EPA903-R-97-016
CBP/TRS 176/97
June 1997
A Chemical Contaminant
Mass Balance Framework for
Chesapeake Bay
Chesapeake Bay Program
tm rtrrclrd partr
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A Chemical Contaminant
Mass Balance Framework
for Chesapeake Bay
June 1997
David Velinsky
Chesapeake Bay Program
410 Severn Avenue, Suite 109
Annapolis, Maryland 21403
1-800-YOUR-BAY
http://www.epa.gov/chesapeake
Printed by the U.S. Environmental Protection Agency for the Chesapeake Bay Program
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TABLE OF CONTENTS
Page #
List of Tables , ii
List of Figures iii
Executive Summary iv
Introduction 1
Conceptual Framework 2
Processes Influencing the Fate of Chemical Contaminants within
Chesapeake Bay 2
Physical Processes 2
Geochemical Processes 6
Biological Processes 11
Physical and Biogeochemical Processing of Contaminants within the Bay . 14
Mass Balance Development for Chesapeake Bay 16
Modeling Framework 17
Compartments of Chemical Contaminants in Chesapeake Bay 18
Transport Processes of Chemical Contaminants to Chesapeake Bay . 20
Summary 25
Loading of Chemical Contaminants to Tidal Chesapeake Bay: A Summary 27
Comparison of the Various Fluxes to the Bay 28
A Preliminary Mass Balance for the Maryland Portion of Tidal Chesapeake Bay:
An Illustrative Example • 30
' Inputs of Metals 31
Metals Burial in the Sediments , 32
Comparison of Inputs and Burial 36
Towards a Chesapeake Bay Chemical Contaminant Mass Balance 39
References 42
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LIST OF TABLES
Page#
1. Potential compartments for the development of a CBMB 19
2. Potential sources, sinks, and processes of chemical contaminants in tidal
Chesapeake Bay 21
3. Summary of contaminant loads to the tidal waters of Chesapeake Bay 29
4. Summary of trace metal loads to the Maryland portion of tidal Chesapeake
Bay 31
5. Surface areas and depositional fractions for the Maryland portion of Chesapeake
Bay 34
6. Mass sedimentation rates for various areas of Chesapeake Bay 34
7. Trace metal concentrations for areas within the Maryland portion of
Chesapeake Bay 35
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LIST OF FIGURES
Page#
1. Conceptual model of the different inputs and outputs for chemical contaminants
to tidal Chesapeake Bay 3
2. Graphic description of a mass balance showing processes and pathways for
Chesapeake Bay 26
3. Inputs and outputs of trace metals to the Maryland portion of Chesapeake
Bay 37
111
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EXECUTIVE SUMMARY
Introduction
Chemical contaminants in the water and sediment of Chesapeake Bay can affect ecosystem
functions as well as pose a direct threat to human health via drinking water and the consumption
of aquatic organisms (e.g., fish and shellfish). The recently-published Chesapeake Bay Basinwide
Toxics Reduction Strategy Reevaluation Report (Chesapeake Bay Program, 1994d) described the
results of a multi-year effort to evaluate the nature, extent, and magnitude of the Bay's chemical
contaminant problems. While this study continued the Chesapeake Bay Program's effort to
account for the sources of chemical contaminants, a more exacting examination of both the
sources and sinks is needed.
One way to place this information into a coherent framework is with the development of a
chemical contaminant mass balance. A mass balance approach requires that the quantities of
chemical contaminants entering the Bay, less the amount stored, transformed, or degraded within
the system, must equal the amount leaving the Bay system. The objective of this report is to
develop a chemical contaminant mass balance framework for Chesapeake Bay. Once fully
developed this framework will point out initial steps, definitions, data needs, capabilities, and
problems that are involved in the development of a mass balance, and would place the various
monitoring, research, and modeling studies into a holistic picture helping to focus future studies
and management actions on specific cleanup actions.
