CHEMISTRY, TOXICITY AND BENTHIC COMMUNITY CONDITIONS

IN SEDIMENTS OF THE SAN DIEGO BAY REGION

FINAL REPORT

September, 1996

California State Water Resources Control Board

National Oceanic and Atmospheric Administration

California Department of Fish and Game

Marine Pollution Studies Laboratory

Moss Landing Marine Laboratories

University of California, Santa Cruz
AUTHORS

Russell Fairey, Carrie Bretz, and Stewart Lamerdin

San Jose State University- Moss Landing Marine Laboratories

John Hunt, Brian Anderson, and Shirley Tudor

University of California Santa Cruz

Craig J. Wilson and Fred LaCaro

State Water Resources Control Board

Mark Stephenson and Max Puckett

California Department of Fish and Game

Edward R. Long

National Oceanic and Atmospheric Administration
i

EXECUTIVE SUMMARY

The following report describes and evaluates chemical and

biological data collected from San Diego Bay and its historical

tributaries between October, 1992 and May, 1994. The study was

conducted as part of the ongoing Bay Protection and Toxic Cleanup

Program, a legislatively mandated program designed to assess the

degree of chemical pollution and associated biological effects in

California's bays and harbors. The workplan for this study

resulted from a cooperative agreement between the State Water

Resources Control Board and the National Oceanic and Atmospheric

Administration (NOAA). Monitoring and reporting aspects of the

study were conducted by the Environmental Services Division, of

the California Department of Fish and Game, and its

subcontractors. 

The study objectives were:

 1. Determine presence or absence of adverse biological

effects in representative areas of the San Diego Bay

Region;

 2. Determine relative degree or severity of adverse

effects, and distinguish more severely impacted

sediments from less severely impacted sediments;

 3. Determine relative spatial extent of toxicantassociated effects in the San Diego Bay Region;

 4. Determine relationships between toxicants and measures

of effects in the San Diego Bay Region.

The research involved chemical analysis of sediments, benthic

community analysis and toxicity testing of sediments and sediment

pore water. Chemical analyses and bioassays were performed using

aliquots of homogenized sediment samples collected synoptically

at each station. Analysis of the benthic community structure was

made on a subset of the total number of stations sampled.

Three hundred and fifty stations were sampled between

October, 1992 and May, 1994. Areas sampled included San Diego

Bay, Mission Bay, the San Diego River Estuary and the Tijuana

River Estuary and are collectively termed "the San Diego Bay

Region" in the following document. Two types of sampling designs

were utilized: direct point sampling and stratified random

sampling.

Chemical pollution was demonstrated by using comparisons to

established sediment quality guidelines. Two sets of guidelines

were used: the Effects Range-Low (ERL)/Effects Range-Median (ERM)

guidelines developed by NOAA (Long and Morgan, 1990; Long et al.,

1995) and the Threshold Effects Level (TEL)/Probable Effects

Level (PEL) guidelines used in Florida (McDonald, 1993; McDonald,

1994). Copper, mercury, zinc, total chlordane, total PCBs and the

PAHs were most often found to exceed critical ERM or PEL values
ii

and were considered the major chemicals or chemical groups of

concern in the San Diego Bay Region. ERM and PEL summary

quotients were used to develop chemical indices for addressing

the pollution of sediments with multiple chemicals. An ERM

summary quotient >0.85 or a PEL summary quotient >1.29 was

indicative of stations where multiple chemicals were

significantly elevated. Stations with any chemical concentration

>4 times its respective ERM or >5.9 times its respective PEL were

considered to exhibit elevated chemistry. Summary quotients and

magnitude of sediment quality guideline exceedances were used as

additional information to help prioritize stations of concern for

Regional Water Quality Control Board staff.

Identification of degraded and undegraded habitat (as determined

by macrobenthic community structure) was conducted using a

cumulative, weight-of-evidence approach. Analyses were performed

to identify relationships between community structure within and

between each station or site (e.g., diversity/evenness indices,

analyses of habitat and species composition, construction of

dissimilarity matrices for pattern testing, assessment of

indicator species, and development of a benthic index, cluster

analyses, and ordination analyses).

Analyses of the 75 stations sampled for benthic community

structure identified 23 undegraded stations, 43 degraded and 9

transitional stations. All sampled stations with an ERM summary

quotient >0.85 were found to have degraded communities. All

sampled stations with P450 Reporter Gene System responses above

60 μg/g BaPEq. were similarly found to have degraded benthic

communities.

The statistical significance of toxicity test results was

determined using two approaches: the reference envelope approach

and laboratory control comparison approach used by the United

States Environmental Protection Agency- Environmental Monitoring

and Assessment Program and NOAA- National Status and Trends

programs. The reference envelope approach indicated that toxicity

for the Rhepoxynius (amphipod) sediment test was significant when

survival was less than 48% in samples tested. No reference

envelope was calculated for the urchin fertilization or

development tests due to high variability in pore water data from

reference stations.

The laboratory control comparison approach was used to compare

test sediment samples against laboratory controls for

determination of statistically significant differences in test

organism response. Criteria for toxicity in this approach were 1)

survival less than 80% of the control value and 2) significant

difference between test samples and controls, as determined using

a t-test. Using this approach, there was no absolute value below

which all samples could be considered toxic, although survival

below a range of 72-80% was generally considered toxic.
iii

Using the EMAP definition of toxicity, 56% of the total area

sampled was toxic to Rhepoxynius. For the Strongylocentrotus

larval development test, percent of total area toxic was 29%,

54%, and 72% respectively for 25%, 50%, and undiluted pore water

concentrations. Samples representing 14%, 27%, or 36% of the

study area were toxic to both Strongylocentrotus in pore water

(25%, 50%, or undiluted, respectively) and Rhepoxynius in solid

phase sediment.

Linear regression analyses failed to reveal strong correlations

between amphipod survival and chemical concentration. It is

suspected instead of a linear response to chemical pollutants,

most organisms are tolerant of pollutants until a threshold is

exceeded. Comparisons to established sediment quality guideline

thresholds demonstrate an increased incidence of toxicity for San

Diego Bay Region samples with chemical concentrations exceeding

the ERM or PEL values. It is further suspected toxicity in urban

bays is caused by exposure to complex mixtures of chemicals.

Comparisons to ERM summary quotients (multiple chemical

indicators) demonstrate that the highest incidence of toxicity

(>78%) is found in samples with elevated ERM summary quotients

(>0.85).

Statistical analyses of the P450 Reporter Gene System responses

versus the PAHs in sediment extracts demonstrated that this

biological response indicator was significantly correlated

(r2 = 0.86) with sediment PAH (total and high molecular weight)

concentration.

Stations requiring further investigation were prioritized based

on existing evidence. Each station receiving a high, moderate or

low priority ranking meets one or more of the criteria under

evaluation for determining hot spot status in the Bay Protection

and Toxic Cleanup Program. Those meeting all criteria were given

the highest priority for further action. A ranking scheme was

developed to evaluate stations of lower priority.

Seven stations (representing four sites) were given a high

priority ranking, 43 stations were given a moderate priority

ranking, and 57 stations were given a low priority ranking. The

seven stations receiving the high priority ranking were in the

Seventh Street channel area, two naval shipyard areas near the

Coronado Bridge, and the Downtown Anchorage area west of the

airport. The majority of stations given moderate rankings were

associated with commercial areas and naval shipyard areas in the

vicinity of the Coronado Bridge. Low priority stations were

interspersed throughout the San Diego Bay Region.

A review of historical data supports the conclusions of the

current research. Recommendations are made for complementary

investigations which could provide additional evidence for

further characterizing stations of concern. 
iv

ACKNOWLEDGMENTS

This study was completed thanks to the efforts of the following

institutions and individuals:

State Water Resources Control Board- Division of Water Quality

Bay Protection and Toxic Cleanup Program

Craig Wilson Mike Reid Fred LaCaro

Syed Ali Gita Kapahi

National Oceanic and Atmospheric Administration

Ed Long Gail Sloane

Regional Water Quality Control Board- Region 9

Pete Michael

California Department of Fish and Game

Environmental Services Division

Mark Stephenson Max Puckett Gary Ichikawa

Kim Paulson Jon Goetzel Jim Kanihan

San Jose State University- Moss Landing Marine Laboratories

Sample Collection And Data Analysis

Russell Fairey Eric Johnson Cassandra Roberts

Ross Clark James Downing Michele Jacobi

Stewart Lamerdin Brenda Konar Eli Landreau 

Lisa Kerr

Total Organic Carbon and Grain Size Analyses

Pat Iampietro Michelle White Sean McDermott

Benthic Community Analysis

John Oliver Jim Oakden Carrie Bretz
v

ACKNOWLEDGMENTS (continued)

University of California at Santa Cruz

Dept. of Chemistry and Biochemistry- Trace Organics Analyses

Ronald Tjeerdema John Newman Debora Holstad

Katharine Semsar Thomas Shyka Gloria J. Blondina

Linda Hannigan Laura Zirelli James Derbin

Matthew Stoetling Raina Scott Dana Longo

Else Gladish-Wilson

Institute of Marine Sciences- Toxicity Testing

John Hunt Brian Anderson Bryn Phillips

Witold Piekarski Matt Englund Shirley Tudor

Michelle Hester Hilary McNulty Steve Osborn

Steve Clark Kelita Smith Lisa Weetman

Columbia Analytical Services

Jack Anderson

EcoAnalysis

Robert Smith 

Funding was provided through a cooperative effort by:

State Water Resources Control Board- Division of Water Quality

Bay Protection and Toxic Cleanup Program

National Oceanic and Atmospheric Administration

Coastal Ocean Program
vi

TABLE OF CONTENTS

EXECUTIVE SUMMARY ............................................ i

ACKNOWLEDGEMENTS ............................................ iv

TABLE OF CONTENTS ............................................ vi

LIST OF FIGURES .............................................. vii

LIST OF TABLES AND APPENDICES ............................... viii

LIST OF ABBREVIATIONS ........................................ ix

INTRODUCTION ................................................. 1

Purpose ................................................. 1

Programmatic Background and Needs ....................... 1

Study Area .............................................. 4

METHODS ...................................................... 9

Sampling Design ......................................... 9

Sample Collection and Processing ........................ 12

Trace Metal Analysis of Sediments ....................... 20

Trace Organic Analysis of Sediments ..................... 21

Total Organic Carbon Analysis of Sediments .............. 24

Grain Size Analysis ..................................... 26

Benthic Community Analysis .............................. 27

Toxicity Testing ....................................... 27

P450 Reporter Gene System .............................. 40

RESULTS ..................................................... 42

Distribution of Chemical Pollutants ..................... 42

Chemical-Specific Screening Values ................. 42

Primary Chemicals of Concern ....................... 43

Copper ........................................ 46

Zinc .......................................... 46

Mercury ....................................... 46

PAHs .......................................... 46

PCBs .......................................... 46

Chlordane ..................................... 67

ERM and PEL Summary Quotients ...................... 67

Distribution of Benthic Community Degradation ........... 76

Data Analyses and Interpretation ................... 76

Abundance and Diversity ............................ 82

Cluster and Ordination Analyses ................... 87

Indicator Species .................................. 91

Benthic Index ...................................... 92

Site and Station Analyses .......................... 93

Distribution of Toxicity ................................ 95

QA/QC Evaluation ................................... 95

Areal Extent of Toxicity Based on EMAP Approach .... 102

Toxicity Based on Reference Envelope Approach ...... 102

Comparison of Toxicity Test Protocols .............. 114

Evaluation of Pore Water Testing ................... 120

Distribution of P450 Reporter Gene System Response ...... 122

Determination of Relationships .......................... 124

Station Specific Sediment Quality Assessments ........... 136

Possible Sources of Pollutants at Prioritized Stations .. 142

Comparisons with Other Water Bodies ..................... 150

Limitations ............................................. 152

CONCLUSIONS .................................................. 153

RECOMMENDATIONS .............................................. 155

REFERENCES ................................................... 157
vii

LIST OF FIGURES

Figure 1 San Diego Bay Region Study Area ............... 2

Figure 2a San Diego Bay Sampling Blocks for Random 

 Stations ................................. 10

Figure 2b Mission Bay and Tijuana River Sampling Blocks 

 for Random Stations ...................... 11

Figure 3(a-d) San Diego Bay Region Sampling Locations ....... 13

Figure 4 Reference Envelope Approach ................... 39

Figure 5 ERM and PEL Exceedances ....................... 45

Figure 6(a-d) Copper in Sediment ............................ 47

Figure 7(a-d) Zinc in Sediment .............................. 51

Figure 8(a-d) Mercury in Sediment ........................... 55

Figure 9(a-d) HMW PAHs in Sediment .......................... 59

Figure 10(a-d) LMW PAHs in Sediment .......................... 63

Figure 11(a-d) Total PCBs in Sediment ........................ 68

Figure 12(a-d) Chlordane in Sediment ......................... 72

Figure 13 ERM & PEL Quotient Confidence Limits .......... 77

Figure 14 ERM Quotient vs. Benthics ..................... 78

Figure 15 Benthic Community Cluster Analysis ............ 88

Figure 16 Cluster Analysis with LA Harbor Comparison .... 89

Figure 17a Benthic Community Multi-Dimensional Scaling ... 90

Figure 17b Multi-Dimensional Scaling Using ERM Quotients . 90

Figure 18(a-d) Benthic Community Analysis .................... 97

Figure 19 CDF of Amphipod Toxicity Using Lab Controls ... 104

Figure 20 CDF for Urchin Toxicity Using Lab Controls ... 105

Figure 21(a-d) Amphipod Toxicity Using Lab Controls .......... 106

Figure 22(a-d) Urchin Development Toxicity Using Lab Controls 110

Figure 23(a-d) Amphipod Toxicity Using Reference Envelope .... 115

Figure 24 P450 RGS Response To Sediment Extracts ........ 123

Figure 25 P450 RGS vs Total PAHs ....................... 125

Figure 26 Toxicity vs. Chemical Concentration Plots ..... 135

Figure 27(a-d) Prioritized Stations of Concern .............. 143
viii

LIST OF TABLES

Table 1 Trace Metal Dry Weight Detection Limits .............. 21

Table 2 Pesticide Dry Weight Detection Limits ................ 22

Table 3 PCB and PAH Dry Weight Detection Limits .............. 22

Table 4 Reference Envelope Stations .......................... 41

Table 5 Sediment Quality Guidelines (ERMs & PELS) ............ 44

Table 6 Benthic Samples from San Diego Bay Region ........... 83

Table 7 Species List for San Diego Bay Region ................ 84

Table 8 Mean Species Densities ............................... 85

Table 9 Macrobenthic Community Variables ..................... 86

Table 10 Benthic Index Assessment by Site ..................... 94

Table 11 Benthic Index Assessment by Station .................. 96

Table 12 Percent Area Toxic Using CDFs ........................ 103

Table 13 Regressions for Chemistry and Amphipod Toxicity ...... 127

Table 14 Regressions for Grouped Navy Stations ................ 128

Table 15 Regressions for Grouped Commercial Stations .......... 129

Table 16 Regressions for Grouped Small Boat Stations .......... 130

Table 17 Regressions for Grouped River Stations ............... 131

Table 18 Regressions for Grouped Other Stations ............... 132

Table 19 Regressions for Adjusted Toxicity .................... 134

Table 20 Prioritization for Triad Stations .................... 138

Table 21 Prioritization for Non-Triad Stations- Toxicity ...... 139

Table 22 Prioritization for Non-Triad Stations- Chemistry ..... 141

LIST OF APPENDICES

Appendix A Data Base Description

Appendix B Analytical Chemistry Data

Section I Sampling Data

Section II Trace Metal Concentrations 

Section III PCB and Aroclor Concentrations

Section IV Pesticide Concentrations

Section V PAH Concentrations

Section VI Grain Size and Total Organic Carbon

Section VII Chemistry Summations and Quotients

Appendix C Benthic Community Analysis Data

Appendix D Toxicity Data

Section I Percent Amphipod Survival for Solid Phase

Section II Percent Normal Urchin Fertilization in Porewater

Section III Percent Normal Urchin Development in Porewater

Section IV Percent Abnormal Mitosis of Urchin in Porewater

Section V Percent Normal Abalone Development in

 Subsurface Water

Section VI Polychaete Growth and Survival for Solid Phase

Section VII Percent Normal Mussel Shell Development in 

 Subsurface Water

Section VIII Percent Normal Mussel Development in Pore Water

Appendix E P450 RGS Response

Appendix F Cumulative Distribution Frequencies Analysis
ix

LIST OF ABBREVIATIONS

AA Atomic Absorption

ASTM American Society for Testing Materials

AVS Acid Volatile Sulfide

BPTCP Bay Protection and Toxic Cleanup Program

CDF Cumulative Distribution Frequencies

CDFG California Department of Fish and Game

CH Chlorinated Hydrocarbon

COC Chain of Custody

COR Chain of Records

EDTA Ethylenediaminetetraacetic Acid

EMAP Environmental Monitoring and Assessment Program

ERL Effects Range Low

ERM Effects Range Median

ERMQ Effects Range Median Summary Quotient

EqP Equilibrium Partitioning Coefficient

FAAS Flame Atomic Absorption Spectroscopy

GC/ECD Gas Chromatograph Electron Capture Detection

GFAAS Graphite Furance Atomic Absorption Spectroscopy

HCl Hydrochloric Acid

HDPE High-density Polyethylene

HMW PAH High Molecular Weight Polynuclear Aromatic 

 Hydrocarbons

HNO3 Nitric Acid

HPLC/SEC High Performance Liquid Chromatography Size Exclusion

H2S Hydrogen Sulfide

IDORG Identification and Organizational Number

KCL Potassium Chloride

LC50 Lethal Concentration (to 50 percent of test

organisms)

LMW PAH Low Molecular Weight Polynuclear Aromatic Hydrocarbons

MDL Method Detection Limit

MDS Multi-Dimensional Scaling

MLML Moss Landing Marine Laboratories

MPSL Marine Pollution Studies Laboratory

NH3 Ammonia

NOAA National Oceanic and Atmospheric Administration

NOEC No Observed Effect Concentration

NS&T National Status and Trends Program

P450 Cytochrome P450 Enzyme System

PAH Polynuclear Aromatic Hydrocarbons

PCB Polychlorinated Biphenyl

PEL Probable Effects Level

PELQ Probable Effects Level Summary Quotient

PPE Porous Polyethylene

PVC Polyvinyl Chloride

QA Quality Assurance

QAPP Quality Assurance Project Plan

QC Quality Control

REF Reference

RGS P450 Reporter Gene System

RWQCB Regional Water Quality Control Board

SCCWRP Southern Calif. Coastal Waters Research Project
x

LIST OF ABBREVIATIONS (continued)

SPARC Scientific Planning and Review Committee

SQC Sediment Quality Criteria

SWRCB State Water Resources Control Board

T Temperature

TBT Tributyltin

TFE Tefzel Teflon®

TEL Threshold Effects Level

TIE Toxicity Identification Evaluation

TOC Total Organic Carbon

TOF Trace Organics Facility

UCSC University of California Santa Cruz

USEPA U.S. Environmental Protection Agency

WCS Whole Core Squeezing

 

Units

liter = 1 l

milliliter = 1 ml

microliter = 1 μl

gram = 1 g

milligram = 1 mg

microgram = 1 μg

nanogram = 1 ng

kilogram = 1 kg

1 part per thousand (ppt) = 1 mg/g

1 part per million (ppm) = 1 mg/kg, 1 μg/g

1 part per billion (ppb) = 1 μg/kg, 1 ng/g 
1

INTRODUCTION

Purpose

In 1992, the State Water Resources Control Board (SWRCB) and the

National Oceanic and Atmospheric Administration (NOAA) entered

into a three-year cooperative agreement to assess potential

adverse biological effects from sediments in coastal bays and

harbors of Southern California (SWRCB and NOAA, 1991, 1992,

1993). The study area for the three-year cooperative agreement 

extended south of the Palos Verdes Peninsula to the USA/Mexico

border. The majority of work focused on selected coastal bays,

harbors and lagoons where depth ranged from approximately 60

meters to the upper limit of the tidal range. In the first phase

of the study, data were collected, analyzed, and reported from

the Los Angeles/Long Beach areas (SWRCB and NOAA, 1994).

This report presents results from data collected in the San Diego

Bay area during the second and third years of the cooperative

agreement. The study was performed in San Diego Bay, Mission Bay,

San Diego River Estuary, and Tijuana River Estuary in southern

California (Figure 1).

The purposes of the present study were:

 1. Determine presence or absence of statistically

significant toxicity effects in representative areas of

the San Diego Bay Region;

 2. Determine relative degree or severity of observed

effects, and distinguish more severely impacted

sediments from less severely impacted sediments;

 3. Determine relative areal extent of significant toxicity

in the San Diego Bay Region;

 4. Determine relationships between pollutants and measures

of effects in these bays.

Programmatic Background and Needs

Due to the long history of human activity in San Diego Bay and

its surrounding waters, there is a need to assess any

environmentally detrimental effects which have been associated

with those activities. The cooperative agreement between NOAA and

SWRCB was designed to investigate these environmental effects by

evaluating the biological and chemical state of San Diego Bay

sediments. The methods used to assess environmental impacts

include sediment and interstitial water bioassays, sediment

chemistry analysis, and benthic community analysis. The study

areas included San Diego Bay, Mission Bay, Tijuana River Estuary,

and the San Diego River. Although these water bodies are

separated physically, and are quite different in character, for

simplicity they will often be referred to collectively as the

"San Diego Bay Region" in this report (Figure 1). The SWRCB and

NOAA have common programmatic needs for this research, however,

some differences exist. NOAA is mandated by Congress to conduct a
Figure 1

San Diego Bay Region Study Area

Mission Bay

North San Diego 

Bay

South San Diego

Bay

Tijuana River Estuary

Mid San Diego 

Bay

San Diego River Estuary
3

program of research and monitoring on marine pollution. Much of

this research is conducted through the National Status and Trends

(NS&T) Program and the Coastal Ocean Program. The NS&T Program

performs intensive regional studies on the magnitude and extent

of toxicant-associated bioeffects in selected coastal embayments

and estuaries. Areas chosen for these regional studies were those

in which pollutant concentrations indicate the greatest potential

for biological effect. These biological studies augment regular

chemical monitoring activities of the NS&T Program, and provide a

means for estimating the extent of toxicity associated with

measured concentrations of sediment pollutants.

The California Water Code, Division 7, Chapter 5.6, Section 13390

mandates the State Water Resources Control Board and the Regional

Water Quality Control Boards to provide the maximum protection of

existing and future beneficial uses of bays and estuarine waters

and to plan for remedial actions at those identified toxic hot

spots where the beneficial uses are being threatened by toxic

pollutants.

A cooperative agreement between NOAA and SWRCB has been

implemented through the Bay Protection and Toxic Cleanup Program

(BPTCP). Sediment characterization approaches currently used by

the BPTCP range from chemical or toxicity monitoring only, to

monitoring designs which attempt to generally correlate the

presence of pollutants with toxicity or benthic community

degradation. Studies were designed, managed, and coordinated by

the SWRCB's Bays and Estuaries Unit as a cooperative effort with

NOAA's Bioeffects Assessment Branch, and the California

Department of Fish and Game's (CDFG) Marine Pollution Studies

Laboratory. Funding was provided by the SWRCB and NOAA's Coastal

Ocean Program.

Research for the San Diego Bay Region involved toxicity testing

and chemical analysis of sediments and sediment pore water.

Toxicity tests and chemical analysis were performed using

aliquots of homogenized sediment samples collected synoptically

from each station, resulting in paired data. Analyses of benthic

community structure and P450 enzyme induction were also made on a

subset of the total number of stations sampled.

Field and laboratory work was accomplished under interagency

agreement with, and under the direction of, the CDFG. Sample

collections were performed by staff of the San Jose State

University Foundation at the Moss Landing Marine Laboratories,

Moss Landing, CA (MLML). Trace metals analyses were performed by

CDFG personnel at the trace metal facility at Moss Landing Marine

Laboratories. Synthetic organic pesticides, polycyclic aromatic

hydrocarbons (PAHs), and polychlorinated biphenyls (PCBs) were

analyzed at the UCSC trace organics analytical facility at Long

Marine Laboratory in Santa Cruz, California. MLML staff also

performed total organic carbon (TOC) and grain size analyses, as

well as benthic community analyses. Toxicity testing was

conducted by the University of California at Santa Cruz (UCSC)

staff at the CDFG toxicity testing laboratory at Granite Canyon,
4

California. P450 Reporter Gene System analyses were conducted by

Columbia Analytical Services in Carlsbad, CA.

Study Area

San Diego Bay

San Diego Bay is the southern-most embayment on the west coast of

the United States. It is located within the Southern California

Bight and is the largest embayment along the 1450 kilometer

stretch of coastline between San Francisco and Central Baja

California. Located 16 kilometers northwest of the Mexico border,

it is considered one of the finest natural harbors in the world.

This reputation is due mainly to its deep entrance and protection

from weather it provides ships. San Diego Bay lies entirely in

the county of San Diego, extending from the entrance at Point

Loma southward to the mouth of the Otay River.

San Diego Bay is a natural, nearly-enclosed, crescent-shaped

estuary that encompasses approximately 52 square kilometers. It

is approximately 24 kilometers (km) in length and varies from

0.4 km to 5.8 km in width. Depths in the Bay vary from 18 meters

near the mouth to less than 1 meter in the southern part of the

bay, with the average depth for the entire bay being slightly

more than 12 meters. The Bay is much deeper and narrower than it

was historically, due mainly to dredging of channels and filling

of nearshore areas.

San Diego Bay opens to the Pacific Ocean and is classified as an

estuarine system due to its fresh water dilution. The diversion

of the San Diego River to Mission Bay by the U.S. Army Corps of

Engineers in 1857 was the first major reduction of freshwater

input into the bay (Smith, 1977). Sweetwater River and the Otay

River were also main sources of freshwater for San Diego Bay,

although these sources have been greatly reduced over the years

as a result of dam construction, extensive ground water use, and

limited rainfall in recent years. Freshwater input is now limited

to periodic surface drainage from the metropolitan area and

intermittent flow from several rivers and creeks during periods

of rainfall. Because of the dry Mediterranean-like climate that

characterizes San Diego Bay, average annual rainfall in the Bay

is usually between 10 and 13 inches, the majority of which falls

between November and February.

Tides in San Diego Bay demonstrate marked variation between the

heights of two high tides and two low tides that occur daily,

classifying them as diurnal. The range between mean higher high

water (MHHW) and mean lower low water (MLLW) is 1.6 meters and

the extreme range of tides within the Bay is approximately 2.9

meters (Browning and Speth, 1973). Tidal currents are strongest

in the northern part of the Bay where surface velocities reach

2.9 knots on ebb tide and 2.2 knots on flood tide (U.S. Army

Corps of Engineers, 1973). Tidal currents are reduced

considerably in the shallower central and south bay areas.

Average tidal flushing for San Diego Bay is about 30% of the
5

entire Bay water volume exchanged per tidal cycle (12.5 hours). 

This volume of water is referred to as the tidal prism and in San

Diego Bay represents approximately 74,000,000 cubic meters. Tidal

flushing rates differ drastically between the Bay entrance and

South Bay. Complete tidal flushing for the South Bay requires

seven to fourteen days, whereas, the entrance of the Bay may only

require one to two days. It has been estimated over the last

century, tidal flushing in San Diego Bay has been reduced by 30%

due to channel dredging and landfill projects (Browning and

Speth, 1973).

San Diego Bay is a sedimentary environment with the bay floor and

bay margins characterized by sand, silt and clay deposits

(Peeling, 1974). Sand deposits are found near the Bay's mouth and

along western margins, while finer silt and clay deposits are

located on the eastern margins and at the southern end of the

Bay.

An early navigation chart issued by the U.S. Coastal Survey in

1859 shows an undredged Bay fifteen miles long with a channel

varying in depth from 22.2 meters decreasing to 3.6 meters. This

natural channel stretched for 13 kilometers from the tip of Point

Loma to the South Bay. Salt marshes existed at the mouths of

seven creeks and river tributaries.

The early residents of the San Diego Bay area were Native

Americans, who hunted and fished in the Bay; Spanish, Mexican,

and American ranchers, who traded hides and tallow; and the early

Yankee whalers who established camps in North Bay. These groups

appeared to have little impact on the water quality in the Bay.

By 1830 there were 16 American whaling vessels operating out of

San Diego Bay. The whaling industry reached its peak in 1871-72

when 55,000 gallons of oil and 200 tons of whalebone were shipped

from Point Loma. Americans participating in the New Town land

boom of the 1880's settled in the central San Diego Bay area,

site of the present downtown San Diego. This settlement soon

represented a considerable increase in the population of the area

as well as a dramatic threat to water quality in the Bay.

The Cuyamaca Dam and a flume were completed in 1888, diverting

freshwater from eastern mountains into what is now Chollas

Reservoir. Forty miles of sewers coupled with a sewage reservoir

and outfall located in San Diego Bay off Market street were also

completed in 1888. This sewage system marked the beginning of the

decline in water quality for the Bay. Conditions within the Bay

continued to decline because of the increase in population

(30,000 in 1901) and acceptance of the Bay as a major harbor for

the U.S. Navy and civilian commerce.

During the next four decades communications and aviation stations

were added and docking facilities expanded. Naval facilities

expanded greatly during World War II as business and industry

boomed. In 1940, the population had increased to 200,000 causing

a failure of the overloaded sewage collection and treatment

facilities. In 1943, raw or minimally treated sewage was being
6

discharged into the Bay from 15 outfalls. After World War II and

the Korean War, San Diego Bay was subject to the dumping of more

than 50 million gallons of sewage and industrial waste per day

(San Diego Interagency Water Quality Panel, 1989).

In 1950, the population of the San Diego metropolitan area had

increased to over 400,000. In an attempt to curtail the flow of

raw sewage into the Bay, San Diego and several neighboring

communities combined their sewage outfalls into one system.

Unfortunately, this new system was constantly operating on

overload and discharging directly into the Bay. Simultaneously,

the Bay received untreated industrial discharge from five fish

canneries, a large rendering operation, a kelp processing plant,

four aircraft manufacturing plants, several shipyards, and the

Pacific coast's largest naval base, naval air station, and

submarine base (San Diego Interagency Water Quality Panel, 1989).

The California Regional Water Quality Control Board was

established in 1950 (following the passage of the Dickey Act in

1949). Through extensive water sampling it was concluded that the

entire Bay had become contaminated, due to heavy loading of

domestic and industrial wastes. Dissolved oxygen concentrations

in the Bay had declined to about half normal levels and turbidity

in the water resulted in a visibility of less than 1 meter. Bait

and game fish had virtually disappeared from the Bay. Coliform

bacteria were routinely isolated from the Bay at significant

levels. In 1955, the State Board of Public Health and the San

Diego Department of Public Health declared much of the Bay

contaminated, and posted quarantine and warning signs along 10

miles of shoreline. By 1963, sludge deposits from the treatment

plant outfall were two meters deep, extended 200 meters seaward,

and along 9000 meters of the shoreline.

A report in the early 1950's from the Regional Board and the San

Diego Sewerage Survey report indicated sewage discharge into the

Bay was becoming a major problem which had to be corrected. In

1960, San Diego voters approved a bond ($42.5 million) which

allowed construction to begin on the Metropolitan Sewerage

System. In August of 1963, a massive collection, treatment, and

ocean disposal system began operation and by February, 1964,

domestic sewage disposal had been eliminated from San Diego Bay.

Following the completion of the new sewage treatment plant,

dissolved oxygen concentrations rose to an average of more than

5 parts per million, visibility increased to 2 meters, and

coliform bacteria counts dropped within the federal safety

standards. Plankton blooms were scarce and sludge deposits of

more than 30 cm were seldom reported. The sewage system currently

processes 170 million gallons of waste per day (City of San

Diego, 1995)

Routine sampling, beginning in the 1970's, revealed new

information regarding the presence of industrial wastes in the

Bay. Regulatory standards were developed for the protection of

humans and wildlife based on new sampling systems and more

refined analytical techniques. The conventional engineering and

bacteriological data gathered earlier did not adequately address
7

the issue of toxic waste in the Bay. During the late 1980's, the

press regarded San Diego Bay as being heavily contaminated,

particularly for PCBs. Although conditions in the Bay are similar

to other urban influenced embayments in the United States, San

Diego Bay has serious problems with chemical pollution. A number

of toxic hotspots in the Bay have been identified on lists of

water quality impairment such as Clean Water Act Section 303(d),

Section 319, Section 304(l) and Section 131.11.

Mission Bay

Mission Bay is located 9 kilometers north of Point Loma and

encompasses an area of 1860 hectares. It has two main

tributaries, Tecolote creek and Rose creek (Dexter, 1983).

Originally named False Bay because its entrance was near San

Diego Bay and occasionally fooled ship captains, it is now

considered a recreational small-craft harbor (United States Coast

Pilot, 1994). Prior to the development of Mission Bay park in

1946, Mission Bay was a natural estuary of over 2020 hectares of

salt marshes, tidal channels, and a shallow central bay. Between

1946 and 1962 major dredging within the Bay and modifications to

the San Diego River flood control channel gave way to its

present-day configuration. Today it is a highly modified lagoon

which receives freshwater input only during infrequent, heavy

rains. The major additions of freshwater into Mission Bay occur

at Rose Inlet, in the northeastern portion of the Bay, and

Tecolote Creek, in the southeast. Because of this limited amount

of freshwater, the salinities throughout the Bay do not change

markedly. Mean tidal range is 1.2 meters and the mean diurnal

range is 1.7 meters at the Bay entrance (Levin, 1983). 

As a result of circulation patterns within Mission Bay, a variety

of sediments are found. In the mouth of the Bay and near the main

channel, water movement is sufficient to maintain a sandy bottom.

In other parts of the Bay, such as Sail Bay and sites located

further east, sediments are muddy with a high silt and clay

content (Dexter, 1983).

Tecolote and Rose creeks carry urban pollutants such as oil,

grease, fertilizers, and high sediment loads into the back bay. 

Furthermore, sewer lines back up occasionally into the back bay.

 The lack of water circulation in the back bay allows these

pollutants to accumulate and has resulted in quarantines for

several months at a time (Marcus, 1989).

