiency or fraction metabolizable calories of food item 

To estimate the caloric content of sediment and suspended sediment within the system and 

consumed by filter feeders and other detritivores, the composition of the sediment and its 

edible fraction (detritus) need to be considered. In littoral zones, flowing rivers, and 

wetlands, detritus is primarily composed of vascular plant material, while in estuaries, bays, 

and the open ocean, detritus is derived largely from algae (e.g., see Mason and Varnell, 1996; 

Valiela, 1995; Parsons et al., 1977). Caloric content of salt marsh bulrush ranges from 

3.2 kcal⋅g-dry weight-1 to 4.8 kcal⋅g-dry weight-1 (USGS, 2002), which compares well with 

the aquatic vascular plant caloric contents as reported by USEPA (1993), 4.0 to 4.3 kcal⋅gdry weight-1. Algae are reported to have a much lower caloric content (2.36 kcal⋅g-dry 

weight-1; USEPA, 1993). For the artificial reefs, PRAM assumes that the detritus present is 

derived from algae. According to Mason and Varnell (1996), the half-life for the 

decomposition of plant material in a salt marsh ranges from 18 to 350 days depending on the 

local conditions. To increase the probability of overestimating exposure, the detritus present 

is considered to be at 50% of its original caloric content as algae or 1.18 kcal⋅g-dry weight-1

(1,180 kcal⋅kg-dry weight-1). 

Given a dry-weight lipid content for algae of 0.103 kg-lipid⋅kg-dry weight-1 (Table 7), the 

caloric content of sediment-associated detritus within the PRAM is approximately 

11,456 kcal⋅kg-lipid-1 (1,180 kcal⋅kg-dry weight-1 ÷0.103 kg-lipid⋅kg-dry weight-1). It is 

further assumed that one-kilogram of lipid is equivalent to one-kilogram of organic carbon 
SECTIONTWO Model Assumptions 

SSC-SD/NEHC/URS 73 

(Thomann et al., 1992 and others); thus the caloric content of organic carbon in the sediment 

is estimated to be 11,456 kcal⋅kg-organic carbon-1. 

On a lipid basis, total ingestion is expressed by denoting each dietary preference as a fraction 

of the total diet as fdiet (decimal fraction) as follows: 

(112) ∑ ∑ = =

⎟

⎟

⎟

⎟

⎟

⎟

⎠

⎞

⎜

⎜

⎜

⎜

⎜

⎜

⎝

⎛

×

⎥

⎥

⎦

⎤

⎢

⎢

⎣

⎡

×

⎥

⎥

⎦

⎤

⎢

⎢

⎣

⎡

⋅ =

⎥

⎥

⎦

⎤

⎢

⎢

⎣

⎡

⋅ =

n

j

j

lp

j

diet i, j lpi n

j lp

lp

i i j

AE

kg

kcal

f kg d

kcal Cn

kg d

kg

I I

1 1

,

λ

where: 

Ii,j = mass ingestion rate of dietary item j by organism i (i.e., [kglp(food) ⋅kglp(body 

weight)

 -1⋅d-1]) 

Cni = caloric ingestion rate of organism i

fdiet i,j = fraction of dietary item j in i diet 

λj = caloric density of dietary item j

n = number of dietary items in i diet 

j = specific dietary item j

AEj = assimilation efficiency or fraction metabolizable calories of dietary item j

Using the flounder diet as an example, 2% is bottom sediments, 20% is polychaete, 20% is 

nematode, and 58% is lobster. Furthermore, using the caloric densities derived from Table 7 

data, the caloric density of sediments as calculated above, the assimilation efficiencies 

(Fraction Metabolizable Energy from Gross) given in Table 7, and the flounder caloric 

ingestion rate of 82.9 [kcal ⋅kglp

-1⋅d-1] from Equation 110; we calculate the flounder 

ingestion rates as follows: 
SECTIONTWO Model Assumptions 

SSC-SD/NEHC/URS 74 

(113) ⎥

⎥

⎦

⎤

⎢

⎢

⎣

⎡

⋅ =

×

× ⋅ = kg d

kg

kg

kcal

kg d

kcal

lp

oc

oc

lp

fl,oc 0.000241

0.60 11,456

0.02 82.9

I

⎥

⎥

⎦

⎤

⎢

⎢

⎣

⎡

⋅ =

×

× ⋅ = kg d

kg

kg

kcal

kg d

kcal

lp

lp

lp

lp

fl,nt 0.000332

0.65 76,923

0.20 82.9

I 

⎥

⎥

⎦

⎤

⎢

⎢

⎣

⎡

⋅ =

×

× ⋅ = kg d

kg

kg

kcal

kg d

kcal

lp

lp

oc

lp

fl,pc 0.000332

0.65 76,923

0.20 82.9

I

⎥

⎥

⎦

⎤

⎢

⎢

⎣

⎡

⋅ =

×

× ⋅ = kg d

kg

kg

kcal

kg d

kcal

lp

lp

lp

lp

fl,lb 0.000252

0.65 29,412

0.58 82.9

I 

2.5.2.3 Assimilation Efficiencies Across Gastrointestinal Tracts 

The assimilation efficiency (α) used in the governing equation (Equation 95) is specific to 

the chemical being assimilated and is not necessarily directly related to the assimilation 

efficiency of foodstuffs30 (e.g., see Gobas et al., 1988; Endicott et al., 1991; Connolly, 1991; 

and Fisk et al., 1998). All of these authors have attempted to develop a relationship between 

a chemical octanol-to-water partition coefficient (Kow) and the assimilation of the chemical 

across the gastrointestinal tract. Based on data collected by Gobas et al. (1988) for various 

hydrophobic organic compounds, the following non-linear regression was developed (Gobas 

et. al, 1988; Equation 2): 

(114) 2.3 8 5.3 10 1 + − α = × Kow

 

30 Matrix effects associated with the assimilation of chemicals have been identified, but the process of actually 

crossing the gastrointestinal tract is believed to be most associated with lipidophilicity (see Spacie and 

Hamelink, 1995; Kleinow and Goodrich, 1993). 
SECTIONTWO Model Assumptions 

SSC-SD/NEHC/URS 75 

where: 

α = assimilation efficiency across gastro-intestinal tract (fraction) 

Kow = octanol-to-water partition coefficient [L⋅kg-1] 

Endicott et al. (1991, Equations 38a, 38b, and 38c) found the following relationships based 

on a review of the available data collected from the scientific literature, again hydrophobic 

organic compounds. Where the chemical log10Kow was below 6, α was equal to 0.90. For 

log10Kow’s between 6 and 6.6 the following relationship was described: 

(115) ( )2

10 0.8409 log 10 37.9 11.216 log α = − Kow + Kow

For chemicals with a log10Kow greater than 6.6, Endicott et al. (1991) found that α was equal 

to 0.50. The degree of fit of the data and the relationships described by Endicott et al. (1991) 

is graphically presented but not extensively discussed in the manuscript. It is notable that no 

chemicals with a log10Kow below 4 appear to have been evaluated by Endicott et al. Further, 

the fit associated with chemicals with a log10Kow greater than 7 are very poor. 

Fisk et al. (1998) similarly attempted to fit the relationship between Kow and growth-adjusted 

α through regression analysis. These investigators recognized that assimilation efficiency 

data collected from the scientific literature might be affected by variable experimental 

designs, especially in consideration of foodstuff types, feeding rates, and complications 

associated with potential water exposures in addition to exposure through the food. These 

investigators used data collected from their experimentation only to develop a regression 

between Kow and dietary assimilation. The form of the regression developed was parabolic 

with the form: 

(116) log 1.8 log (0.08log )

2

10 α = − + 10 Kow − 10 Kow

This regression was statistically significant (p=0.004), but the explained variation was low 

(r2

 = 0.53 where only 53% of the variation of α is explained by the regression). 

It is clear that the methods and results described above are very different. It is notable that 

the efficiencies reported by Fisk et al. (1998) were specific to dietary exposures only, while 

many of the studies used by Endicott et al. (1991) relied on field observations. Figure 9 

presents these estimation regressions across a range of Kows. The significant difference that 
SECTIONTWO Model Assumptions 

SSC-SD/NEHC/URS 76 

lies within the log10Kow range from 5 to 7 is particularly troublesome. This range 

encompasses the majority of the bioaccumulative PCBs at issue within the PRAM. 

Review of the raw data suggested that the form of the relationship between Kow and α is 

perhaps best described as a parabolic function. A parabolic function was calibrated such that 

virtually all of the reported assimilation efficiencies fell below the predicted values. This 

probably tends to result in overestimates of exposure. The resultant algorithm is presented 

below and graphically compared to the observed values reported by Gobas et al. (1988), 

Thomann (1989), and Fisk et al. (1998) in Figure 9. 

(117) 100

10

2 −1.8+1.08logKow−0.08logKow

α =

2.5.2.4 Uptake Rate Constants and Assimilation Efficiencies Across Respiratory Tissues 

The uptake rate (Kui) of a PCB can be calculated based on the respiration of the organism 

(r’) and the relative assimilation efficiency between a chemical and oxygen (E) across 

respiratory tissue (e.g., see Thomann, 1989; Connolly, 1991): 

(118)

⎥

⎦

⎤ ⎢

⎣

⎡

⎥

⎥

⎦

⎤

⎢

⎢

⎣

⎡

⋅ = ×

⎥

⎥

⎦

⎤

⎢

⎢

⎣

⎡

⋅

L

gO C

kg d

gO r

E

kg d

L Ku

O

lp

i

lp

i

2

' 2

2

where: 

Kui = uptake rate constant for water in organism i

E = ratio between the assimilation efficiency for a chemical across respiratory 

tissue over the assimilation efficiency for oxygen across respiratory tissue 

(dimensionless) 

ri’ = oxygen consumption rate 

CO2 = dissolved oxygen concentration in water 

The ratio between the assimilation efficiency for oxygen and that for a chemical has been 

related to the octanol-water partition coefficient (Kow) of the chemical (Thomann, 1989, 

Equation 22), such that E can be derived from the chemical log10Kow and the body weight 

(wet weight) range of the organism(s). For chemicals with a log10Kow between 2 and 5 and 
SECTIONTWO Model Assumptions 

SSC-SD/NEHC/URS 77 

organisms weighing less than 100 grams, E can be calculated using the following 

relationship (Thomann, 1989): 

(119) log10 E = −2.6 + 0.5log10 Kow

Where the log10Kow is between 5 and 6 and the organism is less than 100 grams in body 

weight, E is equal to 0.80. Where the log10Kow is between 6 and 10, E can be calculated as 

follows: 

(120) log10 E = 2.9 − 0.5log10 Kow

A different set of relationships between log10Kow and E apply for organisms greater than 

100 grams in body weight (Thomann, 1989). Where log10Kow is between 2 and 3: 

(121) log10 E = −1.5 + 0.4log10 Kow

Where the log10Kow is between 3 and 6, E is equal to 0.50, and where the log10Kow is between 

6 and 10: 

(122) log10 E = −1.2 + 0.25 log10 Kow

This approach to estimate the efficiency of the transfers of PCBs across respiratory tissues 

for invertebrates, however, is not the most accurate and theoretically appropriate for fish 

(Barber, 2003). Barber (2003) suggests a correction to the uptake rate that is appropriate for 

fish and has been incorporated into the PRAM: 

(123)

1.048

100 K

1400W[g ww] K 0.343

g

cm

ow

ow 0.4

ww

3

⎟

⎟

⎠

⎞

⎜

⎜

⎝

⎛

+

− = ×

⎥

⎥

⎦

⎤

⎢

⎢

⎣

⎡

⋅

− −

d

Ku fish i

where: 

Kufish-i = uptake rate constant for water in fish i

W = fish body weight in grams wet weight (ww) 

Unit conversions of Barber’s uptake rate are accomplished in PRAM as follows: 
SECTIONTWO Model Assumptions 

SSC-SD/NEHC/URS 78 

(124)

( )

⎟

⎟

⎠

⎞

⎜

⎜

⎝

⎛

×⎟

⎟

⎠

⎞

⎜

⎜

⎝

⎛

×

⎟

⎟

⎠

⎞

⎜

⎜

⎝

⎛

×

⎟

⎟

⎠

⎞

⎜

⎜

⎝

⎛

− ×

⎥

⎥

⎦

⎤

⎢

⎢

⎣

⎡

⋅ − =

⎥

⎥

⎦

⎤

⎢

⎢

⎣

⎡

⋅ −

3 1000

1 1000

g

dw g

f

1

dw g

ww g

1 f

1

g d

3 cm Ku

d lp kg

L Ku

cm

L

lp kg

lp g

ww moist,i lp,i lp fish i fish i

2.5.2.5 Depuration Rates (Elimination and Metabolism) 

Depuration is the sum of the loss due to metabolism and/or excretion of the PCB. When 

assuming no growth, the lipid-based elimination rate (Kei) can be related to the Kow

(Thomann, 1989; also Connolly, 1991) and the uptake rate constant such that: 

(125) Kow

Ku

kg d

kg Ke i

lp

PCB

i =

⎥

⎥

⎦

⎤

⎢

⎢

⎣

⎡

⋅

This excretion rate does not account for any metabolism of the chemical by the animal. For 

certain PCBs (e.g., the heavy PCB series such as hepta-CB, octa-CB, etc.), such an 

assumption is valid, but for less chlorinated forms (e.g., mono-CBs, di-CBS, and tri-CBs), 

this assumption is not valid. To account for at least a minimal metabolism of the PCBs, the 

following Kow – elimination (Ke) regression based on larval saltwater fish was evaluated 

(obtained from Petersen and Kristensen, 1998, Table 4): 

(126) Kow

d

Ke 10 10 3.25 0.66 log 1 log = − × ⎥

⎦

⎤ ⎢

⎣

⎡

The metabolic activities of larval fish are quite limited (Peterson and Kristensen, 1998) and 

the modeled metabolism would be underestimated for many of the more juvenile and adult 

forms. 

A similar approach was taken where additional elimination rate constants, as obtained from 

the literature, were evaluated in the context of the algorithm obtained from Peterson and 

Kristensen (1998) to assure that the algorithm produces conservative estimates. A new 

regression of elimination rates (Figure 10) reported by Peterson and Kristensen (1998), 

Thomann (1989) and Fisk et al. (1998) result in slightly lower predicted Ke than that of 

Petersen and Kristensen (1998): 
SECTIONTWO Model Assumptions 

SSC-SD/NEHC/URS 79 

(127) Kow

d

Ke 10 10 1.065 0.4131 log 1 log = − × ⎥

⎦

⎤ ⎢

⎣

⎡

In spite of the metabolism that occurs in many species for the less chlorinated PCBs, the 

most conservative approach to modeling bioaccumulation in PRAM is to ignore such 

metabolism in all species. Gobas and Mackay (1987) developed estimates of several 

bioenergetic parameters by analyzing data from several other researchers. For the estimation 

of elimination rates, exclusive of metabolism, Gobas and Mackay derived the following 

relationship between Kow and Kei: 

(128) 0.00089 0.075 1 = +

⎥

⎥

⎦

⎤

⎢

⎢

⎣

⎡

⋅

Kow

kg d

kg Ke

lp

PCB

i

Gobas and Mackay compared this equation to experimental data obtained by other 

researchers for PCBs in fish and found that it fit the data well. Although it does not include 

any metabolism of the PCBs, equation 128 has been used in PRAM to estimate depuration 

rates. 

2.5.2.6 Derivation of Growth Rates from Bioenergetic Budget 

To estimate the temperature-related growth rate of an organism (G), the bioenergetic budgets 

of the organism are once again used. The growth rate (G) is calculated from the relationship 

between Cn and G (assuming G includes reproduction – see Welch, 1968) and the caloric 

density (λ) of the organism: 

(129)

⎥

⎥

⎦

⎤

⎢

⎢

⎣

⎡

⎟

⎟

⎠

⎞

⎜

⎜

⎝

⎛

×

⎥

⎥

⎦

⎤

⎢

⎢

⎣

⎡

⋅ =

⎥

⎥

⎦

⎤

⎢

⎢

⎣

⎡

⋅

lp

i

grow i

lp

i

i

kg

kcal

f kg d

kcal Cn

G

λ kg d

kg ,

lp

lp

To reiterate the energy budget for flounder, 20% is used for production (growth and 

reproduction – Table 7). Thus, the flounder growth rate, for example, is calculated as 

follows: 
SECTIONTWO Model Assumptions 

SSC-SD/NEHC/URS 80 

(130) ⎥

⎦

⎤ ⎢

⎣

⎡ = ×

× ⋅ = −

d

kg

kcal

kg d

kcal

G

lp

lp 1 7.44 10 22,272

0.20 82.9

4

2.6 SENSITIVITY ANALYSES 

The purpose of a sensitivity analysis is to demonstrate a model’s responses to alterations in 

uncertain input parameters. A sensitivity analysis provides the data necessary to rank the 

input parameters according to their influence on the model results. By ranking the 

parameters, one can identify those variables that require further investigation and define 

those variables to be used in an uncertainty analysis. Such a sensitivity analysis was 

performed on earlier versions of PRAM. 

2.6.1 PRAM Version 1.1 Testing 

Based on the sensitivity testing performed in 2001 on an earlier version of PRAM, which 

predated the review of the model, the parameters that were among the most sensitive for all 

types of fish were: 

• Log10Kow (log of the octanol to water partitioning coefficient) 

• Log10Koc (log of the organic carbon to water partitioning coefficient) 

• Zone of influence - multiplier 

• Sediment fraction organic carbon 

Overall, the parameter groups that seemed to be the most sensitive were PCB inputs and 

environmental inputs. 

2.6.2 PRAM Version 1.2 Testing 

A more detailed sensitivity analysis was conducted for Version 1.2 of PRAM. PRAM 

Version 1.2 included refinements on several model variables, but the greatest improvement 

was the incorporation of additional exposure associated with the interior of the vessel. This 

version of PRAM contained 82 parameters: 
SECTIONTWO Model Assumptions 

SSC-SD/NEHC/URS 81 

• 18 human health exposure assumptions, oral reference doses, and cancer slope 

factors (Parameters 1 to 18 of the model); 

• 17 bio-energetic inputs and dietary preferences for representative fish and 

shellfish species (Parameters 66 to 82 of the model); and 

• 47 physical characteristics, PCB chemical properties, and biological 

characteristics (Parameters 19 to 65 of the model). 

The first 18 parameters were not tested in the sensitivity analysis. A baseline PRAM 

scenario was designated as a benchmark. During the sensitivity analysis, each of the 

remaining parameters was varied from their respective baseline values one at a time over a 

range of values representative of the parameter. For each sensitivity scenario, the reasonable 

maximum exposure (RME) and central tendency exposure (CTE) for both cancer and noncancer risks were calculated. This sensitivity analysis was conducted in a three-phased 

approach: 

• Physical/Chemical Inputs. Sensitivity of calculated risk/hazard to each physical and 

chemical model input (Parameters 19 to 65) was evaluated in the first phase. Results 

were ranked for each species using a sensitivity coefficient: 

( ) P P

R

S

∂ /

∂ =

where: 

S is the normalized sensitivity coefficient which is a measure of the average 

change in the predicted variable per fraction change in the input variable. The 

higher the value of S, the more sensitive the input parameter. 

∂ R is the difference in the predicted risk between the base case and sensitivity 

case 

∂ P is the change in the input parameter between the base case and sensitivity case 

P is the base input parameter value 

Results were also evaluated based on a percent change in model-projected 

carcinogenic risk and non-carcinogenic hazard. 
SECTIONTWO Model Assumptions 

SSC-SD/NEHC/URS 82 

• Bio-energetics/Food web. Sensitivity of calculated risk/hazard to each bio-energetic 

input and dietary preference (Parameters 66 to 82) was evaluated in the second phase. 

These parameters consist of a series of dependent variables that had to be considered 

separately from the independent variables evaluated in the first phase. Results were 

evaluated for each type of fish using percent difference in projected carcinogenic risk 

or non-carcinogenic hazard: 

R

R

PercentDifference

∂ =

where: 

∂ R is the change in the risk from the base case to sensitivity case 

R is the base model risk value 

• PCB-Laden Materials. Sensitivity of calculated risk/hazard to changes in the 

amount of PCB-laden material on board the vessel was evaluated in the third phase. 

Both the amount of material and the PCB release rates for each type of material were 

evaluated. Results were evaluated using a percent difference ranking similar to that 

employed in the second phase. 

The sensitivity analysis conducted on PRAM Version 1.2 qualitatively ranked the degree of 

impact on model results stemming from relatively equivalent variations in each of the 

parameters evaluated. The following parameters were identified as having the greatest 

impact on the PRAM-calculated risk/hazards: 

• Zone of influence 

• Partitioning coefficients Kow and Koc 

• Fraction of organic carbon in sediment and suspended solids 

• Active sediment depth 

• Biodegradation rate constants (PRAM default is for no biodegradation) 

• Release rate of PCBs from PCB-laden materials 

The results from the sensitivity analysis conducted on PRAM Version 1.2 suggested a greater 

propensity to decrease rather than increase risk/hazard when looking at the range of potential 

inputs. This indicates that the default values in the baseline case of the model probably 

overestimate exposure. However, it is also important to note that multiple organisms in the 

food chain are each affected by variables associated with both bio-energetics and dietary 
SECTIONTWO Model Assumptions 

SSC-SD/NEHC/URS 83 

preferences. Some additivity among food chain components may occur, particularly to 

higher trophic level species. Potential additivity was not represented in the PRAM Version 

1.2 sensitivity analysis. 

The analysis concerning the amount of PCB-containing material indicates a link to the 

release rate of the material. If the individual amount of material is changed, the risk is 

affected by a percentage directly related to the release rate. The greatest change in 

risk/hazards stemming from PCB-containing materials involved felt gasket material. 

2.6.3 PRAM Version 1.4c Testing 

PRAM Version 1.4c is an enhanced version of PRAM Version 1.2. Several significant 

enhancements have been made to the model; however, the basic governing equations within 

the model itself have not changed. Therefore, knowledge gained from the extensive 

sensitivity analysis testing performed on previous versions of PRAM has been used to design 

the sensitivity analysis testing program for PRAM Version 1.4c. Two categories of input 

parameters were considered for the PRAM Version 1.4c sensitivity analysis: 

• Abiotic Inputs. This category includes the physical/chemical inputs and the 

PCB-laden materials factors that were evaluated during the PRAM Version 

1.2 sensitivity analyses. 

• Bio-energetics/Food web. This category includes the same biological 

parameters that were evaluated during the PRAM Version 1.2 sensitivity 

analyses. 

Abiotic Sensitivity Analysis 

Variations in the abiotic input parameters in PRAM Version 1.4c are expected to produce 

relatively similar changes in model results as occurred during the sensitivity analyses of the 

earlier versions of PRAM, particularly Version 1.2. Given that variation in most abiotic 

parameters decreased, rather than increased, the risk/hazard in PRAM Version 1.2, the 

sensitivity analysis for PRAM Version 1.4c focused on the model parameter that exerted the 

greatest effect on the PCB concentrations in the water, the Zone of Influence (ZOI). The 

ZOI was identified as the parameter having the greatest impact on model results in the 

sensitivity analyses conducted for PRAM Version 1.2 and one of the highest for PRAM 

Version 1.1. Also, selecting the ZOI is probably the most subjective parameter input entered 
SECTIONTWO Model Assumptions 

SSC-SD/NEHC/URS 84 

into the PRAM because the ZOI artificially establishes limits within which PCB 

concentrations are presumed to affect the biota. For these reasons, the sensitivity analysis for 

abiotic parameters was limited to the ZOI. 

The concept of the ZOI is explained graphically in Figure 13. The ZOI represents a volume 

established by extending the area of a horizontal ellipse vertically through the various layers 

or columns – sediment, lower water column, upper water column, and air – where the model 

results will be calculated. The vessel emitting the PCBs is centered within this horizontal 

ellipse resting on top of the sediment at the bottom of the lower water column (LWC). The 

resulting volume of the elliptical cylinder is determined by the area of the horizontal ellipse. 

The minimum volume ZOI is determined by applying the “footprint” or area of the vessel, 

assuming it is resting upright on the sea floor. Therefore, the minimum ZOI, or ZOI = 1, 

represents an ellipse with the area created by multiplying the length and the width of the 

vessel. The minimum ZOI must encompass the maximum horizontal area of the vessel for 

all of the PCB source to be included within the ZOI. Larger ZOI designations are referenced 

to the number of multiples of the maximum horizontal area of the vessel included within the 

ellipse forming the elliptical cylinder. Therefore, a ZOI = 2 means that the area of the 

horizontal ellipse forming the elliptical cylinder is twice the maximum horizontal vessel area; 

ZOI = 3 means the area is three times the vessel area; etc. The axes of the horizontal ellipse 

are expanded equally to produce the larger areas as the ZOI expands as shown in Figure 13. 

As the ZOI expands, the resulting PCB concentrations in the various columns decline 

because the mass entering the system from the source (the vessel) remains constant while the 

volume of the elliptical cylinder increases. The impact on PCB concentrations of varying the 

ZOI is displayed in the following graph. 
SECTIONTWO Model Assumptions 

SSC-SD/NEHC/URS 85 

ZOI Sensitivity Analysis

0.00

0.20

0.40

0.60

0.80

1.00

0

10

20

30

40

50

60

70

80

90

100

ZOI

Ratio of Water Concentratio

n

in LWC at Varying ZOI

Ratio of Lower Water Column

Concentration at ZOI >1 to

Lower Water Column

Concentration at ZOI = 1

The horizontal or x-axis represents the ZOI increasing from a value of 1 which represents the 

minimum ZOI. The vertical or y-axis represents the ratio of the PCB concentration in the 

LWC at the given ZOI value divided by the maximum PCB concentration in the LWC that 

occurs when the ZOI = 1. The ratio represents the fractional amount of the original PCB 

concentration remaining as the ZOI increases. Subtracting the ratio from one provides the 

fractional amount that the original PCB concentration has decreased as the ZOI increases. 

The applicable percentages can be determined by multiplying the respective fractions by 100. 

As displayed in the graph, most of the reduction in PCB concentrations occurs when the ZOI 

expands from 1 to 10, then the rate of PCB concentration reduction diminishes significantly 

as the ZOI increases to 100. At a ZOI = 1.5, the resulting ratio is approximately 0.76 

indicating the original PCB concentration has decreased by about 24% when the base of the 

ZOI has been expanded by just 50%. When the ZOI = 3, the ratio is close to 0.50 showing 

that approximately 50% of the original PCB concentration is eliminated by expanding the 

base of the ZOI to encompass three times the maximum horizontal area of the vessel. 

Bio-energetics/Food web Sensitivity Analysis 
SECTIONTWO Model Assumptions 

SSC-SD/NEHC/URS 86 

Five parameters involving bio-energetics and/or food web considerations were examined 

during the biological sensitivity analysis. These five parameters include: 

• Octanol to water partition coefficient, Kow; 

• Respiration rate regression parameter β2; 

• Depuration rate, Ke; 

• Growth rate, G; and 

• Assimilation efficiency, α. 

Kow was identified as one of the parameters having great impact on the PRAM-calculated 

risks/hazards during sensitivity analyses of the earlier versions of PRAM. The respiration 

rate was investigated because it directly influences the degree to which aquatic organisms 

take up PCB constituents from other than dietary sources. The depuration rate and the 

growth rate were selected for sensitivity analyses because of their significant impact on the 

Biological Concentration Factor (BCF). The BCF represents the tendency of species to take 

up PCB constituents from factors other than diet. Similarly, the assimilation efficiency was 

chosen for sensitivity analysis due to its influence on the Biological Accumulation Factor 

(BAF). The BAF represents the tendency of species to take up PCB constituents from all 

sources, including diet. 

Octanol-to-water partition coefficient, Kow. The Kow represents the affinity PCB 

constituents have for entering lipids (fat tissue) in preference to remaining dissolved in water. 

The higher the Kow is, the more PCB constituents tend to be taken up by biota rather than 

remaining dissolved in the surrounding water. Each PCB homolog group has a specific Kow

value as indicated in Table 2. A sensitivity analysis was conducted by varying the Kow from 

the base case (Kow x 1) by decreasing the value to half the base case (Kow x 0.5) and also by 

doubling the value (Kow x 2). The resulting percent difference in Central Tendency Exposure 

(CTE) risk from the base case was determined. The percent differences for cancer risk and 

non-cancer hazard were the same for the species included in the sensitivity analysis. The 

results for this sensitivity analysis are shown in the following chart: 

CTE RISK ESTIMATES 

Species 

Kow x 0.5 

Percent Difference 

Kow x 2 

Percent Difference 

Benthic fish TL-IV (flounder) -23.0 +10.6 
SECTIONTWO Model Assumptions 

SSC-SD/NEHC/URS 87 

Benthic shellfish TL-III (lobster) -7.4 +3.8 

Pelagic fish TL-IV (jack) -33.1 +25.8 

Reef fish TL-IV (grouper) -43.1 +43.2 

Reef fish TL-III (triggerfish) -27.6 +17.8 

Reef shellfish TL-III (crab) -12.7 +1.9 

As depicted in the chart, reducing the Kow values to half the base case values for the species 

represented reduced the resulting PCB risks/hazards by 7% to 43%. Similarly, doubling the 

Kow values from the base case increased the resulting PCB risks/hazards by 2% to 43%. 

Considering that the higher trophic levels (TL-IV) tend to consume the lower trophic levels 

(TL-III), particularly within a specific community of biota (benthic, pelagic, or reef), the 

percent differences in risks stemming from variations in the Kow values generally are larger 

in the higher trophic species. 

Respiration rate regression parameter, β2. The respiration rate represents the amount of 

oxygen taken up by a particular aquatic species per mass of lipids content within a single 

day. The respiration rate for a given species is determined by regression analysis on 

laboratory measurements of actual oxygen consumption. Depending on the species, this 

regression analysis yields either two or three coefficients that can be used with an 

exponential equation to estimate the respiration rate for the species as a function of 

temperature. Of these coefficients, the parameter designated as β2 has the most significant 

impact on the calculation because it is multiplied by the exponential term in the equation. 

Therefore, the higher the value of β2 is, the higher the respiration rate is for that particular 

species at a given temperature. As the respiration rate increases, the amount of PCBs taken 

up by the aquatic organism also increases. A sensitivity analysis was conducted by varying 

the β2 value from the base case (β2 x 1) by decreasing the value to half the base case (β2 x 

0.5) and also by doubling the value (β2 x 2). The resulting percent difference in CTE risk 

from the base case was determined. The percent differences for cancer risk and non-cancer 

hazard were the same for the species included in the sensitivity analysis. The results for this 

sensitivity analysis are shown in the following chart: 

CTE RISK ESTIMATES 

Species 

β2 x 0.5 

Percent Difference 

β2 x 2 

Percent Difference 

Benthic fish TL-IV (flounder) -31.1 +55.4 

Benthic shellfish TL-III (lobster) -20.0 +25.5 

Pelagic fish TL-IV (jack) -58.4 +149.4 
SECTIONTWO Model Assumptions 

SSC-SD/NEHC/URS 88 

Reef fish TL-IV (grouper) -41.0 +140.7 

Reef fish TL-III (triggerfish) -25.4 +66.6 

Reef shellfish TL-III (crab) -28.7 +55.4 

As depicted in the chart, reducing the β2 values to half the base case values for the species 

represented decreased the resulting PCB risks/hazards by 20% to 58%. Similarly, doubling 

the β2 values from the base case increased the resulting PCB risks/hazards by 25% to 149%. 

Considering that the higher trophic levels (TL-IV) tend to consume the lower trophic levels 

(TL-III), particularly within a specific community of biota (benthic, pelagic, or reef), the 

percent differences in risks stemming from variations in the β2 values generally are larger in 

the higher trophic species. 

The corresponding respiration rates [gO2⋅kglipid

-1⋅d-1] varied from -45% to -76% when β2 

values were reduced to half the base case values. When β2 values were doubled from the 

base case, the resulting respiration rates varied from +229% to +1,689%. 

Depuration rate, Ke. The depuration rate represents the rate at which PCB constituents 

entering an aquatic species are eliminated from the biota rather than taken up in lipids or fat 

tissue. The higher the depuration rate is, the lower the BCF is for that particular species, and 

the resulting PCB concentrations in the biota are lower. A sensitivity analysis was conducted 

by varying the depuration rate from the base case (Depuration x 1) by decreasing the value to 

half the base case (Depuration x 0.5) and also by doubling the value (Depuration x 2). The 

resulting percent difference in CTE risk from the base case was determined. The percent 

differences for cancer risk and non-cancer hazard were the same for the species included in 

the sensitivity analysis. The results for this sensitivity analysis are shown in the following 

chart: 

CTE RISK ESTIMATES 

Species 

Depuration x 0.5 

Percent Difference 

Depuration x 2 

Percent Difference 

Benthic fish TL-IV (flounder) +35.9 -34.4 

Benthic shellfish TL-III (lobster) +16.6 -19.6 

Pelagic fish TL-IV (jack) +57.1 -43.4 

Reef fish TL-IV (grouper) +76.1 -52.0 

Reef fish TL-III (triggerfish) +44.6 -38.8 
SECTIONTWO Model Assumptions 

SSC-SD/NEHC/URS 89 

CTE RISK ESTIMATES 

Species 

Depuration x 0.5 

Percent Difference 

Depuration x 2 

Percent Difference 

Reef shellfish TL-III (crab) +27.5 -27.2 

As depicted in the chart, reducing the depuration rates to half the base case values for the 

species represented increased the resulting PCB risks/hazards by 17% to 76%. Similarly, 

doubling the depuration rates from the base case decreased the resulting PCB risks/hazards 

by 20% to 52%. Considering that the higher trophic levels (TL-IV) tend to consume the 

lower trophic levels (TL-III), particularly within a specific community of biota (benthic, 

pelagic, or reef), the percent differences in risks stemming from variations in the depuration 

rates generally are larger in the higher trophic species. 

The corresponding water BCF values varied from +1% to +16% when depuration rates were 

reduced to half the base case values. When depuration rates were doubled from the base 

case, the resulting water BCF values varied from -2% to -22%. 

Growth rate, G. The growth rate is the rate at which aquatic species increase in mass as 

they age. The higher the growth rate is, the lower the BCF is for that particular species, and 

the resulting PCB concentrations in the biota are lower. A sensitivity analysis was conducted 

by varying the growth rate from the base case (Growth x 1) by decreasing the value to half 

the base case (Growth x 0.5) and also by doubling the value (Growth x 2). The resulting 

percent difference in CTE risk from the base case was determined. The percent differences 

for cancer risk and non-cancer hazard were the same for the species included in the 

sensitivity analysis. The results for this sensitivity analysis are shown in the following chart: 

CTE RISK ESTIMATES 

Species 

Growth x 0.5 

Percent Difference 

Growth x 2 

Percent Difference 

Benthic fish TL-IV (flounder) +526.4 -77.8 

Benthic shellfish TL-III (lobster) +302.1 -66.5 

Pelagic fish TL-IV (jack) +294.6 -73.2 

Reef fish TL-IV (grouper) +302.3 -72.5 

Reef fish TL-III (triggerfish) +206.5 -66.0 

Reef shellfish TL-III (crab) +124.2 -56.5 

As depicted in the chart, reducing the growth rates to half the base case values for the species 

represented increased the resulting PCB risks/hazards by 124% to 526%. Similarly, doubling 

the growth rates from the base case decreased the resulting PCB risks/hazards by 57% to 

78%. Considering that the higher trophic levels (TL-IV) tend to consume the lower trophic 

levels (TL-III), particularly within a specific community of biota (benthic, pelagic, or reef), 
SECTIONTWO Model Assumptions 

SSC-SD/NEHC/URS 90 

the percent differences in risks stemming from variations in the growth rates generally are 

larger in the higher trophic species. 

The corresponding water BCF values varied from +57% to +96% when growth rates were 

reduced to half the base case values. When growth rates were doubled from the base case, 

the resulting water BCF values varied from -42% to -49%. 

Assimilation efficiency. The assimilation efficiency represents the degree to which various 

species take up PCB constituents from their diets. As the assimilation efficiency increases, 

the more PCB constituents magnify in the food chain. This results in higher PCB 

concentrations in higher trophic species. The base case represented close to the maximum 

assimilation efficiency that could be expected for the species represented. Some of the 

species could not have their assimilation values doubled without exceeding 100%. 

Therefore, a sensitivity analysis was conducted by decreasing the assimilation efficiency first 

by 50% (Assimilation x 0.5) from the base case (Assimilation x 1) and then by 75% 

(Assimilation x 0.25). The resulting percent difference in CTE risk from the base case was 

determined. The percent differences for cancer risk and non-cancer hazard were the same for 

the species included in the sensitivity analysis. The results for this sensitivity analysis are 

shown in the following chart: 

CTE RISK ESTIMATES 

Species 

Assimilation x 0.5 

Percent Difference 

Assimilation x 0.25 

Percent Difference 

Benthic fish TL-IV (flounder) -67.7 -84.2 

Benthic shellfish TL-III (lobster) -42.8 -56.5 

Pelagic fish TL-IV (jack) -69.3 -84.9 

Reef fish TL-IV (grouper) -66.2 -81.7 

Reef fish TL-III (triggerfish) -51.0 -68.8 

Reef shellfish TL-III (crab) -29.8 -44.5 

As depicted in the chart, reducing the assimilation efficiencies to half the base case values for 

the species represented decreased the resulting PCB risks/hazards by 30% to 69%. Similarly, 

decreasing the assimilation efficiencies to 25% of the base case decreased the resulting PCB 

risks/hazards by 44% to 85%. Considering that the higher trophic levels (TL-IV) tend to 

consume the lower trophic levels (TL-III), particularly within a specific community of biota 

(benthic, pelagic, or reef), the percent differences in risks stemming from variations in the 

assimilation efficiencies generally are larger in the higher trophic species. 
SECTIONTWO Model Assumptions 

SSC-SD/NEHC/URS 91 

The corresponding BAF values varied from -33% to -80% when assimilation efficiencies 

were reduced to half the base case values. When assimilation efficiencies were to a quarter 

of the base case, the resulting BAF values varied from -49% to -93% of the corresponding 

species base case BAF values. 

2.7 MODEL UNCERTAINTIES AND LIMITATIONS 

In environmental risk management, the confidence in a model, such as PRAM, to provide 

useful input for decision-making will increase if the model has certain attributes. These 

attributes may include: that the model follows USEPA guidance; has been peer reviewed; 

and has incorporated peer-reviewed and/or scientifically valid algorithms, and site-specific 

input, and that model assumptions are reasonable and plausible. The Navy has pursued these 

goals in the design and construction of PRAM. Moreover, a model is limited by the 

variables that we can account for, and the possibility that a significant variable has been 

missed or misrepresented. In developing the PRAM, all variables believed relevant and 

applicable have been incorporated, to the best of the ability of the modelers and Navy 

contractors. Nevertheless, the PRAM is limited by some attributes that have been 

incorporated as improvements and others that are intrinsic to all models and computer 

simulations. 

2.7.1 Strength 

The PRAM, as with any computer simulation, is limited by the quality and quantity of 

information upon which the predicted outcomes are based. The site-specific information 

provided by the Navy and its contractors concerning the type and mass of PCB-containing 

materials, and by the State of Florida and Escambia County concerning the environmental 

setting for the ex-ORISKANY, should be considered a strength for the predictions made 

here. 

More generally, the PRAM contains a significant number of attributes that can be considered 

strengths: 

• Leach rates data based on experiments that simulated the environment 

(temperature, pressure, and salinity), in which leaching of PCB from the 

product materials in seawater is expected to take place. 
SECTIONTWO Model Assumptions 

SSC-SD/NEHC/URS 92 

• Algorithms used for predicting the fate and transport of PCBs in the aquatic 

environment are well established and generally accepted by the scientific 

community (e.g., same basic algorithms as those used by the USEPA in the 

development of the PCB water quality standard for the Great Lakes). 

• PCBs are modeled as homologs or groups of PCBs with similar physical, 

chemical, and biouptake/bioaccumulation properties, resolving the difficult 

issue of assessing the impacts of PCBs as a mixture in the products. 

• The ability to address various classes of ships with variable amounts and types 

of PCB-containing bulk product materials onboard with variable PCB 

concentrations. 

• The ability to make scenario analysis to ascertain risk-reduction benefits from 

a hypothetical level of mitigation of PCB-containing bulk product material. 

• The design of PRAM is based on consensus reached among scientists in the 

TWG, resolving such issues as ZOI (horizontal and verticality extent), and 

diet-water compositions for various relevant species in different trophic 

levels. 

• Relatively easy to use with the help of the GUI, and can be used to support the 

assessment of risks during the “transient” or pulse-release period. 

The model has been checked for mathematical correctness, structure, and underlying 

premises. In addition to the USEPA, the Navy is also requesting review and comment from 

its independent reviewer, RTI. 

The greatest strength of the PRAM is its capability to serve as a predictive model or tool to 

assist in the decision-making process associated with the use of decommissioned Navy 

vessels as artificial reef building material. 

2.7.2 Limitations 

“All models are wrong, but some are useful” is a common saying within the fate and 

transport and risk modeling community. This observation is appropriate in emphasizing to 

risk managers that a model is a tool for decision-making. While models attempt to predict or 

mimic reality based on scientific principles and assumptions, they are, in and of themselves, 

not faultless predictive tools. Uncertainties or limitations of PRAM include: 
SECTIONTWO Model Assumptions 

SSC-SD/NEHC/URS 93 

• The PRAM requires boundaries for the modeled environment (i.e., the PRAM 

models an “oval-shaped column” around the sunken vessel within the ocean – 

as based on the ZOI). The ZOI dimensions are based on TWG consensus and 

scientific justifications (Appendix F). 

• The vessel is assumed and modeled as a porous material where the PCBs are 

moving from the interior to the exterior uniformly around the reef established 

on the ship. 

• The PRAM assumes steady-state conditions are present. 

• The PRAM does not account for the importation of water or suspended 

sediment containing PCBs from outside the system being modeled. 

• The PRAM does not account for variable life histories of the animals within 

the system whereas some fish may have accumulated PCBs from juvenile 

rearing in ports and bays. 

• The food web module in PRAM is not intended to be all encompassing; 

although it is based on consensus within the TWG, only significant and 

relevant or representative species in the food web pathway are included for 

biouptake/bioaccumulation. 

• The PRAM has not been calibrated with empirical data, has not been updated 

to perform probabilistic risks to assess uncertainties, and has not been 

upgraded to perform multiple sunken vessel risk modeling.31

Uncertainties are always associated with exposure scenario and parametric variability in risk 

assessment modeling. Overall, PRAM is considered a useful risk management tool for the 

Navy REEFEX program because the program follows USEPA risk assessment methodology, 

 

31 Calibration against actual data (e.g., PCB concentrations in marine organisms within selected tropic levels) 

should help improve model accuracy and/or confidence in the model. Calibration could be achieved by 

adjusting bioenergetic algorithms, e.g., gastrointestinal absorption efficiency. Performance of probabilistic 

risk simulations is a requirement per EPA guidance to present a full-spectrum of risks, not just high-end and 

central tendency risks. Performance of a multiple sunken-vessel scenario would be needed if there is a 

plausible need to perform such risk calculations (e.g., a cluster of sunken vessels documented or purported to 

have PCB-containing materials is to be sunk at a specific locality). In addition, if PRAM is to be used to 

estimate ecological risks for comparison with benchmark values, incorporation of a more representative food 

web would be necessary. PRAM could also be improved to assess the risk-reduction impact of various 
SECTIONTWO Model Assumptions 

SSC-SD/NEHC/URS 94 

uses algorithms and structure accepted by the scientific community, has been validated (i.e., 

they were used successfully in previous applications [e.g., Connolly, 1991; USEPA, 1995]), 

and has undergone independent review. PRAM could be further improved, to reduce 

uncertainty, by calibration against empirical data. 

 

remedial options, particularly to address the uncertainty associated with PCB-containing materials that have 

bi-modal or non-normally distributed data. 
SECTIONTHREE References 

SSC-SD/NEHC/URS 1 

3. Section 3 THREE References 

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Altman, P.L., and D.S. Dittmer. 1971. Biological Handbook of Respiration and Circulation. 

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Barber, C. 2003. A review and comparison of models for predicting dynamic chemical 

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Baumgarten, G., B. Reiter, S. Scheil, S. Schwartz, and J. Oliver Wagner. 1996. CemoS Users 

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Bortone, S.A. 2004. Biology and Life History Information on Several Fish Species often 

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associated with artificial-reef fish assemblages. Gulf of Mexico Science 15:17-34. 

Bortone, S., R. Cody, R. Turpin, and C. Bundrich. 1998. The impact of artificial-reef fish 

assemblage on their potential forage area. Ital. J. Zool. 65: Suppl: 265-267. 

Bosworth, W.S., and L.J. Thibodeaux. 1990. Bioturbation: A facilitator of contaminant 

transport in bed sediment. Environ. Progress 9:211-217. 

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Study MMS 2003-009. 

TABLES















Table 9 

Physical Boundaries and Conditions for the ex-ORISKANY Memorial Reef Site 

 Value Units Value Units 

Vessel

Displacement 1 27100 tons 27533600 kg

Length 1 888 ft 271 m

Beam 1a 120 ft 36.6 m

Water depth 5 212 ft 65 m

Surface Water (all depths) 

Depth to the pycnocline 0, 2 15 m

Suspended solids density 2 1.5 g/cm3

Aerosol density 3 1.19 g/cm3

Dissolved organic carbon density 2 1 g/cm3

Suspended solids fraction organic carbon 4 15% percent

Air 

Air temperature 5 22.3 °C

Active air space height above water column 3 10 m

Air current 6 8.5 mph 13677 meters/hr

Aerosol concentration 3 2.38.E-14 g/cm3

Rainfall 7 6.50E-04 m/day

Particle deposition rate 3 10.8 m/hr

Water above the pycnocline 

Temperature 5 24.5 °C

Dissolved oxygen 8 6.12 mg/L

Total suspended solids 3 10 mg/L

Dissolved organic carbon 4 0.6 mg/L

Water current 0, 6 0.5 knot 926 meters/hr

Water below the pycnocline 

Temperature 4 19.5 °C

Dissolved oxygen 8 6.12 mg/L

Total suspended solids 2 10 mg/L

Dissolved organic carbon 4 0.6 mg/L

Water current 0, 6 0.5 knot 926 meters/hr

Page 1 of 2 
Page 2 of 2 

Table 9 

Physical Boundaries and Conditions for the ex-ORISKANY Memorial Reef Site

Value Units Value Units 

Water within the vessel interior 

Temperature 4 19.5 °C 

Dissolved oxygen 9 4.59 mg/L 

Total suspended solids 3 10 mg/L 

Dissolved organic carbon 4 0.6 mg/L 

Water current - inside the vessel to outside the vessel 10 9.26 meters/hr 

Sediment bed 

Temperature 4 19.5 °C 

Dissolved oxygen 9 3.06 mg/L 

Dissolved organic carbon 11 2 mg/L 

Sediment fraction organic carbon 4 1% percent 

Sediment density 2 1.5 g/cm3 

Sediment moisture 2 10% percent 

Bio-active sediment depth 12 0.1 m 

Sediment deposition rate 13 0 m3

/m2-day 

Sediment resuspension rate 13 0 m3

/m2-day 

Sediment burial rate 13 0 m3

/m2-day 

Notes: Source of Input Value 

0 = Consensus of TWG 

1 = Based on Dictionary of American Naval Fighting Ships (online at http://www.hazegary.org/danfs/carriers/cv34.htm). 

1a = Average between hull beam (93 ft) and flight deck beam (147.5 ft) 

2 = Based on professional judgment 

3 = Based on value used by Mackay and Paterson (1991) 

4 = Typical or low-end value for oceans obtained from Parsons et al. 1979 

5 = Yearly average at NOAA buoy # 42040 (online at http://www.ndbc.noaa.gov/station_history.phtml?station=42040). 

6 = FFWCC 2004 

7 = Based on a yearly average rainfall of 60 inches 

8 = Based on Temperature (°C) and 90% saturation level (Spotte 1970) 

9 = Assumes 75% of DO in water below pycnocline 

10 = Assumed to be 1/10 of current of water within water column below pycnocline 

11 = Upper limit for open ocean surface water obtained from Parsons et al. 1979 

12 = Based on evidence obtained from Bosworth and Thibodeaux 1990 

13 = Set at zero - assumes deposition and resuspension balance 


FIGURES
Figure 1

Flow Diagram for the Development of an Environmental Fate and Transport Model

(adapted from Mackay et al., 1995)

Define the Problem

Bound the Problem in Time, Space, and 

Subsystems 

(e.g., food-chains)

Acquire the Required Data for the System

Draw a Conceptual or Process Flow 

Diagram

Write Equations for all Processes and for 

Mass Balance

Solve Equations to Give Desired Results

Verify the Results and Equations, Check all

Coding

Conduct Sensitivity Analysis to Identify 

Key Process Parameters

Calibrate the Model using Available Data

Validate the Model using "New" Data

Transmit to User with Full Documentation 

and Statements of Limitation and 

Reliability

Are Revisions 

Required to Satisfy 

the Model 

Objectives?

Are Revisions Required to Satisfy 

the Model Objectives?

Are the Quantity and Quality of 

Available Data Adequate?

No

Yes

Yes

Establish Data Quality Objectives 

No

I:\Projects\PRAM\33756123 Navy PCB HHRA\_WP\03000\REPORT\PRAM_ORISKANY-FIGS.xls\Fig 1 Page 1 of 1 5/13/2005
Figure 2

PRAM: Modules, Input, and Outputs

Risk Characterization 

(intake / risk algorithms)

Risk Estim

(chronic cancer 

non-cancer h

Loading Term (PCB 

bulk product masses and 

leach rates)

Site Conditions 

(physical and biological)

Abiotic 

(fugacity level III)

Biotic-Food Web 

(BAF and BCF algorithms)

Exposure Conditions 

(site-specific chronic 

exposure pathways and 

assumptions)

Biota Concen

(total PCBs in 

reef, benthic or

Abiotic Me

Concentrations 

suspended solids, 

Input Core Modules Outp

(Graphic User Interface)

I:\Projects\PRAM\33756123 Navy PCB HHRA\_WP\03000\REPORT\PRAM_ORISKANY-FIGS.xls\Fig 2 Page 1 of 1 
Figure 3

Abiotic and Biotic-Food Web Modules in PRAM

Risk Characterization 

(intake / risk algorithms)

Risk Estim

(chronic cancer 

non-cancer h

Loading Term (PCB 

bulk product masses and 

leach rates)

Site Conditions 

(physical and biological)

Abiotic 

(fugacity level III)

Biotic-Food Web 

(BAF and BCF algorithms)

Exposure Conditions 

(site-specific chronic 

exposure pathways and 

assumptions)

Biota Concen

(total PCBs in 

reef, benthic or

Abiotic Me

Concentrations 

suspended solids, 

Input Core Modules Outp

(Graphic User Interface)

I:\Projects\PRAM\33756123 Navy PCB HHRA\_WP\03000\REPORT\PRAM_ORISKANY-FIGS.xls\Fig 3 Page 1 of 1 
Figure 4

Compartment Identification for PCB Transport

in PRAM

Reactive (Transformation) Processes are not presented

Air (1)

Upper Water Column (2)

Lower Water Column (3)

Sunken Vessel (5)

Sediment Bed (4)

From Water to A

W

From Sediment 

Water Colu

A

From Air to 

Water

From Upper Column 

to Lower Water Water 

Column

From Lower Water 

Column to 

Sediment

From Lower Colu

to Upper Water W

Column

S

Pycnocline

From Sunken 

Vessel to Lower 

Water Column

I:\Projects\PRAM\33756123 Navy PCB HHRA\_WP\03000\REPORT\PRAM_ORISKANY-FIGS.xls\Fig 4 Page 1 of 1 
Figure 5

Example PCB Leach Rate Study Results:

Pentachlorobiphenyl (CL5) in Bulkhead Insulation and Ventilation Gaskets

(Adapted from R. George, SSC-SD, 2004)

Bulkhead Insulation

0.01

0.1

1

10

100

1000

0 50 100 150 200 250 300 350 400 450 500

Leaching Time (days)

Leach Rate (ng/g-shipboard solid-day)

Ventilation Gaskets (Rubber)

0.01

0.1

1

10

100

1000

0 50 100 150 200 250 300 350 400 450

Leaching Time (days)

Leach Rate (ng/g-shipboard solid-day)

I:\Projects\PRAM\33756123 Navy PCB HHRA\_WP\03000\REPORT\PRAM_ORISKANY-FIGS.xls\Fig 5 Page 1 of 1 5/13/2005
Figure 6

Transport Coefficients and Conceptual Design for PCB Transport in PRAM

Reactive (Transformation) Processes are not presented

Air (1)

Upper Water Column (2)

Sunken Vessel (5)

Sediment Bed (4)

(D53)

From Water to Air (D21)

Water 

From Sediment to Lowe

Water Column (D43)

Water 

Air Adv

From Air to Water 

(D12)

From Upper Column 

to Lower Water Water

Column

(D23)

From Lower Water 

Column to Sediment 

(D34) 

From Lower Column 

to Upper Water Water

Column (D32)

Sediment 

Pycnocline

Lower Water Column (3)

From Sunken Vessel 

to Lower Water 

Column (D53) 

I:\Projects\PRAM\33756123 Navy PCB HHRA\_WP\03000\REPORT\PRAM_ORISKANY-FIGS.xls\Fig 6 Page 1 of 1 
Figure 7

Fugacity-Based Transport and Transfers of PCBs in PRAM

Legend where:

Advection f = fugacity

Mass Transfer (Diffusive Transport) φ = volume fraction of specific media within compartment

Reaction Z = fugacity capacity of media (mol/m3-Pa)

Emission V = volume of compartment (m3)

Simple partitioning Dij = fugacity mass transfer coefficient (mol/Pa-day)

Total Mass (mol)

% of Total Mass in 

System

Compartment 

Fugacity (Pa)

Concentration 

(mol/m3)

Phase

f 2 Upper Water Column

f 2ZWφ2WV2

f 2ZW

f 2ZWφ2WV2/Σf i Zi Vi

f 2 Suspended Solids (Upper water column)

f 2ZSSφ2SSV2

f 2ZSS

f 2ZSSφ2SSV2/Σf i Zi

V

f Air 1

f 1ZAφ1AV1

f 1ZA

f 1ZAφ1AV1/Σf i Zi Vi

f 3 Lower Water Column

f 3ZWφ3WV3

f 3ZW

f 3ZWφ3WV3/Σf i Zi Vi

f Aerosols 1

f 1ZAEφ1AEV1

f 1ZAE

f 1ZAEφ1AEV1/Σf i Zi Vi f 5 Vessel Interior Water

f 5ZWφ5WV5

f 5ZW

f 5ZWφ5V5/Σf i Zi Vi

f 3 Suspended Solids (Lower water column)

f 3ZSSφ3SSV3

f 3ZSS

f 3ZSSφ3SSV3/Σf i Zi Vi

f 2 Dissolved OC (Upper water column)

f 2ZDCφ2DCV2

f 2ZDC

f 2ZDCφ2DCV2/Σf i Zi Vi

f 3 Dissolved OC (Lower water column)

f 3ZDCφ3DCV3

f 3ZDC

f 3ZDCφ3DCV3/Σf i Zi Vi

DQW + DDW + DPW DV

DA1* φ1AE

DA2* φ2SS

DA1* φ1A

DW

DA2* φ2w

DR2

DA2* φ2DC

DA3* φ3SS DA3* φ3DC

DY

DDX

DRX

DA3* φ3w DR3

DA5* φ5w DA5* φ5SS

DA5* φ5DC

I:\Projects\PRAM\33756123 Navy PCB HHRA\_WP\03000\REPORT\PRAM_ORISKANY-FIGS.xls\Fig 7 Page 1 of 1 
Figure 8

Depiction of Food Web Used in PRAM

OPEN WATER WITHIN VESSEL'S ZONE OF INFLUENCE

SEDIMENT "BIO

*Some organisms split their residence time between the Upper and Lower Water Columns.

SUNKEN VESSEL / ARTIFICIAL REEF

PYCNOCLINE

Infaunal Benthic 

Invertebrates

Trophic Level 2

(e.g., polychaetes)

Reef - Sessile Filter Feeders

Trophic Level 2

(e.g., bivalves, mollusks)

Reef - Planktivores / Omnivores

Trophic Level 2

(e.g., crustaceans, echinoderms)

R

(e

Reef - Top Predators

Trophic Level 4

(e.g., groupers - Serranidae )

Epifaunal Benthic 

Invertebrates

Trophic Level 2

(e.g., nematodes, gastropods, 

echinoderms)

Benthic Top Predators

Trophic Level 4

(e.g., flatfish Pleuronectiformes)

Sediment Particles

Pelagic Producers

Trophic Level 1

(e.g., algae)

Pelagic Invertebrate Planktivores

Trophic Level 2

(e.g., copepods )

Suspended Particles

Pelagic Planktivores / Predators

Trophic Level 3

(e.g., snappers - Latjanidae)

Pelagic Planktivores / Predators

Trophic Level 4

(e.g., jacks - Carangidae )

Certain trophic relationships between pelagic, epi-vessel and benthic compartments are considered insignificant in the context of mass and energy transfers and as such, are not shown here.

Reef Producers

Trophic Level 1

(e.g., attached algae)

Benthic Foragers / Predators

Trophic Level 3

(e.g., crustaceans, cephalopods)

I:\Projects\PRAM\33756123 Navy PCB HHRA\_WP\03000\REPORT\PRAM_ORISKANY-FIGS.xls\Fig 8 Page 1 of 1 Arrows indicate t
Figure 9

Assimilation Efficiencies Across Gastro-Intestinal Tracts

as Function of Chemical-Specific Kow in the Food Web Module of PRAM

Review of the raw data suggested that the form of the relationship between Kow and α is perhaps best described as a parabolic

function. A parabolic function was calibrated to assure a level of conservatism within the PRAM such virtually all of the reported

assimilation efficiencies fell below the predicted values. The resultant algorithm is presented below and graphically compared to

the observed values reported by Gobas et al. (1988), Thomann (1989), and Fisk et al. (1998).

Assimilation vs. LogKow

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

3 4 5 6 7 8 9 10

LogKow

Assimilation

Gobas 1988

Fisk et al. 1998

Endicott et al. 1991

Thomann 1989

Fraction Assimilated vs. LogKow

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

3 4 5 6 7 8 9 10 11

LogKow

Fraction Assimilated

Legend:

♦ Observed values from 

Gobas, Fisk et al., and 

Thomann

 Parabolic relationship 

derived for PRAM

100

10 2 −1.8+1.08 log Kow −0.08 log Kow

α =

Legend:

Regression presented by

I:\Projects\PRAM\33756123 Navy PCB HHRA\_WP\03000\REPORT\PRAM_ORISKANY-FIGS.xls\Fig 9 Page 1 of 1 5/13/2005
Figure 10

Relationship Between Kow and Elimination Rates (Ke) of PCB in Aquatic Animals

Based on Peterson & Kristensen (1998) data only Based on literature values (used in the PRAM)

Kow

day

Ke 10 10 1.065 0.4131 log 1 log = − × ⎥⎦⎤ ⎢⎣⎡ Kow day Ke 10 10 3.25 0.66 log 1 log = − × ⎥⎦⎤ ⎢⎣⎡

0.0001

0.001

0.01

0.1

1

10

100

0 2 4 6 8 10 

LogKow

Elimination (1/day)

Peterson & Kristensen 1998

Based on literature values

Values reported by Peterson & Kristensen 1998, Thomann 1989, Fisk al. 1998

I:\Projects\PRAM\33756123 Navy PCB HHRA\_WP\03000\REPORT\PRAM_ORISKANY-FIGS.xls\Fig 10 Page 1 of 1 
Figure 11

Logic Diagram for Statistical Estimation of Reasonable Maximum PCB Concentration

and Central Tendency Concentration in Source Material Onboard the Ex-ORISKANY

Are there Five or More Samples?

Is Percent Detection >50% ?

Is tha

No

Are 

No Yes

Use Mi

a

Can 

T

Are there Fifteen or More Samples?

Is Raw Data Skewness Significant?

No

Yes

Is Bootstrap Bias Significant?

Yes

Use Standard Bootstrapped Mean and Hall's 

Adjusted Bootstrap Estimate of the t-statistic to 

Derive a mean and UCL

Yes

NoNo

No

Are Bootstrapped Q(Wi's) - Halls' 

Method Normal

Are Standard Bootstrapped Means 

Normal?

Are Bootstrapped Wi's - Pivotal 

Method Normal?