A mass balance model is defined here as an equation that describes a process where matter
entering a system, minus matter leaving the system, equals matter stored, transformed, or
degraded within the system. In this regard, a mass balance model establishes a process for
identifying and consistently evaluating all ways that chemical contaminants can enter and exit a
waterbody such as Chesapeake Bay. The construction of a mass balance needs to account for the
various fluxes or movements between the different interfaces within the Bay, including the air-
water, Bay-ocean, and sediment-water interfaces. Both sources to the Bay and sinks from the
Bay would be combined with internal process information to provide an indication of the relative
magnitude of the Bay's various inputs and outputs and overall fate of chemical contaminants.
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Therefore, a thorough understanding of the physical, geochemical, and biological processes within
Chesapeake Bay is needed in order to fully develop a realistic mass balance. Also, understanding
how similar classes of chemicals cycle through the Bay is needed to help make predictions
concerning the fate of specific chemicals that may be too costly to investigate individually.
Inputs to Chesapeake Bay
The calculation of input fluxes to Chesapeake Bay is a complex task. Problems inherent in
these types of calculations include: 1) a general lack of data, 2) comparability of chemical
measurements and forms for each source category, and 3) incomplete reporting of the various
sources. In many cases, the reporting programs in which data were collected were not set up with
the objective of calculating a load or flux, but rather for assessing the potential biological effects
via comparison with numerical water quality standards. Despite these limitations, initial load
estimates need to be established to assess the relative magnitude of point and non-point inputs and
where data needs are greatest to improve future load estimates.
The loads from the various sources to the tidal Bay are compared in Table A-l. The ranges
presented for atmospheric deposition, river transport, urban runoff, and shoreline erosion were
not calculated similarly, and may be based upon as little as two estimates. Unfortunately, organic
contaminant data for the various sources are lacking, as there is not a coherent program to
measure these parameters, except for the atmospheric and river monitoring studies.
For copper, zinc, and chromium, river transport fluxes are substantially higher than other
sources. The second largest source of trace metals to the tidal Bay appears to be urban runoff.
However, the range of estimates for urban runoff is large, and should be an area of future study to
help constrain these values. Shoreline erosion, along with river transport, appear to be important
sources of chromium and zinc. Generally, there is a lack of adequate data for the quantification of
the inputs of most organic contaminants. The river transport flux for total polychlorinated
biphenyls (PCBs) is approximately ten times greater than atmospheric deposition. Unfortunately,
there are no data for the other possible sources of these chemicals to the Bay. Urban runoff is the
dominant source of the polycyclic aromatic hydrocarbons (PAHs), chrysene and benzo[a]pyrene,
to the Bay.
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Table A-l. Summary of contaminant loads to the entire tidal waters of Chesapeake Bay.
Chemical
Metals
Cadmium
Chromium
Copper
Lead
Zinc
Organics
Benzo[a]pyrene
Chrysene
Total PCBs
Atmospheric Urban
Deposition Runoff
1.3-
2.2-
11 -
9.5-
31-
0.054 -
0.093 -
0.030 -
1.6 0.95-5.3
4.2 5.4 - 30
15 15-84
15 190-360
52 84-460
0.13 0.094
0.19 0.24
0.039 ND
River
Transport
37-
200-
270-
310-
130-
0.19-
71
270
450
410
220
0.36
ND
0.37 -
0.38
Shoreline
Erosion
1.0- 1.9
83-90
28-29
27-28
96- 120
ND
ND
ND
Point
Sources
0.62
19
37
5.3
160
0.044
0.007
ND
Loads are in metric tons per yr. ND - No Data.
These data illustrate the current status of the loading information available as part of the
Chesapeake Bay Basinwide Toxics Loading and Release Inventory (Chesapeake Bay Program,
1994a). While there are many assumptions and problems with the current data set, this exercise
highlights areas that need further study in order to synthesize a more complete understanding and
quantification of the sources of potentially toxic chemicals to Chesapeake Bay. Recommendations
for future loadings studies include: 1) for all sources determine a consistent chemical fraction
(e.g., total, total recoverable, dissolved), 2) use lower detection limit methods for both dissolved
and paniculate analyses, 3) include urban stations in the atmospheric deposition network, 4)
undertake a comprehensive sampling of major point source dischargers, and 5) initiate site specific
studies to better estimate the urban flux of chemical contaminants.