Tijuana River Estuary

The Tijuana River Estuary is located 16 kilometers southeast of

Point Loma. Although the estuary is situated entirely within the

boundaries of San Diego County, three-fourths of its watershed is

in Mexico. It is a wetland dominated estuary with no major

embayment, however, a series of channels allows for a relatively

narrow ocean connection (Herron, 1972). In the classification

scheme developed by Prichard (1967), Tijuana Estuary is

considered an intermittent coastal plain estuary due to the large
8

freshwater input during the winter wet season. During most years,

the river mouth has been open and tidal flushing has prevailed.

The intertidal area supports salt marsh vegetation (Salicornia

virginica, Spartina foliosa), whereas mudflats and sandflats

occupy only a small fraction of the estuary (Zedler et al.,

1992).

The Tijuana River Estuary has been altered substantially by 

natural and human disturbances. In the early 1900's, sewage

disposal practices led to dredging of the east-west channel in

order to connect an adjacent waste collecting lagoon with the

estuary. Dikes were then created to subdivide the lagoon into

three wastewater receiving ponds, however, these dikes were later

removed to increase tidal flow. Gravel extraction for street and

dike construction created isolated ponds within the estuary.

Long-term dumping and filling altered most of the peripheral

topography, while extensive damage to the southern half of the

estuary from military, agricultural, and horse-raising activities

is evident (Marcus, 1989).

Wastewater flow from Tijuana has been a serious threat to water

quality in the estuary. In 1988, approximately 30 million gallons

of sewage per day were produced while only 17 million gallons

were collected. The remaining 13 million gallons emptied directly

into the Tijuana River and estuary (Seamans, 1988). Breaks in the

Tijuana sewer line, which carried collected sewage to an ocean

outfall, were also common.

Recent U.S. projects have reduced the threat of sewage pollution.

 An interceptor on the Tijuana River, completed in early October

1991, diverts approximately 15 million gallons of sewage a day to

the San Diego wastewater facility (Zedler, 1992). A sewage

treatment plant is planned for the U.S. side of the border, and a

new ocean outfall is under evaluation.
9

METHODS

Sampling Design

Two basic sampling designs were used to meet both SWRCB's and

NOAA's goals. A directed point sampling design was required to

address SWRCB's need to identify specific toxic hot spots. A

stratified random sampling design was required to address NOAA's

need to evaluate spatial extent of pollution. This has resulted

in a data set of 350 samples collected between October, 1992 and

May, 1994. Of the 350 total samples, 229 were collected from

directed point sampled stations and 121 were collected from

randomly sampled stations.

When directed point sampling design was required, a two step

process was used. Areas of interest were identified, by regional

and state water board staff, for sampling during an initial

"screening phase". Station locations (latitude & longitude) were

predetermined by agreement with the SWRCB, NOAA, Regional Water

Quality Control Boards, and DFG personnel. Changing of the site

location during sediment collection was allowed only under the

following conditions:

 1. Lack of access to predetermined site,

 2. Inadequate or unusable sediment (i.e. rocks or gravel)

 3. Unsafe conditions

 4. Agreement of appropriate staff

This phase of work was intended to give a broad assessment of

toxicity throughout the San Diego Bay area using multiple test

species and toxicity endpoints. Fifty-six stations were sampled

during the period between October, 1992 and January, 1993.

Chemical analysis was performed on selected samples in which

toxicity results prompted further analysis. Stations which met

certain criteria during the screening phase, or during the random

sampling phase, were then selected for a second round of

sampling, termed the "confirmation phase". During this phase

sampling was replicated and chemical analysis of samples was more

extensive. In addition, benthic community analysis was performed

on all confirmation stations sampled during the summer of 1993.

Evidence from this two step process is used to establish a higher

level of certainty for stations which may later be identified as

"toxic hot spots".

Stratified random sampling began in March, 1993 and continued

through August, 1993, with a total of 121 stations sampled. The

San Diego Bay Region was stratified into areas of similar

physical characteristics or uses, such as transit channels,

anchorages, marinas, commercial shipping or military uses, and

designated as 95 blocks of known size (Figures 2a & 2b). Station

coordinates were chosen randomly within the boundaries of each

sampling block by USEPA Environmental Monitoring and Assessment

Program (USEPA-EMAP) personnel using a computer program developed

for that purpose. Eight alternate locations were chosen for

each block, a maximum of two of which were actually sampled

(Weisberg et al., 1993). This stratified random design "forces"
S(1-2) 5

AA

3

4

1 2

T(1-3)

GG(1-5)

R(1-5)

Q

O(7-14) Z

P

5

O(1-6)

7

4

N(1-2)

8

6

FF(1-8)

Y

J(1-3)

K&L(1-3)

M(1-3)

1

23

U(1-3)

DD(1-3)

EE(1-2)

CC4

I (1-2)

BB3

V (1-2)

H(1-2)

CC3

BB2

CC2

F(1-3)

X

CC1

BB1

G(1-3)

C(1-3)

E(1-3)

D(1-4)

Figure 2a

Sampling Blocks for Random Stations

San Diego Bay
A1

A2

A3

A4

A5

A9

A11

B1

B2

A6

A7

A8 A10

HH1

HH2

HH3

Figure 2b

Sampling Blocks for Random Stations

Mission Bay and San Diego River Estuary

Tijuana River Estuary
12

random samples to cover all areas of the Bay, whereas a pure

random design most likely would miss some areas and oversample

others. In the field, sampling was attempted at each designated

location (x1-x8), beginning with x1, until a sample was retrieved

which met sample acceptability criteria. For example, in block

FF2, Station number 93124 was sampled at the random location x1

while in block FF3, Station #93172 was sampled at random location

x4 because the grain size was too coarse at locations x1, x2 and

x3. Of the 121 stations sampled, ≈15% could not be sampled at the

random x1 location, due to the location being inaccessible by

boat because of obstructions, vessel moorings, piers or shallow

depths. Similarly, ≈3% were not sampled because the grain size

was too coarse at the x1 location. Samples were collected

successfully at alternate locations (x2, x3, x4, ...) for all

stations where x1 was not sampled. This sampling design allows

data from random stations to be used for calculation of areal

extent of toxicity in the San Diego Bay Region. Chemical analyses

were only performed on a limited number of random station

samples.

From the combined sampling designs, a total of 350 samples were

collected from 183 station locations in the San Diego Bay Region

(Figure 3(a-d)). Station locations which were sampled more than

once were always resampled at the original location using

navigational equipment and lineups. Bioassay tests, grain size

and total organic carbon analyses were performed on all 350

samples. Trace metal analysis was performed on 217 samples. Trace

synthetic organic analysis was performed on 229 samples. Benthic

community analysis was performed on 75 samples.

Sample Collection and Processing

Summary of Methods

Specific techniques used for collecting and processing samples

are described in this section. Because collection of sediments

influences the results of all subsequent laboratory and data

analyses, it was important that samples be collected in a

consistent and conventionally acceptable manner. Field and

laboratory technicians were trained to conduct a wide variety of

activities using standardized protocols to ensure comparability

in sample collection among crews and across geographic areas. 

Sampling protocols in the field followed the accepted procedures

of EMAP, NS&T, and ASTM and included methods to avoid crosscontamination; methods to avoid contamination by the sampling

activities, crew, and vessel; collection of representative

samples of the target surficial sediments; careful temperature

control, homogenization and subsampling; and chain of custody

procedures.

Cleaning Procedures

All sampling equipment (i.e., containers, container liners,

scoops, water collection bottles) was made from non-contaminating

materials and was precleaned and packaged protectively prior to

entering the field. Sample collection gear and samples were

handled only by personnel wearing non-contaminating
90071

93161

90028

90029

93216

93162

93217

90063

93138

90048

93141

90056

90104

90049

90102

93164

90023

93134

90026

93136

93149

93163

90103

93231

93188

90016

93169

93148

90001

90025

93199 93200 93202

93135

90027

93186

90101

93143

93153

93152

93139

93140

93166

93167

93165

93137

93168

90024

93232

93154

90050

93201

90055

Figure 3a

Sampling Locations

North San Diego Bay
93155

90004

93156

93142

93208

93207

93221

93205

90037

93206

93222

90002

90003

90039

93123

93146

90017

90018

90020 90021

93178

90005

90019

93182

90006

93211

93180

90030

90031

93213

93185

93223

90032 93212

90007

90022

93183

93214

93194

93147

90015

93195

93122

93124

90043

93157 90051

93192

93193

93145

93144

90038

93177

93125

93172

93173

93181

93210

93179

93126

93170

90014

93224

93215

93133

90008

93184

93226

93225

93171

93187

90009

93227

93228

Figure 3b

Sampling Locations

Mid San Diego Bay
93191

93190

93151

93197

90036

93128

93220

93219

90057

93159

90054

93158

93127

90013

93150

93203

93131

90053

90011

90052

90040

93230

90010

93229

93204

93132

90058

90041

90012

93196

93129

Figure 3c

Sampling Locations

South San Diego Bay
93115

93112

93114

93116

93108 93110

93109

93117

93107

93106

93105

93113

93111

93119

93175

93118

93120

93121

93174

Figure 3d

Sampling Locations

Mission Bay and San Diego River Estuary

Tijuana River Estuary
17

polyethylene gloves. All sample collection equipment (excluding

the sediment grab) was cleaned by using the following sequential

process:

Two-day soak and wash in Micro® detergent, three tapwater rinses, three deionized water rinses, a three-day

soak in 10% HCl, three ASTM Type II Milli-Q® water

rinses, air dry, three petroleum ether rinses, and air

dry.

All cleaning after the Micro® detergent step was performed in a

positive pressure "clean" room to prevent airborne contaminants

from contacting sample collection equipment. Air supplied to the

clean room was filtered.

The sediment grab was cleaned prior to entering the field, and

between sampling stations, by utilizing the following sequential

steps: a vigorous Micro® detergent wash and scrub, a sea-water

rinse, a 10% HCl rinse, and a methanol rinse. The sediment grab

was scrubbed with seawater between successive deployments at the

same station to remove adhering sediments from contact surfaces

possibly originating below the sampled layer. 

Sample storage containers were cleaned in accordance with the

type of analysis to be performed upon its contents. All

containers were cleaned in a positive pressure "clean" room with

filtered air to prevent airborne contaminants from contacting

sample storage containers.

Plastic containers (HDPE or TFE) for trace metal analysis media

(sediment, archive sediment, pore water, and subsurface water)

were cleaned by: a two-day Micro® detergent soak, three tap-water

rinses, three deionized water rinses, a three-day soak in 10% HCl

or HNO3, three Type II Milli-Q® water rinses, and air dry.

Glass containers for total organic carbon, grain size or

synthetic organic analysis media (sediment, archive sediment,

pore water, and subsurface water) and additional teflon sheeting

cap-liners were cleaned by: a two-day Micro® detergent soak,

three tap-water rinses, three deionized water rinses, a three-day

soak in 10% HCl or HNO3, three Type II Milli-Q® water rinses, air

dry, three petroleum ether rinses, and air dry.

Sediment Sample Collection

All sampling locations (latitude & longitude), whether altered in

the field or predetermined, were verified using a Magellan NAV

5000 Global Positioning System, and recorded in the field

logbook. The primary method of sediment collection was by use of

a 0.1m2 Young-modified Van Veen grab aboard a sampling vessel. 

Modifications include a non-contaminating Kynar coating which

covered the grab's sample box and jaws. After the filled grab

sampler was secured on the boat gunnel, the sediment sample was

inspected carefully. The following acceptability criteria were

met prior to taking sediment samples. If a sample did not meet

all the criteria, it was rejected and another sample was

collected.
18

 1. Grab sampler was not over-filled (i.e., the sediment surface

 was not pressed against the top of the grab).

 2. Overlying water was present, indicating minimal leakage. 

 3. Overlying water was not excessively turbid, indicating

 minimal sample disturbance.

 4. Sediment surface was relatively flat, indicating minimal

 sample disturbance.

 5. Sediment sample was not washed out due to an obstruction in

 the sampler jaws.

 6. Desired penetration depth was achieved (i.e., 10 cm).

 7. Sample was muddy (>30% fines), not sandy or gravelly.

 8. Sample did not include excessive shell, organic or man-made

 debris.

It was critical that sample contamination be avoided during

sample collection. All sampling equipment (i.e., siphon hoses,

scoops, containers) was made of non-contaminating material and

was cleaned appropriately before use. Samples were not touched

with un-gloved fingers. In addition, potential airborne

contamination (e.g., from engine exhaust, cigarette smoke) was

avoided. Before sub-samples from the grab sampler were taken, the

overlying water was removed by slightly opening the sampler,

being careful to minimize disturbance or loss of fine-grained

surficial sediment. Once overlying water was removed, the top

2 cm of surficial sediment was sub-sampled from the grab. 

Subsamples were taken using a precleaned flat bottom scoop. This

device allowed a relatively large sub-sample to be taken from a

consistent depth. When subsampling surficial sediments,

unrepresentative material (e.g., large stones or vegetative

material) was removed from the sample in the field. Small rocks

and other small foreign material remained in the sample. 

Determination of overall sample quality was determined by the

chief scientist in the field. Such removals were noted on the

field data sheet. For the sediment sample, the top 2 cm was

removed from the grab and placed in a pre-labeled polycarbonate

container. Between grabs or cores, the sediment sample in the

container was covered with a teflon sheet, and the container

covered with a lid and kept cool. When a sufficient amount of

sediment was collected, the sample was covered with a teflon

sheet assuring no air bubbles. A second, larger teflon sheet was

placed over the top of the container to ensure an air tight seal,

and nitrogen was vented into the container to purge it of oxygen.

If water depth did not permit boat entrance to a site (e.g.,

 <1 meter), divers sampled that site using sediment cores (diver

cores). Cores consisted of a 10 cm diameter polycarbonate tube,

30 cm in length, including plastic end caps to aid in transport.

Divers entered a study site from one end and sampled in one

direction, so as to not disturb the sediment with feet or fins. 

Cores were taken to a depth of at least 15 cm. Sediment was

extruded out of the top end of the core to the prescribed depth

of 2-cm, removed with a polycarbonate spatula and deposited into

a cleaned polycarbonate tub. Additional samples were taken with

the same seawater rinsed core tube until the required total

sample volume was attained. Diver core samples were treated the
19

same as grab samples, with teflon sheets covering the sample and

nitrogen purging. All sample acceptability criteria were met as

with the grab sampler.

Replicate benthic samples (n=5) were obtained at predetermined

sites from separate deployments of the sampler. Three of the

replicates were positioned according to the BPTCP sampling

protocol (e.g., located by previously assigned lat/long

coordinates), while the other two replicates were chosen within

the location range of the previous three samples. The coring

device was 10 cm in diameter and 14 cm in height, enclosing a

0.0075 m2 area. Corers were placed into sediment with minimum

disruption of the surface sediments, capturing essentially all

surface-active fauna as well as species living deeper in the

sediment. Corers were pushed about 12 cm into the sediment and

retrieved by digging along one side, removing the corer and

placing the intact sediment core into a pvc screening device. 

Sediment cores were sieved through a 0.5 mm screen and residues

(e.g., organisms and remaining sediments) were rinsed into prelabeled storage bags and preserved with a 10% formalin solution.

 After 3 to 4 days, samples were rinsed and transferred into 70%

isopropyl alcohol and stored for future taxonomy and enumeration.

Transport of Samples

Six-liter sample containers were packed (three to an ice chest)

with enough ice to keep them cool for 48 hours. Each container

was sealed in precleaned, large plastic bags closed with a cable

tie to prevent contact with other samples or ice or water. Ice

chests were driven back to the laboratory by the sampling crew or

flown by air freight within 24 hours of collection.

Homogenization and Aliquoting of Samples

Samples remained in ice chests (on ice, in double-wrapped plastic

bags) until the containers were brought back to the laboratory

for homogenization. All sample identification information

(station numbers, etc.) was recorded on Chain of Custody (COC)

and Chain of Record (COR) forms prior to homogenizing and

aliquoting. A single container was placed on plastic sheeting

while also remaining in original plastic bags. The sample was

stirred with a polycarbonate stirring rod until mud appeared

homogeneous.

All prelabeled jars were filled using a clean teflon or

polycarbonate scoop and stored in freezer/refrigerator (according

to media/analysis) until analysis. The sediment sample was

aliquoted into appropriate containers for trace metal analysis,

organic analysis, pore water extraction, and bioassay testing. 

Samples were placed in boxes sorted by analysis type and leg

number. Sample containers for sediment bioassays were placed in

a refrigerator (4oC) while sample containers for sediment

chemistry (metals, organics, TOC and grain size) were stored in a

freezer (-20oC). 

Procedures for the Extraction of Pore Water

The BPTCP primarily used whole core squeezing to extract pore

water. The whole core squeezing method, developed by Bender et
20

al. (1987), utilizes low pressure mechanical force to squeeze

pore water from interstitial spaces. The following squeezing

technique was a modification of the original Bender design with

some adaptations based on the work of Fairey (1992), Carr et al.

(1989), and Long and Buchman (1989). The squeezer's major

features consist of an aluminum support framework, 10 cm i.d.

acrylic core tubes with sampling ports and a pressure regulated

pneumatic ram with air supply valves. Acrylic subcore tubes were

filled with approximately 1 liter of homogenized sediment and

pressure was applied to the top piston by adjusting the air

supply to the pneumatic ram. At no time during squeezing did air

pressure exceed 200 psi. A porous prefilter (PPE or TFE) was

inserted in the top piston and used to screen large (> 70

microns) sediment particles. Further filtration was accomplished

with disposable TFE filters of 5 microns and 0.45 microns in-line

with sample effluent. Sample effluent of the required volume was

collected in TFE containers under refrigeration. Pore water was

subsampled in the volumes and specific containers required for

archiving, chemical or toxicological analysis. To avoid

contamination, all sample containers, filters and squeezer

surfaces in contact with the sample were plastics (acrylic, PVC,

and TFE) and cleaned with previously discussed clean techniques.

Chain of Records & Custody

Chain-of-records documents were maintained for each station. 

Each form was a record of all sub-samples taken from each sample.

 IDORG (a unique identification number for only that sample),

station numbers and station names, leg number (sample collection

trip batch number), and date collected were included on each

sheet. A Chain-of-Custody form accompanied every sample so that

each person releasing or receiving a subsample signed and dated

the form. 

Authorization/Instructions to Process Samples

Standardized forms entitled "Authorization/Instructions to

Process Samples" accompanied the receipt of any samples by any

participating laboratory. These forms were completed by DFG

personnel, or its authorized designee, and were signed and

accepted by both the DFG authorized staff and the staff accepting

samples on behalf of the particular laboratory. The forms

contain all pertinent information necessary for the laboratory to

process the samples, such as the exact type and number of tests

to run, number of laboratory replicates, dilutions, exact

eligible cost, deliverable products (including hard and soft copy

specifications and formats), filenames for soft copy files,

expected date of submission of deliverable products to DFG, and

other information specific to the lab/analyses being performed.

Trace Metals Analysis of Sediments

Summary of Methods

Trace Metals analyses were conducted at the California Department

of Fish and Game's (CDFG) Trace Metals Facility at Moss Landing,

CA. Table 1 indicates the trace metals analyzed and lists method

detection limits for sediments. These methods were modifications
21

of those described by Evans and Hanson (1993) as well as those

developed by the CDFG (California Department of Fish and Game,

1990). Samples were selected for chemical analyses by SWRCB staff

based on results from toxicity tests.

Analytes and Detection Limits

Table 1 - Trace Metal Detection Limits in Sediments (μg/g, dry

weight).

 Aluminum 1 Antimony 0.1

 Arsenic 0.1 Cadmium 0.01

 Chromium 0.1 Copper 0.1

 Iron 0.1 Lead 0.1

 Manganese 0.05 Mercury 0.03

 Nickel 0.1 Selenium 0.2

 Silver 0.01 Tin 0.02

 Tributyltin 0.013 Zinc 0.05

Sediment Digestion Procedures

One gram aliquot of sediment was placed in a pre-weighed Teflon

vessel, and one ml concentrated 4:1 nitric:perchloric acid

mixture was added. The vessel was capped and heated in a vented

oven at 1300 C for four hours. Three ml Hydrofluoric acid were

added to vessel, recapped and returned to oven overnight. Twenty

ml of 2.5% boric acid were added to vessel and placed in oven for

an additional 8 hours. Weights of vessel and solution were

recorded, and solution transfered to 30 ml polyethylene bottles.

Atomic Absorption Methods

Samples were analyzed by furnace AA on a Perkin-Elmer Zeeman 3030

Atomic Absorption Spectrophotometer, with an AS60 auto sampler,

or a flame AA Perkin Elmer Model 2280. Samples, blanks, matrix

modifiers, and standards were prepared using clean techniques

inside a clean laboratory. ASTM Type II water and ultra clean

chemicals were used for all standard preparations. All elements

were analyzed with platforms for stabilization of temperatures. 

Matrix modifiers were used when components of the matrix

interferes with adsorption. The matrix modifier was used for Sn,

Sb and Pb. Continuing calibration check standards (CLC) were

analyzed with each furnace sheet, and calibration curves were run

with three concentrations after every 10 samples. Blanks and

standard reference materials, MESS1, PACS, BCSS1 or 1646 were

analyzed with each set of samples for sediments.

Trace Organic Analysis of Sediments (PCBs, Pesticides, and PAHs)

Summary of Methods

Analytical sets of 12 samples were scheduled such that extraction

and analysis will occur within a 40 day window. The methods

employed by the UCSC-TOF were modifications of those described by

Sloan et al. (1993). Tables 2 and 3 indicate the pesticides,

PCBs, and PAHs currently analyzed and list method detection

limits for sediments on a dry weight basis.
22

Analytes and Detection Limits

Table 2. Organochlorine Pesticides Analyzed and Their Detection

Limits in Sediment, ng/g dry weight.

Aldrin 0.5

cis-Chlordane 0.5

trans-Chlordane 0.5

alpha-Chlordene 0.5

gamma-Chlordene 0.5

Chlorpyrifos 1.0

Dacthal 0.2

o,p'-DDD 1.0

p,p'-DDD 0.4

o,p'-DDE 1.0

p,p'-DDE 1.0

p,p'-DDMS 3.0

p,p'-DDMU 2.0

o,p'-DDT 1.0

p,p'-DDT 1.0

p,p'-Dichlorobenzophenone 3.0

Dieldrin 0.5

Endosulfan I 0.5

Endosulfan II 1.0

Endosulfan sulfate 2.0

Endrin 2.0

Ethion 2.0

alpha-HCH 0.2

beta-HCH 1.0

gamma-HCH 0.2

delta-HCH 0.5

Heptachlor 0.5

Heptachlor Epoxide 0.5

Hexachlorobenzene 0.2

Methoxychlor 1.5

Mirex 0.5

cis-Nonachlor 0.5

trans-Nonachlor 0.5

Oxadiazon 2.0

Oxychlordane 0.5

Toxaphene 10

Table 3. PCB Congeners and PAHs Analyzed and Their Detection

Limits in Sediment, ng/g dry weight.

NIST Congeners:

PCB Congener 8 PCB Congener 128

PCB Congener 18 PCB Congener 138

PCB Congener 28 PCB Congener 153

PCB Congener 44 PCB Congener 170

PCB Congener 52 PCB Congener 180

PCB Congener 66 PCB Congener 187

PCB Congener 87 PCB Congener 195

PCB Congener 101 PCB Congener 206
23

Table 3 (cont.). PCB Congeners and PAHs Analyzed and Their

Detection Limits in Sediment, ng/g dry weight.

PCB Congener 105 PCB Congener 209

PCB Congener 118

Additional Congeners:

PCB Congener 5 PCB Congener 137

PCB Congener 15 PCB Congener 149

PCB Congener 27 PCB Congener 151

PCB Congener 29 PCB Congener 156

PCB Congener 31 PCB Congener 157

PCB Congener 49 PCB Congener 158

PCB Congener 70 PCB Congener 174

PCB Congener 74 PCB Congener 177

PCB Congener 95 PCB Congener 183

PCB Congener 97 PCB Congener 189

PCB Congener 99 PCB Congener 194

PCB Congener 110 PCB Congener 201

PCB Congener 132 PCB Congener 203

All individual PCB Congener detection limits were 1

ng/g dry weight.

Aroclors:

Aroclor 5460 50

Polycyclic Aromatic Hydrocarbons

Naphthalene 5

2-Methylnaphthalene 5

1-Methylnaphthalene 5

Biphenyl 5

2,6-Dimethylnaphthalene 5

Acenaphthylene 5

Acenaphthene 5

2,3,5-Trimethylnaphthalene 5

Fluorene 5

Phenanthrene 5

Anthracene 5

1-Methylphenanthrene 5

Fluoranthrene 5

Pyrene 5

Benz[a]anthracene 5

Chrysene 5

Benzo[b]fluoranthrene 5

Benzo[k]fluoranthrene 5

Benzo[e]pyrene 5

Benzo[a]pyrene 5

Perylene 5

Indo[1,2,3-cd]pyrene 5

Dibenz[a,h]anthracene 5

Benzo[ghi]perylene 5
24

Extraction and Analysis

Samples were removed from the freezer and allowed to thaw. A 10

gram sample of sediment was removed for chemical analysis and an

independent 10 gram aliquot was removed for dry weight

determinations. The dry weight sample was placed into a preweighed aluminum pan and dried at 110°C for 24 hours. The dried

sample was reweighed to determine the sample’s percent moisture.

 The analytical sample was extracted 3 times with methylene

chloride in a 250-mL amber Boston round bottle on a modified rock

tumbler. Prior to rolling, sodium sulfate, copper, and

extraction surrogates were added to the bottle. Sodium sulfate

dehydrates the sample allowing for efficient sediment extraction.

 Copper, which was activated with hydrochloric acid, complexes

free sulfur in the sediment.

After combining the three extraction aliquots, the extract was

divided into two portions, one for chlorinated hydrocarbon (CH)

analysis and the other for polycyclic aromatic hydrocarbon (PAH)

analysis.

The CH portion was eluted through a silica/alumina column,

separating the analytes into two fractions. Fraction 1 (F1) was

eluted with 1% methylene chloride in pentane and contains > 90%

of p,p'-DDE and < 10% of p,p'-DDT. Fraction 2 (F2) analytes were

eluted with 100% methylene chloride. The two fractions were

exchanged into hexane and concentrated to 500 μL using a

combination of rotary evaporation, controlled boiling on tube

heaters, and dry nitrogen blow downs.

F1 and F2 fractions were analyzed on Hewlett-Packard 5890 Series

gas chromatographs utilizing capillary columns and electron

capture detection (GC/ECD). A single 2 μl splitless injection

was directed onto two 60m x 0.25mm i.d. columns of different

polarity (DB-17 & DB-5; J&W Scientific) using a glass Y-splitter

to provide a two dimensional confirmation of each analyte. 

Analytes were quantified using internal standard methodologies. 

The extract’s PAH portion was eluted through a silica/alumina

column with methylene chloride. It then underwent additional

cleanup using size-exclusion high performance liquid

chromatography (HPLC/SEC). The collected PAH fraction was

exchanged into hexane and concentrated to 250 μL in the same

manner as the CH fractions.

Total Organic Carbon Analysis of Sediments

Summary of Methods

Samples were received in the frozen state and allowed to thaw at

room temperature. Source samples were gently stirred and subsamples were removed with a stainless steel spatula and placed in

labeled 20 ml polyethylene scintillation vials. Approximately

5 grams equivalent dry weight of the wet sample was sub-sampled.
25

Sub-samples were treated with two, 5 ml additions of 0.5 N,

reagent grade HCl to remove inorganic carbon (CO-3), agitated,

and centrifuged to a clear supernate. Some samples were retreated

with HCl to remove residual inorganic carbon. The evolution of

gas during HCl treatment indicates the direct presence of

inorganic carbon (CO-3). After HCl treatment and decanting,

samples were washed with approximately 15 ml of deionizeddistilled water, agitated, centrifuged to a clear supernate, and

decanted. Two sample washings were required to remove weight

determination and analysis interferences.

Prepared samples were placed in a 60° C convection oven and

allowed to come to complete dryness (approx. 48 hrs.). Visual

inspection of the dried sample before homogenization was used to

ensure complete removal of carbonate containing materials, (shell

fragments). Two 61 mm (1/4") stainless steel solid balls were

added to the dried sample, capped and agitated in a commercially

available ball mill for three minutes to homogenize the dried

sample.

A modification of the high temperature combustion method,

utilizing a Weatstone bridge current differential was used in a

commercially available instrument, (Control Equipment Co., 440

Elemental Analyzer) to determine carbon and nitrogen

concentrations. The manufactures suggested procedures were

followed. The methods are comparable to the validation study of

USEPA method MARPCPN I. Two to three aliquotes of 5-10 mg of

dried prepared sub-sample were used to determine carbon and

nitrogen weight percent values. Calibration of the instrument was

with known standards using Acetanilide or L-Cystine. Detection

limits are 0.2 ug/mg, carbon and 0.01 ug/mg nitrogen dry weight.

The above methods and protocols are modifications of several

published papers, reference procedures and analytical

experimentation experience (Franson, 1981; Froelich, 1980; Hedges

and Stern, 1983; MARPCPN I, 1992).

Quality Control/Quality Assurance

Quality control was tested by the analysis of National Research

Council of Canada Marine Sediment Reference Material, BCSS-1 at

the beginning and end of each sample analysis set (20-30

individual machine analyses). All analyzed values were within

suggested criteria of + 0.09% carbon (2.19% Average). Nitrogen

was not reported on the standard data report, but was accepted at

+ 0.008% nitrogen (0.195% Average) from the EPA study. Quality

assurance was monitored by re-calibration of the instrument every

twenty samples and by the analysis of a standard as a unknown and

comparing known theoretical percentages with resultant analyzed

percentages. Acceptable limits of standard unknowns were less

than + 2%. Duplicate or triplicate sample analysis variance

(standard deviation/mean) greater than 7% is not accepted. 

Samples were re-homogenized and re-analyzed until the variance

between individual runs fell below the acceptable limit of 7.0%.
26

Grain Size Analysis of Sediments

Summary of Methods

The procedure used combined wet and dry sieve techniques to

determine particle size of sediment samples. Methods follow those

of Folk (1974).

Sample Splitting and Preparation

Samples were thawed and thoroughly homogenized by stirring with a

spatula. Spatulas were rinsed of all adhering sediment between

samples. Size of the subsample for analysis was determined by

the sand/silt ratio of the sample. During splitting, the

sand/silt ratio was estimated and an appropriate sample weight

was calculated. Subsamples were placed in clean, pre-weighed

beakers. Debris was removed and any adhering sediment was washed

into the beaker.

Wet Sieve Analysis (separation of coarse and fine fraction) 

Beakers were placed in a drying oven and sediments were dried at

less than 55°C until completely dry (approximately three days). 

Beakers were removed from drying oven and allowed to equilibrate

to room temperature for a least a half-hour. Each beaker and its

contents were weighed to the nearest .01 g. This weight minus the

empty beaker weight was the total sample weight. Sediments in

beakers were disaggregated using 100 ml of a dispersant solution

in water (such as 50g Calgon/L water) and the sample was stirred

until completely mixed and all lumps disappear. The amount and

concentration of dispersant used was recorded on the data sheet

for each sample. Sample beakers were placed in an ultrasonic

cleaner for 15 minutes for disaggregation. Sediment dispersant

slurry was poured into a 63 μm (ASTM #230, 4 phi) stainless steel

or brass sieve in a large glass funnel suspended over a 1L

hydrometer cylinder by a ring stand. All fine sediments were

washed through the sieve with water. Fine sediments were

captured in a 1L hydrometer cylinder. Coarse sediments remaining

in sieve were collected and returned to the original sample

beaker for quantification.

Dry Sieve Analysis (coarse fraction)

The coarse fraction was placed into a preweighed beaker, dried at

55-65°C, allowed to acclimate, and then weighed to 0.01 g. This

weight, minus the empty beaker weight, was the coarse fraction

weight. The coarse fraction was poured into the top sieve of a

stack of ASTM sieves having the following sizes: No. 10 (2.0 mm),

18 (1.0 mm), 45 (0.354 mm), 60 (0.25 mm), 80 (0.177 mm), 120

(0.125 mm), and 170 (0.088 mm). The stack was placed on a

mechanical shaker and shaken at medium intensity for 15 minutes.

 After shaking, each sieve was inverted onto a large piece of

paper and tapped 5 times to free stuck particles. The sieve

fractions were added cumulatively to a weighing dish, and the

cumulative weight after each addition determined to 0.01g. The

sample was returned to its original beaker, and saved until

sample computations were completed and checked for errors.
27

Analytical Procedures

Fractional weights and percentages for various particle size

fractions were calculated. If only wet sieve analysis was used,

weight of fine fraction was computed by subtracting coarse

fraction from total sample weight, and percent fine composition

was calculated using fine fraction and total sample weights. If

dry sieve was employed as well, fractional weights and

percentages for the sieve were calculated using custom software

on a Macintosh computer. Calibration factors were stored in the

computer.

Benthic Community Analysis

Summary of Methods

Each catalogued sample was processed individually in the

laboratory to obtain an accurate assessment of species diversity

and abundance. All macroinvertebrates were sorted from residues

under a dissecting microscope, identified to lowest possible

taxon, and counted. Laboratory processing of benthic cores

consists of both rough and fine sorting. Initial sorting

separates animals into large taxonomic groups such as

polychaetes, crustaceans, mollusks and other (e.g., phoronids). 

Bound laboratory logbooks were maintained and used to record

number of samples processed by each technician, as well as

results of any sample resorts, if necessary. Sorters were

required to sign and date a Milestone Progress Checksheet for

each replicate sample processed. Specimens of similar taxonomic

groups were placed in vials and labelled internally and

externally with project, date collected, site/station

information, and IDORG. Samples were selected for benthic

community analysis by SWRCB staff based on results from toxicity

tests.

In-house senior taxonomists and outside specialists processed and

verified the accuracy of species identification and enumeration.

 An archived voucher specimen collection was established at this

time.

Toxicity Testing

Summary of Methods

All toxicity tests were conducted at the California Department of

Fish and Game's Marine Pollution Studies Laboratory (MPSL) at

Granite Canyon. Toxicity tests were conducted by personnel from

the Institute of Marine Sciences, University of California, Santa

Cruz. 

Pore Water Samples

Once at MPSL, frozen pore water samples were stored in the dark,

at -120C, until required for testing. Experiments performed by

the U.S. National Biological Survey have shown no effects of

freezing porewater upon the results of toxicity tests (Carr et

al., 1995). Samples were thawed on the day of a test, and pH,
28

temperature, salinity, and dissolved oxygen were measured in all

samples to verify water quality criteria were within the limits

defined for test protocol. Pore water samples with salinities

outside specified ranges for each protocol were adjusted to

within the acceptable range. Salinities were increased by the

addition of hypersaline brine, 60 to 80 parts per thousand (ppt),

drawn from partially frozen seawater. Dilution water consisted

of Granite Canyon seawater (32 to 34 ppt). Water quality

parameters were measured at the beginning and end of each test.