Use Jackknife Method to Derive a mean and 

UCL

Use Standard Bootstrapped Mean and Pivotal 

Bootstrap Estimate of the t-statistic to Derive a 

mean and UCL

Yes

Yes

Use Standard Bootstrapped Mean and Bootstrap 

Standard Error with the t-statistic to Derive a 

mean and UCL

No

No

Use Jackknife Method to Derive a mean and 

UCL

Yes

Non-Normal

I:\Projects\PRAM\33756123 Navy PCB HHRA\_WP\03000\REPORT\PRAM_ORISKANY-FIGS.xls\Fig 11

Page 1 of 1 
Figure 12

PCB Concentrations Presented as Box-Whisker Plots

for Materials Found Onboard the Ex-ORSIKANY

ELECTRICAL CABLE

Quantiles for the data set

Minimum 6.10

Lower Quartile 23.0

Median 67.0

Upper Quartile 140

Maximum 29000

VENTILATION GASKETS

Quantiles for the data set

Minimum 0.5

Lower Quartile 0.5

Median 5.5

Upper Quartile 25.0

Maximum 210

RUBBER MATERIALS

Quantiles for the data set

Minimum 6.50

Lower Quartile 10.0

Median 26.0

Upper Quartile 49.0

Maximum 130

The lines represent min and max, white box = 25th to 50 th quantile, gray box = 50th to 75 th quantile, 50 th = the median value

0.00 5000.00 10000.00 15000.00 20000.00 25000.00 30000.00 35000.00

1.00 10.00 100.00 1000.00 10000.00 100000.00

0.0 50.0 100.0 150.0 200.0 250.0 300.0

0.1 1.0 10.0 100.0 1000.0

0.00 50.00 100.00 150.00 200.00 250.00

1.00 10.00 100.00 1000.00

I:\Projects\PRAM\33756123 Navy PCB HHRA\_WP\03000\REPORT\PRAM_ORISKANY-FIGS.xls\Fig 12 Page 1 of 2 5/13/2005
Figure 12

PCB Concentrations Presented as Box-Whisker Plots

for Materials Found Onboard the Ex-ORSIKANY

PAINTS

Quantiles for the data set

Minimum 5.8

Lower Quartile 4.12

Median 5.8

Upper Quartile 24.4

Maximum 28

BULKHEAD INSULATION

Quantiles for the data set

Minimum 5

Lower Quartile 3.18

Median 6.15

Upper Quartile 16.5

Maximum 610

The lines represent min and max, white box = 25th to 50 th quantile, gray box = 50th to 75 th quantile, 50 th = the median value

0 10 20 30 40 50 60 70 80

1 10 100

0 100 200 300 400 500 600 700

1 10 100 1000

I:\Projects\PRAM\33756123 Navy PCB HHRA\_WP\03000\REPORT\PRAM_ORISKANY-FIGS.xls\Fig 12 Page 2 of 2 5/13/2005
Figure 13

Zone of Influence (ZOI) Ellipse Area Calculations

Footprint = Vessel Footprint

= Area of Ellipse

Zone of Influence determines spatial footprint on ocean floor. PRAMmodels this elliptical footprint through upper and lower water columns = as well as air space above vessel. S

=

ZOI = 1 is equivalent to vessel footprint

= π(444)(60)

≈ 83,700 ft2

S

SIDE VIEW

If ZOI = 1

Sediment

Air

Variable ZOI 

Pycnocline

Lower Water Column

Upper Water Column

Length

888'

Beam

120'

Length + ZOI ï i

⎟⎠⎞ ⎜⎝⎛⎟⎠⎞ ⎜⎝⎛ 2 Beam 2 Length π

⎟⎠⎞ ⎜⎝⎛⎟⎠⎞ ⎜⎝⎛ 2 120 2 888 π

Vessel 

Footprint

V

I:\Projects\PRAM\33756123 Navy PCB HHRA\_WP\03000\REPORT\PRAM_ORISKANY-FIGS.xls\Fig 13 Page 1 of 1 
Figure 14

Risk Characterization Module in PRAM

Risk Characterization 

(intake / risk algorithms)

Risk Estim

(chronic cancer 

non-cancer h

Loading Term (PCB 

bulk product masses and 

leach rates)

Site Conditions 

(physical and biological)

Abiotic 

(fugacity level III)

Biotic-Food Web 

(BAF and BCF algorithms)

Exposure Conditions 

(site-specific chronic 

exposure pathways and 

assumptions)

Biota Concen

(total PCBs in 

reef, benthic or

Abiotic Me

Concentrations 

suspended solids, 

Input Core Modules Outp

(Graphic User Interface)

I:\Projects\PRAM\33756123 Navy PCB HHRA\_WP\03000\REPORT\PRAM_ORISKANY-FIGS.xls\Fig 14 Page 1 of 1 
Figure 15

SCEM - Site Conceptual Exposure Model

Marine Biota

PCB-Containing

Materials

in Ship

RE

FISH

WATER

SEDIMENT

PRIMARY

PRODUCERS

SECONDARY

CONSUMERS

PRIMARY

CONSUMERS

P

Steady State exposure pathway

Time Dynamic exposure pathway (complete)

TERTIARY

CONSUMERS

Time Dynamic exposure pathway (partially complete)Minor pathway

I:\Projects\PRAM\33756123 Navy PCB HHRA\_WP\03000\REPORT\PRAM_ORISKANY-FIGS.xls\Fig 15 Page 1 of 1 
APPENDIX A 

REGRESSION ANALYSES: PCB LEACH RATES 

AND MATERIAL FRACTIONS 






































































APPENDIX B 

CALCULATION OF HOMOLOG-SPECIFIC KOWs
OCTANOL TO WATER PARTITIONING COEFFICIENTS (LOG10

KOW) FOR PCB CONGENERS AS OBTA

AND BELISLE (1996)

1 4.601 4 5.023 16 5.311 40 5.561 82 6.142 128 6.961 170 7.277 194 8.683 2 4.421 5 NA 17 5.761 41 6.111 83 6.267 129 7.321 171 6.704 195 7.567 3 4.401 6 5.021 18 5.551 42 5.767 84 6.041 130 7.391 172 7.337 196 7.657 

7 5.15 19 5.481 43 5.757 85 6.611 131 6.587 173 7.027 197 7.3078 5.301 20 5.577 44 5.811 86 6.204 132 6.587 174 7.117 198 7.6279 5.18 21 5.17 45 5.537 87 6.371 133 6.867 175 7.177 199 7.207

10 5.311 22 5.421 46 5.537 88 7.516 134 7.304 176 6.767 200 7.27711 5.343 23 5.577 47 6.291 89 6.077 135 7.151 177 7.087 201 7.62712 5.295 24 5.671 48 5.787 90 6.367 136 6.511 178 7.147 202 8.42313 NA 25 5.677 49 6.221 91 6.137 137 7.711 179 6.737 203 7.65714 5.404 26 5.667 50 5.637 92 6.357 138 7.441 180 7.367 204 7.30715 5.335 27 5.447 51 5.637 93 6.047 139 6.677 181 7.117 205 8.007

28 5.691 52 6.091 94 6.137 140 6.677 182 7.20729 5.743 53 5.627 95 6.137 141 7.592 183 7.20730 5.504 54 5.904 96 5.717 142 6.517 184 6.85731 5.677 55 6.117 97 6.671 143 6.607 185 7.93332 5.751 56 6.117 98 6.137 144 6.677 186 6.69733 5.572 57 6.177 99 7.211 145 6.257 187 7.17734 5.667 58 6.177 100 6.237 146 6.897 188 6.82735 5.827 59 5.957 101 7.071 147 6.647 189 7.71736 4.151 60 5.452 102 6.167 148 6.737 190 7.46737 4.941 61 5.943 103 6.227 149 7.281 191 7.55738 5.767 62 5.897 104 5.817 150 6.327 192 7.52739 5.897 63 6.177 105 6.657 151 6.647 193 7.527

64 5.957 106 6.647 152 6.22765 5.867 107 6.717 153 7.75166 5.452 108 6.717 154 6.76767 6.207 109 6.487 155 7.12368 6.267 110 6.532 156 7.18769 6.047 111 6.767 157 7.18770 6.231 112 6.457 158 7.02771 5.987 113 6.547 159 7.24772 6.267 114 6.657 160 6.93773 6.047 115 6.497 161 7.08774 6.671 116 6.304 162 7.24775 6.057 117 6.467 163 6.99776 6.137 118 7.121 164 7.02777 6.523 119 6.587 165 7.05778 6.357 120 6.797 166 6.93779 6.427 121 6.647 167 7.27780 6.583 122 6.647 168 7.11781 6.367 123 6.747 169 7.427

124 6.737125 6.517126 6.897127 6.957

Monochlorobiphenyls Dichlorobiphenyls Trichlorobiphenyls Tetrachlorobiphenyls Pentachlorobiphenyls Hexachlorobiphenyls Heptachlorobiphenyls Octachlorobiphenyls 

NA = not available Page 1 of 1 I:\Projects\PRAM\33756123 Navy PCB HHRA\_WP\0300
179495 Log10 5.254

Congener Value 208900 Log10 5.320

4 105439 5.023

6 104954 5.021

7 141254 5.150 Number of Values

8 199986 5.301 Maximum Value Minimum Value

9 151356 5.180

10 204644 5.311 Normal Mean Mean Standard Error

11 220293 5.343 Standard Deviation Coefficient of Variance (%)

12 197242 5.295 Dataset Skewness Pass -2.65E-01 Dataset Kurtosis Fail 1.50E+00

14 253513 5.404 Tested for Normality Normality Result (a = 0.05)

15 216272 5.335 Critical Value Calculated Value for dataset

90% UCL using t-statistic 95% UCL using -t-statistic

No values were presented for

congeners 5 and 13 MVUE of the log-mean Standard error of the log-me

Standard Deviation Coefficient of Variance (%)

Dataset Skewness Pass -5.13E-01 Dataset Kurtosis Fail 1.60E+00

Tested for Normality Normality Result (a = 0.05)

Critical Value Calculated Value for dataset

Anderson Darling (AD) A2 AD Probability Pass 6.91E-01

90% UCL of the MVUE 95% UCL of the MVUE

Jackknifed Mean Jackknifed Standard Error

90% UCL of the mean 95% UCL of the mean

90% UCL of the MVUE2 95% UCL of the MVUE2

Standard Bootstrap Mean 1.79E+05 90% UCL 1.98E+05 95% UCL 2.03E+05

Skewness 5.37E-02 Kurtosis 2.99E+00

Pivitol (t) Bootstrap 90% UCL 95% UCL

Skewness 1.19E+00 Kurtosis 9.29E+00

Hall's t Bootstrap 90% UCL 95% UCL

Skewness 3.34E-01 Kurtosis 8.40E+00

2.03E+05

2.02E+05

Quantile fit is good - Bootstrap Output is Normal or nearly so

Jackknife Results

Bootstrap Results (Raw Data)

2.09E+05

2.10E+05

2.00E+05 2.06E+05

1.79E+05

2.02E+05

Raw Data Results

1.05E+05

STATISTICAL ANALYSIS OF OCTANOL-WATER PARTITIONING COEFFICIENTS 

OBTAINED FROM EISLER AND BELISLE (1996)

Dichlorobiphenyls

The data are best described as normally distributed and there were a sufficient number of detected 

values to perform a statistical analysis. 

1.80E+05 1.79E+04

10

2.22E+05

2.54E+05

28%

Natural Log-Transformed Results

1.79E+05 1.60E+04

Normal (Non-transformed) Results

Pass

9.17E-01

2.09E+05

5.07E+04

W-Test

8.42E-01

1.98E+05 2.06E+05

Quantile fit is good - Bootstrap Output is Normal or nearly so

Quantile fit is good - Bootstrap Output is Normal or nearly so

Pass

8.80E-01

W-Test

8.42E-01

Log10Kow

Recommended Mean

Recommended UCL

1.60E+04

5.55E-01

2.11E+05

Normal Mean

UCL based on t-statistic

3.12E-01 3%

I:\Projects\PRAM\33756123 Navy PCB HHRA\_WP\03000\REPORT\PRAM_ORISKANY-APP B.xls\Dichlorobiphenyls-Kow

5/12/2005 4:36 PM

URS 2 = Using the Jackknife

MVUE=Minimum Variance Unbiased Estimator

UCL=Upper Confidence Interval
BOOTSTRAP RESULTS FOR OCTANOL-WATER PARTITIONING COEFFCIENTS FOR 

DICHLOROBIPHENYLS OBTAINED FROM EISLER AND BELISLE (1996)

Standard Bootstrap

0

20

40

60

80

100

120

1 2 3 4 5 6 7 8 910111213141516171819202122232425262728293031323334353637383940

Bootstrap Mean

Number of Datasets

Pivotal Bootstrap

0

10

20

30

40

50

60

123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960616263646566676869707172737475767778798081828384858687888990919293949596979899

Bootstrap t Value

Number of Datasets

Hall's Transformed t Bootstrap

0

10

20

30

40

50

60

70

123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960616263646566676869707172737475767778798081828384858687888990919293949596979899100

Bootstrap Q Value

Number of Datasets

Standard Boot Q-Q Plot

0

0.2

0.4

0.6

0.8

1

1.2

1 86 171 256 341 426 511 596 681 766 851 936

StdBoot Exp

Std Boot Obs

Pivotal-Boot Q-Q Plot

0

0.2

0.4

0.6

0.8

1

1.2

1 84 167 250 333 416 499 582 665 748 831 914 997

Boot t Exp

Boot t Obs

Hall's t Transformed t Boot Q-Q Plot

0

0.2

0.4

0.6

0.8

1

1.2

1 85 169 253 337 421 505 589 673 757 841 925

Boot Q Exp

Boot Q Obs

I:\Projects\PRAM\33756123 Navy PCB HHRA\_WP\03000\REPORT\PRAM_ORISKANY-APP B.xls\B_Dichlorobiphenyls-Kow
403403 Log10 5.606

Congener Value 467582 Log10 5.670

16 204644 5.311

17 576766 5.761

18 355631 5.551 Number of Values

19 302691 5.481 Maximum Value Minimum Value

20 377572 5.577

21 147911 5.170 Normal Mean Mean Standard Error

22 263633 5.421 Standard Deviation Coefficient of Variance (%)

23 377572 5.577 Dataset Skewness Pass -1.63E-01 Dataset Kurtosis Pass 2.58E+00

24 468813 5.671 Tested for Normality NormalityResult (a = 0.05)

25 475335 5.677 Critical Value Calculated Value for dataset

26 464515 5.667 90% UCL using t-statistic 95% UCL using -t-statistic

27 279898 5.447

28 490908 5.691 MVUE of the log-mean Standard error of the log-me

29 553350 5.743 Standard Deviation Coefficient of Variance (%)

30 319154 5.504 Dataset Skewness Fail -2.3E+00 Dataset Kurtosis Fail 9.02E+00

31 475335 5.677 Tested for Normality Normality Result (a = 0.05)

32 563638 5.751 Critical Value Calculated Value for dataset

33 373250 5.572 Anderson Darling (AD) A2 AD Probability Fail 8.82E-02

34 464515 5.667 90% UCL of the MVUE 95% UCL of the MVUE

35 671429 5.827

36 14158 4.151 Jackknifed Mean Jackknifed Standard Error

37 87297 4.941 90% UCL of the mean 95% UCL of the mean

38 584790 5.767 90% UCL of the MVUE2 95% UCL of the MVUE2

39 788860 5.897

Standard Bootstrap Mean 4.02E+05 90% UCL 4.48E+05 95% UCL 4.61E+05

Skewness -2.19E-01 Kurtosis 3.25E+00

Pivitol (t) Bootstrap 90% UCL 95% UCL

Skewness -1.48E-01 Kurtosis 3.65E+00

Hall's t Bootstrap 90% UCL 95% UCL

Skewness -9.08E-02 Kurtosis 4.21E+00

5.35E+05

4.53E+05

Quantile fit is good - Bootstrap Output is Normal or nearly so

Jackknife Results

Bootstrap Results (Raw Data)

4.68E+05

5.55E+05

4.52E+05 4.71E+05

4.03E+05

4.53E+05

Raw Data Results

1.42E+04

STATISTICAL ANALYSIS OF OCTANOL-WATER PARTITIONING COEFFICIENTS 

OBTAINED FROM EISLER AND BELISLE (1996)

Trichlorobiphenyls

The data are best described as normally distributed and there were a sufficient number of detected 

values to perform a statistical analysis. 

4.60E+05 8.60E+04

24

6.99E+05

7.89E+05

45%

Natural Log-Transformed Results

4.03E+05 3.74E+04

Normal (Non-transformed) Results

Pass

9.85E-01

4.68E+05

1.83E+05

W-Test

9.16E-01

4.53E+05 4.73E+05

Quantile fit is good - Bootstrap Output is Normal or nearly so

Quantile fit is good - Bootstrap Output is Normal or nearly so

Fail

7.23E-01

W-Test

9.16E-01

Recommended Mean

Log Recommended UCL 10Kow

3.74E+04

2.03E+00

6.31E+05

Normal Mean

UCL based on t-statistic

8.32E-01 7%

I:\Projects\PRAM\33756123 Navy PCB HHRA\_WP\03000\REPORT\PRAM_ORISKANY-APP B.xls\Trichlorobiphenyls-Kow

5/12/2005 4:35 PM

URS 2 = Using the Jackknife

MVUE=Minimum Variance Unbiased Estimator

UCL=Upper Confidence Interval
BOOTSTRAP RESULTS FOR OCTANOL-WATER PARTITIONING COEFFCIENTS FOR 

TRICHLOROBIPHENYLS OBTAINED FROM EISLER AND BELISLE (1996)

Standard Bootstrap

0

20

40

60

80

100

1 2 3 4 5 6 7 8 91011121314151617181920212223242526272829303132333435363738394041424344

Bootstrap Mean

Number of Datasets

Pivotal Bootstrap

0

10

20

30

40

50

123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960616263646566676869707172737475767778798081828384858687888990919293949596979899

Bootstrap t Value

Number of Datasets

Hall's Transformed t Bootstrap

0

10

20

30

40

50

123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960616263646566676869707172737475767778798081828384858687888990919293949596979899

Bootstrap Q Value

Number of Datasets

Standard Boot Q-Q Plot

0

0.2

0.4

0.6

0.8

1

1.2

1 85 169 253 337 421 505 589 673 757 841 925

StdBoot Exp

Std Boot Obs

Pivotal-Boot Q-Q Plot

0

0.2

0.4

0.6

0.8

1

1.2

1 86 171 256 341 426 511 596 681 766 851 936

Boot t Exp

Boot t Obs

Hall's t Transformed t Boot Q-Q Plot

0

0.2

0.4

0.6

0.8

1

1.2

1 86 171 256 341 426 511 596 681 766 851 936

Boot Q Exp

Boot Q Obs

I:\Projects\PRAM\33756123 Navy PCB HHRA\_WP\03000\REPORT\PRAM_ORISKANY-APP B.xls\B_Trichlorobiphenyls-Kow
1330250 Log10 6.124

Congener Value 1683184 Log10 6.226

40 363915 5.561

41 1291219 6.111

42 584790 5.767 Number of Values

43 571479 5.757 Maximum Value Minimum Value

44 647143 5.811

45 344350 5.537 Normal Mean Mean Standard Error

46 344350 5.537 Standard Deviation Coefficient of Variance (%)

47 1954339 6.291 Dataset Skewness Fail 1.55E+00 Dataset Kurtosis Fail 5.52E+00

48 612350 5.787 Tested for Normality NormalityResult (a = 0.05)

49 1663413 6.221 Critical Value Calculated Value for dataset

50 433511 5.637 90% UCL using t-statistic 95% UCL using -t-statistic

51 433511 5.637

52 1233105 6.091 MVUE of the log-mean Standard error of the log-me

53 423643 5.627 Standard Deviation Coefficient of Variance (%)

54 801678 5.904 Dataset Skewness Pass -6.40E-02 Dataset Kurtosis Pass 2.27E+00

55 1309182 6.117 Tested for Normality Normality Result (a = 0.05)

56 1309182 6.117 Critical Value Calculated Value for dataset

57 1503142 6.177 Anderson Darling (AD) A2 AD Probability Pass 9.54E-01

58 1503142 6.177 90% UCL of the MVUE 95% UCL of the MVUE

59 905733 5.957

60 283139 5.452 Jackknifed Mean Jackknifed Standard Error

61 877001 5.943 90% UCL of the mean 95% UCL of the mean

62 788860 5.897 90% UCL of the MVUE2 95% UCL of the MVUE2

63 1503142 6.177

64 905733 5.957 Standard Bootstrap Mean 1.32E+06 90% UCL 1.52E+06 95% UCL 1.57E+06

65 736207 5.867 Skewness 2.88E-01 Kurtosis 3.39E+00

66 283139 5.452

67 1610646 6.207 Pivitol (t) Bootstrap 90% UCL 95% UCL

68 1849269 6.267 Skewness -6.83E-01 Kurtosis 4.57E+00

69 1114295 6.047

70 1702159 6.231 Hall's t Bootstrap 90% UCL 95% UCL

71 970510 5.987 Skewness ######## Kurtosis 5.78E+00

72 1849269 6.267

73 1114295 6.047

74 4688134 6.671

75 1140250 6.057

76 1370882 6.137

77 3334264 6.523

78 2275097 6.357

79 2673006 6.427

80 3828247 6.583

81 2328091 6.367

1.53E+06

1.51E+06

Quantile fit is good - Bootstrap Output is Normal or nearly so

Jackknife Results

Bootstrap Results (Raw Data)

1.57E+06

1.59E+06

1.54E+06 1.62E+06

1.32E+06

1.51E+06

Raw Data Results

2.83E+05

STATISTICAL ANALYSIS OF OCTANOL-WATER PARTITIONING COEFFICIENTS 

OBTAINED FROM EISLER AND BELISLE (1996)

Tetrachlorobiphenyls

The data are best described as log-normally distributed and there were a sufficient number of 

detected values to perform statistical analysis. The CV is less than 100% 

1.33E+06 1.59E+05

42

1.68E+06

4.69E+06

73%

Natural Log-Transformed Results

1.32E+06 1.48E+05

Normal (Non-transformed) Results

Fail

8.51E-01

1.57E+06

9.62E+05

W-Test

9.42E-01

1.54E+06 1.61E+06

Quantile fit is good - Bootstrap Output is Normal or nearly so

Quantile fit is good - Bootstrap Output is Normal or nearly so

Pass

9.71E-01

W-Test

9.42E-01

Log10Kow

Recommended Mean

Recommended UCL

1.48E+05

2.77E-01

1.59E+06

MVUE of the log-mean

UCL based on H-statistic

7.10E-01 5%

I:\Projects\PRAM\33756123 Navy PCB HHRA\_WP\03000\REPORT\PRAM_ORISKANY-APP B.xls\Tetrachlorobiphenyls-Kow

5/12/2005 4:35 PM

URS 2 = Using the Jackknife

MVUE=Minimum Variance Unbiased Estimator

UCL=Upper Confidence Interval
BOOTSTRAP RESULTS FOR OCTANOL-WATER PARTITIONING COEFFCIENTS FOR 

TETRACHLOROBIPHENYLS OBTAINED FROM EISLER AND BELISLE (1996)

Standard Bootstrap

0

20

40

60

80

100

12345678910112131415161718192021223242526272829303132334353637383940414243445464748495051525354556

Bootstrap Mean

Number of Datasets

Pivotal Bootstrap

0

10

20

30

40

50

60

123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960616263646566676869707172737475767778798081828384858687888990919293949596979899100

Bootstrap t Value

Number of Datasets

Hall's Transformed t Bootstrap

0

10

20

30

40

50

60

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Bootstrap Q Value

Number of Datasets

Standard Boot Q-Q Plot

0

0.2

0.4

0.6

0.8

1

1.2

1 87 173 259 345 431 517 603 689 775 861 947

StdBoot Exp

Std Boot Obs

Pivotal-Boot Q-Q Plot

0

0.2

0.4

0.6

0.8

1

1.2

1 85 169 253 337 421 505 589 673 757 841 925

Boot t Exp

Boot t Obs

Hall's t Transformed t Boot Q-Q Plot

0

0.2

0.4

0.6

0.8

1

1.2

1 86 171 256 341 426 511 596 681 766 851 936

Boot Q Exp

Boot Q Obs

I:\Projects\PRAM\33756123 Navy PCB HHRA\_WP\03000\REPORT\PRAM_ORISKANY-APP B.xls\B_Tetrachlorobiphenyls-Kow
4400776 Log10 6.644

Congener Value 5544897 Log10 6.744

82 1386756 6.142

83 1849269 6.267

84 1099006 6.041 Number of Values

85 4083194 6.611 Maximum Value Minimum Value

86 1599558 6.204

87 2349633 6.371 Normal Mean Mean Standard Error

88 32809529 7.516 Standard Deviation Coefficient of Variance (%)

89 1193988 6.077 Dataset Skewness Fail 3.47E+00 Dataset Kurtosis Fail 1.74E+01

90 2328091 6.367 Tested for Normality NormalityResult (a = 0.05)

91 1370882 6.137 Critical Value Calculated Value for dataset

92 2275097 6.357 90% UCL using t-statistic 95% UCL using -t-statistic

93 1114295 6.047

94 1370882 6.137 MVUE of the log-mean Standard error of the log-me

95 1370882 6.137 Standard Deviation Coefficient of Variance (%)

96 521195 5.717 Dataset Skewness Pass 3.45E-01 Dataset Kurtosis Pass 3.11E+00

97 4688134 6.671 Tested for Normality Normality Result (a = 0.05)

98 1370882 6.137 Critical Value Calculated Value for dataset

99 16255488 7.211 Anderson Darling (AD) A2 AD Probability Pass 8.99E-01

100 1725838 6.237 90% UCL of the MVUE 95% UCL of the MVUE

101 11776060 7.071

102 1468926 6.167 Jackknifed Mean Jackknifed Standard Error

103 1686553 6.227 90% UCL of the mean 95% UCL of the mean

104 656145 5.817 90% UCL of the MVUE2 95% UCL of the MVUE2

105 4539416 6.657

106 4436086 6.647 Standard Bootstrap Mean 4.57E+06 90% UCL 5.58E+06 95% UCL 5.87E+06

107 5211947 6.717 Skewness 4.76E-01 Kurtosis 3.43E+00

108 5211947 6.717

109 3069022 6.487 Pivitol (t) Bootstrap 90% UCL 95% UCL

110 3404082 6.532 Skewness -1.6E+00 Kurtosis 7.30E+00

111 5847901 6.767

112 2864178 6.457 Hall's t Bootstrap 90% UCL 95% UCL

113 3523709 6.547 Skewness -2.6E+00 Kurtosis 1.58E+01

114 4539416 6.657

115 3140509 6.497

116 2013724 6.304

117 2930893 6.467

118 13212956 7.121

119 3863670 6.587

120 6266139 6.797

121 4436086 6.647

122 4436086 6.647

123 5584702 6.747

124 5457579 6.737

125 3288516 6.517

126 7888601 6.897

127 9057326 6.957

Quantile fit is poor do not use Bootstrap Results

Jackknife Results

Bootstrap Results (Raw Data)

5.91E+06

5.54E+06

6.39E+06 7.10E+06

4.58E+06

5.61E+06

5.28E+06

5.91E+06

5.37E+06

W-Test

9.45E-01

5.61E+06

STATISTICAL ANALYSIS OF OCTANOL-WATER PARTITIONING COEFFICIENTS 

OBTAINED FROM EISLER AND BELISLE (1996)

Pentachlorobiphenyls

Recommended Mean

117%

3.28E+07

Raw Data Results

5.21E+05

The data are best described as log-normally distributed and there were a sufficient number of 

detected values to perform statistical analysis. The CV is > 100% 

MVUE of the log-mean

UCL based on Jackknifed MVUE

5.82E+06

Pass

9.79E-01

W-Test

9.45E-01

4.40E+06 6.14E+05

Recommended UCL

8.39E-01 6%

Natural Log-Transformed Results

4.58E+06 7.91E+05

Fail

6.19E-01

Log10Kow

7.91E+05

6.52E+06 7.20E+06

Quantile fit is good - Bootstrap Output is Normal or nearly so

Quantile fit is good - Bootstrap Output is Normal or nearly so

3.48E-01

5.46E+06

46

Normal (Non-transformed) Results

I:\Projects\PRAM\33756123 Navy PCB HHRA\_WP\03000\REPORT\PRAM_ORISKANY-APP B.xls\Pentachlorobiphenyls-Kow

5/12/2005 4:34 PM

URS 2 = Using the Jackknife

MVUE=Minimum Variance Unbiased Estimator

UCL=Upper Confidence Interval
BOOTSTRAP RESULTS FOR OCTANOL-WATER PARTITIONING COEFFCIENTS FOR 

PENTACHLOROBIPHENYLS OBTAINED FROM EISLER AND BELISLE (1996)

Standard Bootstrap

0

10

20

30

40

50

60

1234567891011121314151617181920212223242526272829303132333435363738394041424344454647484950515253545556575859606162636465666768697071727374757677787980818283848586

Bootstrap Mean

Number of Datasets

Pivotal Bootstrap

0

10

20

30

40

50

60

70

80

123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960616263646566676869707172737475767778798081828384858687888990919293949596979899

Bootstrap t Value

Number of Datasets

Hall's Transformed t Bootstrap

0

20

40

60

80

100

120

123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960616263646566676869707172737475767778798081828384858687888990919293949596979899

Bootstrap Q Value

Number of Datasets

Standard Boot Q-Q Plot

0

0.2

0.4

0.6

0.8

1

1.2

1 86 171 256 341 426 511 596 681 766 851 936

StdBoot Exp

Std Boot Obs

Pivotal-Boot Q-Q Plot

0

0.2

0.4

0.6

0.8

1

1.2

1 85 169 253 337 421 505 589 673 757 841 925

Boot t Exp

Boot t Obs

Hall's t Transformed t Boot Q-Q Plot

0

0.2

0.4

0.6

0.8

1

1.2

1 86 171 256 341 426 511 596 681 766 851 936

Boot Q Exp

Boot Q Obs

I:\Projects\PRAM\33756123 Navy PCB HHRA\_WP\03000\REPORT\PRAM_ORISKANY-APP B.xls\B_Pentachlorobiphenyls-Kow
13630937 Log10 7.135

Congener Value 18596711 Log10 7.269

128 9141132 6.961

129 20941125 7.321

130 24603676 7.391 Number of Values

131 3863670 6.587 Maximum Value Minimum Value

132 3863670 6.587

133 7362071 6.867 Normal Mean Mean Standard Error

134 20137242 7.304 Standard Deviation Coefficient of Variance (%)

135 14157938 7.151 Dataset Skewness Fail 1.83E+00 Dataset Kurtosis Fail 6.35E+00

136 3243396 6.511 Tested for Normality NormalityResult (a = 0.05)

137 51404365 7.711 Critical Value Calculated Value for dataset

138 27605779 7.441 90% UCL using t-statistic 95% UCL using -t-statistic

139 4753352 6.677

140 4753352 6.677 MVUE of the log-mean Standard error of the log-me

141 39084090 7.592 Standard Deviation Coefficient of Variance (%)

142 3288516 6.517 Dataset Skewness Pass -2.00E-02 Dataset Kurtosis Pass 2.29E+00

143 4045759 6.607 Tested for Normality Normality Result (a = 0.05)

144 4753352 6.677 Critical Value Calculated Value for dataset

145 1807174 6.257 Anderson Darling (AD) A2 AD Probability Pass 9.75E-01

146 7888601 6.897 90% UCL of the MVUE 95% UCL of the MVUE

147 4436086 6.647

148 5457579 6.737 Jackknifed Mean Jackknifed Standard Error

149 19098533 7.281 90% UCL of the mean 95% UCL of the mean

150 2123244 6.327 90% UCL of the MVUE2 95% UCL of the MVUE2

151 4436086 6.647

152 1686553 6.227 Standard Bootstrap Mean 1.35E+07 90% UCL 1.59E+07 95% UCL 1.65E+07

153 56363766 7.751 Skewness 2.54E-01 Kurtosis 2.89E+00

154 5847901 6.767

155 13273945 7.123 Pivitol (t) Bootstrap 90% UCL 95% UCL

156 15381546 7.187 Skewness -8.04E-01 Kurtosis 4.27E+00

157 15381546 7.187

158 10641430 7.027 Hall's t Bootstrap 90% UCL 95% UCL

159 17660378 7.247 Skewness -1.3E+00 Kurtosis 6.13E+00

160 8649679 6.937

161 12217997 7.087

162 17660378 7.247

163 9931160 6.997

164 10641430 7.027

165 11402498 7.057

166 8649679 6.937

167 18923436 7.277

168 13091819 7.117

169 26730064 7.427

1.62E+07

1.60E+07

Quantile fit is good - Bootstrap Output is Normal or nearly so

Jackknife Results

Bootstrap Results (Raw Data)

1.67E+07

1.70E+07

1.66E+07 1.76E+07

1.35E+07

1.60E+07

Raw Data Results

1.69E+06

STATISTICAL ANALYSIS OF OCTANOL-WATER PARTITIONING COEFFICIENTS 

OBTAINED FROM EISLER AND BELISLE (1996)

Hexachlorobiphenyls

The data are best described as log-normally distributed and there were a sufficient number of 

detected values to perform statistical analysis. The CV is less than 100% 

1.36E+07 2.07E+06

42

1.86E+07

5.64E+07

91%

Natural Log-Transformed Results

1.35E+07 1.90E+06

Normal (Non-transformed) Results

Fail

7.91E-01

1.67E+07

1.23E+07

W-Test

9.42E-01

1.65E+07 1.82E+07

Quantile fit is good - Bootstrap Output is Normal or nearly so

Quantile fit is good - Bootstrap Output is Normal or nearly so

Pass

9.76E-01

W-Test

9.42E-01

Recommended Mean

Log Recommended UCL 10Kow

1.90E+06

2.41E-01

1.73E+07

MVUE of the log-mean

UCL based on H-statistic

8.68E-01 5%

I:\Projects\PRAM\33756123 Navy PCB HHRA\_WP\03000\REPORT\PRAM_ORISKANY-APP B.xls\Hexachlorobiphenyls-Kow

5/12/2005 4:33 PM

URS 2 = Using the Jackknife

MVUE=Minimum Variance Unbiased Estimator

UCL=Upper Confidence Interval
BOOTSTRAP RESULTS FOR OCTANOL-WATER PARTITIONING COEFFCIENTS FOR 

HEXACHLOROBIPHENYLS OBTAINED FROM EISLER AND BELISLE (1996)

Standard Bootstrap

0

10

20

30

40

50

60

70

1234567891011213141516171819202122324252627282930313233435363738394041424344546474849505152535455657585960616263646566768

Bootstrap Mean

Number of Datasets

Pivotal Bootstrap

0

10

20

30

40

50

60

123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960616263646566676869707172737475767778798081828384858687888990919293949596979899

Bootstrap t Value

Number of Datasets

Hall's Transformed t Bootstrap

0

10

20

30

40

50

60

70

123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960616263646566676869707172737475767778798081828384858687888990919293949596979899

Bootstrap Q Value

Number of Datasets

Standard Boot Q-Q Plot

0

0.2

0.4

0.6

0.8

1

1.2

1 87 173 259 345 431 517 603 689 775 861 947

StdBoot Exp

Std Boot Obs

Pivotal-Boot Q-Q Plot

0

0.2

0.4

0.6

0.8

1

1.2

1 85 169 253 337 421 505 589 673 757 841 925

Boot t Exp

Boot t Obs

Hall's t Transformed t Boot Q-Q Plot

0

0.2

0.4

0.6

0.8

1

1.2

1 86 171 256 341 426 511 596 681 766 851 936

Boot Q Exp

Boot Q Obs

I:\Projects\PRAM\33756123 Navy PCB HHRA\_WP\03000\REPORT\PRAM_ORISKANY-APP B.xls\B_Hexachlorobiphenyls-Kow
20323408 Log10 7.308

Congener Value 29257630 Log10 7.466

170 18923436 7.277

171 5058247 6.704

172 21727012 7.337 Number of Values

173 10641430 7.027 Maximum Value Minimum Value

174 13091819 7.117

175 15031420 7.177 Normal Mean Mean Standard Error

176 5847901 6.767 Standard Deviation Coefficient of Variance (%)

177 12217997 7.087 Dataset Skewness Fail 2.02E+00 Dataset Kurtosis Fail 7.33E+00

178 14028137 7.147 Tested for Normality NormalityResult (a = 0.05)

179 5457579 6.737 Critical Value Calculated Value for dataset

180 23280913 7.367 90% UCL using t-statistic 95% UCL using -t-statistic

181 13091819 7.117

182 16106456 7.207 MVUE of the log-mean Standard error of the log-me

183 16106456 7.207 Standard Deviation Coefficient of Variance (%)

184 7194490 6.857 Dataset Skewness Pass 2.56E-01 Dataset Kurtosis Pass 2.33E+00

185 85703785 7.933 Tested for Normality Normality Result (a = 0.05)

186 4977371 6.697 Critical Value Calculated Value for dataset

187 15031420 7.177 Anderson Darling (AD) A2 AD Probability Pass 9.45E-01

188 6714289 6.827 90% UCL of the MVUE 95% UCL of the MVUE

189 52119471 7.717

190 29308932 7.467 Jackknifed Mean Jackknifed Standard Error

191 36057864 7.557 90% UCL of the mean 95% UCL of the mean

192 33651157 7.527 90% UCL of the MVUE2 95% UCL of the MVUE2

193 33651157 7.527

Standard Bootstrap Mean 2.05E+07 90% UCL 2.52E+07 95% UCL 2.66E+07

Skewness 5.50E-01 Kurtosis 3.48E+00

Pivitol (t) Bootstrap 90% UCL 95% UCL

Skewness -1.2E+00 Kurtosis 5.69E+00

Hall's t Bootstrap 90% UCL 95% UCL

Skewness -1.8E+00 Kurtosis 7.95E+00

2.51E+07

2.55E+07

Quantile fit is poor do not use Bootstrap Results

Jackknife Results

Bootstrap Results (Raw Data)

2.70E+07

2.65E+07

2.87E+07 3.19E+07

2.06E+07

2.55E+07

Raw Data Results

4.98E+06

STATISTICAL ANALYSIS OF OCTANOL-WATER PARTITIONING COEFFICIENTS 

OBTAINED FROM EISLER AND BELISLE (1996)

Heptachlorobiphenyls

The data are best described as log-normally distributed and there were a sufficient number of 

detected values to perform statistical analysis. The CV is less than 100% 

2.03E+07 3.41E+06

24

2.93E+07

8.57E+07

88%

Natural Log-Transformed Results

2.06E+07 3.72E+06

Normal (Non-transformed) Results

Fail

7.58E-01

2.70E+07

1.82E+07

W-Test

9.16E-01

2.92E+07 3.25E+07

Quantile fit is good - Bootstrap Output is Normal or nearly so

Quantile fit is good - Bootstrap Output is Normal or nearly so

Pass

9.62E-01

W-Test

9.16E-01

Recommended Mean

Log Recommended UCL 10Kow

3.72E+06

2.91E-01

2.68E+07

MVUE of the log-mean

UCL based on H-statistic

7.57E-01 5%

I:\Projects\PRAM\33756123 Navy PCB HHRA\_WP\03000\REPORT\PRAM_ORISKANY-APP B.xls\Heptachlorobiphenyls-Kow

5/12/2005 4:33 PM

URS 2 = Using the Jackknife

MVUE=Minimum Variance Unbiased Estimator

UCL=Upper Confidence Interval
BOOTSTRAP RESULTS FOR OCTANOL-WATER PARTITIONING COEFFCIENTS FOR 

HEPTACHLOROBIPHENYLS OBTAINED FROM EISLER AND BELISLE (1996)

Standard Bootstrap

0

10

20

30

40

50

60

70

123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960616263646566676869707172737475767778798081828384858687888990

Bootstrap Mean

Number of Datasets

Pivotal Bootstrap

0

10

20

30

40

50

60

70

123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960616263646566676869707172737475767778798081828384858687888990919293949596979899

Bootstrap t Value

Number of Datasets

Hall's Transformed t Bootstrap

0

20

40

60

80

100

123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960616263646566676869707172737475767778798081828384858687888990919293949596979899100

Bootstrap Q Value

Number of Datasets

Standard Boot Q-Q Plot

0

0.2

0.4

0.6

0.8

1

1.2

1 86 171 256 341 426 511 596 681 766 851 936

StdBoot Exp

Std Boot Obs

Pivotal-Boot Q-Q Plot

0

0.2

0.4

0.6

0.8

1

1.2

1 85 169 253 337 421 505 589 673 757 841 925

Boot t Exp

Boot t Obs

Hall's t Transformed t Boot Q-Q Plot

0

0.2

0.4

0.6

0.8

1

1.2

1 85 169 253 337 421 505 589 673 757 841 925

Boot Q Exp

Boot Q Obs

I:\Projects\PRAM\33756123 Navy PCB HHRA\_WP\03000\REPORT\PRAM_ORISKANY-APP B.xls\B_Heptachlorobiphenyls-Kow
94701742 Log10 7.976

Congener Value 167287874 Log10 8.223

194 481947798 8.683

195 36897760 7.567

196 45394162 7.657 Number of Values

197 20276827 7.307 Maximum Value Minimum Value

198 42364297 7.627

199 16106456 7.207 Normal Mean Mean Standard Error

200 18923436 7.277 Standard Deviation Coefficient of Variance (%)

201 42364297 7.627 Dataset Skewness Fail 1.84E+00 Dataset Kurtosis Pass 5.10E+00

202 264850014 8.423 Tested for Normality NormalityResult (a = 0.05)

203 45394162 7.657 Critical Value Calculated Value for dataset

204 20276827 7.307 90% UCL using t-statistic 95% UCL using -t-statistic

205 101624869 8.007

MVUE of the log-mean Standard error of the log-me

Standard Deviation Coefficient of Variance (%)

Dataset Skewness Pass 9.04E-01 Dataset Kurtosis Pass 2.52E+00

Tested for Normality Normality Result (a = 0.05)

Critical Value Calculated Value for dataset

Anderson Darling (AD) A2 AD Probability Pass 5.27E-01

90% UCL of the MVUE 95% UCL of the MVUE

Jackknifed Mean Jackknifed Standard Error

90% UCL of the mean 95% UCL of the mean

90% UCL of the MVUE2 95% UCL of the MVUE2

Standard Bootstrap Mean 9.48E+07 90% UCL 1.46E+08 95% UCL 1.60E+08

Skewness 7.41E-01 Kurtosis 3.45E+00

Pivitol (t) Bootstrap 90% UCL 95% UCL

Skewness -3.4E+00 Kurtosis 1.52E+01

Hall's t Bootstrap 90% UCL 95% UCL

Skewness -4.8E+00 Kurtosis 3.49E+01

1.26E+08

1.50E+08

Quantile fit is poor do not use Bootstrap Results

Jackknife Results

Bootstrap Results (Raw Data)

1.67E+08

1.42E+08

2.95E+08 4.52E+08

9.47E+07

1.50E+08

Raw Data Results

1.61E+07

STATISTICAL ANALYSIS OF OCTANOL-WATER PARTITIONING COEFFICIENTS 

OBTAINED FROM EISLER AND BELISLE (1996)

Octachlorobiphenyls

There is a sufficient number of values for statistical analysis - the data were found to be nonnormally distributed and the number of samples is below 15 

8.17E+07 2.70E+07

12

2.31E+08

4.82E+08

148%

Natural Log-Transformed Results

9.47E+07 4.04E+07

Normal (Non-transformed) Results

Fail

6.03E-01

1.67E+08

1.40E+08

W-Test

8.59E-01

2.92E+08 3.58E+08

Quantile fit is good - Bootstrap Output is Normal or nearly so

Quantile fit is poor do not use Bootstrap Results

Fail

8.56E-01

W-Test

8.59E-01

Recommended Mean

Log Recommended UCL 10Kow

4.04E+07

7.38E-01

1.74E+08

Jackknife Mean

Jackknifed UCL

1.06E+00 6%

I:\Projects\PRAM\33756123 Navy PCB HHRA\_WP\03000\REPORT\PRAM_ORISKANY-APP B.xls\Octachlorobiphenyls-Kow

5/12/2005 4:32 PM

URS 2 = Using the Jackknife

MVUE=Minimum Variance Unbiased Estimator

UCL=Upper Confidence Interval
BOOTSTRAP RESULTS FOR OCTANOL-WATER PARTITIONING COEFFCIENTS FOR 

OCTACHLOROBIPHENYLS OBTAINED FROM EISLER AND BELISLE (1996)

Standard Bootstrap

0

10

20

30

40

50

60

70

123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960616263646566676869707172737475767778798081828384858687888990919293949596979899100

Bootstrap Mean

Number of Datasets

Pivotal Bootstrap

0

20

40

60

80

100

120

140

160

123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960616263646566676869707172737475767778798081828384858687888990919293949596979899100

Bootstrap t Value

Number of Datasets

Hall's Transformed t Bootstrap

0

50

100

150

200

250

300

123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960616263646566676869707172737475767778798081828384858687888990919293949596979899100

Bootstrap Q Value

Number of Datasets

Standard Boot Q-Q Plot

0

0.2

0.4

0.6

0.8

1

1.2

1 87 173 259 345 431 517 603 689 775 861 947

StdBoot Exp

Std Boot Obs

Pivotal-Boot Q-Q Plot

0

0.2

0.4

0.6

0.8

1

1.2

1 85 169 253 337 421 505 589 673 757 841 925

Boot t Exp

Boot t Obs

Hall's t Transformed t Boot Q-Q Plot

0

0.2

0.4

0.6

0.8

1

1.2

1 86 171 256 341 426 511 596 681 766 851 936

Boot Q Exp

Boot Q Obs

I:\Projects\PRAM\33756123 Navy PCB HHRA\_WP\03000\REPORT\PRAM_ORISKANY-APP B.xls\B_Octachlorobiphenyls-Kow
Compound

Solubility 

(ppb) log S Koc

log 

Koc

Monochlorobiphenyls

2- 5,900 3.77 2,951 3.47

3- 3,500 3.54 4,168 3.62

4- 1,190 3.08 7,943 3.90

Dichlorobiphenyls

2,4- 1,400 3.15 7,244 3.86

2,2'- 1,500 3.18 6,918 3.84

2,4'- 1,260 3.10 8,000 3.90

4,4'- 80 1.90 42,658 4.63

Trichlorobiphenyls

2,4,4'- 85 1.93 40,738 4.61

2',3,4- 78 1.89 43,652 4.64

Tetrachlorobiphenyls

2,2',5,5'- 36 1.56 47,000 4.67

2,2',3,3'- 34 1.53 72,443 4.86

2,2',3,5'- 170 2.23 26,915 4.43

2,2',4,4'- 66 1.82 47,863 4.68

2,3',4,4'- 58 1.76 52,480 4.72

2,3',4,5'- 41 1.61 64,565 4.81

3,3',4,4'- 180 2.26 25,633 4.41

Pentachlorobiphenyls

2,2',3,4,5'- 22 1.34 95,324 4.98

2,2',4,5,5'- 31 1.49 76,948 4.89

Hexachlorobiphenyl

2,4,5,2',4',5'- 0.95 -0.02 1,200,000 6.08

SOLUBILITY, Koc, AND Kow OF SEVERAL PCBs

Source = Chou, S.F.J., and R.A. Griffin. 1986. Solubility and soil mobility of 

polychlorinated biphenyls. Chapter 5 IN PCBs in the Environment. J.S. Waid, 

Ed., CRC Press, Boca Ratob, FL.

s/msg/pcbs I:\Projects\PRAM\33756123 Navy PCB HHRA\_WP\03000\REPORT\PRAM_ORISKANY-APP B.xls\Kow
APPENDIX C 

CALCULATION OF HOMOLOG-SPECIFIC VAPOR PRESSURES 































APPENDIX E 

ORGANISM RESPIRATION REGRESSIONS 




APPENDIX F 

ZONE OF INFLUENCE 










APPENDIX G 

CLARIFICATIONS/ADDITIONS AND RESPONSES TO 

BIOLOGY TWG COMMENTS ON 

NAVY ENVIRONMENTAL HEALTH CENTER (NEHC) 

PROPOSED FOOD WEB DIET – WATER EXPOSURE MATRIX















APPENDIX H 

EXAMPLE PRAM OUTPUT 
ZOI = 2 
RISK ESTIMATES RME CTE RME CTE RME CTE 

Benthic fish (flounder) 7.29E-08 5.64E-09 4.25E-03 9.75E-04 2.14E-08 4.34E-Benthic shellfish (lobster) 2.12E-08 1.64E-09 1.24E-03 2.84E-04 6.22E-09 1.26E-Pelagic fish (jack) 3.57E-08 2.77E-09 2.08E-03 4.78E-04 1.05E-08 2.13E-Reef fish TL-IV (grouper) 6.94E-06 5.37E-07 4.05E-01 9.29E-02 2.04E-06 4.13E-Reef fish TL-III (triggerfish) 4.03E-06 3.12E-07 2.35E-01 5.39E-02 1.18E-06 2.40E-Reef shellfish (crab) 2.23E-06 1.73E-07 1.30E-01 2.98E-02 6.54E-07 1.33E-PREDICTED EXPOSURE CONCENTRATIONS (mg/kg in fresh weight)Benthic fish (flounder) 1.18E-03Benthic shellfish (lobster) 3.45E-04Pelagic fish (jack) 5.80E-04Reef fish TL-IV (grouper) 1.13E-01Reef fish TL-III (triggerfish) 6.55E-02Reef shellfish (crab) 3.62E-02RISK INPUTS - Adult RME CTE RISK INPUTS - Child 

Body Weight (BWa) (kg) 70 70 Body Weight (BWc) (kg) Exposure Frequency (EFa) (days) 365 365 Exposure Frequency (EFc) (days) Exposure Duration (EDa) (years) 24 3 Exposure Duration (EDc) (years) Ingestion Rate (IRa) (kg/day) 0.0261 0.0072 Ingestion Rate (IRc) (kg/day) Averaging Time for cancer (ATc) 25550 25550 Averaging Time for cancer (ATc) Averaging Time for noncancer (ATnc-adult) 8760 1095 Averaging Time for noncancer (ATnc-child) Slope Factor (mg/kg-day) 2 1 Slope Factor (mg/kg-day) Reference dose for PCBs (RfD) (mg/kg-day) 2.00E-05 4.50E-05 Reference dose for PCBs (RfD) (mg/kg-day) Fractional Ingestion factor (FI) 0.17 0.25 Fractional Ingestion factor (FI) Ingestion Rates Based on Data from Child - Adult IR scaling factor

Zone of Influence Multiplier 2

Scenario run on

RISK ESTIMATES FOR Ex-Oriskany CV34

Cancer Risk Adult & Child Hazard Adult & Child Cancer Risk Child 

PCB MODELING RESULTS - PROSPECTIVE RISK EVALUATION 

Gulf Coast 

5/11/05 13:36

PRAM_ORISKANY-APP H-ZOI 2.xls Estimate6/3/2005 3:15 PM

Based on NEHC PRAM Version 1.4c

May 2005 
PCB-LADEN MATERIAL INPUTS Fraction Release kg Material PCB Release Ex-Oriskany CV34

PCB Rate (ng/g-d) Onboard (ng/day) Displacement (tons) 

Ventilation Gaskets 3.14E-05 1.58E+03 1.46E+03 7.23E+04 Length (ft) Lubricants 1.03E-04 2.20E+03 0.00E+00 0.00E+00 Beam (ft) Foam Rubber Material 7.60E-03 2.62E+00 0.00E+00 0.00E+00

Black Rubber Material 5.29E-05 1.58E+03 5.40E+03 4.50E+05Electrical Cable 1.85E-03 2.79E+02 2.96E+05 1.53E+08Bulkhead Insulation Material 5.37E-04 6.76E+04 1.44E+04 5.22E+08Aluminum Paint 2.00E-05 1.11E+04 3.87E+05 8.62E+07Total 7.62E+08

ZOI = 2

1.56E+

6.00E

A 1.00E

B 1.50E

C 5.00E+

D 1.00E

E 3.00E

F 6.60E

Air Column

Air 1.56E

Upper Water Colum

Water 2.33E

TSS 1.56E

Lower Water Colum

Water 7.24E

TSS 4.82E

Inside Vessel

Water 5.38E+

TSS 3.59E

Sediment Bed

Sediment 7.78E

Abiotic Inputs Total PCB concentrationsAir Column Air Column

Active air space height above water column (m) 10 Air 6.68E-

Spatial Footprint 

Volu

Modeled D

Outside th

A

C

D

E E

E

VESSEL

B

Pycnocline

PRAM_ORISKANY-APP H-ZOI 2.xls Estimate6/3/2005 3:15 PM

Based on NEHC PRAM Version 1.4c

May 2005 
Air current (m/h) 13677 Upper Water Column

Upper Water Column Freely dissolved in water 1.02E-

Temperature (°C) 24.5 Suspended solids 1.33E-Water depth (m) 15 Dissolved organic carbon 1.78E-Total suspended solids (mg/L) 10 Lower Water ColumnDissolved organic carbon (mg/L) 0.6 Freely dissolved in water 4.39E-Dissolved oxygen (mg/L) 6.12 Suspended solids 1.08E-

Lower Water Column Dissolved organic carbon 9.88E-

Temperature (°C) 19.5 Inside VesselWater depth (m) 50 Freely dissolved in water 1.80E-Total suspended solids (mg/L) 10 Suspended solids 4.44E-Dissolved organic carbon (mg/L) 0.6 Dissolved organic carbon 4.06E-Dissolved oxygen (mg/L) 4.59 Sediment Bed

Inside Vessel Freely dissolved in pore water 4.39E-

Temperature (°C) 19.5 Bedded sediment 7.19E-

Total suspended solids (mg/L) 10 Dissolved organic carbon in pore water 9.88E-Dissolved organic carbon (mg/L) 0.6 Total PCB concentrations in biotaDissolved oxygen (mg/L) 4.59 Pelagic Community 

Sediment Bed Phytoplankton (TL-I) 1.67E-09 mg/kg 

Sediment density (g/cm3) 1.5 Zooplankton (TL-II) 7.72E-05 mg/kg Active sediment depth (m) 0.1 Planktivore (TL-III) 3.74E-04 mg/kg Sediment fraction organic carbon 0.01 Piscivore (TL-IV) 5.80E-04 mg/kg 

All Regions Reef / Vessel Community 

Suspended solids density (g/cm3) 1.5 Attached Algae (TL-I) 7.23E-06 mg/kg 

Suspended solids fraction organic carbon 0.15 Sessile filter feeder (TL-II) 1.58E-04 mg/kg Dissolved organic carbon density (g/cm3) 1 Invertebrate Omnivore (TL-II) 1.69E-02 mg/kg Water current - to out of the ZOI (m/h) 926 Invertebrate Forager (TL-III) 3.62E-02 mg/kg Water current - inside to outside the vessel (m/h) 9.26 Vertebrate Forager (TL-III) 6.55E-02 mg/kg 

Predator (TL-IV) 1.13E-01 mg/kg 

Benthic Community 

Infaunal invert. (TL-II) 5.48E-05 mg/kg 

Epifaunal invert. (TL-II) 1.51E-04 mg/kg Forager (TL-III) 3.45E-04 mg/kg Predator (TL-IV) 1.18E-03 mg/kg 

PRAM_ORISKANY-APP H-ZOI 2.xls Estimate6/3/2005 3:15 PM

Based on NEHC PRAM Version 1.4c

May 2005 
Scenario Run on 10/21/2004 14:10

PCB Homolog Mono Di Tri Tetra Penta Hexa Hepta Octa Nona DeMolecular Weight (g/mol) 1.89E+02 2.23E+02 2.58E+02 2.92E+02 3.26E+02 3.61E+02 3.95E+02 4.30E+02 4.64E+02 4.99ESolubility (mg/L) 2.91E+00 6.78E-01 8.14E-02 6.67E-02 2.61E-02 9.50E-04 2.30E-04 2.11E-08 4.02E-09 1.69E

Solubility (mol/m3) 1.54E-02 3.04E-03 3.16E-04 2.28E-04 8.00E-05 2.63E-06 5.82E-07 4.91E-11 8.65E-12 3.38E

Vapor Pressure (Pa) 6.32E-01 1.41E-01 5.11E-02 2.08E-02 2.96E-03 3.43E-03 2.56E-04 8.65E-05 2.77E-05 1.41E

Henry's (Pa-m3/mol) 4.10E+01 4.65E+01 1.62E+02 9.10E+01 3.70E+01 1.30E+03 4.40E+02 1.76E+06 3.20E+06 4.18E

log10Kow = 4.47 5.24 5.52 5.92 6.50 6.98 7.19 7.70 8.35 9.6

log10Koc = 3.66 4.06 4.63 4.65 4.94 6.08 6.34 6.46 6.97 7.9

log10Kdoc = 3.34 4.11 4.39 4.79 5.51 5.85 6.06 6.57 7.22 8.4

Chemical emission rate (g/day) 1.37E-05 1.12E-01 9.95E-03 1.69E-01 3.20E-01 7.57E-02 7.37E-02 0.00E+00 8.28E-04 4.62E

Chemical emission rate (mol/hr) 3.03E-09 2.09E-05 1.61E-06 2.42E-05 4.08E-05 8.74E-06 7.77E-06 0.00E+00 7.43E-08 3.86E

Biodegradation in sediment (1/hr) 0 0 0 0 0 0 0 000

Biodegradation in water (1/hr) 0 0 0 0 0 0 0 000

Ventilation 

Gaskets Lubricants Foam Rubber Material Black Rubber Material Electrical Cable Bulkhead Insulation Material Aluminized Paint

Fraction PCB in Material (wt/wt) 0.0000314 0.000103 0.76% 0.0000529 0.00185 0.000537 0.00002

Material Mass Onboard (kg) 1459 0 0 5397 296419 14379 386528Total PCBs (kg) 0.0458126 0 0 0.2855013 548.37515 7.721523 7.73056

Total PCB Release rate (ng/g-PCB per day) 1.58E+03 2.20E+03 2.62E+00 1.58E+03 2.79E+02 6.76E+04 1.11E+04

Ventilation 

Gaskets Lubricants Foam Rubber Material Black Rubber Material Electrical Cable Bulkhead Insulation Material Aluminized Paint

Monochlorobiphenyl 4.14E+01 3.47E+01 0.00E+00 4.14E+01 0.00E+00 0.00E+00 0.00E+00Dichlorobiphenyl 1.27E+03 1.72E+02 3.08E-02 1.27E+03 2.03E+02 5.36E+00 0.00E+00Trichlorobiphenyl 5.66E+01 8.97E+01 7.63E-02 5.66E+01 1.14E+00 9.44E+02 2.61E+02Tetrachlorobiphenyl 1.44E+02 1.08E+03 1.29E+00 1.44E+02 1.57E+01 2.07E+04 1.23E+02Pentachlorobiphenyl 6.31E+01 6.60E+02 3.90E-02 6.31E+01 1.80E+01 3.79E+04 2.24E+03Hexachlorobiphenyl 0.00E+00 9.42E+01 5.34E-01 0.00E+00 2.41E+01 6.76E+03 1.33E+03Heptachlorobiphenyl 5.04E+00 7.17E+01 6.46E-01 5.04E+00 1.47E+01 1.30E+03 7.19E+03Octachlorobiphenyl 0.00E+00 0.00E+00 0.00E+00 0.00E+00 0.00E+00 0.00E+00 0.00E+00Nonachlorobiphenyl 0.00E+00 0.00E+00 1.72E-03 0.00E+00 1.51E+00 0.00E+00 0.00E+00Decachlorobiphenyl 0.00E+00 0.00E+00 0.00E+00 0.00E+00 8.43E-01 0.00E+00 0.00E+00Total 1.58E+03 2.20E+03 2.62E+00 1.58E+03 2.79E+02 6.76E+04 1.11E+04Release Rates in nanograms PCB per Day Ventilation Gaskets Lubricants Foam Rubber Material Black Rubber Material Electrical Cable Bulkhead Insulation Material Aluminized Paint Total

Monochlorobiphenyl 1.90E+03 0.00E+00 0.00E+00 1.18E+04 0.00E+00 0.00E+00 0.00E+00 1.37E+04Dichlorobiphenyl 5.80E+04 0.00E+00 0.00E+00 3.62E+05 1.11E+08 4.14E+04 0.00E+00 1.12E+08Trichlorobiphenyl 2.59E+03 0.00E+00 0.00E+00 1.62E+04 6.25E+05 7.29E+06 2.02E+06 9.95E+06Tetrachlorobiphenyl 6.60E+03 0.00E+00 0.00E+00 4.11E+04 8.61E+06 1.60E+08 9.51E+05 1.69E+08Pentachlorobiphenyl 2.89E+03 0.00E+00 0.00E+00 1.80E+04 9.87E+06 2.93E+08 1.73E+07 3.20E+08Hexachlorobiphenyl 0.00E+00 0.00E+00 0.00E+00 0.00E+00 1.32E+07 5.22E+07 1.03E+07 7.57E+07Heptachlorobiphenyl 2.31E+02 0.00E+00 0.00E+00 1.44E+03 8.06E+06 1.01E+07 5.56E+07 7.37E+07Octachlorobiphenyl 0.00E+00 0.00E+00 0.00E+00 0.00E+00 0.00E+00 0.00E+00 0.00E+00 0.00E+00Nonachlorobiphenyl 0.00E+00 0.00E+00 0.00E+00 0.00E+00 8.28E+05 0.00E+00 0.00E+00 8.28E+05Decachlorobiphenyl 0.00E+00 0.00E+00 0.00E+00 0.00E+00 4.62E+05 0.00E+00 0.00E+00 4.62E+05Total 7.23E+04 0.00E+00 0.00E+00 4.50E+05 1.53E+08 5.22E+08 8.62E+07 7.62E+08

Release Rates in nanograms PCB per gram of PCB within the Material

PCB MODELING RESULTS - PROSPECTIVE RISK EVALUATION 

RISK ESTIMATES FOR Ex-Oriskany CV34 High-End Weight of PCB-Laden Materials

Supplemental Information

PRAM 1.4c Supplemental Information6/3/2005 3:16 PM

Based on NEHC PRAM Version 1.4c

May 2005 
PCB MODELING RESULTS - PROSPECTIVE RISK EVALUATION 

RISK ESTIMATES FOR Ex-Oriskany CV34 High-End Weight of PCB-Laden Materials

Supplemental Information

Air Mono Di Tri Tetra Penta Hexa Hepta Octa Nona DeFugacity (Pa) 3.22E-20 1.98E-16 1.30E-17 1.74E-16 1.91E-16 6.72E-18 2.40E-18 0.00E+00 8.51E-22 2.74E

Air concentration (g/m3) 2.47E-21 1.80E-17 1.37E-18 2.07E-17 2.54E-17 9.88E-19 3.86E-19 0.00E+00 1.61E-22 5.56EUpper Water Column Mono Di Tri Tetra Penta Hexa Hepta Octa Nona DeFugacity (Pa) 6.67E-18 5.04E-14 1.22E-14 9.85E-14 4.71E-14 5.99E-14 7.57E-15 0.00E+00 2.11E-14 9.20E

Water concentration (mg/L) 3.07E-17 2.42E-13 1.95E-14 3.16E-13 4.15E-13 1.66E-14 6.80E-15 0.00E+00 3.06E-18 1.10ESuspended solids concentration (mg/kg) 2.12E-14 4.15E-10 1.23E-10 2.14E-09 5.36E-09 2.99E-09 2.23E-09 0.00E+00 4.24E-12 1.44E

Dissolved organic carbon (mg/kg) 6.77E-14 3.09E-09 4.79E-10 1.95E-08 1.35E-07 1.16E-08 7.79E-09 0.00E+00 5.09E-11 3.25E

Lower Water Column Mono Di Tri Tetra Penta Hexa Hepta Octa Nona DeFugacity (Pa) 2.35E-14 1.81E-10 4.61E-11 3.80E-10 2.18E-10 6.75E-10 1.31E-10 0.00E+00 1.83E-09 9.95E

Water concentration (mg/L) 1.08E-13 8.67E-10 7.34E-11 1.22E-09 1.92E-09 1.87E-10 1.18E-10 0.00E+00 2.65E-13 1.19ESuspended solids concentration (mg/kg) 7.47E-11 1.48E-06 4.64E-07 8.25E-06 2.48E-05 3.37E-05 3.87E-05 0.00E+00 3.68E-07 1.55E

Dissolved organic carbon (mg/kg) 2.38E-10 1.11E-05 1.80E-06 7.54E-05 6.26E-04 1.31E-04 1.35E-04 0.00E+00 4.41E-06 3.52E

Inside the Vessel Mono Di Tri Tetra Penta Hexa Hepta Octa Nona DeFugacity (Pa) 9.67E-12 7.43E-08 1.89E-08 1.56E-07 8.96E-08 2.77E-07 5.40E-08 0.00E+00 7.51E-07 4.09E

Water concentration (mg/L) 4.45E-11 3.57E-07 3.02E-08 5.02E-07 7.90E-07 7.68E-08 4.85E-08 0.00E+00 1.09E-10 4.88ESuspended solids concentration (mg/kg) 3.07E-08 6.11E-04 1.91E-04 3.39E-03 1.02E-02 1.39E-02 1.59E-02 0.00E+00 1.51E-04 6.38E

Dissolved organic carbon (mg/kg) 9.80E-08 4.54E-03 7.41E-04 3.10E-02 2.57E-01 5.38E-02 5.56E-02 0.00E+00 1.81E-03 1.45E

Sediment Bed Mono Di Tri Tetra Penta Hexa Hepta Octa Nona DeFugacity (Pa) 2.35E-14 1.81E-10 4.61E-11 3.80E-10 2.18E-10 6.75E-10 1.31E-10 0.00E+00 1.83E-09 9.95E

Pore Water concentration (mg/L) 1.08E-13 8.67E-10 7.34E-11 1.22E-09 1.92E-09 1.87E-10 1.18E-10 0.00E+00 2.65E-13 1.19ESediment concentration (mg/kg) 4.98E-12 9.90E-08 3.09E-08 5.50E-07 1.65E-06 2.25E-06 2.58E-06 0.00E+00 2.45E-08 1.03EBioenergetic Inputs

Species Body Weight Lipid Moisture Caloric Density GE to ME Met Energy Caloric Density Production Respiration Excre

(kg) (%-dw) (%) (kcal/g-dry weight) Fraction (kcal/kg-lipid) (kcal/kg-lipid) (% of total) (% of total) (% of 

Pelagic CommunityPhytoplankton (TL-I) Algae 10% 84% 2.36 0.6 13748 22913 Zooplankton (TL-II) copepods 0.000005 22% 76% 3.6 0.65 10636 16364 18% 24% 58Planktivore (TL-III) herring 0.05 28% 75% 4.9 0.7 12206 17438 20% 60% 20Piscivore (TL-IV) jack 0.5 28% 75% 4.9 0.7 12206 17438 20% 60% 20Reef / Vessel CommunityAttached Algae (TL-I) Algae 10% 84% 2.36 0.6 13748 22913 Sessile filter feeder (TL-II) bivalves (w/o shell) 0.05 5% 82% 4.6 0.65 59800 92000 28% 31% 41Invertebrate Omnivore (TL-II) urchin 0.05 29% 82% 4.6 0.65 10310 15862 7% 25% 68Invertebrate Forager (TL-III) crab 1 9% 74% 2.7 0.65 19118 29412 28% 59% 13Vertebrate Forager (TL-III) triggerfish 1 28% 75% 4.9 0.7 12206 17438 20% 60% 20Predator (TL-IV) grouper 1.5 28% 75% 4.9 0.7 12206 17438 20% 60% 20Benthic CommunityInfaunal invert. (TL-II) polychaete 0.01 6% 84% 4.6 0.65 50000 76923 71% 26% 3% Epifaunal invert. (TL-II) nematode 0.01 6% 82% 4.6 0.65 50000 76923 31% 19% 50Forager (TL-III) lobster 2 9% 74% 2.7 0.65 19118 29412 28% 59% 13Predator (TL-IV) flounder 3 22% 75% 4.9 0.7 15591 22273 20% 60% 20