Preliminary Input-Output Mass Balance of the Maryland Portion of the Tidal Bay
To illustrate some of the problems, pitfalls, and usefulness of constructing a simple input-
output mass balance, information and data from various sources were collected and compared for
the Maryland portion of tidal Chesapeake Bay. Only specific trace metals (e.g., copper, lead, and
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zinc) were quantified due to a larger existing database for these metals than for organic
contaminants.
Yearly burial rates of copper, lead, and zinc to the Maryland portion of the Bay ranged from
220 to 680 metric tons/yr, 360 to 1,200 metric tons/yr, and 1,400 to 4,300 metric tons/yr,
respectively. For both copper and lead there is a reasonable agreement between quantified inputs
and burial, while for zinc the output via sediment burial is approximately three times as high as the
inputs. It is unclear why the burial of zinc is much higher than its input, compared to both copper
and lead (i.e., all sources and sinks were estimated similarly). Variations in the concentration of
surficial concentration of zinc may require further study. Conversely, there may be many
unaccounted or underestimated sources that also need to be assessed or re-assessed. It appears
that the total load introduced to this area can be balanced by what is lost or buried in the
sediments, and very little is transported to the southern portion of the Bay. However, while the
closeness of these fluxes may be real, there are many areas of uncertainty, both for sources and
sinks, that prohibit any definitive conclusions at this point. This exercise helps focus future
research and monitoring programs in order to lower the uncertainty between inputs and outputs
and enable Bay managers to make scientifically-based decisions regarding contaminants in the
Bay.
Towards a Mass Balance for Chesapeake Bay
The example input-output mass balance for the northern Bay appears to be consistent in that
there is a reasonable agreement between total inputs and the loss of these metals via burial.
Unfortunately, due to the lack of data it is impossible to quantify the uncertainty many of these
estimates. However, while the amount of uncertainty in this analysis is most likely large, this
study does allow a focusing of monitoring efforts on specific sources and geographic areas that
would greatly improve and expand a mass balance. Overall, basic monitoring information is
needed for almost all sources and sinks identified in this document. While these monitoring data
will not provide information as to the effects of chemical contaminants, they do provide the
needed information as to where and how much a reduction in a particular source load is needed.
Until both sources and sinks are better quantified, future input-output balances will remain
Vll
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uncertain and of limited quantitative use.
For a more complete mass balance model to be useful, its development must be driven by the
objectives that both managers and scientists decide upon. Also, there are many questions
concerning the feasibility of using a mass balance approach to manage or evaluate chemical
contaminants in Chesapeake Bay. For example, if a concerted effort is applied to determine the
absolute inputs and outputs from significant sources and sinks, will enough specific information
exist to help managers of the various sources of contaminants (e.g., point source regulators or
urban planners) determine the need for potential additional regulation of these sources? Also, if
additional regulatory actions are taken, will living resources that are affected by contaminants
respond and show some improvement (e.g., fewer fish advisories)?
As can be seen from the simple input-output model for Maryland, the data needs for any of
these tasks are enormous and would, therefore, be very expensive. However, the development of
a simple input-output mass balance could be a first step and would be less expensive while
providing useful information to bay managers. The results generated from such a project would
also be a part of the initial data requirements for a larger modeling framework if developed. This
information is heeded to help focus clean-up efforts and the limited dollars to areas and sources
that will make the biggest difference in the overall health of Chesapeake Bay.
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INTRODUCTION
Chemical contaminants in the water and sediment of Chesapeake Bay can affect ecosystem
functions as well as pose a direct threat to human health via drinking water and the consumption
of aquatic organisms (e.g., fish and shellfish). The recently-published Chesapeake Bay Basinwide
Toxics Reduction Strategy Reevaluation Report (Chesapeake Bay Program, 1994d) described the
results of a multi-year effort to evaluate the nature, extent, and magnitude of the Bays chemical
contaminant problems. Also, this report pointed to ways to reduce the impact of contaminants,
and to what information is needed to determine future actions. While this study continued the
Bay Program's effort to account for the sources of chemical contaminants, a more exacting
examination of both the sources and sinks is needed. The identification and quantification of the
different sources, sinks, and storage of anthropogenic and natural chemicals in Chesapeake Bay is
an important step towards understanding their cycling and potential effects in the Bay.