Dissolved oxygen concentrations and pH were measured using an

Orion EA940 expandable ion analyzer. Salinity was measured with

a refractometer. Temperature of each sample was measured with a

mercury thermometer. 

Measurement of Ammonia and Hydrogen Sulfide

Total ammonia concentrations were measured using an Orion Model

95-12 Ammonia Electrode. The concentration of unionized ammonia

was derived from the concentration of total ammonia using the

following equation (from Whitfield 1974, 1978):

[NH3] = [total ammonia] x ((1 + antilog(pKa°- pH))-1),

where pKa° is the stoichiometric acidic hydrolysis constant for

the test temperature and salinity. Values for pKa°were

experimentally derived by Khoo et al. (1977). The method

detection limit for total ammonia was 0.1 mg/L.

Total sulfide concentrations were measured using an Orion Model

94-16 Silver/Sulfide Electrode, except that samples tested after

February, 1994, were measured on a spectrophotometer using a

colorimetric method (Phillips et al. in press). The

concentration of hydrogen sulfide was derived from the

concentration of total sulfide by using the following equation

(ASCE 1989):

[H2S] = [S2-] x (1 - ((1 + antilog(pKa°- pH))-1)),

where temperature and salinity dependent pKa° values were taken

from Savenko (1977). The method detection limit for total

sulfide was 0.1 mg/L for the electrode method, and 0.01 mg/L for

the colorimetric method. Values and corresponding detection

limits for unionized ammonia and hydrogen sulfide were an order

of magnitude lower than those for total ammonia and total

sulfide, respectively.

Subsurface Water Samples

The subsurface water toxicity tests are water column toxicity

tests (abalone development, mussel development, etc..) performed

on water collected with the modified Van Veen grab. A water

sample bottle on the frame of the grab and a stopper is pulled as

the jaws of the grab close for a sediment sample. The water

sample is consequently collected approximately 0.5 meters above

the bottom. Subsurface water samples were held in the dark at 40C

until testing. Toxicity tests were initiated within 14 days of
29

the sample collection date. Water quality parameters, including

ammonia and sulfide concentrations, were measured in one

replicate test container from each sample in the overlying water

as described above. Measurements were taken at the beginning and

end of all tests.

Sediment Samples

Bedded sediment samples were held at 40C until required for

testing. All Rhepoxynius abronius and Neanthes arenaceodentata

solid phase sediment tests were initiated within 14 days of the

sample collection date. All sediment samples were processed

according to procedures described in ASTM (1992). Water quality

parameters, including ammonia and sulfide concentrations, were

measured in one replicate test container from each sample in the

overlying water as described above. Measurements were taken at

the beginning and end of all Rhepoxynius and Neanthes tests, and

during overlying water renewals in the Neanthes tests. 

Sea Urchin Larval Development Test

The sea urchin (Strongylocentrotus purpuratus) larval development

test was conducted on all pore water samples. Details of the

test protocol were given in Dinnel (1992). A brief description

of the method follows. 

Sea urchins were collected from the Monterey County coast near

Granite Canyon, and held at MPSL at ambient seawater temperature

and salinity (approx. 32±2 ppt) until testing. Adult sea urchins

were held in complete darkness to preserve gonadal condition. On

the day of a test, urchins were induced to spawn in air by

injection with 0.5M KCl. Eggs and sperm collected from the

urchins were mixed in seawater at a 500 to 1 sperm to egg ratio,

and embryos were distributed to test containers within 1 hour of

fertilization. Test containers were polyethylene-capped, seawater leached, 20ml glass scintillation vials containing 5 mls of

pore water. Each test container was inoculated with

approximately 150 embryos (30/ml). All pore water samples were

tested at three concentrations: 100, 50 and 25% pore water, each

having three replicates. Pore water samples were diluted when

necessary with one micron-filtered Granite Canyon seawater. 

Laboratory controls were included with each set of samples

tested. Controls include a dilution water control consisting of

Granite Canyon seawater, a brine control with all samples that

require brine adjustment, and in some tests a frozen seawater

control consisting of Granite Canyon seawater that has been

frozen along with the pore water samples. Tests were conducted

at ambient seawater salinity (usually 33±2 ppt). A positive

control reference test was conducted concurrently with each pore

water test using a dilution series of copper chloride as a

reference toxicant.

After an exposure of 72 or 96 hours (no difference in results was

detectable between these periods), larvae were fixed in 5%

buffered formalin. Approximately 100 larvae in each container

were examined under an inverted light microscope at 100x to

determine the proportion of normally developed larvae as
30

described by Dinnel (1992). Visual clues used to identify embryos

as normal included development of skeletal rods (spicules) that

extend beyond half the length of the larvae and normal

development of a three part gut. Slow growing embryos were

considered abnormal.

Percent normal development was calculated as:

 (Number of normally developed larvae) X 100 

 (Total number of observed larvae + number of abnormal

larvae)

Sea Urchin Fertilization Test

The sea urchin (Strongylocentrotus purpuratus) fertilization test

was conducted on pore water samples. Details of the test

protocol were described in Dinnel et al. (1987).

Sea urchins were from the same stock described for the sea urchin

larval development test. On the day of a test, urchins were

induced to spawn in air by injection with 0.5M KCl. Sperm were

exposed in test containers for sixty minutes before approximately

1000 eggs were added. After twenty minutes of fertilization, the

test was fixed in a 5% buffered formalin solution. A constant

sperm to egg ratio of 500 to 1 was used in all tests. This ratio

maintained fertilization in the 70-90% range required by the test

protocol. Fertilization was determined by the presence or absence

of a fertilization membrane (raised chorion completely

surrounding the egg). Test containers were polyethylene-capped,

sea-water leached, 20ml glass scintillation vials containing 5

mls of pore water. All pore water samples were tested at three

concentrations: 100, 50 and 25% pore water, each having three

replicates. Pore water samples were diluted with one micronfiltered Granite Canyon seawater. Laboratory controls were

included with each set of samples tested. Controls included a

dilution water control consisting of Granite Canyon seawater, a

brine control with all samples that require brine adjustment, and

in some tests a frozen seawater control consisting of Granite

Canyon seawater that has been frozen along with the pore water

samples. Tests were conducted at ambient seawater salinity

(usually 33±2 ppt). A positive control reference test was

conducted concurrently with each pore water test using a dilution

series of copper chloride as a reference toxicant. All eggs in

each container were examined under an inverted light microscope

at 100x, and counted as either fertilized or unfertilized.

Percent fertilization was calculated as:

 (Number of fertilized eggs) x 100 

 (Number of fertilized eggs + number of unfertilized eggs)

Sea Urchin Cytogenetics Test

Analysis of cytogenetic abnormalities using sea urchin embryos

followed methods described in Hose (1985). Sea urchin embryos

were exposed to pore water for 48 hours then preserved in 5%

buffered formalin. Embryos were placed on a clean glass
31

microscope slide and excess formalin removed with tissue paper. 

Embryos were then treated with a few drops of aceto-orcein stain

(19 parts aceto-orcein:one part propionic acid) for approximately

1 to 3 minutes, and a cover slip was then applied to the darkly

stained embryos. Excess stain was removed by blotting, and

embryos were compressed into a monolayer by application of direct

pressure. Embryo monolayer preparations were observed under oil

immersion using either an Olympus BH2 or Tiyoda light microscope

at 100x magnification. Cytogenetic abnormalities were observed

in mitotic cells in anaphase and telophase. Possible aberrations

observed followed those described in Hose (1985), including:

stray or lagging chromosomes, accentric or attached chromosome

fragments, and translocated or side-arm bridges . Because a

majority of the embryos exposed to the 100 and 50% pore water

concentrations displayed gross developmental abnormalities,

mitotic aberrations were generally assessed using embryos exposed

to 25% pore water.

Red Abalone Larval Development Test

The red abalone (Haliotis rufescens) larval development test was

conducted on all subsurface water samples. Details of the test

protocol were described in Anderson et al. (1990). The following

was a brief description of the method. Adult male and female

abalone were induced to spawn separately using a dilute solution

of hydrogen peroxide in sea water. Fertilized eggs were

distributed to the test containers within 1 hour of

fertilization. Test containers were polyethylene-capped,

seawater leached scintillation vials containing 10 mls of sample

water. Each of five replicate test containers were inoculated

with 100 embryos (10/ml).

Positive control reference tests using zinc sulfate as a

reference toxicant were conducted concurrently with each batch of

samples. A negative sea water control consisting of one micronfiltered Granite Canyon seawater was tested along with subsurface water samples and zinc concentrations. After 48 hours of

exposure, developing larvae were fixed in 5% buffered formalin. 

Approximately 100 larvae in each container were examined under an

inverted light microscope at 100x to determine the proportion of

veliger larvae with normal shells as described in Anderson et al.

(1990). 

Percent normal development was calculated as:

 (Number of normally developed larvae) x 100 

 Total number of observed larvae

Amphipod Tests

Solid-phase sediment sample toxicity was assessed using the 10-

day amphipod survival toxicity test protocol for Rhepoxynius

abronius (ASTM 1993).

All test organisms were obtained from Northwest Aquatic Sciences

in Yaquina Bay, Oregon. Amphipods were separated into groups of

approximately 100 each, placed in polyethylene boxes containing
32

Yaquina Bay collection site sediment, and then shipped on ice via

overnight courier. Upon arrival at Granite Canyon, the amphipods

were acclimated slowly (<2 ppt per day) to 28 ppt sea water

(T =150C). Once acclimated to 28 ppt, the animals were held for

an additional 48 hours prior to inoculation into the test

containers. 

Test containers were one liter glass beakers or jars containing

two cm of sediment and filled to the 700 ml line with seawater

adjusted to 28 ppt using spring water or distilled well water. 

Test sediments were not sieved for indigenous organisms prior to

testing although at the conclusion of the test, the presence of

predators was noted and recorded on the data sheet. Test sediment

and overlying water were allowed to equilibrate for 24 hours,

after which 20 amphipods were placed in each beaker along with 28

ppt seawater to fill test containers to the one liter line. Test

chambers were aerated gently and illuminated continuously at

ambient laboratory light levels. 

Five laboratory replicates of each sample were tested for ten

days. A negative sediment control consisting of five lab

replicates of Yaquina Bay home sediment was included with each

sediment test. After ten days, the sediments were sieved through

a 0.5 mm Nytex screen to recover the test animals, and the number

of survivors was recorded for each replicate.

Positive control reference tests were conducted concurrently with

each sediment test using cadmium chloride as a reference

toxicant. For these tests, amphipod survival was recorded in

three replicates of four cadmium concentrations after a 96 hour

water-only exposure. A negative seawater control consisting of

one micron-filtered Granite Canyon sea water, diluted to 28 ppt

was compared to all cadmium concentrations. 

Amphipod survival for each replicate was calculated as:

 (Number of surviving amphipods) X 100

 (Initial number of amphipods)

Polychaete Tests

A subset of sediment samples was tested using Neanthes

arenaceodentata. The protocol follows procedures described by

Johns et al. (1990). Newly emergent juvenile Neanthes (2 to 3

weeks old) were obtained from Dr. Donald Reish in Long Beach, 

California. Worms were shipped in seawater in plastic bags at

ambient temperature via overnight mail. Upon arrival at MPSL,

worms were allowed to acclimate gradually to 28 ppt with <2 ppt

daily incremental salinity adjustments. Once acclimated, the

worms were maintained for at least 48 hours, and no longer than

10 days, before the start of a test.

The test setup was similar to the amphipod test. Test containers

were one liter glass beakers or jars, each containing 2 cm of

sediment and filled to the 700 ml line with 28 ppt seawater. 

Seawater was adjusted to the appropriate salinity using spring
33

water or distilled well water. After test sediment and overlying

water were allowed to equilibrate for 24 hours, 5 worms were

placed in each of 5 replicate beakers per sample, and 28 ppt

seawater was added up to the one liter line. Test chambers were

aerated and illuminated continuously during the 20-day test

period. Worms were fed TetraMin® every 2 days, and water was

renewed every 3 days. At the end of 20 days, samples were sieved

through 0.5mm Nitex® screens, and the number of surviving worms

recorded. Surviving worms were placed in pre-weighed foil in a

drying oven until they reached a constant weight. Worms were

weighed to the nearest 0.1mg. 

Worm survival for each replicate was calculated as:

(Number of

surviving worms) x 100

 Initial

number of worms

Mean weight/worm for each replicate was calculated as:

(Total weight) -

(foil weight)

 Number of

surviving worms

Positive control reference tests were conducted using cadmium

chloride as a reference toxicant. Worm survival for 10 worms was

recorded in three replicates of four cadmium concentrations in

seawater after 96 hours of exposure. A negative seawater control

consisting of one micron-filtered Granite Canyon seawater was

compared to all cadmium concentrations. A negative sediment

control consisting of Yaquina Bay amphipod home sediment was also

included in each test.

Mussel Development Test

The bay mussel (Mytilus edulis) larval development test was

conducted on pore water and sub-surface water samples for which

salinity was in the range of 0-26 parts per thousand (ppt). 

Details of the test protocol are given in ASTM (1992). A brief

description of the method follows.

Mussels were shipped via overnight courier and held at MPSL at

ambient temperature (11-13°C) and salinity (32-34 ppt) until

testing. On the day of a test, adult mussels were transferred to

25°C water to induce spawning through heat stress. Sperm and

eggs were mixed in 25 ppt water to give a final sperm-to-egg

ratio of 15 to 1. After approximately 20 minutes, fertilized

eggs were rinsed on a 25 μm screen to remove excess sperm.

Embryos were distributed to the test containers after

approximately 90% of the embryos exhibited first cell cleavage

(approximately 1 hour).
34

Test containers were polyethylene-capped, sea water-leached, 20

ml glass scintillation vials containing 10 mls of test solution.

 Each test container was inoculated with approximately 250

embryos (25/ml). Pore water samples were tested at 25 ± 2 ppt. 

Low salinity samples were adjusted to 25 ppt using frozen

seawater brine. Controls consisted of one micron-filtered

Granite Canyon sea water adjusted to 25 ppt, and a separate brine

control consisting of sea water brine adjusted to 25 ppt with

distilled water. A positive control reference test was conducted

concurrently with each test using a dilution series of cadmium

chloride as a reference toxicant.

After a 48-hour exposure period, larvae were fixed in 5% buffered

formalin. All larvae in each container were examined under an

inverted light microscope at 100x to determine the proportion of

normally developed larvae as described in ASTM (1992). The

percentage normally developed larvae was calculated as:

 Observed number of live normal larvae x 100 

 Mean number of live embryos inoculated at start of test

Statistical Analysis of Toxicity Test Data

A total of three hundred fifty solid-phase sediment samples were

tested for toxicity to amphipods (Rhepoxynius abronius) as part

of this study. A subset of 154 samples of solid-phase sediment

samples were tested with the polychaete Neanthes arenaceodentata.

Two hundred twenty-five pore water samples were tested using the

purple sea urchin (Strongylocentrotus purpuratus) fertilization

test; 196 samples were tested using the sea urchin larval

development test; and 65 subsurface water (water column) samples

were tested with the red abalone (Haliotis rufescens) larval

development test. The bivalve mollusc (Mytilus edulis) larval

development test was used to test eight sub-surface water and

three pore water samples that had salinities below the threshold

(26 ppt) selected for use of the sea urchin test.

There were three primary objectives for the toxicity testing

portion of this study:

(1) Investigate the areal extent of toxicity in the San Diego Bay

region by estimating the percent area considered toxic, based on

toxicity test data for each individual protocol; (2) Identify

those sites which were most toxic to assist in prioritization and

designation of "toxic hot spots"; and (3) Evaluate the

performance of each toxicity test protocol.

The first objective (investigating the spatial extent of

toxicity) was primarily for use of the National Oceanic and

Atmospheric Administration (NOAA)- National Status and Trends

Program. The second objective (identifying and prioritizing

individual sites as "toxic hot spots") was primarily for the

California State Water Resources Control Board.

The different objectives required different sampling designs and

different statistical approaches. The first objective,

determination of the areal extent of toxicity, was accomplished

through a process this report will refer to as the "EMAP

approach": statistical procedures that compared samples from
35

randomly selected stations against the test controls. In this

approach, classification of a particular test sample as "toxic"

was determined by a two step statistical approach comparing test

samples to laboratory controls, as described below.

To accomplish the second objective, distinguishing the most toxic

stations in the region to assist in the designation and

prioritization of "toxic hot spots", a relatively new statistical

method was employed, termed the "reference envelope approach". 

This approach compared organism response (e.g. % survival) from

an individual test sample with mean organism response from a

group of reference sites presumed to represent optimal ambient

conditions in the San Diego Bay region. Optimal ambient

conditions are defined as indicative of conditions that can be

found within the study area at sites that have relatively low

pollutant concentrations and relatively undisturbed benthic

communities. This method was intended to refine the definition

of sample toxicity in order to identify a subset of toxic sites

that were of greatest concern. This method is also described in

detail below.

It should be noted that the EMAP approach and the reference

envelope approach are distinctly different, yet complementary,

statistical methods for determining toxicity. The intent of using

two approaches is to identify non-toxic, significantly toxic and

highly toxic locations based on multiple analyses of the data,

for ranking toxicity results in a tiered approach.

EMAP Approach for Determining Spatial Extent of Toxicity

The "San Diego Bay Region" incorporates three non-connecting

water bodies: San Diego Bay, Mission Bay and Tijuana Slough. 

Ideally these water bodies should be treated as discrete areas

and analyzed separately to determine percent area toxic for each.

 However, the number of samples from Mission Bay and Tijuana

Slough were 13 and 6, respectively, and these were considered too

few to accurately represent toxicity in a frequency distribution.

Consequently, data from all three water bodies were combined in

this report to determine the percentage of total area that was

toxic.

In this analysis, sample toxicity was determined using procedures

described by Schimmel et al. (1991); a method used in the EPA

Environmental Monitoring Assessment Program (EMAP) and in similar

NOAA studies nationwide (e.g., Long et al., 1994). Using the

EMAP approach, samples were defined as toxic if the following two

criteria were met: (1) there was a significant difference in mean

organism response (e.g. percent survival) between a sample and

the control as determined using a t-test, and (2) mean organism

response in the toxicity test was less than 80% of the laboratory

control value. The t-test generates a t statistic by dividing

the difference between control and test sample response by an

expression of the variance between laboratory replicates. If the

variation between control and test sample is sufficiently greater

than the variation among laboratory replicates, the t-test
36

indicates a significant difference in response. A "separate

variance" t-test was used to adjust the degrees of freedom to

account for variance heterogeneity among samples (SYSTAT, 1992).

The second criterion, that sample response must be less than 80%

of the control value to be considered toxic, is useful in

eliminating those samples that were statistically different from

controls only because of a very small variance among laboratory

replicates. For example, a sample that had 90 ± 2 % Rhepoxynius

survival would be significantly different from a control with

survival of 96 ± 2 %, and would therefore be considered toxic

based on a simple t-test even though the biological significance

of this response would be negligible. By adding the second

criterion, any sample with percent survival exceeding 80% of the

controls would be considered non-toxic. The 80% level was

established by examination of numerous amphipod toxicity data

sets (Thursby and Schlekat, 1993). These researchers found that

samples with survival less than 80% relative to controls were

significantly different from controls about 90% of the time.

Preliminary analyses of Rhepoxynius test data from the BPTCP

indicate a similar level of statistical sensitivity. Based on

this observation, the 80% criterion has been adopted previously

(Schimmel et al., 1991; USEPA/USACOE, 1991). Samples identified

as toxic according to these criteria were used to estimate the

percent of total area toxic within the San Diego Bay region.

Using Cumulative Distribution Frequencies to Characterize 

 Spatial Extent

The stratified random sampling design, allowed 121 of the total

350 samples collected in this study, to be used to estimate the

areal extent of toxicity. Samples collected using directed

sampling (non-random sampling directed to areas of particular

characteristics) were not included in this analysis since they

may have been biased toward increased contamination. Directed

non-random sampling was designed to address the State and

Regional Water Quality Boards objective to identify and

prioritize potential toxic hot spots. Samples were collected

from randomly selected stations within 95 non-overlapping mapped

blocks of known area in the San Diego Bay region (Figure 2). 

Total area sampled, calculated as the sum of all 95 block areas,

was 40.9 km2. The estimate of spatial toxicity was determined

from cumulative distribution frequencies (CDFs) that relate

toxicity response to percent of total sampled area. CDF

calculations follow procedures used by both EMAP and NS&T.

CDFs were determined using calculated areas of each block

normalized to the number of samples per block. Block areas were

calculated using a planimeter on NOAA National Ocean Service

navigation chart (means of three trials), calibrated to the scale

of the charts. Because no more than two samples were collected

per block, numbers of toxic samples per block ranged from 0 to 2,

representing 0%, 50% or 100% of a given block area. By combining

the blocks with their toxicity designations in a cumulative

manner, the CDFs indicate the percentage of total area sampled

that was toxic. Sample toxicity was determined from comparisons
37

with laboratory controls as described above in the EMAP approach;

each sample with a mean significantly different from, and less

than 80% of, the laboratory control mean was considered toxic. 

Calculations used to derive percent areas determined to be toxic

are shown on worksheets in Appendix F. CDFs were generated from

toxicity tests using Rhepoxynius survival (solid phase) and

Strongylocentrotus larval development (pore water). There were

insufficient data from randomly selected sites to generate CDFs

for Haliotis, Mytilus and Neanthes tests.

The Reference Envelope Approach for Determining Toxicity

The second objective of this study was to assist in the

identification of "toxic hotspots", where adverse biological

impacts are observed in areas with localized concentrations of

pollutants. Identification of problem sites was an essential

step in prioritizing efforts to improve sediment and water quality

through regulation and remediation programs. While it was

possible large areas of San Diego Bay may be degraded to some

extent, logistical constraints required efforts be focused on

localized areas that were significantly more toxic than optimal

ambient conditions that exist in the greater portion of the bay.

In this study, a "reference envelope" statistical approach was

employed (Smith,1995) to identify samples that exhibit significantly

greater toxicity than expected in San Diego Bay as a whole.

The reference envelope approach uses data from "reference sites"

to characterize the response expected from sites in the absence

of localized pollution. Using data from the reference site

population, a tolerance limit was calculated for comparison with

data from test sites. Samples with toxicity values greater than

the tolerance limit were considered toxic relative to the optimal

ambient condition of the Bay.

This relative standard established using reference sites was

conceptually different from what might be termed the absolute

standard of test organism response in laboratory controls. 

Rather than comparing sample data to control data using t-tests,

with laboratory replication used to characterize the variance

component (as in the "EMAP approach" described above), the

reference envelope approach compared sample data against a

percentile of the reference population of data values, using

variation among reference sites as the variance component. The

reference envelope variance component, therefore, included

variation among laboratory replicates, among field replicates,

among sites, and among sampling events.

The reference stations were assumed to be a random sample from an

underlying population of reference locations that serve as a

standard for what we considered relatively non-impacted

conditions. The toxicity measured at different reference

locations will vary due to the different local conditions that

can affect the toxicity results. In order to determine whether

sediments from a test location were toxic, bioassay results for

the test location were compared with bioassay results from the

population of reference locations.
38

Assuming the bioassay results from the population of reference

locations are normally distributed, an estimate of the

probability that the test sediment is from the underlying

reference station distribution can be made. For example, if the

result for a test sediment was at the first percentile of the

underlying reference location distribution (in the direction of

toxicity), then there would be about a 1% chance that the test

sediment was from the distribution of reference locations.

The toxicity level at the first percentile of the reference

distribution is not known because there were only limited samples

from the underlying distribution and only an estimate could be

made of where the first percentile lies. If an estimate of the

first percentile value was made a large number of times, using

different random samples from the reference distribution, a (noncentral t) distribution of estimates, with the distribution mode

at the actual first percentile would be obtained (Figure 4). In

Figure 4, it can be seen from the distribution of estimates that

about one half of the time the estimate from the sample was above

the actual first percentile. Ideally, identification of an

estimated toxicity value would cover the actual first percentile

for a large percentage of the estimates (say 95% of the time). 

Such a value can be obtained from the left tail of the

distribution of estimates where 5% of the estimates are less than

the chosen value. The definition of p is the percentile of

interest, and alpha is the acceptable error probability

associated with an estimate of the pth percentile. Thus, in this

example, p=1 and alpha = .05.

The toxicity level can be computed that will cover the pth

percentile 1 minus alpha proportion of the time as the lower

bound (L) of a tolerance interval (Vardeman 1992) as follows.

L = Xr - [ ga,p,n * Sr ]

where Xr is the mean of the sample of reference stations, Sr is

the standard deviation of the toxicity results among the

reference stations, and n is the number of reference stations.

The g values, for the given alpha, p, and n values, can be

obtained from tables in Hahn and Meeker (1991) or Gilbert (1987).

 S contains the within- and between-location variability expected

among reference locations. If the reference stations are sampled

at different times, then S will also incorporate between-time

variability. The "edge of the reference envelope" (L) represents

a cutoff toxicity level used to distinguish toxic from non-toxic

sediments. The value used for p will depend on the level of

certainty needed for a particular regulatory situation. In this

study a p value equal to 1% was chosen, to distinguish only the

most toxic samples, that is, samples having a 95% certainty of

being in the most toxic 1%. 

Reference Station Selection for Reference Envelope

Reference stations were selected to represent optimal ambient

conditions available in San Diego Bay, based on available

chemistry and benthic community data. Toxicity data were not
39

used in the selection process. Stations were selected if both

of the following criteria were met: 1) the benthic communities

appeared relatively undisturbed (based on indices described in

the benthic community analysis section), and 2) sediment chemical

concentrations were below Effects Range Median (ERM) levels (Long

et al., 1995) and Probable Effects levels (PELs) (McDonald,

1994). Among all stations, both randomly and non-randomly

41

selected, a total of 75 samples were analyzed for toxicity,

chemistry and benthic ecology in this study. After screening

these 75 samples, eleven stations in the San Diego Bay region

were selected as reference stations (Table 4). It should be noted

these stations were not selected prior to the initiation of the

study, but were selected after all of the analyses for the study

were completed. 

P450 Reporter Gene System

Summary of Methods

A subset of thirty sediment samples was sent to Columbia

Analytical Services (CAS) in Kelso, Washington for extraction

with methylene chloride. Extracts of 20 g sediment samples were

evaporated to 1 ml and placed in small vials for shipment to the

Carlsbad, CA laboratory of CAS where 2 μl samples were applied in

triplicate to genetically engineered human liver cancer cells

(101L cells) developed by Dr. Robert Tukey of the University of

California, at San Diego. A previous study partially funded by

the State Board (Anderson et al., 1995) had demonstrated that low

levels of dioxin, coplanar PCBs and selected PAHs could be

detected by the P450-RGS response to the extracts. When this

small volume of solvent (with extracted contaminants) is applied

to approximately one million cells in 2 ml of medium, induction

of the CYP1A1 gene leads to production of the detoxification

enzyme, P450, and the luminescent enzyme, luciferase. When the

cells are lysed (after 16 hours) and the centrifugate tested with

luciferin, the amount of light measured in a luminometer is a

function of the concentration and potency of the contaminants on

the sediments. When the contents of a single well (containing ≈

one million cells) are centrifuged and placed in the luminometer

the resulting measure is in Relative Light Units (RLU). The RLUs

of the solvent blank are set to unity and by dividing all RLU

readings for the reference toxicant and samples by the RLUs of

the blank, the data are converted to Fold Induction (or times

background). To make the data more relevant to environmental

samples, the data are converted to Equivalents of Benzo(a)pyrene

(BaPEq), a ubiquitous PAH compound of environmental concern (U.S.

EPA, 1995). To convert mean fold induction to BaPEq in μg/g dry

weight, the fold induction values are divided by sixty, which

(based on a dose response curve) is the response of the assay to

1μg/ml of Benzo(a)pyrene (BaP). The μg of BaP per volume of

extract (e.g. 10 μl) is adjusted to an initial volume of 1 ml and

this product divided by the dry grams of sample contained in the

1 ml extract. This method can be used to calculate Equivilants

for PAHs, from benz(a)anthracene to benzo(g,h,i)perylene (Table

4), as well as dioxins/furans and coplanar PCBs. Both sediments

and tissues (marine mussel) from San Diego Bay have been analyzed

for the presence of P450 inducing compounds in previous studies

(Anderson et al. 1996, in press a). The detailed methods and

results of P450-RGS testing with standards and sediment extracts

are described in Postlind et al. (1994), and Anderson et al.

(1995). In 1996, three publications will be available describing

the specific test methods (ASTM, Standard Methods,and CRC Press).
TABLE 4

REFERENCE STATIONS SELECTED FOR REFERENCE ENVELOPE ANALYSIS

Station # Station Name IDORG # Leg % Fines TOC ERMQ PELQ BENTHICS Amphipod Surv. Urchin Devo.(25%)

93112.0 MISSION BAY A8 (x1)-REP 1 856 21 30.12 0.81 0.065 0.116 UNDEGRADED 96 ± 5 20.2 ± 1

93112.0 MISSION BAY A8 (x1)-REP 2 857 21 37.28 0.94 0.082 0.134 UNDEGRADED 98 ± 3 89 ± 4

93112.0 MISSION BAY A8 (x1)-REP 3 858 21 43.56 0.91 0.089 0.145 UNDEGRADED 94 ± 5 53.6 ± 49

93202.0 EAST BASIN I1 (x5) 842 21 46.28 1.11 0.238 0.362 UNDEGRADED 83 ± 6 67.2 ± 17

90013.0 37 SWARTZ (MARINA) 815 20 88.21 1.37 0.217 0.347 UNDEGRADED 81 ± 8 73.8 ± 10

93190.0 MARINA II1 (x1) 816 20 93.97 1.22 0.219 0.356 UNDEGRADED 87 ± 12 59.4 ± 9

90053.0 35 SWARTZ (CORONADO CAYS) 843 21 91.85 1.47 0.180 0.292 UNDEGRADED 75 ± 11 29 ± 25

93108.0 MISSION BAY A4 (x1)-REP 2 860 21 64.60 1.87 0.104 0.166 UNDEGRADED 69 ± 14 78.5 ± 16

93195.0 GLORIETTA BAY U1 (x2) 823 20 48.24 0.95 0.239 0.369 UNDEGRADED 81 ± 9 0 ± 0

93194.0 GLORIETTA BAY U1 (x1) 822 20 55.80 1.14 0.232 0.371 UNDEGRADED 89 ± 7 46.3 ± 7

93231.0 CARRIER BASE V2 (x6) 1000 23 57.66 1.57 0.252 0.404 UNDEGRADED 74 ± 12 0 ± 0

None of the above samples exhibited any chemical exceedance of an ERM or PEL.

None of the above samples exhibited elevated ammonia or hydrogen sulfide during toxicity testing.

Amphipod Survival value is the mean and standard deviation from 5 laboratory replicates. 

Urchin Development values are the mean and standard deviation of 5 replicates in 25% porewater.

ERM and PEL summary quotients are discussed in Appendix B and the report text.
43

Quality Assurance/Quality Control

Summary of Methods

Summaries of quality assurance and quality control procedures are

described under separate cover in the Bay Protection and Toxic

Cleanup Program Quality Assurance Project Plan (QAPP). This

document describes procedures within the program which ensure

data quality and integrity. Quality assurance procedures follow

those of the NS&T Program to ensure comparability with other NOAA

survey areas nationwide. In addition, individual laboratories

prepare quality assurance evaluations of each discrete set of

samples analyzed and authorized by task order. These documents

were submitted to the California Department of Fish and Game for

review, then forwarded to the State Water Resources Control Board

for further review.

RESULTS

Tabulated data for all chemical, benthic, toxicological and P450-

RGS analyses are presented in Appendices B, C, D and E. The

summary data presented in the following results sections were

used to demonstrate significant findings from the analysis of the

full data set in Appendices B, C, and D.

Distribution of Chemical Pollutants

Chemical Specific Screening Values

There have been several recent studies associating pollutant

concentrations with biological responses (Long and Morgan, 1990;

MacDonald, 1992). These studies provide guidance for evaluating

the degree to which sediment chemical pollutants levels are

responsible for effects observed in a toxicity test. Reported

values are based on individual chemical pollutants within

sediments. Therefore, their application may be confounded when

dealing with: biological effects which could be attributed to a

synergistic effect of low levels of multiple chemicals,

unrecognized chemicals, or physical parameters in the sediment

which were not measured.

The National Status and Trends Program has used chemical and

toxicological evidence from a number of modeling, field and

laboratory studies to determine the ranges of chemical

concentrations which are rarely, sometimes, or usually associated

with toxicity (Long and Morgan, 1992). Evaluation of available

data (Long et al., 1995) has led to identification of three

ranges in concentration for each chemical:

 1) Minimal Effects Range: The range in concentration over

which toxic effects are rarely observed:

 2) Possible Effects Range: The range in concentrations

over which toxic effects are occasionally observed;
44

 3) Probable-Effects Range: The range in chemical

concentrations over which toxic effects are frequently

or always observed.

Two slightly different methods were used to determine these

chemical ranges. One method developed by NOAA (Long and Morgan,

1990; Long et al., 1995) used chemical data which were associated

with a toxic biological effect. These data were used to determine

the lower 10th percentile of ranked data where the chemical level

was associated with an effect (Effects Range-Low, or ERL).

Sediment samples in which all chemical concentrations were below

the 25 ERL values were not expected to be toxic. The Effects

Range-Median (ERM) reflects the 50th percentile of ranked data

and represents the level above which effects are expected to

occur. Effects are expected to occur occasionally when chemical

concentrations fall between the ERL and ERM. The probability of

toxicity was expected to increase with the number and degree of

exceedances of the ERM values.

Another method identifies three ranges using chemical

concentration data associated with both toxic biological effects

and no observed effects (MacDonald, 1992; MacDonald, 1994;

MacDonald et al., In Press). The ranges are identified as TEL

(Threshold Effects Level) and the PEL (Probable Effects Level).