PRAM 1.4c Supplemental Information6/3/2005 3:16 PM

Based on NEHC PRAM Version 1.4c

May 2005 
PCB MODELING RESULTS - PROSPECTIVE RISK EVALUATION 

RISK ESTIMATES FOR Ex-Oriskany CV34 High-End Weight of PCB-Laden Materials

Supplemental Information

Bioenergetic Inputs Resp. Rate Resp. Rate Consumption Growth Rate Consumption Consumption

1 gO2 kcal 1 g-wt weight kcal As a 

Pelagic Community day kg-lipid-day kg-lipid-day day g-wt weight-d-wet weight-da body w

Phytoplankton (TL1) AlgaeZooplankton (TL-II) copepods 0.006375522 0 0.039935335 0.015425453 84.24400867 1286.168071 0.014147849 0.32636028 0.06790967 32.Planktivore (TL-III) herring 0.0033 -0.227 0.0548 0.004949927 21.1649 129.2512977 0.001482433 0.01616792 0.0090799 1.6Piscivore (TL-IV) jack 0.001118602 -0.55 0.12 0.000630951 2.697821256 16.47524431 0.000188961 0.00139796 0.00115739 0.1Reef / Vessel CommunityAttached Algae AlgaeSessile filter feeder (TL-II) bivalves (w/o shell) 0.012 0 0.036 0.024213411 581.8482643 6877.300342 0.020930914 0.24377539 0.0618957 24.4Invertebrate Omnivore (TL-II) urchin 0.000675466 0 0.079181846 0.003163548 13.1069075 192.1012396 0.000847751 0.03471132 0.01002768 3.5Invertebrate Forager (TL-III) crab 0.001158234 0 0.071193202 0.004642088 60.75673491 377.3221989 0.003592107 0.01678102 0.00900593 1.7Vertebrate Forager (TL-III) triggerfish 0.015181024 -0.415 0.061 0.002837229 12.13142452 74.08503521 0.00084971 0.00907693 0.00520447 0.9Predator (TL-IV) grouper 0.00279 -0.355 0.0811 0.001011362 4.324384181 26.40845301 0.000302889 0.00264734 0.00185519 0.3Benthic CommunityInfaunal invert. (TL-II) polychaete 0.001682129 0 0.071034762 0.006721006 135.0382801 1903.064429 0.017565285 0.09800757 0.01820852 9.8Epifaunal invert. (TL-II) nematode 0.001682129 0 0.071034762 0.006721006 135.0382801 2604.19343 0.0104949 0.09262416 0.02803154 9.3Forager (TL-III) lobster 0.0035 -0.13 0.066 0.00471923 61.76639253 383.5925529 0.003651801 0.01899736 0.00915559 1.9Predator (TL-IV) flounder 0.0046 -0.24 0.067 0.002486878 13.58174479 82.94195291 0.000744785 0.00974341 0.00456181 1.0Dietary Preferences

Suspended Solids

(Epilimnion)

Suspended 

Solids

(Hypolimnion)

Sediment Phytoplankton Zooplankton Pelagic Plankitivore Attached Algae Reef Sessile Filter Feeder Invertebrate Omnivore Reef Invertebrate Forager Re

Verte

Fora

Pelagic CommunityPhytoplankton (TL1)Zooplankton (TL-II) 15% 15% 70%Planktivore (TL-III) 100%Piscivore (TL-IV) 10% 90%Reef / Vessel CommunityAttached AlgaeSessile filter feeder (TL-II) 10% 80% 10%Invertebrate Omnivore (TL-II) 80% 20%Invertebrate Forager (TL-III) 5% 5% 5% 35% 50%Vertebrate Forager (TL-III) 19% 19% 15% 22% Predator (TL-IV) 15% 60Benthic CommunityInfaunal invert. (TL-II) 50% 30% 20%Epifaunal invert. (TL-II) 25% 30% 20% Forager (TL-III) 5% Predator (TL-IV) 2% 

Respiration Rate Allometric Regression Parameters

a b1 b2

PRAM 1.4c Supplemental Information6/3/2005 3:16 PM

Based on NEHC PRAM Version 1.4c

May 2005 
PCB MODELING RESULTS - PROSPECTIVE RISK EVALUATION 

RISK ESTIMATES FOR Ex-Oriskany CV34 High-End Weight of PCB-Laden Materials

Supplemental Information

Water Exposures

Upper Water 

Column

Lower Water

Column Vessel Interior Sediment Pore Water G

Pelagic Community Sediment (kcal/kg-oc) 114Phytoplankton (TL1) Algae 100% Suspended Sediment (kcal/kg-oc) 114

Zooplankton (TL-II) copepods 50% 50%Planktivore (TL-III) herring 80% 20%Piscivore (TL-IV) jack 80% 20%Reef / Vessel CommunityAttached Algae Algae 100%Sessile filter feeder (TL-II) bivalves (w/o shell) 100%Invertebrate Omnivore (TL-II) urchin 80% 20%Invertebrate Forager (TL-III) crab 70% 30%Vertebrate Forager (TL-III) triggerfish 70% 30%Predator (TL-IV) grouper 80% 20%Benthic CommunityInfaunal invert. (TL-II) polychaete 20% 80%Epifaunal invert. (TL-II) nematode 50% 50%Forager (TL-III) lobster 75% 25%Predator (TL-IV) flounder 90% 10%Respiratory Efficiencies Mono Di Tri Tetra Penta Hexa Hepta Octa Nona DeLow body weight (<100g) 4.335E-01 8.000E-01 8.000E-01 8.000E-01 4.492E-01 2.582E-01 2.018E-01 1.127E-01 5.303E-02 1.255High body weight (>100g) 5.000E-01 5.000E-01 5.000E-01 5.000E-01 3.769E-01 2.857E-01 2.526E-01 1.888E-01 1.295E-01 6.299Dietary Assimilation Efficiencies 27% 46% 53% 62% 69% 69% 68% 59% 44% 16Tissue Conc. (mg/kg-lipid) Mono Di Tri Tetra Penta Hexa Hepta Octa Nona DecaPelagic CommunityPhytoplankton (TL1) 9.143E-13 2.422E-08 1.948E-09 3.159E-08 4.150E-08 1.659E-09 6.797E-10 0.000E+00 3.062E-13 1.097E-15Zooplankton (TL-II) 7.287E-09 2.706E-04 2.729E-05 5.151E-04 5.109E-04 7.310E-05 6.504E-05 0.000E+00 3.261E-07 4.821E-08Planktivore (TL-III) 1.647E-09 2.291E-04 4.178E-05 1.528E-03 2.723E-03 4.285E-04 3.717E-04 0.000E+00 1.230E-06 6.474E-08Piscivore (TL-IV) 4.305E-10 4.039E-05 1.109E-05 8.926E-04 4.773E-03 1.285E-03 1.257E-03 0.000E+00 3.671E-06 8.006E-08Reef / Vessel CommunityAttached Algae 3.222E-09 8.672E-05 7.339E-06 1.220E-04 1.920E-04 1.868E-05 1.179E-05 0.000E+00 2.653E-08 1.186E-09Sessile filter feeder (TL-II) 1.037E-07 3.499E-03 3.456E-04 6.498E-03 6.291E-03 5.571E-04 4.034E-04 0.000E+00 1.291E-06 1.401E-07Invertebrate Omnivore (TL-II) 2.898E-07 2.252E-02 3.328E-03 1.071E-01 1.730E-01 1.224E-02 6.420E-03 0.000E+00 4.488E-06 6.064E-08Invertebrate Forager (TL-III) 2.192E-06 8.951E-02 1.334E-02 4.503E-01 8.597E-01 6.798E-02 3.772E-02 0.000E+00 4.148E-05 2.711E-06Vertebrate Forager (TL-III) 2.015E-07 1.416E-02 3.046E-03 1.785E-01 6.347E-01 6.428E-02 3.756E-02 0.000E+00 4.214E-05 1.385E-06Predator (TL-IV) 1.116E-07 7.257E-03 1.715E-03 1.498E-01 1.156E+00 1.771E-01 1.137E-01 0.000E+00 1.222E-04 2.685E-06Benthic CommunityInfaunal invert. (TL-II) 2.628E-08 1.032E-03 1.073E-04 2.122E-03 2.130E-03 1.950E-04 1.425E-04 0.000E+00 3.977E-07 2.834E-08Epifaunal invert. (TL-II) 3.259E-08 1.919E-03 2.289E-04 5.181E-03 5.709E-03 5.472E-04 4.040E-04 0.000E+00 1.015E-06 5.565E-08Forager (TL-III) 1.903E-08 1.051E-03 1.607E-04 4.856E-03 7.236E-03 6.765E-04 4.610E-04 0.000E+00 7.349E-07 1.686E-08Predator (TL-IV) 1.685E-09 2.802E-04 7.385E-05 4.574E-03 1.378E-02 1.658E-03 1.171E-03 0.000E+00 1.505E-06 2.213E-08

Energy Estimates for Suspended 

PRAM 1.4c Supplemental Information6/3/2005 3:16 PM

Based on NEHC PRAM Version 1.4c

May 2005 
PCB MODELING RESULTS - PROSPECTIVE RISK EVALUATION 

RISK ESTIMATES FOR Ex-Oriskany CV34 High-End Weight of PCB-Laden Materials

Supplemental Information

Tissue Conc. (mg/kg-WW) Mono Di Tri Tetra Penta Hexa Hepta Octa Nona Deca Total PPelagic CommunityPhytoplankton (TL1) 1.507E-14 3.991E-10 3.211E-11 5.207E-10 6.838E-10 2.735E-11 1.120E-11 0.000E+00 5.047E-15 1.807E-17 1.674Zooplankton (TL-II) 3.847E-10 1.429E-05 1.441E-06 2.720E-05 2.698E-05 3.860E-06 3.434E-06 0.000E+00 1.722E-08 2.545E-09 7.722Planktivore (TL-III) 1.157E-10 1.610E-05 2.935E-06 1.073E-04 1.913E-04 3.010E-05 2.611E-05 0.000E+00 8.639E-08 4.548E-09 3.740Piscivore (TL-IV) 3.024E-11 2.837E-06 7.791E-07 6.270E-05 3.353E-04 9.028E-05 8.828E-05 0.000E+00 2.579E-07 5.625E-09 5.804Reef / Vessel CommunityAttached Algae 5.309E-11 1.429E-06 1.209E-07 2.010E-06 3.165E-06 3.078E-07 1.944E-07 0.000E+00 4.372E-10 1.955E-11 7.228Sessile filter feeder (TL-II) 9.335E-10 3.149E-05 3.110E-06 5.848E-05 5.662E-05 5.014E-06 3.631E-06 0.000E+00 1.162E-08 1.261E-09 1.584Invertebrate Omnivore (TL-II) 1.513E-08 1.176E-03 1.737E-04 5.591E-03 9.032E-03 6.389E-04 3.351E-04 0.000E+00 2.343E-07 3.166E-09 1.695Invertebrate Forager (TL-III) 5.231E-08 2.136E-03 3.184E-04 1.075E-02 2.052E-02 1.623E-03 9.003E-04 0.000E+00 9.901E-07 6.469E-08 3.624Vertebrate Forager (TL-III) 1.415E-08 9.949E-04 2.140E-04 1.254E-02 4.459E-02 4.516E-03 2.638E-03 0.000E+00 2.960E-06 9.732E-08 6.550Predator (TL-IV) 7.841E-09 5.098E-04 1.205E-04 1.052E-02 8.122E-02 1.244E-02 7.984E-03 0.000E+00 8.585E-06 1.886E-07 1.128Benthic CommunityInfaunal invert. (TL-II) 2.514E-10 9.875E-06 1.026E-06 2.030E-05 2.038E-05 1.866E-06 1.363E-06 0.000E+00 3.805E-09 2.711E-10 5.482Epifaunal invert. (TL-II) 3.508E-10 2.066E-05 2.464E-06 5.577E-05 6.146E-05 5.891E-06 4.348E-06 0.000E+00 1.092E-08 5.990E-10 1.506Forager (TL-III) 4.541E-10 2.508E-05 3.835E-06 1.159E-04 1.727E-04 1.615E-05 1.100E-05 0.000E+00 1.754E-08 4.024E-10 3.447Predator (TL-IV) 9.265E-11 1.541E-05 4.062E-06 2.516E-04 7.580E-04 9.120E-05 6.440E-05 0.000E+00 8.279E-08 1.217E-09 1.185BAFs (L/kg-lipid) Mono Di Tri Tetra Penta Hexa Hepta Octa Nona DecaPelagic CommunityPhytoplankton (TL1) 2.979E+04 1.000E+05 1.000E+05 1.000E+05 1.000E+05 1.000E+05 1.000E+05 0.000E+00 1.000E+05 1.000E+05Zooplankton (TL-II) 1.347E+05 6.238E+05 7.436E+05 8.445E+05 5.320E+05 7.826E+05 1.103E+06 0.000E+00 2.458E+06 8.127E+06Planktivore (TL-III) 7.603E+04 1.320E+06 2.843E+06 6.258E+06 7.083E+06 1.146E+07 1.576E+07 0.000E+00 2.317E+07 2.729E+07Piscivore (TL-IV) 1.988E+04 2.326E+05 7.548E+05 3.655E+06 1.242E+07 3.439E+07 5.326E+07 0.000E+00 6.917E+07 3.375E+07Reef / Vessel CommunityAttached Algae 2.979E+04 1.000E+05 1.000E+05 1.000E+05 1.000E+05 1.000E+05 1.000E+05 0.000E+00 1.000E+05 1.000E+05Sessile filter feeder (TL-II) 9.590E+05 4.034E+06 4.709E+06 5.328E+06 3.276E+06 2.983E+06 3.420E+06 0.000E+00 4.867E+06 1.181E+07Invertebrate Omnivore (TL-II) 3.226E+04 3.127E+05 5.460E+05 1.057E+06 1.085E+06 7.891E+05 6.556E+05 0.000E+00 2.037E+05 6.157E+04Invertebrate Forager (TL-III) 1.633E+05 8.319E+05 1.465E+06 2.976E+06 3.608E+06 2.934E+06 2.578E+06 0.000E+00 1.260E+06 1.842E+06Vertebrate Forager (TL-III) 1.501E+04 1.316E+05 3.345E+05 1.180E+06 2.664E+06 2.774E+06 2.567E+06 0.000E+00 1.280E+06 9.414E+05Predator (TL-IV) 1.243E+04 1.008E+05 2.815E+05 1.479E+06 7.250E+06 1.142E+07 1.161E+07 0.000E+00 5.547E+06 2.726E+06Benthic CommunityInfaunal invert. (TL-II) 2.429E+05 1.190E+06 1.462E+06 1.740E+06 1.109E+06 1.044E+06 1.208E+06 0.000E+00 1.499E+06 2.389E+06Epifaunal invert. (TL-II) 3.013E+05 2.213E+06 3.119E+06 4.248E+06 2.973E+06 2.930E+06 3.425E+06 0.000E+00 3.825E+06 4.691E+06Forager (TL-III) 1.759E+05 1.212E+06 2.189E+06 3.981E+06 3.768E+06 3.622E+06 3.909E+06 0.000E+00 2.770E+06 1.421E+06Predator (TL-IV) 1.557E+04 3.231E+05 1.006E+06 3.750E+06 7.177E+06 8.877E+06 9.928E+06 0.000E+00 5.673E+06 1.865E+06Notes:Kow = octanol to water partitioning coefficient, Koc = organic carbon partitioning coefficient, Kdoc = dissolved organic carbon partitioning coefficientTL = trophic level, ww = wet weight

PRAM 1.4c Supplemental Information6/3/2005 3:16 PM

Based on NEHC PRAM Version 1.4c

May 2005 
PCB Concentrations Outside the Vessel

0.00E+00

1.00E-04

2.00E-04

3.00E-04

4.00E-04

5.00E-04

6.00E-04

7.00E-04

Mono Di Tri Tetra Penta Hexa Hepta Octa Nona Deca

PCB Homologue

PCB Concentration

Air concentration (g/m3) Water Concentration-LWC (mg/L)

Suspended solids concentration-LWC (mg/kg) Dissolved organic carbon-LWC (mg/kg)

Sediment concentration (mg/kg) Water Concentration-UWC (mg/L)

PCB Concentrations in Biota

0.00E+00

1.00E-02

2.00E-02

3.00E-02

4.00E-02

5.00E-02

6.00E-02

7.00E-02

8.00E-02

9.00E-02

Algae

copepods

herring

jack

Algae

bivalves (w/o shell)

urchin

crab

triggerfish

grouper

polychaete

nematode

lobster

flounder

Organisms by Community

PCB Tissue Concentration (mg/kg-ww)

Mono Di Tri Tetra Penta Hexa Hepta Octa Nona Deca

Pelagic Reef Benthic
PCB Release Rates by Homolog Group

0.00E+00

5.00E+07

1.00E+08

1.50E+08

2.00E+08

2.50E+08

3.00E+08

3.50E+08

Monochlorobiphenyl

Dichlorobiphenyl

Trichlorobiphenyl

Tetrachlorobiphenyl

Pentachlorobiphenyl

Hexachlorobiphenyl

Heptachlorobiphenyl

Octachlorobiphenyl

Nonachlorobiphenyl

Decachlorobiphenyl

PCB Homolog

PCB Release Rate (ng/d)

PCB Release Rates by Source Material

1.00E+00

1.00E+01

1.00E+02

1.00E+03

1.00E+04

1.00E+05

1.00E+06

1.00E+07

1.00E+08

1.00E+09

Ventilation Gaskets

Lubricants

Foam Rubber Material

Black Rubber Material

Electrical Cable

Bulkhead Insulation Material

Aluminized Paint

Source Material

PCB Release Rate (ng/d)
ZOI = 5 
RISK ESTIMATES RME CTE RME CTE RME CTE 

Benthic fish (flounder) 4.23E-08 3.28E-09 2.47E-03 5.66E-04 1.24E-08 2.52E-Benthic shellfish (lobster) 1.23E-08 9.53E-10 7.18E-04 1.65E-04 3.61E-09 7.33E-Pelagic fish (jack) 2.07E-08 1.61E-09 1.21E-03 2.78E-04 6.08E-09 1.23E-Reef fish TL-IV (grouper) 6.86E-06 5.31E-07 4.00E-01 9.18E-02 2.01E-06 4.08E-Reef fish TL-III (triggerfish) 3.98E-06 3.08E-07 2.32E-01 5.33E-02 1.17E-06 2.37E-Reef shellfish (crab) 2.21E-06 1.71E-07 1.29E-01 2.95E-02 6.48E-07 1.31E-PREDICTED EXPOSURE CONCENTRATIONS (mg/kg in fresh weight)Benthic fish (flounder) 6.88E-04Benthic shellfish (lobster) 2.00E-04Pelagic fish (jack) 3.37E-04Reef fish TL-IV (grouper) 1.11E-01Reef fish TL-III (triggerfish) 6.47E-02Reef shellfish (crab) 3.59E-02RISK INPUTS - Adult RME CTE RISK INPUTS - Child 

Body Weight (BWa) (kg) 70 70 Body Weight (BWc) (kg) Exposure Frequency (EFa) (days) 365 365 Exposure Frequency (EFc) (days) Exposure Duration (EDa) (years) 24 3 Exposure Duration (EDc) (years) Ingestion Rate (IRa) (kg/day) 0.0261 0.0072 Ingestion Rate (IRc) (kg/day) Averaging Time for cancer (ATc) 25550 25550 Averaging Time for cancer (ATc) Averaging Time for noncancer (ATnc-adult) 8760 1095 Averaging Time for noncancer (ATnc-child) Slope Factor (mg/kg-day) 2 1 Slope Factor (mg/kg-day) Reference dose for PCBs (RfD) (mg/kg-day) 2.00E-05 4.50E-05 Reference dose for PCBs (RfD) (mg/kg-day) Fractional Ingestion factor (FI) 0.17 0.25 Fractional Ingestion factor (FI) Ingestion Rates Based on Data from Child - Adult IR scaling factor

Zone of Influence Multiplier 5

Scenario run on

PCB MODELING RESULTS - PROSPECTIVE RISK EVALUATION 

Gulf Coast 

5/11/05 13:38

RISK ESTIMATES FOR Ex-Oriskany CV34

Cancer Risk Adult & Child Hazard Adult & Child Cancer Risk Child 

PRAM_ORISKANY-APP H-ZOI 5.xls Estimate6/3/2005 3:18 PM

Based on NEHC PRAM Version 1.4c

May 2005 
PCB-LADEN MATERIAL INPUTS Fraction Release kg Material PCB Release Ex-Oriskany CV34

PCB Rate (ng/g-d) Onboard (ng/day) Displacement (tons) 

Ventilation Gaskets 3.14E-05 1.58E+03 1.46E+03 7.23E+04 Length (ft) Lubricants 1.03E-04 2.20E+03 0.00E+00 0.00E+00 Beam (ft) Foam Rubber Material 7.60E-03 2.62E+00 0.00E+00 0.00E+00

Black Rubber Material 5.29E-05 1.58E+03 5.40E+03 4.50E+05Electrical Cable 1.85E-03 2.79E+02 2.96E+05 1.53E+08Bulkhead Insulation Material 5.37E-04 6.76E+04 1.44E+04 5.22E+08Aluminum Paint 2.00E-05 1.11E+04 3.87E+05 8.62E+07Total 7.62E+08

ZOI = 5

3.89E+

1.50E

A 1.00E

B 1.50E

C 5.00E+

D 1.00E

E 3.68E

F 1.34E

Air Column

Air 3.89E

Upper Water Colum

Water 5.83E

TSS 3.89E

Lower Water Colum

Water 1.89E

TSS 1.26E

Inside Vessel

Water 5.38E+

TSS 3.59E

Sediment Bed

Sediment 3.11E

Abiotic Inputs Total PCB concentrationsAir Column Air Column

Active air space height above water column (m) 10 Air 9.68E-

Modeled D

Outside th

Spatial Footprint 

Volu

A

C

D

E E

E

VESSEL

B

Pycnocline

PRAM_ORISKANY-APP H-ZOI 5.xls Estimate6/3/2005 3:18 PM

Based on NEHC PRAM Version 1.4c

May 2005 
Air current (m/h) 13677 Upper Water Column

Upper Water Column Freely dissolved in water 9.32E-

Temperature (°C) 24.5 Suspended solids 1.22E-Water depth (m) 15 Dissolved organic carbon 1.63E-Total suspended solids (mg/L) 10 Lower Water ColumnDissolved organic carbon (mg/L) 0.6 Freely dissolved in water 2.55E-Dissolved oxygen (mg/L) 6.12 Suspended solids 6.27E-

Lower Water Column Dissolved organic carbon 5.74E-

Temperature (°C) 19.5 Inside VesselWater depth (m) 50 Freely dissolved in water 1.80E-Total suspended solids (mg/L) 10 Suspended solids 4.44E-Dissolved organic carbon (mg/L) 0.6 Dissolved organic carbon 4.06E-Dissolved oxygen (mg/L) 4.59 Sediment Bed

Inside Vessel Freely dissolved in pore water 2.55E-

Temperature (°C) 19.5 Bedded sediment 4.18E-

Total suspended solids (mg/L) 10 Dissolved organic carbon in pore water 5.74E-Dissolved organic carbon (mg/L) 0.6 Total PCB concentrations in biotaDissolved oxygen (mg/L) 4.59 Pelagic Community 

Sediment Bed Phytoplankton (TL-I) 1.54E-09 mg/kg 

Sediment density (g/cm3) 1.5 Zooplankton (TL-II) 4.48E-05 mg/kg Active sediment depth (m) 0.1 Planktivore (TL-III) 2.17E-04 mg/kg Sediment fraction organic carbon 0.01 Piscivore (TL-IV) 3.37E-04 mg/kg 

All Regions Reef / Vessel Community 

Suspended solids density (g/cm3) 1.5 Attached Algae (TL-I) 4.20E-06 mg/kg 

Suspended solids fraction organic carbon 0.15 Sessile filter feeder (TL-II) 9.19E-05 mg/kg Dissolved organic carbon density (g/cm3) 1 Invertebrate Omnivore (TL-II) 1.67E-02 mg/kg Water current - to out of the ZOI (m/h) 926 Invertebrate Forager (TL-III) 3.59E-02 mg/kg Water current - inside to outside the vessel (m/h) 9.26 Vertebrate Forager (TL-III) 6.47E-02 mg/kg 

Predator (TL-IV) 1.11E-01 mg/kg 

Benthic Community 

Infaunal invert. (TL-II) 3.18E-05 mg/kg 

Epifaunal invert. (TL-II) 8.74E-05 mg/kg Forager (TL-III) 2.00E-04 mg/kg Predator (TL-IV) 6.88E-04 mg/kg 

PRAM_ORISKANY-APP H-ZOI 5.xls Estimate6/3/2005 3:18 PM

Based on NEHC PRAM Version 1.4c

May 2005 
Scenario Run on 10/21/2004 14:10

PCB Homolog Mono Di Tri Tetra Penta Hexa Hepta Octa Nona DeMolecular Weight (g/mol) 1.89E+02 2.23E+02 2.58E+02 2.92E+02 3.26E+02 3.61E+02 3.95E+02 4.30E+02 4.64E+02 4.99ESolubility (mg/L) 2.91E+00 6.78E-01 8.14E-02 6.67E-02 2.61E-02 9.50E-04 2.30E-04 2.11E-08 4.02E-09 1.69E

Solubility (mol/m3) 1.54E-02 3.04E-03 3.16E-04 2.28E-04 8.00E-05 2.63E-06 5.82E-07 4.91E-11 8.65E-12 3.38E

Vapor Pressure (Pa) 6.32E-01 1.41E-01 5.11E-02 2.08E-02 2.96E-03 3.43E-03 2.56E-04 8.65E-05 2.77E-05 1.41E

Henry's (Pa-m3/mol) 4.10E+01 4.65E+01 1.62E+02 9.10E+01 3.70E+01 1.30E+03 4.40E+02 1.76E+06 3.20E+06 4.18E

log10Kow = 4.47 5.24 5.52 5.92 6.50 6.98 7.19 7.70 8.35 9.6

log10Koc = 3.66 4.06 4.63 4.65 4.94 6.08 6.34 6.46 6.97 7.9

log10Kdoc = 3.34 4.11 4.39 4.79 5.51 5.85 6.06 6.57 7.22 8.4

Chemical emission rate (g/day) 1.37E-05 1.12E-01 9.95E-03 1.69E-01 3.20E-01 7.57E-02 7.37E-02 0.00E+00 8.28E-04 4.62E

Chemical emission rate (mol/hr) 3.03E-09 2.09E-05 1.61E-06 2.42E-05 4.08E-05 8.74E-06 7.77E-06 0.00E+00 7.43E-08 3.86E

Biodegradation in sediment (1/hr) 0 0 0 0 0 0 0 000

Biodegradation in water (1/hr) 0 0 0 0 0 0 0 000

Ventilation 

Gaskets Lubricants Foam Rubber Material Black Rubber Material Electrical Cable Bulkhead Insulation Material Aluminized Paint

Fraction PCB in Material (wt/wt) 0.0000314 0.000103 0.76% 0.0000529 0.00185 0.000537 0.00002

Material Mass Onboard (kg) 1459 0 0 5397 296419 14379 386528Total PCBs (kg) 0.0458126 0 0 0.2855013 548.37515 7.721523 7.73056

Total PCB Release rate (ng/g-PCB per day) 1.58E+03 2.20E+03 2.62E+00 1.58E+03 2.79E+02 6.76E+04 1.11E+04

Ventilation 

Gaskets Lubricants Foam Rubber Material Black Rubber Material Electrical Cable Bulkhead Insulation Material Aluminized Paint

Monochlorobiphenyl 4.14E+01 3.47E+01 0.00E+00 4.14E+01 0.00E+00 0.00E+00 0.00E+00Dichlorobiphenyl 1.27E+03 1.72E+02 3.08E-02 1.27E+03 2.03E+02 5.36E+00 0.00E+00Trichlorobiphenyl 5.66E+01 8.97E+01 7.63E-02 5.66E+01 1.14E+00 9.44E+02 2.61E+02Tetrachlorobiphenyl 1.44E+02 1.08E+03 1.29E+00 1.44E+02 1.57E+01 2.07E+04 1.23E+02Pentachlorobiphenyl 6.31E+01 6.60E+02 3.90E-02 6.31E+01 1.80E+01 3.79E+04 2.24E+03Hexachlorobiphenyl 0.00E+00 9.42E+01 5.34E-01 0.00E+00 2.41E+01 6.76E+03 1.33E+03Heptachlorobiphenyl 5.04E+00 7.17E+01 6.46E-01 5.04E+00 1.47E+01 1.30E+03 7.19E+03Octachlorobiphenyl 0.00E+00 0.00E+00 0.00E+00 0.00E+00 0.00E+00 0.00E+00 0.00E+00Nonachlorobiphenyl 0.00E+00 0.00E+00 1.72E-03 0.00E+00 1.51E+00 0.00E+00 0.00E+00Decachlorobiphenyl 0.00E+00 0.00E+00 0.00E+00 0.00E+00 8.43E-01 0.00E+00 0.00E+00Total 1.58E+03 2.20E+03 2.62E+00 1.58E+03 2.79E+02 6.76E+04 1.11E+04Release Rates in nanograms PCB per Day Ventilation Gaskets Lubricants Foam Rubber Material Black Rubber Material Electrical Cable Bulkhead Insulation Material Aluminized Paint Total

Monochlorobiphenyl 1.90E+03 0.00E+00 0.00E+00 1.18E+04 0.00E+00 0.00E+00 0.00E+00 1.37E+04Dichlorobiphenyl 5.80E+04 0.00E+00 0.00E+00 3.62E+05 1.11E+08 4.14E+04 0.00E+00 1.12E+08Trichlorobiphenyl 2.59E+03 0.00E+00 0.00E+00 1.62E+04 6.25E+05 7.29E+06 2.02E+06 9.95E+06Tetrachlorobiphenyl 6.60E+03 0.00E+00 0.00E+00 4.11E+04 8.61E+06 1.60E+08 9.51E+05 1.69E+08Pentachlorobiphenyl 2.89E+03 0.00E+00 0.00E+00 1.80E+04 9.87E+06 2.93E+08 1.73E+07 3.20E+08Hexachlorobiphenyl 0.00E+00 0.00E+00 0.00E+00 0.00E+00 1.32E+07 5.22E+07 1.03E+07 7.57E+07Heptachlorobiphenyl 2.31E+02 0.00E+00 0.00E+00 1.44E+03 8.06E+06 1.01E+07 5.56E+07 7.37E+07Octachlorobiphenyl 0.00E+00 0.00E+00 0.00E+00 0.00E+00 0.00E+00 0.00E+00 0.00E+00 0.00E+00Nonachlorobiphenyl 0.00E+00 0.00E+00 0.00E+00 0.00E+00 8.28E+05 0.00E+00 0.00E+00 8.28E+05Decachlorobiphenyl 0.00E+00 0.00E+00 0.00E+00 0.00E+00 4.62E+05 0.00E+00 0.00E+00 4.62E+05Total 7.23E+04 0.00E+00 0.00E+00 4.50E+05 1.53E+08 5.22E+08 8.62E+07 7.62E+08

Release Rates in nanograms PCB per gram of PCB within the Material

PCB MODELING RESULTS - PROSPECTIVE RISK EVALUATION 

RISK ESTIMATES FOR Ex-Oriskany CV34 High-End Weight of PCB-Laden Materials

Supplemental Information

PRAM 1.4c Supplemental Information6/3/2005 3:19 PM

Based on NEHC PRAM Version 1.4c

May 2005 
PCB MODELING RESULTS - PROSPECTIVE RISK EVALUATION 

RISK ESTIMATES FOR Ex-Oriskany CV34 High-End Weight of PCB-Laden Materials

Supplemental Information

Air Mono Di Tri Tetra Penta Hexa Hepta Octa Nona DeFugacity (Pa) 4.65E-20 2.86E-16 1.89E-17 2.52E-16 2.76E-16 9.75E-18 3.48E-18 0.00E+00 1.23E-21 3.97E

Air concentration (g/m3) 3.58E-21 2.60E-17 1.98E-18 3.00E-17 3.67E-17 1.43E-18 5.60E-19 0.00E+00 2.33E-22 8.06EUpper Water Column Mono Di Tri Tetra Penta Hexa Hepta Octa Nona DeFugacity (Pa) 6.12E-18 4.63E-14 1.12E-14 9.04E-14 4.32E-14 5.50E-14 6.95E-15 0.00E+00 1.94E-14 8.44E

Water concentration (mg/L) 2.82E-17 2.22E-13 1.79E-14 2.90E-13 3.81E-13 1.52E-14 6.24E-15 0.00E+00 2.81E-18 1.01ESuspended solids concentration (mg/kg) 1.95E-14 3.80E-10 1.13E-10 1.96E-09 4.92E-09 2.75E-09 2.05E-09 0.00E+00 3.89E-12 1.32E

Dissolved organic carbon (mg/kg) 6.21E-14 2.83E-09 4.39E-10 1.79E-08 1.24E-07 1.07E-08 7.15E-09 0.00E+00 4.67E-11 2.99E

Lower Water Column Mono Di Tri Tetra Penta Hexa Hepta Octa Nona DeFugacity (Pa) 1.37E-14 1.05E-10 2.67E-11 2.21E-10 1.27E-10 3.92E-10 7.63E-11 0.00E+00 1.06E-09 5.78E

Water concentration (mg/L) 6.28E-14 5.03E-10 4.26E-11 7.08E-10 1.11E-09 1.08E-10 6.85E-11 0.00E+00 1.54E-13 6.89ESuspended solids concentration (mg/kg) 4.34E-11 8.62E-07 2.69E-07 4.79E-06 1.44E-05 1.96E-05 2.25E-05 0.00E+00 2.13E-07 9.01E

Dissolved organic carbon (mg/kg) 1.38E-10 6.41E-06 1.05E-06 4.38E-05 3.63E-04 7.60E-05 7.85E-05 0.00E+00 2.56E-06 2.04E

Inside the Vessel Mono Di Tri Tetra Penta Hexa Hepta Octa Nona DeFugacity (Pa) 9.67E-12 7.43E-08 1.89E-08 1.56E-07 8.96E-08 2.77E-07 5.40E-08 0.00E+00 7.51E-07 4.09E

Water concentration (mg/L) 4.45E-11 3.57E-07 3.02E-08 5.02E-07 7.90E-07 7.68E-08 4.85E-08 0.00E+00 1.09E-10 4.88ESuspended solids concentration (mg/kg) 3.07E-08 6.11E-04 1.91E-04 3.39E-03 1.02E-02 1.39E-02 1.59E-02 0.00E+00 1.51E-04 6.38E

Dissolved organic carbon (mg/kg) 9.80E-08 4.54E-03 7.41E-04 3.10E-02 2.57E-01 5.38E-02 5.56E-02 0.00E+00 1.81E-03 1.45E

Sediment Bed Mono Di Tri Tetra Penta Hexa Hepta Octa Nona DeFugacity (Pa) 1.37E-14 1.05E-10 2.67E-11 2.21E-10 1.27E-10 3.92E-10 7.63E-11 0.00E+00 1.06E-09 5.78E

Pore Water concentration (mg/L) 6.28E-14 5.03E-10 4.26E-11 7.08E-10 1.11E-09 1.08E-10 6.85E-11 0.00E+00 1.54E-13 6.89ESediment concentration (mg/kg) 2.89E-12 5.75E-08 1.80E-08 3.19E-07 9.60E-07 1.30E-06 1.50E-06 0.00E+00 1.42E-08 6.01EBioenergetic Inputs

Species Body Weight Lipid Moisture Caloric Density GE to ME Met Energy Caloric Density Production Respiration Excre

(kg) (%-dw) (%) (kcal/g-dry weight) Fraction (kcal/kg-lipid) (kcal/kg-lipid) (% of total) (% of total) (% of 

Pelagic CommunityPhytoplankton (TL-I) Algae 10% 84% 2.36 0.6 13748 22913 Zooplankton (TL-II) copepods 0.000005 22% 76% 3.6 0.65 10636 16364 18% 24% 58Planktivore (TL-III) herring 0.05 28% 75% 4.9 0.7 12206 17438 20% 60% 20Piscivore (TL-IV) jack 0.5 28% 75% 4.9 0.7 12206 17438 20% 60% 20Reef / Vessel CommunityAttached Algae (TL-I) Algae 10% 84% 2.36 0.6 13748 22913 Sessile filter feeder (TL-II) bivalves (w/o shell) 0.05 5% 82% 4.6 0.65 59800 92000 28% 31% 41Invertebrate Omnivore (TL-II) urchin 0.05 29% 82% 4.6 0.65 10310 15862 7% 25% 68Invertebrate Forager (TL-III) crab 1 9% 74% 2.7 0.65 19118 29412 28% 59% 13Vertebrate Forager (TL-III) triggerfish 1 28% 75% 4.9 0.7 12206 17438 20% 60% 20Predator (TL-IV) grouper 1.5 28% 75% 4.9 0.7 12206 17438 20% 60% 20Benthic CommunityInfaunal invert. (TL-II) polychaete 0.01 6% 84% 4.6 0.65 50000 76923 71% 26% 3% Epifaunal invert. (TL-II) nematode 0.01 6% 82% 4.6 0.65 50000 76923 31% 19% 50Forager (TL-III) lobster 2 9% 74% 2.7 0.65 19118 29412 28% 59% 13Predator (TL-IV) flounder 3 22% 75% 4.9 0.7 15591 22273 20% 60% 20

PRAM 1.4c Supplemental Information6/3/2005 3:19 PM

Based on NEHC PRAM Version 1.4c

May 2005 
PCB MODELING RESULTS - PROSPECTIVE RISK EVALUATION 

RISK ESTIMATES FOR Ex-Oriskany CV34 High-End Weight of PCB-Laden Materials

Supplemental Information

Bioenergetic Inputs Resp. Rate Resp. Rate Consumption Growth Rate Consumption Consumption

1 gO2 kcal 1 g-wt weight kcal As a 

Pelagic Community day kg-lipid-day kg-lipid-day day g-wt weight-d-wet weight-da body w

Phytoplankton (TL1) AlgaeZooplankton (TL-II) copepods 0.006375522 0 0.039935335 0.015425453 84.24400867 1286.168071 0.014147849 0.32636028 0.06790967 32.Planktivore (TL-III) herring 0.0033 -0.227 0.0548 0.004949927 21.1649 129.2512977 0.001482433 0.01616792 0.0090799 1.6Piscivore (TL-IV) jack 0.001118602 -0.55 0.12 0.000630951 2.697821256 16.47524431 0.000188961 0.00139796 0.00115739 0.1Reef / Vessel CommunityAttached Algae AlgaeSessile filter feeder (TL-II) bivalves (w/o shell) 0.012 0 0.036 0.024213411 581.8482643 6877.300342 0.020930914 0.24377539 0.0618957 24.4Invertebrate Omnivore (TL-II) urchin 0.000675466 0 0.079181846 0.003163548 13.1069075 192.1012396 0.000847751 0.03471132 0.01002768 3.5Invertebrate Forager (TL-III) crab 0.001158234 0 0.071193202 0.004642088 60.75673491 377.3221989 0.003592107 0.01678102 0.00900593 1.7Vertebrate Forager (TL-III) triggerfish 0.015181024 -0.415 0.061 0.002837229 12.13142452 74.08503521 0.00084971 0.00907693 0.00520447 0.9Predator (TL-IV) grouper 0.00279 -0.355 0.0811 0.001011362 4.324384181 26.40845301 0.000302889 0.00264734 0.00185519 0.3Benthic CommunityInfaunal invert. (TL-II) polychaete 0.001682129 0 0.071034762 0.006721006 135.0382801 1903.064429 0.017565285 0.09800757 0.01820852 9.8Epifaunal invert. (TL-II) nematode 0.001682129 0 0.071034762 0.006721006 135.0382801 2604.19343 0.0104949 0.09262416 0.02803154 9.3Forager (TL-III) lobster 0.0035 -0.13 0.066 0.00471923 61.76639253 383.5925529 0.003651801 0.01899736 0.00915559 1.9Predator (TL-IV) flounder 0.0046 -0.24 0.067 0.002486878 13.58174479 82.94195291 0.000744785 0.00974341 0.00456181 1.0Dietary Preferences

Suspended Solids

(Epilimnion)

Suspended 

Solids

(Hypolimnion)

Sediment Phytoplankton Zooplankton Pelagic Plankitivore Attached Algae Reef Sessile Filter Feeder Invertebrate Omnivore Reef Invertebrate Forager Re

Verte

Fora

Pelagic CommunityPhytoplankton (TL1)Zooplankton (TL-II) 15% 15% 70%Planktivore (TL-III) 100%Piscivore (TL-IV) 10% 90%Reef / Vessel CommunityAttached AlgaeSessile filter feeder (TL-II) 10% 80% 10%Invertebrate Omnivore (TL-II) 80% 20%Invertebrate Forager (TL-III) 5% 5% 5% 35% 50%Vertebrate Forager (TL-III) 19% 19% 15% 22% Predator (TL-IV) 15% 60Benthic CommunityInfaunal invert. (TL-II) 50% 30% 20%Epifaunal invert. (TL-II) 25% 30% 20% Forager (TL-III) 5% Predator (TL-IV) 2% 

Respiration Rate Allometric Regression Parameters

a b1 b2

PRAM 1.4c Supplemental Information6/3/2005 3:19 PM

Based on NEHC PRAM Version 1.4c

May 2005 
PCB MODELING RESULTS - PROSPECTIVE RISK EVALUATION 

RISK ESTIMATES FOR Ex-Oriskany CV34 High-End Weight of PCB-Laden Materials

Supplemental Information

Water Exposures

Upper Water 

Column

Lower Water

Column Vessel Interior Sediment Pore Water G

Pelagic Community Sediment (kcal/kg-oc) 114Phytoplankton (TL1) Algae 100% Suspended Sediment (kcal/kg-oc) 114

Zooplankton (TL-II) copepods 50% 50%Planktivore (TL-III) herring 80% 20%Piscivore (TL-IV) jack 80% 20%Reef / Vessel CommunityAttached Algae Algae 100%Sessile filter feeder (TL-II) bivalves (w/o shell) 100%Invertebrate Omnivore (TL-II) urchin 80% 20%Invertebrate Forager (TL-III) crab 70% 30%Vertebrate Forager (TL-III) triggerfish 70% 30%Predator (TL-IV) grouper 80% 20%Benthic CommunityInfaunal invert. (TL-II) polychaete 20% 80%Epifaunal invert. (TL-II) nematode 50% 50%Forager (TL-III) lobster 75% 25%Predator (TL-IV) flounder 90% 10%Respiratory Efficiencies Mono Di Tri Tetra Penta Hexa Hepta Octa Nona DeLow body weight (<100g) 4.335E-01 8.000E-01 8.000E-01 8.000E-01 4.492E-01 2.582E-01 2.018E-01 1.127E-01 5.303E-02 1.255High body weight (>100g) 5.000E-01 5.000E-01 5.000E-01 5.000E-01 3.769E-01 2.857E-01 2.526E-01 1.888E-01 1.295E-01 6.299Dietary Assimilation Efficiencies 27% 46% 53% 62% 69% 69% 68% 59% 44% 16Tissue Conc. (mg/kg-lipid) Mono Di Tri Tetra Penta Hexa Hepta Octa Nona DecaPelagic CommunityPhytoplankton (TL1) 8.387E-13 2.222E-08 1.787E-09 2.899E-08 3.807E-08 1.523E-09 6.239E-10 0.000E+00 2.811E-13 1.007E-15Zooplankton (TL-II) 4.231E-09 1.571E-04 1.585E-05 2.991E-04 2.967E-04 4.244E-05 3.776E-05 0.000E+00 1.893E-07 2.799E-08Planktivore (TL-III) 9.564E-10 1.331E-04 2.426E-05 8.873E-04 1.581E-03 2.488E-04 2.158E-04 0.000E+00 7.140E-07 3.758E-08Piscivore (TL-IV) 2.501E-10 2.346E-05 6.441E-06 5.183E-04 2.772E-03 7.462E-04 7.296E-04 0.000E+00 2.131E-06 4.648E-08Reef / Vessel CommunityAttached Algae 1.870E-09 5.035E-05 4.260E-06 7.080E-05 1.115E-04 1.084E-05 6.847E-06 0.000E+00 1.540E-08 6.887E-10Sessile filter feeder (TL-II) 6.022E-08 2.031E-03 2.006E-04 3.773E-03 3.652E-03 3.235E-04 2.342E-04 0.000E+00 7.497E-07 8.135E-08Invertebrate Omnivore (TL-II) 2.883E-07 2.235E-02 3.298E-03 1.060E-01 1.708E-01 1.202E-02 6.275E-03 0.000E+00 4.231E-06 5.249E-08Invertebrate Forager (TL-III) 2.186E-06 8.904E-02 1.325E-02 4.464E-01 8.506E-01 6.702E-02 3.707E-02 0.000E+00 4.056E-05 2.689E-06Vertebrate Forager (TL-III) 2.009E-07 1.406E-02 3.019E-03 1.767E-01 6.272E-01 6.326E-02 3.683E-02 0.000E+00 4.112E-05 1.369E-06Predator (TL-IV) 1.112E-07 7.216E-03 1.703E-03 1.483E-01 1.143E+00 1.745E-01 1.116E-01 0.000E+00 1.199E-04 2.665E-06Benthic CommunityInfaunal invert. (TL-II) 1.525E-08 5.992E-04 6.227E-05 1.232E-03 1.237E-03 1.132E-04 8.273E-05 0.000E+00 2.309E-07 1.645E-08Epifaunal invert. (TL-II) 1.892E-08 1.114E-03 1.329E-04 3.008E-03 3.315E-03 3.177E-04 2.345E-04 0.000E+00 5.892E-07 3.231E-08Forager (TL-III) 1.105E-08 6.101E-04 9.328E-05 2.819E-03 4.201E-03 3.928E-04 2.676E-04 0.000E+00 4.266E-07 9.788E-09Predator (TL-IV) 9.779E-10 1.627E-04 4.287E-05 2.656E-03 8.002E-03 9.627E-04 6.798E-04 0.000E+00 8.739E-07 1.285E-08

Energy Estimates for Suspended 

PRAM 1.4c Supplemental Information6/3/2005 3:19 PM

Based on NEHC PRAM Version 1.4c

May 2005 
PCB MODELING RESULTS - PROSPECTIVE RISK EVALUATION 

RISK ESTIMATES FOR Ex-Oriskany CV34 High-End Weight of PCB-Laden Materials

Supplemental Information

Tissue Conc. (mg/kg-WW) Mono Di Tri Tetra Penta Hexa Hepta Octa Nona Deca Total PPelagic CommunityPhytoplankton (TL1) 1.382E-14 3.661E-10 2.946E-11 4.777E-10 6.275E-10 2.510E-11 1.028E-11 0.000E+00 4.633E-15 1.659E-17 1.536Zooplankton (TL-II) 2.234E-10 8.295E-06 8.368E-07 1.579E-05 1.567E-05 2.241E-06 1.994E-06 0.000E+00 9.996E-09 1.478E-09 4.484Planktivore (TL-III) 6.719E-11 9.348E-06 1.704E-06 6.233E-05 1.111E-04 1.748E-05 1.516E-05 0.000E+00 5.016E-08 2.640E-09 2.172Piscivore (TL-IV) 1.757E-11 1.648E-06 4.525E-07 3.641E-05 1.947E-04 5.242E-05 5.125E-05 0.000E+00 1.497E-07 3.265E-09 3.371Reef / Vessel CommunityAttached Algae 3.082E-11 8.297E-07 7.021E-08 1.167E-06 1.837E-06 1.787E-07 1.128E-07 0.000E+00 2.538E-10 1.135E-11 4.196Sessile filter feeder (TL-II) 5.420E-10 1.828E-05 1.806E-06 3.395E-05 3.287E-05 2.911E-06 2.108E-06 0.000E+00 6.748E-09 7.322E-10 9.194Invertebrate Omnivore (TL-II) 1.505E-08 1.167E-03 1.722E-04 5.534E-03 8.918E-03 6.275E-04 3.276E-04 0.000E+00 2.209E-07 2.740E-09 1.675Invertebrate Forager (TL-III) 5.217E-08 2.125E-03 3.163E-04 1.065E-02 2.030E-02 1.600E-03 8.848E-04 0.000E+00 9.682E-07 6.418E-08 3.588Vertebrate Forager (TL-III) 1.411E-08 9.880E-04 2.121E-04 1.241E-02 4.406E-02 4.444E-03 2.587E-03 0.000E+00 2.889E-06 9.615E-08 6.471Predator (TL-IV) 7.809E-09 5.069E-04 1.196E-04 1.042E-02 8.031E-02 1.226E-02 7.840E-03 0.000E+00 8.420E-06 1.872E-07 1.115Benthic CommunityInfaunal invert. (TL-II) 1.460E-10 5.733E-06 5.958E-07 1.179E-05 1.183E-05 1.083E-06 7.915E-07 0.000E+00 2.209E-09 1.574E-10 3.183Epifaunal invert. (TL-II) 2.037E-10 1.199E-05 1.431E-06 3.238E-05 3.568E-05 3.420E-06 2.525E-06 0.000E+00 6.343E-09 3.478E-10 8.744Forager (TL-III) 2.636E-10 1.456E-05 2.226E-06 6.728E-05 1.003E-04 9.375E-06 6.388E-06 0.000E+00 1.018E-08 2.336E-10 2.001Predator (TL-IV) 5.379E-11 8.946E-06 2.358E-06 1.461E-04 4.401E-04 5.295E-05 3.739E-05 0.000E+00 4.806E-08 7.065E-10 6.879BAFs (L/kg-lipid) Mono Di Tri Tetra Penta Hexa Hepta Octa Nona DecaPelagic CommunityPhytoplankton (TL1) 2.979E+04 1.000E+05 1.000E+05 1.000E+05 1.000E+05 1.000E+05 1.000E+05 0.000E+00 1.000E+05 1.000E+05Zooplankton (TL-II) 1.347E+05 6.238E+05 7.437E+05 8.446E+05 5.321E+05 7.827E+05 1.103E+06 0.000E+00 2.458E+06 8.127E+06Planktivore (TL-III) 7.602E+04 1.319E+06 2.842E+06 6.256E+06 7.082E+06 1.146E+07 1.575E+07 0.000E+00 2.317E+07 2.729E+07Piscivore (TL-IV) 1.988E+04 2.325E+05 7.546E+05 3.654E+06 1.241E+07 3.439E+07 5.326E+07 0.000E+00 6.917E+07 3.375E+07Reef / Vessel CommunityAttached Algae 2.979E+04 1.000E+05 1.000E+05 1.000E+05 1.000E+05 1.000E+05 1.000E+05 0.000E+00 1.000E+05 1.000E+05Sessile filter feeder (TL-II) 9.590E+05 4.034E+06 4.709E+06 5.328E+06 3.276E+06 2.983E+06 3.420E+06 0.000E+00 4.867E+06 1.181E+07Invertebrate Omnivore (TL-II) 3.223E+04 3.116E+05 5.434E+05 1.051E+06 1.076E+06 7.781E+05 6.433E+05 0.000E+00 1.928E+05 5.351E+04Invertebrate Forager (TL-III) 1.633E+05 8.295E+05 1.459E+06 2.957E+06 3.579E+06 2.899E+06 2.540E+06 0.000E+00 1.235E+06 1.831E+06Vertebrate Forager (TL-III) 1.500E+04 1.310E+05 3.324E+05 1.170E+06 2.639E+06 2.736E+06 2.523E+06 0.000E+00 1.252E+06 9.322E+05Predator (TL-IV) 1.243E+04 1.006E+05 2.806E+05 1.470E+06 7.197E+06 1.130E+07 1.144E+07 0.000E+00 5.462E+06 2.716E+06Benthic CommunityInfaunal invert. (TL-II) 2.429E+05 1.190E+06 1.462E+06 1.740E+06 1.109E+06 1.044E+06 1.208E+06 0.000E+00 1.499E+06 2.389E+06Epifaunal invert. (TL-II) 3.013E+05 2.213E+06 3.119E+06 4.248E+06 2.973E+06 2.930E+06 3.425E+06 0.000E+00 3.825E+06 4.691E+06Forager (TL-III) 1.759E+05 1.212E+06 2.189E+06 3.981E+06 3.768E+06 3.622E+06 3.909E+06 0.000E+00 2.770E+06 1.421E+06Predator (TL-IV) 1.557E+04 3.231E+05 1.006E+06 3.751E+06 7.177E+06 8.878E+06 9.928E+06 0.000E+00 5.673E+06 1.865E+06Notes:Kow = octanol to water partitioning coefficient, Koc = organic carbon partitioning coefficient, Kdoc = dissolved organic carbon partitioning coefficientTL = trophic level, ww = wet weight

PRAM 1.4c Supplemental Information6/3/2005 3:19 PM

Based on NEHC PRAM Version 1.4c

May 2005 
PCB Concentrations Outside the Vessel

0.00E+00

5.00E-05

1.00E-04

1.50E-04

2.00E-04

2.50E-04

3.00E-04

3.50E-04

4.00E-04

Mono Di Tri Tetra Penta Hexa Hepta Octa Nona Deca

PCB Homolog

PCB Concentration

Air concentration (g/m3) Water Concentration-LWC (mg/L)

Suspended solids concentration-LWC (mg/kg) Dissolved organic carbon-LWC (mg/kg)

Sediment concentration (mg/kg) Water Concentration-UWC (mg/L)

PCB Concentrations in Biota

0.00E+00

1.00E-02

2.00E-02

3.00E-02

4.00E-02

5.00E-02

6.00E-02

7.00E-02

8.00E-02

9.00E-02

Algae

copepods

herring

jack

Algae

bivalves (w/o shell)

urchin

crab

triggerfish

grouper

polychaete

nematode

lobster

flounder

Organisms by Community

PCB Tissue Concentration (mg/kg-ww)

Mono Di Tri Tetra Penta Hexa Hepta Octa Nona Deca

Pelagic Reef Benthic
PCB Release Rates by Homolog Group

0.00E+00

5.00E+07

1.00E+08

1.50E+08

2.00E+08

2.50E+08

3.00E+08

3.50E+08

Monochlorobiphenyl

Dichlorobiphenyl

Trichlorobiphenyl

Tetrachlorobiphenyl

Pentachlorobiphenyl

Hexachlorobiphenyl

Heptachlorobiphenyl

Octachlorobiphenyl

Nonachlorobiphenyl

Decachlorobiphenyl

PCB Homolog

PCB Release Rate (ng/d)

PCB Release Rates by Source Material

1.00E+00

1.00E+01

1.00E+02

1.00E+03

1.00E+04

1.00E+05

1.00E+06

1.00E+07

1.00E+08

1.00E+09

Ventilation Gaskets

Lubricants

Foam Rubber Material

Black Rubber Material

Electrical Cable

Bulkhead Insulation Material

Aluminized Paint

Source Material

PCB Release Rate (ng/d)
APPENDIX I 

Response to EPA Comments on Ex-ORISKANY Artificial Reef Project:

Prospective Risk Assessment Model (PRAM). June 2005 (Draft Final) 

Amended 12/15/05 Page 1 of 12 
Comment

No. EPA’s Comments Response

1 When PRAM version 1.3c was initially reviewed by EPA during Fall 2004, 

numerous and potentially serious shortcomings were identified regarding aspects ofthe model’s conceptual formulation, technical documentation, identification ofmodel assumptions and uncertainties, and quality assurance. The vast majority of these shortcomings have been addressed in PRAM version 1.4c. EPA believes thatthe U.S. Navy has developed a credible modeling tool that can be used to analyze the fate and transport, bioaccumulation, and potential impacts of PCBs that can be expected to be leached from a decommissioned naval vessel that has been remediated and deployed as an artificial reef under certain prescribed conditions. Inparticular, PRAM version 1.4c appears to be a credible tool for predicting expected steady-state or chronic levels of PCB contamination that are likely to occur from the artificial reefing of the ex-Oriskany off the coast of Pensacola, FL assuming no preexisting PCB contamination. Although EPA Program and Regional Offices often

use exposure and bioaccumulation modeling approaches different from those employed by PRAM, PRAM is nonetheless based on a sound conceptual framework and utilizes widely accepted scientific principles to make its predictions. 

We acknowledge the comment that PRAM scientific principles and is a credible modeliPCB levels that are likely to occur from the Oriskany off the coast of Pensacola, FL, asscontamination.

2 PRAM’s conceptual framework as outlined in Sections 1.1, 1.2, 1.3, 2.1, 2.2, 3.1, 

3.2, and 3.3 is well done. PRAM’s technical documentation in Sections 2.5, 2.6, and2.7 is clear and comprehensive within the stated objectives and scales of resolution 

of the model. Issues related to the model uncertainties, mathematical sensitivities, and data quality are adequately discussed in Sections 2.3, 2.4, 4.1, and 4.9 and inAppendix F.

We acknowledge the comment that PRAM’technical documentation in the referred sectadequate. 

3 EPA reviewers found PRAM model predictions to be credible and logically

consistent. For example, PRAM predictions for the model option “Estimate risk given kilograms of PCB-laden material” using the default loadings and parameters corresponding to a 73% removal of PCB source materials from the ex-Oriskany seemed reasonable to EPA reviewers who focused on PRAM predictions for pentaPCB (i.e., the dominant PCB homologue on the ex-Oriskany and in most other environmental assessments) in triggerfish (i.e., reef/vessel vertebrate foragers) and groupers (i.e., reef/vessel predators). These biotic endpoints were selected not onlybecause of their recreational importance but also because EPA reviewers had independent datasets to cross-check PRAM predictions against BASS/FGETS predictions. Whereas the predicted penta-PCB concentrations in the upper water column for ZOIs equal to 2 and 5 were 4.15E-7 and 3.81E-7 ng/L, respectively, the predicted concentrations in the lower water column for ZOIs equal to 2 and 5 were 1.92E-3 and 1.11E-3 ng/L, respectively. The four orders of magnitude differencebetween the upper and lower column concentrations seems realistic and corroborates EPA’s original concern regarding the conceptual boundaries of PRAMversion 1.3 and its associated ZOIs. Importantly, these predictions are properly 

We appreciate that the reviewer conducted tdemonstrated that PRAM predictions are reareported in literature. 

Amended 12/15/05 Page 2 of 12 
Comment

No. EPA’s Comments Response

bounded by simple screening calculation. For example, assume that the prevailingcurrent over the ex-Oriskany is always parallel to the length of the ship and has a constant velocity of 0.575 mph (= 22,228 m/d). The total flow of water over thePCB source material would therefore be approximately 5.28E10 L/day assuming a total water depth of 65m and a vessel beam wide of 120 feet. The emission rate ofpenta-PCB into this current volume predicted by PRAM is 3.20E8 ng/day.Dividing this emission rate by the estimated current volume yields a predicted“point” concentration equal to 6.06E-3 ng/L. If this calculation is repeatedassuming that the prevailing current over the ex-Oriskany is always parallel to the beam of the ship, the estimated “point” concentration equals 0.818E-3 ng/L. PRAM’s bioaccumulation predictions for this scenario are also credible. Forexample, the lipid-based BAFs predicted by PRAM for penta-PCBs in triggerfish and grouper are approximately 2.64E6 and 7.19E6, respectively. Because the lipidfraction of both of these species is assumed to be 0.07, these lipid-based BAFs are 

equivalent to log10 whole-fish BAFs equal to 5.27 and 5.70. Both of these latter 

values agree well with EPA’s independent BASS/FGETS model predictions madefor these species (i.e., log10 BAF ≈ 5.32 for triggerfish and log10 BAF ≈ 5.68 for gag 

grouper). Whereas the whole-body concentrations of penta-PCB for triggerfish andgroupers in a ZOI of 2 are 0.0446 and 0.0812 mg/kg, respectively, whole-bodyconcentrations for triggerfish and groupers in a ZOI of 5 are 0.0441 and 0.0803mg/kg, respectively. 

4 Although EPA finds PRAM model predictions to be credible, EPA is nevertheless 

concerned with the fact that PRAM currently assumes that the reefed ship ofconcern is the only source of PCBs that must be considered. Currently, users cannot evaluate the very real scenario of reefing a ship in waters that have preexisting PCB contamination. For example, what if this reef were to be sunk off the coast of New Jersey or in one of the Great Lakes. Even though the risk associated with sinking the vessel at a pristine site may be acceptable, sinking it at a site that already has PCBs at the site may exceed an acceptable risk. This is a critical shortcoming of PRAM 1.4c that should be corrected in a future version. 

The Navy concurs that the incorporation of the model a more comprehensive risk assessmay be considered for a future version of PRPermit. 

5 EPA believes the some of PRAM could be better documented. For example, 

PRAM could use more up-to-date QSAR equations to derive estimates for severalphysical/chemicals properties of PCBs (e.g., Koc (Page 2-13), Kdoc (Page 2-14),and water solubility (Page 2-32)). PRAM currently uses freshwater solubilities ofPCBs rather than (the more appropriate) sea water solubilities of PCBs to estimate Henry’s Law Constants (Page 2-32). It was still unclear to some EPA reviewers how PRAM justifies the use of information, data, and models for fresh water systems in a deep water marine system. 

The Navy appreciates EPA's continued suppQSARs utilized in PRAM will be considerevessels, once data supporting the update becTo the best of our knowledge, PCB solubilitabundant whereas solubility data in salt watsolubility for freshwater, which is generally more conservative since more dissolved PCand bioaccumulation. 

Amended 12/15/05 Page 3 of 12 
Comment

No. EPA’s Comments Response

6 EPA believes that the Navy should clearly state that the PRAM risk assessment tool 

was specifically developed because it may not be possible to remove all regulated 

PCBs on the vessel. PRAM was not merely developed “to assess the potential 

risks, to human health and the environment that could be associated with deploying decommissioned ships as artificial reefs.” Statements such as that made on Page 1-5 under section 1.2.3, 2nd paragraph, 1st sentence, should be revised as:

“The PRAM was developed in order to be able to assess the potential risks, tohuman health and the environment, that could be associated with leaving PCBs of

greater than or equal to 50ppm on decommissioned ships that will be deployed as artificial reefs.” 

The statement on Page 1-5 will be revised a

7 General Editorial Comment: A consistent units notation should be used throughout 

the report. For example, the units of fugacity capacity appear as 

 mols / m3 * Pa page 2-30 

while the units of the Henry’s Law Constant, the reciprocal of fugacity capacity, appear as 

 Equation (12) 

 Pa - m3/mol pages 2-31 and 2-33 

A simple, unambiguous power notation should be used throughout the report. For example, the units of fugacity capacity should be reported consistently as [mols C Pa-1 • m-3] or some variation thereof. Similarly, the units of the Henry’s Law 

Constant should be reported consistently as [Pa • m3 C mol-1] or some variation 

thereof. A consistent notation should also be adopted to designate the type of mass (or other fundamental unit) that is being reference. For example, in most places within the

text this is done using subscripts (e.g., mgPCB or kglp). However, in other place subscripts use is abandoned or inconsistently applied (e.g., gO2/gC or gO2/kglpday). Finally, “day” as a unit should be consistently spelled out or consistently abbreviated as “d.” 

All unit notations throughout the document 

Amended 12/15/05 Page 4 of 12 
Comment

No. EPA’s Comments Response

SPECIFIC COMMENTS 

1 Acknowledgement: Under the Technical Working Group participants, EPA

Headquarters: Laura Johnson noted that she is not a Dr. 

Ms. Johnson’s title will be changed.

2 Dedication: EPA believes that it is entirely fitting and appropriate for the Navy to

dedicate this document to Mark Goodrich. 

Comment acknowledged.

3 Pages iii -v: Page numbers for Figures, Tables, and Appendices should be given. Tables, Figures and Appendices are present

sequential order, and therefore have no page Table of Contents. 

4 Page 1-1, Section 1.1 2nd paragraph: The stated “problem” should also include an

ecological component. 

Although PRAM outputs are currently being risk assessment, the original problem outlindescribes the genesis of PRAM. The documthe evolution of PRAM into a tool useful fohealth and the environment. The following of the 2nd paragraph of Section 1.1:

“Since the adoption of this initial problem sutilized to determine the ecological risks assonboard a sunken-vessel artificial reef.” 