One way to place this information into a coherent framework is with the development of a
chemical contaminant mass balance. A mass balance approach requires that the quantities of
chemical contaminants entering the Bay, less the amount stored, transformed, or degraded within
the system, must equal the amount leaving the Bay system. With a working mass balance budget,
various control strategies can be simulated to evaluate long-term changes for each contaminant
(see Chesapeake Bay Program, 1994b). Such simulations and predictions can be valuable in the
assessment of the effect of chemical contaminants on human and ecosystem health, and can help
make expensive monitoring programs within the Bay more cost-effective.
The objective of this report is to develop a chemical contaminant mass balance framework
for Chesapeake Bay. This framework will point out initial steps, definitions, data needs,
capabilities, and problems that are involved in the development of a mass balance. This
framework would place the various monitoring, research, and modeling studies into a holistic
picture helping to focus future studies and management decisions on specific cleanup actions.
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CONCEPTUAL FRAMEWORK
The mass balance framework for chemical contaminants would involve a fate and transport
set of calculations or model(s) for particle-reactive chemicals. If bioaccumulation of contaminants
in phytoplankton, zooplankton, and fish is included, then a food-web dynamics model (e.g.,
Thomann et al. 1989; 1992) would be incorporated into the fate and transport computations.
Each type of model is complex, but would yield important information concerning potential
impact and cycling of contaminants within the Bay. A conceptual model of the sources, transport,
and fete of chemical contaminants within Chesapeake Bay is presented in Figure 1. Depicted in
this model are the different sources of contaminants, both point and non-point. A long-term goal
of any modeling exercise is to integrate hydrodynamic, water quality (both chemical contaminants
and nutrients), and ecosystem function models for a comprehensive understanding of Chesapeake
Bay. While this objective is daunting, Kemp and Baker (1994; preliminary results) and Kemp et
al. (1995; preliminary results) initiated a model simulation study of relevant ecosystem interactions
in the control of chemical speciation, transport, and biological effects of synthetic organic
chemicals (e.g., polychlorinated biphenyls). Their goal is to describe the relevant processes
controlling bioavailability and accumulation of these chemicals in the Bay. Also, Madden et al.
(1994) proposed to use a similar computational framework to study organic contaminant
ecosystem interactions within Baltimore Harbor, which has been listed as a Chesapeake Bay
Region of Concern (Chesapeake Executive Council, 1994).
In the following section, the different physical and biogeochemical processes that play a role
in the cycling of chemical contaminants are introduced. This information is crucial in the
understanding and development of a mass balance framework for chemical contaminants in the
Bay.
Processes Influencing the Fate of Chemical Contaminants within Chesapeake Bay
Physical Processes
Estuaries, such as Chesapeake Bay, are dynamic systems in which physical processes such as
circulation, stratification, mixing, and flushing are affected primarily by temporal changes in river
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Agriculture
SUppinc
Wet + Dry Deposition
Gu Exchanc*
Chesapeake/Delaware Bay
A Depodtioi
>billution T
Retnobillution
DepodlJon Water
Sediment
Defradadon
Burial
Figure 1. Conceptual model of the different inputs and outputs of chemical contaminants to tidal Chesapeake Bay.
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discharge, tides, and wind patterns. In a partially-stratified estuary (e.g., Chesapeake Bay), these
processes have been classified according to the time scale in which they occur (Itsweire and
Phillips, 1987). Seasonal physical processes are mainly determined by solar heating and
freshwater inflow, and generate a two-layer estuarine circulation (Pritchard, 1952; 1967). The
strength of stratification affects the amount of vertical mixing between bottom and surface layers.