TEL values were derived by taking the geometric mean of the 50th

percentile of the "no effects" data and the 15th percentile of

the "effects" data. The PEL values were derived by taking the

geometric mean of the 85th percentile of the "no effects" data 

and the 50th percentile of the "effects" data. Although different

percentiles were used for these two methods, they are in close

agreement, usually within a factor of 2. Values reported for both

methods are shown in Table 5. Neither of these methods is

advocated over the use of the other in this report. Instead, both

are used in the following analysis to create a weight of evidence

which should help explain toxicity observed from some sediments.

A cautionary note should be included; the degree of confidence

which MacDonald (1994) and Long et al. (1995) had in their

respective guidelines varied considerably among the different

chemicals. For example, they express low confidence in the values

derived for nickel, mercury, DDTs, chlordane, dieldrin, and

endrin. When more data becomes available regarding these

chemicals and their potential effects, the guidelines may be

revised, probably upward for some substances.

Primary Chemicals of Concern

Figure 5 presents a summary of the chemicals and chemical groups

which exceeded ERM or PEL values at the 217 stations where

complete chemical analysis was performed. Copper, mercury, zinc,

total chlordane, total PCBs and the PAHs were most often found to

exceed ERM or PEL values and are considered the six major

chemicals or chemical groups of concern in the San Diego Bay
Table 5- Comparison of Sediment Screening Levels

Developed by NOAA and the State of Florida 

 State of Florida (1) NOAA (2) (2)

SUBSTANCE TEL PEL ERL ERM 

 Organics (ug/kg- dry weight)

Total PCBs 21.550 188.79 22.70 180.0

PAHs

Acenaphthene 6.710 88.90 16.00 500.0

Acenaphthylene 5.870 127.89 44.00 640.0

Anthracene 46.850 245.00 85.30 1100.0

Fluorene 21.170 144.35 19.00 540.0

2-methylnaphthalene 20.210 201.28 70.00 670.0

Naphthalene 34.570 390.64 160.00 2100.0

Phenanthrene 86.680 543.53 240.00 1500.0

Total LMW-PAHs 311.700 1442.00 552.00 3160.0

Benz(a)anthracene 74.830 692.53 261.00 1600.0

Benzo(a)pyrene 88.810 763.22 430.00 1600.0

Chrysene 107.710 845.98 384.00 2800.0

Dibenz(a,h)anthracene 6.220 134.61 63.40 260.0

Fluoranthene 112.820 1493.54 600.00 5100.0

Pyrene 152.660 1397.60 665.00 2600.0

Total HMW-PAHs 655.340 6676.14 1700.00 9600.0

Total PAHs 1684.060 16770.54 4022.00 44792.0

Pesticides

p,p'-DDE 2.070 374.17 2.20 27.0

p,p'-DDT 1.190 4.77

Total DDT 3.890 51.70 1.58 46.1

Lindane 0.320 0.99

Chlordane 2.260 4.79 0.50 6.0

Dieldrin 0.715 4.30 0.02 8.0

Endrin 0.02 45.0

Metals (mg/kg- dry weight)

Arsenic 7.240 41.60 8.20 70.0

Antimony 2.00 2.5

Cadmium 0.676 4.21 1.20 9.6

Chromium 52.300 160.40 81.00 370.0

Copper 18.700 108.20 34.00 270.0

Lead 30.240 112.18 46.70 218.0

Mercury 0.130 0.70 0.15 0.7

Nickel 15.900 42.80 20.90 51.6

Silver 0.733 1.77 1.00 3.7

Zinc 124.000 271.00 150.00 410.0

(1) D.D. MacDonald, 1994

(2) Long et al., 1995

47

Region. MacDonald (1994) and Long et al. (1995) express

relatively high confidence in the ERM and PEL values derived for

copper, zinc, total PCBs and PAHs. Figures 6-12 map the

geographical distribution of the six chemicals of concern

throughout the San Diego Bay Region. Three ranges of chemical

concentration are given for each chemical: (1) below the TEL, (2)

between the TEL and PEL and (3) above the PEL to the maximum

concentration determined.

Copper is a broad spectrum biocide which may be associated with

acute and chronic toxicity, reduction in growth, and a wide

variety of sublethal effects (Spear and Pierce, 1979). Elevated

copper concentrations above the PEL (>108.2 mg/kg) or ERM (>270

mg/kg) were found throughout San Diego Bay (Figure 6(a-d)), with

small boat harbors, commercial shipping berths and military

berths most often impacted. Considering the historical use of

copper based anti-fouling paint in the area, this distribution

pattern is expected.

Zinc demonstrates a similar pattern of distribution, although

actual exceedances of PEL levels (>271 mg/kg) or ERM levels

(>410 mg/kg) only occur in the central portion of the bay, along

the naval shipyard waterfront (Figure 7(a-d).

Mercury, particularly methylmercury, is highly toxic to aquatic

biota. Although there is variability in sensitivity of different

organisms to the substance, bioaccumulation of mercury in aquatic

species has significant implications with respect to human

health. PEL exceedances (> 0.696 mg/kg) and ERM exceedances

(>0.71 mg/kg) of mercury were found in several small boat areas,

near commercial shipping operations and predominately near naval

shipyard areas (Figure 8(a-d)).

Polycyclic (polynuclear) aromatic hydrocarbons (PAHs) are

base/neutral organic compounds with a fused ring structure of two

or more benzene rings. They are components of crude and refined

petroleum products and are also products of incomplete combustion

of organic materials. Exposure to PAHs may result in a wide range

of carcinogenic, teratogenic and mutagenic effects to terrestrial

and aquatic organisms (Eisler, 1987). Due to their similar modes

of toxic action, individual PAHs are often grouped into low and

high molecular weight compounds, for concise reporting purposes.

Individual PAHs used for the summations of low and high molecular

weight PAHs in this report are given in Appendix B -Section VII.

PAH pollution, as shown for high molecular weight PAHs in Figure

9(a-d), exceeds the PEL (>6676.14 μg/kg) or ERM (>9600 μg/kg)

near commercial shipping operations and naval shipyard areas, as

well as the submarine facility near the mouth of the harbor. The

pattern for PEL (>1442 μg/kg) or ERM (>3160 μg/kg) exceedances of

low molecular weight PAHs is similar to high molecular weight

PAHs (Fig. 10(a-d)).

A significant concern is polychlorinated biphenyls (PCBs) levels

found in sediments throughout San Diego Bay. PCBs are

base/neutral compounds which are formed by direct chlorination of
90071

93161

90028

90029

93216

93162

93217

90063

93138

90048

93141

90056

90104

90049

90102

93164

90023

93134

90026

93136

93149

93163

90103

93231

93188

90016

93169

93148

90001

90025

93199 93200 93202

93135

90027

93186

90101

93143

93153

93152

93139

93140

93166

93167

93165

93137

93168

90024

93232

93154

90050

93201

90055

Figure 6a

Copper Concentrations in Sediment

North San Diego Bay 

Copper

(dry weight)

Not Analyzed

0 to 18.7ppm-below TEL

18.7 to 108.2ppm-below PEL

108.2 to 660ppm-above PEL
93155

90004

93156

93142

93208

93207

93221

93205

90037

93206

93222

90002

90003

90039

93123

93146

90017

90018

90020 90021

93178

90005

90019

93182

90006

93211

93180

90030

90031

93213

93185

93223

90032 93212

90007

90022

93183

93214

93194

93147

90015

93195

93122

93124

90043

93157 90051

93192

93193

93145

93144

90038

93177

93125

93172

93173

93181

93210

93179

93126

93170

90014

93224

93215

93133

90008

93184

93226

93225

93171

93187

90009

93227

93228

Copper

(dry weight)

Not Analyzed

0 to 18.7ppm-below TEL

18.7 to 108.2ppm-below PEL

108.2 to 660ppm-above PEL

Figure 6b

Copper Concentrations in Sediment

Mid San Diego Bay 
93191

93190

93151

93197

90036

93128

93220

93219

90057

93159

90054

93158

93127

90013

93150

93203

93131

90053

90011

90052

90040

93230

90010

93229

93204

93132

90058

90041

90012

93196

93129

Copper

(dry weight)

Not Analyzed

0 to 18.7ppm-below TEL

18.7 to 108.2ppm-below PEL

108.2 to 660ppm-above PEL

Figure 6c

Copper Concentrations in Sediment

South San Diego Bay 
93115

93112

93114

93116

93108 93110

93109

93117

93107

93106

93105

93113

93111

Copper

(dry weight)

Not Analyzed

0 to 18.7ppm-below TEL

18.7 to 108.2ppm-below PEL

108.2 to 660ppm-above PEL

93119

93175

93118

93120

93121

93174

Copper

(dry weight)

Not Analyzed

0 to 18.7ppm-below TEL

18.7 to 108.2ppm-below PEL

108.2 to 660ppm-above PEL

Figure 6d

Copper Concentrations in Sediment

Mission Bay and San Diego River Estuary 

Tijuana River Estuary
90071

93161

90028

90029

93216

93162

93217

90063

93138

90048

93141

90056

90104

90049

90102

93164

90023

93134

90026

93136

93149

93163

90103

93231

93188

90016

93169

93148

90001

90025

93199 93200 93202

93135

90027

93186

90101

93143

93153

93152

93139

93140

93166

93167

93165

93137

93168

90024

93232

93154

90050

93201

90055

Figure 7a

Zinc Concentrations in Sediment

North San Diego Bay

Zinc

(dry weight)

Not Analyzed

0 to 124ppm-below TEL

124 to 271ppm-below PEL

271 to 1600ppm-above PEL
93155

90004

93156

93142

93208

93207

93221

93205

90037

93206

93222

90002

90003

90039

93123

93146

90017

90018

90020 90021

93178

90005

90019

93182

90006

93211

93180

90030

90031

93213

93185

93223

90032 93212

90007

90022

93183

93214

93194

93147

90015

93195

93122

93124

90043

93157 90051

93192

93193

93145

93144

90038

93177

93125

93172

93173

93181

93210

93179

93126

93170

90014

93224

93215

93133

90008

93184

93226

93225

93171

93187

90009

93227

93228

Zinc

(dry weight)

Not Analyzed

0 to 124ppm-below TEL

124 to 271ppm-below PEL

271 to 1600ppm-above PEL

Figure 7b

Zinc Concentrations in Sediment

Mid San Diego Bay
93191

93190

93151

93197

90036

93128

93220

93219

90057

93159

90054

93158

93127

90013

93150

93203

93131

90053

90011

90052

90040

93230

90010

93229

93204

93132

90058

90041

90012

93196

93129

Zinc

(dry weight)

Not Analyzed

0 to 124ppm-below TEL

124 to 271ppm-below PEL

271 to 1600ppm-above PEL

Figure 7c

Zinc Concentrations in Sediment

South San Diego Bay
93115

93112

93114

93116

93108 93110

93109

93117

93107

93106

93105

93113

93111

Zinc

(dry weight)

Not Analyzed

0 to 124ppm-below TEL

124 to 271ppm-below PEL

271 to 1600ppm-above PEL

93119

93175

93118

93120

93121

93174

Zinc

(dry weight)

Not Analyzed

0 to 124ppm-below TEL

124 to 271ppm-below PEL

271 to 1600ppm-above PEL

Figure 7d

Zinc Concentrations in Sediment

Mission Bay & San Diego River Estuary

Tijuana River Estuary
90071

93161

90028

90029

93216

93162

93217

90063

93138

90048

93141

90056

90104

90049

90102

93164

90023

93134

90026

93136

93149

93163

90103

93231

93188

90016

93169

93148

90001

90025

93199 93200 93202

93135

90027

93186

90101

93143

93153

93152

93139

93140

93166

93167

93165

93137

93168

90024

93232

93154

90050

93201

90055

Figure 8a

Mercury Concentrations in Sediment

North San Diego Bay 

Mercury

(dry weight)

Not Analyzed

0 to 0.13ppm-below TEL

0.13 to 0.696ppm-below PEL

0.696 to 3.5ppm-above PEL
93155

90004

93156

93142

93208

93207

93221

93205

90037

93206

93222

90002

90003

90039

93123

93146

90017

90018

90020 90021

93178

90005

90019

93182

90006

93211

93180

90030

90031

93213

93185

93223

90032 93212

90007

90022

93183

93214

93194

93147

90015

93195

93122

93124

90043

93157 90051

93192

93193

93145

93144

90038

93177

93125

93172

93173

93181

93210

93179

93126

93170

90014

93224

93215

93133

90008

93184

93226

93225

93171

93187

90009

93227

93228

93229

Mercury

(dry weight)

Not Analyzed

0 to 0.13ppm-below TEL

0.13 to 0.696ppm-below PEL

0.696 to 3.5ppm-above PEL

Figure 8b

Mercury Concentrations in Sediment

Mid San Diego Bay
93191

93190

93151

93197

90036

93128

93220

93219

90057

93159

90054

93158

93127

90013

93150

93203

93131

90053

90011

90052

90040

93230

90010

93229

93204

93132

90058

90041

90012

93196

93129

Mercury

(dry weight)

Not Analyzed

0 to 0.13ppm-below TEL

0.13 to 0.696ppm-below PEL

0.696 to 3.5ppm-above PEL

Figure 8c

Mercury Concentrations in Sediment

South San Diego Bay
93115

93112

93114

93116

93108 93110

93109

93117

93107

93106

93105

93113

93111

Mercury

(dry weight)

Not Analyzed

0 to 0.13ppm-below TEL

0.13 to 0.696ppm-below PEL

0.696 to 3.5ppm-above PEL

93119

93175

93118

93120

93121

93174

Mercury

(dry weight)

Not Analyzed

0 to 0.13ppm-below TEL

0.13 to 0.696ppm-below PEL

0.696 to 3.5ppm-above PEL

Figure 8d

Mercury Concentrations in Sediment

Mission Bay & San Diego River Estuary

Tijuana River Estuary
90071

93161

90028

90029

93216

93162

93217

90063

93138

90048

93141

90056

90104

90049

90102

93164

90023

93134

90026

93136

93149

93163

90103

93231

93188

90016

93169

93148

90001

90025

93199 93200 93202

93135

90027

93186

90101

93143

93153

93152

93139

93140

93166

93167

93165

93137

93168

90024

93232

93154

90050

93201

90055

Figure 9a

High Molecular Weight PAH Concentrations in Sediment

North San Diego Bay

High MW PAH

(dry weight)

Not Analyzed

0 to 655.34ppb-below TEL

655.34 to 6676.14ppb-below PEL

6676.14 to 56500ppb-above PEL
93155

90004

93156

93142

93208

93207

93221

93205

90037

93206

93222

90002

90003

90039

93123

93146

90017

90018

90020 90021

93178

90005

90019

93182

90006

93211

93180

90030

90031

93213

93185

93223

90032 93212

90007

90022

93183

93214

93194

93147

90015

93195

93122

93124

90043

93157 90051

93192

93193

93145

93144

90038

93177

93125

93172

93173

93181

93210

93179

93126

93170

90014

93224

93215

93133

90008

93184

93226

93225

93171

93187

90009

93227

93228

High MW PAH

(dry weight)

Not Analyzed

0 to 655.34ppb-below TEL

655.34 to 6676.14ppb-below PEL

6676.14 to 56500ppb-above PEL

Figure 9b

High Molecular Weight PAH Concentrations in Sediment

Mid San Diego Bay
93191

93190

93151

93197

90036

93128

93220

93219

90057

93159

90054

93158

93127

90013

93150

93203

93131

90053

90011

90052

90040

93230

90010

93229

93204

93132

90058

90041

90012

93196

93129

High MW PAH

(dry weight)

Not Analyzed

0 to 655.34ppb-below TEL

655.34 to 6676.14ppb-below PEL

6676.14 to 56500ppb-above PEL

Figure 9c

High Molecular Weight PAH Concentrations in Sediment

South San Diego Bay
93115

93112

93114

93116

93108 93110

93109

93117

93107

93106

93105

93113

93111

High MW PAH

(dry weight)

Not Analyzed

0 to 655.34ppb-below TEL

655.34 to 6676.14ppb-below PEL

6676.14 to 56500ppb-above PEL

93119

93175

93118

93120

93121

93174

High MW PAH

(dry weight)

Not Analyzed

0 to 655.34ppb-below TEL

655.34 to 6676.14ppb-below PEL

6676.14 to 56500ppb-above PEL

Figure 9d

High Molecular Weight PAH Concentrations in Sediment

Mission Bay and San Diego River Estuary

Tijuana River Estuary
90071

93161

90028

90029

93216

93162

93217

90063

93138

90048

93141

90056

90104

90049

90102

93164

90023

93134

90026

93136

93149

93163

90103

93231

93188

90016

93169

93148

90001

90025

93199 93200 93202

93135

90027

93186

90101

93143

93153

93152

93139

93140

93166

93167

93165

93137

93168

90024

93232

93154

90050

93201

90055

Figure 10a

Low Molecular Weight PAH Concentrations in Sediment

North San Diego Bay

Low MW PAH

(dry weight)

Not Analyzed

0 to 311.7ppb-below TEL

311.7 to 1442ppb-below PEL

1442 to 27200ppb-above PEL
93155

90004

93156

93142

93208

93207

93221

93205

90037

93206

93222

90002

90003

90039

93123

93146

90017

90018

90020 90021

93178

90005

90019

93182

90006

93211

93180

90030

90031

93213

93185

93223

90032 93212

90007

90022

93183

93214

93194

93147

90015

93195

93122

93124

90043

93157 90051

93192

93193

93145

93144

90038

93177

93125

93172

93173

93181

93210

93179

93126

93170

90014

93224

93215

93133

90008

93184

93226

93225

93171

93187

90009

93227

93228

Low MW PAH

(dry weight)

Not Analyzed

0 to 311.7ppb-below TEL

311.7 to 1442ppb-below PEL

1442 to 27200ppb-above PEL

Figure 10b

Low Molecular Weight PAH Concentrations in Sediment

Mid San Diego Bay
93191

93190

93151

93197

90036

93128

93220

93219

90057

93159

90054

93158

93127

90013

93150

93203

93131

90053

90011

90052

90040

93230

90010

93229

93204

93132

90058

90041

90012

93196

93129

Low MW PAH

(dry weight)

Not Analyzed

0 to 311.7ppb-below TEL

311.7 to 1442ppb-below PEL

1442 to 27200ppb-above PEL

Figure 10c

Low Molecular Weight PAH Concentrations in Sediment

South San Diego Bay
93115

93112

93114

93116

93108 93110

93109

93117

93107

93106

93105

93113

93111

Low MW PAH

(dry weight)

Not Analyzed

0 to 311.7ppb-below TEL

311.7 to 1442ppb-below PEL

1442 to 27200ppb-above PEL

93119

93175

93118

93120

93121

93174

Low MW PAH

(dry weight)

Not Analyzed

0 to 311.7ppb-below TEL

311.7 to 1442ppb-below PEL

1442 to 27200ppb-above PEL

Figure 10d

Low Molecular Weight PAH Concentrations in Sediment

Mission Bay and San Diego River Estuary

Tijuana River Estuary
68

biphenyl. There are 209 numerically designated individual

compounds, called congeners (i.e., PCB #101), based on the

possible chlorine substitution patterns. Mixtures of various PCB

congeners have been manufactured in the U.S. since 1929

(Phillips, 1987) and are used commercially under the trade name

Aroclor. Each PCB mixture has a number designation (i.e., Aroclor

1254) with the last two numbers indicating the percentage of

chlorine in the mixture. PCB mixtures were used extensively in

the U.S. prior to 1979 for industrial applications which required

fluids with thermal stability, fire and oxidation resistance and

solubility in organic compounds (Hodges, 1977). PCBs have proven

to be extremely persistent in the environment and have

demonstrated a variety of adverse carcinogenic and noncarcinogenic effects (USEPA, 1993c). These substances have a high

potential to accumulate in the tissues of aquatic organisms and

can represent significant hazards to consumers of aquatic species

(Moore and Walker, 1991). Total PCB (the sum of 18 congeners,

Appendix B - Section VII) pollution is most prominent in

sediments along the naval shipyard waterfront (Figure 11(a-d)),

although several locations along the downtown waterfront and

small boat harbors also show total PCB values in excess of the

PEL (>188.79 μg/kg) and ERM (>180 μg/kg).

Chlordane is a multipurpose insecticide which has been used

extensively in home and agricultural applications for the control

of termites and other insects. Although use of this compound

ended in the mid-70s, its persistence in sediments of the region

is apparent. Total chlordane is the summation of major

constituents of technical grade chlordane and its metabolite

(Appendix B - Section VII). Chlordane pollution is extensive

along the north shore of San Diego Bay, the San Diego River, and

the most northerly station in Mission Bay (Figure 12(a-d)). Areas

which receive storm runoff, such as Chollas Creek, Seventh St.

Channel, and urban storm drains appear to be the most heavily

contaminated (PEL (>4.79 μg/kg) or ERM (>6 μg/kg)).

ERM and PEL Summary Quotients

In this report, comparisons of the data to effects-based

numerical guidelines were made to assess how sediment pollution

in the San Diego Bay Region compares to sediment pollution on a

national scale. Additionally, these guidelines were used to

identify chemicals of concern for sediment quality management

within the San Diego Bay Region. Rankings and comparisons were

made in this report using summary ERM-quotients (ERMQ) and PELquotients (PELQ). Summary quotients are summations of chemical

concentrations for chemicals listed in Table 5, divided by their

respective ERM or PEL value, and then divided by total number of

chemicals used. In samples where levels of measured chemicals

were below the analytical method detection limit (MDL), a value

of one-half the MDL was used for summations. Methods and analytes

used for summations and averaging are given in Appendix BSection VII. This was a simple approach for addressing overall

chemical pollution where there were multiple pollutants at a

station, and was in addition to the standard chemical by chemical
90071

93161

90028

90029

93216

93162

93217

90063

93138

90048

93141

90056

90104

90049

90102

93164

90023

93134

90026

93136

93149

93163

90103

93231

93188

90016

93169

93148

90001

90025

93199 93200 93202

93135

90027

93186

90101

93143

93153

93152

93139

93140

93166

93167

93165

93137

93168

90024

93232

93154

90050

93201

90055

Figure 11a

Total PCB Concentrations in Sediment

North San Diego Bay

Total PCB

(dry weight)

Not Analyzed

0 to 21.55ppb-below TEL

21.55 to 188.79ppb-below PEL

188.79 to 1380ppb-above PEL
93155

90004

93156

93142

93208

93207

93221

93205

90037

93206

93222

90002

90003

90039

93123

93146

90017

90018

90020 90021

93178

90005

90019

93182

90006

93211

93180

90030

90031

93213

93185

93223

90032 93212

90007

90022

93183

93214

93194

93147

90015

93195

93122

93124

90043

93157 90051

93192

93193

93145

93144

90038

93177

93125

93172

93173

93181

93210

93179

93126

93170

90014

93224

93215

93133

90008

93184

93226

93225

93171

93187

90009

93227

93228

Total PCB

(dry weight)

Not Analyzed

0 to 21.55ppb-below TEL

21.55 to 188.79ppb-below PEL

188.79 to 1380ppb-above PEL

Figure 11b

Total PCB Concentrations in Sediment

Mid San Diego Bay
93191

93190

93151

93197

90036

93128

93220

93219

90057

93159

90054

93158

93127

90013

93150

93203

93131

90053

90011

90052

90040

93230

90010

93229

93204

93132

90058

90041

90012

93196

93129

Total PCB

(dry weight)

Not Analyzed

0 to 21.55ppb-below TEL

21.55 to 188.79ppb-below PEL

188.79 to 1380ppb-above PEL

Figure 11c

Total PCB Concentrations in Sediment

South San Diego Bay
93115

93112

93114

93116

93108 93110

93109

93117

93107

93106

93105

93113

93111

Total PCB

(dry weight)

Not Analyzed

0 to 21.55ppb-below TEL

21.55 to 188.79ppb-below PEL

188.79 to 1380ppb-above PEL

93119

93175

93118

93120

93121

93174

Total PCB

(dry weight)

Not Analyzed

0 to 21.55ppb-below TEL

21.55 to 188.79ppb-below PEL

188.79 to 1380ppb-above PEL

Figure 11d

Total PCB Concentrations in Sediment

Mission Bay and San Diego River Estuary

Tijuana River Estuary
90071

93161

90028

90029

93216

93162

93217

90063

93138

90048

93141

90056

90104

90049

90102

93164

90023

93134

90026

93136

93149

93163

90103

93231

93188

90016

93169

93148

90001

90025

93199 93200 93202

93135

90027

93186

90101

93143

93153

93152

93139

93140

93166

93167

93165

93137

93168

90024

93232

93154

90050

93201

90055

Figure 12a

Total Chlordane Concentrations in Sediment

North San Diego Bay

Total Chlordane

(dry weight)

Not Analyzed

0 to 2.26ppb-below TEL

2.26 to 4.79ppb-below PEL

4.79 to 160ppb-above PEL
93155

90004

93156

93142

93208

93207

93221

93205

90037

93206

93222

90002

90003

90039

93123

93146

90017

90018

90020 90021

93178

90005

90019

93182

90006

93211

93180

90030

90031

93213

93185

93223

90032 93212

90007

90022

93183

93214

93194

93147

90015

93195

93122

93124

90043

93157 90051

93192

93193

93145

93144

90038

93177

93125

93172

93173

93181

93210

93179

93126

93170

90014

93224

93215

93133

90008

93184

93226

93225

93171

93187

90009

93227

93228

93229

Total Chlordane

(dry weight)

Not Analyzed

0 to 2.26ppb-below TEL

2.26 to 4.79ppb-below PEL

4.79 to 160ppb-above PEL

Figure 12b

Total Chlodane Concentrations in Sediment

Mid San Diego Bay
93191

93190

93151

93197

90036

93128

93220

93219

90057

93159

90054

93158

93127

90013

93150

93203

93131

90053

90011

90052

90040

93230

90010

93229

93204

93132

90058

90041

90012

93196

93129

Total Chlordane

(dry weight)

Not Analyzed

0 to 2.26ppb-below TEL

2.26 to 4.79ppb-below PEL

4.79 to 160ppb-above PEL

Figure 12c

Total Chlordane Concentrations in Sediment

South San Diego Bay
93115

93112

93114

93116

93108 93110

93109

93117

93107

93106

93105

93113

93111

Total Chlordane

(dry weight)

Not Analyzed

0 to 2.26ppb-below TEL

2.26 to 4.79ppb-below PEL

4.79 to 160ppb-above PEL

93119

93175

93118

93120

93121

93174

Total Chlordane

(dry weight)

Not Analyzed

0 to 2.26ppb-below TEL

2.26 to 4.79ppb-below PEL

4.79 to 160ppb-above PEL

Figure 12d

Total Chlordane Concentrations in Sediment

Mission Bay and San Diego River Estuary

Tijuana River Estuary
77

approach discussed earlier. This approach considered not only the

presence of guideline exceedances, but the number and degree of

multiple exceedances.

Based upon analyses of the national NS&T and EMAP database, the

incidence of toxicity has been shown to increase with increasing

summary ERM and PEL quotients (Long, Field and MacDonald, in

prep). Synergistic effects are possible, but not implied by the

quotient summations, therefore, this method should be recognized

only as a ranking scheme meant to better focus management efforts

on interpretation of ambient sediment chemistry data. 

Interpretations using ERM and PEL summary quotients were limited

to statistical analysis within this dataset because the approach

has not been formally presented in other reports, therefore,

outside comparisons are unavailable at this time. The 90%

confidence interval from a 1-tailed t-distribution was chosen as

an arbitrary threshold level for evaluating the data set. For the

220 stations on which chemical analysis was performed, stations

with an ERMQ>0.85 or a PELQ>1.29 were found to fall above this

confidence interval (Figure 13). Although these values of 0.85

and 1.29 cannot be considered threshold levels with proven

ecological significance, they can be used for within bay

comparative purposes. Forty-one stations exhibited ERM or PEL

quotient levels exceeding the confidence interval cutoffs. Of

these forty-one stations, twelve received benthic community

analysis, all which were determined to have degraded communities

in the analysis discussed later (Figure 14). All 41 stations were

tested for Rhepoxynius toxicity, of which 29% demonstrated

significant toxicity, at the 48% limit established by the

reference envelope method discussed later. This difference in

biological response to pollutants, between benthic community

structure and bioassays, may be explained by long term exposure

to pollutants in the benthic community relative to short term (10

day) pollutant exposure in bioassay tests. Use of the ERM and PEL

quotients appear to give a worthwhile representation of overall

chemical pollution and are used later in this report for station

rankings and characterizations.

Distribution of Benthic Community Degradation

Data Analyses and Interpretation

The identification of benthic degraded and undegraded habitat (as

determined by macrobenthic community structure) was conducted

using a cumulative, weight-of-evidence approach. Tests were

employed without prior knowledge or integration of results from

laboratory exposures or chemical analyses. Analyses were

performed to identify relationships between community structure

within and between each station or site. This included

diversity/evenness indices, analyses of habitat and species

composition, construction of dissimilarity matrices for pattern

testing, assessment of indicator species and development of a

benthic index, cluster and ordination (multidimensional scaling)

analyses. Initially, a triangular correlation matrix was produced
0

10

20

30

40

50

60

PEL QUOTIENT

FREQUENCY DISTRIBUTION OF STATIONS BY

PEL SUMMARY QUOTIENT

0 0 . 0 . 0 . 0 . 1 . 1 . 1 . 1 . 1 . 2 . 2 . 2 . 2 . >

4

5

8

5

9

1

8

1

3

2

8

3

1

3

7

2

8

1

3

1

3

2

6

4

6

7

1

Figure 13. Histogram of the number of stations by

ERM or PEL summary quotient group. Vertical

dashed line indicates 90% confidence limit of the

mean.

90%

con f i dence

lim i t

( 1 - t a ile d ) = 1 . 2 9

0

10

20

30

40

50

60

ERM QUOTIENT

FREQUENCY DISTRIBUTION OF STATIONS BY

ERM SUMMARY QUOTIENT

0 0 . 0 . 0 . 0 . 1 . 1 . 1 . 1 . 1 . 2 . 2 . 2 . 2 . >

1

6

1 1 1 1

2

3

8

9

8

5

1

0

9

2

2 5

1

4

5

5

5

90%

con f i dence

lim i t

( 1 - t a ile d ) = 0 . 8 5
XXXXXXXXXXXXXXXXXXXXXXXXXXX XX XX X X X X X

XXXXX XXX

X XXXXXX XXXX

-0.5

1.5

0.00 0.50 1.00 1.50 2.00 2.50

90% conf idence

lim it=0.85

UNDEGRADE

TRANS IT I O N A

DEGRADE

Figure 14. Benthic index grouping vs. ERM summary

quotient value. Each data point represents one station

(n=75).

Ben thic Community Ind e x Grouping

vs. ERM S umm a ry Quotient
80

from species density data from each site using the Systat®

statistical program. From this matrix several tests for

association of variables were performed. The tests employed are

common in marine and estuarine benthic community analyses and are

well-documented in the literature (Field et al., 1982; Pearson et

al 1983; Swartz et al., 1985; Gray, 1989; Clark and Ainsworth,

1993). Classification analysis was employed to demonstrate siterelated community patterns such as species dominance. Cluster

analysis is a multivariate procedure for detecting natural

groupings in data, and, for our purposes, data were grouped by

average similarities in total composition and species abundance

(Krebs, 1989). The average-linkage method calculates similarity

between a pair of cluster groups as the average similarity among

entities in the two groups. Species information is used to

compute similarity index values. Grouped stations were clustered

at a conservative distance limit of 50-60% similarity, however,

this level was purely arbitrary. Because classification analyses

have the tendency to force data into artificially distinct

groups, another method (e.g., multi-dimensional scaling) was used

to confirm the validity of group clusters and site similarity.

Ordination analysis was useful because it enables one to see

multidimensional gradients in data rather than just groupings

(Smith, personal communication).

Multi-dimensional scaling (MDS) is used extensively in the

analyses of benthic communities, particularly in estuarine and

marine pollution studies. MDS is a procedure for fitting a set of

points in space such that the distance between points correspond

to a given set of dissimilarities. This technique is more

flexible than principal co-ordinate analyses when handling the

large number of zero counts generally characteristic of speciessamples matrices. Nonmetric MDS analyses were performed using

Systat®. For a detailed account of MDS statistical procedures,

see Clarke and Ainsworth (1993) and Warwick and Clarke (1993).

Inferences from the resultant ordination are also presented. 

It is important to note that, as with cluster analyses, MDS

results are not definitive and must be used in conjunction with

additional ecological information. MDS results are based on total

species number and numbers of individuals. Inferences from the

resultant ordination are also presented.

After classification and ordination patterns were determined, the

raw data were reevaluated to assess which species may have

influenced the observed patterns. Indicator species were then

selected on the basis of a literature review (i.e., distribution,

life history strategies and habitat preference), by

recommendations from other experienced benthic taxonomists, and

review of the raw data. Initially, community analyses were

conducted as a per "site" comparison. Later, it was decided

analyses also be expanded to a per "station" comparison to

produce a more definitive data set for the reference pool. The

extended analysis of station variability was performed using the

benthic index.
81

Benthic assemblages have many attributes which make them reliable

and sensitive indicators of the ecological condition in estuarine

environments. The following procedure summarizes the construction

and application of the benthic index used to reliably

discriminate between degraded and undegraded conditions at sites

in the San Diego Bay Region. Although there are problems with

trying to simplify complex biological communities, we attempted

to develop a quantitative method which creates a partition

between degraded and undegraded areas. Polluted sites can not be

conclusively identified using results from benthic community

analyses alone, but these analyses impartially describe

"environmentally stressed" areas. This benthic index is based on

species (indicators), and group (general taxa) information. The

index also evaluates community parameters, such as species

richness, and abundance or presence of pollution indicators,

which identify the extremes of the community characteristics.

Sites are ranked according to these extremes and are represented

by a single value. In general, decreasing numbers of species,

increasing numbers of individuals, and decreasing diversity

values are common responses observed near polluted areas. These

trends are incorporated into the index. One of the important

restrictions with the existing method is it evaluates this

limited San Diego Bay benthic data set when dividing groups for

categorization. Construction and subsequent validation of this

simplified benthic index are loosely based on criteria developed

by several agencies, including USEPA-EMAP and SCCWRP. However,

the benthic index developed by USEPA-EMAP (Weisberg et al., 1993)

included several environmental variables in its construction

(e.g. dissolved O2), while the index for San Diego Bay data used

only biological parameters. Briefly, the following major steps

were followed in constructing and validating this benthic index:

 1. Degraded and undegraded (i.e., reference condition)

stations were identified on the basis of measured

environmental and biological variables.