5 Page 1-1, footnote #3: Although the Office of Water was recognized in the 

Acknowledgements as having participated on the Technical Workgroup, they are not acknowledged elsewhere. Please insert OW into the list of participants in footnote #3. Also delete SINKEX from this and all documents. With these edits the third footnote should be read as follows: The REEFEX interagency Technical Working Group (TWG) was comprised ofU.S. Environmental Protection Agency (USEPA) representatives from the Office of Pollution Prevention and Toxics (USEPA OPPT) and the Office of Water (USEPA OW), Navy representatives, and contractors to the Navy. 

The referenced footnote will be revised as foThe REEFEX interagency Technical Workiof representatives of the U.S. EnvironmentaRegion 4, the Office of Pollution Prevention Office of Water (USEPA OW), the State of Commission, Escambia County Marine Resrepresentatives, and contractors to the NavyReferences to SINKEX will be deleted in al

6 Page 1-2, 1st full paragraph, 2nd sentence: Please delete SINKEX. Although some

members of the TWG for the ex-Oriskany project do overlap with those who have participated on SINKEX workgroups in the past, the two workgroups wereestablished for completely different projects. Pairing together as presented in this document gives a very different perception.

The reference to SINKEX will be deleted in 

7 Page 1-2, 1st full paragraph, 7th and 13th sentences: These sentences refer to

“external peer review” and “peer review,” respectively. Does either of these reviews actually meet the criteria of a peer review? Perhaps they could just say“review.” 

The terms “external peer review” and “peer “review.” 

8 Page 1-2, footnote #4: The vessel information presented does not give a clear The year of vessel construction will be adde

Amended 12/15/05 Page 5 of 12 
Comment

No. EPA’s Comments Response

picture of the concerns associated with this vessel. Putting the year of decommissioning is not as important as the year the vessel was built – whichdictates the types of materials that were initially used on the vessel. 

9 Page 1-7: The citation Mackay (2001) is missing from the References in Section 5. The following citation will be added to the r

Mackay, D. 2001. “Multimedia EnvironmenApproach – Second Edition,” Lewis Publish

10 Page 1-8: The citation Exposure Factors Handbook (1997) should be Exposure

Factors Handbook (USEPA, 1997). 

The citation will be changed to: Exposure F

11 Page 1-9, Section 1.2.6, all three bullets: Because the Navy states that PRAM uses 

empirical data from the three significant sources (listed as the bullets), these documents are as important as the “Primary Deliverables.” For this reason, a thorough review of these documents should take place as well. 

The Navy understands that these three docuStudy and Fish Consumption Survey) are imtherefore they were included in the package review. 

12 Page 1-13, Section 1.4.2, 1st paragraph, 1st sentence: This paragraph could provide 

more detail regarding the Navy’s project. This could easily be addressed in the first sentence by stating exactly what the Navy would like to do ... to leave approximately 722 pounds of regulated PCBs on the ex-Oriskany at the time of its deployment to be an artificial reef. Does this document ever state what the Navy plans to do?

The first sentence of the paragraph will be c“Human health and ecological risk assessmevessel as an artificial reef must be conducted utilized as an artificial reef with approximatonboard at the time of its reefing.” 

13 Page 1-14: The text pertaining to the Project Manager/Project Coordinator contact

information is incorrect. The email address for Elizabeth Freese is incorrect (it 

should read elizabeth.freese@navy.mil), and is Washington Navy Yard, D.C. reallya city?

Washington Navy Yard, D.C. is the correct address will be changed to: elizabeth.freese@

14 Page 2-2, Last sentence: The goal of PRAM is to analyze the potential risk of 

leaving regulated PCBs on the vessel. This significant point is left out. The lastsentence could be re-written as follows: “The goal is to provide decision makers with additional information about the potential exposure conditions and human health risks associated with the exOriskany artificial reef so they can determine whether the artificial reef wouldpresent an unacceptable risk to human health or the environment.” 

The sentence will be rewritten as requested ecorisk support in accordance with specific 

15 Page 2-8: The reported units for conductance, i.e., (mol/day), in the third line from

the bottom of the Page are incorrect. The correct units are (m/day). 

The referenced units will be changed to: m/d

16 Page 2-8 and elsewhere: The citation (USEPA, 1982) is missing from the 

References in Section 5. Is this citation supposed to be for the EXAMS fate and transport model?

The reference is indeed for the EXAMS fate referenced on page 5-8 with other USEPA rrevised as follows to avoid further confusionUSEPA (United State Environmental ProtecAnalysis Modeling System (EXAMS): User Documentation. Office of Research and Dev

Amended 12/15/05 Page 6 of 12 
Comment

No. EPA’s Comments Response

Research Laboratory, Athens, GA., EPA-60

17 Page 2-9: In the explanation the parameters/variables of Equation (3), the variables 

Mi and Mj should be subscripted.

The referenced variables will be changed to

18 Page 2-14: The citation (Kleinow and Goodrich, 1994) is missing from the 

References in Section 5. However, the references do list Kleinow, K.M. and M.S. Goodrich. 1993. 

The correct date for the citation is 1993. Threvised. 

19 Page 2-15: By standard mathematical conventions, Log10 should be reported 

either as Log10 or as simply Log. 

References to the base 10 logarithm throughto: Log10. 

Amended 12/15/05 Page 7 of 12 
Comment

No. EPA’s Comments Response

20 Page 2-15, first paragraph: There is an apparent inconsistency in the PRAM

documentation relative to potential degradation of PCBs. In particular, is the residence time in the sunken vessel sufficient to allow degradation of PCBs?

The last sentence of this paragraph will be dmodule allows input of biodegradation rates

21 Pages 2-15 to 2-27: Sections 2.3 seem out of place to some reviewers. EPA 

suggests making these sections the last two sections in Chapter 2 since their contentdepends directly on the model descriptions in the current Sections 2.5, 2.6, and 2.7.

Sections 2.3 and 2.4 will be moved to the en

22 Pages 2-38 and 2-39, Equations (25) – (28): The subscripts on the parameters φ

should be DOC not DC. 

The subscripts will be changed to DOC in E

23 Page 2-46, last paragraph: Incorrect units are reported for Henry’s Law Constant. The units reported for Henry’s Law Constan24 Page 2-50: The citation Jury et al. (1983) is missing from the References in Section

5. However, the references do list Jury 1983. 

The citation in the reference section will be Jury, W., W. Spencer, and W. Farmer. 1983trace organics in soil: I. Model description. 12:558-564. 

25 Page 2-69, Section 2.6.2.5, second paragraph: Should there be more consideration 

given to people eating crabs and lobsters (why should sports fish be the only focus)?The Navy does state that people would eat them (also see Page 2-75, 2nd paragraph,

2nd sentence). 

The Navy had intended to imply crabs and lpredator fish) will be revised to (primarily toshellfish). 

26 Page 2-72, Section 2.6.3.2, 1st paragraph, 3rd sentence: The sentence does not seem

to make sense. Should “these waters” be replaced with “these algae”?

Either “these waters” or “these algae” would and the waters to which they are exposed arfurther confusion, the third and fourth sentewill be combined into the following sentenc“Since the top portion of the ship is predicteattached algae have been assumed to be expcolumn (Table 6).” 

27 Page 2-85: The citation Thurston and Gehrke, 1993 is misplaced from the 

References in Section 5. 

The following citation will be added to the rThurston, R.V. and P.C. Gehrke, 1993. Respfishes: description of OXYREF, a data file bthe published literature. p. 95-108. In R.C. RPhysiology, Toxicology, and Water Quality International Symposium, Sacramento, Cali1990. US Environmental Protection Agency 

28 Page 2-86, Equation (107): The units reported for the respiration rate r are 

technically incorrect. Although the units are reported to be [1/day], they are in fact [gO2Cgww-1Cday-1]. Note that the units of the following equation, Equation (108), 

are correct and follow directly from this comment/correction. 

The units presented in Equation 107 are techwith those used in the literature for a metabothe rate as gww/gww-day. It is critical to main

metabolic rate and a direct rate since the memass of oxygen taken up by the organism. Econversion to a direct rate of oxygen consum

Amended 12/15/05 Page 8 of 12 
Comment

No. EPA’s Comments Response

ratios between oxygen and carbon and betw

29 Page 2-90: The citation (Kleinow and Goodrich, 1992) is missing from the 

References in Section 5. However, the references do list Kleinow, K.M. and M.S. Goodrich. 1993. 

The correct date for the citation is 1993. Threvised. 

30 Page 2-93, Equation (123): This equation is the calibration equation suggested by

Barber (2003) for the Gobas and Mackay uptake model; see Equation (107) andTable 14/Model 5 in Barber (2003). If the intent of the authors is to calibrate PRAM Equations (118) – (122) using the results of Barber (2003), the authors should use the results reported for the Norstrom-Neely-Thomann model in Table 14of Barber (2003). In this case the desired calibration equation would be something like Ku calibrated = 3.87 Ku Equation (118) 0.854

The intent of the authors was to respond to Ucomment dated September 15, 2004. The RReport was submitted in Appendix K of the (see Response to Comment 1.1). Dr. Barber used algorithm in PRAM to estimate gill upcalibrated or replaced. The authors chose to Barber’s comment did not specify a preferenalgorithm. The authors do not intend to furtsupport evaluation of the ex-ORISKANY foThe Navy will consider gill uptake and excrfuture upgrade to PRAM to support the Nati

Amended 12/15/05 Page 9 of 12 
Comment

No. EPA’s Comments Response

31 Page 2-95: The citation Gobas and Mackay (1987) is missing from the References 

in Section 5.

The following citation will be added to the R

Gobas, F.A.P.C. and Mackay, D. 1987. DynChemical Bioconcentration in Fish. Environ

32 Page 3-3: More appropriate terms are “volatilize” and “wind” rather than “volatize” 

and “wind current,” respectively. 

The listed corrections will be made to the PR

33 Page 5-4: The correct spelling of “W. Brock Meely” in the references is “W. Brock 

Neely.” 

The listed correction will be made to the PR

GENERAL COMMENTS BY SAB 

1 The PRAM is well documented for the bioaccumulation and human health modules, 

but there are gaps in the discussion, presentation of algorithms, and presentation ofphysical transfer processes that are critically missing from the fate and transport module. This should include a good explanation of why a fugacity-based modelwas selected for use in a very dynamic water environment, a better description ofthe transfer functions between the four water components, better documentation ofthe parameters selected for the model, and an expanded discussion of theuncertainty associated with the PRAM output. 

Fugacity-based models are based on the assuenvironment, including water column, sedimparticles, reach ultimate balance, chemicallythe results provided by the fugacity model whuman health and ecological risk assessmenPRAM model adopts the Level III fugacity state, non-equilibrium conditions in all the mpresentation of transfer functions in the modLevel I and Level II, which primarily dictate mass balance assumption. The details of theevolutions can be found in the published refdocumentation. Before finalizing PRAM dothorough review of the document to make suthe model are referenced or documented. Wspecific comments on PRAM, we will expanuncertainty section to provide a better underlimitations of the model. 

Amended 12/15/05 Page 10 of 12
Comment

No. EPA’s Comments Response

3.1 There are some inconsistencies which state whether the PRAM is applied to human

health and/or the environment. This should be clearer. 

PRAM has built-in modules to estimate PCB biotic media, and has a built-in human healtestimate human health carcinogenic risk and does not have a built-in ecological risk assefrom the abiotic and biotic/food-web modulORISKANY study does, to characterize riskdetails follow:The abiotic module in PRAM is a fate and tfugacity approach. The module calculates creef environment (water and sediment). To assessment, the PRAM-calculated abiotic copublished benchmark concentrations related concentrations for PCBs in marine environmThe biotic module in PRAM is a food-web uthat calculates bioaccumulation factors (BA(BCFs) for each organism in the food web aconcentrations. To support an ecological riscalculated BAFs and BCFs can be compared for marine environments. The human health risk characterization modincremental risks to human health from the with the artificial reef. To support a human PRAM-calculated human health carcinogencompared to EPA acceptable points of depaassessment of incremental human health imThe text in the PRAM documentation will binformation.

3.2 Microorganisms are left out of the food web. PRAM does not currently include a discrete 

degradation pathway. These processes will next version of PRAM. However, the microout of the food web, they have been incorpoand sediment compartments as follows. Thcalculates PCB concentrations in suspended compartment (upper water column, lower wand PCB concentrations in the sediment. Thhave a fraction organic carbon value assigneassumed to represent both living and dead m

Amended 12/15/05 Page 11 of 12
Amended 12/15/05 Page 12 of 12 

Comment 

No. EPA’s Comments Response

carbon fractions for these media are assignefood for higher trophic level organisms in th

3.3 The existence of a pycnocline to bound the lower/upper water compartments in 

PRAM, and in the TDM, appears to have been invoked in order to provide for a conservative analysis; i.e., a smaller water volume for the initial distribution of released PCBs. This should be stated explicitly. Pycnoclines are likely more dynamic and variable in reality than described and used in PRAM. 

The pycnocline is known to exist in the vicilocation for the ex-ORISKANY. The REEFmodel would be more technically complete a flux boundary between the upper and lowesteady-state model, and an average annual ddetermined based on both reported data and This average depth is included in the revised agreement between the EPA and Navy. The Navy acknowledges the seasonal variaband will be adding a discussion of this variareference data from NOAA that indicates thsummer, deepens during the fall months, anthe winter months. The text will also be expvariability in the pycnocline, upwelling in thevents such as hurricanes may potentially dithe PRAM-predicted health risks. 

6.1 The TDM (and the PRAM) need to be validated before their usefulness for other 

applications can be confirmed. Thus there is a need for a validation protocol to be specified for the PRAM, one that takes into account that such “higher order” models 

require a redefined approach to validation. Since data sets that stress all aspects of the model do not, and are unlikely to exist, or are prohibitively expensive, the usual approach of comparing output with data is not practical. The Panel recommends following the protocol developed by Beck at the University of Georgia. 

We agree with the reviewers' comments; fulcalibration/verification is extremely difficulhave been various published reports/papers calibration/verification, most of them are on issue, including the paper by Beck at the Unrecommended by the panel. There have beefor model calibration/verification. While PRverified, the model compiles and adopts mabioaccumulation models commonly used by and published in peer-reviewed journals. Thbe collected from the ex-ORISKANY to be discussed within the Science Workgroup for 
APPENDIX J 

Response to EPA’s December 2, 2005 Second Round of Comments on 

Ex-ORISKANY Artificial Reef Project: 

Prospective Risk Assessment Model (PRAM). June 2005 (Draft Final). 

Amended 12/15/05 Page 1 of 2 
Amended 12/15/05 Page 2 of 2 

Comment Comment Responses

General Comment No. 5 

The Navy responded to Comment 5 by saying they will update the QSARs for physical/chemical properties for future vessels, but by omission of its mention, apparently not for exOriskany. It is not clear why, since the suggested updates were minor. 

We agree that the updates are minor, but the scarcity of data fQSARs will require additional research and agency coordinatcompleted prior to issuance of final documents for the ex-Oritime frame available for completing the evaluation of risks asOriskany, including the utilization of PRAM outputs in the ENavy believes the best course of action is to update QSARs in PRAM when relevant data becomes available. The research updated QSARs will be conducted in consultation with the NWorkgroup, which will make the final decision of which QSAIt should be noted that the QSARs in the current version of Pdata for freshwater, which is more conservative for risk prediHHRA, since PCBs are more soluble in freshwater than saltwdissolved PCBs are available for uptake and bioaccumulationComment will be deferred for resolution in the National Apprstated otherwise 
Appendix K: An Evaluation of the Prospective Risk Assessment Model 

(PRAM Version 1.4c) to Predict the Bioaccumulation of PCBs in the Food 

Chain of a Sunken Ship Artificial Reef 

Prepared by

Robert K. Johnston 

Marine Environmental Support Office 

Space and Naval Warfare Systems Center Code 2375 

San Diego, CA 92107 

johnston@spawar.navy.mil

December 3, 2005 

Introduction 

The output from the TDM and PRAM models were evaluated to the extent possible to 

identify any biases and verify the reliability of the results. Because the models are simulating 

future conditions, no field data are readily available to validate the model output. However 

model performance was evaluated to assure that the model results were internally consistent, that

the predictions of the model conformed to the physiochemical properties being modeled, and that 

results produced by the model were consistent with similar studies reported in the literature. 

Critical in this evaluation was to judge whether the model could reliably perform the task of 

predicting PCB bioaccumulation in the reef environment. This provides an important quality 

assurance that PRAM can be used to support the risk assessment (Beck et al. 1997, Chen and 

Beck 1999, Beck and Chen 2000). 

Model Evaluation 

Model performance was evaluated to assure that the model results are internally 

consistent (the same set of inputs gives the same set of results), that the predictions of the model 

conform with the physiochemical properties being modeled, and that results produced by the 

model were consistent with similar studies reported in the literature. 

The main quality control check on the TDM model (NEHC/SSC-SD 2005b, 2006b) was 

to assure that mass balance was accounted for within the model. Subroutines were incorporated 

into the model to check for conservation of mass and the simulation results were evaluated to 

determine whether the results were reasonable approximations of natural phenomena. 

Additionally, Dr. Keith Little (RTI, International, Research Triangle Park, NC) conducted a 

detailed third party peer review of the model code and output to assure that model structure, 

algorithms, kinetics, and simulated output conformed to accepted conventions and standards with 

satisfactory results (Dr. Keith Little, RTI, International, personal communication). Dr. Little also 

performed a similar review of PRAM 1.4, which also met with satisfactory results (Dr. Keith 

Little, RTI, International, personal communication). 

The PRAM output was compared to literature values to evaluate the validity and 

accuracy of the biological uptake and trophic transfer algorithms. The results of this evaluation 

are provided below. 

K - 1
Zone of Influence 

Initial runs using PRAM 1.4c (NEHC/SSC-SD 2005a, 2006a) were conducted to verify 

model stability and accuracy by assuring that the model provided the same set of results for the 

same set of inputs and verifying that the model was functioning properly. A series of PRAM runs 

were conducted by keeping all parameters constant using the default values and varying the ZOI 

parameter from 1, 2, 3, 4, 5, and 10 (see Appendix K.2 PRAM Output for Varying ZOI). 

Changing the ZOI only changes the physical dimensions of the model – the volume of air, water, 

and sediment included in the model (Figure K- 1) – all the physical, chemical, and bioenergetic 

equations and food chain linkages remain the same. Only the volume of water in the vessel’s 

interior remains constant at 5.38 × 104

 m

3

(14,214,003 gallons). The ZOI represents a column of 

water directly around the ship. At ZOI=1 the water column boundary is defined by the hull of the 

ship, there is no sediment compartment,1

 the lower water column is the water surrounding the 

ship which extends up to the pycnocline and is about 3 times larger (range 2.87 to 3.29 for 

ZOI=1 to 10) than the upper water column and about 4.5 times larger (range 4.31 to 4.83 for 

ZOI=1 to 10) than the overlying air compartment. The interior of the vessel was interpreted as 

the interior compartments of ship, the spaces separated from the water column by bulkheads, 

passageways, and hatches. The hangar-deck and other spaces that are open to ocean currents 

were considered to be the exterior of the ship. These are the primary surfaces that will be used as 

substrate by colonizing reef organisms where they will be exposed to PCB concentrations in the 

lower water column. 

For purposes of evaluating ecological effects from water column exposure the bulk water 

concentration (CBW) was calculated as: 

CBW = CW_FD + TSS × CTSS + DOC × CDOC [mg/L] [1]

where

CW_FD = Freely dissolved concentration in water [mg/L] 

CTSS = Concentration in suspended sediments [mg/Kg] 

CDOC = Concentration in dissolved organic carbon [mg/Kg] 

TSS = The amount of suspended sediment = 10 [mg/L] 

DOC = The amount of dissolved organic matter = 0.6 [mg/L] 

Based on the default inputs for PRAM (Appendix K.2.2 PRAM Default Parameters (ZOI 

=2 )) changing the ZOI from 1 to 10 resulted in about a 40% to 75% decrease in the 

concentration of the lower water column and pore water, a 10% to 20% decrease in the upper 

water column concentration, and the interior vessel water concentration remained constant at 

6.7 × 10-4 mg/L (Figure K- 2). The interior vessel water was about 2-3 orders of magnitude 

higher than the concentration of the lower water column, 5 orders of magnitude higher than the 

concentrations in sediment pore water, and 6 orders of magnitude higher than the concentrations 

predicted for the upper water column. 

Total PCB concentrations in the sediment also decreased 40-80% as a function of ZOI, 

with the greatest decrease occurring between ZOI=1 and ZOI=2 when the sediment bed is added 

to the model (Figure K- 3, NEHC/SSC-SD 2005a, 2006a). Slight increases in the concentration 

 

1

 Although the sediment compartment is undefined for ZOI=1 PRAM still provides results for sediment and

porewater concentrations, so it was assumed that this represented sediments “very “close to the ship, e.g. ≤ 15 m

from the ship, such as sediment that could accumulate on the flight or hanger decks.

K - 2
of Total PCB in the air compartment were modeled as a function of ZOI (Figure K- 4). This was 

probably due to the effect of increasing the boundary between air and water, which resulted in an 

increase in the mass transfer of PCBs between the upper water column and the overlying air as 

the ZOI was increased. 

The change in concentration of Total PCB modeled by PRAM in food chains of the 

pelagic, benthic, and reef communities as a function of changes in the ZOI is shown in Figure K5 and summarized in Table K - 1. The concentration of Total PCB modeled in the pelagic and 

benthic food chains decreased in proportion to the 40-75% reduction observed for the lower 

water column and pore water concentrations. However, the upper trophic levels of the reef 

community remained relatively constant, decreasing by less than 2-4% over the range of ZOIs 

used. This is because the accumulation of PCBs in the reef community is controlled by exposure 

to interior vessel water that does not change as a function of ZOI. 

Bioaccumulation Factor 

The lipid-based bioaccumulation factor (BAFLIPID) is defined as the lipid based 

concentration of a -chemical (CLipid) in a organism divided by the freely dissolved concentration 

in the water (CW_FD): 

BAFLIPID = CLipid / CW_FD [2]

The BAFLIPID represents the amount of chemical bioaccumulated from exposure to water 

and food (Fisk et al. 1998, 2001). In PRAM the BAFLIPID is calculated using the weighted 

average of the steady state water concentration in each compartment of the model that the 

organism is exposed to (interior water, lower water column, upper water column, and pore water, 

NEHC/SSC-SD 2005a, p2-84). Since changing the ZOI only affects the physical dimensions of 

the model, varying the ZOI has the effect of reduce the steady concentrations of the abiotic 

compartments because the size of the compartments are changed (NEHC/SSC-SD 2005a, p2-10). 

Therefore, changing the ZOI should not appreciably the BAFLIPIDs predicted by the model 

because PCB concentrations in target tissues are expected to decrease in proportion to that of all 

environmental media (biotic as well as abiotic) as the dilution volume of the ZOI changes. 

The BAFLIPID obtained from PRAM with a ZOI=1 for the components of the pelagic, 

benthic, and reef communities as a function of Log(Kow) are shown in Figure K- 6. The 

BAFLIPIDs followed the generally expected behavior of higher bioaccumulation of homologs with 

a Kow > 4.7. The primary producers (phytoplankton and algae) had a constant BAFLIPID for the 

di- to decachlorobiphenyls reflecting the fact that a constant BCF was used for the homologs 

with Kow > 5.0, as is recommended in the literature (Spacie et al. 1995, Connolly 1991, 

NEHC/SSC-SD 2005a, p2-82). The highest BAFLIPIDs were calculated for jack, herring, crab, 

and grouper, while lower BAFLIPIDs were obtained for the benthic community, zooplankton from 

the pelagic community, and urchin and triggerfish from the reef community. The BAFLIPIDs 

calculated for bivalves followed a different pattern than the other species, the bivalve BAFLIPIDs 

were relatively constant for the homologs modeled. Only slight changes in the modeled 

BAFLIPIDs were detected over the range of ZOI=1 to 10 (Figure K- 7, Table K - 2). 

Predicting PCB bioaccumulation 

The accuracy of PRAM to predict bioaccumulation between trophic levels was evaluated 

by comparing data reported in the literature on PCB bioaccumulation as a function of diet to 

K - 3
predictions obtained from PRAM. The important aspect of this evaluation is not necessarily to 

reproduce the predicted concentrations, but to evaluate whether the general pattern (increasing 

bioaccumulation as a function of Kow), degree of biomagnification between trophic levels, and 

determine if the relative magnitude of the accumulation is in agreement with literature data. In a 

study on the bioaccumulation of PCBs in the top predators (Chinook and Coho salmon) of the 

food chain in tributaries to Lake Michigan, Jackson et al. (2001) reported statistically significant 

regressions that predicted PCB homolog levels in salmon (TL4) as a function of tissue 

concentrations in pelagic mysids (Mysis relicta) and benthic amphipods (Diporeia spp.), which 

occupied TL2 in the limnetic food chain. 

CSalmon(i) = mi(CPrey(i)) + bi [3]

where

CSalmon(i) = Concentration of homolog(i) in Coho or Chinook salmon 

CPrey(i) PCB concentration of homolog(i) in mysid or amphipod 

mi = Slope for homolog(i) 

bi = Intercept for homolog(i)

The food chain studied by Jackson et al. (2001) was very similar to the pelagic and 

benthic communities modeled by PRAM and there was a high degree of correlation between the 

TL2 macroinvertebrates and the TL3 salmon because the macroinvertebrates were the main route 

of transfer in the pelagic (mysid) and benthic (amphipod) food webs in the lake. Using the 

concentrations predicted by PRAM for TL2 pelagic (zooplankton) and benthic (infauna) prey the 

regressions were used to predict the PCB concentrations in the TL4 pelagic (jack) and benthic 

(flounder) and compared to the TL4 concentrations modeled by PRAM. When both the slope and 

intercept of the regression were used the results showed a similar pattern, but the PRAM 

predictions were less than what was obtained using the regressions, with a greater difference for 

the pelagic food chain than for the benthic food web (Figure K- 8). A similar pattern was found 

for the predicted Total PCB concentrations, PRAM under predicted bioaccumulation in the 

pelagic food chain was within the range obtained for the benthic food chain Figure K- 9. Note, 

that the Coho and Chinook concentrations for the benthic community and Chinook concentration 

for the lower chlorinated homologs could not be predicted, because the prey concentration were 

too low and the regression with intercept resulted in a negative value. This probably occurred 

because the modeled concentrations were outside (lower) than the empirical data used to 

calculate the regression. However, when PCB homologs were predicted using just the slope from 

the regression a much better agreement was obtained between PRAM and the regression results 

for both the pelagic and benthic communities for homologs (Figure K- 10) and Total PCB 

(Figure K- 11). 

These predictions are based on the assumption that the Lake Michigan food chains are 

similar to the pelagic and benthic food chains modeled in PRAM, which is a fairly reasonable 

assumption given that the food chain studied by Jackson et al. (2001) was relatively simple and 

that the primary route of exposure was through the diet. Jackson et al. (2001) reported that the 

diet of secondary consumers (alewife and scorpion fish, for pelagic and benthic food chains, 

respectively) was made up of “almost pure” mysids and amphipods leaving little doubt about the 

route of PCB transfer in the food chain to the tertiary consumers (salmon). It is reasonable to 

compare the PRAM output with the values obtained using just the slope of the uptake 

regressions, because the intercept is very site-specific and affected by factors like analytical 

detection limits, analytical and sampling biases, and differences in contaminant residues in wild 

K - 4
fish due differences in gender, age, size, health, and other geographic variations in the sample 

population (Johnston et al. 2002). Although there are undoubtedly differences in the source 

signatures of PCBs present in Lake Michigan compared to the source of PCBs in PRAM, the 

sources are probably all derived from Aroclor mixtures and any PCBs released would be 

subjected to the same physical, chemical, and biological processes that are modeled in PRAM. 

The good agreement between the PRAM predictions and the uptake regressions shows that 

PRAM is providing reasonable estimates for this aspect of the model. 

The purpose of the comparison above was to determine if PRAM could model the pattern 

of PCBs bioaccumulated as a function of Kow, the degree of biomagnification between trophic 

levels, and the magnitude of the accumulation relative to the concentration in the prey. Note that 

Figure K- 8 and Figure K- 10 show that accumulation for individual congeners from Jackson (et 

al. 2001) and homologs from PRAM while Figure K- 9 and Figure K- 11 show Total PCB 

reported by Jackson (et al. 2001) and Total PCB (sum of homologs) from PRAM, and different 

regressions were used for each (that is why the Predator (IV) concentration is higher than coho). 

Figure K- 10 shows that PRAM does very well in predicting the bioaccumulation of homologs 

with a Kow ≥6.5 (penta-, hexa-, and heptachlorobiphenyl), these homologs account for 49%, 

10%, and 10%, respectively of the total PCBs released at steady state from materials expected to 

be on the ex-ORISKANY after sinking. 

Biomagnification between trophic levels 

Another means of evaluating the output from PRAM is to compare the relative increase 

in bioaccumulation as a function of the links in the food chain or trophic level (Stapleton et al 

2001, Fisk et al. 2001). This approach evaluates the biomagnification (BMF) factor, or step 

increase in PCB accumulation moving from one trophic level to the next, by comparing the 

relative increases in PCBs between predator and prey modeled by PRAM to data reported in the 

literature. 

The lipid-based, trophic level corrected BMFTLC is calculated by the ratio of the lipidbased tissue concentration of the predator (CPRED_L) to its prey (CPREY_L) normalized to the TL of 

each organism (Fisk et al. 2001): 

BMFTLC = 

CPRED_L / CPREY_L

---------------------- 

 TLPRED / TLPREY

[4]

The TL for the PRAM food chain was calculated based on the weighted average of each 

component of a organism’s diet: 

TL(j) = 1 + Σ fdiet(i) x TLPrey(i) [5]

where

TL(j) = Trophic level for species (j), summed for number of (i) prey 

items modeled 

fdiet(i) = Fraction of diet for prey item (i) 

TLPrey(i) Trophic level of prey item (i) 

The default dietary preferences used by PRAM and the TL determined by diet for each 

compartment modeled in the food chain is shown in Table K - 3. For the calculations it was 

assumed that algae and plankton were assigned a TL of 1, and suspended sediments in the upper 

K - 5
water column, suspended sediment in the lower water column, and sediment were assigned a TL 

of 1.125, 1.250, and 1.5, respectively, to represent the relative increase in recycled detrital matter 

in the sediment pool. 

Stapleton et al. (2001) reported Total PCB concentrations in the pelagic, benthic, and 

demersal food chains in Grand Traverse Bay Lake Michigan for which BMFTLC’s were 

calculated. Fisk et al (2001) reported BMFTLC‘s for PCB congeners in a demersal food chain 

from Arctic waters of the Northwater Polynya near northern Greenland, and Mackintosk et al. 

(2004) reported data on the accumulation of six PCB congeners in a coastal marine food web in 

False Creek Harbor, Vancouver, BC, Canada. These studies provide data on the bioaccumulation 

of Total PCBs and specific congeners from a wide range of ecosystems for comparison to 

PRAM. 

The following food chains were evaluated: 

Food Chain TL2 TL3 TL4 

Grand Traverse Bay 

 Pelagic Zooplankton → Alewife → Lake Trout 

 Benthic Amphipod → Sculpin → Salmon 

 Demersal Mysid → Bloater → Burbot 

Northwater Polynya 

 Demersal Copepods → Amphipod → Arctic Cod 

False Creek Harbor 

 Pelagic Juvenile Perch → Greenling → Dogfish 

 Benthic Clams → English Sole → Dogfish 

 Demersal Juvenile Perch → Staghorn Sculpin → Dogfish 

The BMFTLC obtained for the predictions from PRAM compared very well to the 

literature values from the studies cited above (Figure K- 12, Table K - 4). This analysis assumed 

that the food chain links evaluated were similar and subject to the same physical and chemical 

processes modeled in PRAM. Although there is uncertainty associated with the trophic level 

assignments reported in the literature studies, the TL assignments were all based on 

measurements of δN13 and δC13 isotopes. In calculating the BMFTLC’s it was assumed that 100% 

of the diet came from the prey species being evaluated, which actually varied in PRAM as it does 

in natural food webs. The analysis provides a way to independently evaluate model performance 

by comparing the relative increases in PCB accumulation along specific links of the food chain. 

Another source of uncertainty is that the PCB concentrations from the literature were reported as 

sums of congeners (Stapleton et al. 2001, Fisk et al. 2001) or individual PCBs (Mackintosh et al. 

2001) and the PRAM output was evaluated as the sum of homologs (Total PCB). More detailed 

evaluations could be performed for individual homologs and groups of congeners to further 

evaluate the model. Based on the current analysis it appears that the predictions from PRAM 

agree with the expected BMFs of PCBs in similar food chains. 

Trophic level and Bioaccumulation Factors 

The relationship between trophic level and BAFs was evaluated by comparing measured 

BAFs reported by Burkhard et al. (2003, Figure K- 13) to the BAFs predicted by PRAM as a 

function of Kow (Figure K- 14). The comparison of the lipid-based bioaccumulation factors 

(BAFLIPIDs) predicted by PRAM and BAFs reported for 13 species of fish from Green Bay Lake 

K - 6
Michigan, the Hudson River, and Lake Ontario generally showed good agreement, although 

there appeared to be less PCBs accumulated for homologs between Log(Kow) 6 and 7, the pentaand hexachlorobiphenyls. The fact that PRAM showed the general trend of increasing BAFLIPIDs 

as a function of Log(Kow) that tracks the literature values is very encouraging. The deviation 

from literature values for some of the TL3 (triggerfish) and TL4 (flounder and grouper) indicates 

that some model tuning may be warranted. The invertebrate predators were included on the plot 

for comparison purposes; comparable data on the BAFLIPIDs in upper trophic level invertebrates 

are currently not available. Data for the higher chlorinated congeners and homologs with 

Log(Kow) > 7 were also not available. The BAFLIPIDs for hepta- to decachlorobiphenyls would 

probably begin to decline as was indicated by the PRAM results. 

In comparing the results from PRAM to BAFLIPIDs obtained from field data, it must be 

noted that there are many reasons for variability in BAFLIPIDs obtained from field data. These 

include differences in the actual trophic level and the nominal or measured (with δN13 and δC13

isotopes), the fact that most ecosystems are in disequilibria with chemical inputs and losses, 

errors and biases in sampling and analytical chemistry, and difference in age, size, gender, 

growth rate, and reproductive status of the specimens sampled (Burkhard et al. 2003, Johnston et 

al. 2002). 

Food Web Magnification Factors 

Perhaps the best way of evaluating the PRAM output is to look at bioaccumulation across 

the food web as a whole by calculating the Food Web Magnification Factor (FWMF, Fisk et al. 

2001): 

FWMF = e

b [6]

Where b is the slope of the log-linear (natural log) regression between PCB 

concentration and TL: 

Ln(PCB) = a + b(TL) [7]

The regression takes into account bioaccumulation within the food web as a whole and b

represents the rate of PCB accumulation as a chemical (in this case PCBs) moves up the food 

chain. When FWMF > 1 it means that the chemical is biomagnifing; FWMF < 1 indicates trophic 

dilution (Fisk et al. 2001, Mackintosh et al. 2004). 

The FWMF for the pelagic, benthic, and reef food chains modeled by PRAM were 

calculated with the default PRAM output (ZOI=2) by regressing the Ln(PCB) for each homolog 

against the TLs calculated for the pelagic, benthic, and reef communities to obtain the regression 

coefficient (b) for each of the homologs (Figure K- 15, Figure K- 16, Figure K- 17 and Table K - 

5). The resulting FWMFs from PRAM were compared to FWMFs reported for the Northwater 

Polynya Arctic Food Web (Fisk et al. 2001), the False Creek Harbor food web (Mackintosh et al. 

2004), and a marine food web from Bohai Bay, China (Wan et al. 2005, Figure K- 18). 

The highest FWMFs obtained from PRAM were for the hexa-, hepta-, and 

nonachlorobiphenyls in the reef and pelagic communities. The homologs with Log(Kow) < 5.6 

did not biomagnify in any of the communities and decachlorobiphenyl did not biomagnify in the 

benthic food web. There was very good agreement between the FWMF predicted by PRAM and 

the literature values. The PRAM results encompassed the range of FWMFs reported in the 

literature with the reef community having the highest FWMFs. Once again, the PRAM results 

follow the general trend observed in the literature data. There is quite a bit of scatter in the 

K - 7
literature data, because values were calculated for individual congeners (including coplanar and 

non-coplanar PCBs) within greatly varying food webs. The Arctic food web encompassed a wide 

range of predator-prey interactions including sea birds and mammals (Fisk et al. 2001), while the 

marine food webs from Canada and China had similar structure at the lower TL they supported 

different top-level predators (Mackintosh et al. 2004, Wan et al. 2005). 

Summary of Model Evaluations 

These results add to the confidence that PRAM is able to model food chain 

bioaccumulation of PCBs with reasonable accuracy. The model validation analysis described 

above for PRAM only evaluated the trophic transfer mechanisms in the model, which are 

independent of the input conditions (PCB releases rates) and transport processes also simulated 

in the model. While there is uncertainty about the results obtained from PRAM the analysis 

shows that PRAM is giving reasonable and plausible results that can be used to assess risks 

associated with the ex-ORISKANY. Comparison of the overall food web magnification factor 

(FWMF) obtained from PRAM to data available from field studies showed that biomagnification 

in the reef community modeled by PRAM was higher than all the available literature values 

(Figure K- 18) and the FWMF for the pelagic and benthic communities fell within the range of

the field data. This adds to confidence that the results from PRAM are valid. Although some

fine-tuning of certain aspects of the model may be desirable, the good agreement with literature 

values indicates that the results from PRAM are plausible and reasonably good estimates of what 

would occur given that the other model assumptions and input procedures are accurate 

representations of what is occurring at the site. 

K - 8
Appendix K Tables 

K - 9
Table K-1. Summary of PCB concentrations (mg/Kg-ww) predicted by PRAM for ZOI=1, 2, 3, 4, 5, and 10.

ZOI=1

Tissue Conc. (mg/kg-WW) Mono Di Tri Tetra Penta Hexa Hepta Octa Nona Pelagic CommunityPhytoplankton (TL1) 1.676E-14 4.439E-10 3.571E-11 5.792E-10 7.606E-10 3.041E-11 1.246E-11 0.000E+00 5.612E-15 Zooplankton (TL-II) 6.050E-10 2.246E-05 2.266E-06 4.277E-05 4.242E-05 6.070E-06 5.400E-06 0.000E+00 2.708E-08 Planktivore (TL-III) 1.819E-10 2.531E-05 4.615E-06 1.688E-04 3.008E-04 4.733E-05 4.107E-05 0.000E+00 1.359E-07 Piscivore (TL-IV) 4.755E-11 4.461E-06 1.225E-06 9.859E-05 5.272E-04 1.420E-04 1.388E-04 0.000E+00 4.055E-07 Reef / Vessel CommunityAttached Algae 8.350E-11 2.248E-06 1.902E-07 3.161E-06 4.977E-06 4.841E-07 3.057E-07 0.000E+00 6.876E-10 Sessile filter feeder (TL-II) 1.468E-09 4.952E-05 4.891E-06 9.197E-05 8.903E-05 7.886E-06 5.710E-06 0.000E+00 1.828E-08 Invertebrate Omnivore (TL-II 1.523E-08 1.188E-03 1.758E-04 5.668E-03 9.186E-03 6.545E-04 3.455E-04 0.000E+00 2.527E-07 

Invertebrate Forager (TL-III) 5.250E-08 2.152E-03 3.213E-04 1.087E-02 2.081E-02 1.654E-03 9.215E-04 0.000E+00 1.020E-06 

Vertebrate Forager (TL-III) 1.421E-08 1.004E-03 2.165E-04 1.272E-02 4.530E-02 4.613E-03 2.709E-03 0.000E+00 3.057E-06 Predator (TL-IV) 7.885E-09 5.138E-04 1.217E-04 1.066E-02 8.247E-02 1.270E-02 8.181E-03 0.000E+00 8.810E-06 Benthic CommunityInfaunal invert. (TL-II) 3.954E-10 1.553E-05 1.614E-06 3.193E-05 3.205E-05 2.934E-06 2.144E-06 0.000E+00 5.984E-09 Epifaunal invert. (TL-II) 5.517E-10 3.249E-05 3.875E-06 8.770E-05 9.664E-05 9.264E-06 6.838E-06 0.000E+00 1.718E-08 Forager (TL-III) 7.142E-10 3.944E-05 6.031E-06 1.823E-04 2.716E-04 2.539E-05 1.730E-05 0.000E+00 2.758E-08 Predator (TL-IV) 1.457E-10 2.423E-05 6.388E-06 3.956E-04 1.192E-03 1.434E-04 1.013E-04 0.000E+00 1.302E-07 

ZOI=2

Tissue Conc. (mg/kg-WW) Mono Di Tri Tetra Penta Hexa Hepta Octa Nona Pelagic CommunityPhytoplankton (TL1) 1.507E-14 3.991E-10 3.211E-11 5.207E-10 6.838E-10 2.735E-11 1.120E-11 0.000E+00 5.047E-15 Zooplankton (TL-II) 3.847E-10 1.429E-05 1.441E-06 2.720E-05 2.698E-05 3.860E-06 3.434E-06 0.000E+00 1.722E-08 Planktivore (TL-III) 1.157E-10 1.610E-05 2.935E-06 1.073E-04 1.913E-04 3.010E-05 2.611E-05 0.000E+00 8.639E-08 Piscivore (TL-IV) 3.024E-11 2.837E-06 7.791E-07 6.270E-05 3.353E-04 9.028E-05 8.828E-05 0.000E+00 2.579E-07 Reef / Vessel CommunityAttached Algae 5.309E-11 1.429E-06 1.209E-07 2.010E-06 3.165E-06 3.078E-07 1.944E-07 0.000E+00 4.372E-10 Sessile filter feeder (TL-II) 9.335E-10 3.149E-05 3.110E-06 5.848E-05 5.662E-05 5.014E-06 3.631E-06 0.000E+00 1.162E-08 Invertebrate Omnivore (TL-II 1.513E-08 1.176E-03 1.737E-04 5.591E-03 9.032E-03 6.389E-04 3.351E-04 0.000E+00 2.343E-07 

Invertebrate Forager (TL-III) 5.231E-08 2.136E-03 3.184E-04 1.075E-02 2.052E-02 1.623E-03 9.003E-04 0.000E+00 9.901E-07 

Vertebrate Forager (TL-III) 1.415E-08 9.949E-04 2.140E-04 1.254E-02 4.459E-02 4.516E-03 2.638E-03 0.000E+00 2.960E-06 Predator (TL-IV) 7.841E-09 5.098E-04 1.205E-04 1.052E-02 8.122E-02 1.244E-02 7.984E-03 0.000E+00 8.585E-06 Benthic CommunityInfaunal invert. (TL-II) 2.514E-10 9.875E-06 1.026E-06 2.030E-05 2.038E-05 1.866E-06 1.363E-06 0.000E+00 3.805E-09 Epifaunal invert. (TL-II) 3.508E-10 2.066E-05 2.464E-06 5.577E-05 6.146E-05 5.891E-06 4.348E-06 0.000E+00 1.092E-08 Forager (TL-III) 4.541E-10 2.508E-05 3.835E-06 1.159E-04 1.727E-04 1.615E-05 1.100E-05 0.000E+00 1.754E-08 Predator (TL-IV) 9.265E-11 1.541E-05 4.062E-06 2.516E-04 7.580E-04 9.120E-05 6.440E-05 0.000E+00 8.279E-08 

Table K-1 - page 1
Table K-1 Cont.

ZOI=3

Tissue Conc. (mg/kg-WW) Mono Di Tri Tetra Penta Hexa Hepta Octa Nona Pelagic CommunityPhytoplankton (TL1) 1.442E-14 3.819E-10 3.073E-11 4.983E-10 6.545E-10 2.618E-11 1.072E-11 0.000E+00 4.831E-15 Zooplankton (TL-II) 3.007E-10 1.117E-05 1.127E-06 2.126E-05 2.109E-05 3.017E-06 2.684E-06 0.000E+00 1.346E-08 Planktivore (TL-III) 9.043E-11 1.258E-05 2.294E-06 8.391E-05 1.495E-04 2.353E-05 2.041E-05 0.000E+00 6.753E-08 Piscivore (TL-IV) 2.364E-11 2.218E-06 6.091E-07 4.901E-05 2.621E-04 7.057E-05 6.900E-05 0.000E+00 2.016E-07 Reef / Vessel CommunityAttached Algae 4.150E-11 1.117E-06 9.453E-08 1.571E-06 2.474E-06 2.406E-07 1.519E-07 0.000E+00 3.418E-10 Sessile filter feeder (TL-II) 7.297E-10 2.461E-05 2.431E-06 4.571E-05 4.425E-05 3.919E-06 2.838E-06 0.000E+00 9.084E-09 Invertebrate Omnivore (TL-II 1.509E-08 1.171E-03 1.729E-04 5.561E-03 8.973E-03 6.330E-04 3.312E-04 0.000E+00 2.273E-07 

Invertebrate Forager (TL-III) 5.224E-08 2.131E-03 3.173E-04 1.070E-02 2.041E-02 1.611E-03 8.923E-04 0.000E+00 9.787E-07 

Vertebrate Forager (TL-III) 1.413E-08 9.913E-04 2.130E-04 1.247E-02 4.432E-02 4.478E-03 2.612E-03 0.000E+00 2.923E-06 Predator (TL-IV) 7.825E-09 5.083E-04 1.201E-04 1.047E-02 8.075E-02 1.235E-02 7.909E-03 0.000E+00 8.499E-06 Benthic CommunityInfaunal invert. (TL-II) 1.965E-10 7.718E-06 8.022E-07 1.587E-05 1.593E-05 1.458E-06 1.066E-06 0.000E+00 2.974E-09 Epifaunal invert. (TL-II) 2.742E-10 1.615E-05 1.926E-06 4.359E-05 4.804E-05 4.604E-06 3.399E-06 0.000E+00 8.539E-09 Forager (TL-III) 3.550E-10 1.960E-05 2.998E-06 9.058E-05 1.350E-04 1.262E-05 8.600E-06 0.000E+00 1.371E-08 Predator (TL-IV) 7.241E-11 1.204E-05 3.175E-06 1.966E-04 5.925E-04 7.128E-05 5.034E-05 0.000E+00 6.471E-08 

ZOI=4

Tissue Conc. (mg/kg-WW) Mono Di Tri Tetra Penta Hexa Hepta Octa Nona Pelagic CommunityPhytoplankton (TL1) 1.406E-14 3.724E-10 2.996E-11 4.859E-10 6.382E-10 2.552E-11 1.046E-11 0.000E+00 4.711E-15 Zooplankton (TL-II) 2.540E-10 9.431E-06 9.514E-07 1.796E-05 1.781E-05 2.548E-06 2.267E-06 0.000E+00 1.137E-08 Planktivore (TL-III) 7.638E-11 1.063E-05 1.938E-06 7.087E-05 1.263E-04 1.987E-05 1.724E-05 0.000E+00 5.703E-08 Piscivore (TL-IV) 1.997E-11 1.873E-06 5.144E-07 4.140E-05 2.214E-04 5.960E-05 5.827E-05 0.000E+00 1.702E-07 Reef / Vessel CommunityAttached Algae 3.504E-11 9.434E-07 7.983E-08 1.327E-06 2.089E-06 2.032E-07 1.283E-07 0.000E+00 2.886E-10 Sessile filter feeder (TL-II) 6.162E-10 2.078E-05 2.053E-06 3.860E-05 3.737E-05 3.310E-06 2.397E-06 0.000E+00 7.672E-09 Invertebrate Omnivore (TL-II 1.507E-08 1.168E-03 1.725E-04 5.545E-03 8.940E-03 6.297E-04 3.290E-04 0.000E+00 2.234E-07 

Invertebrate Forager (TL-III) 5.220E-08 2.127E-03 3.167E-04 1.067E-02 2.034E-02 1.604E-03 8.878E-04 0.000E+00 9.723E-07 

Vertebrate Forager (TL-III) 1.412E-08 9.894E-04 2.125E-04 1.243E-02 4.416E-02 4.458E-03 2.597E-03 0.000E+00 2.902E-06 Predator (TL-IV) 7.815E-09 5.075E-04 1.198E-04 1.044E-02 8.048E-02 1.229E-02 7.868E-03 0.000E+00 8.451E-06 Benthic CommunityInfaunal invert. (TL-II) 1.659E-10 6.518E-06 6.774E-07 1.340E-05 1.345E-05 1.231E-06 8.999E-07 0.000E+00 2.512E-09 Epifaunal invert. (TL-II) 2.316E-10 1.364E-05 1.626E-06 3.681E-05 4.057E-05 3.888E-06 2.870E-06 0.000E+00 7.211E-09 Forager (TL-III) 2.998E-10 1.656E-05 2.531E-06 7.650E-05 1.140E-04 1.066E-05 7.263E-06 0.000E+00 1.158E-08 Predator (TL-IV) 6.115E-11 1.017E-05 2.681E-06 1.661E-04 5.004E-04 6.020E-05 4.251E-05 0.000E+00 5.465E-08 

Table K-1 - page 2
Table K-1 Cont.

ZOI=5

Tissue Conc. (mg/kg-WW) Mono Di Tri Tetra Penta Hexa Hepta Octa Nona Pelagic CommunityPhytoplankton (TL1) 1.382E-14 3.661E-10 2.946E-11 4.777E-10 6.275E-10 2.510E-11 1.028E-11 0.000E+00 4.633E-15 Zooplankton (TL-II) 2.234E-10 8.295E-06 8.368E-07 1.579E-05 1.567E-05 2.241E-06 1.994E-06 0.000E+00 9.996E-09 Planktivore (TL-III) 6.719E-11 9.348E-06 1.704E-06 6.233E-05 1.111E-04 1.748E-05 1.516E-05 0.000E+00 5.016E-08 Piscivore (TL-IV) 1.757E-11 1.648E-06 4.525E-07 3.641E-05 1.947E-04 5.242E-05 5.125E-05 0.000E+00 1.497E-07 Reef / Vessel CommunityAttached Algae 3.082E-11 8.297E-07 7.021E-08 1.167E-06 1.837E-06 1.787E-07 1.128E-07 0.000E+00 2.538E-10 Sessile filter feeder (TL-II) 5.420E-10 1.828E-05 1.806E-06 3.395E-05 3.287E-05 2.911E-06 2.108E-06 0.000E+00 6.748E-09 Invertebrate Omnivore (TL-II 1.505E-08 1.167E-03 1.722E-04 5.534E-03 8.918E-03 6.275E-04 3.276E-04 0.000E+00 2.209E-07 

Invertebrate Forager (TL-III) 5.217E-08 2.125E-03 3.163E-04 1.065E-02 2.030E-02 1.600E-03 8.848E-04 0.000E+00 9.682E-07 

Vertebrate Forager (TL-III) 1.411E-08 9.880E-04 2.121E-04 1.241E-02 4.406E-02 4.444E-03 2.587E-03 0.000E+00 2.889E-06 Predator (TL-IV) 7.809E-09 5.069E-04 1.196E-04 1.042E-02 8.031E-02 1.226E-02 7.840E-03 0.000E+00 8.420E-06 Benthic CommunityInfaunal invert. (TL-II) 1.460E-10 5.733E-06 5.958E-07 1.179E-05 1.183E-05 1.083E-06 7.915E-07 0.000E+00 2.209E-09 Epifaunal invert. (TL-II) 2.037E-10 1.199E-05 1.431E-06 3.238E-05 3.568E-05 3.420E-06 2.525E-06 0.000E+00 6.343E-09 Forager (TL-III) 2.636E-10 1.456E-05 2.226E-06 6.728E-05 1.003E-04 9.375E-06 6.388E-06 0.000E+00 1.018E-08 Predator (TL-IV) 5.379E-11 8.946E-06 2.358E-06 1.461E-04 4.401E-04 5.295E-05 3.739E-05 0.000E+00 4.806E-08 

ZOI=10

Tissue Conc. (mg/kg-WW) Mono Di Tri Tetra Penta Hexa Hepta Octa Nona Pelagic CommunityPhytoplankton (TL1) 1.326E-14 3.513E-10 2.827E-11 4.585E-10 6.023E-10 2.410E-11 9.872E-12 0.000E+00 4.449E-15 Zooplankton (TL-II) 1.517E-10 5.634E-06 5.684E-07 1.073E-05 1.064E-05 1.522E-06 1.354E-06 0.000E+00 6.788E-09 Planktivore (TL-III) 4.564E-11 6.349E-06 1.158E-06 4.234E-05 7.545E-05 1.187E-05 1.030E-05 0.000E+00 3.406E-08 Piscivore (TL-IV) 1.194E-11 1.119E-06 3.074E-07 2.473E-05 1.323E-04 3.560E-05 3.480E-05 0.000E+00 1.017E-07 Reef / Vessel CommunityAttached Algae 2.093E-11 5.634E-07 4.767E-08 7.923E-07 1.248E-06 1.213E-07 7.662E-08 0.000E+00 1.724E-10 Sessile filter feeder (TL-II) 3.680E-10 1.241E-05 1.226E-06 2.306E-05 2.232E-05 1.977E-06 1.431E-06 0.000E+00 4.582E-09 Invertebrate Omnivore (TL-II 1.502E-08 1.163E-03 1.715E-04 5.509E-03 8.868E-03 6.224E-04 3.242E-04 0.000E+00 2.149E-07 

Invertebrate Forager (TL-III) 5.211E-08 2.120E-03 3.153E-04 1.061E-02 2.021E-02 1.589E-03 8.779E-04 0.000E+00 9.585E-07 

Vertebrate Forager (TL-III) 1.409E-08 9.850E-04 2.113E-04 1.235E-02 4.383E-02 4.412E-03 2.564E-03 0.000E+00 2.857E-06 Predator (TL-IV) 7.795E-09 5.056E-04 1.192E-04 1.037E-02 7.990E-02 1.218E-02 7.776E-03 0.000E+00 8.347E-06 Benthic CommunityInfaunal invert. (TL-II) 9.910E-11 3.893E-06 4.046E-07 8.004E-06 8.036E-06 7.355E-07 5.375E-07 0.000E+00 1.500E-09 Epifaunal invert. (TL-II) 1.383E-10 8.144E-06 9.714E-07 2.199E-05 2.423E-05 2.322E-06 1.714E-06 0.000E+00 4.307E-09 Forager (TL-III) 1.790E-10 9.887E-06 1.512E-06 4.569E-05 6.809E-05 6.366E-06 4.337E-06 0.000E+00 6.915E-09 Predator (TL-IV) 3.652E-11 6.074E-06 1.601E-06 9.918E-05 2.989E-04 3.595E-05 2.539E-05 0.000E+00 3.264E-08 

Table K-1 - page 3
Table K-2. Summary of BAFs (L/Kg-lipid) calculated by PRAM for ZOI=1, 2, 5, and 10.

ZOI=1

BAFs (L/kg-lipid) Mono Di Tri Tetra Penta Hexa Hepta Octa Nona Deca

Pelagic Community

Phytoplankton (TL1) 2.979E+04 1.000E+05 1.000E+05 1.000E+05 1.000E+05 1.000E+05 1.000E+05 0.000E+00 1.000E+05 1.000E+05

Zooplankton (TL-II) 1.347E+05 6.237E+05 7.436E+05 8.445E+05 5.319E+05 7.826E+05 1.103E+06 0.000E+00 2.458E+06 8.127E+06

Planktivore (TL-III) 7.604E+04 1.320E+06 2.844E+06 6.259E+06 7.084E+06 1.147E+07 1.576E+07 0.000E+00 2.317E+07 2.729E+07

Piscivore (TL-IV) 1.988E+04 2.326E+05 7.549E+05 3.656E+06 1.242E+07 3.439E+07 5.326E+07 0.000E+00 6.917E+07 3.375E+07

Reef / Vessel Community

Attached Algae 2.979E+04 1.000E+05 1.000E+05 1.000E+05 1.000E+05 1.000E+05 1.000E+05 0.000E+00 1.000E+05 1.000E+05

Sessile filter feeder (TL-II) 9.590E+05 4.034E+06 4.709E+06 5.328E+06 3.275E+06 2.983E+06 3.420E+06 0.000E+00 4.867E+06 1.181E+07

Invertebrate Omnivore (TL-II 3.231E+04 3.143E+05 5.495E+05 1.066E+06 1.097E+06 8.039E+05 6.721E+05 0.000E+00 2.185E+05 7.246E+04

Invertebrate Forager (TL-III) 1.634E+05 8.353E+05 1.474E+06 3.001E+06 3.648E+06 2.981E+06 2.630E+06 0.000E+00 1.294E+06 1.856E+06

Vertebrate Forager (TL-III) 1.502E+04 1.324E+05 3.373E+05 1.193E+06 2.698E+06 2.825E+06 2.627E+06 0.000E+00 1.318E+06 9.538E+05

Predator (TL-IV) 1.243E+04 1.010E+05 2.827E+05 1.490E+06 7.321E+06 1.159E+07 1.183E+07 0.000E+00 5.661E+06 2.739E+06

Benthic Community

Infaunal invert. (TL-II) 2.429E+05 1.190E+06 1.462E+06 1.740E+06 1.109E+06 1.044E+06 1.208E+06 0.000E+00 1.499E+06 2.389E+06

Epifaunal invert. (TL-II) 3.013E+05 2.213E+06 3.119E+06 4.248E+06 2.973E+06 2.930E+06 3.425E+06 0.000E+00 3.825E+06 4.691E+06

Forager (TL-III) 1.759E+05 1.212E+06 2.189E+06 3.981E+06 3.768E+06 3.622E+06 3.908E+06 0.000E+00 2.770E+06 1.421E+06

Predator (TL-IV) 1.557E+04 3.231E+05 1.006E+06 3.750E+06 7.176E+06 8.877E+06 9.928E+06 0.000E+00 5.673E+06 1.865E+06

9.590E+05 4.034E+06 4.709E+06 6.259E+06 1.242E+07 3.439E+07 5.326E+07 0.000E+00 6.917E+07 3.375E+07

ZOI=2

BAFs (L/kg-lipid) Mono Di Tri Tetra Penta Hexa Hepta Octa Nona Deca

Pelagic Community

Phytoplankton (TL1) 2.979E+04 1.000E+05 1.000E+05 1.000E+05 1.000E+05 1.000E+05 1.000E+05 0.000E+00 1.000E+05 1.000E+05

Zooplankton (TL-II) 1.347E+05 6.238E+05 7.436E+05 8.445E+05 5.320E+05 7.826E+05 1.103E+06 0.000E+00 2.458E+06 8.127E+06

Planktivore (TL-III) 7.603E+04 1.320E+06 2.843E+06 6.258E+06 7.083E+06 1.146E+07 1.576E+07 0.000E+00 2.317E+07 2.729E+07

Piscivore (TL-IV) 1.988E+04 2.326E+05 7.548E+05 3.655E+06 1.242E+07 3.439E+07 5.326E+07 0.000E+00 6.917E+07 3.375E+07

Reef / Vessel Community

Attached Algae 2.979E+04 1.000E+05 1.000E+05 1.000E+05 1.000E+05 1.000E+05 1.000E+05 0.000E+00 1.000E+05 1.000E+05

Sessile filter feeder (TL-II) 9.590E+05 4.034E+06 4.709E+06 5.328E+06 3.276E+06 2.983E+06 3.420E+06 0.000E+00 4.867E+06 1.181E+07

Invertebrate Omnivore (TL-II 3.226E+04 3.127E+05 5.460E+05 1.057E+06 1.085E+06 7.891E+05 6.556E+05 0.000E+00 2.037E+05 6.157E+04

Invertebrate Forager (TL-III) 1.633E+05 8.319E+05 1.465E+06 2.976E+06 3.608E+06 2.934E+06 2.578E+06 0.000E+00 1.260E+06 1.842E+06

Vertebrate Forager (TL-III) 1.501E+04 1.316E+05 3.345E+05 1.180E+06 2.664E+06 2.774E+06 2.567E+06 0.000E+00 1.280E+06 9.414E+05

Predator (TL-IV) 1.243E+04 1.008E+05 2.815E+05 1.479E+06 7.250E+06 1.142E+07 1.161E+07 0.000E+00 5.547E+06 2.726E+06

Benthic Community

Infaunal invert. (TL-II) 2.429E+05 1.190E+06 1.462E+06 1.740E+06 1.109E+06 1.044E+06 1.208E+06 0.000E+00 1.499E+06 2.389E+06

Epifaunal invert. (TL-II) 3.013E+05 2.213E+06 3.119E+06 4.248E+06 2.973E+06 2.930E+06 3.425E+06 0.000E+00 3.825E+06 4.691E+06

Forager (TL-III) 1.759E+05 1.212E+06 2.189E+06 3.981E+06 3.768E+06 3.622E+06 3.909E+06 0.000E+00 2.770E+06 1.421E+06

Predator (TL-IV) 1.557E+04 3.231E+05 1.006E+06 3.750E+06 7.177E+06 8.877E+06 9.928E+06 0.000E+00 5.673E+06 1.865E+06

Table K-2 - page 1
Table K-2 Cont.