Short-term processes can be broken down to those that are greater than a tidal period and less
than approximately a month, and those that are less than a tidal cycle. These processes include
wind forcing, tidal variations, fronts, and plumes. Shorter-term influences include turbulent mixing
that also have time scales of less than a tidal cycle. Itsweire and Phillips (1987) stated that
seasonal and some short-term mixing processes control the horizontal distribution, transport, and
diffusion of water properties, while small-scale mixing processes control vertical distributions and
exchange. The specific temporal and spatial scales ultimately will affect the mixing, transport,
potential reactions, and residence time of chemical contaminants.
Variations in water currents from tidal action can have an important effect on suspended
matter and particle-bound chemical contaminants (Officer, 1981). Short period increases in
current velocity can resuspend and transport bottom sediments to other locations, transporting
particle-bound material as well. At a site in northern Chesapeake Bay, Sanford et al. (1991)
measured near bottom increases of suspended sediments from a background of approximately 15
mg/L to 50 mg/L within an hour of the maximum tidal current. Schubel (1968) and Nichols
(1986) reported 4 to 10 time higher suspended sediment concentrations in studies of the northern
Bay area. The increase in concentration of suspended sediments and particle-reactive
contaminants during tidal as well as storm events (Sanford, 1994; Swift, 1994; preliminary results)
would increase the time chemical contaminants spent in the water column (i.e., increase residence
time) and thus would have a major role in the cycling and potential biological effects.
The transport and cycling of chemical contaminants are affected by the movement of water
and various biogeochemical reactions occurring within the estuary. Processes like river flow, tidal
and storm resuspension of bottom sediments, biological uptake and degradation help determine
the overall distribution and flux of material through an estuary. Material can be transported in
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either the dissolved or participate phases, and many interactions between these phases occur
during transport within the Bay. The mixing behavior of chemical contaminants during transport
down an estuary can be classified according to their reactivity. Chemicals that are unreactive
during transport and generally follow the distribution of non-reactive chemicals (i.e., salt) are
termed conservative, while chemicals that are removed or added to the dissolved phase during
transport are described as nonconservative (Boyle et al. 1974). Conservative mixing is indicated
by a linear distribution between the dissolved concentration of a chemical contaminant and its
corresponding salinity, while a curvi-linear relationship generally indicates either a source or sink
of material (Boyle et al. 1974; Officer, 1979; Kaul and Froelich, 1984 and others). This graphical
and computational method for assessing the mixing behavior and quantity of a dissolved species
removed or added is technically not applicable to particulate-bound contaminants as they are also
affected by resuspension and settling within the estuarine environment.
Riverwater concentration variability and hydrodynamics play a significant role in the
interpretation and modeling of property-salinity plots (Loder and Reichard, 1981; Officer and
Lynch, 1981; Cifuentes et al. 1990). An assumption in using property-salinity plots is that the
dissolved salt is mixed conservatively and that the endmember concentration, either freshwater or
saltwater, remains constant relative to the hydrodynamic residence time within the estuary. This
is not always the case, especially for freshwater concentrations. For example, Cifuentes et al.
(1990) showed that significant variations in the freshwater concentration of nitrate (at 0%o
salinity) over time can result in an apparent removal (nonconservative behavior) during transport
through the Delaware Estuary. When endmember variability was taken into account within the
modeling framework, the distribution of nitrate indicated conservative behavior. Therefore, it is
necessary that this tool for evaluating the behavior of chemical contaminants during mixing takes
into account the potential variability of chemical concentrations of both endmembers.
The importance in understanding how physical processes modify the fate, transport, and
effect of chemical contaminants is related to the movement of material and overall residence time
a contaminant resides in the waters of the Bay. The longer the residence time, the longer the
various reactions have to act on a chemical contaminant. For example, if the freshwater flow into
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the Bay is large, then a dissolved contaminant in the water would have a short residence time
within the system. With a short time period spent within the Bay waters, biogeochemical
reactions such as biological uptake/degradation and flocculation/adsorption reactions would have
less time to modify the speciation and chemical form of a contaminant. The contaminant would
then be flushed out onto the coastal shelf unaltered by estuarine processes. If the freshwater flow
into the Bay is small, the residence time of the water increases. Biogeochemical reactions could
then alter the chemical form of a contaminant, removing it to the paniculate phase with possible
subsequent settlement to the bottom, or by making it more or less bioavailable. Therefore, it is
important to understand the physical dynamics within Chesapeake Bay and their relationship to
the time (and spatial) scales of different biogeochemical reactions.