 2. A list of "candidate" parameters was developed using

species abundance data. The list included metrics

having ecological relevance (e.g., species diversity

indices, etc.) which were used to discriminate between

degraded and reference areas.

 3. A value for each candidate parameter (i.e., diversity,

abundance, taxonomic composition) was calculated for

each station (e.g., total species per station, total

individuals per station, total crustaceans species per

station, total number of polychaete individuals, total

amphipods per station, etc.).

 4. Range of values per metric was determined (lowest to

highest value).

 5. Quartiles from that range were determined.

 6. Ranking within quartiles were assigned: upper

quartile=2, lower quartile=0, middle quartile=1. These

calculations were applied to the metrics from step 3.
82

 7. The index was defined by values of 0, 1, or 2. A value

of 0 defines the degraded (detectable stress)

stations(s), and 2 identifies environmentally

undegraded stations(s). Stations with an index value

of 1 are considered transitional communities, which

are neither degraded nor reference stations.

Transitional stations have species or other parameters

which indicate both degraded and undegraded habitats.

These stations are investigated further to determine

the cause of ambiguity of the transitional status.

 8. Relative abundance of indicator species (both degraded

and undegraded habitat indicators) per station is

assessed.

A primary concern regarding the benthic index is how well it

fulfills the objective of discriminating among degraded and

undegraded estuarine conditions. This simplified version forms

the basis for ongoing iterative procedures involved in

construction of an index. This index will include a variety of

indicator values (Bascom et al., 1978; Kerans et al., 1994;

EcoAnalysis et al., 1995) for future applications of the

assessment of benthic community structure. The following sections

report results of benthic community analyses based solely on

composition and abundance of macrobenthic species from sediment

cores throughout San Diego Bay and its vicinity. Environmental

parameters (e.g., total organic carbon levels and sediment grain

size range) and other factors capable of influencing benthic

composition were examined, but not evaluated in conjunction with

the data presented here. Those data are examined later in

sections which address correlative analyses.

In this study, bioeffects are required to be demonstrated in

relation to properly selected reference sites and to occur in

association with significant pollutant levels. The following

evidence for undegraded (possible reference) and degraded

(possible contaminated) sites was based on benthic community

"quality" at each site and station. Benthic community structure

was evaluated as an indicator of environmentally degraded or

undegraded areas and not as a pollution or contamination

indicator. Benthic reference sites were determined predominantly

by analyses of specific indicator species and groups (e.g.,

amphipods). These species are generally not found in polluted or

disturbed areas.

The intention of this section is to clearly describe the

condition of macrobenthic communities from sampling areas.

Definitions of degraded, transitional, and undegraded used in

this section are adopted from several papers (Bascom et al.,

1978; Pearson and Rosenberg, 1978; Schindler, 1987; Swartz et

al., 1985; Underwood and Peterson, 1988). Although the boundaries

set in Bascom et al. (1978) were based on food supply and not on

toxicants, the same general principles apply to this study. In

benthic analyses, the term "degraded" does not refer to a
83

community response to significant levels of toxic chemicals.

Degraded areas are those which contain significant numbers of

opportunistic species, in the absence of non-opportunistic

species, and have relatively low species diversity. Correlations

are later used to determine if community profiles are influenced

by chemistry or by natural environmental disturbances. Sites and

stations which are categorized as "undegraded" have high species

diversity, high proportional abundance of amphipods and other

crustaceans, while noting there are a few exceptions to this rule

(e.g., Grandidierella japonica, etc.). Undegraded areas generally

contain species which are known to be sensitive to pollutants.

Transitional sites and stations are those which are not

confidently partitioned into the other two categories. These

areas may solicit further study. Overall, an integration of data

from laboratory exposures, chemical analyses, and benthic

community assessments provide strong complementary evidence of

the degree of pollution-induced degradation in aquatic

communities. The following data analyses were conducted on a per

site basis using sample replicates (n=5) at each sampling

location (Table 6). An analysis also was performed using per

station data (n=1) and is presented later in this section. Tests

included classification and ordination analyses, diversity

measurements, construction of a benthic index, and assessment of

indicator species. One cautionary note is each of the benthic

community and population condition tests are subject to effects

of not only the pollutants measured in this study, but many other

confounding natural factors, such as depth, salinity, sediment

texture, and/or predation.

Abundance and Diversity

There were 7,232 individuals, representing 198 macrobenthic

species, collected from 375 benthic cores during sampling legs 20

through 23 of the San Diego Bay confirmation phase (Table 7).

Mean number of species was calculated from 5 replicates per site

(Table 8). Polychaetes comprised the majority of specimens in

samples. Great numbers of mollusks in sites within West Basin,

Downtown Piers, and Glorietta Bay were due to the bivalve

Musculista senhousei which was collected as large aggregates.

Echinoderms were found at only 6 of the 25 sites, and were

significantly (p>0.01) greater at the Mission Bay A3 site

(640.0±216.6) and the Mission Bay A8 site (213.3±53.3) compared

to all other sites. Holothurians comprised the majority of

echinoderms found at these sites, although ophiuroids were also

present. Colonial species were not present. Diversity ranged from

9 to 46 benthic species per site in collected samples.

Significant differences in species diversity were not as distinct

as with other indices and no trends were obvious. Results shown

in Table 9 indicate most communities in this study were

relatively diverse and even. Simpson's diversity index (D') which

emphasizes more common species, and Shannon-Weaver (H') which

puts statistical weight on rare species, showed differences in

the range of diversity values. Chula Vista Yacht Basin was the

only site which showed a moderately high level of dominance as




88

shown by the evenness index (J'=0.490). This was due to an

abundance of Mediomastus californiensis and Leitoscoloplos

pugettensis polychaetes. Compared to all other sites, Chula Vista

had a significantly lower density of crustaceans. The Mission Bay

A4 site had moderately high species diversity but comparatively

low species abundance.

Cluster and Ordination Analyses

Cluster analyses produced the dendrogram (Figure 15) of station

affinities, based on mean root-root transformed abundance of the

198 macrobenthic species, using Pearson's correlation of

similarity and group-average sorting. A root-root transformation,

reduced the weighting of abundant species (Field et al., 1982).

The similarity level, although arbitrary, was designated somewhat

conservatively near 50%. The resulting classification of

assemblages reflect general patterns of benthic species

composition, domination, and evenness (e.g., sites along the 0.00

line would be identical in species composition and abundance).

Six major groups were delineated from the hierarchical clusters,

which were defined by an overall dominant species. Group I, which

included only a single site (32 Swartz, Sweetwater Channel) was

co-dominated by the tube-building tanaid Zuexo normandi and

polychaete worm Leitoscoloplos pugettensis. Groups IV, V and VI

were all dominated by the polychaete worm species L. pugettensis,

Prionospio heterobranchia, and co-dominants P. heterobranchia and

oligochaetes, respectively. Amphipods (Acuminodeutopus

heteruropus) were the most abundant group in cluster II. The

seemingly ubiquitous bivalve Musculista senhousei was the

numerically important species in Group III. When plotted, these

biologically-based clusters provide a qualitative assessment of

the pattern of physical data and visually demonstrate the

relationship of one site to another. To put the relationship of

samples into a more general perspective, the level of similarity

found between San Diego Bay site samples and those from Los

Angeles Harbor was between 5-10% (Figure 16), revealing the

benthos of these northerly areas should not be used

comparatively, due to differences in habitats and biotic

response. Although tidally influenced, the species composition

of the San Diego River B1 site was also found to be highly

dissimilar to other San Diego Bay samples, presumably due to

habitat differences.

In addition to conventional methods, non-metric multi-dimensional

scaling (MDS) using a weighted Spearman rank correlation

coefficient dissimilarity matrix was used to determine similarity

in species composition between stations. Non-metric MDS can

handle large numbers of zeros, missing data, and unequal

replication. MDS seeks a representation of individuals in a space

of low dimensionality where the distances between individuals in

ordination space optimally represent their dissimilarities in

variable space (Kenkel and Orloci, 1986). Typically, transformed

biotic and abiotic data are initially analyzed separately, then

combined to assess common MDS spatial patterns. The resulting

ordination for biotic variables is demonstrated here.



92

displays the 2-dimensional representation resulting from

multidimensional scaling, using the same matrix data applied to

classification analysis. Letters surrounded by each circle

represent the partitioned cluster groups delineated in the

cluster hierarchy. The configuration was not altered when the

outlier (T) was removed. The x- and y-axes represent scores for

the first and second ordination axes. These scores are based on

species diversity data and abundance and composition data.

When sites with chemistry values which exceeded ERM levels were

assessed on the MDS plot in a qualitative, cursory manner as

shown in Figure 17b (shown with squares), the sites clustered

together. When interpreted along the axis gradient, these data

suggested dimension 1 likely defined the pollution gradient,

where the top quadrant within the plot identified the most

contaminated sites (i.e., Q or H). This is assuming the plot

configuration is affected by toxic pollution alone and not by any

organic enrichment. The y-axis may represent responses to a

salinity gradient or change in sediment grain size. These

analyses are especially revealing when environmental variables

(e.g, TOC, grain size, water depth, total PAHs, individual

metals, etc.) and biota are scaled together to determine which

variables influence the configuration. However, even in the

absence of these parallel plots, patterns are apparent from the

correlations illustrated in other sections of this report.

Indicator Species

Despite the numerous studies performed in San Diego Bay, there

have been no analyses of the fauna as bioindicators (SCCWRPDiener, personal communication). Indicator species are assessed

to determine which species are responsible for the separation of

groups in classification and ordination analyses (Field et al.,

1982). Indicator species used in this study were selected on the

basis of overall abundance in the San Diego Bay data set,

literature review which determined distribution, known life

histories and habitat preference, and discussions with ecologists

experienced with Southern California marine biota and marine

habitats. Species indicative of control or reference sites were

derived from frequency of occurrence data. The presence or

absence of specific polychaetes in sediments provided one

valuable indication of the condition or health (Pocklington and

Wells, 1992) of the benthic communities in San Diego Bay. The

presence of Capitella capitata or Streblospio benedicti, in the

absence of other species, is widely accepted as pollution

indicators. Sensitive species like Harmothoe imbricata are

represented at sites Carrier Base V2 and Mission Bay A8, and are

typically found in uncontaminated areas. Additionally, Nereidae

are accepted as indicators of early successional phases of

environmental recovery (Pearson and Rosenberg, 1978) and are

evident at site Carrier Base V2. Mediomastus polychaetes are

found throughout the bay and have been considered to be

identifiers of environmentally stressed areas. However, this

species was found at the majority of sites. Another common

species found in 16 out of 25 station samples was Diplocirrus sp.
93

which had not been found in previous studies in San Diego Bay

(SCCWRP, personal communication). Dipolocirrus sp. was

significantly (p>0.05) abundant at the Mission Bay A8 site. This

unusual species is thought to have been introduced from the

arctic region (G. Ruff, personal communication).

The benthic index discussed later was used to rank and calculate

site partitions using the following indicator species: Capitella

capitata (polychaete), Armandia brevis (polychaete), Dorvillea

longicornis (polychaete), Heterophoxus oculatus (gammarid

amphipod), and Diastylis sp. (cumacean). The polychaete worm C.

capitata is widely accepted as a pollution indicator. Diastylis

sp. ("sand-licker") feeds on nutrients adhered to sand grains and

its presence indicates a relatively clean sample. Although it can

tolerate moderately contaminated sediments, H. oculatus is a

burrower and is considered an indicator of clean sediment.

One of the limitations in benthic community assessment is that

patterns are more apparent where there is a strong gradient of

pollutants, or when samples are selected from areas with

distinctively low and high pollutant signals. There are

limitations to what can be surmised from analyses of abundance of

specific species, and selection of indicator species are highly

site specific (Swartz et al., 1985). However, these species,

combined with information from ordination and other supplemental

analyses, make it apparent that these are important as

ecologically relevant data. Many species used to assess

environmental quality are used because they respond quickly to

changes in environmental conditions. (Pocklington and Wells,

1992). Therefore, a station designated in the initial phases of

sample collection as a having reference conditions, based on

toxicity test or chemical analysis results, could be removed from

the reference station list based on subsequent benthic community

analyses.

Benthic Index

Benthic communities, and occasionally single benthic species,

have been used to elucidate the severity of human disturbance to

nearshore marine and estuarine environments. It is possible to

develop a comparable disturbance classification for species and

use a simple numerical infaunal index with these species.

Distinct pollution gradients are rare in most embayments because

of confounding environmental gradients and historical changes.

Still, an index has the best potential to quantitatively assess

benthic community responses to disturbance. Some benthic indices

are based on a priori information and are developed using test

sites representing the extremes within a range of environmental

conditions which adversely affect benthos. In contrast, the index

developed and used in this study was based solely on information

which characterized the benthic community, such as specific

indicator species and community parameters (species richness,

abundance, presence of pollution indicator species, etc.). This

elementary index approach may be best for this study because San

Diego Bay encompasses a variety of habitats, each of which may
94

require a very specific set of index variables (SCCWRP-Diener,

personal communication). Note that identification of degraded and

undegraded sites here resulted from evaluation of a limited data

set, without site comparison to an existing known reference. The

index was used within this limited data set to designate the

partition between degraded, undegraded and transitional areas.

Site and Station Application of Benthic Index

Table 10 shows the results of benthic index application to data

from sampling sites in legs 20-23. Sites (25 sites with 5

replicates each) were ranked and partitioned into 9 degraded, 3

undegraded and 13 transitional sites using 8 biotic parameters.

Due to spatial differences in sampling of the benthic replicates

at the 25 sites, the benthic index was also applied to individual

stations (n=75). When benthic community structure was evaluated

"by site", 5 replicates were used. Replicates 1, 2 and 3 were

sampled at numbered stations locations (Table 6) where associated

toxicity and chemistry data could be directly compared. When

later analyses were expanded to a "by station" evaluation, the

4th and 5th replicates were not included in the per station

assessment. These replicates were randomly sampled within the

"site" for benthic community analysis only and did not receive

synoptic chemistry and toxicity analysis. While the results did

not alter the degraded and undegraded determination of sites

assessed "by site", it did separate stations within the initial

"transitional" status into one of the three categories (e.g.,

degraded, transitional or undegraded). Station analyses heavily

emphasized benthic index, amphipod abundance, species diversity

and crustacean numbers.

As part of analytical procedure, the BPTCP Scientific Planning

and Review Committee (SPARC) recommended additional emphasis on

the use of amphipod abundance and overall species diversity as

indicators of degraded and undegraded areas. These parameters

were assessed and incorporated into the "station evaluation"

versions of the benthic index. Species number and abundance of

amphipods were calculated from the proportions of total species

and total individuals, respectively. The resultant categorization

of stations into one of the three partitions (e.g., degraded,

transitional, undegraded) did not change, so the assessment of

amphipods further supported the partition derived from previous

analyses. The density of all amphipods was significantly more

abundant at the following stations: West Basin (90050, 93199,

93200), East Basin (90001, 93201), Downtown Anchorage (93221,

93222), Coronado Cays (90053, 93203), Sweetwater Channel (93220),

Mission Bay A8 (93112), Carrier Base V2 (90025) and Grape St.

Stormdrain (90037). No amphipods were found at stations 14

Downtown Piers (90003), Naval Base O7 (93212), Naval Base/SY O10

(93223, 93224), Naval Base/SH O13 (93225, 93226), 7th St.

Channel Q1 (90009, 93227, 93228), Marine Terminal R3 (93229), K

Swartz Naval Base O4 (93210), Sub Base C2 (93216, 93217), and 

Naval Base O12 (93215). Stations with abundant amphipods but

dominated by Grandidierella japonica were evaluated with caution,

because G. japonica has been found to be tolerant of high

96

sediment toxicity (Slattery and Swartz, personal communication).

Final benthic community evaluation of 75 stations (Table 11)

resulted in the designation of 23 undegraded, 43 degraded and 9

transitional stations. A map of the distribution of degraded,

transitional and undegraded stations is shown in Figure 18(a-d).

Degraded stations were found at the submarine base in North San

Diego Bay. Commercial shipping, storm drainages and the naval

shipyard waterfronts all had degraded communities in the Mid San

Diego Bay. In South San Diego Bay, industrial and small boat

locations exhibited benthic community degradation. In Mission Bay

the stations near Rose Inlet and in the San Diego River were

found to be degraded.

Chemically clean sites, as determined by ERM and PEL summary

quotients and lack of ERM and PEL guideline exceedances, were

reexamined to expand the undegraded list from possible

"borderline" transitional stations. Stations 93194 and 93231

appropriately fit this category (Table 4) and were used as

undegraded stations in the construction of the reference envelope

for toxicity determination, discussed earlier. 

As shown earlier in Figure 14, the relationship between benthic

community conditions and elevated chemical conditions (as

determined by using ERM and PEL Summary Quotients) was quite

dramatic. Benthic communities were always found to be degraded

when chemical levels were elevated (ERMQ>0.85), where both

analyses were performed at a station. 

Distribution Of Toxicity

The results of all toxicity tests conducted as part of this study

are presented in tables in Appendix D. These tables show means

and standard deviations for each toxicity test response (e.g.

percent survival of amphipods; percent normal development of

larval sea urchins) for three to five replicates of each sample

tested. Associated ammonia and hydrogen sulfide concentrations

are also presented in Appendix D.

Toxicity Testing Quality Assurance/Quality Control Evaluation

All toxicity test data produced for this report were evaluated

for acceptability using the Quality Assurance guidelines

described in the BPTCP Quality Assurance Project Plan (QAPP;

Stephenson et al., 1994). Toxicity data reported here met all

test acceptability standards for each protocol, with the

following exceptions. Of the solid phase tests with amphipods,

two samples (Station 93120- IDORG# 702 and Station 93107- IDORG#

721) were tested with only one laboratory replicate, due to a

lack of sufficient sample volume. Survival in those two samples

was 90% and 85%, respectively, indicating a lack of toxicity. 

All amphipod samples tested in Leg 15 (Appendix D) have the

following QA qualification. The test protocol requires five

replicates of a control sample to be tested concurrently with

test samples. In some early sampling legs of this study, 15

laboratory replicates of the control sediment were tested, to

93217 90028 93216

Sub Base C2

Carrier Base V2

90001

93201

93202

West Basin

East Basin

90050

93199 93200

90025

93232

93231

Figure 18a

Benthic Community Analyses

North San Diego Bay

Index of Degradation

0 Degraded

1 Transitional

2 Undegraded
93217 90028 93216

Sub Base C2

Carrier Base V2

90001

93201

93202

West Basin

East Basin

90050

93199 93200

90025

93232

93231

Figure 18a

Benthic Community Analyses

North San Diego Bay

Index of Degradation

0 Degraded

1 Transitional

2 Undegraded
Intercont. Marina

90003

93206

90037

93222

90051 93192

93207

93193

Glorietta Bay

Grape St.

Dowtown Piers

G. St. Pier Marina

Downtown Anch.

93223

93224

93215

90007

90022

93214

Naval Base /SH 010

Naval Base 012

93212

93211

93210 90021

90006

93213

Naval Base O7

Naval Base O4

Seventh St. Channel

Q1

93227

90008

93226

93225

90009

93228

Naval Base/

SH O13

90002

93221

93205

93208

90004

93194

90015 93195

Index of Degradation

0 Degraded

1 Transitional

2 Undegraded

Figure 18b

Benthic Community Analyses

Mid San Diego Bay
93197 93196

90012

90013

93230

90010

93229

Marine Terminal R3

Sweetwater Ch.

Marina

Coronado Cays

93191

93190

90052

93220

93219

93203

90053

93204

CV Yacht Basin

Index of Degradation

0 Degraded

1 Transitional

2 Undegraded

Figure 18c

Benthic Community Analyses

South San Diego Bay
93112

93116

93107

Mission Bay A8

Mission Bay A4

San Diego River B1

Mission Bay A3 93108

Index of Degradation

0 Degraded

1 Transitional

2 Undegraded

Figure 18d

Benthic Community Analyses

Mission Bay and San Diego River Estuary
102

allow use of alternative statistical procedures. Of the fifteen

control replicates in Leg 15, two had 75% survival, which is

below the 80% criterion given in the protocol. In tests using the

Neanthes arenaceodentata (hereafter Neanthes) protocol on solid

phase sediments, all samples tested in Leg 21 used sediment that

was held in the laboratory three days beyond the fourteen-day

specified holding time. These QA exceptions in solid phase tests

have been judged by the toxicity project officers to not

adversely affect interpretation of toxicity results. These and

lesser departures from acceptable standards are recorded in the

Quality Assurance Evaluative Reports accompanying each dataset

for this study. Quality Assurance Evaluative Reports for toxicity

testing are available for review from the SWRCB. Minor departures

not mentioned above included elevated dissolved oxygen

measurements in overlying water and other variations in water

quality measurement that were considered to have little

probability of affecting the outcome of the respective toxicity

test.

There were no deviations from quality assurance criteria, other

than minor deviations in measurement of water quality parameters

as cited above, in any of the abalone, mussel, or sea urchin

larval development tests in pore water or water column samples

(subsurface water).

Sea urchin fertilization tests were conducted on over 300 pore

water samples. Many of these were retested because of poor

response in brine controls. Bay et al. (1993) discussed commonly

observed problems using the Strongylocentrotus purpuratus

(hereafter Strongylocentrotus) fertilization test in samples

requiring salinity adjustment with hypersaline brine. Through

numerous repeated tests, acceptable brine control results were

produced for all but one sample. However, as described in BPTCP

QA reports to the SWRCB, an additional control for the storage

effects of frozen pore water samples in Teflon bottles was

included in later tests. These additional controls, which were

not required by the original QAPP, indicated that toxicity may be

associated with frozen sample storage in Teflon bottles. Because

all pore water samples for fertilization tests were stored frozen

in Teflon bottles, we have no assurance the data from any of

these fertilization tests is truly indicative of sample toxicity.

Any toxicity observed in the fertilization tests may be wholly or

partially due to storage effects. For this reason, we retested

all samples from legs 15-23 with the sea urchin larval

development test, unless those samples had already been tested

with the development test. The urchin larval development test has

been unaffected by storage artifacts, as indicated by response in

frozen storage bottle controls. While sea urchin fertilization

data are reported in Appendix D, they were not used in any

further data analysis for this report. The use of fertilization

data, for determination of toxicity, was therefore not considered

prudent considering the possibility of false positive results

related to sample storage.
103

Areal Extent of Toxicity Based on the EMAP Approach

The Cumulative Distribution Frequency (CDF) analyses indicated

that 56% of the total area sampled was toxic to Rhepoxynius

abronius (hereafter Rhepoxynius) (Table 12, Figure 19). The sea

urchin larval development test of undiluted (100%), 50%, and 25%

pore water indicated 74%, 54%, and 29% percent of the total study

area was toxic, respectively (Table 12, Figure 20). A number of

samples were toxic to both sea urchins and amphipods. Samples

representing 36%, 27%, or 14% of the study area were toxic to

Rhepoxynius in solid phase sediment and to sea urchin larvae in

100%, 50%, or 25% pore water, respectively. The percentage of

area toxic was based on comparisons with laboratory controls

using the EMAP statistical approach described in the methods

section. These analyses utilized data from random stations within

the stratified sampling blocks, and did not include data from

stations utilizing the non-random, directed sampling design

(Figure 21a-d, Figure 22a-d).

The curves on the CDF plots indicate the magnitude of toxicity

throughout the Region. Each point on the CDF plot represents a

single sample. The distribution of the amphipod data (Figure 19)

show there were few samples with survival less than 40%, a

greater number of samples with survival between 40% and 80%, and

about half of all samples with survival greater than 80%. NOAA

surveys of Tampa Bay, Florida and EMAP surveys of the MidAtlantic coast region (Virginian Province) produced CDF curves

for amphipod mortality data further right on the scale and much

steeper than the San Diego Bay Region plot, and had more than 90%

of samples with greater than 90% survival in both regions (Long

et al., 1994; Schimmel et al., 1991).

The CDF plot of San Diego Bay Region sea urchin larval

development test data (Figure 20) shows a cluster of samples with

0% normal larval development, a smaller number of samples with

intermediate response, and a cluster of samples with percent

normal development roughly equal to that observed in controls.

The 25% pore water dilutions had a majority of samples resulting

in percent normal larval development roughly equal to controls.

As pore water concentration increased to 50% and 100% pore water,

the distribution of samples shifted toward the more toxic end of

the scale, and the 100% pore water tests had a majority of

samples resulting in 0% normal larval development. A similar

pattern was observed in sea urchin fertilization tests of pore

water from Tampa Bay, Florida (NOAA, 1994). As with the amphipod

data, the San Diego distribution is shifted further to the left,

indicating higher overall toxicity observed from San Diego Bay

Region samples.

Toxicity Based on Reference Envelope Approach

Using the Rhepoxynius data and a p-value of 1%, a lower reference

envelope tolerance bound of 48% survival was calculated,

indicating that samples with survival values below 48% are

significantly more toxic than samples representative of less



93162

93161

93152

93216

93217

93186

93143

93153

93163

93134

93149

93166

93140

93164

93136

93139

93167

93141

93165

93168

93135

93138

93231

93137 93169

93199

93201

93200 93202

93154

93188

93232

93148

Figure 21a

Amphipod Toxicity Using Lab Controls

for Randomly Sampled Stations 

North San Diego Bay

Significantly Different &

<80% of Lab Controls

Toxic

Nontoxic
93156

93144

93192

93193

93145

93207

93142

93205

93221

93222

93155

93157

93206

93208

93122

93147

93146

93124

93172

93123

93195

93194

93173

93126

93179

93180

93125

93177

93211

93178 93210

93182

93213

93133

93224

93215

93185

93181

93223

93212

93184

93170 93183

93228

93227

93214

93226

93225

93171

93187

Significantly Different &

<80% of Lab Controls

Toxic

Nontoxic

Figure 21b

Amphipod Toxicity Using Lab Controls

for Randomly Sampled Stations 

Mid San Diego Bay
93190

93158

93159

93131

93127

93191

93150

93151 93220

93219

93230

93229

93203

93129

93204

93132

93128

93197

93196

Significantly Different &

<80% of Lab Controls

Toxic

Nontoxic

Figure 21c

Amphipod Toxicity Using Lab Controls

for Randomly Sampled Stations 

South San Diego Bay
93115

93112

93114

93110

93109

93116

93108

93107

93105

93117

93111

93106

93113

Significantly Different &

<80% of Lab Controls

Toxic

Nontoxic

93118 93119

93175

93120

93121

93174

Significantly Different &

<80% of Lab Controls

Toxic

Nontoxic

Figure 21d

Amphipod Toxicity Using Lab Controls

for Randomly Sampled Stations

Mission Bay and San Diego River Estuary

Tijuana River Estuary
93162

93161

93152

93216

93217

93186

93143

93153

93163

93134

93149

93166

93140

93164

93136

93139

93167

93141

93165

93168

93135

93138

93231

93137 93169

93199

93201

93200 93202

93154

93188

93232

93148

Figure 22a

Urchin Development Toxicity Using Lab Controls

for Randomly Sampled Stations 

North San Diego Bay

Significantly Different &

80% of Lab Controls

Toxic

Nontoxic

Not Analyzed

Dilution Factors

Undiluted

50% Dilution

25% Dilution
93156

93144

93192

93193

93145

93207

93142

93205

93221

93222

93155

93157

93206

93208

93122

93147

93146

93124

93172

93123

93195

93194

93173

93126

93179

93180

93125

93177

93211

93178 93210

93182

93213

93133

93224

93215

93185

93181

93223

93212

93184

93170 93183

93228

93227

93214

93226

93225

93171

93187

Significantly Different &

80% of Lab Controls

Toxic

Nontoxic

Not Analyzed

Figure 22b

Urchin Development Toxicity Using Lab Controls

for Randomly Sampled Stations 

Mid San Diego Bay

Dilution Factors

Undiluted

50% Dilution

25% Dilution
93190

93158

93159

93131

93127

93191

93150

93151 93220

93219

93230

93229

93203

93129

93204

93132

93128

93197

93196

Significantly Different &

80% of Lab Controls

Toxic

Nontoxic

Not Analyzed

Figure 22c

Urchin Development Toxicity Using Lab Controls

for Randomly Sampled Stations 

South San Diego Bay

Dilution Factors

Undiluted

50% Dilution

25% Dilution
93115

93112

93114

93110

93109

93116

93108

93107

93105

93117

93111

93106

93113

Significantly Different &

80% of Lab Controls

Toxic

Nontoxic

Not Analyzed

93118 93119

93175

93120

93121

93174

Significantly Different &

80% of Lab Controls

Toxic

Nontoxic

Not Analyzed

Figure 22d

Urchin Development Toxicity Using Lab Controls

for Randomly Sampled Stations

Mission Bay and San Diego River Estuary

Dilution Factors

Undiluted

50% Dilution

25% Dilution

Dilution Factors

Undiluted

50% Dilution

25% Dilution

Tijuana River Estuary
115

contaminated ambient conditions in the San Diego Bay Region. 

There is a 95% probability that samples with survival values less

than 48% are more toxic than the most toxic 1% of samples from

the reference site population. Of 350 samples tested with the

Rhepoxynius test (from both random and non-randomly selected

stations), 61 samples were found to be toxic using the reference

envelope analysis (Figure 23a-d). Toxicity based on the reference

envelope approach is used later in this report for prioritizing

stations of concern.

Strongylocentrotus pore water data from reference stations

produced a lower mean value and greater variability than was

found for the amphipod solid phase data (Table 4). The

variability in pore water data from sea urchin larval development

tests produced a reference site distribution extending across the

range from 0 to 100% normal development. A p-value of 1% (see

Methods Section) produced a tolerance bound (reference envelope

edge) which was below zero, indicating no distinctions could be

made between reference and toxic stations. The high degree of

variability in the pore water results from the reference sites

may be related to the sensitivity of this test to measured or

unmeasured toxicants, and/or may reflect artifacts related to

pore water extraction and handling. Potential artifacts and

sources of variability related to pore water testing are

discussed below.

Comparison of Toxicity Test Protocols

Solid phase toxicity tests using the amphipod Rhepoxynius

provided a wide range of response, from 0 to 98% survival.

Amphipod survival ranged from 68-98 % for the eleven reference

stations, suggesting that relatively high Rhepoxynius survival is

a consistent feature of sites with relatively low chemical

concentrations and undegraded benthic communities. The

Rhepoxynius test identified multiple toxic samples, which

indicated adequate sensitivity. Of the two solid phase protocols

used in this study, the Rhepoxynius test provided the best test

performance in terms of convenience, consistency, and

sensitivity.

Solid phase toxicity tests which used the polychaete Neanthes

were less sensitive than the Rhepoxynius test, and usually

indicated no toxicity in samples that were toxic to test

organisms using other protocols. In all instances where a

sediment sample was toxic to Neanthes (survival or growth -

relative to controls), it was also toxic to Rhepoxynius, whereas

many samples that were toxic to Rhepoxynius were not toxic to

Neanthes test. Because the Neanthes test demonstrated

considerably less sensitivity than the Rhepoxynius test, the

Neanthes test was not recommended for continued use in this

program.

Two pore water tests, using Strongylocentrotus fertilization and

larval development protocols, were performed on three

concentrations of pore water samples to evaluate their usefulness
90071

93161

90028

90029

93216

93162

93217

90063

93138

90048

93141

90056

90104

90049

90102

93164

90023

93134

90026

93136

93149

93163

90103

93231

93188

90016

93169

93148

90001

90025

93199 93200 93202

93135

90027

93186

90101

93143

93153

93152

93139

93140

93166

93167

93165

93137

93168

90024

93232

93154

90050

93201

90055

Figure 23a

Amphipod Toxicity Using Reference Envelope

for All Stations

North San Diego Bay

Percent Survival

48 to 100% Survival

0 to 48% Survival
93155

90004

93156

93142

93208

93207

93221

93205

90037

93206

93222

90002

90003

90039

93123

93146

90017

90018

90020 90021

93178

90005

90019

93182

90006

93211

93180

90030

90031

93213

93185

93223

90032 93212

90007

90022

93183

93214

93194

93147

90015

93195

93122

93124

90043

93157 90051

93192

93193

93145

93144

90038

93177

93125

93172

93173

93181

93210

93179

93126

93170

90014

93224

93215

93133

90008

93184

93226

93225

93171

93187

90009

93227

93228

Percent Survival

48 to 100% Survival

0 to 48% Survival

Figure 23b

Amphipod Toxicity Using Reference Envelope

for All Stations 

Mid San Diego Bay
93191

93190

93151

93197

90036

93128

93220

93219

90057

93159

90054

93158

93127

90013

93150

93203

93131

90053

90011

90052

90040

93230

90010

93229

93204

93132

90058

90041

90012

93196

93129

Percent Survival

48 to 100% Survival

0 to 48% Survival

Figure 23c

Amphipod Toxicity Using Reference Envelope

for All Stations

South San Diego Bay
93115

93112

93114

93116

93108 93110

93109

93117

93107

93106

93105

93113

93111

Percent Survival

48 to 100% Survival

0 to 48% Survival

93119

93175

93118

93120

93121

93174

Percent Survival

48 to 100% Survival

0 to 48% Survival

Figure 23d

Amphipod Toxicity Using Reference Envelope

for All Stations

Mission Bay and San Diego River Estuary

Tijuana River Estuary
120

as components of the BPTCP. Results indicated these tests were

extremely sensitive to pollutants and/or other pore water

constituents in the study area, particularly at the 100%

porewater concentration. It is reasonable to expect that pore

water sea urchin tests, which measure sublethal effects on

sensitive early life stages, would be more sensitive than the

amphipod solid phase tests, which measure adult mortality. It is

also likely that all three protocols respond differently to

different contaminants. The high sensitivity of the sea urchin

protocols has been observed in other studies assessing pore water

toxicity (Burgess et al., 1993; Carr and Chapman, 1992; Long et

al., 1990).

Rhepoxynius solid phase test results agreed with

Strongylocentrotus development (100% and 50%) pore water results

in 61 of 117 concurrently tested samples (52%). For the 25% pore

water dilution, results agreed in 48% of samples. The three

dilutions for the Strongylocentrotus tests agreed with each other

56% of the time. In all but two cases, Strongylocentrotus

results differed from each other because samples were less toxic

as pore water was increasingly diluted. In one case the 50% pore

water was toxic when the 100% and 25% were not, and in another

case, the 50% and 25% were toxic when the 100% was not.