ZOI=5

BAFs (L/kg-lipid) Mono Di Tri Tetra Penta Hexa Hepta Octa Nona Deca

Pelagic Community

Phytoplankton (TL1) 2.979E+04 1.000E+05 1.000E+05 1.000E+05 1.000E+05 1.000E+05 1.000E+05 0.000E+00 1.000E+05 1.000E+05

Zooplankton (TL-II) 1.347E+05 6.238E+05 7.437E+05 8.446E+05 5.321E+05 7.827E+05 1.103E+06 0.000E+00 2.458E+06 8.127E+06

Planktivore (TL-III) 7.602E+04 1.319E+06 2.842E+06 6.256E+06 7.082E+06 1.146E+07 1.575E+07 0.000E+00 2.317E+07 2.729E+07

Piscivore (TL-IV) 1.988E+04 2.325E+05 7.546E+05 3.654E+06 1.241E+07 3.439E+07 5.326E+07 0.000E+00 6.917E+07 3.375E+07

Reef / Vessel Community

Attached Algae 2.979E+04 1.000E+05 1.000E+05 1.000E+05 1.000E+05 1.000E+05 1.000E+05 0.000E+00 1.000E+05 1.000E+05

Sessile filter feeder (TL-II) 9.590E+05 4.034E+06 4.709E+06 5.328E+06 3.276E+06 2.983E+06 3.420E+06 0.000E+00 4.867E+06 1.181E+07

Invertebrate Omnivore (TL-II 3.223E+04 3.116E+05 5.434E+05 1.051E+06 1.076E+06 7.781E+05 6.433E+05 0.000E+00 1.928E+05 5.351E+04

Invertebrate Forager (TL-III) 1.633E+05 8.295E+05 1.459E+06 2.957E+06 3.579E+06 2.899E+06 2.540E+06 0.000E+00 1.235E+06 1.831E+06

Vertebrate Forager (TL-III) 1.500E+04 1.310E+05 3.324E+05 1.170E+06 2.639E+06 2.736E+06 2.523E+06 0.000E+00 1.252E+06 9.322E+05

Predator (TL-IV) 1.243E+04 1.006E+05 2.806E+05 1.470E+06 7.197E+06 1.130E+07 1.144E+07 0.000E+00 5.462E+06 2.716E+06

Benthic Community

Infaunal invert. (TL-II) 2.429E+05 1.190E+06 1.462E+06 1.740E+06 1.109E+06 1.044E+06 1.208E+06 0.000E+00 1.499E+06 2.389E+06

Epifaunal invert. (TL-II) 3.013E+05 2.213E+06 3.119E+06 4.248E+06 2.973E+06 2.930E+06 3.425E+06 0.000E+00 3.825E+06 4.691E+06

Forager (TL-III) 1.759E+05 1.212E+06 2.189E+06 3.981E+06 3.768E+06 3.622E+06 3.909E+06 0.000E+00 2.770E+06 1.421E+06

Predator (TL-IV) 1.557E+04 3.231E+05 1.006E+06 3.751E+06 7.177E+06 8.878E+06 9.928E+06 0.000E+00 5.673E+06 1.865E+06

ZOI=10

BAFs (L/kg-lipid) Mono Di Tri Tetra Penta Hexa Hepta Octa Nona Deca

Pelagic Community

Phytoplankton (TL1) 2.979E+04 1.000E+05 1.000E+05 1.000E+05 1.000E+05 1.000E+05 1.000E+05 0.000E+00 1.000E+05 1.000E+05

Zooplankton (TL-II) 1.347E+05 6.239E+05 7.438E+05 8.447E+05 5.321E+05 7.827E+05 1.103E+06 0.000E+00 2.458E+06 8.127E+06

Planktivore (TL-III) 7.601E+04 1.319E+06 2.841E+06 6.254E+06 7.080E+06 1.146E+07 1.575E+07 0.000E+00 2.317E+07 2.729E+07

Piscivore (TL-IV) 1.988E+04 2.325E+05 7.544E+05 3.653E+06 1.241E+07 3.438E+07 5.325E+07 0.000E+00 6.917E+07 3.375E+07

Reef / Vessel Community

Attached Algae 2.979E+04 1.000E+05 1.000E+05 1.000E+05 1.000E+05 1.000E+05 1.000E+05 0.000E+00 1.000E+05 1.000E+05

Sessile filter feeder (TL-II) 9.590E+05 4.035E+06 4.709E+06 5.329E+06 3.276E+06 2.983E+06 3.421E+06 0.000E+00 4.867E+06 1.181E+07

Invertebrate Omnivore (TL-II 3.221E+04 3.111E+05 5.422E+05 1.048E+06 1.071E+06 7.733E+05 6.379E+05 0.000E+00 1.879E+05 4.991E+04

Invertebrate Forager (TL-III) 1.632E+05 8.284E+05 1.456E+06 2.949E+06 3.565E+06 2.883E+06 2.523E+06 0.000E+00 1.224E+06 1.827E+06

Vertebrate Forager (TL-III) 1.500E+04 1.308E+05 3.315E+05 1.166E+06 2.628E+06 2.720E+06 2.503E+06 0.000E+00 1.240E+06 9.282E+05

Predator (TL-IV) 1.243E+04 1.005E+05 2.801E+05 1.466E+06 7.174E+06 1.124E+07 1.137E+07 0.000E+00 5.425E+06 2.712E+06

Benthic Community

Infaunal invert. (TL-II) 2.429E+05 1.190E+06 1.462E+06 1.740E+06 1.109E+06 1.044E+06 1.208E+06 0.000E+00 1.499E+06 2.389E+06

Epifaunal invert. (TL-II) 3.013E+05 2.213E+06 3.120E+06 4.249E+06 2.974E+06 2.930E+06 3.426E+06 0.000E+00 3.825E+06 4.691E+06

Forager (TL-III) 1.759E+05 1.212E+06 2.190E+06 3.982E+06 3.768E+06 3.622E+06 3.909E+06 0.000E+00 2.770E+06 1.421E+06

Predator (TL-IV) 1.557E+04 3.231E+05 1.006E+06 3.751E+06 7.178E+06 8.878E+06 9.929E+06 0.000E+00 5.673E+06 1.865E+06

9.590E+05 4.035E+06 4.709E+06 6.254E+06 1.241E+07 3.438E+07 5.325E+07 0.000E+00 6.917E+07 3.375E+07

Table K-2 - page 2
Data from Stapleton et al. 2001 sumPCB

Lake Pelagic TL ng/g lipid 3:2 / 4:3 4:2 sumPCB n 3:2 / 4:3 4:2 

Zooplankton 2.00 1120.0 351.0 Alewife 3.00 4957.4 3.0 2144.7 4.1 Lake Trout 4.00 8522.7 1.3 3.8 4048.1 1.4 5.8 

Lake Demersal

Mysid 2.00 828.6 378.9 Bloater 3.00 13135.6 10.6 6740.5 11.9 Burbot 4.00 17750.0 1.0 10.7 17750.0 2.0 23.4 

Lake Benthic

Amphipod 2.00 1447.1 670.8 Sculpin 3.00 3468.2 1.6 1479.8 1.5 Salmon 4.00 23788.5 5.1 8.2 23788.5 12.1 17.7 Data from Mackintosh et al. 2004

PCB118

Coastal Pelagic TL ng/g lipid 3:2 / 4:3 4:2 PCB118 ng 3:2 / 4:3 4:2 

Juvenile Perch 2.30 263.0 166.0 Greenling 3.81 354.8 0.8 95.5 0.3 Dogfish 4.07 645.7 1.7 1.4 302.0 3.0 1.0 

Coastal Demersal

Oyster 2.48 64.6 37.2 Crab 3.55 467.7 5.1 245.5 4.6 Dogfish 4.07 645.7 1.2 6.1 302.0 1.1 5.0 

Coastal Benthic

Manila Clam/Geoduck Clam 2.40 34.5 3.0 English Sole 3.64 549.5 10.5 112.2 25.1 Dogfish 4.07 645.7 1.1 11.0 302.0 2.4 60.3 Reported by Fisk, Hobson, & Norstrom 2001

Arctic Benthic TL sumPCB 3:2 / 4:3 4:2

Copepod 2.0Amphipod 2.6 7.8Artic Cod 3.7 0.9Table K-3. Calculation of PCB biomagnification factors (BMFTLC) for trophic levels (TL) 3:2, 4:3, and 4:2 observed in pelagic, demersaGrand Traverse Bay, Lake Michigan (Stapleton et al. 2001), False Creek Harbor, Vancouver, BC Canada (Mackintosh et al. 2004), a Northwater Polynya, Arctic (Fisk, Hobson, & Norstrom 2001), and predicted by PRAM.

average average - std

BMFTLC BMFTLC 

BMFTLC BMFTLC BMFTLC

Table K-3 - page 1
Table K-3 Cont.

Data from PRAM 1.4CTissue Conc. (mg/kg-lipid) mg/Kg Lipid

Pelagic Community TL Total PCB 3:2 / 4:3 4:2

Phytoplankton (TL1) 1.00 1.02E-07Zooplankton (TL-II) 2.06 0.001462Planktivore (TL-III) 3.06 0.005323 2.4Piscivore (TL-IV) 3.96 0.008262 1.2 2.9

Reef / Vessel Community

Attached Algae 1.00 0.000439Sessile filter feeder (TL-II) 2.13 0.017595Invertebrate Omnivore (TL-II) 2.23 0.324634Invertebrate Forager (TL-III) 3.18 1.518546 3.3Vertebrate Forager (TL-III) 2.96 0.932337 2.2Predator (TL-IV) 3.95 1.605862 1.3 2.79

Benthic Community

Infaunal invert. (TL-II) 2.46 0.005729Epifaunal invert. (TL-II) 2.70 0.013991Forager (TL-III) 3.52 0.014441 1.8Predator (TL-IV) 4.10 0.021541 1.3 2.3

BMFTLC

Table K-3 - page 2
Food Chain chemical log(Kow) b r

2 FWMF

PELAGIC Mono 4.474 -1.488 1.00 0.23

PELAGIC Di 5.236 -0.9857 0.79 0.37

PELAGIC Tri 5.521 -0.4574 0.41 0.63

PELAGIC Tetra 5.922 0.304 0.28 1.36

PELAGIC Penta 6.4951 1.1852 0.94 3.27

PELAGIC Hexa 6.9761 1.5136 0.99 4.54

PELAGIC Hepta 7.19 1.5619 0.99 4.77

PELAGIC Nona 8.351 1.2752 0.99 3.58

PELAGIC Deca 9.603 0.2675 0.99 1.31

REEF Mono 4.474 0.1444 0.00 1.16

REEF Di 5.236 0.2575 0.03 1.29

REEF Tri 5.521 0.6319 0.13 1.88

REEF Tetra 5.922 1.316 0.38 3.73

REEF Penta 6.4951 2.285 0.63 9.83

REEF Hexa 6.9761 2.6 0.73 13.46

REEF Hepta 7.19 2.597 0.77 13.42

REEF Nona 8.351 2.3579 0.89 10.57

REEF Deca 9.603 2.1129 0.79 8.27

BENTHIC Mono 4.474 -1.576 0.75 0.21

BENTHIC Di 5.236 -0.865 0.65 0.42

BENTHIC Tri 5.521 -0.34 0.28 0.71

BENTHIC Tetra 5.922 0.3047 0.30 1.36

BENTHIC Penta 6.4951 0.9336 0.83 2.54

BENTHIC Hexa 6.9761 1.0687 0.85 2.91

BENTHIC Hepta 7.19 1.0346 0.82 2.81

BENTHIC Nona 8.351 0.5492 0.55 1.73

BENTHIC Deca 9.603 -0.4238 0.39 0.65

Table K-4. The food web magnification factor (FWMF) calculated from the regression of ln(PCB) 

versus TL to obtain the slope (b) for the accumulation of each homolog in the pelagic, reef, and 

benthic communities modeled by PRAM.

Table K-4
Appendix K Figures 

K - 15
0

25

50

75

100

125

150

175

200

225

012 345678 9 10 11

ZOI

Met

ers

y = 388760x - 53776

y = 116628x

y = 77752x - 2E-10 0

1,000,000

2,000,000

3,000,000

4,000,000

5,000,000

012345 6789 10 11

ZOI

Volu

m

e (m3

)

Lower Water Column

Upper Water Column

B.

A.

y = 777.52x - 777.52

0

1000

2000

3000

4000

5000

6000

7000

8000

0 1 2 3 4 5 6 7 8 9 10 11

ZOI

Volu

m

e (

m3

)

Sediment

Air

C.

Fig. K-1. The change in physical dimensions of PRAM as a function of ZOI for distance from 

ship (A), the volumes of the upper and lower water columns (B), and the sediment bed (C). 

interior vessel volume remains constant at 5.38 x 104 m3.
1.E-10

1.E-09

1.E-08

1.E-07

1.E-06

1.E-05

1.E-04

1.E-03

0.0 2.0 4.0 6.0 8.0 10.0 12.0

ZOI

Total PC

B

m

g/L

Sed. Pore Wat

Upper Water C

Water Concentration

0.E+00

5.E-07

1.E-06

2.E-06

2.E-06

3.E-06

3.E-06

0.0 2.0 4.0 6.0 8.0 10.0 12.0

ZOI

Total P

C

B mg/L

Lower Water Column

Sed. Pore Water

Upper Water Column

Water Concentration

0.E+00

1.E-09

2.E-09

3.E-09

4.E-09

5.E-09

6.E-09

7.E-09

8.E-09

0.0 2.0 4.0 6.0 8.0 10.0 12.0

ZOI

T

otal PC

B

mg/L

Sed. Pore Water

Upper Water Column

Fig. K-2. Changes in Total PCB concentration in bulk water compartments in PRAM as a 

function of changing ZOI. Note that the concentration of Total PCB inside the vessel did not 

change as a function of ZOI.
1.E-06

1.E-05

1.E-04

0.0 2.0 4.0 6.0 8.0 10.0 12

ZOI

T

otal P

C

B m

g/K

g

Sedi

Sediment Concentration

0.0E+00

2.0E-06

4.0E-06

6.0E-06

8.0E-06

1.0E-05

1.2E-05

0.0 2.0 4.0 6.0 8.0 10.0 12

ZOI

Tot

al P

C

B m

g/Kg 

Sedi

Fig. K-3. Concentrations of Total PCB in the bulk sediment compartment of PRAM as a funct

ZOI.
1.E-17

1.E-16

1.E-15

0.0 2.0 4.0 6.0 8.0 10.0 12

ZOI

Total PC

B g/

m3 

Concentration in Air

0.0E+00

2.0E-17

4.0E-17

6.0E-17

8.0E-17

1.0E-16

1.2E-16

1.4E-16

0.0 2.0 4.0 6.0 8.0 10.0 12

ZOI

Total P

C

B g/

m3 

A

Fig. K-4. The concentration of Total PCB in the air compartment of PRAM as a function of Z
Pelagic Community

1.E-09

1.E-08

1.E-07

1.E-06

1.E-05

1.E-04

1.E-03

1.E-02

1.E-01

1.E+00

0.0 2.0 4.0 6.0 8.0 10.0 12.0

ZOI

Total PCB mg/Kg W

W

Piscivore (IV)

Planktivore (III)

Zoo (II)

Phyto (I)

Pelagic Community

0.000000

0.000100

0.000200

0.000300

0.000400

0.000500

0.000600

0.000700

0.000800

0.000900

0.001000

0.0 2.0 4.0 6.0 8.0 10.0 

ZOI

Total PCB mg/Kg W

W

Benthic Community

1.E-05

1.E-04

1.E-03

1.E-02

1.E-01

1.E+00

02468 10 12

ZOI

Total PCB (mg/Kg W

W)

Predator (IV)

Forager (III)

Epifauna (II)

Infauna (II)

Benthic Community

0.0000

0.0002

0.0004

0.0006

0.0008

0.0010

0.0012

0.0014

0.0016

0.0018

0.0020

0 246 8 10 

ZOI

Total PCB (mg/Kg W

W)

Reef Community

1.E-06

1.E-05

1.E-04

1.E-03

1.E-02

1.E-01

1.E+00

0.0 2.0 4.0 6.0 8.0 10.0 12.0

ZOI

Total PCB (mg/Kg W

W)

Predator (IV)

Vert. Forager (III)

Invert. Forager (III)

Invert. Omniv. (III)

Sessile F. F. (II)

Encrus. Alage (I)

Reef Community

0.00

0.02

0.04

0.06

0.08

0.10

0.12

0.14

0.0 2.0 4.0 6.0 8.0 10.0 

ZOI

Total PCB (

mg/Kg W

W)

Pre

Ve

Inve

Inve

Ses

Enc

Fig. K-5. Change in concentration of Total PCB in food chains of pelagic, benthic, and reef 

communities modeled by PRAM as a function of changes in the ZOI. Data are ploted on log 

(left panels) and linear (right panels) y-axes.
1.E+04

1.E+05

1.E+06

1.E+07

1.E+08

1.E+09

4.0 5.0 6.0 7.0 8.0 9.0 10.0

Log(Kow)

B

AF (

L/Kg Li

pid)

Phyto

Benthic Community (ZOI=1)

1.E+04

1.E+05

1.E+06

1.E+07

1.E+08

1.E+09

4.0 5.0 6.0 7.0 8.0 9.0 10.0

Log(Kow)

B

AF (

L/Kg Lipid)

Flounder

Lobster

Nematode

Polychaete

Reef Community (ZOI=1)

1.E+04

1.E+05

1.E+06

1.E+07

1.E+08

1.E+09

4.0 5.0 6.0 7.0 8.0 9.0 10.0

Log(Kow)

B

AF (

L/K

g Lipid)

Grouper

Triggerfish

Crab

Urchin

Bivalve

Algae

Fig. K-6. The BAFLIPID obtained from PRAM with a ZOI=1 for the components of the pelagic

benthic, and reef communities as a function of Log(Kow).
Pentachlorobiphenyl

97.5%

98.0%

98.5%

99.0%

99.5%

100.0%

100.5%

024 ZOI 6 8 10

BAF (L/Kg Lipid)

Jack

Grouper

Flounder

96.5%

97.0%

97.5%

98.0%

98.5%

99.0%

99.5%

100.0%

100.5%

024 ZOI 6 8 

B

AF (L/Kg Lipid)

J

G

F

Hexachlorobiphenyl

%

of nI it ai l B

A

F (L

pi di )

%

of nI it ai l B

A

F (L

pi di )

A.

95.0%

96.0%

97.0%

98.0%

99.0%

100.0%

101.0%

0 2 4 ZOI 6 8 10

BAF (L/Kg Lipid)

Jack

Grouper

Flounder

Heptachlorobiphenyl

95.0%

96.0%

97.0%

98.0%

99.0%

100.0%

101.0%

0 2 4 ZOI 6 8 

BAF (L/Kg Lipid)

J

G

F

Heptachlorobiphenyl

%

of nI it ai l B

A

F (L

pi di )

%

of nI it ai l B

A

F (L

pi di )

Triggerfish Bioaccumulation

93%

94%

95%

96%

97%

98%

99%

100%

0 2 4 6 8 10 

ZOI

% of Initial B

A

F (

Lipid)

Pe

He

He

No

B.

Fig. K-7. Changes in the BAFLIPID for the upper trophic level (TL=IV) fishes (A) and for

triggerfish (TL=3, B) as a function of ZOI and homolog.
0.0000001

0.000001

0.00001

0.0001

0.001

0.01

0.1

1

5.000 5.500 6.000 6.500 7.000 7.500

Log(Kow)

PCB m

g/K

g wet

Jackson Chinook

Benthic Community

0.000001

0.00001

0.0001

0.001

0.01

0.1

1

5.000 5.500 6.000 6.500 7.000 7.500

Log(Kow)

P

C

B m

g/K

g wet

PRAM Predator (IV

Jackson Coho

Jackson Chinook

B.

Fig. K-8. PCB homolog concentrations in top predators in the pelagic and benthic food chain

predicted by PRAM compared to the concentrations predicted for Coho and Chinook salmon

using the slope and intercept of the regressions reported by Jackson et al. 2001.
0

0.001

0.002

0.003

0.004

0.005

0.006

Piscivore

(I

V)

Co

h

o

Chin

o

o

k

Predator

(IV)

Co

h

o

Chin

o

o

k

Tot

alP

C

B m

g/K

g

PRAM Jackson et al. 2001

Pelagic Community Benthic Community

Fig. K-9. Total PCB concentrations in top predators in the Pelagic and Benthic food chains 

predicted by PRAM compared to the concentrations predicted for Coho and Chinook salmon

using the slope and intercept of the regressions reported by Jackson et al. 2001.
Pelagic Community

0.0000001

0.000001

0.00001

0.0001

0.001

0.01

0.1

1

5.000 5.500 6.000 6.500 7.000 7.500

Log(Kow)

PCB m

g/K

g w

et

PRAM Piscivore (IV

Jackson Coho

Jackson Chinook

Benthic Community

0.000001

0.00001

0.0001

0.001

0.01

0.1

1

5.000 5.500 6.000 6.500 7.000 7.500

Log(Kow)

P

C

B m

g/K

g wet

PRAM Predator (IV

Jackson Coho

Jackson Chinook

Fig. K-10. PCB homolog concentrations in top predators in the Pelagic and Benthic food cha

predicted by PRAM compared to the concentrations predicted for Coho and Chinook salmon

using just the slope of the regressions reported by Jackson et al. 2001.
0

0.001

0.002

0.003

0.004

0.005

Piscivore

(I

V)

Co

h

o

Chin

o

o

k

Predator

(IV)

Co

h

o

Chin

o

o

k

Tot

alP

C

B m

g/K

g

PRAM Jackson et al. 2001

Pelagic Community Benthic Community

Fig. K-11. Total PCB concentrations in top predators in the Pelagic and Benthic food chains 

predicted by PRAM compared to the concentrations predicted for Coho and Chinook salmon

using just the slope of the regressions reported by Jackson et al. 2001.
Biomagnification Factors (BMF)

0.1

1.0

10.0

100.0

Pela

gic

3:

2

Pela

gic

4:

3

Pela

gic

4:

2

Dem

ersal

3:

2

Dem

ersal

4:

3

Dem

ersal

4:

2

B

enthi

c

3:

2

B

enthi

c

4:

3

B

enthi

c

4:

2

BM

F

PRAM

Stapleton 2001 Lk. 

Fisk 2001 Arctic

Mackintosh BC Coa

Fig. K-12. Comparison of PCB biomagnification factors (BMFTLC) for trophic levels 3:2, 4:3, a

4:2 predicted by PRAM and observed in pelagic, demersal, and benthic food webs from Gra

Traverse Bay, Lake Michigan (Stapleton et al. 2001), False Creek Harbor, Vancouver, BC 

Canada (Mackintosh et al. 2004), and a demersal food web from the Northwater Polynya, 

Arctic (Fisk, Hobson, & Norstrom 2001).
Fig. K-13. BAFLIPID s reported for PCB congeners in Burkhard et al. (2003).
Trophic Level III

4

5

6

7

8

9

4 5 678 9 

Log(Kow)

Log(

B

AF [

L/Kg Lipid])

PRAM Herring

PRAM Trigger

PRAM Crab

PRAM Lobste

Burkhard et al. 

Trophic Level IV

4

5

6

7

8

9

10

4 5 678 9 

Log(Kow)

Log(

B

A

F [

L/Kg Lipid])

PRAM Jack

PRAM Groupe

PRAM Flound

Burkhard et al. 

Fig. K-14. Comparison of the lipid-based bioaccumulation factors (BAFLIPID s) predicted by 

PRAM and BAFs reported in the literature from Green Bay Lake Michigan, the Hudson River

and Lake Ontario for Trophic Level III (A) and Trophic Level IV (B) predators.
y = 0.1444x - 8.6281

R2 = 0.0075

y = -1.4888x - 8.7676

R2

 = 1

y = -1.576x - 6.2217

R2

 = 0.7531

-16

-14

-12

-10

-8

-6

-4

-2

1 1.5 2 2.5 3 3.5 4 4.5

Trophic Level

Ln(P

C

B ng/g Lipi

d)

REEF

PELAGIC

BENTHIC

Biomagnification of Dichlorobiphenyl

y = 0.2575x + 1.9547

R2

 = 0.0246

y = -0.9857x + 0.9829

R2

 = 0.7908

y = -0.8653x + 2.6319

R2 = 0.6508

-4

-3

-2

-1

0

1

2

3

4

5

1 1.5 2 2.5 3 3.5 4 4.5

Trophic Level

Ln(P

C

B n

g/g Lipi

d)

REEF

PELAGIC

BENTHIC

REEF

PELAGIC

BENTHIC

Biomagnification of Trichlorobiphenyl

y = 0.6319x - 0.9493

R2

 = 0.1276

y = -0.4574x - 2.3768

R2

 = 0.4122

y = -0.34x - 0.9481

R2

 = 0.275

-5

-4

-3

-2

-1

0

1

2

3

1 1.5 2 2.5 3 3.5 4 4.5

Trophic Level

Ln(P

C

B ng/g Lipid)

REEF

PELAGIC

BENTHIC

REEF

PELAGIC

BENTHIC

Fig. K-15. Biomagnification of mono-, di-, and trichlorobiphenyl predicted by PRAM.
R2

 = 0.3772

y = 0.304x - 1.0366

R2

 = 0.2825

y = 0.3047x + 0.4003

R2 = 0.3041

-2

-1

0

1

2

3

4

5

6

7

1 1.5 2 2.533.5 4 4.5

Trophic Level

Ln(

P

C

B ng/g Lipid)

BENTHIC

REEF

PELAGIC

BENTHIC

Biomagnification of Pentachlorobiphenyl

y = 2.2825x - 1.1448

R2

 = 0.6309

y = 1.1852x - 2.9518

R2

 = 0.9391

y = 0.9336x - 1.2098

R2

 = 0.8309

-2

0

2

4

6

8

10

12345

Trophic Level

Ln(P

C

B ng/g Lipid)

REEF

PELAGIC

BENTHIC

REEF

PELAGIC

BENTHIC

REEF Biomagnification of Hexachlorobiphenyl

y = 2.6x - 4.4176

R2

 = 0.7305

y = 1.5136x - 5.6464

R2

 = 0.9893

y = 1.0689x - 3.9482

R2

 = 0.8459

-4

-3

-2

-1

0

1

2

3

4

5

6

7

1 1.522.5 3 3.5 4 4.5

Trophic Level

Ln(P

C

B ng/g Lipid)

PELAGIC

BENTHIC

REEF

PELAGIC

BENTHIC

Fig. K-16. Biomagnification of tetra-, penta-, and hexachlorobiphenyl predicted by PRAM.
y = 2.597x - 4.9164

R2 = 0.7703

y = 1.5619x - 5.8863

R2

 = 0.9949

y = 1.0346x - 4.1757

R2

 = 0.8238

-4

-3

-2

-1

0

1

2

3

4

5

6

1 1.5 2 2.533.5 4 4.5

Trophic Level

Ln(

P

C

B ng/g Lipid)

REEF

PELAGIC

BENTHIC

Biomagnification of Nonachlorobiphenyl

y = 2.3579x - 10.916

R2 = 0.8901

y = 1.2752x - 10.634

R2

 = 0.9994

y = 0.5492x - 8.8654

R2

 = 0.545

-9

-8

-7

-6

-5

-4

-3

-2

-1

0

1 1.522.5 3 3.544.5

Trophic Level

Ln(

P

C

B ng/g Lipid)

REEF

PELAGIC

BENTHIC

REEF

PELAGIC

BENTHIC

Biomagnification of Decachlorobiphenyl

y = 2.1129x - 13.505

R2

 = 0.7907

y = 0.2675x - 10.481

R2

 = 0.996

y = -0.4238x - 9.1392

R2

 = 0.3931

-12

-11

-10

-9

-8

-7

-6

-5

-4

1 1.5 2 2.5 3 3.5 4 4.5

Trophic Level

Ln(

P

C

B ng/g Lipid)

REEF

PELAGIC

BENTHIC

REEF

PELAGIC

BENTHIC

Fig. K-17. Biomagnification of hepta-, nona-, and decachlorobiphenyl predicted by PRAM.
0.00

2.00

4.00

6.00

8.00

10.00

12.00

14.00

16.00

4 5 6 7 8 9 10 11

Log(Kow)

FWMF

PRAM Pelagic

PRAM REEF

PRAM Benthic

Fisk 2001 Arcti

Won 2005 Chin

Mackintosh 200

error bars on Mackintosh 2004 are 95th% CL

error bars on Fisk 2001 are +/- 1 Std error

Fig. K-18. Comparison of the food web magnification factor (FWMF) predicted by PRAM for 

pelagic, reef, and benthic communities and the FWMF reported in the literature for food web

from the Arctic (Fisk et al. 2001), China Sea (Wan et al. 2005), and coastal British Columbia 

(Mackintosh et al. 2004).
Appendix K References 

Beck, M.B., J.R. Ravetz, L.A. Mulkey, and T.O. Barnwell 1997. On the problem of 

model validation for predictive exposure assessments. Stochastic Hydrology and 

Hydraulics 11: 229-254. 

Beck, M.B. and Jining Chen 2000. Assuring the quality of models designed for predictive 

tasks. In Sensitivity Analysis, A. Saltelli, K. Chan, and E. Marian Scott (eds), 

John Wiley & Sons, LTD, pp401-420. 

Burkhard, Lawrence P., Douglas D. Endicott, Philip M. Cook, Keith G. Sappington, and 

Erik L. Winchester, 2003.Evaluation of Two Methods for Prediction of 

Bioaccumulation FactorsEnviron. Sci. Technol.; 2003; 37(20) pp 4626 - 4634; 

(Article) DOI 

Chen, J. and M.B. Beck. 1999. Quality Assurance of Multi-Media Model for Predictive 

Screening Tasks. U.S. Environmental Protection Agency, Athens, GA. 

Publication No. EPA/600/R-98/106. 

Connolly, J. P.; Zahakos, H. A.; Benaman, J.; Ziegler, C. K.; Rhea, J. R.; Russell, K.; 2000;

A Model of PCB Fate in the Upper Hudson River Environ. Sci. Technol.; (Article); 

34(19); 4076-4087. DOI: 10.1021/es001046v Abstract Full: HTML / PDF

Fisk et al. 1998, 

Fisk, A. T.; Hobson, K. A.; Norstrom, R. J.; 2001. Influence of Chemical and Biological 

Factors on Trophic Transfer of Persistent Organic Pollutants in the Northwater 

Polynya Marine Food Web Environ. Sci. Technol.; (Article); 2001; 35(4); 732-738. 

DOI 

Jackson, L. J.; Carpenter, S. R.; Manchester-Neesvig, J.; Stow, C. A.; 2001. PCB Congeners 

in Lake Michigan Coho (Oncorhynchus kisutch) and Chinook (Oncorhynchus

tshawytscha) Salmon Environ. Sci. Technol.; (Article); 2001; 35(5); 856-862. 

Johnston, T. A.; Fisk, A. T.; Whittle, D. M.; Muir, D. C. G.; 2002. Variation in 

Organochlorine Bioaccumulation by a Predatory Fish; Gender, Geography, and Data 

Analysis Methods Environ. Sci. Technol.; (Article); 2002; 36(20); 4238-4244. 

Mackintosh, C. E.; Maldonado, J.; Hongwu, J.; Hoover, N.; Chong, A.; Ikonomou, M. G.; 

Gobas, F. A. P. C. 2005. Distribution of Phthalate Esters in a Marine Aquatic Food 

Web: Comparison to Polychlorinated Biphenyls; Environ. Sci. Technol.; (Article); 

2004; 38(7); 2011-2020. 

NEHC/SSC-SD 2005a. Prospective Risk Assessment Model (PRAM) Version 1.4 

Documentation. Draft Final, May 2005. Prepared for Navy Environmental Health 

Center, Portsmouth, VA and Space and Naval Warfare Systems Center, San Diego, 

CA under U.S. Army Corps of Engineers Contract #DACA67-02-D-2003, DO 

0027, MOD 02, by URS Corporation, Seattle, WA. 

http://www.epa.gov/region4/air/lead/documents/ProspectiveRiskAssessmentModelPRAM-Version1-4CDocumentation5-05-DraftFinal_000.pdf 

K - 37
NEHC/SSC-SD 2005b. Time Dynamic Model (TDM) Documentation. Draft Final, May 

2005. Prepared for Navy Environmental Health Center, Portsmouth, VA and Space

and Naval Warfare Systems Center, San Diego, CA under U.S. Army Corps of

Engineers Contract #DACA67-02-D-2003, DO 0027, MOD 02, by URS 

Corporation, Seattle, WA. 

http://www.epa.gov/region4/air/lead/documents/TimeDynamicModel-TDMDocumentation5-05-DraftFinal.pdf.pdf 

NEHC/SSC-SD 2006a. Prospective Risk Assessment Model (PRAM) Version 1.4 

Documentation. Final Report, January 2006. Prepared for Navy Environmental 

Health Center, Portsmouth, VA and Space and Naval Warfare Systems Center, San 

Diego, CA under U.S. Army Corps of Engineers Contract #DACA67-02-D-2003, 

DO 0027, MOD 02, by URS Corporation, Seattle, WA. 

NEHC/SSC-SD 2006b. Time Dynamic Model (TDM) Documentation. Final Report, 

January 2005. Prepared for Navy Environmental Health Center, Portsmouth, VA 

and Space and Naval Warfare Systems Center, San Diego, CA under U.S. Army 

Corps of Engineers Contract #DACA67-02-D-2003, DO 0027, MOD 02, by URS 

Corporation, Seattle, WA. 

Spacie, A, L. McCarty, and G. Rand, 1995. Bioaccumulation and bioavailability in 

multiphase systems. Chapter 16, in Fudamentals of Aquatic Toxicology, G. Rand 

(Ed.), Taylor and Francis, Washington DC 

Stapleton, H. M.; Letcher, R. J.; Baker, J. E.; 2001. Metabolism of PCBs by the Deepwater 

Sculpin (Myoxocephalus thompsoni) Environ. Sci. Technol.; (Article); 2001; 

35(24); 4747-4752. 

Stapleton, H. M.; Masterson, C.; Skubinna, J.; Ostrom, P.; Ostrom, N. E.; Baker, J. E.; 2001. 

Accumulation of Atmospheric and Sedimentary PCBs and Toxaphene in a Lake

Michigan Food Web Environ. Sci. Technol.; (Article); 2001; 35(16); 3287-3293 

Wan, Y.; Hu, J.; Yang, M.; An, L.; An, W.; Jin, X.; Hattori, T.; Itoh, M., 2005. 

Characterization of Trophic Transfer for Polychlorinated Dibenzo-p-dioxins, 

Dibenzofurans, Non- and Mono-ortho Polychlorinated Biphenyls in the Marine 

Food Web of Bohai Bay, North China Environ. Sci. Technol.; (Article); 2005; 39(8); 

2417-2425. 

K - 38
Appendix K.2 PRAM Output for Varying ZOI 

K.2.1 PRAM Output ZOI = 1 

Risk Estimate 

Supplemental Information 

K.2.2 PRAM Default Parameters (ZOI =2 ) 

Risk Estimate 

Supplemental Information 

K.2.3 PRAM Output ZOI = 3 

Risk Estimate 

Supplemental Information 

K.2.4 PRAM Output ZOI = 4 

Risk Estimate 

Supplemental Information 

K.2.5 PRAM Output ZOI = 5 

Risk Estimate 

Supplemental Information 

K.2.6 PRAM Output ZOI = 10 

Risk Estimate 

Supplemental Information 

K.2.7 Summary of Total PCBs concentrations modeled for biological and abiotic 

compartments as a function of ZOI. 

K - 39
ZOI = 1

RISK ESTIMATES RME CTE RME CTE RME CTE RME CTE

Benthic fish (flounder) 1.15E-07 8.88E-09 6.69E-03 1.53E-03 3.36E-08 6.82E-09 9.81E-03 1.77E-03

Benthic shellfish (lobster) 3.33E-08 2.58E-09 1.95E-03 4.46E-04 9.79E-09 1.98E-09 2.85E-03 5.15E-04

Pelagic fish (jack) 5.61E-08 4.35E-09 3.28E-03 7.51E-04 1.65E-08 3.34E-09 4.81E-03 8.66E-04

Reef fish TL-IV (grouper) 7.05E-06 5.46E-07 4.11E-01 9.44E-02 2.07E-06 4.20E-07 6.04E-01 1.09E-01

Reef fish TL-III (triggerfish) 4.10E-06 3.17E-07 2.39E-01 5.48E-02 1.20E-06 2.44E-07 3.51E-01 6.32E-02

Reef shellfish (crab) 2.26E-06 1.75E-07 1.32E-01 3.02E-02 6.63E-07 1.35E-07 1.93E-01 3.49E-02

PREDICTED EXPOSURE CONCENTRATIONS (mg/kg in fresh weight)

Benthic fish (flounder) 1.86E-03

Benthic shellfish (lobster) 5.42E-04

Pelagic fish (jack) 9.13E-04

Reef fish TL-IV (grouper) 1.15E-01

Reef fish TL-III (triggerfish) 6.66E-02

Reef shellfish (crab) 3.67E-02

RISK INPUTS - Adult RME CTE RISK INPUTS - Child RME CTE

Body Weight (BWc) (kg) 70 70 Body Weight (BWc) (kg) 15 15

Ingestion Rate (IRc) (kg/day) 0.0261 0.0072 Ingestion Rate (IRc) (kg/day) 0.0092916 0.0025632

Exposure Duration (EDc) (years) 24 3 Exposure Duration (EDc) (years) 6 6

Exposure Frequency (EFc) (days) 365 365 Exposure Frequency (EFc) (days) 365 365

Averaging Time for cancer (ATc) 25550 25550 Averaging Time for cancer (ATc) 25550 25550

Slope Factor (mg/kg-day) 2 1 Slope Factor (mg/kg-day) 2 1

Reference dose for PCBs (RfD) (mg/kg-day) 0.00002 0.000045 Reference dose for PCBs (RfD) (mg/kg-day) 0.00002 0.000045

Averaging Time for noncancer (ATnc-child) 8.76E+03 1.10E+03 Averaging Time for noncancer (ATnc-child) 2.19E+03 2.19E+03

Fractional Ingestion factor (FI) 0.17 0.25 Fractional Ingestion factor (FI) 0.17 0.25

Child - Adult IR scaling factor

Zone of Influence Multiplier 1

Scenario run on

PCB-LADEN MATERIAL INPUTS Fraction Release kg Material PCB Release Ex-Oriskany CV34

PCB Rate (ng/g-d) Onboard (ng/day) Ex-Oriskany CV34 27100

Ventilation Gaskets 3.14E-05 1.58E+03 1.46E+03 7.23E+04 Length (ft) 888

Lubricants 1.03E-04 2.20E+03 0.00E+00 0.00E+00 Beam (ft) 120

Foam Rubber Material 0.76% 2.62E+00 0.00E+00 0.00E+00

Black Rubber Material 5.29E-05 1.58E+03 5.40E+03 4.50E+05

Electrical Cable 1.85E-03 2.79E+02 2.96E+05 1.53E+08

Bulkhead Insulation Material 5.37E-04 6.76E+04 1.44E+04 5.22E+08

Aluminum Paint 2.00E-05 1.11E+04 3.87E+05 8.62E+07

Total 7.62E+08

ZOI = 1

7.78E+03 m2

3.00E-03 mile2

A 1.00E+01 m

B 1.50E+01 m

C 5.00E+01 m

D 1.00E-01 m

E 2.71E+02 m

F 3.66E+01 m

Air Column

Air 7.78E+04 m3

Upper Water Column

Water 1.17E+05 m3

TSS 7.78E-01 m3

Lower Water Column

Water 3.35E+05 m3

TSS 2.23E+00 m3

Inside Vessel

Water 5.38E+04 m3

TSS 3.59E-01 m3

Sediment Bed

Sediment 0.00E+00 m3

Abiotic Inputs Total PCB concentrations

Air Column Air Column

Active air space height above water column (m) 10 Air 5.26E-17 g/m3

Air current (m/h) 13677 Upper Water Column

Upper Water Column Freely dissolved in water 1.13E-12 mg/L

Temperature (oC) 24.5 Suspended solids 1.48E-08 mg/kg

Water depth (m) 15 Dissolved organic carbon 1.98E-07 mg/kg

Total suspended solids (mg/L) 10 Lower Water Column

Dissolved organic carbon (mg/L) 0.6 Freely dissolved in water 6.90E-09 mg/L

Dissolved oxygen (mg/L) 6.12 Suspended solids 1.70E-04 mg/kg

Lower Water Column Dissolved organic carbon 1.55E-03 mg/kg

Temperature (oC) 19.5 Inside Vessel

Water depth (m) 50 Freely dissolved in water 1.80E-06 mg/L

Total suspended solids (mg/L) 10 Suspended solids 4.44E-02 mg/kg

Dissolved organic carbon (mg/L) 0.6 Dissolved organic carbon 4.06E-01 mg/kg

Dissolved oxygen (mg/L) 4.59 Sediment Bed

Inside Vessel Freely dissolved in pore water 6.90E-09 mg/L

Temperature (oC) 19.5 Bedded sediment 1.13E-05 mg/kg

Total suspended solids (mg/L) 10 Dissolved organic carbon in pore water 1.55E-03 mg/kg

Dissolved organic carbon (mg/L) 0.6 Total PCB concentrations in biota

Dissolved oxygen (mg/L) 4.59 Pelagic Community Upper WC Lower WC

Sediment Bed Phytoplankton (TL-I) 1.86E-09 mg/kg 100% 0%

Sediment density (g/cm3) 1.5 Zooplankton (TL-II) 1.21E-04 mg/kg 50% 50%

Active sediment depth (m) 0.1 Planktivore (TL-III) 5.88E-04 mg/kg 80% 20%

Sediment fraction organic carbon 0.01 Piscivore (TL-IV) 9.13E-04 mg/kg 80% 20%

All Regions Reef / Vessel Community Lower WC Vessel Int.

Suspended solids density (g/cm3) 1.5 Attached Algae (TL-I) 1.14E-05 mg/kg 100% 0%

Suspended solids fraction organic carbon 0.15 Sessile filter feeder (TL-II) 2.49E-04 mg/kg 100% 0%

Dissolved organic carbon density (g/cm3) 1 Invertebrate Omnivore (TL-II) 1.72E-02 mg/kg 80% 20%

Water current - to out of the ZOI (m/h) 926 Invertebrate Forager (TL-III) 3.67E-02 mg/kg 70% 30%

Water current - inside to outside the vessel (m/h) 9.26 Vertebrate Forager (TL-III) 6.66E-02 mg/kg 70% 30%

Predator (TL-IV) 1.15E-01 mg/kg 80% 20%

Benthic Community Lower WC Pore Water

Infaunal invert. (TL-II) 8.62E-05 mg/kg 20% 80%

Epifaunal invert. (TL-II) 2.37E-04 mg/kg 50% 50%

Forager (TL-III) 5.42E-04 mg/kg 75% 25%

Predator (TL-IV) 1.86E-03 mg/kg 90% 10%

Percent Exposures

Spatial Footprint on Ocean Floor

RISK ESTIMATES FOR Ex-Oriskany CV34

Volumes

Cancer Risk Adult & Child Hazard Adult & Child Cancer Risk Child Hazard Child

0.356

PCB MODELING RESULTS - PROSPECTIVE RISK EVALUATION 

Modeled Dimensions

Outside the Vessel

5/31/05 14:31

A

C

D

E E

E

VESSEL

B

Pycnocline

A

C

D

E E

E

VESSEL

B

Pycnocline

F_Xappdx_2b.xls B2.1_zoi1_Estimate

1/23/2006 11:00 PM

Based on NEHC PRAM Version 1.4

May 2005 Page 1 of 25
Scenario Run on ZOI = 1

PCB Homolog Mono Di Tri Tetra Penta Hexa Hepta Octa Nona Deca

Molecular Weight (g/mol) 1.89E+02 2.23E+02 2.58E+02 2.92E+02 3.26E+02 3.61E+02 3.95E+02 4.30E+02 4.64E+02 4.99E+02

Solubility (mg/L) 2.91E+00 6.78E-01 8.14E-02 6.67E-02 2.61E-02 9.50E-04 2.30E-04 2.11E-08 4.02E-09 1.69E-10

Solubility (mol/m3

) 1.54E-02 3.04E-03 3.16E-04 2.28E-04 8.00E-05 2.63E-06 5.82E-07 4.91E-11 8.65E-12 3.38E-13

Vapor Pressure (Pa) 6.32E-01 1.41E-01 5.11E-02 2.08E-02 2.96E-03 3.43E-03 2.56E-04 8.65E-05 2.77E-05 1.41E-05

Henry's (Pa-m3

/mol) 4.10E+01 4.65E+01 1.62E+02 9.10E+01 3.70E+01 1.30E+03 4.40E+02 1.76E+06 3.20E+06 4.18E+07

log10Kow = 4.47 5.24 5.52 5.92 6.50 6.98 7.19 7.70 8.35 9.60

log10Koc = 3.66 4.06 4.63 4.65 4.94 6.08 6.34 6.46 6.97 7.94

log10Kdoc = 3.34 4.11 4.39 4.79 5.51 5.85 6.06 6.57 7.22 8.47

Chemical emission rate (g/day) 1.37E-05 1.12E-01 9.95E-03 1.69E-01 3.20E-01 7.57E-02 7.37E-02 0.00E+00 8.28E-04 4.62E-04

Chemical emission rate (mol/hr) 3.03E-09 2.09E-05 1.61E-06 2.42E-05 4.08E-05 8.74E-06 7.77E-06 0.00E+00 7.43E-08 3.86E-08

Biodegradation in sediment (1/hr) 0 0 0 0 0 0 0 000

Biodegradation in water (1/hr) 0 0 0 0 0 0 0 000

Ventilation 

Gaskets Lubricants Foam Rubber 

Material

Black Rubber 

Material

Electrical 

Cable

Bulkhead 

Insulation 

Material

Aluminized 

Paint

Fraction PCB in Material (wt/wt) 0.0000314 0.000103 0.76% 0.0000529 0.00185 0.000537 0.00002

Material Mass Onboard (kg) 1459 0 0 5397 296419 14379 386528

Total PCBs (kg) 0.0458126 0 0 0.2855013 548.37515 7.721523 7.73056

Total PCB Release rate (ng/g-PCB per day) 1.58E+03 2.20E+03 2.62E+00 1.58E+03 2.79E+02 6.76E+04 1.11E+04

Ventilation 

Gaskets Lubricants Foam Rubber Material

Black Rubber 

Material

Electrical 

Cable

Bulkhead 

Insulation 

Material

Aluminized 

Paint

Monochlorobiphenyl 4.14E+01 3.47E+01 0.00E+00 4.14E+01 0.00E+00 0.00E+00 0.00E+00

Dichlorobiphenyl 1.27E+03 1.72E+02 3.08E-02 1.27E+03 2.03E+02 5.36E+00 0.00E+00

Trichlorobiphenyl 5.66E+01 8.97E+01 7.63E-02 5.66E+01 1.14E+00 9.44E+02 2.61E+02

Tetrachlorobiphenyl 1.44E+02 1.08E+03 1.29E+00 1.44E+02 1.57E+01 2.07E+04 1.23E+02

Pentachlorobiphenyl 6.31E+01 6.60E+02 3.90E-02 6.31E+01 1.80E+01 3.79E+04 2.24E+03

Hexachlorobiphenyl 0.00E+00 9.42E+01 5.34E-01 0.00E+00 2.41E+01 6.76E+03 1.33E+03

Heptachlorobiphenyl 5.04E+00 7.17E+01 6.46E-01 5.04E+00 1.47E+01 1.30E+03 7.19E+03

Octachlorobiphenyl 0.00E+00 0.00E+00 0.00E+00 0.00E+00 0.00E+00 0.00E+00 0.00E+00

Nonachlorobiphenyl 0.00E+00 0.00E+00 1.72E-03 0.00E+00 1.51E+00 0.00E+00 0.00E+00

Decachlorobiphenyl 0.00E+00 0.00E+00 0.00E+00 0.00E+00 8.43E-01 0.00E+00 0.00E+00

Total 1.58E+03 2.20E+03 2.62E+00 1.58E+03 2.79E+02 6.76E+04 1.11E+04

Release Rates in nanograms PCB per Day Ventilation 

Gaskets Lubricants Foam Rubber 

Material

Black Rubber 

Material

Electrical 

Cable

Bulkhead 

Insulation 

Material

Aluminized 

Paint Total

Monochlorobiphenyl 1.90E+03 0.00E+00 0.00E+00 1.18E+04 0.00E+00 0.00E+00 0.00E+00 1.37E+04

Dichlorobiphenyl 5.80E+04 0.00E+00 0.00E+00 3.62E+05 1.11E+08 4.14E+04 0.00E+00 1.12E+08

Trichlorobiphenyl 2.59E+03 0.00E+00 0.00E+00 1.62E+04 6.25E+05 7.29E+06 2.02E+06 9.95E+06

Tetrachlorobiphenyl 6.60E+03 0.00E+00 0.00E+00 4.11E+04 8.61E+06 1.60E+08 9.51E+05 1.69E+08

Pentachlorobiphenyl 2.89E+03 0.00E+00 0.00E+00 1.80E+04 9.87E+06 2.93E+08 1.73E+07 3.20E+08

Hexachlorobiphenyl 0.00E+00 0.00E+00 0.00E+00 0.00E+00 1.32E+07 5.22E+07 1.03E+07 7.57E+07

Heptachlorobiphenyl 2.31E+02 0.00E+00 0.00E+00 1.44E+03 8.06E+06 1.01E+07 5.56E+07 7.37E+07

Octachlorobiphenyl 0.00E+00 0.00E+00 0.00E+00 0.00E+00 0.00E+00 0.00E+00 0.00E+00 0.00E+00

Nonachlorobiphenyl 0.00E+00 0.00E+00 0.00E+00 0.00E+00 8.28E+05 0.00E+00 0.00E+00 8.28E+05

Decachlorobiphenyl 0.00E+00 0.00E+00 0.00E+00 0.00E+00 4.62E+05 0.00E+00 0.00E+00 4.62E+05

Total 7.23E+04 0.00E+00 0.00E+00 4.50E+05 1.53E+08 5.22E+08 8.62E+07 7.62E+08

Air Mono Di Tri Tetra Penta Hexa Hepta Octa Nona Deca

Fugacity (Pa) 2.53E-20 1.56E-16 1.02E-17 1.37E-16 1.50E-16 5.28E-18 1.89E-18 0.00E+00 6.69E-22 2.15E-24

Air concentration (g/m3) 1.95E-21 1.42E-17 1.07E-18 1.63E-17 2.00E-17 7.77E-19 3.04E-19 0.00E+00 1.26E-22 4.37E-25

Upper Water Column Mono Di Tri Tetra Penta Hexa Hepta Octa Nona Deca

Fugacity (Pa) 7.42E-18 5.61E-14 1.36E-14 1.10E-13 5.24E-14 6.67E-14 8.42E-15 0.00E+00 2.34E-14 1.02E-15

Water concentration (mg/L) 3.41E-17 2.69E-13 2.17E-14 3.51E-13 4.62E-13 1.85E-14 7.56E-15 0.00E+00 3.41E-18 1.22E-20

Suspended solids concentration (mg/kg) 2.36E-14 4.61E-10 1.37E-10 2.38E-09 5.96E-09 3.33E-09 2.48E-09 0.00E+00 4.72E-12 1.60E-13

Dissolved organic carbon (mg/kg) 7.53E-14 3.43E-09 5.32E-10 2.17E-08 1.50E-07 1.29E-08 8.66E-09 0.00E+00 5.65E-11 3.62E-12

Lower Water Column Mono Di Tri Tetra Penta Hexa Hepta Octa Nona Deca

Fugacity (Pa) 3.70E-14 2.84E-10 7.24E-11 5.98E-10 3.43E-10 1.06E-09 2.07E-10 0.00E+00 2.87E-09 1.56E-09

Water concentration (mg/L) 1.70E-13 1.36E-09 1.15E-10 1.92E-09 3.02E-09 2.94E-10 1.85E-10 0.00E+00 4.17E-13 1.87E-14

Suspended solids concentration (mg/kg) 1.18E-10 2.34E-06 7.30E-07 1.30E-05 3.90E-05 5.30E-05 6.09E-05 0.00E+00 5.78E-07 2.44E-07

Dissolved organic carbon (mg/kg) 3.75E-10 1.74E-05 2.83E-06 1.19E-04 9.85E-04 2.06E-04 2.13E-04 0.00E+00 6.93E-06 5.53E-06

Inside the Vessel Mono Di Tri Tetra Penta Hexa Hepta Octa Nona Deca

Fugacity (Pa) 9.67E-12 7.43E-08 1.89E-08 1.56E-07 8.96E-08 2.77E-07 5.40E-08 0.00E+00 7.51E-07 4.09E-07

Water concentration (mg/L) 4.45E-11 3.57E-07 3.02E-08 5.02E-07 7.90E-07 7.68E-08 4.85E-08 0.00E+00 1.09E-10 4.88E-12

Suspended solids concentration (mg/kg) 3.07E-08 6.11E-04 1.91E-04 3.39E-03 1.02E-02 1.39E-02 1.59E-02 0.00E+00 1.51E-04 6.38E-05

Dissolved organic carbon (mg/kg) 9.80E-08 4.54E-03 7.41E-04 3.10E-02 2.57E-01 5.38E-02 5.56E-02 0.00E+00 1.81E-03 1.45E-03

Sediment Bed Mono Di Tri Tetra Penta Hexa Hepta Octa Nona Deca

Fugacity (Pa) 3.70E-14 2.84E-10 7.24E-11 5.98E-10 3.43E-10 1.06E-09 2.07E-10 0.00E+00 2.87E-09 1.56E-09

Pore Water concentration (mg/L) 1.70E-13 1.36E-09 1.15E-10 1.92E-09 3.02E-09 2.94E-10 1.85E-10 0.00E+00 4.17E-13 1.87E-14

Sediment concentration (mg/kg) 7.84E-12 1.56E-07 4.87E-08 8.65E-07 2.60E-06 3.53E-06 4.06E-06 0.00E+00 3.85E-08 1.63E-08

Bioenergetic Inputs

Species Body Weight Lipid Moisture Caloric 

Density GE to ME Met Energy Caloric 

Density Production Respiration Excretion Caloric 

Density Met Energy

(kg) (%-dw) (%) (kcal/g-dry 

weight) Fraction (kcal/kg-lipid) (kcal/kg-lipid) (% of total) (% of total) (% of total) (kcal/g-wt 

weight)

 (kcal/g-wt 

weight)

Pelagic Community

Phytoplankton (TL-I) Algae 10% 84% 2.36 0.6 13748 22913 0.3776 0.22656

Zooplankton (TL-II) copepods 0.000005 22% 76% 3.6 0.65 10636 16364 18% 24% 58% 0.864 0.5616

Planktivore (TL-III) herring 0.05 28% 75% 4.9 0.7 12206 17438 20% 60% 20% 1.225 0.8575

Piscivore (TL-IV) jack 0.5 28% 75% 4.9 0.7 12206 17438 20% 60% 20% 1.225 0.8575

Reef / Vessel Community

Attached Algae (TL-I) Algae 10% 84% 2.36 0.6 13748 22913 0.3776 0.22656

Sessile filter feeder (TL-II) bivalves (w/o shell) 0.05 5% 82% 4.6 0.65 59800 92000 28% 31% 41% 0.828 0.5382

Invertebrate Omnivore (TL-II) urchin 0.05 29% 82% 4.6 0.65 10310 15862 7% 25% 68% 0.828 0.5382

Invertebrate Forager (TL-III) crab 1 9% 74% 2.7 0.65 19118 29412 28% 59% 13% 0.702 0.4563

Vertebrate Forager (TL-III) triggerfish 1 28% 75% 4.9 0.7 12206 17438 20% 60% 20% 1.225 0.8575

Predator (TL-IV) grouper 1.5 28% 75% 4.9 0.7 12206 17438 20% 60% 20% 0.2 0.14

Benthic Community

Infaunal invert. (TL-II) polychaete 0.01 6% 84% 4.6 0.65 50000 76923 71% 26% 3% 0.736 0.4784

Epifaunal invert. (TL-II) nematode 0.01 6% 82% 4.6 0.65 50000 76923 31% 19% 50% 0.828 0.5382

Forager (TL-III) lobster 2 9% 74% 2.7 0.65 19118 29412 28% 59% 13% 0.702 0.4563

Predator (TL-IV) flounder 3 22% 75% 4.9 0.7 15591 22273 20% 60% 20% 1.225 0.8575

Bioenergetic Inputs Resp. Rate Resp. Rate Consumption Growth Rate Consumption Consumption

1 gO2 kcal 1 g-wt weight kcal As a % of

Pelagic Community day kg-lipid-day kg-lipid-day day g-wt weight-d-wet weight-da body weight

Phytoplankton (TL1) Algae

Zooplankton (TL-II) copepods 0.006375522 0 0.039935335 0.015425453 84.24400867 1286.168071 0.014147849 0.32636028 0.06790967 32.6%

Planktivore (TL-III) herring 0.0033 -0.227 0.0548 0.004949927 21.1649 129.2512977 0.001482433 0.01616792 0.0090799 1.6%

Piscivore (TL-IV) jack 0.001118602 -0.55 0.12 0.000630951 2.697821256 16.47524431 0.000188961 0.00139796 0.00115739 0.1%

Reef / Vessel Community

Attached Algae Algae

Sessile filter feeder (TL-II) bivalves (w/o shell) 0.012 0 0.036 0.024213411 581.8482643 6877.300342 0.020930914 0.24377539 0.0618957 24.4%

Invertibrate Omnivore (TL-II) urchin 0.000675466 0 0.079181846 0.003163548 13.1069075 192.1012396 0.000847751 0.03471132 0.01002768 3.5%

Invertibrate Forager (TL-III) crab 0.001158234 0 0.071193202 0.004642088 60.75673491 377.3221989 0.003592107 0.01678102 0.00900593 1.7%

Vertibrate Forager (TL-III) triggerfish 0.015181024 -0.415 0.061 0.002837229 12.13142452 74.08503521 0.00084971 0.00907693 0.00520447 0.9%

Predator (TL-IV) grouper 0.00279 -0.355 0.0811 0.001011362 4.324384181 26.40845301 0.000302889 0.00264734 0.00185519 0.3%

Benthic Community

Infaunal invert. (TL-II) polychaete 0.001682129 0 0.071034762 0.006721006 135.0382801 1903.064429 0.017565285 0.09800757 0.01820852 9.8%

Epifaunal invert. (TL-II) nematode 0.001682129 0 0.071034762 0.006721006 135.0382801 2604.19343 0.0104949 0.09262416 0.02803154 9.3%

Forager (TL-III) lobster 0.0035 -0.13 0.066 0.00471923 61.76639253 383.5925529 0.003651801 0.01899736 0.00915559 1.9%

Predator (TL-IV) flounder 0.0046 -0.24 0.067 0.002486878 13.58174479 82.94195291 0.000744785 0.00974341 0.00456181 1.0%

PCB MODELING RESULTS - PROSPECTIVE RISK EVALUATION 

RISK ESTIMATES FOR Ex-Oriskany CV34

Supplemental Information

Release Rates in nanograms PCB per gram of PCB within the Material

Respiration Rate Allometric Regression Parameters

a b1 b2

5/31/05 14:31

PRAM 1.3 Supplemental Information

1/23/2006 11:00 PM

Based on NEHC PRAM Version 1.3

May 2004 Page 2 of 25
PCB MODELING RESULTS - PROSPECTIVE RISK EVALUATION 

RISK ESTIMATES FOR Ex-Oriskany CV34

Supplemental Information

Dietary Preferences

Suspended Solids

(Epilimnion)

Suspended 

Solids

(Hypolimnion)

Sediment Phytoplankton Zooplankton Pelagic 

Plankitivore

Attached 

Algae

Reef Sessile 

Filter Feeder

Invertebrate 

Omnivore

Reef

Invertebrate

Forager

Reef

Vertebrate

Forager

Infaunal 

Benthos

Epifaunal 

Benthos

Benthic 

Forager

Pelagic Community

Phytoplankton (TL1)

Zooplankton (TL-II) 15% 15% 70%

Planktivore (TL-III) 100%

Piscivore (TL-IV) 10% 90%

Reef / Vessel Community

Attached Algae

Sessile filter feeder (TL-II) 10% 80% 10%

Invertebrate Omnivore (TL-II) 80% 20%

Invertebrate Forager (TL-III) 5% 5% 5% 35% 50%

Vertebrate Forager (TL-III) 19% 19% 15% 22% 12.5% 12.5%

Predator (TL-IV) 15% 60% 8% 8% 8%

Benthic Community

Infaunal invert. (TL-II) 50% 30% 20%

Epifaunal invert. (TL-II) 25% 30% 20% 25%

Forager (TL-III) 5% 50% 45%

Predator (TL-IV) 2% 20% 20% 58%

Water Exposures

Upper Water 

Column

Lower Water

Column Vessel Interior Sediment PoreWater GE ME ME as kcal/g-ww

Pelagic Community Sediment (kcal/kg-oc) 11456 6873.6 0.6 0.01099776

Phytoplankton (TL1) Algae 100% Suspended Sediment (kcal/kg-oc) 11456 6873.6 0.6 0.1649664

Zooplankton (TL-II) copepods 50% 50%

Planktivore (TL-III) herring 80% 20%

Piscivore (TL-IV) jack 80% 20%

Reef / Vessel Community

Attached Algae Algae 100%

Sessile filter feeder (TL-II) bivalves (w/o shell) 100%

Invertebrate Omnivore (TL-II) urchin 80% 20%

Invertebrate Forager (TL-III) crab 70% 30%

Vertebrate Forager (TL-III) triggerfish 70% 30%

Predator (TL-IV) grouper 80% 20%

Benthic Community

Infaunal invert. (TL-II) polychaete 20% 80%

Epifaunal invert. (TL-II) nematode 50% 50%

Forager (TL-III) lobster 75% 25%

Predator (TL-IV) flounder 90% 10%

Respiratory Efficiencies Mono Di Tri Tetra Penta Hexa Hepta Octa Nona Deca

Low body weight (<100g) 4.335E-01 8.000E-01 8.000E-01 8.000E-01 4.492E-01 2.582E-01 2.018E-01 1.127E-01 5.303E-02 1.255E-02

High body weight (>100g) 5.000E-01 5.000E-01 5.000E-01 5.000E-01 3.769E-01 2.857E-01 2.526E-01 1.888E-01 1.295E-01 6.299E-02

Dietary Assimilation Efficiencies 27% 46% 53% 62% 69% 69% 68% 59% 44% 16%

Tissue Conc. (mg/kg-lipid) Mono Di Tri Tetra Penta Hexa Hepta Octa Nona Deca

Pelagic Community

Phytoplankton (TL1) 1.017E-12 2.694E-08 2.167E-09 3.514E-08 4.615E-08 1.845E-09 7.559E-10 0.000E+00 3.406E-13 1.219E-15

Zooplankton (TL-II) 1.146E-08 4.254E-04 4.292E-05 8.101E-04 8.034E-04 1.150E-04 1.023E-04 0.000E+00 5.128E-07 7.581E-08

Planktivore (TL-III) 2.589E-09 3.603E-04 6.569E-05 2.403E-03 4.282E-03 6.738E-04 5.846E-04 0.000E+00 1.934E-06 1.018E-07

Piscivore (TL-IV) 6.768E-10 6.350E-05 1.744E-05 1.403E-03 7.505E-03 2.021E-03 1.976E-03 0.000E+00 5.773E-06 1.259E-07

Reef / Vessel Community

Attached Algae 5.066E-09 1.364E-04 1.154E-05 1.918E-04 3.020E-04 2.938E-05 1.855E-05 0.000E+00 4.173E-08 1.866E-09

Sessile filter feeder (TL-II) 1.631E-07 5.502E-03 5.434E-04 1.022E-02 9.893E-03 8.762E-04 6.344E-04 0.000E+00 2.031E-06 2.204E-07

Invertebrate Omnivore (TL-II) 2.918E-07 2.276E-02 3.368E-03 1.086E-01 1.760E-01 1.254E-02 6.618E-03 0.000E+00 4.840E-06 7.177E-08

Invertebrate Forager (TL-III) 2.200E-06 9.016E-02 1.346E-02 4.556E-01 8.720E-01 6.930E-02 3.861E-02 0.000E+00 4.273E-05 2.740E-06

Vertebrate Forager (TL-III) 2.023E-07 1.430E-02 3.082E-03 1.811E-01 6.449E-01 6.567E-02 3.856E-02 0.000E+00 4.352E-05 1.408E-06

Predator (TL-IV) 1.122E-07 7.313E-03 1.732E-03 1.518E-01 1.174E+00 1.808E-01 1.165E-01 0.000E+00 1.254E-04 2.713E-06

Benthic Community

Infaunal invert. (TL-II) 4.132E-08 1.623E-03 1.687E-04 3.337E-03 3.350E-03 3.066E-04 2.241E-04 0.000E+00 6.254E-07 4.457E-08

Epifaunal invert. (TL-II) 5.125E-08 3.018E-03 3.600E-04 8.148E-03 8.978E-03 8.606E-04 6.353E-04 0.000E+00 1.596E-06 8.752E-08

Forager (TL-III) 2.992E-08 1.653E-03 2.527E-04 7.636E-03 1.138E-02 1.064E-03 7.249E-04 0.000E+00 1.156E-06 2.651E-08

Predator (TL-IV) 2.649E-09 4.406E-04 1.161E-04 7.193E-03 2.167E-02 2.608E-03 1.841E-03 0.000E+00 2.367E-06 3.480E-08

Tissue Conc. (mg/kg-WW) Mono Di Tri Tetra Penta Hexa Hepta Octa Nona Deca Total PCB

Pelagic Community

Phytoplankton (TL1) 1.676E-14 4.439E-10 3.571E-11 5.792E-10 7.606E-10 3.041E-11 1.246E-11 0.000E+00 5.612E-15 2.010E-17 1.862E-09

Zooplankton (TL-II) 6.050E-10 2.246E-05 2.266E-06 4.277E-05 4.242E-05 6.070E-06 5.400E-06 0.000E+00 2.708E-08 4.003E-09 1.214E-04

Planktivore (TL-III) 1.819E-10 2.531E-05 4.615E-06 1.688E-04 3.008E-04 4.733E-05 4.107E-05 0.000E+00 1.359E-07 7.152E-09 5.880E-04

Piscivore (TL-IV) 4.755E-11 4.461E-06 1.225E-06 9.859E-05 5.272E-04 1.420E-04 1.388E-04 0.000E+00 4.055E-07 8.845E-09 9.127E-04

Reef / Vessel Community

Attached Algae 8.350E-11 2.248E-06 1.902E-07 3.161E-06 4.977E-06 4.841E-07 3.057E-07 0.000E+00 6.876E-10 3.074E-11 1.137E-05

Sessile filter feeder (TL-II) 1.468E-09 4.952E-05 4.891E-06 9.197E-05 8.903E-05 7.886E-06 5.710E-06 0.000E+00 1.828E-08 1.983E-09 2.490E-04

Invertebrate Omnivore (TL-II) 1.523E-08 1.188E-03 1.758E-04 5.668E-03 9.186E-03 6.545E-04 3.455E-04 0.000E+00 2.527E-07 3.746E-09 1.722E-02

Invertebrate Forager (TL-III) 5.250E-08 2.152E-03 3.213E-04 1.087E-02 2.081E-02 1.654E-03 9.215E-04 0.000E+00 1.020E-06 6.540E-08 3.674E-02

Vertebrate Forager (TL-III) 1.421E-08 1.004E-03 2.165E-04 1.272E-02 4.530E-02 4.613E-03 2.709E-03 0.000E+00 3.057E-06 9.893E-08 6.657E-02