Carr and Chapman (1992) noted that sensitive toxicity test

protocols are necessary to adequately characterize the toxicity

of potentially contaminated sediments. Pore water tests provide

the following advantages: allow the use of a variety of sensitive

sublethal toxicity test protocols which have not yet been

developed for solid phase tests; eliminate interference from

physical factors such as sediment grain size; and allow test

organisms to be directly exposed to the aqueous sediment

fraction, the probable primary route of pollutant exposure to

organisms (Adams et al., 1985; DiToro, 1990). In addition, pore

water is currently the only sediment matrix suitable for toxicity

identification evaluations that may be useful in identifying

toxicants responsible for observed sediment toxicity.

Despite the need to evaluate pore water toxicity, logistical

issues of pore water extraction and handling are still a focus of

current research (Carr et al., 1995). Among the samples

associated with high toxicity in the sea urchin pore water tests

were a number from the selected reference stations. These

stations had non-degraded benthic communities, relatively low

concentrations of pollutants, and ammonia concentrations below

levels expected to have an observable effect. The wide range in

pore water toxicity at the reference stations was unexpected, and

prevented identification of toxic sites using the reference

envelope approach. Pore water properties and sampling

manipulations that may have affected pore water test results are

discussed later.

Samples of water collected one meter above the sediment surface

were tested for toxicity at a number of stations. These

subsurface water samples were tested as one of the suite of
121

screening bioassays conducted on suspected areas of water quality

impairment. Sixty-five subsurface water samples were tested with

the red abalone (Haliotis rufescens) larval shell development

protocol. Of these, eleven samples were significantly toxic,

indicating degradation of the water column in 17% of the stations

tested. Water column testing has not been a consistent component

of the BPTCP, and will probably be reserved for special

investigations. The abalone test appears appropriate for this

application.

The bivalve (Mytilus sp.) larval shell development test was used

to test eight subsurface water samples and three pore water

samples. This test was used only in cases where salinity was less

than 30 or 26 parts per thousand, the low end of salinity ranges

for abalone and sea urchin larval development tests,

respectively. Because seawater salinities in the San Diego Bay

region were usually in the acceptable range for abalone and sea

urchins, the bivalve test was used sparingly. None of the

subsurface water samples tested with mussels were significantly

toxic, and one of three pore water samples tested with mussels

was significantly toxic. This protocol is well established as a

sensitive test method, and has the advantage of a relatively wide

salinity range. In situations where the salinity range precludes

the use of abalone or sea urchins, the bivalve test is an

acceptable alternative.

The presence of mitotic aberrations in anaphase cells (cytogentic

abnormalities) of Strongylocentrotus were determined in some

samples. Cells undergoing mitosis were analyzed for chromosomal

abnormalities. This porewater test is appropriate for identifying

samples containing genotoxic compounds, which may affect

reproductive capacity in a wide variety of organisms. Though the

test is useful for specific applications, it proved timeconsuming for assessing large numbers of samples. Most porewater

samples that demonstrated increased aberration rates also were

significantly toxic in larval development tests. Since the larval

development test was considerably easier to quantify and was

being used routinely as part of the study, the mitotic aberration

endpoint was discontinued for logistical reasons. It would be

useful in specific applications where the effects of genotoxic

compounds must be assessed. 

Evaluation of Utilization of Pore Water as a Test Medium for the

BPTCP

The diffusive flux of dissolved chemicals through the sediment

water interface into the overlying water column is a major

component of sediment diagenesis and chemical cycles. Bioassay

testing of the filtered pore water is an attempt to address

exposure of animals living in the sediment matrix, or near the

sediment/water interface, to chemicals not associated with the

particulate phase. Equilibrium-partitioning theory predicts pore

water is the controlling exposure medium in the toxicity of

sediments to infaunal organisms (Adams et al., 1985; DiToro,

1990). To accurately interpret pore water test results, it is
122

important to determine how manipulations of pore water during

extraction and handling may have affected observed toxicity. The

BPTCP utilized a low pressure (<200psi) squeezing extraction

technique with filtration to 0.45 um, and subsequent freezing of

pore water samples, prior to testing. There has been some debate

regarding appropriate pore water extraction methods and sample

manipulations for the purposes of toxicity testing (Carr et al.,

1995; Schults et al., 1992). Squeezing techniques allow pore

water to be selectively filtered, thus eliminating particulates.

Suspected artifacts from the squeezing technique may include

chemical disequilibria through physical disruption of weakly

charged ion/particulate associations or lysing of cell walls with

resultant changes in concentration of dissolved and particulate

organic carbon or other organic components. There is also concern

that filtration has a profound effect on observed toxicity. Pore

size and filter material can cause variability in measured

chemical concentrations (Schults, et al., 1992). Many scientists

are now using centrifugation to obtain pore water from sediment

for toxicity testing, because this method may be less subject to

toxicity artifacts than squeezing (Lange et al., 1992; Giesy et

al., 1990).

Toxicity has been observed to decrease in bedded sediments which

are tested after freezing and thawing, with observed changes

assumed to be related to the release of soluble organic carbon

through disruption of natural lattices, clay aggregates and

organic matter (Schuytema et al., 1989). Although solids are

removed from pore water samples, there remain some soluble

organic carbon concerns due to disruption of colloidal

aggregations in the pore water, however centrifugation of pore

water samples prior to freezing helps minimize this effect (Carr

and Chapman, 1995). There are other unresolved concerns related

to the toxicity testing of sediment pore waters which require

additional study. These include sediment sample handling and

storage conditions prior to testing, oxygen contamination,

storage time of pore water samples prior to testing (Lange et

al., 1992) and sorption kinetics in toxicity test containers and

extraction devices (Pittinger, 1988). 

Dose responses from the three pore water dilutions demonstrate

decreasing toxicity with increasing pore water dilution,

confirming that some factor associated with pore water was

causing toxicity. However, considering the uncertainty of

introduced artifacts during sample manipulations, the ability to

discriminate more severely impacted sediments from less severely

impacted sediments (a primary goal of the BPTCP) is clearly

compromised. As a result of this uncertainty, toxicity testing

using pore water as the test medium was suspended in August,

1993, pending further method evaluation. Pore water extraction

methods and pore water sample handling have been under evaluation

by the BPTCP since that time, with preliminary results indicating

that centrifugation and refrigerated (not frozen) sample storage

may be the preferable methods when testing this matrix. Recent

method comparison research of Carr and Chapman (1995) supports
123

the use of squeezing technique yet concludes that in situations

where hydrophobic organic compounds are a concern (as they are in

this program), centrifugation is the method of choice for

maximizing the sensitivity of the toxicity test. Sample storage

and holding times were critical for all methods evaluated and

require further investigation (Schults et al., 1992).

As pore water test methods, test organism selection, and the

interpretation of results continue to evolve, they will be

evaluated for use by the BPTCP. Because test sensitivity is

necessary for accurate sediment characterization, the

Strongylocentrotus pore water larval development toxicity test

protocol should continue to be included in BPTCP. At present,

pore water toxicity data by themselves are difficult to

interpret. If pore water toxicity tests are used in conjunction

with solid phase toxicity tests, chemical measurements and

benthic community evaluations, they can provide useful additional

information when using a weight of evidence approach toward site

characterization.

Distribution of P450 Reporter Gene System Response

Induction of the CYP1A1 gene on the human chromosome is produced

by such compounds as dioxins, furans, dioxin-like PCB congeners

(coplanar), and several high molecular weight polycyclic aromatic

hydrocarbons. This induction and resulting production of the

detoxifying enzyme, P450, infers that these xenobiotics are

present at levels that are potentially toxic, carcinogenic, or

mutagenic to organisms. The P450 Reporter Gene System (RGS) assay

can measure the response of human (101L) cells to organic

extracts when a firefly plasmid at the CYP1A1 site produces the

enzyme luciferase. A luminometer is used to quantify the

luciferase as a function of concentration and potency of the

organics in the extract. Solvent extracts (using standard

extraction methods EPA 3510, 3450 or 3550) of water, aquatic

sediments, soils and tissues can be tested in the assay system,

with a measured response in 16 hours (Anderson et al., 1996).

Findings of the P450 Reporter Gene System (RGS) assay of sediment

extracts from 30 stations are summarized in Figure 24, where the

RGS responses (in 101L cells) are expressed as μg/g (ppm) of

benzo(a)pyrene equivalents (BaPEq). The Mission Bay A8 (93112)

station, Coronado Cays T2 (93203, 93204) stations, Shelter

Island E1 & E3 (93138, 63164) and the Sweetwater Channel stations

produced baseline responses in the range of 5.3 to 10.4 μg/g

BaPEq. Figure 24 shows that all Naval Shipyard stations, the

Commercial Basin station, the Marine Terminal and Downtown piers,

as well as Seventh Street and the Sub Base stations all produced

strong RGS responses. These responses suggest that benthic fish

and invertebrates living in contact with these sediments have a

high probability of P450 enzyme levels above background, which

could result in chronic toxicity, and/or damage to tissues and

reproductive potential.

http://www.norcalsetac.org/meetings.htm

Examination of the relationship between RGS response to sediment

extracts and total PAHs concentration in sediments demonstrates
CORONADO CAYS T1 (x1)-93131

CORONADO CAYS T2 (x2)-93204

SHELTER ISLAND E1 (x1)-93164

CORONADO CAYS T2 (x1)-93203

MISSION BAY A8 (x1)-REP 2-93112

SWEETWATER CH. JJ1 (x1)-REP 2-93219

GLORIETTA BAY U1 (x2)-93195

SOUTH SHORE-CORONADO DD3 (x1)-93122

NAVY ESTUARY G2 (x1)-93166

SHELTER ISLAND E3 (x2)-93138

GLORIETTA BAY U3 (x1)-93147

CARRIER BASE V1 (x2)-93188

NAVAL SHIPYARDS O11 (x1)-93184

COMMERCIAL BASIN F3 (x1)-93141

CARRIER BASE V2 (x7)-93232

NAVAL SHIPYARDS O6 (x1)-93181

P SWARTZ (NAVAL BASE O12)-90022

MARINE TERMINAL R3 (x3)-93230

NAVAL SHIPYARDS O3 (x1)-93179

NAVAL BASE/SHIPYARDS O4 (x1)-93210

NAVAL BASE/SHIPYARDS O7 (x4)-93213

MARINE TERMINAL R3 (x1)-93229

NAVAL BASE/SHIPYARD O10 (x2)-93223

NAVAL BASE/SHIPYARD O13 (x1)-93225

DOWNTOWN PIERS K1 (x11)-93206

NAVAL BASE/SHIPYARDS O4 (x2)-93211

NAVAL SHIPYARDS O2 (x1)-93178

NAVAL SHIPYARDS O1 (x1)-93177

SEVENTH ST CHANNEL Q1 (x6)-93228

SUB BASE C2 (x3)-93217

0 20 40 60 80 100 120

D

D

D

D

D

D

D

D

U

D

D

D

D

D

U

D

U

D

U

T D

Figur e 24 . P450 Respo n s es to E xtra c ts

o f Sed i m e nts F rom Sa n Diego Bay

P450-RGS response (expressed as benzo(a)pyrene equivalents) and

benthic commun ity index. Stations with degraded benthic communities

are shown w ith a "D" label. Undegraded are shown with "UD," and

transitional stations are shown with " T ." Benth ic commun ity analysis was

not performed on unlabeled stations.

Benzo(a)py r ene Equ i v a l ents ( μ g / g )
125

a strong correlation (r2= 0.86) between the two measures (Figure

25). This is expected, because samples significantly contaminated

with PAHs and/or other compounds (coplanar PCBs) have been shown

to produce induction of the CYP1A1 gene and the RGS response

(Anderson et al., 1995).

Figures 9a-d show stations with high molecular weight PAHs at the

PEL (6676 ng/g) and above in black. Examination of these data

demonstrated that RGS responses above 60 μg/g BaPEq were always

associated with total PAHs at levels above the PEL. This

comparison with the PEL suggested that sediment samples with RGS

responses above 60 μg/g BaPEq also had a high probability of

demonstrating a toxic biological effect, based on sediment

quality guidelines. Interestingly, stations identified by RGS to

contain significant amounts of inducing organic compounds

(> 60μg/g BaPEq) were also found to have degraded benthic

communities, at all stations where both analyses were performed.

Toxicity test results did not demonstrate a similar strong

association with the RGS response.

The P450 Reporter Gene System proved to be effective for rapidly

(16 hr test) and inexpensively assessing the magnitude of PAHs at

selected stations in the San Diego Bay Region. It further proved

useful by demonstrating a RGS response threshold above which

benthic community degradation was expected. This method may be

appropriate as a screening test at additional locations when

benthic community degradation and contamination from multiple

PAHs, coplanar PCBs, dioxins and furans is suspected. The

bioeffects branch of NOAA has utilized this assay in

investigations of coastal studies in southern California,

Charleston Harbor, S.C., Sabine Lake and Galveston Bay, Texas,

and Biscane Bay Florida. In concert with other chemical and

biological measures, this method provides additional convincing

evidence for the assessment of overall pollution at sites of

chemical concern.

Determination of Relationships Between Toxicity and Chemistry 

Linear regression was used to describe the relationship between

toxicity and chemical concentrations. The dependent variable

values are assumed to be normally distributed around the

predicted values on the regression line. If this assumption has

been met, then a significance test evaluating the null hypothesis

(slope of the regression equation is equal to zero), is

performed. In addition to a significant probability (p< 0.05),

the coefficient of determination (r2) is also an indication of

regression strength. The coefficient of determination value

represents the proportion of total variance of the dependent

variable which can be explained by the independent variable, with

a r

2 value of greater than 0.60 being significant. Regression is

preferable to non-parametric tests because there is greater power

to detect significant relationships with this method (Zar, 1984).

Linear regressions were used to assess the relationship between

Rhepoxynius (amphipod) mean survival and chemical concentration.
Figur e 25 . T o ta l PAHs vs P450-RGS

Respo n s e E xpr essed as Be nzo( a )py re ne

E q uiv a le n ts

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Total PAHs (ng/g)

f(x) = 7 . 274070E - 1 * (x ^ 4 . 642875E - 1 )

R^2 = 8 . 602227E - 1
127

Systat® v.5.04 was used for all analyses. The arcsine (square

root) transformation is utilized to equalize variance over the

entire range of proportions. Chemistry data were checked for

normality and transformed using Log(x+1), when necessary (Zar,

1984). Examination of residuals reveal homogeneity of variances

exists when these transformations are performed and therefore,

the statistical assumptions of a regression can be met. The

coefficient of determination (r2) was reported only when the

linear regression was significant (p<0.05).

Regressions using amphipod data and chemical concentrations for

all stations were analyzed. Testing the degree of dependence of

amphipod survival on individual chemical concentrations yielded

several regressions which are significant, however, there were no

r

2

 values greater than 0.072 (Table 13).

To investigate dependence of amphipods on chemistry within

specific areas of the Bay, all stations were grouped into one of

six specific areas (Appendix B). Groupings were performed to

combine stations with similar physical characteristics or uses.

These six groups were military use areas (Navy), commercial

basins for shipping and industrial activities, small boat harbors

and marinas, Mission Bay, rivers (San Diego and Tijuana), and

"other" stations, which generally were in open areas removed from

San Diego Bay shorelines. The area into which each station was

grouped is reported in Appendix B. These regressions were used to

test the degree of relationship between amphipod survival and

specific areas in the San Diego Bay Region.

Regressions using the navy station group were significant for

some chemical groups although no regression had an r

2 value

greater than 0.272 (Table 14). In commercial basins, low and high

molecular weight PAHs, several metals and one PCB compound were

significant, but all had low r2 values (Table 15). In the small

boat harbor group, several PAH and PCB compounds and one

pesticide were significant, however, no r2 values were greater

than 0.167 (Table 16). In river stations low molecular weight

PAHs were strongly correlated with amphipod survival (Table 17),

producing the most significant regressions of the statistical

analysis. These regression results from the river stations were

somewhat misleading, however, because PAH levels were low

relative to most stations in San Diego Bay and to ERM guidelines.

 For regressions using the "other" station designations, several

metals and PCB compounds and one PAH, were significant (Table 18)

yet, r2 values were never better than 0.265. When testing the six

station groups, there were no significant regressions for

chemistry or amphipods within the Mission Bay group. This was

expected because of the low chemical concentrations, therefore no

table is shown.

Ammonia, hydrogen sulfide and grain size are suspected nonanthropogenic contributors to toxicity, and have been discussed

previously by Ankley et al.(1990), Knesovich et al. (In Press),

and DeWitt et al. (1988). To investigate whether these natural






134

factors influenced the effects of anthropogenic chemicals in test

sediments from the San Diego Bay Region, data were adjusted to

exclude tests where unionized ammonia was greater than O.4 mg/L

in overlying water and/or hydrogen sulfide was greater than 0.06

mg/L. The 0.4 mg/L ammonia threshold value is based on the NOEC

value for the EPA test protocols for marine amphipods (USEPA,

1994) and the 0.06 mg/L hydrogen sulfide threshold value is based

on data presented by Knesovich et al. (In Press). A general trend

is seen by DeWitt et al. (1988), in which survival decreases with

increasing fines. However, because this trend was not apparent

in the San Diego Bay Region and no clear cutoff has been

conclusively demonstrated, data were not adjusted to exclude

samples with a high percentage of fines. NH3 and H2S adjusted

amphipod data were compared to the thirty two chemicals or

chemical groups, for which PEL values have been derived, and to

ERM and PEL summary quotients. Regressions were significant for

cadmium, chromium, copper, nickel, silver, zinc, DDT, dieldrin,

acenapthene, and the ERM and PEL summary quotients (Table 19). By

eliminating high ammonia concentrations (>0.4 mg/L) and high

hydrogen sulfide concentrations (0.06 mg/L), regressions do

improve slightly, however r2 values are generally low. It is

prudent though to recognize that these natural factors may

confound interpretation of toxicity results and that caution

should be exercised when elevated ammonia or hydrogen is noted.

In summary, simple linear regressions provide few clues to

understanding the relationship between amphipod survival in the

toxicity tests and measured single chemical concentrations. When

viewing scatter plots, it remains difficult to convincingly argue

that there is, or should be, a linear toxic response to

increasing chemical concentrations in natural settings. In

industrialized settings such as San Diego Bay, where multiple

pollutants are common, co-variation and possible synergistic

effects within a group of multiple pollutants further confound

the separation of effects to single pollutants. A single multiple

regression or a variable selection technique may statistically

better describe the relationship between toxicity and multiple

chemicals, but these were not performed in this analysis.

Figure 26 is typical of chemical vs. toxicity scatter plots seen

throughout the region, with considerable scatter at low chemical

concentrations and a gradual decrease in survival at elevated

chemical concentrations. Because regressions did not generally

support a linear toxic response to chemical pollutants, it is

suspected that most organisms are tolerant of pollutants until a

threshold is exceeded. This threshold effect appears well

demonstrated in the San Diego Bay Region's benthic communities

setting, as illustrated in Figure 14.

Although it was less evident for acute toxicity tests, where high

amphipod survival was observed even at elevated chemical levels

(Figure 26), a distinct response pattern still emerges. When the

EMAP approach for determination of toxicity (significantly

different from controls and less than 80% of controls) was used,

 28 of 39 (72%) sediment samples were toxic when copper

Figur e 26 . Amphipod Surviv a l vs

ERM S ummm a ry Quo tie nt o r

C h e m i c a l L eve l

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137

concentrations exceeded the ERM value whereas only about 7 of 28

samples (25%) were toxic when copper concentrations were below

the ERL value. This was also seen with total PCBs with 73% of the

samples being toxic when PCB concentrations exceeded the ERM

value and only 53% toxic below the ERL. Because it is suspected

that toxicity in urban bays is caused by exposure to complex

mixtures of chemicals comparisons to ERM summary quotients

(multiple chemical indicators) were made. The highest incidence

of toxicity (>78%) is found in samples with elevated ERM summary

quotients (>0.85), supporting the theory that the effects of

elevated levels of multiple pollutants may elucidate the toxic

response. This pattern of increased incidence of toxicity when

chemical concentrations exceed established sediment quality

guidelines or the summary quotient 90% confidence interval seems

to support the threshold response theory for amphipod bioassays

in the San Diego Bay Region.

Guideline thresholds are quantitatively estimated from large

national or statewide data sets, as described earlier, but the

applicability of calculated values may be limited in specific

water bodies. Use of unique guidelines for the San Diego Bay

Region, which account for local physical, chemical and biological

conditions, would be optimal when evaluating data. However,

without substantial additional data, chemical specific thresholds

for the San Diego Bay region cannot be accurately determined.

Currently the most useful tools for addressing the relationship

between toxicity and chemical concentration appears to be

threshold approaches, such as the ERM/ERL and TEL/PEL guidelines.

Station Specific Sediment Quality Assessments

One of the primary goals of the BPTCP is to establish state

guidelines under which contaminated or toxic stations can be

designated "toxic hot spots". These guidelines are currently

being developed based on data collected throughout the state.

Although final guidelines are contingent upon further data

analysis, the "toxic hot spot" definition currently utilized by

the BPTCP, requires that one or more of the following criteria

must be met:

1. The water or sediment exhibits toxicity associated with

toxic pollutants, based on toxicity tests acceptable to the

SWRCB or the RWQCB. To determine whether toxicity exists,

recurrent measurements (at least two separate sampling

dates) should demonstrate an effect. 

2. Significant degradation in biological populations and/or

benthic communities associated with presence of elevated

levels of toxic pollutants.

3. The site exceeds water or sediment quality objectives for

toxic pollutants which are contained in appropriate water

quality control plans, or exceeds water quality criteria

promulgated by the U.S. Environmental Protection Agency.
138

4. The tissue toxic pollutant levels of organisms collected

from the site exceed levels established by the United

States Food and Drug Administration (FDA) for protection of

human health, or the National Academy of Sciences (NAS) for

the protection of human health or wildlife. 

Because tissue residues were not analyzed in this study, criteria

are limited to the first three. Satisfying any one of these

criteria can designate a site a "toxic hot spot". Satisfying more

than one criterion and the severity demonstrated within each

criterion determines the weighting for which qualitative rankings

can be made. In this report, stations were not designated as

"toxic hot spots", because this designation is still under

evaluation and development by the BPTCP. Instead, stations were

prioritized for further evaluation for hot spot status. This

priority was classified as high, moderate, low, or no action and

may be used by State and Regional Water Board staff to direct

further investigations at these stations. Each station receiving

a high to low priority ranking meets one or more of the first

three criteria established above. Those meeting all three

criteria were designated as the highest priority for further

action.

Stations were evaluated for repeat toxicity (criterion 1) using

the reference envelope method, the most conservative measure

developed. Only those stations which demonstrated amphipod

survival less than 48% in repeated tests, without confounding

ammonia, hydrogen sulfide or grain size effects, were considered

to exhibit repeat toxicity hits. Because only one critical value

could be determined for any of the dilutions of the pore water

bioassays, pore water toxicity results were not evaluated for

repeat toxicity when prioritizing stations.

Stations with repeat toxicity and elevated chemistry and/or

degraded benthic communities, were assigned a moderate or high

priority. Stations with repeat toxicity, but lacking elevated

chemistry or degraded benthic communities, were assigned a low

priority (Tables 20 and 21- REPEAT TOXICITY HITS). 

 

Stations with only a single toxicity hit were also considered a

moderate or high priority, when associated with elevated

chemistry and/or degraded benthic communities. Stations with a

single toxicity hit, but lacking elevated chemistry or degraded

benthic communities, were assigned a low priority. (Tables 20 and

21- SINGLE TOXICITY HITS).

Nineteen stations demonstrated repeat or single toxicity hits but

were given a "no action" recommendation at this time (Tables 20

and 21). These stations had measured hydrogen sulfide or ammonia

concentrations which confounded interpretation of the bioassay

test results. Chemistry levels were low, or not analyzed, and the

benthic community was undegraded or transitional, where sampled.

These results provided little or no evidence that these stations

should be prioritized for hot spot status. A toxicity

identification evaluation (TIE) should be considered for these 


141

sites to confirm the source of toxicity as non-anthropogenic.

Stations were evaluated for benthic community condition using the

benthic index discussed earlier (Table 11). Stations determined

to be degraded, with elevated chemistry and/or toxicity, were

assigned a moderate or high priority. Stations determined to be

degraded, but which did not demonstrate elevated chemistry or

toxicity, were assigned a low priority. Transitional and

undegraded stations were not considered a priority unless

chemical or toxicity results initially prioritized the stations.

(Table 20- DEGRADED BENTHICS)

Stations were evaluated for elevated chemistry (criterion 3)

using an ERM Summary Quotient >0.85 or a PEL Summary Quotient

>1.29. In the earlier discussion of ERM and PEL summary

quotients, it was determined these values are statistically above

the 90% confidence interval of summary quotients from all

stations analyzed. These quotients were used to identify stations

where multiple pollutants were near or above established ERM and

PEL guidelines (Table 22-CHEMISTRY-Summary Quotients). As shown

in Figure 14, 100% of the stations analyzed for benthics were

found to be degraded when chemical analysis demonstrated an ERMQ

above 0.85. Although the eighteen stations in Table 22

(CHEMISTRY-Summary Quotients) did not have benthic community

analysis performed, it is likely these stations will demonstrate

degraded benthic communities, when analyzed. In consideration of

this concern, all stations with elevated chemistry, based on ERM

summary quotients above 0.85, were assigned a moderate priority

ranking. 

In situations where high summary quotient values were not found,

but where any single chemical concentration exceeded four times

(4x) its associated ERM or 5.9 times (5.9x) its associated PEL,

the station was also considered to exhibit elevated chemistry.

The 4x and 5.9x cutoffs were not statistically determined using

the 90% confidence interval as they were with the summary

quotients. Values for individual chemical quotients were not

normally distributed and transformations did not improve

distributions, so statistical determination of confidence limits

was not appropriate. Instead, a qualitative examination of the

data set indicated that only in the top 10th percentile of

chemical measurements do values exceed four times their

respective ERM or 5.9 times their respective PEL (Tables 20

and 22- CHEMISTRY-Individual Chemicals). These cutoffs were used

to help identify stations where any single chemical was extremely

elevated. Stations with elevated individual chemical quotients

and evidence of benthic community degradation were assigned a

moderate ranking. Stations which exhibited elevated chemistry,

but showed no biological effects, were assigned a low priority.

Stations which satisfied all three of the criteria were

considered a triad hit and are given the highest priority

ranking. These stations demonstrated toxicity in the bioassay

tests, benthic community degradation and elevated chemistry. Four

stations (representing three sites) fell in this category: the

Seventh Street Channel (90009-leg 23 and 93228), 12 Swartz
TABLE 22

FUTURE INVESTIGATION PRIORITY LIST FOR THE SAN DIEGO BAY REGION

Stations Without Synoptic Chemical, Toxicological and Benthic Community Analyses

STANUM STATION IDORG LEG H2S NH3 % AMPHI. SURVIVAL >4X ERM OR >5.9X PEL ERMQ PELQ BENTHICS COMMENTS PRIORITY

CHEMISTRY-Summary Quotients

90020.0 G DE LAPPE 169 12 not analyzed 0.020 49.00 0.964 1.255 not analyzed ELEVATED CHEM MODERATE

90020.0 G DE LAPPE-REP 1 1104 27 0.0006 0.086 65.00 1.051 1.411 not analyzed ELEVATED CHEM MODERATE

90020.0 G DE LAPPE-REP 2 1105 27 0.0007 0.087 59.00 1.043 1.401 not analyzed ELEVATED CHEM MODERATE

90020.0 G DE LAPPE-REP 3 1106 27 0.0009 0.049 57.00 0.947 1.293 not analyzed ELEVATED CHEM MODERATE

90030.0 BF SCHROEDER SITE F-REP 1 1144 28 0.0012 0.192 70.00 0.948 1.419 not analyzed ELEVATED CHEM MODERATE

90030.0 BF SCHROEDER SITE F-REP 2 1145 28 0.0025 0.616 76.00 PAHs 1.000 1.537 not analyzed ELEVATED CHEM MODERATE

90030.0 BF SCHROEDER SITE F-REP 3 1146 28 0.0013 0.017 68.00 1.007 1.438 not analyzed ELEVATED CHEM MODERATE

93178.0 NAVAL SHIPYARDS O2 (x1)-REP 1 1119 27 0.0022 0.185 61.00 0.934 1.294 not analyzed ELEVATED CHEM MODERATE

93178.0 NAVAL SHIPYARDS O2 (x1)-REP 2 1120 27 nd 0.145 66.00 PCBs 1.170 1.618 not analyzed ELEVATED CHEM MODERATE

93178.0 NAVAL SHIPYARDS O2 (x1)-REP 3 1121 27 0.0007 0.168 67.00 PCBs 1.269 1.651 not analyzed ELEVATED CHEM MODERATE

90022.0 P SWARTZ-REP 1 1107 27 0.0003 0.061 58.00 PAHs 1.042 1.549 not analyzed ELEVATED CHEM MODERATE

90022.0 P SWARTZ-REP 2 1108 27 0.0008 0.073 61.00 PAHs 1.109 1.770 not analyzed ELEVATED CHEM MODERATE

90022.0 P SWARTZ-REP 3 1109 27 0.0008 0.038 54.00 PAHs 1.107 1.724 not analyzed ELEVATED CHEM MODERATE

93179.0 NAVAL SHIPYARDS O3 (x1)-REP 2 1123 27 nd 0.049 51.00 1.071 1.462 not analyzed ELEVATED CHEM MODERATE

93179.0 NAVAL SHIPYARDS O3 (x1)-REP 3 1124 27 nd 0.115 78.00 Antimony 1.330 1.658 not analyzed ELEVATED CHEM MODERATE

93184.0 NAVAL SHIPYARDS O11 (x1) 802 19 not analyzed 0.070 53.00 DDT 1.226 1.774 not analyzed ELEVATED CHEM MODERATE

90017.0 C DELAPPE 166 6 not analyzed 0.840 64.00 PAHs 1.183 1.943 not analyzed ELEVATED CHEM MODERATE

93181.0 NAVAL SHIPYARDS O6 (x1)-REP 3 1112 27 0.003 0.037 65.00 0.904 1.362 not analyzed ELEVATED CHEM MODERATE

CHEMISTRY-Individual Chemicals

93162.0 SUB BASE C3 (x1) 775 18 not analyzed 0.585 53.00 PAHs 0.347 0.596 not analyzed ELEVATED CHEM LOW

90037.0 STORMDRAIN EM(GRAPE ST.)-REP 3 1161 29 0.0012 0.290 85.00 Chlordane 0.656 0.934 not analyzed ELEVATED CHEM LOW

93141.0 COMMERCIAL BASIN F3 (x1)-REP 3 1170 29 0.0004 0.057 70.00 Mercury 0.650 0.905 not analyzed ELEVATED CHEM LOW

93116.0 SAN DIEGO RIVER B1 (x4) 711 15 0.0893 0.137 88.00 Chlordane 0.659 0.913 not analyzed ELEVATED CHEM, SITE DEGRADED IN LEG 22 MODERATE

93120.0 TIJUANA R. ESTUARY HH2 (x1) 715 15 0.0002 0.087 85.00 DDE 0.321 0.358 not analyzed ELEVATED CHEM LOW

93121.0 TIJUANA R. ESTUARY HH2 (x5) 716 15 0.0016 0.010 85.00 DDE 0.287 0.314 not analyzed ELEVATED CHEM LOW

93174.0 TIJUANA R. EST. HH3 (x2)-REP 3 1152 28 0.0044 0.084 80.00 DDE 0.325 0.395 not analyzed ELEVATED CHEM LOW

93177.0 NAVAL SHIPYARDS O1 (x1) 795 19 not analyzed 0.023 50.00 PAHs 0.694 1.204 not analyzed ELEVATED CHEM LOW
143

Downtown Anchorage (90002) and Naval Base/Shipyards O4 (93210).

Three stations were given a high priority ranking although not

all conditions of the triad were met (Seventh Street Channel

(90009-leg 7) and Naval Shipyards O3 (93179- legs 19 & 27)).

These stations demonstrated repeated toxicity and elevated

chemistry but no benthic analyses were performed. However,

benthic data for stations analyzed in the same proximity, or

later sampling of the station, led to the concern that these

sites would have been found degraded, if analyzed. In addition,

chemical summary quotients at these three stations were at levels

which suggest probable benthic community degradation, as

discussed earlier. These concerns warranted upgrading these three

stations from a moderate priority to a high priority. Forty three

stations were given moderate priorities and 57 were given low

priorities, based on the methods of prioritization previously

discussed. Prioritized stations are mapped in Figure 27(a-d).

Stations were prioritized to assist SWRCB and RWQCB staff in

meeting sediment quality management objectives for San Diego Bay.

These recommendations were based on scientific evaluation of data

collected between 1992 and 1994. They are intended to focus

future efforts toward scientifically and economically responsible

characterization of locations which have a high probability of

causing adverse effects to aquatic life. This report should be

evaluated in conjunction with all available information and

additional research when management and policy decisions are made

by SWRCB and RWQCB staff.

Possible Sources of Pollutants at Prioritized Stations

A brief description is given, where additional information was

available, of factors which may have contributed to elevated

chemical levels, toxicity, or benthic community degradation at

the prioritized stations. Descriptions are given in order of

geographic distribution, proceeding from north (Mission Bay) to

south (Tijuana River Estuary).

In Mission Bay only one location was given the moderate priority

ranking (station 93116). This station was located in the San

Diego River flood control channel and demonstrated high total

chlordane concentrations (36.1 ppb). Chlordane is not expected to

undergo significant hydrolysis, oxidation, or direct photolysis

in water, thus it may persist in soils for extended periods of

time (Howard, 1991). Cohen et al. (1990) conducted a study on

chlordane in soil samples near golf courses and found unusually

high concentrations of chlordane (4.75-4310 ppb). Station 93116

is located directly down river from a golf course, therefore,

runoff from this facility could be a chlordane source. Station

93107, in the mouth of Rose Inlet (northern Mission Bay),

received a moderate priority listing, based on high chlordane

concentrations. Its location is also near a golf course.