Predator (TL-IV) 7.885E-09 5.138E-04 1.217E-04 1.066E-02 8.247E-02 1.270E-02 8.181E-03 0.000E+00 8.810E-06 1.906E-07 1.147E-01

Benthic Community

Infaunal invert. (TL-II) 3.954E-10 1.553E-05 1.614E-06 3.193E-05 3.205E-05 2.934E-06 2.144E-06 0.000E+00 5.984E-09 4.264E-10 8.621E-05

Epifaunal invert. (TL-II) 5.517E-10 3.249E-05 3.875E-06 8.770E-05 9.664E-05 9.264E-06 6.838E-06 0.000E+00 1.718E-08 9.420E-10 2.368E-04

Forager (TL-III) 7.142E-10 3.944E-05 6.031E-06 1.823E-04 2.716E-04 2.539E-05 1.730E-05 0.000E+00 2.758E-08 6.328E-10 5.421E-04

Predator (TL-IV) 1.457E-10 2.423E-05 6.388E-06 3.956E-04 1.192E-03 1.434E-04 1.013E-04 0.000E+00 1.302E-07 1.914E-09 1.863E-03

BAFs (L/kg-lipid) Mono Di Tri Tetra Penta Hexa Hepta Octa Nona Deca

Pelagic Community

Phytoplankton (TL1) 2.979E+04 1.000E+05 1.000E+05 1.000E+05 1.000E+05 1.000E+05 1.000E+05 0.000E+00 1.000E+05 1.000E+05

Zooplankton (TL-II) 1.347E+05 6.237E+05 7.436E+05 8.445E+05 5.319E+05 7.826E+05 1.103E+06 0.000E+00 2.458E+06 8.127E+06

Planktivore (TL-III) 7.604E+04 1.320E+06 2.844E+06 6.259E+06 7.084E+06 1.147E+07 1.576E+07 0.000E+00 2.317E+07 2.729E+07

Piscivore (TL-IV) 1.988E+04 2.326E+05 7.549E+05 3.656E+06 1.242E+07 3.439E+07 5.326E+07 0.000E+00 6.917E+07 3.375E+07

Reef / Vessel Community

Attached Algae 2.979E+04 1.000E+05 1.000E+05 1.000E+05 1.000E+05 1.000E+05 1.000E+05 0.000E+00 1.000E+05 1.000E+05

Sessile filter feeder (TL-II) 9.590E+05 4.034E+06 4.709E+06 5.328E+06 3.275E+06 2.983E+06 3.420E+06 0.000E+00 4.867E+06 1.181E+07

Invertebrate Omnivore (TL-II) 3.231E+04 3.143E+05 5.495E+05 1.066E+06 1.097E+06 8.039E+05 6.721E+05 0.000E+00 2.185E+05 7.246E+04

Invertebrate Forager (TL-III) 1.634E+05 8.353E+05 1.474E+06 3.001E+06 3.648E+06 2.981E+06 2.630E+06 0.000E+00 1.294E+06 1.856E+06

Vertebrate Forager (TL-III) 1.502E+04 1.324E+05 3.373E+05 1.193E+06 2.698E+06 2.825E+06 2.627E+06 0.000E+00 1.318E+06 9.538E+05

Predator (TL-IV) 1.243E+04 1.010E+05 2.827E+05 1.490E+06 7.321E+06 1.159E+07 1.183E+07 0.000E+00 5.661E+06 2.739E+06

Benthic Community

Infaunal invert. (TL-II) 2.429E+05 1.190E+06 1.462E+06 1.740E+06 1.109E+06 1.044E+06 1.208E+06 0.000E+00 1.499E+06 2.389E+06

Epifaunal invert. (TL-II) 3.013E+05 2.213E+06 3.119E+06 4.248E+06 2.973E+06 2.930E+06 3.425E+06 0.000E+00 3.825E+06 4.691E+06

Forager (TL-III) 1.759E+05 1.212E+06 2.189E+06 3.981E+06 3.768E+06 3.622E+06 3.908E+06 0.000E+00 2.770E+06 1.421E+06

Predator (TL-IV) 1.557E+04 3.231E+05 1.006E+06 3.750E+06 7.176E+06 8.877E+06 9.928E+06 0.000E+00 5.673E+06 1.865E+06

Notes:

Kow = octanol to water partitioning coefficient, Koc = organic carbon partitioning coefficient, Kdoc = dissolved organic carbon partitioning coefficient

TL = trophic level, ww = wet weight

Energy Estimates for Suspended Sediment and Bedded Sediment

PRAM 1.3 Supplemental Information

1/23/2006 11:00 PM

Based on NEHC PRAM Version 1.3

May 2004 Page 3 of 25
ZOI = 2

RISK ESTIMATES RME CTE RME CTE RME CTE RME CTE

Benthic fish (flounder) 7.29E-08 5.64E-09 4.25E-03 9.75E-04 2.14E-08 4.34E-09 6.24E-03 1.12E-03

Benthic shellfish (lobster) 2.12E-08 1.64E-09 1.24E-03 2.84E-04 6.22E-09 1.26E-09 1.81E-03 3.27E-04

Pelagic fish (jack) 3.57E-08 2.77E-09 2.08E-03 4.78E-04 1.05E-08 2.13E-09 3.06E-03 5.51E-04

Reef fish TL-IV (grouper) 6.94E-06 5.37E-07 4.05E-01 9.29E-02 2.04E-06 4.13E-07 5.94E-01 1.07E-01

Reef fish TL-III (triggerfish) 4.03E-06 3.12E-07 2.35E-01 5.39E-02 1.18E-06 2.40E-07 3.45E-01 6.22E-02

Reef shellfish (crab) 2.23E-06 1.73E-07 1.30E-01 2.98E-02 6.54E-07 1.33E-07 1.91E-01 3.44E-02

PREDICTED EXPOSURE CONCENTRATIONS (mg/kg in fresh weight)

Benthic fish (flounder) 1.18E-03

Benthic shellfish (lobster) 3.45E-04

Pelagic fish (jack) 5.80E-04

Reef fish TL-IV (grouper) 1.13E-01

Reef fish TL-III (triggerfish) 6.55E-02

Reef shellfish (crab) 3.62E-02

RISK INPUTS - Adult RME CTE RISK INPUTS - Child RME CTE

Body Weight (BWc) (kg) 70 70 Body Weight (BWc) (kg) 15 15

Ingestion Rate (IRc) (kg/day) 0.0261 0.0072 Ingestion Rate (IRc) (kg/day) 0.0092916 0.0025632

Exposure Duration (EDc) (years) 24 3 Exposure Duration (EDc) (years) 6 6

Exposure Frequency (EFc) (days) 365 365 Exposure Frequency (EFc) (days) 365 365

Averaging Time for cancer (ATc) 25550 25550 Averaging Time for cancer (ATc) 25550 25550

Slope Factor (mg/kg-day) 2 1 Slope Factor (mg/kg-day) 2 1

Reference dose for PCBs (RfD) (mg/kg-day) 0.00002 0.000045 Reference dose for PCBs (RfD) (mg/kg-day) 0.00002 0.000045

Averaging Time for noncancer (ATnc-child) 8.76E+03 1.10E+03 Averaging Time for noncancer (ATnc-child) 2.19E+03 2.19E+03

Fractional Ingestion factor (FI) 0.17 0.25 Fractional Ingestion factor (FI) 0.17 0.25

Child - Adult IR scaling factor

Zone of Influence Multiplier 2

Scenario run on

PCB-LADEN MATERIAL INPUTS Fraction Release kg Material PCB Release Ex-Oriskany CV34

PCB Rate (ng/g-d) Onboard (ng/day) Ex-Oriskany CV34 27100

Ventilation Gaskets 3.14E-05 1.58E+03 1.46E+03 7.23E+04 Length (ft) 888

Lubricants 1.03E-04 2.20E+03 0.00E+00 0.00E+00 Beam (ft) 120

Foam Rubber Material 0.76% 2.62E+00 0.00E+00 0.00E+00

Black Rubber Material 5.29E-05 1.58E+03 5.40E+03 4.50E+05

Electrical Cable 1.85E-03 2.79E+02 2.96E+05 1.53E+08

Bulkhead Insulation Material 5.37E-04 6.76E+04 1.44E+04 5.22E+08

Aluminum Paint 2.00E-05 1.11E+04 3.87E+05 8.62E+07

Total 7.62E+08

ZOI = 2

1.56E+04 m2

6.00E-03 mile2

A 1.00E+01 m

B 1.50E+01 m

C 5.00E+01 m

D 1.00E-01 m

E 3.00E+02 m

F 6.60E+01 m

Air Column

Air 1.56E+05 m3

Upper Water Column

Water 2.33E+05 m3

TSS 1.56E+00 m3

Lower Water Column

Water 7.24E+05 m3

TSS 4.82E+00 m3

Inside Vessel

Water 5.38E+04 m3

TSS 3.59E-01 m3

Sediment Bed

Sediment 7.78E+02 m3

Abiotic Inputs Total PCB concentrations

Air Column Air Column

Active air space height above water column (m) 10 Air 6.68E-17 g/m3

Air current (m/h) 13677 Upper Water Column

Upper Water Column Freely dissolved in water 1.02E-12 mg/L

Temperature (oC) 24.5 Suspended solids 1.33E-08 mg/kg

Water depth (m) 15 Dissolved organic carbon 1.78E-07 mg/kg

Total suspended solids (mg/L) 10 Lower Water Column

Dissolved organic carbon (mg/L) 0.6 Freely dissolved in water 4.39E-09 mg/L

Dissolved oxygen (mg/L) 6.12 Suspended solids 1.08E-04 mg/kg

Lower Water Column Dissolved organic carbon 9.88E-04 mg/kg

Temperature (oC) 19.5 Inside Vessel

Water depth (m) 50 Freely dissolved in water 1.80E-06 mg/L

Total suspended solids (mg/L) 10 Suspended solids 4.44E-02 mg/kg

Dissolved organic carbon (mg/L) 0.6 Dissolved organic carbon 4.06E-01 mg/kg

Dissolved oxygen (mg/L) 4.59 Sediment Bed

Inside Vessel Freely dissolved in pore water 4.39E-09 mg/L

Temperature (oC) 19.5 Bedded sediment 7.19E-06 mg/kg

Total suspended solids (mg/L) 10 Dissolved organic carbon in pore water 9.88E-04 mg/kg

Dissolved organic carbon (mg/L) 0.6 Total PCB concentrations in biota

Dissolved oxygen (mg/L) 4.59 Pelagic Community Upper WC Lower WC

Sediment Bed Phytoplankton (TL-I) 1.67E-09 mg/kg 100% 0%

Sediment density (g/cm3) 1.5 Zooplankton (TL-II) 7.72E-05 mg/kg 50% 50%

Active sediment depth (m) 0.1 Planktivore (TL-III) 3.74E-04 mg/kg 80% 20%

Sediment fraction organic carbon 0.01 Piscivore (TL-IV) 5.80E-04 mg/kg 80% 20%

All Regions Reef / Vessel Community Lower WC Vessel Int.

Suspended solids density (g/cm3) 1.5 Attached Algae (TL-I) 7.23E-06 mg/kg 100% 0%

Suspended solids fraction organic carbon 0.15 Sessile filter feeder (TL-II) 1.58E-04 mg/kg 100% 0%

Dissolved organic carbon density (g/cm3) 1 Invertebrate Omnivore (TL-II) 1.69E-02 mg/kg 80% 20%

Water current - to out of the ZOI (m/h) 926 Invertebrate Forager (TL-III) 3.62E-02 mg/kg 70% 30%

Water current - inside to outside the vessel (m/h) 9.26 Vertebrate Forager (TL-III) 6.55E-02 mg/kg 70% 30%

Predator (TL-IV) 1.13E-01 mg/kg 80% 20%

Benthic Community Lower WC Pore Water

Infaunal invert. (TL-II) 5.48E-05 mg/kg 20% 80%

Epifaunal invert. (TL-II) 1.51E-04 mg/kg 50% 50%

Forager (TL-III) 3.45E-04 mg/kg 75% 25%

Predator (TL-IV) 1.18E-03 mg/kg 90% 10%

Percent Exposures

Spatial Footprint on Ocean Floor

RISK ESTIMATES FOR Ex-Oriskany CV34

Volumes

Cancer Risk Adult & Child Hazard Adult & Child Cancer Risk Child Hazard Child

0.356

PCB MODELING RESULTS - PROSPECTIVE RISK EVALUATION 

Modeled Dimensions

Outside the Vessel

5/26/05 8:46

A

C

D

E E

E

VESSEL

B

Pycnocline

A

C

D

E E

E

VESSEL

B

Pycnocline

F_Xappdx_2b.xls B2.2_zoi2_Estimate

1/23/2006 11:00 PM

Based on NEHC PRAM Version 1.4

May 2005 Page 4 of 25
Scenario Run on ZOI=2

PCB Homolog Mono Di Tri Tetra Penta Hexa Hepta Octa Nona Deca

Molecular Weight (g/mol) 1.89E+02 2.23E+02 2.58E+02 2.92E+02 3.26E+02 3.61E+02 3.95E+02 4.30E+02 4.64E+02 4.99E+02

Solubility (mg/L) 2.91E+00 6.78E-01 8.14E-02 6.67E-02 2.61E-02 9.50E-04 2.30E-04 2.11E-08 4.02E-09 1.69E-10

Solubility (mol/m3

) 1.54E-02 3.04E-03 3.16E-04 2.28E-04 8.00E-05 2.63E-06 5.82E-07 4.91E-11 8.65E-12 3.38E-13

Vapor Pressure (Pa) 6.32E-01 1.41E-01 5.11E-02 2.08E-02 2.96E-03 3.43E-03 2.56E-04 8.65E-05 2.77E-05 1.41E-05

Henry's (Pa-m3

/mol) 4.10E+01 4.65E+01 1.62E+02 9.10E+01 3.70E+01 1.30E+03 4.40E+02 1.76E+06 3.20E+06 4.18E+07

log10Kow = 4.47 5.24 5.52 5.92 6.50 6.98 7.19 7.70 8.35 9.60

log10Koc = 3.66 4.06 4.63 4.65 4.94 6.08 6.34 6.46 6.97 7.94

log10Kdoc = 3.34 4.11 4.39 4.79 5.51 5.85 6.06 6.57 7.22 8.47

Chemical emission rate (g/day) 1.37E-05 1.12E-01 9.95E-03 1.69E-01 3.20E-01 7.57E-02 7.37E-02 0.00E+00 8.28E-04 4.62E-04

Chemical emission rate (mol/hr) 3.03E-09 2.09E-05 1.61E-06 2.42E-05 4.08E-05 8.74E-06 7.77E-06 0.00E+00 7.43E-08 3.86E-08

Biodegradation in sediment (1/hr) 0 0 0 0 0 0 0 000

Biodegradation in water (1/hr) 0 0 0 0 0 0 0 000

Ventilation 

Gaskets Lubricants Foam Rubber 

Material

Black Rubber 

Material

Electrical 

Cable

Bulkhead 

Insulation 

Material

Aluminized 

Paint

Fraction PCB in Material (wt/wt) 0.0000314 0.000103 0.76% 0.0000529 0.00185 0.000537 0.00002

Material Mass Onboard (kg) 1459 0 0 5397 296419 14379 386528

Total PCBs (kg) 0.0458126 0 0 0.2855013 548.37515 7.721523 7.73056

Total PCB Release rate (ng/g-PCB per day) 1.58E+03 2.20E+03 2.62E+00 1.58E+03 2.79E+02 6.76E+04 1.11E+04

Ventilation 

Gaskets Lubricants Foam Rubber Material

Black Rubber 

Material

Electrical 

Cable

Bulkhead 

Insulation 

Material

Aluminized 

Paint

Monochlorobiphenyl 4.14E+01 3.47E+01 0.00E+00 4.14E+01 0.00E+00 0.00E+00 0.00E+00

Dichlorobiphenyl 1.27E+03 1.72E+02 3.08E-02 1.27E+03 2.03E+02 5.36E+00 0.00E+00

Trichlorobiphenyl 5.66E+01 8.97E+01 7.63E-02 5.66E+01 1.14E+00 9.44E+02 2.61E+02

Tetrachlorobiphenyl 1.44E+02 1.08E+03 1.29E+00 1.44E+02 1.57E+01 2.07E+04 1.23E+02

Pentachlorobiphenyl 6.31E+01 6.60E+02 3.90E-02 6.31E+01 1.80E+01 3.79E+04 2.24E+03

Hexachlorobiphenyl 0.00E+00 9.42E+01 5.34E-01 0.00E+00 2.41E+01 6.76E+03 1.33E+03

Heptachlorobiphenyl 5.04E+00 7.17E+01 6.46E-01 5.04E+00 1.47E+01 1.30E+03 7.19E+03

Octachlorobiphenyl 0.00E+00 0.00E+00 0.00E+00 0.00E+00 0.00E+00 0.00E+00 0.00E+00

Nonachlorobiphenyl 0.00E+00 0.00E+00 1.72E-03 0.00E+00 1.51E+00 0.00E+00 0.00E+00

Decachlorobiphenyl 0.00E+00 0.00E+00 0.00E+00 0.00E+00 8.43E-01 0.00E+00 0.00E+00

Total 1.58E+03 2.20E+03 2.62E+00 1.58E+03 2.79E+02 6.76E+04 1.11E+04

Release Rates in nanograms PCB per Day Ventilation 

Gaskets Lubricants Foam Rubber 

Material

Black Rubber 

Material

Electrical 

Cable

Bulkhead 

Insulation 

Material

Aluminized 

Paint Total

Monochlorobiphenyl 1.90E+03 0.00E+00 0.00E+00 1.18E+04 0.00E+00 0.00E+00 0.00E+00 1.37E+04

Dichlorobiphenyl 5.80E+04 0.00E+00 0.00E+00 3.62E+05 1.11E+08 4.14E+04 0.00E+00 1.12E+08

Trichlorobiphenyl 2.59E+03 0.00E+00 0.00E+00 1.62E+04 6.25E+05 7.29E+06 2.02E+06 9.95E+06

Tetrachlorobiphenyl 6.60E+03 0.00E+00 0.00E+00 4.11E+04 8.61E+06 1.60E+08 9.51E+05 1.69E+08

Pentachlorobiphenyl 2.89E+03 0.00E+00 0.00E+00 1.80E+04 9.87E+06 2.93E+08 1.73E+07 3.20E+08

Hexachlorobiphenyl 0.00E+00 0.00E+00 0.00E+00 0.00E+00 1.32E+07 5.22E+07 1.03E+07 7.57E+07

Heptachlorobiphenyl 2.31E+02 0.00E+00 0.00E+00 1.44E+03 8.06E+06 1.01E+07 5.56E+07 7.37E+07

Octachlorobiphenyl 0.00E+00 0.00E+00 0.00E+00 0.00E+00 0.00E+00 0.00E+00 0.00E+00 0.00E+00

Nonachlorobiphenyl 0.00E+00 0.00E+00 0.00E+00 0.00E+00 8.28E+05 0.00E+00 0.00E+00 8.28E+05

Decachlorobiphenyl 0.00E+00 0.00E+00 0.00E+00 0.00E+00 4.62E+05 0.00E+00 0.00E+00 4.62E+05

Total 7.23E+04 0.00E+00 0.00E+00 4.50E+05 1.53E+08 5.22E+08 8.62E+07 7.62E+08

Air Mono Di Tri Tetra Penta Hexa Hepta Octa Nona Deca

Fugacity (Pa) 3.22E-20 1.98E-16 1.30E-17 1.74E-16 1.91E-16 6.72E-18 2.40E-18 0.00E+00 8.51E-22 2.74E-24

Air concentration (g/m3) 2.47E-21 1.80E-17 1.37E-18 2.07E-17 2.54E-17 9.88E-19 3.86E-19 0.00E+00 1.61E-22 5.56E-25

Upper Water Column Mono Di Tri Tetra Penta Hexa Hepta Octa Nona Deca

Fugacity (Pa) 6.67E-18 5.04E-14 1.22E-14 9.85E-14 4.71E-14 5.99E-14 7.57E-15 0.00E+00 2.11E-14 9.20E-16

Water concentration (mg/L) 3.07E-17 2.42E-13 1.95E-14 3.16E-13 4.15E-13 1.66E-14 6.80E-15 0.00E+00 3.06E-18 1.10E-20

Suspended solids concentration (mg/kg) 2.12E-14 4.15E-10 1.23E-10 2.14E-09 5.36E-09 2.99E-09 2.23E-09 0.00E+00 4.24E-12 1.44E-13

Dissolved organic carbon (mg/kg) 6.77E-14 3.09E-09 4.79E-10 1.95E-08 1.35E-07 1.16E-08 7.79E-09 0.00E+00 5.09E-11 3.25E-12

Lower Water Column Mono Di Tri Tetra Penta Hexa Hepta Octa Nona Deca

Fugacity (Pa) 2.35E-14 1.81E-10 4.61E-11 3.80E-10 2.18E-10 6.75E-10 1.31E-10 0.00E+00 1.83E-09 9.95E-10

Water concentration (mg/L) 1.08E-13 8.67E-10 7.34E-11 1.22E-09 1.92E-09 1.87E-10 1.18E-10 0.00E+00 2.65E-13 1.19E-14

Suspended solids concentration (mg/kg) 7.47E-11 1.48E-06 4.64E-07 8.25E-06 2.48E-05 3.37E-05 3.87E-05 0.00E+00 3.68E-07 1.55E-07

Dissolved organic carbon (mg/kg) 2.38E-10 1.11E-05 1.80E-06 7.54E-05 6.26E-04 1.31E-04 1.35E-04 0.00E+00 4.41E-06 3.52E-06

Inside the Vessel Mono Di Tri Tetra Penta Hexa Hepta Octa Nona Deca

Fugacity (Pa) 9.67E-12 7.43E-08 1.89E-08 1.56E-07 8.96E-08 2.77E-07 5.40E-08 0.00E+00 7.51E-07 4.09E-07

Water concentration (mg/L) 4.45E-11 3.57E-07 3.02E-08 5.02E-07 7.90E-07 7.68E-08 4.85E-08 0.00E+00 1.09E-10 4.88E-12

Suspended solids concentration (mg/kg) 3.07E-08 6.11E-04 1.91E-04 3.39E-03 1.02E-02 1.39E-02 1.59E-02 0.00E+00 1.51E-04 6.38E-05

Dissolved organic carbon (mg/kg) 9.80E-08 4.54E-03 7.41E-04 3.10E-02 2.57E-01 5.38E-02 5.56E-02 0.00E+00 1.81E-03 1.45E-03

Sediment Bed Mono Di Tri Tetra Penta Hexa Hepta Octa Nona Deca

Fugacity (Pa) 2.35E-14 1.81E-10 4.61E-11 3.80E-10 2.18E-10 6.75E-10 1.31E-10 0.00E+00 1.83E-09 9.95E-10

Pore Water concentration (mg/L) 1.08E-13 8.67E-10 7.34E-11 1.22E-09 1.92E-09 1.87E-10 1.18E-10 0.00E+00 2.65E-13 1.19E-14

Sediment concentration (mg/kg) 4.98E-12 9.90E-08 3.09E-08 5.50E-07 1.65E-06 2.25E-06 2.58E-06 0.00E+00 2.45E-08 1.03E-08

Bioenergetic Inputs

Species Body Weight Lipid Moisture Caloric 

Density GE to ME Met Energy Caloric 

Density Production Respiration Excretion Caloric 

Density Met Energy

(kg) (%-dw) (%) (kcal/g-dry 

weight) Fraction (kcal/kg-lipid) (kcal/kg-lipid) (% of total) (% of total) (% of total) (kcal/g-wt 

weight)

 (kcal/g-wt 

weight)

Pelagic Community

Phytoplankton (TL-I) Algae 10% 84% 2.36 0.6 13748 22913 0.3776 0.22656

Zooplankton (TL-II) copepods 0.000005 22% 76% 3.6 0.65 10636 16364 18% 24% 58% 0.864 0.5616

Planktivore (TL-III) herring 0.05 28% 75% 4.9 0.7 12206 17438 20% 60% 20% 1.225 0.8575

Piscivore (TL-IV) jack 0.5 28% 75% 4.9 0.7 12206 17438 20% 60% 20% 1.225 0.8575

Reef / Vessel Community

Attached Algae (TL-I) Algae 10% 84% 2.36 0.6 13748 22913 0.3776 0.22656

Sessile filter feeder (TL-II) bivalves (w/o shell) 0.05 5% 82% 4.6 0.65 59800 92000 28% 31% 41% 0.828 0.5382

Invertebrate Omnivore (TL-II) urchin 0.05 29% 82% 4.6 0.65 10310 15862 7% 25% 68% 0.828 0.5382

Invertebrate Forager (TL-III) crab 1 9% 74% 2.7 0.65 19118 29412 28% 59% 13% 0.702 0.4563

Vertebrate Forager (TL-III) triggerfish 1 28% 75% 4.9 0.7 12206 17438 20% 60% 20% 1.225 0.8575

Predator (TL-IV) grouper 1.5 28% 75% 4.9 0.7 12206 17438 20% 60% 20% 0.2 0.14

Benthic Community

Infaunal invert. (TL-II) polychaete 0.01 6% 84% 4.6 0.65 50000 76923 71% 26% 3% 0.736 0.4784

Epifaunal invert. (TL-II) nematode 0.01 6% 82% 4.6 0.65 50000 76923 31% 19% 50% 0.828 0.5382

Forager (TL-III) lobster 2 9% 74% 2.7 0.65 19118 29412 28% 59% 13% 0.702 0.4563

Predator (TL-IV) flounder 3 22% 75% 4.9 0.7 15591 22273 20% 60% 20% 1.225 0.8575

Bioenergetic Inputs Resp. Rate Resp. Rate Consumption Growth Rate Consumption Consumption

1 gO2 kcal 1 g-wt weight kcal As a % of

Pelagic Community day kg-lipid-day kg-lipid-day day g-wt weight-d-wet weight-da body weight

Phytoplankton (TL1) Algae

Zooplankton (TL-II) copepods 0.006375522 0 0.039935335 0.015425453 84.24400867 1286.168071 0.014147849 0.32636028 0.06790967 32.6%

Planktivore (TL-III) herring 0.0033 -0.227 0.0548 0.004949927 21.1649 129.2512977 0.001482433 0.01616792 0.0090799 1.6%

Piscivore (TL-IV) jack 0.001118602 -0.55 0.12 0.000630951 2.697821256 16.47524431 0.000188961 0.00139796 0.00115739 0.1%

Reef / Vessel Community

Attached Algae Algae

Sessile filter feeder (TL-II) bivalves (w/o shell) 0.012 0 0.036 0.024213411 581.8482643 6877.300342 0.020930914 0.24377539 0.0618957 24.4%

Invertibrate Omnivore (TL-II) urchin 0.000675466 0 0.079181846 0.003163548 13.1069075 192.1012396 0.000847751 0.03471132 0.01002768 3.5%

Invertibrate Forager (TL-III) crab 0.001158234 0 0.071193202 0.004642088 60.75673491 377.3221989 0.003592107 0.01678102 0.00900593 1.7%

Vertibrate Forager (TL-III) triggerfish 0.015181024 -0.415 0.061 0.002837229 12.13142452 74.08503521 0.00084971 0.00907693 0.00520447 0.9%

Predator (TL-IV) grouper 0.00279 -0.355 0.0811 0.001011362 4.324384181 26.40845301 0.000302889 0.00264734 0.00185519 0.3%

Benthic Community

Infaunal invert. (TL-II) polychaete 0.001682129 0 0.071034762 0.006721006 135.0382801 1903.064429 0.017565285 0.09800757 0.01820852 9.8%

Epifaunal invert. (TL-II) nematode 0.001682129 0 0.071034762 0.006721006 135.0382801 2604.19343 0.0104949 0.09262416 0.02803154 9.3%

Forager (TL-III) lobster 0.0035 -0.13 0.066 0.00471923 61.76639253 383.5925529 0.003651801 0.01899736 0.00915559 1.9%

Predator (TL-IV) flounder 0.0046 -0.24 0.067 0.002486878 13.58174479 82.94195291 0.000744785 0.00974341 0.00456181 1.0%

PCB MODELING RESULTS - PROSPECTIVE RISK EVALUATION 

RISK ESTIMATES FOR Ex-Oriskany CV34

Supplemental Information

Release Rates in nanograms PCB per gram of PCB within the Material

Respiration Rate Allometric Regression Parameters

a b1 b2

5/26/05 8:46

PRAM 1.3 Supplemental Information

1/23/2006 11:00 PM

Based on NEHC PRAM Version 1.3

May 2004 Page 5 of 25
PCB MODELING RESULTS - PROSPECTIVE RISK EVALUATION 

RISK ESTIMATES FOR Ex-Oriskany CV34

Supplemental Information

TROPHIC LEVEL BASED ON DIET 1.125 1.25 1.5 1 2.05625 3.05625 1 2.130625 2.226125 3.17690625 2.964776563 2.46125 2.7015625 3.521328125

Dietary Preferences

Suspended Solids

(Epilimnion)

Suspended 

Solids

(Hypolimnion)

Sediment Phytoplankton Zooplankton Pelagic 

Plankitivore

Attached 

Algae

Reef Sessile 

Filter Feeder

Invertebrate 

Omnivore

Reef

Invertebrate

Forager

Reef

Vertebrate

Forager

Infaunal 

Benthos

Epifaunal 

Benthos

Benthic 

Forager

Pelagic Community

Phytoplankton (TL1)

Zooplankton (TL-II) 15% 15% 70%

Planktivore (TL-III) 100%

Piscivore (TL-IV) 10% 90%

Reef / Vessel Community

Attached Algae

Sessile filter feeder (TL-II) 10% 80% 10%

Invertebrate Omnivore (TL-II) 80% 20%

Invertebrate Forager (TL-III) 5% 5% 5% 35% 50%

Vertebrate Forager (TL-III) 19% 19% 15% 22% 12.5% 12.5%

Predator (TL-IV) 15% 60% 8% 8% 8%

Benthic Community

Infaunal invert. (TL-II) 50% 30% 20%

Epifaunal invert. (TL-II) 25% 30% 20% 25%

Forager (TL-III) 5% 50% 45%

Predator (TL-IV) 2% 20% 20% 58%

Water Exposures

Upper Water 

Column

Lower Water

Column Vessel Interior Sediment PoreWater GE ME ME as kcal/g-ww

Pelagic Community Sediment (kcal/kg-oc) 11456 6873.6 0.6 0.01099776

Phytoplankton (TL1) Algae 100% Suspended Sediment (kcal/kg-oc) 11456 6873.6 0.6 0.1649664

Zooplankton (TL-II) copepods 50% 50%

Planktivore (TL-III) herring 80% 20%

Piscivore (TL-IV) jack 80% 20%

Reef / Vessel Community

Attached Algae Algae 100%

Sessile filter feeder (TL-II) bivalves (w/o shell) 100%

Invertebrate Omnivore (TL-II) urchin 80% 20%

Invertebrate Forager (TL-III) crab 70% 30%

Vertebrate Forager (TL-III) triggerfish 70% 30%

Predator (TL-IV) grouper 80% 20%

Benthic Community

Infaunal invert. (TL-II) polychaete 20% 80%

Epifaunal invert. (TL-II) nematode 50% 50%

Forager (TL-III) lobster 75% 25%

Predator (TL-IV) flounder 90% 10%

Respiratory Efficiencies Mono Di Tri Tetra Penta Hexa Hepta Octa Nona Deca

Low body weight (<100g) 4.335E-01 8.000E-01 8.000E-01 8.000E-01 4.492E-01 2.582E-01 2.018E-01 1.127E-01 5.303E-02 1.255E-02

High body weight (>100g) 5.000E-01 5.000E-01 5.000E-01 5.000E-01 3.769E-01 2.857E-01 2.526E-01 1.888E-01 1.295E-01 6.299E-02

Dietary Assimilation Efficiencies 27% 46% 53% 62% 69% 69% 68% 59% 44% 16%

Tissue Conc. (mg/kg-lipid) Mono Di Tri Tetra Penta Hexa Hepta Octa Nona Deca

Pelagic Community

Phytoplankton (TL1) 9.143E-13 2.422E-08 1.948E-09 3.159E-08 4.150E-08 1.659E-09 6.797E-10 0.000E+00 3.062E-13 1.097E-15

Zooplankton (TL-II) 7.287E-09 2.706E-04 2.729E-05 5.151E-04 5.109E-04 7.310E-05 6.504E-05 0.000E+00 3.261E-07 4.821E-08

Planktivore (TL-III) 1.647E-09 2.291E-04 4.178E-05 1.528E-03 2.723E-03 4.285E-04 3.717E-04 0.000E+00 1.230E-06 6.474E-08

Piscivore (TL-IV) 4.305E-10 4.039E-05 1.109E-05 8.926E-04 4.773E-03 1.285E-03 1.257E-03 0.000E+00 3.671E-06 8.006E-08

Reef / Vessel Community

Attached Algae 3.222E-09 8.672E-05 7.339E-06 1.220E-04 1.920E-04 1.868E-05 1.179E-05 0.000E+00 2.653E-08 1.186E-09

Sessile filter feeder (TL-II) 1.037E-07 3.499E-03 3.456E-04 6.498E-03 6.291E-03 5.571E-04 4.034E-04 0.000E+00 1.291E-06 1.401E-07

Invertebrate Omnivore (TL-II) 2.898E-07 2.252E-02 3.328E-03 1.071E-01 1.730E-01 1.224E-02 6.420E-03 0.000E+00 4.488E-06 6.064E-08

Invertebrate Forager (TL-III) 2.192E-06 8.951E-02 1.334E-02 4.503E-01 8.597E-01 6.798E-02 3.772E-02 0.000E+00 4.148E-05 2.711E-06

Vertebrate Forager (TL-III) 2.015E-07 1.416E-02 3.046E-03 1.785E-01 6.347E-01 6.428E-02 3.756E-02 0.000E+00 4.214E-05 1.385E-06

Predator (TL-IV) 1.116E-07 7.257E-03 1.715E-03 1.498E-01 1.156E+00 1.771E-01 1.137E-01 0.000E+00 1.222E-04 2.685E-06

Benthic Community

Infaunal invert. (TL-II) 2.628E-08 1.032E-03 1.073E-04 2.122E-03 2.130E-03 1.950E-04 1.425E-04 0.000E+00 3.977E-07 2.834E-08

Epifaunal invert. (TL-II) 3.259E-08 1.919E-03 2.289E-04 5.181E-03 5.709E-03 5.472E-04 4.040E-04 0.000E+00 1.015E-06 5.565E-08

Forager (TL-III) 1.903E-08 1.051E-03 1.607E-04 4.856E-03 7.236E-03 6.765E-04 4.610E-04 0.000E+00 7.349E-07 1.686E-08

Predator (TL-IV) 1.685E-09 2.802E-04 7.385E-05 4.574E-03 1.378E-02 1.658E-03 1.171E-03 0.000E+00 1.505E-06 2.213E-08

Tissue Conc. (mg/kg-WW) Mono Di Tri Tetra Penta Hexa Hepta Octa Nona Deca Total PCB

Pelagic Community

Phytoplankton (TL1) 1.507E-14 3.991E-10 3.211E-11 5.207E-10 6.838E-10 2.735E-11 1.120E-11 0.000E+00 5.047E-15 1.807E-17 1.674E-09

Zooplankton (TL-II) 3.847E-10 1.429E-05 1.441E-06 2.720E-05 2.698E-05 3.860E-06 3.434E-06 0.000E+00 1.722E-08 2.545E-09 7.722E-05

Planktivore (TL-III) 1.157E-10 1.610E-05 2.935E-06 1.073E-04 1.913E-04 3.010E-05 2.611E-05 0.000E+00 8.639E-08 4.548E-09 3.740E-04

Piscivore (TL-IV) 3.024E-11 2.837E-06 7.791E-07 6.270E-05 3.353E-04 9.028E-05 8.828E-05 0.000E+00 2.579E-07 5.625E-09 5.804E-04

Reef / Vessel Community

Attached Algae 5.309E-11 1.429E-06 1.209E-07 2.010E-06 3.165E-06 3.078E-07 1.944E-07 0.000E+00 4.372E-10 1.955E-11 7.228E-06

Sessile filter feeder (TL-II) 9.335E-10 3.149E-05 3.110E-06 5.848E-05 5.662E-05 5.014E-06 3.631E-06 0.000E+00 1.162E-08 1.261E-09 1.584E-04

Invertebrate Omnivore (TL-II) 1.513E-08 1.176E-03 1.737E-04 5.591E-03 9.032E-03 6.389E-04 3.351E-04 0.000E+00 2.343E-07 3.166E-09 1.695E-02

Invertebrate Forager (TL-III) 5.231E-08 2.136E-03 3.184E-04 1.075E-02 2.052E-02 1.623E-03 9.003E-04 0.000E+00 9.901E-07 6.469E-08 3.624E-02

Vertebrate Forager (TL-III) 1.415E-08 9.949E-04 2.140E-04 1.254E-02 4.459E-02 4.516E-03 2.638E-03 0.000E+00 2.960E-06 9.732E-08 6.550E-02

Predator (TL-IV) 7.841E-09 5.098E-04 1.205E-04 1.052E-02 8.122E-02 1.244E-02 7.984E-03 0.000E+00 8.585E-06 1.886E-07 1.128E-01

Benthic Community

Infaunal invert. (TL-II) 2.514E-10 9.875E-06 1.026E-06 2.030E-05 2.038E-05 1.866E-06 1.363E-06 0.000E+00 3.805E-09 2.711E-10 5.482E-05

Epifaunal invert. (TL-II) 3.508E-10 2.066E-05 2.464E-06 5.577E-05 6.146E-05 5.891E-06 4.348E-06 0.000E+00 1.092E-08 5.990E-10 1.506E-04

Forager (TL-III) 4.541E-10 2.508E-05 3.835E-06 1.159E-04 1.727E-04 1.615E-05 1.100E-05 0.000E+00 1.754E-08 4.024E-10 3.447E-04

Predator (TL-IV) 9.265E-11 1.541E-05 4.062E-06 2.516E-04 7.580E-04 9.120E-05 6.440E-05 0.000E+00 8.279E-08 1.217E-09 1.185E-03

BAFs (L/kg-lipid) Mono Di Tri Tetra Penta Hexa Hepta Octa Nona Deca

Pelagic Community

Phytoplankton (TL1) 2.979E+04 1.000E+05 1.000E+05 1.000E+05 1.000E+05 1.000E+05 1.000E+05 0.000E+00 1.000E+05 1.000E+05

Zooplankton (TL-II) 1.347E+05 6.238E+05 7.436E+05 8.445E+05 5.320E+05 7.826E+05 1.103E+06 0.000E+00 2.458E+06 8.127E+06

Planktivore (TL-III) 7.603E+04 1.320E+06 2.843E+06 6.258E+06 7.083E+06 1.146E+07 1.576E+07 0.000E+00 2.317E+07 2.729E+07

Piscivore (TL-IV) 1.988E+04 2.326E+05 7.548E+05 3.655E+06 1.242E+07 3.439E+07 5.326E+07 0.000E+00 6.917E+07 3.375E+07

Reef / Vessel Community

Attached Algae 2.979E+04 1.000E+05 1.000E+05 1.000E+05 1.000E+05 1.000E+05 1.000E+05 0.000E+00 1.000E+05 1.000E+05

Sessile filter feeder (TL-II) 9.590E+05 4.034E+06 4.709E+06 5.328E+06 3.276E+06 2.983E+06 3.420E+06 0.000E+00 4.867E+06 1.181E+07

Invertebrate Omnivore (TL-II) 3.226E+04 3.127E+05 5.460E+05 1.057E+06 1.085E+06 7.891E+05 6.556E+05 0.000E+00 2.037E+05 6.157E+04

Invertebrate Forager (TL-III) 1.633E+05 8.319E+05 1.465E+06 2.976E+06 3.608E+06 2.934E+06 2.578E+06 0.000E+00 1.260E+06 1.842E+06

Vertebrate Forager (TL-III) 1.501E+04 1.316E+05 3.345E+05 1.180E+06 2.664E+06 2.774E+06 2.567E+06 0.000E+00 1.280E+06 9.414E+05

Predator (TL-IV) 1.243E+04 1.008E+05 2.815E+05 1.479E+06 7.250E+06 1.142E+07 1.161E+07 0.000E+00 5.547E+06 2.726E+06

Benthic Community

Infaunal invert. (TL-II) 2.429E+05 1.190E+06 1.462E+06 1.740E+06 1.109E+06 1.044E+06 1.208E+06 0.000E+00 1.499E+06 2.389E+06

Epifaunal invert. (TL-II) 3.013E+05 2.213E+06 3.119E+06 4.248E+06 2.973E+06 2.930E+06 3.425E+06 0.000E+00 3.825E+06 4.691E+06

Forager (TL-III) 1.759E+05 1.212E+06 2.189E+06 3.981E+06 3.768E+06 3.622E+06 3.909E+06 0.000E+00 2.770E+06 1.421E+06

Predator (TL-IV) 1.557E+04 3.231E+05 1.006E+06 3.750E+06 7.177E+06 8.877E+06 9.928E+06 0.000E+00 5.673E+06 1.865E+06

Notes:

Kow = octanol to water partitioning coefficient, Koc = organic carbon partitioning coefficient, Kdoc = dissolved organic carbon partitioning coefficient

TL = trophic level, ww = wet weight

Energy Estimates for Suspended Sediment and Bedded Sediment

PRAM 1.3 Supplemental Information

1/23/2006 11:00 PM

Based on NEHC PRAM Version 1.3

May 2004 Page 6 of 25
ZOI = 3

RISK ESTIMATES RME CTE RME CTE RME CTE RME CTE

Benthic fish (flounder) 5.70E-08 4.41E-09 3.32E-03 7.62E-04 1.67E-08 3.39E-09 4.88E-03 8.79E-04

Benthic shellfish (lobster) 1.66E-08 1.28E-09 9.67E-04 2.22E-04 4.86E-09 9.87E-10 1.42E-03 2.56E-04

Pelagic fish (jack) 2.79E-08 2.16E-09 1.63E-03 3.74E-04 8.19E-09 1.66E-09 2.39E-03 4.31E-04

Reef fish TL-IV (grouper) 6.90E-06 5.34E-07 4.02E-01 9.23E-02 2.02E-06 4.11E-07 5.90E-01 1.06E-01

Reef fish TL-III (triggerfish) 4.00E-06 3.10E-07 2.34E-01 5.36E-02 1.17E-06 2.38E-07 3.43E-01 6.18E-02

Reef shellfish (crab) 2.22E-06 1.72E-07 1.29E-01 2.97E-02 6.51E-07 1.32E-07 1.90E-01 3.42E-02

PREDICTED EXPOSURE CONCENTRATIONS (mg/kg in fresh weight)

Benthic fish (flounder) 9.26E-04

Benthic shellfish (lobster) 2.69E-04

Pelagic fish (jack) 4.54E-04

Reef fish TL-IV (grouper) 1.12E-01

Reef fish TL-III (triggerfish) 6.51E-02

Reef shellfish (crab) 3.61E-02

RISK INPUTS - Adult RME CTE RISK INPUTS - Child RME CTE

Body Weight (BWc) (kg) 70 70 Body Weight (BWc) (kg) 15 15

Ingestion Rate (IRc) (kg/day) 0.0261 0.0072 Ingestion Rate (IRc) (kg/day) 0.0092916 0.0025632

Exposure Duration (EDc) (years) 24 3 Exposure Duration (EDc) (years) 6 6

Exposure Frequency (EFc) (days) 365 365 Exposure Frequency (EFc) (days) 365 365

Averaging Time for cancer (ATc) 25550 25550 Averaging Time for cancer (ATc) 25550 25550

Slope Factor (mg/kg-day) 2 1 Slope Factor (mg/kg-day) 2 1

Reference dose for PCBs (RfD) (mg/kg-day) 0.00002 0.000045 Reference dose for PCBs (RfD) (mg/kg-day) 0.00002 0.000045

Averaging Time for noncancer (ATnc-child) 8.76E+03 1.10E+03 Averaging Time for noncancer (ATnc-child) 2.19E+03 2.19E+03

Fractional Ingestion factor (FI) 0.17 0.25 Fractional Ingestion factor (FI) 0.17 0.25

Child - Adult IR scaling factor

Zone of Influence Multiplier 3

Scenario run on

PCB-LADEN MATERIAL INPUTS Fraction Release kg Material PCB Release Ex-Oriskany CV34

PCB Rate (ng/g-d) Onboard (ng/day) Ex-Oriskany CV34 27100

Ventilation Gaskets 3.14E-05 1.58E+03 1.46E+03 7.23E+04 Length (ft) 888

Lubricants 1.03E-04 2.20E+03 0.00E+00 0.00E+00 Beam (ft) 120

Foam Rubber Material 0.76% 2.62E+00 0.00E+00 0.00E+00

Black Rubber Material 5.29E-05 1.58E+03 5.40E+03 4.50E+05

Electrical Cable 1.85E-03 2.79E+02 2.96E+05 1.53E+08

Bulkhead Insulation Material 5.37E-04 6.76E+04 1.44E+04 5.22E+08

Aluminum Paint 2.00E-05 1.11E+04 3.87E+05 8.62E+07

Total 7.62E+08

ZOI = 3

2.33E+04 m2

9.01E-03 mile2

A 1.00E+01 m

B 1.50E+01 m

C 5.00E+01 m

D 1.00E-01 m

E 3.25E+02 m

F 9.13E+01 m

Air Column

Air 2.33E+05 m3

Upper Water Column

Water 3.50E+05 m3

TSS 2.33E+00 m3

Lower Water Column

Water 1.11E+06 m3

TSS 7.42E+00 m3

Inside Vessel

Water 5.38E+04 m3

TSS 3.59E-01 m3

Sediment Bed

Sediment 1.56E+03 m3

Abiotic Inputs Total PCB concentrations

Air Column Air Column

Active air space height above water column (m) 10 Air 7.83E-17 g/m3

Air current (m/h) 13677 Upper Water Column

Upper Water Column Freely dissolved in water 9.72E-13 mg/L

Temperature (oC) 24.5 Suspended solids 1.27E-08 mg/kg

Water depth (m) 15 Dissolved organic carbon 1.70E-07 mg/kg

Total suspended solids (mg/L) 10 Lower Water Column

Dissolved organic carbon (mg/L) 0.6 Freely dissolved in water 3.43E-09 mg/L

Dissolved oxygen (mg/L) 6.12 Suspended solids 8.43E-05 mg/kg

Lower Water Column Dissolved organic carbon 7.72E-04 mg/kg

Temperature (oC) 19.5 Inside Vessel

Water depth (m) 50 Freely dissolved in water 1.80E-06 mg/L

Total suspended solids (mg/L) 10 Suspended solids 4.44E-02 mg/kg

Dissolved organic carbon (mg/L) 0.6 Dissolved organic carbon 4.06E-01 mg/kg

Dissolved oxygen (mg/L) 4.59 Sediment Bed

Inside Vessel Freely dissolved in pore water 3.43E-09 mg/L

Temperature (oC) 19.5 Bedded sediment 5.62E-06 mg/kg

Total suspended solids (mg/L) 10 Dissolved organic carbon in pore water 7.72E-04 mg/kg

Dissolved organic carbon (mg/L) 0.6 Total PCB concentrations in biota

Dissolved oxygen (mg/L) 4.59 Pelagic Community Upper WC Lower WC

Sediment Bed Phytoplankton (TL-I) 1.60E-09 mg/kg 100% 0%

Sediment density (g/cm3) 1.5 Zooplankton (TL-II) 6.04E-05 mg/kg 50% 50%

Active sediment depth (m) 0.1 Planktivore (TL-III) 2.92E-04 mg/kg 80% 20%

Sediment fraction organic carbon 0.01 Piscivore (TL-IV) 4.54E-04 mg/kg 80% 20%

All Regions Reef / Vessel Community Lower WC Vessel Int.

Suspended solids density (g/cm3) 1.5 Attached Algae (TL-I) 5.65E-06 mg/kg 100% 0%

Suspended solids fraction organic carbon 0.15 Sessile filter feeder (TL-II) 1.24E-04 mg/kg 100% 0%

Dissolved organic carbon density (g/cm3) 1 Invertebrate Omnivore (TL-II) 1.68E-02 mg/kg 80% 20%

Water current - to out of the ZOI (m/h) 926 Invertebrate Forager (TL-III) 3.61E-02 mg/kg 70% 30%

Water current - inside to outside the vessel (m/h) 9.26 Vertebrate Forager (TL-III) 6.51E-02 mg/kg 70% 30%

Predator (TL-IV) 1.12E-01 mg/kg 80% 20%

Benthic Community Lower WC Pore Water

Infaunal invert. (TL-II) 4.28E-05 mg/kg 20% 80%

Epifaunal invert. (TL-II) 1.18E-04 mg/kg 50% 50%

Forager (TL-III) 2.69E-04 mg/kg 75% 25%

Predator (TL-IV) 9.26E-04 mg/kg 90% 10%

Percent Exposures

Spatial Footprint on Ocean Floor

RISK ESTIMATES FOR Ex-Oriskany CV34

Volumes

Cancer Risk Adult & Child Hazard Adult & Child Cancer Risk Child Hazard Child

0.356

PCB MODELING RESULTS - PROSPECTIVE RISK EVALUATION 

Modeled Dimensions

Outside the Vessel

6/1/05 12:00

A

C

D

E E

E

VESSEL

B

Pycnocline

A

C

D

E E

E

VESSEL

B

Pycnocline

F_Xappdx_2b.xls B2.3_zoi3_Estimate

1/23/2006 11:00 PM

Based on NEHC PRAM Version 1.4

May 2005 Page 7 of 25
Scenario Run on ZOI = 3

PCB Homolog Mono Di Tri Tetra Penta Hexa Hepta Octa Nona Deca

Molecular Weight (g/mol) 1.89E+02 2.23E+02 2.58E+02 2.92E+02 3.26E+02 3.61E+02 3.95E+02 4.30E+02 4.64E+02 4.99E+02

Solubility (mg/L) 2.91E+00 6.78E-01 8.14E-02 6.67E-02 2.61E-02 9.50E-04 2.30E-04 2.11E-08 4.02E-09 1.69E-10

Solubility (mol/m3

) 1.54E-02 3.04E-03 3.16E-04 2.28E-04 8.00E-05 2.63E-06 5.82E-07 4.91E-11 8.65E-12 3.38E-13

Vapor Pressure (Pa) 6.32E-01 1.41E-01 5.11E-02 2.08E-02 2.96E-03 3.43E-03 2.56E-04 8.65E-05 2.77E-05 1.41E-05

Henry's (Pa-m3

/mol) 4.10E+01 4.65E+01 1.62E+02 9.10E+01 3.70E+01 1.30E+03 4.40E+02 1.76E+06 3.20E+06 4.18E+07

log10Kow = 4.47 5.24 5.52 5.92 6.50 6.98 7.19 7.70 8.35 9.60

log10Koc = 3.66 4.06 4.63 4.65 4.94 6.08 6.34 6.46 6.97 7.94

log10Kdoc = 3.34 4.11 4.39 4.79 5.51 5.85 6.06 6.57 7.22 8.47

Chemical emission rate (g/day) 1.37E-05 1.12E-01 9.95E-03 1.69E-01 3.20E-01 7.57E-02 7.37E-02 0.00E+00 8.28E-04 4.62E-04

Chemical emission rate (mol/hr) 3.03E-09 2.09E-05 1.61E-06 2.42E-05 4.08E-05 8.74E-06 7.77E-06 0.00E+00 7.43E-08 3.86E-08

Biodegradation in sediment (1/hr) 0 0 0 0 0 0 0 000

Biodegradation in water (1/hr) 0 0 0 0 0 0 0 000

Ventilation 

Gaskets Lubricants Foam Rubber 

Material

Black Rubber 

Material

Electrical 

Cable

Bulkhead 

Insulation 

Material

Aluminized 

Paint

Fraction PCB in Material (wt/wt) 0.0000314 0.000103 0.76% 0.0000529 0.00185 0.000537 0.00002

Material Mass Onboard (kg) 1459 0 0 5397 296419 14379 386528

Total PCBs (kg) 0.0458126 0 0 0.2855013 548.37515 7.721523 7.73056

Total PCB Release rate (ng/g-PCB per day) 1.58E+03 2.20E+03 2.62E+00 1.58E+03 2.79E+02 6.76E+04 1.11E+04

Ventilation 

Gaskets Lubricants Foam Rubber Material

Black Rubber 

Material

Electrical 

Cable

Bulkhead 

Insulation 

Material

Aluminized 

Paint

Monochlorobiphenyl 4.14E+01 3.47E+01 0.00E+00 4.14E+01 0.00E+00 0.00E+00 0.00E+00

Dichlorobiphenyl 1.27E+03 1.72E+02 3.08E-02 1.27E+03 2.03E+02 5.36E+00 0.00E+00

Trichlorobiphenyl 5.66E+01 8.97E+01 7.63E-02 5.66E+01 1.14E+00 9.44E+02 2.61E+02

Tetrachlorobiphenyl 1.44E+02 1.08E+03 1.29E+00 1.44E+02 1.57E+01 2.07E+04 1.23E+02

Pentachlorobiphenyl 6.31E+01 6.60E+02 3.90E-02 6.31E+01 1.80E+01 3.79E+04 2.24E+03

Hexachlorobiphenyl 0.00E+00 9.42E+01 5.34E-01 0.00E+00 2.41E+01 6.76E+03 1.33E+03

Heptachlorobiphenyl 5.04E+00 7.17E+01 6.46E-01 5.04E+00 1.47E+01 1.30E+03 7.19E+03

Octachlorobiphenyl 0.00E+00 0.00E+00 0.00E+00 0.00E+00 0.00E+00 0.00E+00 0.00E+00

Nonachlorobiphenyl 0.00E+00 0.00E+00 1.72E-03 0.00E+00 1.51E+00 0.00E+00 0.00E+00

Decachlorobiphenyl 0.00E+00 0.00E+00 0.00E+00 0.00E+00 8.43E-01 0.00E+00 0.00E+00

Total 1.58E+03 2.20E+03 2.62E+00 1.58E+03 2.79E+02 6.76E+04 1.11E+04

Release Rates in nanograms PCB per Day Ventilation 

Gaskets Lubricants Foam Rubber 

Material

Black Rubber 

Material

Electrical 

Cable

Bulkhead 

Insulation 

Material

Aluminized 

Paint Total

Monochlorobiphenyl 1.90E+03 0.00E+00 0.00E+00 1.18E+04 0.00E+00 0.00E+00 0.00E+00 1.37E+04

Dichlorobiphenyl 5.80E+04 0.00E+00 0.00E+00 3.62E+05 1.11E+08 4.14E+04 0.00E+00 1.12E+08

Trichlorobiphenyl 2.59E+03 0.00E+00 0.00E+00 1.62E+04 6.25E+05 7.29E+06 2.02E+06 9.95E+06

Tetrachlorobiphenyl 6.60E+03 0.00E+00 0.00E+00 4.11E+04 8.61E+06 1.60E+08 9.51E+05 1.69E+08

Pentachlorobiphenyl 2.89E+03 0.00E+00 0.00E+00 1.80E+04 9.87E+06 2.93E+08 1.73E+07 3.20E+08

Hexachlorobiphenyl 0.00E+00 0.00E+00 0.00E+00 0.00E+00 1.32E+07 5.22E+07 1.03E+07 7.57E+07

Heptachlorobiphenyl 2.31E+02 0.00E+00 0.00E+00 1.44E+03 8.06E+06 1.01E+07 5.56E+07 7.37E+07

Octachlorobiphenyl 0.00E+00 0.00E+00 0.00E+00 0.00E+00 0.00E+00 0.00E+00 0.00E+00 0.00E+00

Nonachlorobiphenyl 0.00E+00 0.00E+00 0.00E+00 0.00E+00 8.28E+05 0.00E+00 0.00E+00 8.28E+05

Decachlorobiphenyl 0.00E+00 0.00E+00 0.00E+00 0.00E+00 4.62E+05 0.00E+00 0.00E+00 4.62E+05

Total 7.23E+04 0.00E+00 0.00E+00 4.50E+05 1.53E+08 5.22E+08 8.62E+07 7.62E+08

Air Mono Di Tri Tetra Penta Hexa Hepta Octa Nona Deca

Fugacity (Pa) 3.77E-20 2.32E-16 1.53E-17 2.04E-16 2.24E-16 7.88E-18 2.81E-18 0.00E+00 9.97E-22 3.21E-24

Air concentration (g/m3) 2.89E-21 2.11E-17 1.60E-18 2.43E-17 2.97E-17 1.16E-18 4.52E-19 0.00E+00 1.89E-22 6.51E-25

Upper Water Column Mono Di Tri Tetra Penta Hexa Hepta Octa Nona Deca

Fugacity (Pa) 6.39E-18 4.83E-14 1.17E-14 9.43E-14 4.51E-14 5.74E-14 7.25E-15 0.00E+00 2.02E-14 8.80E-16

Water concentration (mg/L) 2.94E-17 2.32E-13 1.86E-14 3.02E-13 3.97E-13 1.59E-14 6.51E-15 0.00E+00 2.93E-18 1.05E-20

Suspended solids concentration (mg/kg) 2.03E-14 3.97E-10 1.18E-10 2.05E-09 5.13E-09 2.86E-09 2.14E-09 0.00E+00 4.06E-12 1.37E-13

Dissolved organic carbon (mg/kg) 6.47E-14 2.95E-09 4.58E-10 1.87E-08 1.29E-07 1.11E-08 7.46E-09 0.00E+00 4.87E-11 3.11E-12

Lower Water Column Mono Di Tri Tetra Penta Hexa Hepta Octa Nona Deca

Fugacity (Pa) 1.84E-14 1.41E-10 3.60E-11 2.97E-10 1.70E-10 5.27E-10 1.03E-10 0.00E+00 1.43E-09 7.78E-10

Water concentration (mg/L) 8.45E-14 6.78E-10 5.74E-11 9.53E-10 1.50E-09 1.46E-10 9.22E-11 0.00E+00 2.07E-13 9.27E-15

Suspended solids concentration (mg/kg) 5.84E-11 1.16E-06 3.63E-07 6.45E-06 1.94E-05 2.63E-05 3.03E-05 0.00E+00 2.87E-07 1.21E-07

Dissolved organic carbon (mg/kg) 1.86E-10 8.64E-06 1.41E-06 5.89E-05 4.89E-04 1.02E-04 1.06E-04 0.00E+00 3.44E-06 2.75E-06

Inside the Vessel Mono Di Tri Tetra Penta Hexa Hepta Octa Nona Deca

Fugacity (Pa) 9.67E-12 7.43E-08 1.89E-08 1.56E-07 8.96E-08 2.77E-07 5.40E-08 0.00E+00 7.51E-07 4.09E-07

Water concentration (mg/L) 4.45E-11 3.57E-07 3.02E-08 5.02E-07 7.90E-07 7.68E-08 4.85E-08 0.00E+00 1.09E-10 4.88E-12

Suspended solids concentration (mg/kg) 3.07E-08 6.11E-04 1.91E-04 3.39E-03 1.02E-02 1.39E-02 1.59E-02 0.00E+00 1.51E-04 6.38E-05

Dissolved organic carbon (mg/kg) 9.80E-08 4.54E-03 7.41E-04 3.10E-02 2.57E-01 5.38E-02 5.56E-02 0.00E+00 1.81E-03 1.45E-03

Sediment Bed Mono Di Tri Tetra Penta Hexa Hepta Octa Nona Deca

Fugacity (Pa) 1.84E-14 1.41E-10 3.60E-11 2.97E-10 1.70E-10 5.27E-10 1.03E-10 0.00E+00 1.43E-09 7.78E-10

Pore Water concentration (mg/L) 8.45E-14 6.78E-10 5.74E-11 9.53E-10 1.50E-09 1.46E-10 9.22E-11 0.00E+00 2.07E-13 9.27E-15

Sediment concentration (mg/kg) 3.89E-12 7.74E-08 2.42E-08 4.30E-07 1.29E-06 1.76E-06 2.02E-06 0.00E+00 1.92E-08 8.09E-09

Bioenergetic Inputs

Species Body Weight Lipid Moisture Caloric 

Density GE to ME Met Energy Caloric 

Density Production Respiration Excretion Caloric 

Density Met Energy

(kg) (%-dw) (%) (kcal/g-dry 

weight) Fraction (kcal/kg-lipid) (kcal/kg-lipid) (% of total) (% of total) (% of total) (kcal/g-wt 

weight)

 (kcal/g-wt 

weight)

Pelagic Community

Phytoplankton (TL-I) Algae 10% 84% 2.36 0.6 13748 22913 0.3776 0.22656

Zooplankton (TL-II) copepods 0.000005 22% 76% 3.6 0.65 10636 16364 18% 24% 58% 0.864 0.5616

Planktivore (TL-III) herring 0.05 28% 75% 4.9 0.7 12206 17438 20% 60% 20% 1.225 0.8575

Piscivore (TL-IV) jack 0.5 28% 75% 4.9 0.7 12206 17438 20% 60% 20% 1.225 0.8575

Reef / Vessel Community

Attached Algae (TL-I) Algae 10% 84% 2.36 0.6 13748 22913 0.3776 0.22656

Sessile filter feeder (TL-II) bivalves (w/o shell) 0.05 5% 82% 4.6 0.65 59800 92000 28% 31% 41% 0.828 0.5382

Invertebrate Omnivore (TL-II) urchin 0.05 29% 82% 4.6 0.65 10310 15862 7% 25% 68% 0.828 0.5382

Invertebrate Forager (TL-III) crab 1 9% 74% 2.7 0.65 19118 29412 28% 59% 13% 0.702 0.4563

Vertebrate Forager (TL-III) triggerfish 1 28% 75% 4.9 0.7 12206 17438 20% 60% 20% 1.225 0.8575

Predator (TL-IV) grouper 1.5 28% 75% 4.9 0.7 12206 17438 20% 60% 20% 0.2 0.14

Benthic Community

Infaunal invert. (TL-II) polychaete 0.01 6% 84% 4.6 0.65 50000 76923 71% 26% 3% 0.736 0.4784

Epifaunal invert. (TL-II) nematode 0.01 6% 82% 4.6 0.65 50000 76923 31% 19% 50% 0.828 0.5382

Forager (TL-III) lobster 2 9% 74% 2.7 0.65 19118 29412 28% 59% 13% 0.702 0.4563

Predator (TL-IV) flounder 3 22% 75% 4.9 0.7 15591 22273 20% 60% 20% 1.225 0.8575

Bioenergetic Inputs Resp. Rate Resp. Rate Consumption Growth Rate Consumption Consumption

1 gO2 kcal 1 g-wt weight kcal As a % of

Pelagic Community day kg-lipid-day kg-lipid-day day g-wt weight-d-wet weight-da body weight

Phytoplankton (TL1) Algae

Zooplankton (TL-II) copepods 0.006375522 0 0.039935335 0.015425453 84.24400867 1286.168071 0.014147849 0.32636028 0.06790967 32.6%

Planktivore (TL-III) herring 0.0033 -0.227 0.0548 0.004949927 21.1649 129.2512977 0.001482433 0.01616792 0.0090799 1.6%

Piscivore (TL-IV) jack 0.001118602 -0.55 0.12 0.000630951 2.697821256 16.47524431 0.000188961 0.00139796 0.00115739 0.1%

Reef / Vessel Community

Attached Algae Algae

Sessile filter feeder (TL-II) bivalves (w/o shell) 0.012 0 0.036 0.024213411 581.8482643 6877.300342 0.020930914 0.24377539 0.0618957 24.4%

Invertibrate Omnivore (TL-II) urchin 0.000675466 0 0.079181846 0.003163548 13.1069075 192.1012396 0.000847751 0.03471132 0.01002768 3.5%

Invertibrate Forager (TL-III) crab 0.001158234 0 0.071193202 0.004642088 60.75673491 377.3221989 0.003592107 0.01678102 0.00900593 1.7%

Vertibrate Forager (TL-III) triggerfish 0.015181024 -0.415 0.061 0.002837229 12.13142452 74.08503521 0.00084971 0.00907693 0.00520447 0.9%

Predator (TL-IV) grouper 0.00279 -0.355 0.0811 0.001011362 4.324384181 26.40845301 0.000302889 0.00264734 0.00185519 0.3%

Benthic Community

Infaunal invert. (TL-II) polychaete 0.001682129 0 0.071034762 0.006721006 135.0382801 1903.064429 0.017565285 0.09800757 0.01820852 9.8%

Epifaunal invert. (TL-II) nematode 0.001682129 0 0.071034762 0.006721006 135.0382801 2604.19343 0.0104949 0.09262416 0.02803154 9.3%

Forager (TL-III) lobster 0.0035 -0.13 0.066 0.00471923 61.76639253 383.5925529 0.003651801 0.01899736 0.00915559 1.9%

Predator (TL-IV) flounder 0.0046 -0.24 0.067 0.002486878 13.58174479 82.94195291 0.000744785 0.00974341 0.00456181 1.0%

PCB MODELING RESULTS - PROSPECTIVE RISK EVALUATION 

RISK ESTIMATES FOR Ex-Oriskany CV34

Supplemental Information

Release Rates in nanograms PCB per gram of PCB within the Material

Respiration Rate Allometric Regression Parameters

a b1 b2

6/1/05 12:00

PRAM 1.3 Supplemental Information

1/23/2006 11:00 PM

Based on NEHC PRAM Version 1.3

May 2004 Page 8 of 25
PCB MODELING RESULTS - PROSPECTIVE RISK EVALUATION 

RISK ESTIMATES FOR Ex-Oriskany CV34

Supplemental Information

Dietary Preferences

Suspended Solids

(Epilimnion)

Suspended 

Solids

(Hypolimnion)

Sediment Phytoplankton Zooplankton Pelagic 

Plankitivore

Attached 

Algae

Reef Sessile 

Filter Feeder

Invertebrate 

Omnivore

Reef

Invertebrate

Forager

Reef

Vertebrate

Forager

Infaunal 

Benthos

Epifaunal 

Benthos

Benthic 

Forager

Pelagic Community

Phytoplankton (TL1)

Zooplankton (TL-II) 15% 15% 70%

Planktivore (TL-III) 100%

Piscivore (TL-IV) 10% 90%

Reef / Vessel Community

Attached Algae

Sessile filter feeder (TL-II) 10% 80% 10%

Invertebrate Omnivore (TL-II) 80% 20%

Invertebrate Forager (TL-III) 5% 5% 5% 35% 50%

Vertebrate Forager (TL-III) 19% 19% 15% 22% 12.5% 12.5%

Predator (TL-IV) 15% 60% 8% 8% 8%

Benthic Community

Infaunal invert. (TL-II) 50% 30% 20%

Epifaunal invert. (TL-II) 25% 30% 20% 25%

Forager (TL-III) 5% 50% 45%

Predator (TL-IV) 2% 20% 20% 58%

Water Exposures

Upper Water 

Column

Lower Water

Column Vessel Interior Sediment PoreWater GE ME ME as kcal/g-ww

Pelagic Community Sediment (kcal/kg-oc) 11456 6873.6 0.6 0.01099776

Phytoplankton (TL1) Algae 100% Suspended Sediment (kcal/kg-oc) 11456 6873.6 0.6 0.1649664

Zooplankton (TL-II) copepods 50% 50%

Planktivore (TL-III) herring 80% 20%

Piscivore (TL-IV) jack 80% 20%

Reef / Vessel Community

Attached Algae Algae 100%

Sessile filter feeder (TL-II) bivalves (w/o shell) 100%

Invertebrate Omnivore (TL-II) urchin 80% 20%

Invertebrate Forager (TL-III) crab 70% 30%

Vertebrate Forager (TL-III) triggerfish 70% 30%

Predator (TL-IV) grouper 80% 20%

Benthic Community

Infaunal invert. (TL-II) polychaete 20% 80%

Epifaunal invert. (TL-II) nematode 50% 50%

Forager (TL-III) lobster 75% 25%

Predator (TL-IV) flounder 90% 10%

Respiratory Efficiencies Mono Di Tri Tetra Penta Hexa Hepta Octa Nona Deca

Low body weight (<100g) 4.335E-01 8.000E-01 8.000E-01 8.000E-01 4.492E-01 2.582E-01 2.018E-01 1.127E-01 5.303E-02 1.255E-02

High body weight (>100g) 5.000E-01 5.000E-01 5.000E-01 5.000E-01 3.769E-01 2.857E-01 2.526E-01 1.888E-01 1.295E-01 6.299E-02

Dietary Assimilation Efficiencies 27% 46% 53% 62% 69% 69% 68% 59% 44% 16%

Tissue Conc. (mg/kg-lipid) Mono Di Tri Tetra Penta Hexa Hepta Octa Nona Deca

Pelagic Community

Phytoplankton (TL1) 8.750E-13 2.318E-08 1.865E-09 3.024E-08 3.972E-08 1.588E-09 6.506E-10 0.000E+00 2.932E-13 1.050E-15

Zooplankton (TL-II) 5.696E-09 2.115E-04 2.134E-05 4.027E-04 3.994E-04 5.714E-05 5.083E-05 0.000E+00 2.549E-07 3.768E-08

Planktivore (TL-III) 1.287E-09 1.791E-04 3.266E-05 1.194E-03 2.129E-03 3.349E-04 2.905E-04 0.000E+00 9.612E-07 5.060E-08

Piscivore (TL-IV) 3.366E-10 3.157E-05 8.670E-06 6.977E-04 3.731E-03 1.005E-03 9.822E-04 0.000E+00 2.869E-06 6.258E-08

Reef / Vessel Community

Attached Algae 2.518E-09 6.778E-05 5.736E-06 9.533E-05 1.501E-04 1.460E-05 9.218E-06 0.000E+00 2.074E-08 9.272E-10

Sessile filter feeder (TL-II) 8.107E-08 2.734E-03 2.701E-04 5.079E-03 4.917E-03 4.355E-04 3.153E-04 0.000E+00 1.009E-06 1.095E-07

Invertebrate Omnivore (TL-II) 2.890E-07 2.243E-02 3.312E-03 1.065E-01 1.719E-01 1.213E-02 6.345E-03 0.000E+00 4.354E-06 5.640E-08

Invertebrate Forager (TL-III) 2.189E-06 8.926E-02 1.329E-02 4.483E-01 8.549E-01 6.748E-02 3.738E-02 0.000E+00 4.100E-05 2.699E-06

Vertebrate Forager (TL-III) 2.011E-07 1.411E-02 3.032E-03 1.776E-01 6.308E-01 6.375E-02 3.718E-02 0.000E+00 4.161E-05 1.377E-06

Predator (TL-IV) 1.114E-07 7.236E-03 1.709E-03 1.490E-01 1.149E+00 1.758E-01 1.126E-01 0.000E+00 1.210E-04 2.674E-06

Benthic Community

Infaunal invert. (TL-II) 2.054E-08 8.067E-04 8.384E-05 1.658E-03 1.665E-03 1.524E-04 1.114E-04 0.000E+00 3.108E-07 2.215E-08

Epifaunal invert. (TL-II) 2.547E-08 1.500E-03 1.789E-04 4.050E-03 4.463E-03 4.277E-04 3.158E-04 0.000E+00 7.933E-07 4.350E-08

Forager (TL-III) 1.487E-08 8.214E-04 1.256E-04 3.795E-03 5.656E-03 5.288E-04 3.603E-04 0.000E+00 5.744E-07 1.318E-08

Predator (TL-IV) 1.317E-09 2.190E-04 5.772E-05 3.575E-03 1.077E-02 1.296E-03 9.152E-04 0.000E+00 1.176E-06 1.729E-08

Tissue Conc. (mg/kg-WW) Mono Di Tri Tetra Penta Hexa Hepta Octa Nona Deca Total PCB

Pelagic Community

Phytoplankton (TL1) 1.442E-14 3.819E-10 3.073E-11 4.983E-10 6.545E-10 2.618E-11 1.072E-11 0.000E+00 4.831E-15 1.730E-17 1.602E-09

Zooplankton (TL-II) 3.007E-10 1.117E-05 1.127E-06 2.126E-05 2.109E-05 3.017E-06 2.684E-06 0.000E+00 1.346E-08 1.989E-09 6.036E-05

Planktivore (TL-III) 9.043E-11 1.258E-05 2.294E-06 8.391E-05 1.495E-04 2.353E-05 2.041E-05 0.000E+00 6.753E-08 3.555E-09 2.923E-04

Piscivore (TL-IV) 2.364E-11 2.218E-06 6.091E-07 4.901E-05 2.621E-04 7.057E-05 6.900E-05 0.000E+00 2.016E-07 4.396E-09 4.537E-04

Reef / Vessel Community

Attached Algae 4.150E-11 1.117E-06 9.453E-08 1.571E-06 2.474E-06 2.406E-07 1.519E-07 0.000E+00 3.418E-10 1.528E-11 5.649E-06

Sessile filter feeder (TL-II) 7.297E-10 2.461E-05 2.431E-06 4.571E-05 4.425E-05 3.919E-06 2.838E-06 0.000E+00 9.084E-09 9.857E-10 1.238E-04

Invertebrate Omnivore (TL-II) 1.509E-08 1.171E-03 1.729E-04 5.561E-03 8.973E-03 6.330E-04 3.312E-04 0.000E+00 2.273E-07 2.944E-09 1.684E-02

Invertebrate Forager (TL-III) 5.224E-08 2.131E-03 3.173E-04 1.070E-02 2.041E-02 1.611E-03 8.923E-04 0.000E+00 9.787E-07 6.442E-08 3.606E-02

Vertebrate Forager (TL-III) 1.413E-08 9.913E-04 2.130E-04 1.247E-02 4.432E-02 4.478E-03 2.612E-03 0.000E+00 2.923E-06 9.671E-08 6.509E-02

Predator (TL-IV) 7.825E-09 5.083E-04 1.201E-04 1.047E-02 8.075E-02 1.235E-02 7.909E-03 0.000E+00 8.499E-06 1.879E-07 1.121E-01

Benthic Community

Infaunal invert. (TL-II) 1.965E-10 7.718E-06 8.022E-07 1.587E-05 1.593E-05 1.458E-06 1.066E-06 0.000E+00 2.974E-09 2.119E-10 4.285E-05

Epifaunal invert. (TL-II) 2.742E-10 1.615E-05 1.926E-06 4.359E-05 4.804E-05 4.604E-06 3.399E-06 0.000E+00 8.539E-09 4.682E-10 1.177E-04

Forager (TL-III) 3.550E-10 1.960E-05 2.998E-06 9.058E-05 1.350E-04 1.262E-05 8.600E-06 0.000E+00 1.371E-08 3.145E-10 2.694E-04

Predator (TL-IV) 7.241E-11 1.204E-05 3.175E-06 1.966E-04 5.925E-04 7.128E-05 5.034E-05 0.000E+00 6.471E-08 9.512E-10 9.260E-04

BAFs (L/kg-lipid) Mono Di Tri Tetra Penta Hexa Hepta Octa Nona Deca

Pelagic Community

Phytoplankton (TL1) 2.979E+04 1.000E+05 1.000E+05 1.000E+05 1.000E+05 1.000E+05 1.000E+05 0.000E+00 1.000E+05 1.000E+05

Zooplankton (TL-II) 1.347E+05 6.238E+05 7.437E+05 8.446E+05 5.320E+05 7.827E+05 1.103E+06 0.000E+00 2.458E+06 8.127E+06

Planktivore (TL-III) 7.603E+04 1.319E+06 2.843E+06 6.257E+06 7.083E+06 1.146E+07 1.575E+07 0.000E+00 2.317E+07 2.729E+07

Piscivore (TL-IV) 1.988E+04 2.326E+05 7.548E+05 3.655E+06 1.242E+07 3.439E+07 5.326E+07 0.000E+00 6.917E+07 3.375E+07

Reef / Vessel Community

Attached Algae 2.979E+04 1.000E+05 1.000E+05 1.000E+05 1.000E+05 1.000E+05 1.000E+05 0.000E+00 1.000E+05 1.000E+05

Sessile filter feeder (TL-II) 9.590E+05 4.034E+06 4.709E+06 5.328E+06 3.276E+06 2.983E+06 3.420E+06 0.000E+00 4.867E+06 1.181E+07

Invertebrate Omnivore (TL-II) 3.225E+04 3.121E+05 5.447E+05 1.054E+06 1.080E+06 7.834E+05 6.492E+05 0.000E+00 1.981E+05 5.738E+04

Invertebrate Forager (TL-III) 1.633E+05 8.307E+05 1.462E+06 2.966E+06 3.593E+06 2.916E+06 2.558E+06 0.000E+00 1.247E+06 1.836E+06

Vertebrate Forager (TL-III) 1.501E+04 1.313E+05 3.334E+05 1.175E+06 2.651E+06 2.754E+06 2.544E+06 0.000E+00 1.266E+06 9.366E+05

Predator (TL-IV) 1.243E+04 1.007E+05 2.810E+05 1.474E+06 7.223E+06 1.136E+07 1.152E+07 0.000E+00 5.503E+06 2.721E+06

Benthic Community

Infaunal invert. (TL-II) 2.429E+05 1.190E+06 1.462E+06 1.740E+06 1.109E+06 1.044E+06 1.208E+06 0.000E+00 1.499E+06 2.389E+06

Epifaunal invert. (TL-II) 3.013E+05 2.213E+06 3.119E+06 4.248E+06 2.973E+06 2.930E+06 3.425E+06 0.000E+00 3.825E+06 4.691E+06

Forager (TL-III) 1.759E+05 1.212E+06 2.189E+06 3.981E+06 3.768E+06 3.622E+06 3.909E+06 0.000E+00 2.770E+06 1.421E+06

Predator (TL-IV) 1.557E+04 3.231E+05 1.006E+06 3.750E+06 7.177E+06 8.877E+06 9.928E+06 0.000E+00 5.673E+06 1.865E+06

Notes:

Kow = octanol to water partitioning coefficient, Koc = organic carbon partitioning coefficient, Kdoc = dissolved organic carbon partitioning coefficient

TL = trophic level, ww = wet weight

Energy Estimates for Suspended Sediment and Bedded Sediment

PRAM 1.3 Supplemental Information

1/23/2006 11:00 PM

Based on NEHC PRAM Version 1.3

May 2004 Page 9 of 25
ZOI = 4

RISK ESTIMATES RME CTE RME CTE RME CTE RME CTE

Benthic fish (flounder) 4.81E-08 3.73E-09 2.81E-03 6.44E-04 1.41E-08 2.86E-09 4.12E-03 7.42E-04

Benthic shellfish (lobster) 1.40E-08 1.08E-09 8.16E-04 1.87E-04 4.11E-09 8.33E-10 1.20E-03 2.16E-04

Pelagic fish (jack) 2.36E-08 1.83E-09 1.38E-03 3.16E-04 6.92E-09 1.40E-09 2.02E-03 3.64E-04

Reef fish TL-IV (grouper) 6.87E-06 5.32E-07 4.01E-01 9.20E-02 2.02E-06 4.09E-07 5.88E-01 1.06E-01

Reef fish TL-III (triggerfish) 3.99E-06 3.09E-07 2.33E-01 5.34E-02 1.17E-06 2.37E-07 3.41E-01 6.16E-02

Reef shellfish (crab) 2.21E-06 1.71E-07 1.29E-01 2.96E-02 6.49E-07 1.32E-07 1.89E-01 3.41E-02

PREDICTED EXPOSURE CONCENTRATIONS (mg/kg in fresh weight)

Benthic fish (flounder) 7.82E-04

Benthic shellfish (lobster) 2.28E-04

Pelagic fish (jack) 3.83E-04

Reef fish TL-IV (grouper) 1.12E-01

Reef fish TL-III (triggerfish) 6.49E-02

Reef shellfish (crab) 3.60E-02

RISK INPUTS - Adult RME CTE RISK INPUTS - Child RME CTE

Body Weight (BWc) (kg) 70 70 Body Weight (BWc) (kg) 15 15

Ingestion Rate (IRc) (kg/day) 0.0261 0.0072 Ingestion Rate (IRc) (kg/day) 0.0092916 0.0025632

Exposure Duration (EDc) (years) 24 3 Exposure Duration (EDc) (years) 6 6

Exposure Frequency (EFc) (days) 365 365 Exposure Frequency (EFc) (days) 365 365

Averaging Time for cancer (ATc) 25550 25550 Averaging Time for cancer (ATc) 25550 25550

Slope Factor (mg/kg-day) 2 1 Slope Factor (mg/kg-day) 2 1

Reference dose for PCBs (RfD) (mg/kg-day) 0.00002 0.000045 Reference dose for PCBs (RfD) (mg/kg-day) 0.00002 0.000045

Averaging Time for noncancer (ATnc-child) 8.76E+03 1.10E+03 Averaging Time for noncancer (ATnc-child) 2.19E+03 2.19E+03

Fractional Ingestion factor (FI) 0.17 0.25 Fractional Ingestion factor (FI) 0.17 0.25

Child - Adult IR scaling factor

Zone of Influence Multiplier 4

Scenario run on

PCB-LADEN MATERIAL INPUTS Fraction Release kg Material PCB Release Ex-Oriskany CV34

PCB Rate (ng/g-d) Onboard (ng/day) Ex-Oriskany CV34 27100

Ventilation Gaskets 3.14E-05 1.58E+03 1.46E+03 7.23E+04 Length (ft) 888

Lubricants 1.03E-04 2.20E+03 0.00E+00 0.00E+00 Beam (ft) 120

Foam Rubber Material 0.76% 2.62E+00 0.00E+00 0.00E+00

Black Rubber Material 5.29E-05 1.58E+03 5.40E+03 4.50E+05

Electrical Cable 1.85E-03 2.79E+02 2.96E+05 1.53E+08

Bulkhead Insulation Material 5.37E-04 6.76E+04 1.44E+04 5.22E+08

Aluminum Paint 2.00E-05 1.11E+04 3.87E+05 8.62E+07

Total 7.62E+08

ZOI = 4

3.11E+04 m2

1.20E-02 mile2

A 1.00E+01 m

B 1.50E+01 m

C 5.00E+01 m

D 1.00E-01 m

E 3.48E+02 m

F 1.14E+02 m

Air Column

Air 3.11E+05 m3

Upper Water Column

Water 4.67E+05 m3

TSS 3.11E+00 m3

Lower Water Column

Water 1.50E+06 m3

TSS 1.00E+01 m3

Inside Vessel

Water 5.38E+04 m3

TSS 3.59E-01 m3

Sediment Bed

Sediment 2.33E+03 m3

Abiotic Inputs Total PCB concentrations

Air Column Air Column

Active air space height above water column (m) 10 Air 8.81E-17 g/m3

Air current (m/h) 13677 Upper Water Column

Upper Water Column Freely dissolved in water 9.48E-13 mg/L

Temperature (oC) 24.5 Suspended solids 1.24E-08 mg/kg

Water depth (m) 15 Dissolved organic carbon 1.66E-07 mg/kg

Total suspended solids (mg/L) 10 Lower Water Column

Dissolved organic carbon (mg/L) 0.6 Freely dissolved in water 2.89E-09 mg/L

Dissolved oxygen (mg/L) 6.12 Suspended solids 7.12E-05 mg/kg

Lower Water Column Dissolved organic carbon 6.52E-04 mg/kg

Temperature (oC) 19.5 Inside Vessel

Water depth (m) 50 Freely dissolved in water 1.80E-06 mg/L

Total suspended solids (mg/L) 10 Suspended solids 4.44E-02 mg/kg

Dissolved organic carbon (mg/L) 0.6 Dissolved organic carbon 4.06E-01 mg/kg

Dissolved oxygen (mg/L) 4.59 Sediment Bed

Inside Vessel Freely dissolved in pore water 2.89E-09 mg/L

Temperature (oC) 19.5 Bedded sediment 4.75E-06 mg/kg

Total suspended solids (mg/L) 10 Dissolved organic carbon in pore water 6.52E-04 mg/kg

Dissolved organic carbon (mg/L) 0.6 Total PCB concentrations in biota

Dissolved oxygen (mg/L) 4.59 Pelagic Community Upper WC Lower WC

Sediment Bed Phytoplankton (TL-I) 1.56E-09 mg/kg 100% 0%

Sediment density (g/cm3) 1.5 Zooplankton (TL-II) 5.10E-05 mg/kg 50% 50%

Active sediment depth (m) 0.1 Planktivore (TL-III) 2.47E-04 mg/kg 80% 20%

Sediment fraction organic carbon 0.01 Piscivore (TL-IV) 3.83E-04 mg/kg 80% 20%

All Regions Reef / Vessel Community Lower WC Vessel Int.

Suspended solids density (g/cm3) 1.5 Attached Algae (TL-I) 4.77E-06 mg/kg 100% 0%

Suspended solids fraction organic carbon 0.15 Sessile filter feeder (TL-II) 1.05E-04 mg/kg 100% 0%

Dissolved organic carbon density (g/cm3) 1 Invertebrate Omnivore (TL-II) 1.68E-02 mg/kg 80% 20%

Water current - to out of the ZOI (m/h) 926 Invertebrate Forager (TL-III) 3.60E-02 mg/kg 70% 30%

Water current - inside to outside the vessel (m/h) 9.26 Vertebrate Forager (TL-III) 6.49E-02 mg/kg 70% 30%

Predator (TL-IV) 1.12E-01 mg/kg 80% 20%

Benthic Community Lower WC Pore Water

Infaunal invert. (TL-II) 3.62E-05 mg/kg 20% 80%

Epifaunal invert. (TL-II) 9.94E-05 mg/kg 50% 50%

Forager (TL-III) 2.28E-04 mg/kg 75% 25%

Predator (TL-IV) 7.82E-04 mg/kg 90% 10%

Percent Exposures

Spatial Footprint on Ocean Floor

RISK ESTIMATES FOR Ex-Oriskany CV34

Volumes

Cancer Risk Adult & Child Hazard Adult & Child Cancer Risk Child Hazard Child

0.356

PCB MODELING RESULTS - PROSPECTIVE RISK EVALUATION 

Modeled Dimensions

Outside the Vessel

6/1/05 12:02

A

C

D

E E

E

VESSEL

B

Pycnocline

A

C

D

E E

E

VESSEL

B

Pycnocline

F_Xappdx_2b.xls B2.4_zoi4_Estimate

1/23/2006 11:00 PM

Based on NEHC PRAM Version 1.4

May 2005 Page 10 of 25
Scenario Run on 

ZOI+4

PCB Homolog Mono Di Tri Tetra Penta Hexa Hepta Octa Nona Deca

Molecular Weight (g/mol) 1.89E+02 2.23E+02 2.58E+02 2.92E+02 3.26E+02 3.61E+02 3.95E+02 4.30E+02 4.64E+02 4.99E+02

Solubility (mg/L) 2.91E+00 6.78E-01 8.14E-02 6.67E-02 2.61E-02 9.50E-04 2.30E-04 2.11E-08 4.02E-09 1.69E-10

Solubility (mol/m3

) 1.54E-02 3.04E-03 3.16E-04 2.28E-04 8.00E-05 2.63E-06 5.82E-07 4.91E-11 8.65E-12 3.38E-13

Vapor Pressure (Pa) 6.32E-01 1.41E-01 5.11E-02 2.08E-02 2.96E-03 3.43E-03 2.56E-04 8.65E-05 2.77E-05 1.41E-05

Henry's (Pa-m3

/mol) 4.10E+01 4.65E+01 1.62E+02 9.10E+01 3.70E+01 1.30E+03 4.40E+02 1.76E+06 3.20E+06 4.18E+07

log10Kow = 4.47 5.24 5.52 5.92 6.50 6.98 7.19 7.70 8.35 9.60

log10Koc = 3.66 4.06 4.63 4.65 4.94 6.08 6.34 6.46 6.97 7.94

log10Kdoc = 3.34 4.11 4.39 4.79 5.51 5.85 6.06 6.57 7.22 8.47

Chemical emission rate (g/day) 1.37E-05 1.12E-01 9.95E-03 1.69E-01 3.20E-01 7.57E-02 7.37E-02 0.00E+00 8.28E-04 4.62E-04

Chemical emission rate (mol/hr) 3.03E-09 2.09E-05 1.61E-06 2.42E-05 4.08E-05 8.74E-06 7.77E-06 0.00E+00 7.43E-08 3.86E-08

Biodegradation in sediment (1/hr) 0 0 0 0 0 0 0 000

Biodegradation in water (1/hr) 0 0 0 0 0 0 0 000

Ventilation 

Gaskets Lubricants Foam Rubber 

Material

Black Rubber 

Material

Electrical 

Cable

Bulkhead 

Insulation 

Material

Aluminized 

Paint

Fraction PCB in Material (wt/wt) 0.0000314 0.000103 0.76% 0.0000529 0.00185 0.000537 0.00002

Material Mass Onboard (kg) 1459 0 0 5397 296419 14379 386528

Total PCBs (kg) 0.0458126 0 0 0.2855013 548.37515 7.721523 7.73056

Total PCB Release rate (ng/g-PCB per day) 1.58E+03 2.20E+03 2.62E+00 1.58E+03 2.79E+02 6.76E+04 1.11E+04

Ventilation 

Gaskets Lubricants Foam Rubber Material

Black Rubber 

Material

Electrical 

Cable

Bulkhead 

Insulation 

Material

Aluminized 

Paint

Monochlorobiphenyl 4.14E+01 3.47E+01 0.00E+00 4.14E+01 0.00E+00 0.00E+00 0.00E+00

Dichlorobiphenyl 1.27E+03 1.72E+02 3.08E-02 1.27E+03 2.03E+02 5.36E+00 0.00E+00

Trichlorobiphenyl 5.66E+01 8.97E+01 7.63E-02 5.66E+01 1.14E+00 9.44E+02 2.61E+02

Tetrachlorobiphenyl 1.44E+02 1.08E+03 1.29E+00 1.44E+02 1.57E+01 2.07E+04 1.23E+02

Pentachlorobiphenyl 6.31E+01 6.60E+02 3.90E-02 6.31E+01 1.80E+01 3.79E+04 2.24E+03

Hexachlorobiphenyl 0.00E+00 9.42E+01 5.34E-01 0.00E+00 2.41E+01 6.76E+03 1.33E+03

Heptachlorobiphenyl 5.04E+00 7.17E+01 6.46E-01 5.04E+00 1.47E+01 1.30E+03 7.19E+03

Octachlorobiphenyl 0.00E+00 0.00E+00 0.00E+00 0.00E+00 0.00E+00 0.00E+00 0.00E+00

Nonachlorobiphenyl 0.00E+00 0.00E+00 1.72E-03 0.00E+00 1.51E+00 0.00E+00 0.00E+00

Decachlorobiphenyl 0.00E+00 0.00E+00 0.00E+00 0.00E+00 8.43E-01 0.00E+00 0.00E+00

Total 1.58E+03 2.20E+03 2.62E+00 1.58E+03 2.79E+02 6.76E+04 1.11E+04

Release Rates in nanograms PCB per Day Ventilation 

Gaskets Lubricants Foam Rubber 

Material

Black Rubber 

Material

Electrical 

Cable

Bulkhead 

Insulation 

Material

Aluminized 

Paint Total

Monochlorobiphenyl 1.90E+03 0.00E+00 0.00E+00 1.18E+04 0.00E+00 0.00E+00 0.00E+00 1.37E+04

Dichlorobiphenyl 5.80E+04 0.00E+00 0.00E+00 3.62E+05 1.11E+08 4.14E+04 0.00E+00 1.12E+08

Trichlorobiphenyl 2.59E+03 0.00E+00 0.00E+00 1.62E+04 6.25E+05 7.29E+06 2.02E+06 9.95E+06

Tetrachlorobiphenyl 6.60E+03 0.00E+00 0.00E+00 4.11E+04 8.61E+06 1.60E+08 9.51E+05 1.69E+08

Pentachlorobiphenyl 2.89E+03 0.00E+00 0.00E+00 1.80E+04 9.87E+06 2.93E+08 1.73E+07 3.20E+08

Hexachlorobiphenyl 0.00E+00 0.00E+00 0.00E+00 0.00E+00 1.32E+07 5.22E+07 1.03E+07 7.57E+07

Heptachlorobiphenyl 2.31E+02 0.00E+00 0.00E+00 1.44E+03 8.06E+06 1.01E+07 5.56E+07 7.37E+07

Octachlorobiphenyl 0.00E+00 0.00E+00 0.00E+00 0.00E+00 0.00E+00 0.00E+00 0.00E+00 0.00E+00

Nonachlorobiphenyl 0.00E+00 0.00E+00 0.00E+00 0.00E+00 8.28E+05 0.00E+00 0.00E+00 8.28E+05

Decachlorobiphenyl 0.00E+00 0.00E+00 0.00E+00 0.00E+00 4.62E+05 0.00E+00 0.00E+00 4.62E+05

Total 7.23E+04 0.00E+00 0.00E+00 4.50E+05 1.53E+08 5.22E+08 8.62E+07 7.62E+08

Air Mono Di Tri Tetra Penta Hexa Hepta Octa Nona Deca

Fugacity (Pa) 4.24E-20 2.61E-16 1.72E-17 2.30E-16 2.51E-16 8.87E-18 3.16E-18 0.00E+00 1.12E-21 3.61E-24

Air concentration (g/m3) 3.26E-21 2.37E-17 1.80E-18 2.73E-17 3.34E-17 1.30E-18 5.09E-19 0.00E+00 2.12E-22 7.33E-25

Upper Water Column Mono Di Tri Tetra Penta Hexa Hepta Octa Nona Deca

Fugacity (Pa) 6.23E-18 4.71E-14 1.14E-14 9.19E-14 4.40E-14 5.60E-14 7.07E-15 0.00E+00 1.97E-14 8.59E-16

Water concentration (mg/L) 2.86E-17 2.26E-13 1.82E-14 2.95E-13 3.87E-13 1.55E-14 6.34E-15 0.00E+00 2.86E-18 1.02E-20

Suspended solids concentration (mg/kg) 1.98E-14 3.87E-10 1.15E-10 2.00E-09 5.00E-09 2.79E-09 2.08E-09 0.00E+00 3.96E-12 1.34E-13

Dissolved organic carbon (mg/kg) 6.31E-14 2.88E-09 4.47E-10 1.82E-08 1.26E-07 1.08E-08 7.27E-09 0.00E+00 4.75E-11 3.04E-12

Lower Water Column Mono Di Tri Tetra Penta Hexa Hepta Octa Nona Deca

Fugacity (Pa) 1.55E-14 1.19E-10 3.04E-11 2.51E-10 1.44E-10 4.45E-10 8.67E-11 0.00E+00 1.21E-09 6.57E-10

Water concentration (mg/L) 7.14E-14 5.72E-10 4.84E-11 8.05E-10 1.27E-09 1.23E-10 7.78E-11 0.00E+00 1.75E-13 7.83E-15

Suspended solids concentration (mg/kg) 4.93E-11 9.80E-07 3.06E-07 5.45E-06 1.64E-05 2.22E-05 2.55E-05 0.00E+00 2.43E-07 1.02E-07

Dissolved organic carbon (mg/kg) 1.57E-10 7.29E-06 1.19E-06 4.98E-05 4.13E-04 8.64E-05 8.92E-05 0.00E+00 2.91E-06 2.32E-06

Inside the Vessel Mono Di Tri Tetra Penta Hexa Hepta Octa Nona Deca

Fugacity (Pa) 9.67E-12 7.43E-08 1.89E-08 1.56E-07 8.96E-08 2.77E-07 5.40E-08 0.00E+00 7.51E-07 4.09E-07

Water concentration (mg/L) 4.45E-11 3.57E-07 3.02E-08 5.02E-07 7.90E-07 7.68E-08 4.85E-08 0.00E+00 1.09E-10 4.88E-12

Suspended solids concentration (mg/kg) 3.07E-08 6.11E-04 1.91E-04 3.39E-03 1.02E-02 1.39E-02 1.59E-02 0.00E+00 1.51E-04 6.38E-05

Dissolved organic carbon (mg/kg) 9.80E-08 4.54E-03 7.41E-04 3.10E-02 2.57E-01 5.38E-02 5.56E-02 0.00E+00 1.81E-03 1.45E-03

Sediment Bed Mono Di Tri Tetra Penta Hexa Hepta Octa Nona Deca

Fugacity (Pa) 1.55E-14 1.19E-10 3.04E-11 2.51E-10 1.44E-10 4.45E-10 8.67E-11 0.00E+00 1.21E-09 6.57E-10

Pore Water concentration (mg/L) 7.14E-14 5.72E-10 4.84E-11 8.05E-10 1.27E-09 1.23E-10 7.78E-11 0.00E+00 1.75E-13 7.83E-15

Sediment concentration (mg/kg) 3.29E-12 6.53E-08 2.04E-08 3.63E-07 1.09E-06 1.48E-06 1.70E-06 0.00E+00 1.62E-08 6.83E-09

Bioenergetic Inputs

Species Body Weight Lipid Moisture Caloric 

Density GE to ME Met Energy Caloric 

Density Production Respiration Excretion Caloric 

Density Met Energy

(kg) (%-dw) (%) (kcal/g-dry 

weight) Fraction (kcal/kg-lipid) (kcal/kg-lipid) (% of total) (% of total) (% of total) (kcal/g-wt 

weight)

 (kcal/g-wt 

weight)

Pelagic Community

Phytoplankton (TL-I) Algae 10% 84% 2.36 0.6 13748 22913 0.3776 0.22656

Zooplankton (TL-II) copepods 0.000005 22% 76% 3.6 0.65 10636 16364 18% 24% 58% 0.864 0.5616

Planktivore (TL-III) herring 0.05 28% 75% 4.9 0.7 12206 17438 20% 60% 20% 1.225 0.8575

Piscivore (TL-IV) jack 0.5 28% 75% 4.9 0.7 12206 17438 20% 60% 20% 1.225 0.8575

Reef / Vessel Community

Attached Algae (TL-I) Algae 10% 84% 2.36 0.6 13748 22913 0.3776 0.22656

Sessile filter feeder (TL-II) bivalves (w/o shell) 0.05 5% 82% 4.6 0.65 59800 92000 28% 31% 41% 0.828 0.5382

Invertebrate Omnivore (TL-II) urchin 0.05 29% 82% 4.6 0.65 10310 15862 7% 25% 68% 0.828 0.5382

Invertebrate Forager (TL-III) crab 1 9% 74% 2.7 0.65 19118 29412 28% 59% 13% 0.702 0.4563

Vertebrate Forager (TL-III) triggerfish 1 28% 75% 4.9 0.7 12206 17438 20% 60% 20% 1.225 0.8575

Predator (TL-IV) grouper 1.5 28% 75% 4.9 0.7 12206 17438 20% 60% 20% 0.2 0.14

Benthic Community

Infaunal invert. (TL-II) polychaete 0.01 6% 84% 4.6 0.65 50000 76923 71% 26% 3% 0.736 0.4784

Epifaunal invert. (TL-II) nematode 0.01 6% 82% 4.6 0.65 50000 76923 31% 19% 50% 0.828 0.5382

Forager (TL-III) lobster 2 9% 74% 2.7 0.65 19118 29412 28% 59% 13% 0.702 0.4563

Predator (TL-IV) flounder 3 22% 75% 4.9 0.7 15591 22273 20% 60% 20% 1.225 0.8575

Bioenergetic Inputs Resp. Rate Resp. Rate Consumption Growth Rate Consumption Consumption

1 gO2 kcal 1 g-wt weight kcal As a % of

Pelagic Community day kg-lipid-day kg-lipid-day day g-wt weight-d-wet weight-da body weight

Phytoplankton (TL1) Algae

Zooplankton (TL-II) copepods 0.006375522 0 0.039935335 0.015425453 84.24400867 1286.168071 0.014147849 0.32636028 0.06790967 32.6%

Planktivore (TL-III) herring 0.0033 -0.227 0.0548 0.004949927 21.1649 129.2512977 0.001482433 0.01616792 0.0090799 1.6%

Piscivore (TL-IV) jack 0.001118602 -0.55 0.12 0.000630951 2.697821256 16.47524431 0.000188961 0.00139796 0.00115739 0.1%

Reef / Vessel Community

Attached Algae Algae

Sessile filter feeder (TL-II) bivalves (w/o shell) 0.012 0 0.036 0.024213411 581.8482643 6877.300342 0.020930914 0.24377539 0.0618957 24.4%

Invertibrate Omnivore (TL-II) urchin 0.000675466 0 0.079181846 0.003163548 13.1069075 192.1012396 0.000847751 0.03471132 0.01002768 3.5%

Invertibrate Forager (TL-III) crab 0.001158234 0 0.071193202 0.004642088 60.75673491 377.3221989 0.003592107 0.01678102 0.00900593 1.7%

Vertibrate Forager (TL-III) triggerfish 0.015181024 -0.415 0.061 0.002837229 12.13142452 74.08503521 0.00084971 0.00907693 0.00520447 0.9%

Predator (TL-IV) grouper 0.00279 -0.355 0.0811 0.001011362 4.324384181 26.40845301 0.000302889 0.00264734 0.00185519 0.3%

Benthic Community

Infaunal invert. (TL-II) polychaete 0.001682129 0 0.071034762 0.006721006 135.0382801 1903.064429 0.017565285 0.09800757 0.01820852 9.8%

Epifaunal invert. (TL-II) nematode 0.001682129 0 0.071034762 0.006721006 135.0382801 2604.19343 0.0104949 0.09262416 0.02803154 9.3%

Forager (TL-III) lobster 0.0035 -0.13 0.066 0.00471923 61.76639253 383.5925529 0.003651801 0.01899736 0.00915559 1.9%

Predator (TL-IV) flounder 0.0046 -0.24 0.067 0.002486878 13.58174479 82.94195291 0.000744785 0.00974341 0.00456181 1.0%

PCB MODELING RESULTS - PROSPECTIVE RISK EVALUATION 

RISK ESTIMATES FOR Ex-Oriskany CV34

Supplemental Information

Release Rates in nanograms PCB per gram of PCB within the Material

Respiration Rate Allometric Regression Parameters

a b1 b2

6/1/05 12:02

PRAM 1.3 Supplemental Information

1/23/2006 11:00 PM

Based on NEHC PRAM Version 1.3

May 2004 Page 11 of 25
PCB MODELING RESULTS - PROSPECTIVE RISK EVALUATION 

RISK ESTIMATES FOR Ex-Oriskany CV34

Supplemental Information

Dietary Preferences

Suspended Solids

(Epilimnion)

Suspended 

Solids

(Hypolimnion)

Sediment Phytoplankton Zooplankton Pelagic 

Plankitivore

Attached 

Algae

Reef Sessile 

Filter Feeder

Invertebrate 

Omnivore

Reef

Invertebrate

Forager

Reef

Vertebrate

Forager

Infaunal 

Benthos

Epifaunal 

Benthos

Benthic 

Forager

Pelagic Community

Phytoplankton (TL1)

Zooplankton (TL-II) 15% 15% 70%

Planktivore (TL-III) 100%

Piscivore (TL-IV) 10% 90%

Reef / Vessel Community

Attached Algae

Sessile filter feeder (TL-II) 10% 80% 10%

Invertebrate Omnivore (TL-II) 80% 20%

Invertebrate Forager (TL-III) 5% 5% 5% 35% 50%

Vertebrate Forager (TL-III) 19% 19% 15% 22% 12.5% 12.5%

Predator (TL-IV) 15% 60% 8% 8% 8%

Benthic Community

Infaunal invert. (TL-II) 50% 30% 20%

Epifaunal invert. (TL-II) 25% 30% 20% 25%

Forager (TL-III) 5% 50% 45%

Predator (TL-IV) 2% 20% 20% 58%

Water Exposures

Upper Water 

Column

Lower Water

Column Vessel Interior Sediment PoreWater GE ME ME as kcal/g-ww

Pelagic Community Sediment (kcal/kg-oc) 11456 6873.6 0.6 0.01099776

Phytoplankton (TL1) Algae 100% Suspended Sediment (kcal/kg-oc) 11456 6873.6 0.6 0.1649664

Zooplankton (TL-II) copepods 50% 50%

Planktivore (TL-III) herring 80% 20%

Piscivore (TL-IV) jack 80% 20%

Reef / Vessel Community

Attached Algae Algae 100%

Sessile filter feeder (TL-II) bivalves (w/o shell) 100%

Invertebrate Omnivore (TL-II) urchin 80% 20%

Invertebrate Forager (TL-III) crab 70% 30%

Vertebrate Forager (TL-III) triggerfish 70% 30%

Predator (TL-IV) grouper 80% 20%

Benthic Community

Infaunal invert. (TL-II) polychaete 20% 80%

Epifaunal invert. (TL-II) nematode 50% 50%

Forager (TL-III) lobster 75% 25%

Predator (TL-IV) flounder 90% 10%

Respiratory Efficiencies Mono Di Tri Tetra Penta Hexa Hepta Octa Nona Deca

Low body weight (<100g) 4.335E-01 8.000E-01 8.000E-01 8.000E-01 4.492E-01 2.582E-01 2.018E-01 1.127E-01 5.303E-02 1.255E-02

High body weight (>100g) 5.000E-01 5.000E-01 5.000E-01 5.000E-01 3.769E-01 2.857E-01 2.526E-01 1.888E-01 1.295E-01 6.299E-02

Dietary Assimilation Efficiencies 27% 46% 53% 62% 69% 69% 68% 59% 44% 16%

Tissue Conc. (mg/kg-lipid) Mono Di Tri Tetra Penta Hexa Hepta Octa Nona Deca

Pelagic Community

Phytoplankton (TL1) 8.531E-13 2.260E-08 1.818E-09 2.948E-08 3.872E-08 1.549E-09 6.345E-10 0.000E+00 2.859E-13 1.024E-15

Zooplankton (TL-II) 4.810E-09 1.786E-04 1.802E-05 3.401E-04 3.373E-04 4.826E-05 4.293E-05 0.000E+00 2.153E-07 3.182E-08

Planktivore (TL-III) 1.087E-09 1.513E-04 2.758E-05 1.009E-03 1.798E-03 2.828E-04 2.454E-04 0.000E+00 8.118E-07 4.273E-08

Piscivore (TL-IV) 2.843E-10 2.667E-05 7.323E-06 5.893E-04 3.151E-03 8.484E-04 8.295E-04 0.000E+00 2.423E-06 5.285E-08

Reef / Vessel Community

Attached Algae 2.126E-09 5.724E-05 4.844E-06 8.050E-05 1.268E-04 1.233E-05 7.785E-06 0.000E+00 1.751E-08 7.830E-10

Sessile filter feeder (TL-II) 6.847E-08 2.309E-03 2.281E-04 4.289E-03 4.153E-03 3.678E-04 2.663E-04 0.000E+00 8.524E-07 9.249E-08

Invertebrate Omnivore (TL-II) 2.886E-07 2.238E-02 3.304E-03 1.062E-01 1.713E-01 1.206E-02 6.303E-03 0.000E+00 4.280E-06 5.404E-08

Invertebrate Forager (TL-III) 2.187E-06 8.913E-02 1.327E-02 4.471E-01 8.523E-01 6.720E-02 3.719E-02 0.000E+00 4.074E-05 2.693E-06

Vertebrate Forager (TL-III) 2.010E-07 1.408E-02 3.024E-03 1.770E-01 6.287E-01 6.345E-02 3.696E-02 0.000E+00 4.131E-05 1.372E-06

Predator (TL-IV) 1.113E-07 7.224E-03 1.705E-03 1.486E-01 1.146E+00 1.750E-01 1.120E-01 0.000E+00 1.203E-04 2.668E-06

Benthic Community

Infaunal invert. (TL-II) 1.734E-08 6.813E-04 7.080E-05 1.401E-03 1.406E-03 1.287E-04 9.406E-05 0.000E+00 2.625E-07 1.871E-08

Epifaunal invert. (TL-II) 2.151E-08 1.267E-03 1.511E-04 3.420E-03 3.769E-03 3.612E-04 2.667E-04 0.000E+00 6.699E-07 3.673E-08

Forager (TL-III) 1.256E-08 6.936E-04 1.061E-04 3.205E-03 4.776E-03 4.466E-04 3.043E-04 0.000E+00 4.851E-07 1.113E-08

Predator (TL-IV) 1.112E-09 1.849E-04 4.875E-05 3.019E-03 9.098E-03 1.095E-03 7.729E-04 0.000E+00 9.936E-07 1.461E-08

Tissue Conc. (mg/kg-WW) Mono Di Tri Tetra Penta Hexa Hepta Octa Nona Deca Total PCB

Pelagic Community

Phytoplankton (TL1) 1.406E-14 3.724E-10 2.996E-11 4.859E-10 6.382E-10 2.552E-11 1.046E-11 0.000E+00 4.711E-15 1.687E-17 1.562E-09

Zooplankton (TL-II) 2.540E-10 9.431E-06 9.514E-07 1.796E-05 1.781E-05 2.548E-06 2.267E-06 0.000E+00 1.137E-08 1.680E-09 5.098E-05

Planktivore (TL-III) 7.638E-11 1.063E-05 1.938E-06 7.087E-05 1.263E-04 1.987E-05 1.724E-05 0.000E+00 5.703E-08 3.002E-09 2.469E-04

Piscivore (TL-IV) 1.997E-11 1.873E-06 5.144E-07 4.140E-05 2.214E-04 5.960E-05 5.827E-05 0.000E+00 1.702E-07 3.713E-09 3.832E-04

Reef / Vessel Community

Attached Algae 3.504E-11 9.434E-07 7.983E-08 1.327E-06 2.089E-06 2.032E-07 1.283E-07 0.000E+00 2.886E-10 1.290E-11 4.771E-06

Sessile filter feeder (TL-II) 6.162E-10 2.078E-05 2.053E-06 3.860E-05 3.737E-05 3.310E-06 2.397E-06 0.000E+00 7.672E-09 8.324E-10 1.045E-04

Invertebrate Omnivore (TL-II) 1.507E-08 1.168E-03 1.725E-04 5.545E-03 8.940E-03 6.297E-04 3.290E-04 0.000E+00 2.234E-07 2.821E-09 1.678E-02

Invertebrate Forager (TL-III) 5.220E-08 2.127E-03 3.167E-04 1.067E-02 2.034E-02 1.604E-03 8.878E-04 0.000E+00 9.723E-07 6.427E-08 3.595E-02

Vertebrate Forager (TL-III) 1.412E-08 9.894E-04 2.125E-04 1.243E-02 4.416E-02 4.458E-03 2.597E-03 0.000E+00 2.902E-06 9.637E-08 6.486E-02

Predator (TL-IV) 7.815E-09 5.075E-04 1.198E-04 1.044E-02 8.048E-02 1.229E-02 7.868E-03 0.000E+00 8.451E-06 1.875E-07 1.117E-01

Benthic Community

Infaunal invert. (TL-II) 1.659E-10 6.518E-06 6.774E-07 1.340E-05 1.345E-05 1.231E-06 8.999E-07 0.000E+00 2.512E-09 1.790E-10 3.619E-05

Epifaunal invert. (TL-II) 2.316E-10 1.364E-05 1.626E-06 3.681E-05 4.057E-05 3.888E-06 2.870E-06 0.000E+00 7.211E-09 3.954E-10 9.941E-05

Forager (TL-III) 2.998E-10 1.656E-05 2.531E-06 7.650E-05 1.140E-04 1.066E-05 7.263E-06 0.000E+00 1.158E-08 2.656E-10 2.275E-04

Predator (TL-IV) 6.115E-11 1.017E-05 2.681E-06 1.661E-04 5.004E-04 6.020E-05 4.251E-05 0.000E+00 5.465E-08 8.033E-10 7.821E-04

BAFs (L/kg-lipid) Mono Di Tri Tetra Penta Hexa Hepta Octa Nona Deca

Pelagic Community

Phytoplankton (TL1) 2.979E+04 1.000E+05 1.000E+05 1.000E+05 1.000E+05 1.000E+05 1.000E+05 0.000E+00 1.000E+05 1.000E+05

Zooplankton (TL-II) 1.347E+05 6.238E+05 7.437E+05 8.446E+05 5.320E+05 7.827E+05 1.103E+06 0.000E+00 2.458E+06 8.127E+06

Planktivore (TL-III) 7.602E+04 1.319E+06 2.843E+06 6.256E+06 7.082E+06 1.146E+07 1.575E+07 0.000E+00 2.317E+07 2.729E+07

Piscivore (TL-IV) 1.988E+04 2.325E+05 7.547E+05 3.655E+06 1.241E+07 3.439E+07 5.326E+07 0.000E+00 6.917E+07 3.375E+07

Reef / Vessel Community

Attached Algae 2.979E+04 1.000E+05 1.000E+05 1.000E+05 1.000E+05 1.000E+05 1.000E+05 0.000E+00 1.000E+05 1.000E+05

Sessile filter feeder (TL-II) 9.590E+05 4.034E+06 4.709E+06 5.328E+06 3.276E+06 2.983E+06 3.420E+06 0.000E+00 4.867E+06 1.181E+07

Invertebrate Omnivore (TL-II) 3.224E+04 3.118E+05 5.439E+05 1.052E+06 1.077E+06 7.802E+05 6.457E+05 0.000E+00 1.949E+05 5.504E+04

Invertebrate Forager (TL-III) 1.633E+05 8.300E+05 1.460E+06 2.961E+06 3.584E+06 2.905E+06 2.547E+06 0.000E+00 1.240E+06 1.833E+06

Vertebrate Forager (TL-III) 1.501E+04 1.311E+05 3.328E+05 1.172E+06 2.644E+06 2.744E+06 2.531E+06 0.000E+00 1.258E+06 9.340E+05

Predator (TL-IV) 1.243E+04 1.006E+05 2.807E+05 1.472E+06 7.207E+06 1.132E+07 1.147E+07 0.000E+00 5.478E+06 2.718E+06

Benthic Community

Infaunal invert. (TL-II) 2.429E+05 1.190E+06 1.462E+06 1.740E+06 1.109E+06 1.044E+06 1.208E+06 0.000E+00 1.499E+06 2.389E+06

Epifaunal invert. (TL-II) 3.013E+05 2.213E+06 3.119E+06 4.248E+06 2.973E+06 2.930E+06 3.425E+06 0.000E+00 3.825E+06 4.691E+06

Forager (TL-III) 1.759E+05 1.212E+06 2.189E+06 3.981E+06 3.768E+06 3.622E+06 3.909E+06 0.000E+00 2.770E+06 1.421E+06

Predator (TL-IV) 1.557E+04 3.231E+05 1.006E+06 3.750E+06 7.177E+06 8.878E+06 9.928E+06 0.000E+00 5.673E+06 1.865E+06

Notes:

Kow = octanol to water partitioning coefficient, Koc = organic carbon partitioning coefficient, Kdoc = dissolved organic carbon partitioning coefficient

TL = trophic level, ww = wet weight

Energy Estimates for Suspended Sediment and Bedded Sediment

PRAM 1.3 Supplemental Information

1/23/2006 11:00 PM

Based on NEHC PRAM Version 1.3

May 2004 Page 12 of 25
ZOI = 5

RISK ESTIMATES RME CTE RME CTE RME CTE RME CTE

Benthic fish (flounder) 4.23E-08 3.28E-09 2.47E-03 5.66E-04 1.24E-08 2.52E-09 3.62E-03 6.53E-04

Benthic shellfish (lobster) 1.23E-08 9.53E-10 7.18E-04 1.65E-04 3.61E-09 7.33E-10 1.05E-03 1.90E-04

Pelagic fish (jack) 2.07E-08 1.61E-09 1.21E-03 2.78E-04 6.08E-09 1.23E-09 1.77E-03 3.20E-04

Reef fish TL-IV (grouper) 6.86E-06 5.31E-07 4.00E-01 9.18E-02 2.01E-06 4.08E-07 5.87E-01 1.06E-01

Reef fish TL-III (triggerfish) 3.98E-06 3.08E-07 2.32E-01 5.33E-02 1.17E-06 2.37E-07 3.41E-01 6.14E-02

Reef shellfish (crab) 2.21E-06 1.71E-07 1.29E-01 2.95E-02 6.48E-07 1.31E-07 1.89E-01 3.41E-02

PREDICTED EXPOSURE CONCENTRATIONS (mg/kg in fresh weight)

Benthic fish (flounder) 6.88E-04

Benthic shellfish (lobster) 2.00E-04

Pelagic fish (jack) 3.37E-04

Reef fish TL-IV (grouper) 1.11E-01

Reef fish TL-III (triggerfish) 6.47E-02

Reef shellfish (crab) 3.59E-02

RISK INPUTS - Adult RME CTE RISK INPUTS - Child RME CTE

Body Weight (BWc) (kg) 70 70 Body Weight (BWc) (kg) 15 15

Ingestion Rate (IRc) (kg/day) 0.0261 0.0072 Ingestion Rate (IRc) (kg/day) 0.0092916 0.0025632

Exposure Duration (EDc) (years) 24 3 Exposure Duration (EDc) (years) 6 6

Exposure Frequency (EFc) (days) 365 365 Exposure Frequency (EFc) (days) 365 365

Averaging Time for cancer (ATc) 25550 25550 Averaging Time for cancer (ATc) 25550 25550

Slope Factor (mg/kg-day) 2 1 Slope Factor (mg/kg-day) 2 1

Reference dose for PCBs (RfD) (mg/kg-day) 0.00002 0.000045 Reference dose for PCBs (RfD) (mg/kg-day) 0.00002 0.000045

Averaging Time for noncancer (ATnc-child) 8.76E+03 1.10E+03 Averaging Time for noncancer (ATnc-child) 2.19E+03 2.19E+03

Fractional Ingestion factor (FI) 0.17 0.25 Fractional Ingestion factor (FI) 0.17 0.25

Child - Adult IR scaling factor

Zone of Influence Multiplier 5

Scenario run on

PCB-LADEN MATERIAL INPUTS Fraction Release kg Material PCB Release Ex-Oriskany CV34

PCB Rate (ng/g-d) Onboard (ng/day) Ex-Oriskany CV34 27100

Ventilation Gaskets 3.14E-05 1.58E+03 1.46E+03 7.23E+04 Length (ft) 888

Lubricants 1.03E-04 2.20E+03 0.00E+00 0.00E+00 Beam (ft) 120

Foam Rubber Material 0.76% 2.62E+00 0.00E+00 0.00E+00

Black Rubber Material 5.29E-05 1.58E+03 5.40E+03 4.50E+05

Electrical Cable 1.85E-03 2.79E+02 2.96E+05 1.53E+08

Bulkhead Insulation Material 5.37E-04 6.76E+04 1.44E+04 5.22E+08

Aluminum Paint 2.00E-05 1.11E+04 3.87E+05 8.62E+07

Total 7.62E+08

ZOI = 5

3.89E+04 m2

1.50E-02 mile2

A 1.00E+01 m

B 1.50E+01 m

C 5.00E+01 m

D 1.00E-01 m

E 3.68E+02 m

F 1.34E+02 m

Air Column

Air 3.89E+05 m3

Upper Water Column

Water 5.83E+05 m3

TSS 3.89E+00 m3

Lower Water Column

Water 1.89E+06 m3

TSS 1.26E+01 m3

Inside Vessel

Water 5.38E+04 m3

TSS 3.59E-01 m3

Sediment Bed

Sediment 3.11E+03 m3

Abiotic Inputs Total PCB concentrations

Air Column Air Column

Active air space height above water column (m) 10 Air 9.68E-17 g/m3

Air current (m/h) 13677 Upper Water Column

Upper Water Column Freely dissolved in water 9.32E-13 mg/L

Temperature (oC) 24.5 Suspended solids 1.22E-08 mg/kg

Water depth (m) 15 Dissolved organic carbon 1.63E-07 mg/kg

Total suspended solids (mg/L) 10 Lower Water Column

Dissolved organic carbon (mg/L) 0.6 Freely dissolved in water 2.55E-09 mg/L

Dissolved oxygen (mg/L) 6.12 Suspended solids 6.27E-05 mg/kg

Lower Water Column Dissolved organic carbon 5.74E-04 mg/kg

Temperature (oC) 19.5 Inside Vessel

Water depth (m) 50 Freely dissolved in water 1.80E-06 mg/L

Total suspended solids (mg/L) 10 Suspended solids 4.44E-02 mg/kg

Dissolved organic carbon (mg/L) 0.6 Dissolved organic carbon 4.06E-01 mg/kg

Dissolved oxygen (mg/L) 4.59 Sediment Bed

Inside Vessel Freely dissolved in pore water 2.55E-09 mg/L

Temperature (oC) 19.5 Bedded sediment 4.18E-06 mg/kg

Total suspended solids (mg/L) 10 Dissolved organic carbon in pore water 5.74E-04 mg/kg

Dissolved organic carbon (mg/L) 0.6 Total PCB concentrations in biota

Dissolved oxygen (mg/L) 4.59 Pelagic Community Upper WC Lower WC

Sediment Bed Phytoplankton (TL-I) 1.54E-09 mg/kg 100% 0%

Sediment density (g/cm3) 1.5 Zooplankton (TL-II) 4.48E-05 mg/kg 50% 50%

Active sediment depth (m) 0.1 Planktivore (TL-III) 2.17E-04 mg/kg 80% 20%

Sediment fraction organic carbon 0.01 Piscivore (TL-IV) 3.37E-04 mg/kg 80% 20%

All Regions Reef / Vessel Community Lower WC Vessel Int.