One site in North San Diego Bay (Point Loma area) received a

moderate priority recommendation; stations 90028 (Submarine

Base). This station had degraded benthic communities, high
93148

90028

93217

93162

93138 90023

93154

90055

90102 90050

90104

93141

93216

93166

93188

90025

90024

93232

Figure 27a

Future Investigation Priority List

North San Diego Bay

PRIORITIES

High

Moderate

Low

No Action
90003

90002

Downtown Anchorage

93179 90018

Naval Shipyards O3

90020

90043

90030

93210 93211

Naval Shipyards O4

90009

Seventh St. Channel

93228

93206

93205

93208

90004

93207

93122

90017

90051

93177

90021

90039 93178

93125

93213

90006 93223

90008

93224

93215

93181

93212

93184

90007

90022

93226

93214

93225

Figure 27b

Future Investigation Priority List

Mid San Diego Bay

PRIORITIES

High

Moderate

Low

No Action
93127

93219

93159

93128

90012

93196

93197

90057

90036

93158

93204

93132

93220

90010

93229

93230

Figure 27c

Future Investigation Priority List

South San Diego Bay

PRIORITIES

High

Moderate

Low

No Action
93106

93116

93107

93117

Figure 27d

Future Investigation Priority List

Mission Bay and San Diego River Estuary

PRIORITIES

High

Moderate

Low

No Action

93118

93119

93175

93174

93120 93121

PRIORITIES

High

Moderate

Low

No Action

Tijuana River Estuary
148

concentrations of low and high molecular weight PAHs, and

moderate levels of metals. Historically the Naval Complex at

Point Loma has received plating waste, sewage, and sludge

containing high concentrations of metals and chlorinated

hydrocarbons (Johnston et al., 1989). Although it is difficult to

identify the source of high concentrations of PAHs at these

stations, Lung (1983) suggests ground water gradients promote

groundwater flow towards San Diego Bay, thus potentially allowing

PAHs in the nearby soil to migrate to the Bay. A number sites

investigated by the Navy (Eakes and Smith, 1986), which were

previously used for waste oil and drum disposal, are located

onshore adjacent to and immediately north of stations 93216,

93217 and 90028. Migration of pollutants from these onshore sites

is likely. Minor spills during fueling operations at the

submarine base are also possible.

Station 90002 (Downtown Anchorage), located in the northern end

of mid San Diego Bay, was one of the stations which received a

high priority recommendation. High concentrations of metals and

chlordane were present, as well as a degraded benthic community.

This station also had a low survival for Rhepoxynius in solid

phase toxicity tests. Perhaps the most obvious explanation for

these data would be the presence of a large storm drain and

numerous smaller storm drains, which empty into the Bay near this

station. These storm drains drain parking lots, light industrial

and commercial areas (Conway and Gilb, 1990). Another possible

source for observed toxicity and chemistry is runoff from nearby

San Diego International Airport. Results from the State Mussel

Watch Program 1987-1993 indicate elevated levels of both metals

and pesticides in mussel tissue and sediments in this area.

Elevated levels of metals could have originated from anti-fouling

paints on private boats anchored near the station (90002). The

area around this station becomes a modified eddy during ebb tide

and may serve to recirculate pollutants, creating a pollutant

sink and preventing chemicals from being flushed out of the area

(Peeling, 1974).

Located just south of station 90002, stations 93205 and 93206

(Downtown Piers) were given moderate priority ratings based on

high chlordane and PAHs concentrations, and degraded benthic

communities. Located between the B street pier and the Broadway

pier, elevated levels of pollutants can most likely be attributed

to sources similar to those described above. Commercial shipping

is likely an additional contributor to the observed PAH signal in

this area.

Two stations, 90017 and 90039 (located immediately north of the

10th avenue marine terminal), were assigned moderate priority

rankings based on high concentrations of chlordane, metals, and

PAHs at each of these stations. Campbell Industries operate five

ship repair piers and four dry-docking facilities in this area.

Sandblasting, painting, and other ship repair activities are

probably the cause of the elevated levels of copper, zinc and

mercury. High concentrations of metals have historically been

detected at this site (Barry, 1972). The 10th avenue Marine
149

Terminal berths 1 and 2 are also located in this area (station

90039). Ships are loaded and unloaded at this site and supplied

with fuel from four steel storage tanks located near the berths.

Increased levels of PAHs and metals detected in this area may be

related to the cargo transfer facility.

In addition to the ship repair facilities and cargo transfer

areas, there is a large storm drain system which is directly

south of the 10th and Imperial Trolley station. The system drains

approximately eleven square kilometers of residential (including

Balboa Park) and industrial areas before emptying into the Bay.

The elevated levels of chlordane and PAHs at both of the sites

could have additional sources from within this drainage system.

Immediately south of the Coronado Bridge was station 93179 (Naval

Shipyards-O3) which was designated as a high priority site for

future investigations. To the north and south of this site are

numerous stations assigned a moderate prioritization. The

predominant activity in this area is ship building and repair

(NASSCO, Continental Maritime, Southwest Marine), thus indicating

the probable source of high levels of metals, PCBs and PAHs found

at stations sampled in this area. A stormdrain, which drains an

industrial area and empties into the Bay immediately adjacent to

the bridge, is the likely chlordane source to the area. Runoff

from the bridge itself could also be viewed as a potential source

of PAHs and metals in the Bay. The California State Mussel Watch

Program (1995) has sampled extensively in this area of San Diego

Bay and found chemistry values for mussels and sediment to be

comparable to the current study. This area has also been

extensively sampled in other studies resulting in similar

conclusions (de Lappe, 1989; Martin, 1985; Anderson, 1989).

Toxicity, chemical pollution and benthic community degradation

are extensive in this area and warrant further site

characterizations.

Stations 93212, 93213, and 90006 (Naval Shipyards-O7) were

located near the 28th Street pier and were each given a moderate

priority ranking. Chollas Creek empties into the Bay near this

site, carrying with it runoff from a large urban area. This creek

is believed to carry high concentrations of PAHs into the Bay

(McCain et al., 1992) and is the likely source of high chlordane

levels at the site.

Numerous low, moderate and high priority sites were located in

the Naval Station between the 28th Street pier and 7th Street

channel. This area demonstrated toxicity, high metal and

chemistry concentrations and degraded benthic communities. The

area is predominantly used for ship repair, outfitting, and

conversion. Sand blasting, painting, and the changing of zinc

electrolysis plates are some of the specific activities conducted

in this area and are likely the main sources of metals found in

the sediments.

Station 93227 was located in the 7th Street Channel at the

southern end of the San Diego Naval Station. This site was given
150

the high priority ranking based on high metal, chlordane and PAH

concentrations, as well as toxicity and degraded benthic

communities. Repeated sampling of this site resulted in similar

findings. Paleta Creek runs directly into 7th Street channel

with numerous drains located in the immediate area emptying into

the creek and bay. Also, a large stormdrain is present which

drains a residential area east of Interstate 5 and the Naval

station adjacent to the channel.

The Navy has used 7th Street channel and the surrounding area for

a variety of activities. Excess materials (solid waste, ships

stores, and waste hydraulic fluids) from decommissioned ships

were disposed of in the ship repair basins. Overflow from salvage

yards, lube and hydraulic oil wastes, and paint sludge from 

nearby Naval repair facilities were often taken to the area's wet

docks for disposal. In the late 1970's trucks and heavy equipment

returning form Vietnam were routinely decontaminated by spraying

with diesel fuel and dunking (by crane) into Paleta Creek. It is

estimated that approximately 75,000 to 360,000 gallons of

petroleum based material were disposed of at this site during its

period of operation (1945-1973).

The 7th Street channel is located near a Navy salvage yard which

has stormdrains emptying directly into the channel. In 1976, soil

samples retrieved from the area contained PCB concentrations high

enough to result in the upper eight inches of soil being removed

as contaminated waste and the entire area paved. Although the

Navy has attempted to deal with this historic pollution in the

area, further investigations were requested by a Naval initial

assessment team in 1986 (Eakes and Smith, 1986). Furthermore, the

California State Mussel Watch program has stations located in the

area and concluded 7th Street channel had some of the highest

chemical concentrations in San Diego Bay (State Mussel Watch

Program, 1995).

The Marine terminal site (stations 90010, 93230 and 93229)

demonstrated elevated copper and PAH levels and a degraded

benthic community. Moderate and low priorities were assigned to

these stations even though a portion of this area is currently

undergoing cleanup activities. Due to the large amount ore

spillage at the PACO copper loading facility, this area should

continue to be monitored after cleanup activities are completed.

The southern portion of San Diego Bay, from 7th Street channel to

the Otay River, did not receive any moderate or high priority

rankings. Although this result could give the impression south

San Diego Bay is in not polluted, it is important to note some

stations still demonstrated high metals concentrations. The

Sweetwater channel area (station 93220), and other sites in the

South San Diego Bay had high concentrations of copper, most

likely reflecting the input from the copper ore loading facility

(Martin, 1985). Three stations in the Chula Vista area and one in

Coronado Cays received low priority rankings due to elevated

levels of metals and degraded benthic communities. Each of these

stations were located within marinas where numerous private boats
151

are berthed. Increased levels of metals detected in this area are

probably from anti-fouling paint scrapings or zinc electrolysis

blocks used on virtually all boats. Few studies have concentrated

sampling in the South San Diego Bay, presumably due to reduced

shipping activity and population.

Stations from the Tijuana River Estuary demonstrated elevated

concentrations of DDT and DDE, as well as toxicity to amphipods.

This resulted in a number of stations receiving moderate and low

prioritizations. The presumed sources of this pesticide were

wastewater discharges from Mexico, into the Tijuana River

(California State Coastal Conservancy, 1989).

Comparison of Pollution with Other Water Bodies

Numerous studies comparing San Diego Bay with other bays and

harbors have been conducted (NOAA, 1991; Grovenhoug et al., 1987;

Goldberg et al., 1978). In one such study, Robertson (1989)

analyzed sediments for a number of organic pollutants at

approximately 200 sites around the coasts of the United States. 

Results ranked San Diego Bay seventh highest in the country for

total concentrations of PCBs. Interestingly, San Diego Bay did

not rank high in comparison to the rest of the country for any

other organic pollutant, although results from the current study

clearly showed elevated concentrations (relative to ERMs and

PELs) of total PAHs, chlordane, and certain trace metals

throughout the Bay.

In a similar study, Johnston (1990) evaluated 367 waste disposal

sites at 58 Navy and Marine Corps bases located throughout the

country. Each of the bases, or areas of activity, were located in

the coastal zone and were reviewed to characterize the

pollutants, disposal methods, and potential impact to the

surrounding aquatic environment. Four sites were chosen in San

Diego Bay: Naval Station San Diego (located immediately south of

the seventh street channel), Naval Amphibious Base (near

Glorietta Bay), Naval Training Center, and Naval Complex Point

Loma. Although these sites were not ranked or compared with sites

in other parts of the country, the types of contamination listed

were somewhat similar for each of the sites described. Paint,

oil, and solvent contamination was reported at all of the sites

in addition to some site specific forms of contamination( i.e.

sandblasting grit disposal area at the Naval Amphibious Base and

drum disposal area at the Naval Complex Point Loma).

San Diego Bay has also been compared to other bodies of water on

a regional scale. In a SCCWRP project funded by the State Board,

Anderson and Gossett (1987) analyzed PAHs in sediments collected

at stations between Santa Monica Bay and San Diego Bay and found

the Seventh Street (Paleta Creek) and Chollas Creek stations to

contain the highest levels of these hydrocarbons. In a follow-up

State Board/SCCWRP study Anderson et al. (1988) compared ten

coastal sites in southern California for concentrations of trace

metals, PAHs, chlorinated hydrocarbons and toxicity. Samples from

San Diego Bay were shown to have the highest concentrations of
152

metals, PAHs, and hydrocarbons of all stations sampled, and were

the most toxic in two out of three toxicity tests used. 

Anderson et al. (1988) identified the Seventh Street Channel

station as the most polluted area in the San Diego Bay Region.

This conclusion is corroborated by the current study which also

found sampling stations in the Seventh Street Channel to be the

most polluted and most toxic stations in the region.

Flegal and Sanudo-Wilhelmy (1993) showed total dissolved trace

metal (Ag, Cd, Co, Cu, Ni, and Pb) concentrations in San Diego

Bay are comparable to levels of trace element pollution in south

San Francisco Bay. Specifically, copper was found in elevated

concentrations in both bays. The current study found copper to be

the predominant trace element pollutant in San Diego Bay. Flegal

and Sanudo-Wilhelmy concluded that unlike south San Francisco

Bay, elevated trace metal concentrations in San Diego Bay could

not be directly linked to point-source inputs, because all

wastewater discharges to San Diego Bay were terminated in 1964.

Copper based anti-fouling paints and urban runoff are currently

the most likely sources of copper. Elevated concentrations of

copper in San Diego Bay have also been reported in other studies

(Zirino et al., 1978).

It is also important to analyze available site specific data

within San Diego Bay from previous studies. In the current study,

commercial and naval shipyards located near the Coronado Bridge

consistently demonstrated high concentrations of pollutants, a

high incidence of toxicity, and benthic community degradation. 

Shipbuilding activity, in addition to storm drains and creeks,

appear to be the primary sources of organic and trace metal

pollutants in these areas (Conway and Gilb, 1990). Secondary

sources of contamination may include runoff from the Coronado

Bridge (San Diego Interagency Water Quality Panel, 1989) and

polluted fill in the area (Peter Michael, San Diego Regional

Water Quality Control Board, personal communication). This is

supported by the conclusions of McCain (1992) who found several

major sources of pollutants in the central portion of San Diego

Bay.

Specific organic pollutants such as PCBs have been historically

identified in certain parts of the bay. In one of the earliest

studies of PCBs in San Diego Bay, Young and Heesen (1977)

identified PCBs in mussel tissues. The highest measured

concentrations occurred in Commercial Basin (Shelter Island).

Subsequent studies have also shown elevated levels of PCBs in the

Shelter Island area, as well as near Harbor Island and numerous

other spots throughout the Bay (Stephenson et al., 1980; Martin,

1985). Similar results were obtained from sediment samples in the

current study in which high concentrations of PCBs were reported

from areas near the Coronado Bridge, west Commercial Basin and

East Basin near Harbor Island. The Regional Water Quality Control

Board has identified a 60 inch storm drain as the main source of

PCBs into the East Basin site. Cleanup and Abatement Orders,

regarding PCBs, have been issued to boatyards in and around

Shelter Island and Harbor Island (San Diego Interagency Water

Quality Panel, 1994).
153

Tributyltin (TBT), an organic based biocide, was widely used as

an antifoulant on ships and small craft until 1988 (Richard and

Lillebo, 1988). Although TBT is highly efficient at killing

fouling organisms it is also acutely toxic to non-target

organisms, making it a continuing concern in the San Diego Bay

Region. Toxic effects have been observed in concentrations as low

as 1 ng/L (Henderson, 1988). Long term monitoring of U.S. harbors

indicates that among naval bases, San Diego has relatively low

concentrations of TBT (Kram et al., 1989; Seligman et al., 1990).

 These studies focused on comparisons between U.S. Naval

facilities (i.e. Pearl harbor, Norfolk harbor) where use of TBT

anti-fouling paints is not restricted on vessels over 25 meters

in length (Organotin Antifouling Paint Control Act, 1988). 

Because San Diego Bay is a multi-use port, where smaller nonnaval vessels must conform to the 1988 legislation, TBT values

are expectedly lower than harbors which solely contain large

naval vessels. In the current study, TBT values were highest in

naval and commercial basin areas, similar to the findings of

Seligman et al. (1990). Although both studies found elevated

levels of TBT in commercial and naval sites, data from the

current study indicates an overall decline in TBT sediment

concentrations at these locations. This is most likely a

reflection of restrictive legislation on TBT use in antifouling

paints. Given the historical use of antifouling paints in San

Diego Bay, continued monitoring is recommended, although results

from the current study were encouraging.

Limitations

The two step sampling design of this study relied on an initial

"screening phase" to give a broad assessment of toxicity in the

San Diego Bay Region. Subsequent toxicity test, chemical analysis

and benthic community analysis were performed only on selected

stations (≈ 40% of the screened stations) which demonstrated

toxicity during the screening phase, or were considered

candidates as reference stations. The remaining stations, from

the screening phase, did not receive additional testing or

analysis. Therefore, statistical analyses, comparisons to

chemical specific screening values, identification of undegraded

and degraded habitats, and prioritized rankings could not be

performed on all stations sampled. Currently these stations fall

under a no action recommendation, but it should be understood

that for these stations a weight-of-evidence evaluation was not

performed, due to the absence of chemical and/or benthic

community data. 

In determination of toxicity for the reference envelope approach,

values must be chosen for alpha and the percentile (p) to

calculate the edge of the reference envelope (L) using the

following equation:

 L = Xr - [ ga,p,n * Sr ]
154

The values of alpha and p are chosen to express the degree of

certainty desired when classifying a sample as toxic. In this

study values of alpha=.05 and p=1 were used to distinguish the

most toxic samples which have a 95% certainty of being in the

most toxic 1% (Figure 4). This calculation resulted in a

determination of toxicity for the Rhepoxynius test when samples

had a mean survival of less than 48%. If the value of p was

chosen to equal 10% (i.e., a 95% certainty of being in the most

toxic 10%) the determination of toxicity (edge of the reference

envelope) would have been at 63% survival. Obviously, a choice of

p=10% would broaden the range of samples which would be

classified as "toxic". It must be recognized the 48% level used

in this study was chosen as a conservative guideline to identify

only the most toxic stations for setting priorities for future

work. The 48% survival cutoff used in this study should be

recognized as a statistical determination which may or may not

reflect the certainty desired by SWRCB and RWQCB staff for

sediment quality management purposes. 

There is a necessary caution to the ecological applicability of

data collected from studies such as reported here. Although

measures of toxicity and chemical concentration are used

extensively in this study, they can only be used as indicators of

possible adverse effects to indigenous communities. Benthic

community assessment is the only tool used in this study which

can demonstrate actual effects to resident biological

communities. In combination, these three measures provide a

strong weight of evidence for the conditions found at a

particular sampling location. However, it is recommended these

lines of evidence be supported with an ecological risk assessment

during subsequent investigations of stations of concern.

CONCLUSIONS

The major conclusions of this study were:

1. Two sets of sediment quality guidelines were useful in

demonstrating chemical pollution: The ERL/ERM thresholds

developed by NOAA (Long and Morgan, 1990; Long et al., 1995) and

the TEL/PEL thresholds used in Florida (MacDonald, 1993;

MacDonald, 1994). Copper, mercury, zinc, total chlordane, total

PCBs, and PAHs were most often found to exceed critical ERM or

PEL values. These were considered the major chemicals or chemical

groups of concern in the San Diego Bay Region. ERM and PEL

summary quotients were developed as chemical indices for

evaluating pollution of sediments with multiple chemicals. An ERM

summary quotient >0.85 or a PEL summary quotient >1.29 was

indicative of sites where multiple chemicals were significantly

elevated. Stations with any chemical concentration >4 times its

respective ERM or >5.9 times its respective PEL were considered

to exhibit elevated chemistry. 
155

2. The identification of degraded and undegraded habitat was

determined by macrobenthic community structure, using a

cumulative, weight-of-evidence approach. Analyses of the 75

stations sampled for benthic community structure identified 23

undegraded stations, 43 degraded and 9 transitional stations. All

sampled stations with an ERM quotient>0.85 were found to have

degraded communities. All sampled stations with P450 responses

above 60 μg/g BaPEq. were found to have degraded benthic

communities.

3. Exceedances of toxicity thresholds were determined using two

approaches: the reference envelope approach and laboratory

control comparison approach. The reference envelope approach was

the more conservative of the two, indicating toxicity for the

Rhepoxynius (amphipod) sediment test was significant when

survival was less than 48%, in samples tested. No reference

envelope was determined for the Strongylocentrotus (urchin)

fertilization or development tests. High variability in pore

water data from reference stations produced a lower confidence

boundary for the reference envelope below 0% survival. This

indicates no significant distinction in toxicity could be made

between reference stations and other stations for these pore

water tests.

4. Using the EMAP definition of toxicity, 56% of the total area

sampled in the San Diego Bay Region was toxic to Rhepoxynius. For

Strongylocentrotus development test, percent of total area toxic

was 29%, 54%, and 72% respectively for 25%, 50%, and undiluted

pore water concentrations. Samples representing 36%, 27%, or 14%

of the study area were toxic to both Rhepoxynius in solid phase

sediment and to Strongylocentrotus larvae in 100%, 50%, or 25%

pore water, respectively. Spatial extent of toxicity was not

determined using the reference envelope definition of toxicity.

5. Linear regression analyses failed to reveal strong

correlations between amphipod survival and chemical

concentration. It is suspected instead of a linear response to

chemical pollutants, most organisms are tolerant of pollutants

until a threshold is exceeded. Comparisons to established

sediment quality guideline thresholds demonstrate an increased

incidence of toxicity for San Diego Bay Region samples with

chemical concentrations exceeding the ERM or PEL values. It is

further suspected toxicity in urban bays is caused by exposure to

complex mixtures of chemicals. Comparisons to ERM summary

quotients (multiple chemical indicators) demonstrate that the

highest incidence of toxicity (>78%) is found in samples with

elevated ERM summary quotients (>0.85).

Statistical analyses of the P450 Reporter Gene System responses

versus the PAHs in sediment extracts demonstrated that this

biological response indicator was significantly correlated

(r

2

 = 0.86) with sediment PAH (total and high molecular weight)

concentrations.
156

6. Stations requiring further investigation were prioritized

based on combined evidence from toxicity, chemical and benthic

community data. Prioritizations were developed to help direct

future investigations by State and Regional Water Board staff at

these stations. Each station receiving a high, moderate, or low

priority ranking meets one or more of the criteria under

evaluation for determining hot spot status in the Bay Protection

and Toxic Cleanup Program. Those meeting all criteria were given

the highest priority for further action.

Seven stations (representing four sites) were given a high

priority ranking, 43 stations were given a moderate priority

ranking, and 57 stations were given a low priority ranking. The

seven stations receiving the high priority ranking were in the

Seventh Street channel area, two naval shipyard areas near the

Coronado Bridge, and the Downtown Anchorage area west of the

airport. The majority of stations given moderate rankings were

associated with commercial areas and naval shipyard areas in the

vicinity of the Coronado Bridge. Low priority stations were

interspersed throughout the San Diego Bay Region.

7. A review of historical data supports the conclusions of the

current research. Possible sources for pollution at prioritized

stations are given. Recommendations are made for complementary

investigations which could provide additional evidence for

further characterizing stations of concern. 

RECOMMENDATIONS

Given the supporting evidence of previous studies, the patterns

of chemical pollution and bioeffects observed during this

assessment of the San Diego Bay Region are convincing. There are

additional avenues of investigation though which would complement

the results of this study. The results also should be confirmed

with further studies before any adverse ecological impacts can be

conclusively demonstrated.

Due to the large number of elevated chemicals at the majority of

the prioritized sampling stations, toxic biological responses can

only be associated with overall chemical pollution, rather than a

particular chemical. However, stations on the priority list,

where the number of ERM or PEL exceedances is low and the

exceedance for a particular chemical is high, are excellent

candidates for toxicity identification evaluations (TIE). The

ability to distinguish between causative factors of toxicity is

enhanced when multiple chemicals are not involved. Stations Naval

Base O7(x1), 12 Swartz (Downtown Anchorage), and the San Diego

River, where high chlordane concentrations are found, are well

suited for TIE manipulations which would attempt to test this

organic pesticide as the causative toxicity agent. The Naval

Base/Shipyard O10(x6) station, which only demonstrates ERM or PEL

exceedances for trace metals, is well suited for manipulations

which could remove metal toxicity (e.g., EDTA additions). 
157

Several chemicals of concern identified in the San Diego Bay

region have been shown to bioconcentrate and biomagnify in the

tissues of marine species. A tissue contamination study for

lipophilic compounds such as PCBs, chlordane, and possibly

methylmercury is recommended to address human health concerns due

to consumption of impacted resident species. This line of

investigation seems necessary considering tissue contamination is

the only BPTCP criterion not investigated during this study.

Although specific stations are identified as having a high

probability of causing adverse effects, no attempt can be made to

define the boundaries of the impacted area. Sampling specifically

designed to quantify areal extent of an impacted area must be

addressed during intensive site characterizations.
158

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J.K.Summers, H.T. Wilson, R.M. Valente, D.G. Heimbuch, J.

Gerritsen, S.C. Schimmel, and R.W. Latimer. 1993. EMAPEstuaries Virginian Province 1990 Demonstration Project Report.

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Environmental Research Laboratory, Narragansett, RI.

Whitfield, M. 1974. The hydrolysis of ammonium ions in sea

water - a theoretical approach. J. Mar. Biol. Ass. U.K. 54:565-

580.

Whitfield, M. 1978. The hydrolysis of ammonium ions in sea

water - experimental confirmation of predicted constants at one

atmosphere pressure. J. Mar. Biol. Ass. U.K. 58:781-787.

Williams, W.T., H.T. Clifford and G.N. Lance. 1971. Group-sized

dependence: A rationale for choice between numerical

classifications. Comput. J. 14:157-162.

Word, J.Q. 1978. The infaunal index. Southern California

Coastal Water Research Project, annual report, p. 19-39.

Young, D.R. and T.C. Heesen. 1977. Southern California Coastal

Water Research Project. Annual Rep. So. Calif. Coast Water-ResProj. 77-1:23-30.

Zar, J. H. 1984. Biostatistical Analysis: Second Edition.

Prentice Hall. Englewood Cliffs, New Jersey.

Zedler, J.B., C.S. Nordby, and B.E. Kus. 1992. The Ecology of

Tijuana Estuary, California: a national estuarine research

reserve. NOAA Office of Coastal Resource Management, Sanctuaries

and Reserves Division, Washington, D.C.

Zirino, A., S.H. Lieberman, and C. Clavell. 1978. Measurement

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APPENDIX A

DATA BASE DESCRIPTION

for the

SWRCB/NOAA COOPERATIVE PROJECT

SAN DIEGO BAY

A Report prepared for the

California State Water Resources Control Board

Bays and Estuaries Unit

 Bay Protection and Toxic Cleanup Program

by the

California Department of Fish and Game

Marine Pollution Studies Laboratories

7711 Sandholdt Road

Moss Landing, CA 95039

September, 1996
I. OVERVIEW OF THE BAY PROTECTION PROGRAM

The California State Water Resources Control Board (SWRCB) has

contracted the California Department of Fish and Game (CDFG) to

coordinate the scientific aspects of the Bay Protection and Toxic

Cleanup Program (BPTCP), a SWRCB program mandated by the

California Legislature. The BPTCP is a comprehensive, long-term

effort to regulate toxic pollutants in California's enclosed bays

and estuaries. The program consists of both short-term and longterm activities. The short-term activities include the

identification and priority ranking of toxic hot spots,

development and implementation of regional monitoring programs

designed to identify toxic hot spots, development of narrative

sediment quality objectives, development and implementation of

cleanup plans, revision of waste discharge requirements as needed

to alleviate impacts of toxic pollutants, and development of a

comprehensive database containing information pertinent to

describing and managing toxic hot spots. The long-term

activities include development of numeric sediment quality

objectives; development and implementation of strategies to

prevent the formation of new toxic hot spots and to reduce the

severity of effects from existing toxic hot spots; revision of

water quality control plans, cleanup plans, and monitoring

programs; and maintenance of the comprehensive database.

Actual field and laboratory work is performed under contract by

the California Department of Fish and Game (CDFG). The CDFG

subcontracts the toxicity testing to Dr. Ron Tjeerdema at the

University of California at Santa Cruz (UCSC) and the laboratory

testing is performed at the CDFG toxicity testing laboratory at

Granite Canyon, south of Carmel. The CDFG contracts the majority

of the sample collection activities to Dr. John Oliver of San

Jose State University at the Moss Landing Marine Laboratories

(MLML) in Moss Landing. Dr. Oliver also is subcontracted to

perform the TOC and grain size analyses, as well as to perform

the benthic community analyses. CDFG personnel perform the trace

metals analyses at the trace metals facility at Moss Landing

Marine Laboratories in Moss Landing. The synthetic organic

pesticides, PAHs and PCBs are contracted by CDFG to Dr. Ron

Tjeerdema at the UCSC trace organics facility at Long Marine

Laboratory in Santa Cruz. MLML currently maintains the Bay

Protection and Toxic Cleanup Database for the SWRCB. Described

below is a description of that database system.

II. DESCRIPTION OF COMPUTER FILES

The sample collection/field information, chemical, and toxicity

data are stored on hard copy, computer disks and on a 486DX PC at

Moss Landing Marine Laboratories. Access is limited to Russell

Fairey. Contact Russell Fairey at (408) 633-6035 for copies of

data. The data are stored in a dBase 4 program and can be

exported to a variety of formats. There are three backups of

this database stored in two different laboratories. The data are

entered into 1 of 2 files. REG9CHEM.DBF file contains all the

collection and chemical data. REG9TOX.DBF file contains all the

collection and toxicity test data. A hardcopy printout of the

dBase database structure is attached, showing precise

characteristics of each field. 
The REG9CHEM.DBF file is the chemistry data file which contains

the following fields (the number at the start of each field is

the field number):

1. STANUM. This numeric field is 7 characters wide with 1

decimal place and contains the CDFG station numbers that are used

statewide. The format is YXXXX.Z where Y is the Regional Water

Quality Control Board Region number and XXXX is the number that

corresponds to a given location or site and Z is the number of

the station within that site. An example is West Basin in San

Diego Harbor where the STANUM is 90050.0. The 9 indicates Region

9. The 0050 indicates that it is Site 50 and the .0 is the

replicate (if any) at the station within Site 50.

2. STATION. This character field is 30 characters wide and

contains the exact name of the station.

3. IDORG. This numeric field is 8 characters wide and

contains the unique i.d. organizational number for the sample. 

For each station collected on a unique date, an idorg sample

number is assigned. This should be the field that links the

collection, toxicity, chemical, and other data bases.

4. DATE. This date field is 8 characters long and is the

date that each sample was collected in the field. It is listed

as MM/DD/YY.

5. LEG. This numeric field is 6 characters wide and is the

leg number of the project in which the sample was collected.

6. LATITUDE. This character field is 12 characters wide and

contains the latitude of the center of the station sampled. The

format is a character field as follows: XX,YY,ZZ, where XX is in

degrees, YY is in minutes, and ZZ is in seconds or hundreds.

7. LONGITUDE. This character field is 14 characters

wide and contains the

longitude of the center of the station sampled. The

format is a character field as follows: XX,YY,ZZ,

where XXX is in degrees, YY is in minutes, and ZZ is

in seconds or hundreds.

8. GISLAT. This numeric field is 12 characters wide with 8

decimal places and contains the latitude of the station sampled

in Geographical Information System format. The format is a

numeric field as follows: XX.YYYYYYYY, where XX is in degrees

and YYYYYYYY is a decimal fraction of the preceding degree.

9. GISLONG. This character field is 14 characters wide with

8 decimal places and contains the longitude of the station

sampled. The format is a character field as follows:

XXXX.YYYYYYYY where XXXX is in degrees and YYYYYYYY is a decimal

fraction of the preceding degree.

10. HUND_SECS. This character is 1 character wide and

contains the designation "h" if the latitude and longitude are
given in degrees, minutes and hundredths of a minute. The

designation "s" is given when latitude and longitude are given in

degrees, minutes and seconds.

11. DEPTH. This character field is 4 characters wide and

contains the depth at which the sediment sample was collected, in

meters to the nearest one half meter.

12. METADATA. This is an index directing the user to tables

or files of ancillary data pertinent to associated test. 

Character field, width 12.

TRACE METALS IN SEDIMENT are presented in fields 13 through 32. 

All sediment trace metal results are reported on a dry weight

basis in parts per million (ppm).

 A. When the value is missing or not analyzed, the value is

reported as "-9.0" = not analyzed.

 B. When the value is less than the detection limit of the

analytical test, the value is reported as "-8.0" = not

detected.

Sediment trace metals are numeric fields of varying character

width, and including the following elements, listed by field

number, then field name as it appears in the database, then

numeric character width and number of decimal places:

13. TMMOIST. 6.2

14. ALUMINUM. 9.2

15. ANTIMONY. 7.3

16. ARSENIC. 6.3

17. CADMIUM. 7.4

18. CHROMIUM. 8.3

19. COPPER. 7.2

20. IRON. 7.1

21. LEAD. 6.3

22. MANGANESE. 7.2

23. MERCURY. 7.4

24. NICKEL. 7.3

25. SILVER. 7.4

26. SELENIUM. 6.3

27. TIN. 8.4

28. ZINC. 9.4

29. ASBATCH. 5.1

30. SEBATCH. 5.1

31. TMBATCH. The Batch number that the sample was digested

in, numeric character width 5 and 1 decimal places.

32. TMDATAQC. Data qualifier codes are notations used by

data reviewers to

briefly describe, or qualify data and the systems

producing data, numeric character width 3. Data

qualifier codes are as follows:

 A. When the sample meets or exceeds the control criteria 

requirements,

the value is reported as "-4".

 B. When the sample has minor exceedances of control criteria
but is generally usable for most assessments and reporting

purposes, the value is reported as "-5". For samples coded "-5"

it is recommended that if assessments are made that are

especially sensitive or critical, QA evaluations should be

consulted before using the data.

 C. When QA samples have major exceedances of control criteria

requirements and the data are not usable for most

assessments and reporting purposes, the value is reported

as "-6".

 D. When the sample has minor exceedances of control

criteriaand is unlikely to affect assessments, the value is

reported as -3.

SYNTHETIC ORGANICS are presented in fields 33 through 147. All

synthetic organic results are reported on a dry weight basis in

parts per billion (ppb or ng/g).

 A. When the value is missing or not analyzed, the value is

reported as "-9.0" = not analyzed.

 B. When the value is less than the detection limit of the

analytical test, the value is reported as "-8.0" = not

detected.

Synthetic organics are reported on a dry weight basis in parts

per billion (ppb or ng/g) and are numeric fields of varying

character width, and include the following compounds, listed by

field number, then field name as it appears in database (and

followed by the compound name if not obvious), and then finally,

the numeric character width and number of decimal places is

given:

33. SOWEIGHT. This numeric field is 6 characters wide with 2

decimal places and contains the weight of the sample extracted

for analysis.

34. SOMOIST. This numeric field is 6 characters wide with 2

decimal places and contains the percent moisture of the sample

extracted.