Suspended solids density (g/cm3) 1.5 Attached Algae (TL-I) 4.20E-06 mg/kg 100% 0%

Suspended solids fraction organic carbon 0.15 Sessile filter feeder (TL-II) 9.19E-05 mg/kg 100% 0%

Dissolved organic carbon density (g/cm3) 1 Invertebrate Omnivore (TL-II) 1.67E-02 mg/kg 80% 20%

Water current - to out of the ZOI (m/h) 926 Invertebrate Forager (TL-III) 3.59E-02 mg/kg 70% 30%

Water current - inside to outside the vessel (m/h) 9.26 Vertebrate Forager (TL-III) 6.47E-02 mg/kg 70% 30%

Predator (TL-IV) 1.11E-01 mg/kg 80% 20%

Benthic Community Lower WC Pore Water

Infaunal invert. (TL-II) 3.18E-05 mg/kg 20% 80%

Epifaunal invert. (TL-II) 8.74E-05 mg/kg 50% 50%

Forager (TL-III) 2.00E-04 mg/kg 75% 25%

Predator (TL-IV) 6.88E-04 mg/kg 90% 10%

PCB MODELING RESULTS - PROSPECTIVE RISK EVALUATION 

Modeled Dimensions

Outside the Vessel

5/26/05 8:48

Percent Exposures

Spatial Footprint on Ocean Floor

RISK ESTIMATES FOR Ex-Oriskany CV34

Volumes

Cancer Risk Adult & Child Hazard Adult & Child Cancer Risk Child Hazard Child

0.356

A

C

D

E E

E

VESSEL

B

Pycnocline

A

C

D

E E

E

VESSEL

B

Pycnocline

F_Xappdx_2b.xls B2.5_zoi5_Estimate

1/23/2006 11:00 PM

Based on NEHC PRAM Version 1.4

May 2005 Page 13 of 25
Scenario Run on ZOI = 5

PCB Homolog Mono Di Tri Tetra Penta Hexa Hepta Octa Nona Deca

Molecular Weight (g/mol) 1.89E+02 2.23E+02 2.58E+02 2.92E+02 3.26E+02 3.61E+02 3.95E+02 4.30E+02 4.64E+02 4.99E+02

Solubility (mg/L) 2.91E+00 6.78E-01 8.14E-02 6.67E-02 2.61E-02 9.50E-04 2.30E-04 2.11E-08 4.02E-09 1.69E-10

Solubility (mol/m3

) 1.54E-02 3.04E-03 3.16E-04 2.28E-04 8.00E-05 2.63E-06 5.82E-07 4.91E-11 8.65E-12 3.38E-13

Vapor Pressure (Pa) 6.32E-01 1.41E-01 5.11E-02 2.08E-02 2.96E-03 3.43E-03 2.56E-04 8.65E-05 2.77E-05 1.41E-05

Henry's (Pa-m3

/mol) 4.10E+01 4.65E+01 1.62E+02 9.10E+01 3.70E+01 1.30E+03 4.40E+02 1.76E+06 3.20E+06 4.18E+07

log10Kow = 4.47 5.24 5.52 5.92 6.50 6.98 7.19 7.70 8.35 9.60

log10Koc = 3.66 4.06 4.63 4.65 4.94 6.08 6.34 6.46 6.97 7.94

log10Kdoc = 3.34 4.11 4.39 4.79 5.51 5.85 6.06 6.57 7.22 8.47

Chemical emission rate (g/day) 1.37E-05 1.12E-01 9.95E-03 1.69E-01 3.20E-01 7.57E-02 7.37E-02 0.00E+00 8.28E-04 4.62E-04

Chemical emission rate (mol/hr) 3.03E-09 2.09E-05 1.61E-06 2.42E-05 4.08E-05 8.74E-06 7.77E-06 0.00E+00 7.43E-08 3.86E-08

Biodegradation in sediment (1/hr) 0 0 0 0 0 0 0 000

Biodegradation in water (1/hr) 0 0 0 0 0 0 0 000

Ventilation 

Gaskets Lubricants Foam Rubber 

Material

Black Rubber 

Material

Electrical 

Cable

Bulkhead 

Insulation 

Material

Aluminized 

Paint

Fraction PCB in Material (wt/wt) 0.0000314 0.000103 0.76% 0.0000529 0.00185 0.000537 0.00002

Material Mass Onboard (kg) 1459 0 0 5397 296419 14379 386528

Total PCBs (kg) 0.0458126 0 0 0.2855013 548.37515 7.721523 7.73056

Total PCB Release rate (ng/g-PCB per day) 1.58E+03 2.20E+03 2.62E+00 1.58E+03 2.79E+02 6.76E+04 1.11E+04

Ventilation 

Gaskets Lubricants Foam Rubber Material

Black Rubber 

Material

Electrical 

Cable

Bulkhead 

Insulation 

Material

Aluminized 

Paint

Monochlorobiphenyl 4.14E+01 3.47E+01 0.00E+00 4.14E+01 0.00E+00 0.00E+00 0.00E+00

Dichlorobiphenyl 1.27E+03 1.72E+02 3.08E-02 1.27E+03 2.03E+02 5.36E+00 0.00E+00

Trichlorobiphenyl 5.66E+01 8.97E+01 7.63E-02 5.66E+01 1.14E+00 9.44E+02 2.61E+02

Tetrachlorobiphenyl 1.44E+02 1.08E+03 1.29E+00 1.44E+02 1.57E+01 2.07E+04 1.23E+02

Pentachlorobiphenyl 6.31E+01 6.60E+02 3.90E-02 6.31E+01 1.80E+01 3.79E+04 2.24E+03

Hexachlorobiphenyl 0.00E+00 9.42E+01 5.34E-01 0.00E+00 2.41E+01 6.76E+03 1.33E+03

Heptachlorobiphenyl 5.04E+00 7.17E+01 6.46E-01 5.04E+00 1.47E+01 1.30E+03 7.19E+03

Octachlorobiphenyl 0.00E+00 0.00E+00 0.00E+00 0.00E+00 0.00E+00 0.00E+00 0.00E+00

Nonachlorobiphenyl 0.00E+00 0.00E+00 1.72E-03 0.00E+00 1.51E+00 0.00E+00 0.00E+00

Decachlorobiphenyl 0.00E+00 0.00E+00 0.00E+00 0.00E+00 8.43E-01 0.00E+00 0.00E+00

Total 1.58E+03 2.20E+03 2.62E+00 1.58E+03 2.79E+02 6.76E+04 1.11E+04

Release Rates in nanograms PCB per Day Ventilation 

Gaskets Lubricants Foam Rubber 

Material

Black Rubber 

Material

Electrical 

Cable

Bulkhead 

Insulation 

Material

Aluminized 

Paint Total

Monochlorobiphenyl 1.90E+03 0.00E+00 0.00E+00 1.18E+04 0.00E+00 0.00E+00 0.00E+00 1.37E+04

Dichlorobiphenyl 5.80E+04 0.00E+00 0.00E+00 3.62E+05 1.11E+08 4.14E+04 0.00E+00 1.12E+08

Trichlorobiphenyl 2.59E+03 0.00E+00 0.00E+00 1.62E+04 6.25E+05 7.29E+06 2.02E+06 9.95E+06

Tetrachlorobiphenyl 6.60E+03 0.00E+00 0.00E+00 4.11E+04 8.61E+06 1.60E+08 9.51E+05 1.69E+08

Pentachlorobiphenyl 2.89E+03 0.00E+00 0.00E+00 1.80E+04 9.87E+06 2.93E+08 1.73E+07 3.20E+08

Hexachlorobiphenyl 0.00E+00 0.00E+00 0.00E+00 0.00E+00 1.32E+07 5.22E+07 1.03E+07 7.57E+07

Heptachlorobiphenyl 2.31E+02 0.00E+00 0.00E+00 1.44E+03 8.06E+06 1.01E+07 5.56E+07 7.37E+07

Octachlorobiphenyl 0.00E+00 0.00E+00 0.00E+00 0.00E+00 0.00E+00 0.00E+00 0.00E+00 0.00E+00

Nonachlorobiphenyl 0.00E+00 0.00E+00 0.00E+00 0.00E+00 8.28E+05 0.00E+00 0.00E+00 8.28E+05

Decachlorobiphenyl 0.00E+00 0.00E+00 0.00E+00 0.00E+00 4.62E+05 0.00E+00 0.00E+00 4.62E+05

Total 7.23E+04 0.00E+00 0.00E+00 4.50E+05 1.53E+08 5.22E+08 8.62E+07 7.62E+08

Air Mono Di Tri Tetra Penta Hexa Hepta Octa Nona Deca

Fugacity (Pa) 4.65E-20 2.86E-16 1.89E-17 2.52E-16 2.76E-16 9.75E-18 3.48E-18 0.00E+00 1.23E-21 3.97E-24

Air concentration (g/m3) 3.58E-21 2.60E-17 1.98E-18 3.00E-17 3.67E-17 1.43E-18 5.60E-19 0.00E+00 2.33E-22 8.06E-25

Upper Water Column Mono Di Tri Tetra Penta Hexa Hepta Octa Nona Deca

Fugacity (Pa) 6.12E-18 4.63E-14 1.12E-14 9.04E-14 4.32E-14 5.50E-14 6.95E-15 0.00E+00 1.94E-14 8.44E-16

Water concentration (mg/L) 2.82E-17 2.22E-13 1.79E-14 2.90E-13 3.81E-13 1.52E-14 6.24E-15 0.00E+00 2.81E-18 1.01E-20

Suspended solids concentration (mg/kg) 1.95E-14 3.80E-10 1.13E-10 1.96E-09 4.92E-09 2.75E-09 2.05E-09 0.00E+00 3.89E-12 1.32E-13

Dissolved organic carbon (mg/kg) 6.21E-14 2.83E-09 4.39E-10 1.79E-08 1.24E-07 1.07E-08 7.15E-09 0.00E+00 4.67E-11 2.99E-12

Lower Water Column Mono Di Tri Tetra Penta Hexa Hepta Octa Nona Deca

Fugacity (Pa) 1.37E-14 1.05E-10 2.67E-11 2.21E-10 1.27E-10 3.92E-10 7.63E-11 0.00E+00 1.06E-09 5.78E-10

Water concentration (mg/L) 6.28E-14 5.03E-10 4.26E-11 7.08E-10 1.11E-09 1.08E-10 6.85E-11 0.00E+00 1.54E-13 6.89E-15

Suspended solids concentration (mg/kg) 4.34E-11 8.62E-07 2.69E-07 4.79E-06 1.44E-05 1.96E-05 2.25E-05 0.00E+00 2.13E-07 9.01E-08

Dissolved organic carbon (mg/kg) 1.38E-10 6.41E-06 1.05E-06 4.38E-05 3.63E-04 7.60E-05 7.85E-05 0.00E+00 2.56E-06 2.04E-06

Inside the Vessel Mono Di Tri Tetra Penta Hexa Hepta Octa Nona Deca

Fugacity (Pa) 9.67E-12 7.43E-08 1.89E-08 1.56E-07 8.96E-08 2.77E-07 5.40E-08 0.00E+00 7.51E-07 4.09E-07

Water concentration (mg/L) 4.45E-11 3.57E-07 3.02E-08 5.02E-07 7.90E-07 7.68E-08 4.85E-08 0.00E+00 1.09E-10 4.88E-12

Suspended solids concentration (mg/kg) 3.07E-08 6.11E-04 1.91E-04 3.39E-03 1.02E-02 1.39E-02 1.59E-02 0.00E+00 1.51E-04 6.38E-05

Dissolved organic carbon (mg/kg) 9.80E-08 4.54E-03 7.41E-04 3.10E-02 2.57E-01 5.38E-02 5.56E-02 0.00E+00 1.81E-03 1.45E-03

Sediment Bed Mono Di Tri Tetra Penta Hexa Hepta Octa Nona Deca

Fugacity (Pa) 1.37E-14 1.05E-10 2.67E-11 2.21E-10 1.27E-10 3.92E-10 7.63E-11 0.00E+00 1.06E-09 5.78E-10

Pore Water concentration (mg/L) 6.28E-14 5.03E-10 4.26E-11 7.08E-10 1.11E-09 1.08E-10 6.85E-11 0.00E+00 1.54E-13 6.89E-15

Sediment concentration (mg/kg) 2.89E-12 5.75E-08 1.80E-08 3.19E-07 9.60E-07 1.30E-06 1.50E-06 0.00E+00 1.42E-08 6.01E-09

Bioenergetic Inputs

Species Body Weight Lipid Moisture Caloric 

Density GE to ME Met Energy Caloric 

Density Production Respiration Excretion Caloric 

Density Met Energy

(kg) (%-dw) (%) (kcal/g-dry 

weight) Fraction (kcal/kg-lipid) (kcal/kg-lipid) (% of total) (% of total) (% of total) (kcal/g-wt 

weight)

 (kcal/g-wt 

weight)

Pelagic Community

Phytoplankton (TL-I) Algae 10% 84% 2.36 0.6 13748 22913 0.3776 0.22656

Zooplankton (TL-II) copepods 0.000005 22% 76% 3.6 0.65 10636 16364 18% 24% 58% 0.864 0.5616

Planktivore (TL-III) herring 0.05 28% 75% 4.9 0.7 12206 17438 20% 60% 20% 1.225 0.8575

Piscivore (TL-IV) jack 0.5 28% 75% 4.9 0.7 12206 17438 20% 60% 20% 1.225 0.8575

Reef / Vessel Community

Attached Algae (TL-I) Algae 10% 84% 2.36 0.6 13748 22913 0.3776 0.22656

Sessile filter feeder (TL-II) bivalves (w/o shell) 0.05 5% 82% 4.6 0.65 59800 92000 28% 31% 41% 0.828 0.5382

Invertebrate Omnivore (TL-II) urchin 0.05 29% 82% 4.6 0.65 10310 15862 7% 25% 68% 0.828 0.5382

Invertebrate Forager (TL-III) crab 1 9% 74% 2.7 0.65 19118 29412 28% 59% 13% 0.702 0.4563

Vertebrate Forager (TL-III) triggerfish 1 28% 75% 4.9 0.7 12206 17438 20% 60% 20% 1.225 0.8575

Predator (TL-IV) grouper 1.5 28% 75% 4.9 0.7 12206 17438 20% 60% 20% 0.2 0.14

Benthic Community

Infaunal invert. (TL-II) polychaete 0.01 6% 84% 4.6 0.65 50000 76923 71% 26% 3% 0.736 0.4784

Epifaunal invert. (TL-II) nematode 0.01 6% 82% 4.6 0.65 50000 76923 31% 19% 50% 0.828 0.5382

Forager (TL-III) lobster 2 9% 74% 2.7 0.65 19118 29412 28% 59% 13% 0.702 0.4563

Predator (TL-IV) flounder 3 22% 75% 4.9 0.7 15591 22273 20% 60% 20% 1.225 0.8575

Bioenergetic Inputs Resp. Rate Resp. Rate Consumption Growth Rate Consumption Consumption

1 gO2 kcal 1 g-wt weight kcal As a % of

Pelagic Community day kg-lipid-day kg-lipid-day day g-wt weight-d-wet weight-da body weight

Phytoplankton (TL1) Algae

Zooplankton (TL-II) copepods 0.006375522 0 0.039935335 0.015425453 84.24400867 1286.168071 0.014147849 0.32636028 0.06790967 32.6%

Planktivore (TL-III) herring 0.0033 -0.227 0.0548 0.004949927 21.1649 129.2512977 0.001482433 0.01616792 0.0090799 1.6%

Piscivore (TL-IV) jack 0.001118602 -0.55 0.12 0.000630951 2.697821256 16.47524431 0.000188961 0.00139796 0.00115739 0.1%

Reef / Vessel Community

Attached Algae Algae

Sessile filter feeder (TL-II) bivalves (w/o shell) 0.012 0 0.036 0.024213411 581.8482643 6877.300342 0.020930914 0.24377539 0.0618957 24.4%

Invertibrate Omnivore (TL-II) urchin 0.000675466 0 0.079181846 0.003163548 13.1069075 192.1012396 0.000847751 0.03471132 0.01002768 3.5%

Invertibrate Forager (TL-III) crab 0.001158234 0 0.071193202 0.004642088 60.75673491 377.3221989 0.003592107 0.01678102 0.00900593 1.7%

Vertibrate Forager (TL-III) triggerfish 0.015181024 -0.415 0.061 0.002837229 12.13142452 74.08503521 0.00084971 0.00907693 0.00520447 0.9%

Predator (TL-IV) grouper 0.00279 -0.355 0.0811 0.001011362 4.324384181 26.40845301 0.000302889 0.00264734 0.00185519 0.3%

Benthic Community

Infaunal invert. (TL-II) polychaete 0.001682129 0 0.071034762 0.006721006 135.0382801 1903.064429 0.017565285 0.09800757 0.01820852 9.8%

Epifaunal invert. (TL-II) nematode 0.001682129 0 0.071034762 0.006721006 135.0382801 2604.19343 0.0104949 0.09262416 0.02803154 9.3%

Forager (TL-III) lobster 0.0035 -0.13 0.066 0.00471923 61.76639253 383.5925529 0.003651801 0.01899736 0.00915559 1.9%

Predator (TL-IV) flounder 0.0046 -0.24 0.067 0.002486878 13.58174479 82.94195291 0.000744785 0.00974341 0.00456181 1.0%

PCB MODELING RESULTS - PROSPECTIVE RISK EVALUATION 

RISK ESTIMATES FOR Ex-Oriskany CV34

Supplemental Information

Release Rates in nanograms PCB per gram of PCB within the Material

Respiration Rate Allometric Regression Parameters

a b1 b2

5/26/05 8:48

PRAM 1.3 Supplemental Information

1/23/2006 11:00 PM

Based on NEHC PRAM Version 1.3

May 2004 Page 14 of 25
PCB MODELING RESULTS - PROSPECTIVE RISK EVALUATION 

RISK ESTIMATES FOR Ex-Oriskany CV34

Supplemental Information

Dietary Preferences

Suspended Solids

(Epilimnion)

Suspended 

Solids

(Hypolimnion)

Sediment Phytoplankton Zooplankton Pelagic 

Plankitivore

Attached 

Algae

Reef Sessile 

Filter Feeder

Invertebrate 

Omnivore

Reef

Invertebrate

Forager

Reef

Vertebrate

Forager

Infaunal 

Benthos

Epifaunal 

Benthos

Benthic 

Forager

Pelagic Community

Phytoplankton (TL1)

Zooplankton (TL-II) 15% 15% 70%

Planktivore (TL-III) 100%

Piscivore (TL-IV) 10% 90%

Reef / Vessel Community

Attached Algae

Sessile filter feeder (TL-II) 10% 80% 10%

Invertebrate Omnivore (TL-II) 80% 20%

Invertebrate Forager (TL-III) 5% 5% 5% 35% 50%

Vertebrate Forager (TL-III) 19% 19% 15% 22% 12.5% 12.5%

Predator (TL-IV) 15% 60% 8% 8% 8%

Benthic Community

Infaunal invert. (TL-II) 50% 30% 20%

Epifaunal invert. (TL-II) 25% 30% 20% 25%

Forager (TL-III) 5% 50% 45%

Predator (TL-IV) 2% 20% 20% 58%

Water Exposures

Upper Water 

Column

Lower Water

Column Vessel Interior Sediment PoreWater GE ME ME as kcal/g-ww

Pelagic Community Sediment (kcal/kg-oc) 11456 6873.6 0.6 0.01099776

Phytoplankton (TL1) Algae 100% Suspended Sediment (kcal/kg-oc) 11456 6873.6 0.6 0.1649664

Zooplankton (TL-II) copepods 50% 50%

Planktivore (TL-III) herring 80% 20%

Piscivore (TL-IV) jack 80% 20%

Reef / Vessel Community

Attached Algae Algae 100%

Sessile filter feeder (TL-II) bivalves (w/o shell) 100%

Invertebrate Omnivore (TL-II) urchin 80% 20%

Invertebrate Forager (TL-III) crab 70% 30%

Vertebrate Forager (TL-III) triggerfish 70% 30%

Predator (TL-IV) grouper 80% 20%

Benthic Community

Infaunal invert. (TL-II) polychaete 20% 80%

Epifaunal invert. (TL-II) nematode 50% 50%

Forager (TL-III) lobster 75% 25%

Predator (TL-IV) flounder 90% 10%

Respiratory Efficiencies Mono Di Tri Tetra Penta Hexa Hepta Octa Nona Deca

Low body weight (<100g) 4.335E-01 8.000E-01 8.000E-01 8.000E-01 4.492E-01 2.582E-01 2.018E-01 1.127E-01 5.303E-02 1.255E-02

High body weight (>100g) 5.000E-01 5.000E-01 5.000E-01 5.000E-01 3.769E-01 2.857E-01 2.526E-01 1.888E-01 1.295E-01 6.299E-02

Dietary Assimilation Efficiencies 27% 46% 53% 62% 69% 69% 68% 59% 44% 16%

Tissue Conc. (mg/kg-lipid) Mono Di Tri Tetra Penta Hexa Hepta Octa Nona Deca

Pelagic Community

Phytoplankton (TL1) 8.387E-13 2.222E-08 1.787E-09 2.899E-08 3.807E-08 1.523E-09 6.239E-10 0.000E+00 2.811E-13 1.007E-15

Zooplankton (TL-II) 4.231E-09 1.571E-04 1.585E-05 2.991E-04 2.967E-04 4.244E-05 3.776E-05 0.000E+00 1.893E-07 2.799E-08

Planktivore (TL-III) 9.564E-10 1.331E-04 2.426E-05 8.873E-04 1.581E-03 2.488E-04 2.158E-04 0.000E+00 7.140E-07 3.758E-08

Piscivore (TL-IV) 2.501E-10 2.346E-05 6.441E-06 5.183E-04 2.772E-03 7.462E-04 7.296E-04 0.000E+00 2.131E-06 4.648E-08

Reef / Vessel Community

Attached Algae 1.870E-09 5.035E-05 4.260E-06 7.080E-05 1.115E-04 1.084E-05 6.847E-06 0.000E+00 1.540E-08 6.887E-10

Sessile filter feeder (TL-II) 6.022E-08 2.031E-03 2.006E-04 3.773E-03 3.652E-03 3.235E-04 2.342E-04 0.000E+00 7.497E-07 8.135E-08

Invertebrate Omnivore (TL-II) 2.883E-07 2.235E-02 3.298E-03 1.060E-01 1.708E-01 1.202E-02 6.275E-03 0.000E+00 4.231E-06 5.249E-08

Invertebrate Forager (TL-III) 2.186E-06 8.904E-02 1.325E-02 4.464E-01 8.506E-01 6.702E-02 3.707E-02 0.000E+00 4.056E-05 2.689E-06

Vertebrate Forager (TL-III) 2.009E-07 1.406E-02 3.019E-03 1.767E-01 6.272E-01 6.326E-02 3.683E-02 0.000E+00 4.112E-05 1.369E-06

Predator (TL-IV) 1.112E-07 7.216E-03 1.703E-03 1.483E-01 1.143E+00 1.745E-01 1.116E-01 0.000E+00 1.199E-04 2.665E-06

Benthic Community

Infaunal invert. (TL-II) 1.525E-08 5.992E-04 6.227E-05 1.232E-03 1.237E-03 1.132E-04 8.273E-05 0.000E+00 2.309E-07 1.645E-08

Epifaunal invert. (TL-II) 1.892E-08 1.114E-03 1.329E-04 3.008E-03 3.315E-03 3.177E-04 2.345E-04 0.000E+00 5.892E-07 3.231E-08

Forager (TL-III) 1.105E-08 6.101E-04 9.328E-05 2.819E-03 4.201E-03 3.928E-04 2.676E-04 0.000E+00 4.266E-07 9.788E-09

Predator (TL-IV) 9.779E-10 1.627E-04 4.287E-05 2.656E-03 8.002E-03 9.627E-04 6.798E-04 0.000E+00 8.739E-07 1.285E-08

Tissue Conc. (mg/kg-WW) Mono Di Tri Tetra Penta Hexa Hepta Octa Nona Deca Total PCB

Pelagic Community

Phytoplankton (TL1) 1.382E-14 3.661E-10 2.946E-11 4.777E-10 6.275E-10 2.510E-11 1.028E-11 0.000E+00 4.633E-15 1.659E-17 1.536E-09

Zooplankton (TL-II) 2.234E-10 8.295E-06 8.368E-07 1.579E-05 1.567E-05 2.241E-06 1.994E-06 0.000E+00 9.996E-09 1.478E-09 4.484E-05

Planktivore (TL-III) 6.719E-11 9.348E-06 1.704E-06 6.233E-05 1.111E-04 1.748E-05 1.516E-05 0.000E+00 5.016E-08 2.640E-09 2.172E-04

Piscivore (TL-IV) 1.757E-11 1.648E-06 4.525E-07 3.641E-05 1.947E-04 5.242E-05 5.125E-05 0.000E+00 1.497E-07 3.265E-09 3.371E-04

Reef / Vessel Community

Attached Algae 3.082E-11 8.297E-07 7.021E-08 1.167E-06 1.837E-06 1.787E-07 1.128E-07 0.000E+00 2.538E-10 1.135E-11 4.196E-06

Sessile filter feeder (TL-II) 5.420E-10 1.828E-05 1.806E-06 3.395E-05 3.287E-05 2.911E-06 2.108E-06 0.000E+00 6.748E-09 7.322E-10 9.194E-05

Invertebrate Omnivore (TL-II) 1.505E-08 1.167E-03 1.722E-04 5.534E-03 8.918E-03 6.275E-04 3.276E-04 0.000E+00 2.209E-07 2.740E-09 1.675E-02

Invertebrate Forager (TL-III) 5.217E-08 2.125E-03 3.163E-04 1.065E-02 2.030E-02 1.600E-03 8.848E-04 0.000E+00 9.682E-07 6.418E-08 3.588E-02

Vertebrate Forager (TL-III) 1.411E-08 9.880E-04 2.121E-04 1.241E-02 4.406E-02 4.444E-03 2.587E-03 0.000E+00 2.889E-06 9.615E-08 6.471E-02

Predator (TL-IV) 7.809E-09 5.069E-04 1.196E-04 1.042E-02 8.031E-02 1.226E-02 7.840E-03 0.000E+00 8.420E-06 1.872E-07 1.115E-01

Benthic Community

Infaunal invert. (TL-II) 1.460E-10 5.733E-06 5.958E-07 1.179E-05 1.183E-05 1.083E-06 7.915E-07 0.000E+00 2.209E-09 1.574E-10 3.183E-05

Epifaunal invert. (TL-II) 2.037E-10 1.199E-05 1.431E-06 3.238E-05 3.568E-05 3.420E-06 2.525E-06 0.000E+00 6.343E-09 3.478E-10 8.744E-05

Forager (TL-III) 2.636E-10 1.456E-05 2.226E-06 6.728E-05 1.003E-04 9.375E-06 6.388E-06 0.000E+00 1.018E-08 2.336E-10 2.001E-04

Predator (TL-IV) 5.379E-11 8.946E-06 2.358E-06 1.461E-04 4.401E-04 5.295E-05 3.739E-05 0.000E+00 4.806E-08 7.065E-10 6.879E-04

BAFs (L/kg-lipid) Mono Di Tri Tetra Penta Hexa Hepta Octa Nona Deca

Pelagic Community

Phytoplankton (TL1) 2.979E+04 1.000E+05 1.000E+05 1.000E+05 1.000E+05 1.000E+05 1.000E+05 0.000E+00 1.000E+05 1.000E+05

Zooplankton (TL-II) 1.347E+05 6.238E+05 7.437E+05 8.446E+05 5.321E+05 7.827E+05 1.103E+06 0.000E+00 2.458E+06 8.127E+06

Planktivore (TL-III) 7.602E+04 1.319E+06 2.842E+06 6.256E+06 7.082E+06 1.146E+07 1.575E+07 0.000E+00 2.317E+07 2.729E+07

Piscivore (TL-IV) 1.988E+04 2.325E+05 7.546E+05 3.654E+06 1.241E+07 3.439E+07 5.326E+07 0.000E+00 6.917E+07 3.375E+07

Reef / Vessel Community

Attached Algae 2.979E+04 1.000E+05 1.000E+05 1.000E+05 1.000E+05 1.000E+05 1.000E+05 0.000E+00 1.000E+05 1.000E+05

Sessile filter feeder (TL-II) 9.590E+05 4.034E+06 4.709E+06 5.328E+06 3.276E+06 2.983E+06 3.420E+06 0.000E+00 4.867E+06 1.181E+07

Invertebrate Omnivore (TL-II) 3.223E+04 3.116E+05 5.434E+05 1.051E+06 1.076E+06 7.781E+05 6.433E+05 0.000E+00 1.928E+05 5.351E+04

Invertebrate Forager (TL-III) 1.633E+05 8.295E+05 1.459E+06 2.957E+06 3.579E+06 2.899E+06 2.540E+06 0.000E+00 1.235E+06 1.831E+06

Vertebrate Forager (TL-III) 1.500E+04 1.310E+05 3.324E+05 1.170E+06 2.639E+06 2.736E+06 2.523E+06 0.000E+00 1.252E+06 9.322E+05

Predator (TL-IV) 1.243E+04 1.006E+05 2.806E+05 1.470E+06 7.197E+06 1.130E+07 1.144E+07 0.000E+00 5.462E+06 2.716E+06

Benthic Community

Infaunal invert. (TL-II) 2.429E+05 1.190E+06 1.462E+06 1.740E+06 1.109E+06 1.044E+06 1.208E+06 0.000E+00 1.499E+06 2.389E+06

Epifaunal invert. (TL-II) 3.013E+05 2.213E+06 3.119E+06 4.248E+06 2.973E+06 2.930E+06 3.425E+06 0.000E+00 3.825E+06 4.691E+06

Forager (TL-III) 1.759E+05 1.212E+06 2.189E+06 3.981E+06 3.768E+06 3.622E+06 3.909E+06 0.000E+00 2.770E+06 1.421E+06

Predator (TL-IV) 1.557E+04 3.231E+05 1.006E+06 3.751E+06 7.177E+06 8.878E+06 9.928E+06 0.000E+00 5.673E+06 1.865E+06

Notes:

Kow = octanol to water partitioning coefficient, Koc = organic carbon partitioning coefficient, Kdoc = dissolved organic carbon partitioning coefficient

TL = trophic level, ww = wet weight

Energy Estimates for Suspended Sediment and Bedded Sediment

PRAM 1.3 Supplemental Information

1/23/2006 11:00 PM

Based on NEHC PRAM Version 1.3

May 2004 Page 15 of 25
ZOI = 10

RISK ESTIMATES RME CTE RME CTE RME CTE RME CTE

Benthic fish (flounder) 2.87E-08 2.23E-09 1.68E-03 3.85E-04 8.43E-09 1.71E-09 2.46E-03 4.43E-04

Benthic shellfish (lobster) 8.36E-09 6.47E-10 4.88E-04 1.12E-04 2.45E-09 4.98E-10 7.15E-04 1.29E-04

Pelagic fish (jack) 1.41E-08 1.09E-09 8.21E-04 1.88E-04 4.13E-09 8.38E-10 1.21E-03 2.17E-04

Reef fish TL-IV (grouper) 6.82E-06 5.28E-07 3.98E-01 9.13E-02 2.00E-06 4.06E-07 5.84E-01 1.05E-01

Reef fish TL-III (triggerfish) 3.96E-06 3.07E-07 2.31E-01 5.30E-02 1.16E-06 2.36E-07 3.39E-01 6.11E-02

Reef shellfish (crab) 2.20E-06 1.70E-07 1.28E-01 2.94E-02 6.45E-07 1.31E-07 1.88E-01 3.39E-02

PREDICTED EXPOSURE CONCENTRATIONS (mg/kg in fresh weight)

Benthic fish (flounder) 4.67E-04

Benthic shellfish (lobster) 1.36E-04

Pelagic fish (jack) 2.29E-04

Reef fish TL-IV (grouper) 1.11E-01

Reef fish TL-III (triggerfish) 6.44E-02

Reef shellfish (crab) 3.57E-02

RISK INPUTS - Adult RME CTE RISK INPUTS - Child RME CTE

Body Weight (BWc) (kg) 70 70 Body Weight (BWc) (kg) 15 15

Ingestion Rate (IRc) (kg/day) 0.0261 0.0072 Ingestion Rate (IRc) (kg/day) 0.0092916 0.0025632

Exposure Duration (EDc) (years) 24 3 Exposure Duration (EDc) (years) 6 6

Exposure Frequency (EFc) (days) 365 365 Exposure Frequency (EFc) (days) 365 365

Averaging Time for cancer (ATc) 25550 25550 Averaging Time for cancer (ATc) 25550 25550

Slope Factor (mg/kg-day) 2 1 Slope Factor (mg/kg-day) 2 1

Reference dose for PCBs (RfD) (mg/kg-day) 0.00002 0.000045 Reference dose for PCBs (RfD) (mg/kg-day) 0.00002 0.000045

Averaging Time for noncancer (ATnc-child) 8.76E+03 1.10E+03 Averaging Time for noncancer (ATnc-child) 2.19E+03 2.19E+03

Fractional Ingestion factor (FI) 0.17 0.25 Fractional Ingestion factor (FI) 0.17 0.25

Child - Adult IR scaling factor

Zone of Influence Multiplier 10

Scenario run on

PCB-LADEN MATERIAL INPUTS Fraction Release kg Material PCB Release Ex-Oriskany CV34

PCB Rate (ng/g-d) Onboard (ng/day) Ex-Oriskany CV34 27100

Ventilation Gaskets 3.14E-05 1.58E+03 1.46E+03 7.23E+04 Length (ft) 888

Lubricants 1.03E-04 2.20E+03 0.00E+00 0.00E+00 Beam (ft) 120

Foam Rubber Material 0.76% 2.62E+00 0.00E+00 0.00E+00

Black Rubber Material 5.29E-05 1.58E+03 5.40E+03 4.50E+05

Electrical Cable 1.85E-03 2.79E+02 2.96E+05 1.53E+08

Bulkhead Insulation Material 5.37E-04 6.76E+04 1.44E+04 5.22E+08

Aluminum Paint 2.00E-05 1.11E+04 3.87E+05 8.62E+07

Total 7.62E+08

ZOI = 10

7.78E+04 m2

3.00E-02 mile2

A 1.00E+01 m

B 1.50E+01 m

C 5.00E+01 m

D 1.00E-01 m

E 4.53E+02 m

F 2.19E+02 m

Air Column

Air 7.78E+05 m3

Upper Water Column

Water 1.17E+06 m3

TSS 7.78E+00 m3

Lower Water Column

Water 3.83E+06 m3

TSS 2.56E+01 m3

Inside Vessel

Water 5.38E+04 m3

TSS 3.59E-01 m3

Sediment Bed

Sediment 7.00E+03 m3

Abiotic Inputs Total PCB concentrations

Air Column Air Column

Active air space height above water column (m) 10 Air 1.31E-16 g/m3

Air current (m/h) 13677 Upper Water Column

Upper Water Column Freely dissolved in water 8.95E-13 mg/L

Temperature (oC) 24.5 Suspended solids 1.17E-08 mg/kg

Water depth (m) 15 Dissolved organic carbon 1.57E-07 mg/kg

Total suspended solids (mg/L) 10 Lower Water Column

Dissolved organic carbon (mg/L) 0.6 Freely dissolved in water 1.73E-09 mg/L

Dissolved oxygen (mg/L) 6.12 Suspended solids 4.25E-05 mg/kg

Lower Water Column Dissolved organic carbon 3.90E-04 mg/kg

Temperature (oC) 19.5 Inside Vessel

Water depth (m) 50 Freely dissolved in water 1.80E-06 mg/L

Total suspended solids (mg/L) 10 Suspended solids 4.44E-02 mg/kg

Dissolved organic carbon (mg/L) 0.6 Dissolved organic carbon 4.06E-01 mg/kg

Dissolved oxygen (mg/L) 4.59 Sediment Bed

Inside Vessel Freely dissolved in pore water 1.73E-09 mg/L

Temperature (oC) 19.5 Bedded sediment 2.84E-06 mg/kg

Total suspended solids (mg/L) 10 Dissolved organic carbon in pore water 3.90E-04 mg/kg

Dissolved organic carbon (mg/L) 0.6 Total PCB concentrations in biota

Dissolved oxygen (mg/L) 4.59 Pelagic Community Upper WC Lower WC

Sediment Bed Phytoplankton (TL-I) 1.47E-09 mg/kg 100% 0%

Sediment density (g/cm3) 1.5 Zooplankton (TL-II) 3.05E-05 mg/kg 50% 50%

Active sediment depth (m) 0.1 Planktivore (TL-III) 1.47E-04 mg/kg 80% 20%

Sediment fraction organic carbon 0.01 Piscivore (TL-IV) 2.29E-04 mg/kg 80% 20%

All Regions Reef / Vessel Community Lower WC Vessel Int.

Suspended solids density (g/cm3) 1.5 Attached Algae (TL-I) 2.85E-06 mg/kg 100% 0%

Suspended solids fraction organic carbon 0.15 Sessile filter feeder (TL-II) 6.24E-05 mg/kg 100% 0%

Dissolved organic carbon density (g/cm3) 1 Invertebrate Omnivore (TL-II) 1.67E-02 mg/kg 80% 20%

Water current - to out of the ZOI (m/h) 926 Invertebrate Forager (TL-III) 3.57E-02 mg/kg 70% 30%

Water current - inside to outside the vessel (m/h) 9.26 Vertebrate Forager (TL-III) 6.44E-02 mg/kg 70% 30%

Predator (TL-IV) 1.11E-01 mg/kg 80% 20%

Benthic Community Lower WC Pore Water

Infaunal invert. (TL-II) 2.16E-05 mg/kg 20% 80%

Epifaunal invert. (TL-II) 5.94E-05 mg/kg 50% 50%

Forager (TL-III) 1.36E-04 mg/kg 75% 25%

Predator (TL-IV) 4.67E-04 mg/kg 90% 10%

Percent Exposures

Spatial Footprint on Ocean Floor

RISK ESTIMATES FOR Ex-Oriskany CV34

Volumes

Cancer Risk Adult & Child Hazard Adult & Child Cancer Risk Child Hazard Child

0.356

PCB MODELING RESULTS - PROSPECTIVE RISK EVALUATION 

Modeled Dimensions

Outside the Vessel

6/1/05 12:03

A

C

D

E E

E

VESSEL

B

Pycnocline

A

C

D

E E

E

VESSEL

B

Pycnocline

F_Xappdx_2b.xls B2.6_zoi10_Estimate

1/23/2006 11:00 PM

Based on NEHC PRAM Version 1.4

May 2005 Page 16 of 25
Scenario Run on ZOI=10

PCB Homolog Mono Di Tri Tetra Penta Hexa Hepta Octa Nona Deca

Molecular Weight (g/mol) 1.89E+02 2.23E+02 2.58E+02 2.92E+02 3.26E+02 3.61E+02 3.95E+02 4.30E+02 4.64E+02 4.99E+02

Solubility (mg/L) 2.91E+00 6.78E-01 8.14E-02 6.67E-02 2.61E-02 9.50E-04 2.30E-04 2.11E-08 4.02E-09 1.69E-10

Solubility (mol/m3

) 1.54E-02 3.04E-03 3.16E-04 2.28E-04 8.00E-05 2.63E-06 5.82E-07 4.91E-11 8.65E-12 3.38E-13

Vapor Pressure (Pa) 6.32E-01 1.41E-01 5.11E-02 2.08E-02 2.96E-03 3.43E-03 2.56E-04 8.65E-05 2.77E-05 1.41E-05

Henry's (Pa-m3

/mol) 4.10E+01 4.65E+01 1.62E+02 9.10E+01 3.70E+01 1.30E+03 4.40E+02 1.76E+06 3.20E+06 4.18E+07

log10Kow = 4.47 5.24 5.52 5.92 6.50 6.98 7.19 7.70 8.35 9.60

log10Koc = 3.66 4.06 4.63 4.65 4.94 6.08 6.34 6.46 6.97 7.94

log10Kdoc = 3.34 4.11 4.39 4.79 5.51 5.85 6.06 6.57 7.22 8.47

Chemical emission rate (g/day) 1.37E-05 1.12E-01 9.95E-03 1.69E-01 3.20E-01 7.57E-02 7.37E-02 0.00E+00 8.28E-04 4.62E-04

Chemical emission rate (mol/hr) 3.03E-09 2.09E-05 1.61E-06 2.42E-05 4.08E-05 8.74E-06 7.77E-06 0.00E+00 7.43E-08 3.86E-08

Biodegradation in sediment (1/hr) 0 0 0 0 0 0 0 000

Biodegradation in water (1/hr) 0 0 0 0 0 0 0 000

Ventilation 

Gaskets Lubricants Foam Rubber 

Material

Black Rubber 

Material

Electrical 

Cable

Bulkhead 

Insulation 

Material

Aluminized 

Paint

Fraction PCB in Material (wt/wt) 0.0000314 0.000103 0.76% 0.0000529 0.00185 0.000537 0.00002

Material Mass Onboard (kg) 1459 0 0 5397 296419 14379 386528

Total PCBs (kg) 0.0458126 0 0 0.2855013 548.37515 7.721523 7.73056

Total PCB Release rate (ng/g-PCB per day) 1.58E+03 2.20E+03 2.62E+00 1.58E+03 2.79E+02 6.76E+04 1.11E+04

Ventilation 

Gaskets Lubricants Foam Rubber Material

Black Rubber 

Material

Electrical 

Cable

Bulkhead 

Insulation 

Material

Aluminized 

Paint

Monochlorobiphenyl 4.14E+01 3.47E+01 0.00E+00 4.14E+01 0.00E+00 0.00E+00 0.00E+00

Dichlorobiphenyl 1.27E+03 1.72E+02 3.08E-02 1.27E+03 2.03E+02 5.36E+00 0.00E+00

Trichlorobiphenyl 5.66E+01 8.97E+01 7.63E-02 5.66E+01 1.14E+00 9.44E+02 2.61E+02

Tetrachlorobiphenyl 1.44E+02 1.08E+03 1.29E+00 1.44E+02 1.57E+01 2.07E+04 1.23E+02

Pentachlorobiphenyl 6.31E+01 6.60E+02 3.90E-02 6.31E+01 1.80E+01 3.79E+04 2.24E+03

Hexachlorobiphenyl 0.00E+00 9.42E+01 5.34E-01 0.00E+00 2.41E+01 6.76E+03 1.33E+03

Heptachlorobiphenyl 5.04E+00 7.17E+01 6.46E-01 5.04E+00 1.47E+01 1.30E+03 7.19E+03

Octachlorobiphenyl 0.00E+00 0.00E+00 0.00E+00 0.00E+00 0.00E+00 0.00E+00 0.00E+00

Nonachlorobiphenyl 0.00E+00 0.00E+00 1.72E-03 0.00E+00 1.51E+00 0.00E+00 0.00E+00

Decachlorobiphenyl 0.00E+00 0.00E+00 0.00E+00 0.00E+00 8.43E-01 0.00E+00 0.00E+00

Total 1.58E+03 2.20E+03 2.62E+00 1.58E+03 2.79E+02 6.76E+04 1.11E+04

Release Rates in nanograms PCB per Day Ventilation 

Gaskets Lubricants Foam Rubber 

Material

Black Rubber 

Material

Electrical 

Cable

Bulkhead 

Insulation 

Material

Aluminized 

Paint Total

Monochlorobiphenyl 1.90E+03 0.00E+00 0.00E+00 1.18E+04 0.00E+00 0.00E+00 0.00E+00 1.37E+04

Dichlorobiphenyl 5.80E+04 0.00E+00 0.00E+00 3.62E+05 1.11E+08 4.14E+04 0.00E+00 1.12E+08

Trichlorobiphenyl 2.59E+03 0.00E+00 0.00E+00 1.62E+04 6.25E+05 7.29E+06 2.02E+06 9.95E+06

Tetrachlorobiphenyl 6.60E+03 0.00E+00 0.00E+00 4.11E+04 8.61E+06 1.60E+08 9.51E+05 1.69E+08

Pentachlorobiphenyl 2.89E+03 0.00E+00 0.00E+00 1.80E+04 9.87E+06 2.93E+08 1.73E+07 3.20E+08

Hexachlorobiphenyl 0.00E+00 0.00E+00 0.00E+00 0.00E+00 1.32E+07 5.22E+07 1.03E+07 7.57E+07

Heptachlorobiphenyl 2.31E+02 0.00E+00 0.00E+00 1.44E+03 8.06E+06 1.01E+07 5.56E+07 7.37E+07

Octachlorobiphenyl 0.00E+00 0.00E+00 0.00E+00 0.00E+00 0.00E+00 0.00E+00 0.00E+00 0.00E+00

Nonachlorobiphenyl 0.00E+00 0.00E+00 0.00E+00 0.00E+00 8.28E+05 0.00E+00 0.00E+00 8.28E+05

Decachlorobiphenyl 0.00E+00 0.00E+00 0.00E+00 0.00E+00 4.62E+05 0.00E+00 0.00E+00 4.62E+05

Total 7.23E+04 0.00E+00 0.00E+00 4.50E+05 1.53E+08 5.22E+08 8.62E+07 7.62E+08

Air Mono Di Tri Tetra Penta Hexa Hepta Octa Nona Deca

Fugacity (Pa) 6.30E-20 3.88E-16 2.56E-17 3.42E-16 3.74E-16 1.32E-17 4.72E-18 0.00E+00 1.68E-21 5.39E-24

Air concentration (g/m3) 4.84E-21 3.52E-17 2.69E-18 4.07E-17 4.97E-17 1.95E-18 7.60E-19 0.00E+00 3.17E-22 1.10E-24

Upper Water Column Mono Di Tri Tetra Penta Hexa Hepta Octa Nona Deca

Fugacity (Pa) 5.87E-18 4.44E-14 1.08E-14 8.67E-14 4.15E-14 5.28E-14 6.67E-15 0.00E+00 1.86E-14 8.11E-16

Water concentration (mg/L) 2.70E-17 2.13E-13 1.72E-14 2.78E-13 3.65E-13 1.46E-14 5.99E-15 0.00E+00 2.70E-18 9.67E-21

Suspended solids concentration (mg/kg) 1.87E-14 3.65E-10 1.09E-10 1.88E-09 4.72E-09 2.64E-09 1.97E-09 0.00E+00 3.74E-12 1.27E-13

Dissolved organic carbon (mg/kg) 5.96E-14 2.72E-09 4.21E-10 1.72E-08 1.19E-07 1.02E-08 6.87E-09 0.00E+00 4.48E-11 2.87E-12

Lower Water Column Mono Di Tri Tetra Penta Hexa Hepta Octa Nona Deca

Fugacity (Pa) 9.27E-15 7.12E-11 1.82E-11 1.50E-10 8.59E-11 2.66E-10 5.18E-11 0.00E+00 7.20E-10 3.92E-10

Water concentration (mg/L) 4.26E-14 3.42E-10 2.89E-11 4.81E-10 7.57E-10 7.36E-11 4.65E-11 0.00E+00 1.05E-13 4.68E-15

Suspended solids concentration (mg/kg) 2.95E-11 5.85E-07 1.83E-07 3.25E-06 9.78E-06 1.33E-05 1.53E-05 0.00E+00 1.45E-07 6.12E-08

Dissolved organic carbon (mg/kg) 9.40E-11 4.36E-06 7.10E-07 2.97E-05 2.47E-04 5.16E-05 5.33E-05 0.00E+00 1.74E-06 1.39E-06

Inside the Vessel Mono Di Tri Tetra Penta Hexa Hepta Octa Nona Deca

Fugacity (Pa) 9.67E-12 7.43E-08 1.89E-08 1.56E-07 8.96E-08 2.77E-07 5.40E-08 0.00E+00 7.51E-07 4.09E-07

Water concentration (mg/L) 4.45E-11 3.57E-07 3.02E-08 5.02E-07 7.90E-07 7.68E-08 4.85E-08 0.00E+00 1.09E-10 4.88E-12

Suspended solids concentration (mg/kg) 3.07E-08 6.11E-04 1.91E-04 3.39E-03 1.02E-02 1.39E-02 1.59E-02 0.00E+00 1.51E-04 6.38E-05

Dissolved organic carbon (mg/kg) 9.80E-08 4.54E-03 7.41E-04 3.10E-02 2.57E-01 5.38E-02 5.56E-02 0.00E+00 1.81E-03 1.45E-03

Sediment Bed Mono Di Tri Tetra Penta Hexa Hepta Octa Nona Deca

Fugacity (Pa) 9.27E-15 7.12E-11 1.82E-11 1.50E-10 8.59E-11 2.66E-10 5.18E-11 0.00E+00 7.20E-10 3.92E-10

Pore Water concentration (mg/L) 4.26E-14 3.42E-10 2.89E-11 4.81E-10 7.57E-10 7.36E-11 4.65E-11 0.00E+00 1.05E-13 4.68E-15

Sediment concentration (mg/kg) 1.96E-12 3.90E-08 1.22E-08 2.17E-07 6.52E-07 8.85E-07 1.02E-06 0.00E+00 9.66E-09 4.08E-09

Bioenergetic Inputs

Species Body Weight Lipid Moisture Caloric 

Density GE to ME Met Energy Caloric 

Density Production Respiration Excretion Caloric 

Density Met Energy

(kg) (%-dw) (%) (kcal/g-dry 

weight) Fraction (kcal/kg-lipid) (kcal/kg-lipid) (% of total) (% of total) (% of total) (kcal/g-wt 

weight)

 (kcal/g-wt 

weight)

Pelagic Community

Phytoplankton (TL-I) Algae 10% 84% 2.36 0.6 13748 22913 0.3776 0.22656

Zooplankton (TL-II) copepods 0.000005 22% 76% 3.6 0.65 10636 16364 18% 24% 58% 0.864 0.5616

Planktivore (TL-III) herring 0.05 28% 75% 4.9 0.7 12206 17438 20% 60% 20% 1.225 0.8575

Piscivore (TL-IV) jack 0.5 28% 75% 4.9 0.7 12206 17438 20% 60% 20% 1.225 0.8575

Reef / Vessel Community

Attached Algae (TL-I) Algae 10% 84% 2.36 0.6 13748 22913 0.3776 0.22656

Sessile filter feeder (TL-II) bivalves (w/o shell) 0.05 5% 82% 4.6 0.65 59800 92000 28% 31% 41% 0.828 0.5382

Invertebrate Omnivore (TL-II) urchin 0.05 29% 82% 4.6 0.65 10310 15862 7% 25% 68% 0.828 0.5382

Invertebrate Forager (TL-III) crab 1 9% 74% 2.7 0.65 19118 29412 28% 59% 13% 0.702 0.4563

Vertebrate Forager (TL-III) triggerfish 1 28% 75% 4.9 0.7 12206 17438 20% 60% 20% 1.225 0.8575

Predator (TL-IV) grouper 1.5 28% 75% 4.9 0.7 12206 17438 20% 60% 20% 0.2 0.14

Benthic Community

Infaunal invert. (TL-II) polychaete 0.01 6% 84% 4.6 0.65 50000 76923 71% 26% 3% 0.736 0.4784

Epifaunal invert. (TL-II) nematode 0.01 6% 82% 4.6 0.65 50000 76923 31% 19% 50% 0.828 0.5382

Forager (TL-III) lobster 2 9% 74% 2.7 0.65 19118 29412 28% 59% 13% 0.702 0.4563

Predator (TL-IV) flounder 3 22% 75% 4.9 0.7 15591 22273 20% 60% 20% 1.225 0.8575

Bioenergetic Inputs Resp. Rate Resp. Rate Consumption Growth Rate Consumption Consumption

1 gO2 kcal 1 g-wt weight kcal As a % of

Pelagic Community day kg-lipid-day kg-lipid-day day g-wt weight-d-wet weight-da body weight

Phytoplankton (TL1) Algae

Zooplankton (TL-II) copepods 0.006375522 0 0.039935335 0.015425453 84.24400867 1286.168071 0.014147849 0.32636028 0.06790967 32.6%

Planktivore (TL-III) herring 0.0033 -0.227 0.0548 0.004949927 21.1649 129.2512977 0.001482433 0.01616792 0.0090799 1.6%

Piscivore (TL-IV) jack 0.001118602 -0.55 0.12 0.000630951 2.697821256 16.47524431 0.000188961 0.00139796 0.00115739 0.1%

Reef / Vessel Community

Attached Algae Algae

Sessile filter feeder (TL-II) bivalves (w/o shell) 0.012 0 0.036 0.024213411 581.8482643 6877.300342 0.020930914 0.24377539 0.0618957 24.4%

Invertibrate Omnivore (TL-II) urchin 0.000675466 0 0.079181846 0.003163548 13.1069075 192.1012396 0.000847751 0.03471132 0.01002768 3.5%

Invertibrate Forager (TL-III) crab 0.001158234 0 0.071193202 0.004642088 60.75673491 377.3221989 0.003592107 0.01678102 0.00900593 1.7%

Vertibrate Forager (TL-III) triggerfish 0.015181024 -0.415 0.061 0.002837229 12.13142452 74.08503521 0.00084971 0.00907693 0.00520447 0.9%

Predator (TL-IV) grouper 0.00279 -0.355 0.0811 0.001011362 4.324384181 26.40845301 0.000302889 0.00264734 0.00185519 0.3%

Benthic Community

Infaunal invert. (TL-II) polychaete 0.001682129 0 0.071034762 0.006721006 135.0382801 1903.064429 0.017565285 0.09800757 0.01820852 9.8%

Epifaunal invert. (TL-II) nematode 0.001682129 0 0.071034762 0.006721006 135.0382801 2604.19343 0.0104949 0.09262416 0.02803154 9.3%

Forager (TL-III) lobster 0.0035 -0.13 0.066 0.00471923 61.76639253 383.5925529 0.003651801 0.01899736 0.00915559 1.9%

Predator (TL-IV) flounder 0.0046 -0.24 0.067 0.002486878 13.58174479 82.94195291 0.000744785 0.00974341 0.00456181 1.0%

PCB MODELING RESULTS - PROSPECTIVE RISK EVALUATION 

RISK ESTIMATES FOR Ex-Oriskany CV34

Supplemental Information

Release Rates in nanograms PCB per gram of PCB within the Material

Respiration Rate Allometric Regression Parameters

a b1 b2

6/1/05 12:03

PRAM 1.3 Supplemental Information

1/23/2006 11:00 PM

Based on NEHC PRAM Version 1.3

May 2004 Page 17 of 25
PCB MODELING RESULTS - PROSPECTIVE RISK EVALUATION 

RISK ESTIMATES FOR Ex-Oriskany CV34

Supplemental Information

Dietary Preferences

Suspended Solids

(Epilimnion)

Suspended 

Solids

(Hypolimnion)

Sediment Phytoplankton Zooplankton Pelagic 

Plankitivore

Attached 

Algae

Reef Sessile 

Filter Feeder

Invertebrate 

Omnivore

Reef

Invertebrate

Forager

Reef

Vertebrate

Forager

Infaunal 

Benthos

Epifaunal 

Benthos

Benthic 

Forager

Pelagic Community

Phytoplankton (TL1)

Zooplankton (TL-II) 15% 15% 70%

Planktivore (TL-III) 100%

Piscivore (TL-IV) 10% 90%

Reef / Vessel Community

Attached Algae

Sessile filter feeder (TL-II) 10% 80% 10%

Invertebrate Omnivore (TL-II) 80% 20%

Invertebrate Forager (TL-III) 5% 5% 5% 35% 50%

Vertebrate Forager (TL-III) 19% 19% 15% 22% 12.5% 12.5%

Predator (TL-IV) 15% 60% 8% 8% 8%

Benthic Community

Infaunal invert. (TL-II) 50% 30% 20%

Epifaunal invert. (TL-II) 25% 30% 20% 25%

Forager (TL-III) 5% 50% 45%

Predator (TL-IV) 2% 20% 20% 58%

Water Exposures

Upper Water 

Column

Lower Water

Column Vessel Interior Sediment PoreWater GE ME ME as kcal/g-ww

Pelagic Community Sediment (kcal/kg-oc) 11456 6873.6 0.6 0.01099776

Phytoplankton (TL1) Algae 100% Suspended Sediment (kcal/kg-oc) 11456 6873.6 0.6 0.1649664

Zooplankton (TL-II) copepods 50% 50%

Planktivore (TL-III) herring 80% 20%

Piscivore (TL-IV) jack 80% 20%

Reef / Vessel Community

Attached Algae Algae 100%

Sessile filter feeder (TL-II) bivalves (w/o shell) 100%

Invertebrate Omnivore (TL-II) urchin 80% 20%

Invertebrate Forager (TL-III) crab 70% 30%

Vertebrate Forager (TL-III) triggerfish 70% 30%

Predator (TL-IV) grouper 80% 20%

Benthic Community

Infaunal invert. (TL-II) polychaete 20% 80%

Epifaunal invert. (TL-II) nematode 50% 50%

Forager (TL-III) lobster 75% 25%

Predator (TL-IV) flounder 90% 10%

Respiratory Efficiencies Mono Di Tri Tetra Penta Hexa Hepta Octa Nona Deca

Low body weight (<100g) 4.335E-01 8.000E-01 8.000E-01 8.000E-01 4.492E-01 2.582E-01 2.018E-01 1.127E-01 5.303E-02 1.255E-02

High body weight (>100g) 5.000E-01 5.000E-01 5.000E-01 5.000E-01 3.769E-01 2.857E-01 2.526E-01 1.888E-01 1.295E-01 6.299E-02

Dietary Assimilation Efficiencies 27% 46% 53% 62% 69% 69% 68% 59% 44% 16%

Tissue Conc. (mg/kg-lipid) Mono Di Tri Tetra Penta Hexa Hepta Octa Nona Deca

Pelagic Community

Phytoplankton (TL1) 8.048E-13 2.132E-08 1.715E-09 2.782E-08 3.655E-08 1.462E-09 5.990E-10 0.000E+00 2.699E-13 9.667E-16

Zooplankton (TL-II) 2.873E-09 1.067E-04 1.076E-05 2.032E-04 2.015E-04 2.882E-05 2.564E-05 0.000E+00 1.286E-07 1.900E-08

Planktivore (TL-III) 6.497E-10 9.038E-05 1.648E-05 6.027E-04 1.074E-03 1.689E-04 1.466E-04 0.000E+00 4.848E-07 2.552E-08

Piscivore (TL-IV) 1.699E-10 1.593E-05 4.375E-06 3.521E-04 1.883E-03 5.067E-04 4.954E-04 0.000E+00 1.447E-06 3.156E-08

Reef / Vessel Community

Attached Algae 1.270E-09 3.418E-05 2.893E-06 4.807E-05 7.570E-05 7.363E-06 4.649E-06 0.000E+00 1.046E-08 4.676E-10

Sessile filter feeder (TL-II) 4.089E-08 1.379E-03 1.362E-04 2.562E-03 2.480E-03 2.197E-04 1.590E-04 0.000E+00 5.091E-07 5.524E-08

Invertebrate Omnivore (TL-II) 2.877E-07 2.227E-02 3.285E-03 1.055E-01 1.699E-01 1.192E-02 6.211E-03 0.000E+00 4.116E-06 4.887E-08

Invertebrate Forager (TL-III) 2.183E-06 8.883E-02 1.321E-02 4.447E-01 8.466E-01 6.659E-02 3.678E-02 0.000E+00 4.016E-05 2.679E-06

Vertebrate Forager (TL-III) 2.006E-07 1.402E-02 3.008E-03 1.758E-01 6.239E-01 6.281E-02 3.650E-02 0.000E+00 4.067E-05 1.361E-06

Predator (TL-IV) 1.110E-07 7.198E-03 1.697E-03 1.476E-01 1.137E+00 1.733E-01 1.107E-01 0.000E+00 1.188E-04 2.655E-06

Benthic Community

Infaunal invert. (TL-II) 1.036E-08 4.069E-04 4.229E-05 8.365E-04 8.399E-04 7.687E-05 5.618E-05 0.000E+00 1.568E-07 1.117E-08

Epifaunal invert. (TL-II) 1.285E-08 7.566E-04 9.025E-05 2.043E-03 2.251E-03 2.158E-04 1.593E-04 0.000E+00 4.001E-07 2.194E-08

Forager (TL-III) 7.500E-09 4.142E-04 6.334E-05 1.914E-03 2.853E-03 2.667E-04 1.817E-04 0.000E+00 2.897E-07 6.646E-09

Predator (TL-IV) 6.640E-10 1.104E-04 2.911E-05 1.803E-03 5.434E-03 6.537E-04 4.616E-04 0.000E+00 5.934E-07 8.723E-09

Tissue Conc. (mg/kg-WW) Mono Di Tri Tetra Penta Hexa Hepta Octa Nona Deca Total PCB

Pelagic Community

Phytoplankton (TL1) 1.326E-14 3.513E-10 2.827E-11 4.585E-10 6.023E-10 2.410E-11 9.872E-12 0.000E+00 4.449E-15 1.593E-17 1.474E-09

Zooplankton (TL-II) 1.517E-10 5.634E-06 5.684E-07 1.073E-05 1.064E-05 1.522E-06 1.354E-06 0.000E+00 6.788E-09 1.003E-09 3.045E-05

Planktivore (TL-III) 4.564E-11 6.349E-06 1.158E-06 4.234E-05 7.545E-05 1.187E-05 1.030E-05 0.000E+00 3.406E-08 1.793E-09 1.475E-04

Piscivore (TL-IV) 1.194E-11 1.119E-06 3.074E-07 2.473E-05 1.323E-04 3.560E-05 3.480E-05 0.000E+00 1.017E-07 2.217E-09 2.289E-04

Reef / Vessel Community

Attached Algae 2.093E-11 5.634E-07 4.767E-08 7.923E-07 1.248E-06 1.213E-07 7.662E-08 0.000E+00 1.724E-10 7.707E-12 2.849E-06

Sessile filter feeder (TL-II) 3.680E-10 1.241E-05 1.226E-06 2.306E-05 2.232E-05 1.977E-06 1.431E-06 0.000E+00 4.582E-09 4.971E-10 6.243E-05

Invertebrate Omnivore (TL-II) 1.502E-08 1.163E-03 1.715E-04 5.509E-03 8.868E-03 6.224E-04 3.242E-04 0.000E+00 2.149E-07 2.551E-09 1.666E-02

Invertebrate Forager (TL-III) 5.211E-08 2.120E-03 3.153E-04 1.061E-02 2.021E-02 1.589E-03 8.779E-04 0.000E+00 9.585E-07 6.394E-08 3.572E-02

Vertebrate Forager (TL-III) 1.409E-08 9.850E-04 2.113E-04 1.235E-02 4.383E-02 4.412E-03 2.564E-03 0.000E+00 2.857E-06 9.563E-08 6.436E-02

Predator (TL-IV) 7.795E-09 5.056E-04 1.192E-04 1.037E-02 7.990E-02 1.218E-02 7.776E-03 0.000E+00 8.347E-06 1.865E-07 1.109E-01

Benthic Community

Infaunal invert. (TL-II) 9.910E-11 3.893E-06 4.046E-07 8.004E-06 8.036E-06 7.355E-07 5.375E-07 0.000E+00 1.500E-09 1.069E-10 2.161E-05

Epifaunal invert. (TL-II) 1.383E-10 8.144E-06 9.714E-07 2.199E-05 2.423E-05 2.322E-06 1.714E-06 0.000E+00 4.307E-09 2.361E-10 5.938E-05

Forager (TL-III) 1.790E-10 9.887E-06 1.512E-06 4.569E-05 6.809E-05 6.366E-06 4.337E-06 0.000E+00 6.915E-09 1.586E-10 1.359E-04

Predator (TL-IV) 3.652E-11 6.074E-06 1.601E-06 9.918E-05 2.989E-04 3.595E-05 2.539E-05 0.000E+00 3.264E-08 4.798E-10 4.671E-04

BAFs (L/kg-lipid) Mono Di Tri Tetra Penta Hexa Hepta Octa Nona Deca

Pelagic Community

Phytoplankton (TL1) 2.979E+04 1.000E+05 1.000E+05 1.000E+05 1.000E+05 1.000E+05 1.000E+05 0.000E+00 1.000E+05 1.000E+05

Zooplankton (TL-II) 1.347E+05 6.239E+05 7.438E+05 8.447E+05 5.321E+05 7.827E+05 1.103E+06 0.000E+00 2.458E+06 8.127E+06

Planktivore (TL-III) 7.601E+04 1.319E+06 2.841E+06 6.254E+06 7.080E+06 1.146E+07 1.575E+07 0.000E+00 2.317E+07 2.729E+07

Piscivore (TL-IV) 1.988E+04 2.325E+05 7.544E+05 3.653E+06 1.241E+07 3.438E+07 5.325E+07 0.000E+00 6.917E+07 3.375E+07

Reef / Vessel Community

Attached Algae 2.979E+04 1.000E+05 1.000E+05 1.000E+05 1.000E+05 1.000E+05 1.000E+05 0.000E+00 1.000E+05 1.000E+05

Sessile filter feeder (TL-II) 9.590E+05 4.035E+06 4.709E+06 5.329E+06 3.276E+06 2.983E+06 3.421E+06 0.000E+00 4.867E+06 1.181E+07

Invertebrate Omnivore (TL-II) 3.221E+04 3.111E+05 5.422E+05 1.048E+06 1.071E+06 7.733E+05 6.379E+05 0.000E+00 1.879E+05 4.991E+04

Invertebrate Forager (TL-III) 1.632E+05 8.284E+05 1.456E+06 2.949E+06 3.565E+06 2.883E+06 2.523E+06 0.000E+00 1.224E+06 1.827E+06

Vertebrate Forager (TL-III) 1.500E+04 1.308E+05 3.315E+05 1.166E+06 2.628E+06 2.720E+06 2.503E+06 0.000E+00 1.240E+06 9.282E+05

Predator (TL-IV) 1.243E+04 1.005E+05 2.801E+05 1.466E+06 7.174E+06 1.124E+07 1.137E+07 0.000E+00 5.425E+06 2.712E+06

Benthic Community

Infaunal invert. (TL-II) 2.429E+05 1.190E+06 1.462E+06 1.740E+06 1.109E+06 1.044E+06 1.208E+06 0.000E+00 1.499E+06 2.389E+06

Epifaunal invert. (TL-II) 3.013E+05 2.213E+06 3.120E+06 4.249E+06 2.974E+06 2.930E+06 3.426E+06 0.000E+00 3.825E+06 4.691E+06

Forager (TL-III) 1.759E+05 1.212E+06 2.190E+06 3.982E+06 3.768E+06 3.622E+06 3.909E+06 0.000E+00 2.770E+06 1.421E+06

Predator (TL-IV) 1.557E+04 3.231E+05 1.006E+06 3.751E+06 7.178E+06 8.878E+06 9.929E+06 0.000E+00 5.673E+06 1.865E+06

Notes:

Kow = octanol to water partitioning coefficient, Koc = organic carbon partitioning coefficient, Kdoc = dissolved organic carbon partitioning coefficient

TL = trophic level, ww = wet weight

Energy Estimates for Suspended Sediment and Bedded Sediment

PRAM 1.3 Supplemental Information

1/23/2006 11:00 PM

Based on NEHC PRAM Version 1.3

May 2004 Page 18 of 25
K2.7 zoi summary

B.3 Summary of Total PCBs concentrations modeled for biological and abiotic compartments as a function of ZOI.

ZOI 1 2 3 4 5 10

Tissue Conc. (mg/kg-WW) Total PCB Total PCB Total PCB Total PCB Total PCB Total PCB

Pelagic Community

Phytoplankton (TL1) 1.86E-09 1.67E-09 1.60E-09 1.56E-09 1.54E-09 1.47E-09

Zooplankton (TL-II) 1.21E-04 7.72E-05 6.04E-05 5.10E-05 4.48E-05 3.05E-05

Planktivore (TL-III) 5.88E-04 3.74E-04 2.92E-04 2.47E-04 2.17E-04 1.47E-04

Piscivore (TL-IV) 9.13E-04 5.80E-04 4.54E-04 3.83E-04 3.37E-04 2.29E-04

Reef / Vessel Community

Attached Algae 1.14E-05 7.23E-06 5.65E-06 4.77E-06 4.20E-06 2.85E-06

Sessile filter feeder (TL-II) 2.49E-04 1.58E-04 1.24E-04 1.05E-04 9.19E-05 6.24E-05

Invertebrate Omnivore (TL-II) 1.72E-02 1.69E-02 1.68E-02 1.68E-02 1.67E-02 1.67E-02

Invertebrate Forager (TL-III) 3.67E-02 3.62E-02 3.61E-02 3.60E-02 3.59E-02 3.57E-02

Vertebrate Forager (TL-III) 6.66E-02 6.55E-02 6.51E-02 6.49E-02 6.47E-02 6.44E-02

Predator (TL-IV) 1.15E-01 1.13E-01 1.12E-01 1.12E-01 1.11E-01 1.11E-01

Benthic Community

Infaunal invert. (TL-II) 8.62E-05 5.48E-05 4.28E-05 3.62E-05 3.18E-05 2.16E-05

Epifaunal invert. (TL-II) 2.37E-04 1.51E-04 1.18E-04 9.94E-05 8.74E-05 5.94E-05

Forager (TL-III) 5.42E-04 3.45E-04 2.69E-04 2.28E-04 2.00E-04 1.36E-04

Predator (TL-IV) 1.86E-03 1.18E-03 9.26E-04 7.82E-04 6.88E-04 4.67E-04

Air concentration (g/m3) 5.26E-17 6.68E-17 7.83E-17 8.81E-17 9.68E-17 1.31E-16

Upper Water Column

Fugacity (Pa)

Water concentration (mg/L) 1.13E-12 1.02E-12 9.72E-13 9.48E-13 9.32E-13 8.95E-13

Suspended solids concentration (mg/kg) 1.48E-08 1.33E-08 1.27E-08 1.24E-08 1.22E-08 1.17E-08

Dissolved organic carbon (mg/kg) 1.98E-07 1.78E-07 1.70E-07 1.66E-07 1.63E-07 1.57E-07

Bulk Upper Water Col (mg/L) 2.67E-10 2.40E-10 2.30E-10 2.24E-10 2.21E-10 2.12E-10

Lower Water Column

Fugacity (Pa)

Water concentration (mg/L) 6.90E-09 4.39E-09 3.43E-09 2.89E-09 2.55E-09 1.73E-09

Suspended solids concentration (mg/kg) 1.70E-04 1.08E-04 8.43E-05 7.12E-05 6.27E-05 4.25E-05

Dissolved organic carbon (mg/kg) 1.55E-03 9.88E-04 7.72E-04 6.52E-04 5.74E-04 3.90E-04

Bulk Lower Water Col (mg/L) 2.64E-06 1.68E-06 1.31E-06 1.11E-06 9.73E-07 6.61E-07

Inside the Vessel

Fugacity (Pa)

Water concentration (mg/L) 1.80E-06 1.80E-06 1.80E-06 1.80E-06 1.80E-06 1.80E-06

Suspended solids concentration (mg/kg) 4.44E-02 4.44E-02 4.44E-02 4.44E-02 4.44E-02 4.44E-02

Dissolved organic carbon (mg/kg) 4.06E-01 4.06E-01 4.06E-01 4.06E-01 4.06E-01 4.06E-01

Bulk Water Inside Vessel (mg/L) 6.89E-04 6.89E-04 6.89E-04 6.89E-04 6.89E-04 6.89E-04

Sediment Bed

Fugacity (Pa)

Pore Water concentration (mg/L) 6.90E-09 4.39E-09 3.43E-09 2.89E-09 2.55E-09 1.73E-09

Sediment concentration (mg/kg) 1.13E-05 7.19E-06 5.62E-06 4.75E-06 4.18E-06 2.84E-06

K2.7 zoi summary