35. ALDRIN. 9.3

36. CCHLOR. cis-Chlordane. 9.3

37. TCHLOR. trans-Chlordane. 9.3

38. ACDEN. alpha-Chlordene. 9.3

39. GCDEN. gamma-Chlordene. 9.3

40. CLPYR. Chlorpyrifos. 8.2

41. DACTH. Dacthal. 9.3

42. OPDDD. o,p'-DDD. 8.2

43. PPDDD. p,p'-DDD. 9.3

44. OPDDE. o,p'-DDE. 8.2

45. PPDDE. p,p'-DDE. 8.2

46. PPDDMS. p,p'-DDMS. 8.2

47. PPDDMU. p,p'-DDMU. 8.2

48. OPDDT. o,p'-DDT. 8.2

49. PPDDT. p,p'-DDT. 8.2

50. DICLB. p,p'-Dichlorobenzophenone. 8.2

51. DIELDRIN. 9.3

52. ENDO_I. Endosulfan I. 9.3

53. ENDO_II. Endosulfan II. 8.2

54. ESO4. Endosulfan sulfate. 8.2
55. ENDRIN. 8.2

56. ETHION. 8.2

57. HCHA. alpha HCH 9.3

58. HCHB. beta HCH 8.2

59. HCHG. gamma HCH (Lindane) 9.3

60. HCHD. delta HCH 9.3

61. HEPTACHLOR. 9.3

62. HE. Heptachlor Epoxide. 9.3

63. HCB. Hexachlorobenzene. 9.3

64. METHOXY. Methoxychlor. 8.2

65. MIREX. 9.3

66. CNONA. cis-Nonachlor. 9.3

67. TNONA. trans-nonachlor. 9.3

68. OXAD. Oxadiazon. 8.2

69. OCDAN. Oxychlordane. 9.3

70. TOXAPH. Toxaphene. 7.2

71. PESBATCH.The batch number that the sample was

extracted in, numeric

character width 6 and 2 decimal places.

72. TBT. tributyltin. 8.4

73. TBTBATCH.The batch number that the sample was

extracted in, numeric

character width 5 and 1 decimal place.

74. PCB5. 9.3

75. PCB8. 9.3

76. PCB15. 9.3

77. PCB18. 9.3

78. PCB27. 9.3

79. PCB28. 9.3

80. PCB29. 9.3

81. PCB31. 9.3

82. PCB44. 9.3

83. PCB49. 9.3

84. PCB52. 9.3

85. PCB66. 9.3

86. PCB70. 9.3

87. PCB74. 9.3

88. PCB87. 9.3

89. PCB95. 9.3

90. PCB97. 9.3

91. PCB99. 9.3

92. PCB101. 9.3

93. PCB105. 9.3

94. PCB11O. 9.3

95. PCB118. 9.3

96. PCB128. 9.3

97. PCB132. 9.3

98. PCB137. 9.3

99. PCB138. 9.3

100. PCB149. 9.3

101. PCB151. 9.3

102. PCB153. 9.3

103. PCB156. 9.3

104. PCB157. 9.3

105. PCB158. 9.3

106. PCB170. 9.3

107. PCB174. 9.3
108. PCB177. 9.3

109. PCB180. 9.3

110. PCB183. 9.3

111. PCB187. 9.3

112. PCB189. 9.3

113. PCB194. 9.3

114. PCB195. 9.3

115. PCB201. 9.3

116. PCB203. 9.3

117. PCB206. 9.3

118. PCB209. 9.3

119. PCBBATCH. The batch number that the sample was extracted

in, numeric character width 6 and 2 decimal place.

120. ARO5460. 9.3

121. ACY. Acenaphthylene. 8.2

122. ACE. Acenaphthene. 8.2

123. ANT. Anthracene. 8.2

124. BAA. Benz[a]anthracene. 8.2

125. BAP. Benzo[a]pyrene. 8.2

126. BBF. Benzo[b]fluoranthrene. 8.2

127. BKF. Benzo[k]fluoranthrene. 8.2

128. BGP. Benzo[ghi]perylene. 8.2

129. BEP. Benzo[e]pyrene. 8.2

130. BPH. Biphenyl. 8.2

131. CHR. Chrysene. 8.2

132. DBA. Dibenz[a,h]anthracene. 8.2

133. DMN. 2,6-Dimethylnaphthalene. 8.2

134. FLA. Fluoranthrene. 8.2

135. FLU. Fluorene. 8.2

136. IND. Indo[1,2,3-cd]pyrene. 8.2

137. MNP1. 1-Methylnaphthalene. 8.2

138. MNP2. 2-Methylnaphthalene. 8.2

139. MPH1. 1-Methylphenanthrene. 8.2

140. NPH. Naphthalene. 8.2

141. PHN. Phenanthrene. 8.2

142. PER. Perylene. 8.2

143. PYR. Pyrene. 8.2

144. TMN. 2,3,4-Trimethylnaphthalene. 8.2

145. PAHBATCH. The batch number that the sample was extracted

in, numeric character width 6 and 2 decimal places.

146. SOBATCH. The batch number that the sample was extracted

in, numeric character width 6 and 2 decimal places.

147. SODATAQA. Data qualifier codes are notations used by

data reviewers to

briefly describe, or qualify data and the systems

producing data, numeric character width 3. Data

qualifier codes are as follows:

 A. When the sample meets or exceeds the control criteria

requirements, the value is reported as "-4".

 B. When the sample has minor exceedances of control criteria

but is generally usable for most assessments and reporting

purposes, the value is reported as "-5". For samples coded "-5"

it is recommended that if assessments are made that are

especially sensitive or critical, the QA evaluations should be

consulted before using the data.

 C. When QA samples have major exceedances of control criteria

requirements and the data are not usable for most assessments and
reporting purposes, the value is reported as "-6".

 D. When the sample has minor exceedances of control criteria

and is unlikely to affect assessments, the value is reported as -

3.

SEDIMENT PARTICULATE SIZE ANALYSES DATA. Field 148, with a field

name of "FINES", represents the sediment particulate size ("grain

size") analyses data for each station. The grain size results

are reported as percent fines.

148. FINES. Sediment grain size (percent fines) for each

station. Numeric field, width 5 and 2 decimal places.

 A. When the value is missing or not analyzed, the value is

reported as "-9.0" = not analyzed.

 B. When the value is less than the detection limit of the

analytical test, the value is reported as "-8.0" = not detected.

149. FINEBATCH. The batch number that the sample was analyzed

in, numeric field character width 4.

150. FINEDATAQC. Data qualifier codes are notations used by

data reviewers to briefly describe, or qualify data and the

systems producing data, numeric character width 3. Data

qualifier codes are as follows:

 A. When the sample meets or exceeds the control criteria

requirements, the value is reported as "-4".

 B. When the sample has minor exceedances of control criteria

but is generally usable for most assessments and reporting

purposes, the value is reported as "-5". For samples coded "-5"

it is recommended that if assessments are made that are

especially sensitive or critical, QA evaluations should be

consulted before using the data.

 C. When QA samples have major exceedances of control criteria

requirements and the data are not usable for most assessments and

reporting purposes, the value is reported as "-6".

 D. When the sample has minor exceedances of control criteria

and is unlikely to affect assessments, the value is reported as -

3.

SEDIMENT TOTAL ORGANIC CARBON (TOC) ANALYSES DATA. Field 151

presents the levels of total organic carbon detected in the

sediment samples at each station. All TOC results are reported

as percent of dry weight.

151. TOC. Total Organic Carbon (TOC) levels (percent of dry

weight) in sediment, for each station. Numeric field, width 6

and 2 decimal places.

 A. When the value is missing or not analyzed, the value is

reported as "-9.0" = not analyzed.

 B. When the value is less than the detection limit of the

analytical test, the value is reported as "-8.0" = not detected.

152. TOCBATCH. The batch number that the sample was analyzed

in, numeric field character width 4.

153. TOCDATAQC. Data qualifier codes are notations used by data

reviewers to briefly describe, or qualify data and the systems

producing data, numeric character width 3. Data qualifier codes

are as follows:

 A. When the sample meets or exceeds the control criteria
requirements, the value is reported as "-4".

 B. When the sample has minor exceedances of control criteria

but is generally usable for most assessments and reporting

purposes, the value is reported as "-5". For samples coded "-5"

it is recommended that if assessments are made that are

especially sensitive or critical, the QA evaluations should be

consulted before using the data.

 C. When QA samples have major exceedances of control criteria

requirements and the data are not usable for most assessments and

reporting purposes, the value is reported as "-6".

 D. When the sample has minor exceedances of control criteria

and is unlikely to affect assessments, the value is reported as -

3.

The REG9TOX.DBF file is the toxicity data file which contains the

following fields (the number at the start of each field is the

field number:

1. STANUM. This numeric field is 7 characters wide with 1

decimal place and contains the CDFG station numbers that are used

statewide. The format is YXXXX.Z where Y is the Regional Water

Quality Control Board Region number and XXXX is the number that

corresponds to a given location or site and Z is the number of

the station within that site. An example is West Basin in San

Diego Harbor where the STANUM is 90050.0. The 9 indicates Region

9. The 0050 indicates that it is Site 50 and the .0 is the

replicate (if any) at the station within Site 50.

2. STATION. This character field is 30 characters wide and

contains the exact name of the station.

3. IDORG. This numeric field is 8 characters wide with 1

decimal place and contains the unique i.d. organizational number

for the sample. For each station collected on a unique date, an

idorg sample number is assigned. This should be the field that

links the collection, toxicity, chemical, and other data bases.

4. DATE. This date field is 8 characters long and is the

date that each sample was collected in the field. It

is listed as MM/DD/YY.

5. LEG. This numeric field is 6 characters wide and is the

leg number of the project in which the sample was collected.

6. TYPE. This character field is 7 characters wide and

describes whether the sample was a field sample, replicate or

control.

7. METADATA. This is an index directing the user to tables 

or files of ancillary data pertinent to associated test. 

Character field, width 12.

8. CTRL. This character field is 5 characters wide and

describes the type of control being used.

9. LATITUDE. This character field is 12 characters wide and

contains the latitude of the center of the station sampled. The

format is a character field as follows: XX,YY,ZZ, where XX is in

degrees, YY is in minutes, and ZZ is in seconds or hundreds.

10. LONGITUDE. This character field is 14 characters wide and

contains the longitude of the center of the station sampled. The

format is a character field as follows: XX,YY,ZZ, where XXX is

in degrees, YY is in minutes, and ZZ is in seconds or hundreds.

11. GISLAT. This numeric field is 12 characters wide with 8

decimal places and contains the latitude of the station sampled
in Geographical Information System format. The format is a

numeric field as follows: XX.YYYYYYYY, where XX is in degrees

and YYYYYYYY is a decimal fraction of the preceding degree.

12. GISLONG. This character field is 14 characters wide

with 8 decimal places and contains the longitude of

the station sampled. The format is a character field

as follows: XXXX.YYYYYYYY where XXXX is in degrees

and YYYYYYYY is a decimal fraction of the preceding

degree.

AMPHIPOD SURVIVAL TOXICITY TEST DATA. The following are

descriptions of the field headings for the amphipod (Rhepoxynius

abronius (RA), presented in fields 13 through 24.

13. RA_MN. Station mean percent survival. Numeric field,

width 6 and 2 decimal places.

14. RA_SD. Station standard deviation of percent survival.

Numeric field, width 6 and 2 decimal places.

15. RA_SG. Station statistical significance,

representing the significance of the statistical test

between the home sediment and the sample. A single *

represents significance at the .05 level, and double

** represents significance at the .01 level. ns = not

statistically significant. Character field, width 5.

16. RASITE_MN. Station mean percent survival for

replicate of three, when appropriate. Numeric field,

width 6 and 2 decimal places.

17. RASITE_SD. Station standard deviation of percent

survival for replicate of three, when appropriate. 

Numeric field, width 6 and 2 decimal places.

18. RASITE_SG. Station statistical significance,

representing the significance of the statistical test

between the home sediment and the sample. A single *

represents significance at the .05 level, and double

** represents significance at the .01 level. ns = not

statistically significant. Character field, width 5.

19. RA_OTNH3. Total ammonia concentration (mg/L in

water) in overlying water (water above bedded sediment

used for amphipod tests) for each station analyzed

using amphipod toxicity tests. When the value is

missing or not analyzed, the value is reported as "-

9.0" = not analyzed. When the value is less than the

detection limit of the analytical test, the value is

reported as "-8.0" = not detected. Numeric field,

width 7 and 3 decimal places.

20. RA_OUNH3. Unionized ammonia concentration (mg/L in

water) in overlying water (water above bedded sediment used for

amphipod tests) for each station analyzed using amphipod toxicity

tests. When the value is missing or not analyzed, the value is 

reported as "-9.0" = not analyzed. When the value is less than

the detection limit of the analytical test, the value is reported

as "-8.0" = not detected. Numeric field, width 7 and 3 decimal

places.

21. RA_OH2S. Hydrogen sulfide concentration (mg/L in

water) in overlying water (water above bedded sediment

used for amphipod tests) for each station analyzed

using amphipod toxicity tests. When the value is
missing or not analyzed, the value is reported as "-

9.0" = not analyzed. When the value is less than the

detection limit of the analytical test, the value is

reported as "-8.0" = not detected. Numeric field,

width 7 and 4 decimal places.

22. RA_ITNH3. Total ammonia concentration (mg/L in water) in

interstitial water (water above bedded sediment used for amphipod

tests) for each station analyzed using amphipod toxicity tests. 

When the value is missing or not analyzed, the value is reported

as "-9.0" = not analyzed. When the value is less than the

detection limit of the analytical test, the value is reported as

"-8.0" = not detected. Numeric field, width 10 and 3 decimal

places.

23. RA_IUNH3. Unionized ammonia concentration (mg/L in 

water) interstitial water (water within bedded sediment used for

amphipod tests) for each station analyzed using amphipod toxicity

tests. When the value is missing or not analyzed, the value is 

reported as "9.0" = not analyzed. When the value is less than the

detection limit of the analytical test, the value is reported as

"-8.0" = not detected. Numeric field, width 10 and 3 decimal

places.

24. RA_IH2S. Hydrogen sulfide concentration (mg/L in

water) in interstitial water (water within bedded

sediment used for amphipod tests) for each station

analyzed using amphipod toxicity tests. When the

value is missing or not analyzed, the value is

reported as "-9.0" = not analyzed. When the value is

less than the detection limit of the analytical test,

the value is reported as "-8.0" = not detected. 

Numeric field, width 10 and 4 decimal places.

25. RABATCH. The batch number that the sample were run

in, numeric character width 10.

26. RADATAQC. Data qualifier codes are notations used by

data reviewers to briefly describe, or qualify data

and the systems producing data, numeric character

width 4. Data qualifier codes are as follows:

 A. When the sample meets or exceeds the control criteria

requirements, the value is reported as "-4".

 B. When the sample has minor exceedances of control

criteria but is generally usable for most assessments

and reporting purposes, the value is reported as "-5".

 For samples coded "-5" it is recommended that if

assessments are made that are especially sensitive or

critical, the QA evaluations should be consulted

before using the data.

 C. When the QA sample has major exceedances of control

criteria requirements and the data is not usable for most

assessments and reporting purposes, the value is reported as

"-6".

 D. When the sample has minor exceedances of control

criteria and is unlikely to affect assessments, the

value is reported as -3.

ABALONE LARVAL SHELL DEVELOPMENT TOXICITY TEST DATA. The 

following are descriptions of the field headings for the larval

(Haliotis rufescens) shell development toxicity tests, presented

in fields 27 through 30. Results are given for undiluted
subsurface water (100%).

27. HRS100_MN. Station mean percent normal development in

100% subsurface water. Numeric field, width 6 and 2 decimal

places.

28. HRS100_SD. Station standard deviation of percent

normal development in 100% subsurface water. Numeric

field, width 6 and 2 decimal places.

29. HRS100_SG. Station statistical significance,

representing the significance of the statistical test

between the home sediment and the sample. A single *

represents significance at the .05 level, and double

** represents significance at the .01 level. ns = not

statistically significant. Character field, width 5.

30. HRS100_NH3. Unionized ammonia concentration (mg/L in

water) in subsurface water for each station analyzed

in abalone toxicity tests. When the value is missing

or not analyzed, the value is reported as "-9.0" = not

analyzed. When the value is less than the detection

limit of the analytical test, the value is reported as

"-8.0" = not detected. Numeric field, width 6 and 3

decimal places.

The following are descriptions of the field headings for the sea

urchin (Strongylocentrotus purpuratus) fertilization toxicity

tests, presented in fields 31 through 41. Results are given for

undiluted pore water (100% pore water), pore water that is

diluted with Granite Canyon seawater to a 50% of original

concentration (50% pore water), and pore water that is diluted

with Granite Canyon seawater to a 25% of original concentration

(25% pore water).

31. SPPF100_MN. Station mean percent fertilization in

100% pore water. Numeric field, width 6 and 2 decimal

places.

32. SPPF100_SD.Station standard deviation of percent

fertilization in 100% pore water. Numeric field, width

6 and 2 decimal places.

33. SPPF100_SG. Station statistical significance,

representing the significance of the statistical test

between the home sediment and the sample. A single *

represents significance at the .05 level, and double

** represents significance at the .01 level. ns = not

statistically significant. Character field, width 5.

34. SPPF100NH3. Unionized ammonia concentration (mg/L in

water) in pore water samples (100%). When the value

is missing or not analyzed, the value is reported as

"-9.0" = not analyzed. When the value is less than

the detection limit of the analytical test, the value

is reported as "-8.0" = not detected. Numeric field,

width 7 and 3 decimal places.

35. SPPF100H2S. Hydrogen sulfide concentration (mg/L in

water) in pore water samples (100%). When the value is

missing or not analyzed, the value is reported as "-

9.0" = not analyzed. When the value is less than the

detection limit of the analytical test, the value is

reported as "-8.0"= not detected. Numeric field,
width 7 and 4 decimal places.

36. SPPF50_MN. Station mean percent fertilization in 50%

pore water. Numeric field, width 6 and 2 decimal

places.

37. SPPF50_SD. Station standard deviation of %

fertilization in 50% pore water. Numeric field, width

6 and 2 decimal places.

38. SPPF50_SG. Station statistical significance,

representing the significance of the statistical test

between the home sediment and the sample. A single *

represents significance at the .05 level, and double

** represents significance at the .01 level. ns = not

statistically significant. Character field, width 5.

39. SPPF25_MN. Station mean percent fertilization in 25%

pore water. Numeric field, width 6 and 2 decimal

places.

40. SPPF25_SD. Station standard deviation of percent

fertilization in 25% pore water. Numeric field, width

6 and 2 decimal places.

41. SPPF25_SG. Station statistical significance,

representing the significance of the statistical test

between the home sediment and the sample. A single *

represents significance at the .05 level, and double

** represents significance at the .01 level. ns = not

statistically significant. Character field, width 5.

The following are descriptions of the field headings for the sea

urchin embryo (Strongylocentrotus purpuratus) development tests,

presented in fields 42 through 54. Results are given for

undiluted pore water (100% pore water), pore water that is

diluted with Granite Canyon seawater to a 50% of original

concentration (50% pore water), and porewater that is diluted

with Granite Canyon seawater to a 25% of original concentration

(25% pore water).

42. SPPD100_MN. Station mean percent normal development

in 100% pore water. Numeric field, width 6 and 2

decimal places.

43. SPPD100_SD. Station standard deviation of percent

normal development in 100% pore water. Numeric field,

width 6 and 2 decimal places.

44. SPPD100_SG. Station statistical significance,

representing the significance of the statistical test

between the home sediment and the sample. A single *

represents significance at the .05 level, and double

** represents significance at the .01 level. ns = not

statistically significant. Character field, width 5.

45. SPPD100NH3. Unionized ammonia concentration (mg/L in

water) in pore water samples (100%). When the value

is missing or not analyzed, the value is reported as

"-9.0" = not analyzed. When the value is less than

the detection limit of the analytical test, the value

is reported as "-8.0" = not detected. Numeric field,

width 7 and 3 decimal places.

46. SPPD100H2S. Hydrogen sulfide concentration (mg/L in

water) in pore water samples (100%). When the value is

missing or not analyzed, the value is reported as "-
9.0" = not analyzed. When the value is less than the

detection limit of the analytical test, the value is

reported as "-8.0"= not detected. Numeric field,

width 7 and 4 decimal places.

47. SPPD50_MN. Station mean percent normal development

in 50% pore water. Numeric field, width 6 and 2

decimal places.

48. SPPD50_SD. Station standard deviation of percent

normal development in 50% pore water. Numeric field,

width 6 and 2 decimal places.

49. SPPD50_SG. Station statistical significance,

representing the significance of the statistical test

between the home sediment and the sample. A single *

represents significance at the .05 level, and double

** represents significance at the .01 level. ns = not

statistically significant. Character field, width 5.

50. SPPD25_MN. Station mean percent normal development

in 25% pore water. Numeric field, width 6 and 2

decimal places.

51. SPPD25_SD. Station standard deviation of percent

normal development in 25% pore water. Numeric field,

width 6 and 2 decimal places.

52. SPPD25_SG. Station statistical significance,

representing the significance of the statistical test

between the home sediment and the sample. A single *

represents significance at the .05 level, and double

** represents significance at the .01 level. ns = not

statistically significant. Character field, width 5.

53. SPPDBATCH. The batch number that the samples were

analyzed in, numeric character width 10.

54. SPPDQC. Data qualifier codes are notations used by

data reviewers to briefly describe, or qualify data

and the systems producing data, numeric character

width 3. Data qualifier codes are as follows:

 A. When the sample meets or exceeds the control criteria

requirements, the value is reported as "-4".

 B. When the sample has minor exceedances of control

criteria but is generally usable for most assessments

and reporting purposes, the value is reported as "-5".

 For samples coded "-5" it is recommended that if 

assessments are made that are especially sensitive or

critical, the QA evaluations should be consulted

before using the data.

 C. When the QA sample has major exceedances of control

criteria requirements and the data is not usable for

most assessments and reporting purposes, the value is

reported as "-6".

 D. When the sample has minor exceedances of control

criteria and is unlikely to affect assessments, the

value is reported as -3.

The following are descriptions of the field headings for the sea

urchin embryo (Strongylocentrotus purpuratus) cytogenetic tests,

presented in fields 55 through 59. Results are given for

undiluted pore water (100% pore water).

55. SPPC100_MN. Station mean percent normal mitosis in
100% pore water. Numeric field, width 6 and 2 decimal

places.

56. SPPC100_SD. Station standard deviation of percent

normal mitosis in 100% pore water. Numeric field,

width 6 and 2 decimal places.

57. SPPC100_SG. Station statistical significance,

representing the significance of the statistical test

between the home sediment and the sample. A single *

represents significance at the .05 level, and double

** represents significance at the .01 level. ns = not

statistically significant. Character field, width 6.

58. SPPC100NH3. Unionized ammonia concentration (mg/L in

water) in pore water samples (100%). When the value

is missing or not analyzed, the value is reported as

"-9.0" = not analyzed. When the value is less than

the detection limit of the analytical test, the value

is reported as "-8.0" = not detected. Numeric field,

width 6 and 3 decimal places.

59. SPPC100H2S. Hydrogen sulfide concentration (mg/L in

water) in pore water samples (100%). When the value is

missing or not analyzed, the value is reported as "-

9.0" = not analyzed. When the value is less than the

detection limit of the analytical test, the value is

reported as "-8.0"= not detected. Numeric field,

width 7 and 4 decimal places.

MUSSEL LARVAL SHELL DEVELOPMENT TOXICITY TEST DATA. The

following are descriptions of the field headings for the larval

(Mytilus edulis) shell development toxicity tests, presented in

fields 60 through 63. Results are given for undiluted subsurface

water (100%).

60. MES100_MN. Station mean percent normal development

in 100% subsurface water. Numeric field, width 6 and

2 decimal places.

61. MES100_SD. Station standard deviation of percent

normal development in 100% subsurface water. Numeric

field, width 6 and 2 decimal places.

62. MES100_SG. Station statistical significance,

representing the significance of the statistical test

between the home sediment and the sample. A single *

represents significance at the .05 level, and double

** represents significance at the .01 level. ns = not

statistically significant. Character field, width 5.

63. MES100_NH3. Unionized ammonia concentration (mg/L in

water) in subsurface water. When the value is missing

or not analyzed, the value is reported as "-9.0" = not

analyzed. When the value is less than the detection

limit of the analytical test, the value is reported as

"-8.0" = not detected. Numeric field, width 6 and 3

decimal places.

The following are descriptions of the field headings for the

larval (Mytilus edulis) shell development toxicity tests,

presented in fields 64 through 68. Results are given for

undiluted pore water (100% pore water).
64. MEP100_MN. Station mean percent normal development

in 100% pore water. Numeric field, width 6 and 2

decimal places.

65. MEP100_SD. Station standard deviation of percent

normal development in 100% pore water. Numeric field,

width 6 and 2 decimal places.

66. MEP100_SG. Station statistical significance,

representing the significance of the statistical test

between the home sediment and the sample. A single *

represents significance at the .05 level, and double

** represents significance at the .01 level. ns = not

statistically significant. Character field, width 5.

67. MEP100_NH3. Unionized ammonia concentration (mg/L in

water) in pore water samples (100%). When the value

is missing or not analyzed, the value is reported as

"-9.0" = not analyzed. When the value is less than the

detection limit of the analytical test, the value is

reported as "-8.0" = not detected. Numeric field,

width 6 and 3 decimal places.

68. MEP100_H2S. Hydrogen sulfide concentration (mg/L in

water) in pore water samples (100%). When the value

is missing or not analyzed, the value is reported as

"-9.0" = not analyzed. When the value is less than

the detection limit of the analytical test, the value

is reported as "-8.0"= not detected. Numeric field,

width 7 and 4 decimal places.

POLYCHAETE SURVIVAL TOXICITY TEST DATA. The following are

descriptions of the field headings for the polychaete worm

(Neanthes arenaceodentata) survival toxicity tests, presented in

fields 69 through 71.

69. NASURV_MN. Station mean percent survival. Numeric

field, width 6 and 2 decimal places.

70. NASURV_SD. Station standard deviation of % survival.

Numeric field, width 6 and 2 decimal places.

71. NASURV_SG. Station statistical significance,

representing the significance of the statistical test

between the home sediment and the sample. A single *

represents significance at the .05 level, and double

** represents significance at the .01 level. ns = not

statistically significant. Character field, width 5.

POLYCHAETE WEIGHT TOXICITY TEST DATA. The following are

descriptions of the field headings for the polychaete worm

(Neanthes arenaceodentata) weight toxicity tests, presented in

fields 72 through 80.

72. NAWT_MN. Station mean weight (gm). Numeric field,

width 6 and 2 decimal places.

73. NAWT_SD. Station standard deviation of weight (gm).

Numeric field, width 6 and 2 decimal places.

74. NAWT_SG. Station statistical significance,

representing the significance of the statistical test

between the home sediment and the sample. A single *

represents significance at the .05 level, and double

** represents significance at the .01 level. ns = not
statistically significant. Character field, width 5.

75. NA_OTNH3. Total ammonia concentration (mg/L in

water) in overlying water (water above bedded

sediment used for polychaete tests) for each station

analyzed using polychaete toxicity tests. When the

value is missing or not analyzed, the value is 

reported as "-9.0" = not analyzed. When the value is

less than the detection limit of the analytical test,

the value is reported as "-8.0" = not detected. 

Numeric field, width 7 and 3 decimal places.

76. NA_OUNH3. Unionized ammonia concentration (mg/L in

water) in overlying water (water above bedded sediment

used for polychaete tests) for each station analyzed

using polychaete toxicity tests. When the value is

missing or not analyzed, the value is reported as "-

9.0" = not analyzed. When the value is less than the

detection limit of the analytical test, the value is

reported as "-8.0" = not detected. Numeric field,

width 7 and 3 decimal places.

77. NA_OH2S. Hydrogen sulfide concentration (mg/L in

water) in overlying water (water above bedded sediment

used for polychaete tests) for each station analyzed

using polychaete toxicity tests. When the value is

missing or not analyzed, the value is reported as "-

9.0" = not analyzed. When the value is less than the

detection limit of the analytical test, the value is

reported as "-8.0" = not detected. Numeric field,

width 9 and 4 decimal places.

78. NA_ITNH3. Total ammonia concentration (mg/L in

water) in interstitial water (water above bedded

sediment used for polychaete tests) for each station

analyzed using polychaete toxicity tests. When the

value is missing or not analyzed, the value is 

reported as "-9.0" = not analyzed. When the value is

less than the detection limit of the analytical test,

the value is reported as "-8.0" = not detected. 

Numeric field, width 9 and 3 decimal places.

79. NA_IUNH3. Unionized ammonia concentration (mg/L in

water) in interstitial water (water within bedded

sediment used for polychaete tests) for each station

analyzed using polychaete toxicity tests. When the

value is missing or not analyzed, the value is

reported as "-9.0" = not analyzed. When the value is

less than the detection limit of the analytical test,

the value is reported as "-8.0" = not detected. 

Numeric field, width 9 and 3 decimal places.

80. NA_IH2S. Hydrogen sulfide concentration (mg/L in

water) in interstitial water (water within bedded

sediment used for amphipod tests) for each station

analyzed using amphipod toxicity tests. When the

value is missing or not analyzed, the value is

reported as "-9.0" = not analyzed. When the value is

less than the detection limit of the analytical test,

the value is reported as "-8.0" = not detected. 

Numeric field, width 9 and 4 decimal places.
CHEMICAL SUMMATIONS AND QUOTIENTS

In the following section, chemical summations (total chlordane,

total DDT, total PCBs, LMW PAHs, HMW PAHs, total PAHs) and

quotients (ERM and PEL) are presented. Beginning with samples

collected during Leg 20 (June, 1993), additional analytes were

added to the standard BPTCP synthetic organic analyte list. These

additions were made to enable the data set to be more comparable

with other monitoring programs. This included addition of

analytes used for some of the chemical summations of the PAHs and

total chlordane. Resulting summations may be conservative for the

PAH and chlordane data for samples taken before Leg 20, because

some of the constituents could not be included.

For purposes of these summations, samples which were found to

have chemical concentrations less than the method detection limit

(-8 in Appendix A) were adjusted to a value of one-half of the

method detection limits given in the methods description. The

summations were calculated as follows:

Total chlordane

Leg<15 (TTL_CHLR) = Σ ([cis-Chlordane] [trans-Nonachlor])

Leg=15 (TTL_CHLR) = Σ ([cis-Chlordane] [trans-Chlordane])

Leg>15 (TTL_CHLR) = Σ ([cis-Chlordane] [trans-Chlordane]

[cis-Nonachlor] [trans-Nonachlor] [Oxychlordane])

Total DDT

All Legs (TTL_DDT) = Σ ([o',p' DDD] [p',p' DDD] [o',p' DDE] 

[p',p' DDE] [o',p' DDT] [p',p' DDT])

Total PCB

All Legs (TTL_PCB) = Σ ([PCB8] [PCB18] [PCB28] [PCB44] [PCB52]

[PCB66] [PCB101] [PCB105] [PCB118] [PCB128] [PCB138] [PCB153]

[PCB170] [PCB180] [PCB187] [PCB195] [PCB206] [PCB209])

Low Molecular Weight PAHs

Leg<16 (LMW_PAH) = Σ ([ACE] [ANT] [BPH] [DMN] [FLU]

[MNP1] [MPH1] [PHN])

Leg≥16 (LMW_PAH) = Σ ([ACE] [ACY] [ANT] [BPH] [DMN] [FLU]

[MNP1] [MNP2] [MPH1] [NPH] [PHN] [TMN])

High Molecular Weight PAHs

Leg<16 (HMW_PAH) = Σ ([BAA] [BAP] [BEP] [CHR] [DBA]

[FLA] [PER] [PYR])

Leg≥16 (HMW_PAH) = Σ ([BAA] [BAP] [BBF] [BKF] [BGP] [BEP]

[CHR] [DBA] [FLA] [IND] [PER] [PYR])

Total PAHs

All legs (TTL_PAH) = Σ ([LMW_PAH] [HMW_PAH])

ERM Quotients and PEL Quotients were calculated using summations

of the individual chemicals for which ERMs and PELs have been
derived (Table 5). Chemical concentrations are divided by their

respective ERM or PEL values to obtain a specific individual

chemical quotient (example 1). A value greater than one indicates

the chemical concentration in that sample exceeded its respective

ERM or PEL. A value of five would indicate the chemical was five

times higher than the ERM or PEL in that sample.

example - sample IDORG #199 Copper concentration= 170 mg/g

 PEL for copper= 108.2

CopperQ= (170 mg/g) / (108.2 mg/g) = 1.57

Summations and averaging of the individual chemical quotients

were calculated to give summary ERM Quotients (ERMQ) and PEL

Quotients (PELQ). Each quotient summation is divided by the

number of analytes used in the summation (Table 5) to yield an

average summary quotient. 

Summary ERM Quotient

ERMQ = ((ANTIMONYQ + ARSENICQ + CADMIUMQ + CHROMIUMQ +

COPPERQ + LEADQ + MERCURYQ + SILVERQ + ZINCQ + TTL_DDTQ +

TTL_CHLRQ + DIELDRINQ + ENDRINQ + TTL_PCBQ + LMW_PAHQ + HMW_PAHQ)

/ 16)

Summary PEL Quotient

PELQ = ((ARSENICQ + CADMIUMQ + CHROMIUMQ + COPPERQ

+ LEADQ + MERCURYQ + SILVERQ + ZINCQ + TTL_DDTQ +

TTL_CHLRQ + DIELDRINQ + LINDANEQ + TTL_PCBQ + LMW_PAHQ

+ HMW_PAHQ) / 15)
Description of calculations for cumulative frequency

distributions of percent area toxic.

The following identifies and describes each of the spreadsheet

columns used to generate cumulative frequency functions for

estimates of percent area toxic.

Idorg : lists all samples tested for each toxicity test

protocol/pore water dilution.

Block#: lists assigned letter/number code for each area (block)

based on EMAP block designations. See Figure 2.

# samples/block: lists total number of samples collected in

given block.

toxic: "1" indicates sample toxicity based on EMAP definition

(both significant difference from laboratory control and toxicity

value <80% of control value). Blank cell indicates no significant

toxicity.

mn as % of control : lists sample toxicity means normalized to 

percentage of the control value.

Area/block : Area in km2 for block associated with each sample

Area/sample : Area in km2 represented by each sample, calculated

as: Block area/number of samples collected in given block.

Area/sample as % of total : Area represented by each sample as

a percent of the total area sampled.

Cum area/sample as % of total : Cumulative area per sample as a

percent of the total area sampled.

% total area toxic/sample : Area represented by each toxic

sample as a percent of the total area.

SUMS : Numbers in this row show column totals. Sum of

Area/sample gives total area sampled for a given toxicity test

protocol. Sum of % of total area toxic/sample gives the total

area defined as toxic for given test protocol /pore water

dilution.