*
Geochemical Processes
As organic or inorganic particle-reactive chemical contaminants are transported down an
estuary, they can undergo several types of geochemical transformations and reactions. Many of
these processes can alter the chemical form and speciation of a contaminant, thereby affecting its
biological availability and fate. It is important to identify these processes to help determine the
type and complexity needed for a mass balance framework. In fact, many of these processes are
currently under investigation as part of the National Oceanic and Atmospheric Administration's
Chesapeake Bay Environmental Effects Toxics Program (National Oceanic and Atmospheric
Administration, 1993; 1994; 1995).
A dominant factor in the cycling of a chemical contaminant is its distribution or partitioning
between dissolved and paiticulate forms. Processes that can influence chemical contaminant
phase distribution within the estuarine environment can include: flocculation of colloidal matter,
adsorption-desorption, precipitation-dissolution, and complex formation. Many of these
processes are modified as a result of salinity, reduction-oxidation equilibria (i.e., redox), and pH
changes within the estuarine environment. Also, depending on the physical-chemical properties of
each contaminant, these processes will affect the contaminant's speciation, bioavailability, and fate
differently. However, many of these processes and changes can be predicted for specific classes
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of metals or organic contaminants using basic geochemical principles. This helps in the
development of a mass balance framework for Bay chemical contaminants.
The partitioning between the dissolved and paniculate phases of a contaminant is governed
by many of the factors listed above. Most suspended particles in the water column are negatively
charged and cationic metals are attracted to their surfaces. Many trace metals (e.g., type A metals
like chromium (Cr) and cobalt (Co)) are adsorbed onto clay surfaces through ion-exchange
reactions or onto surface hydroxides of iron or manganese (Stumm and Morgan, 1981).
Scavenging of metals is generally thought to consist of multiple steps (Jannasch et al. 1988). The
first step is the rapid uptake of metals, via exchange with protons of the hydroxyl group of oxides,
followed by a much slower step with other binding sites. Once a contaminant is participate bound
it can settle to the bottom to be buried or resuspended. One tool to describe the partitioning
between dissolved and paniculate forms of a chemical is the distribution, or partition coefficient,
defined here as Kd = C,/CW (units: L/kg), where Cp is the concentration of a specific contaminant
associated with a given mass of panicles and Cw is the concentration of the same contaminant in a
given mass of water. In theory, this empirical ratio describes the equilibrium partitioning of a
contaminant between the dissolved and paniculate phases; however, these phases are, at best,
operationally defined and are dependent on the method of filtration. Operationally, Cw includes
material that is both truly dissolved and colloidal material that can pass through a particular filter
(e.g., 0.40 um pore size filter). Also, material that is either sorbed onto the paniculate matter
during filtration or desorbed from the particles can limit the use of Kd as an accurate measure of
the partitioning between chemicals.
The use of Kd is limited by factors other than the filtration step. It is assumed that the ratio
between dissolved and particulate phases is at equilibrium (i.e., complete reversibility), and
equilibrium should remain constant over a range of environmental conditions. Depending on the
particle residence time within the estuary, kinetic effects can be very important in determining the
degree to which a chemical is dissolved or associated with the particulate phase. In other words,
if a particle is removed quickly from the surface waters to the sediments, it may not have enough
time to come into thermodynamic equilibrium with the dissolved fraction. Also, for many metals
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and organic compounds, the physical-chemical environment within the estuary is very important in
determining the degree to which a contaminant may be in the dissolved or paniculate phase (i.e.,
KJ. As a contaminant moves down the estuary it experiences variable conditions of ionic
strength, pH, particle concentration, and redox conditions. Each of these conditions can either
enhance or hinder sorption reactions and ultimately affect the bioavailability and removal of
contaminants from the water column.
Organic contaminants, many of which are hydrophobic, tend to associate or partition with
either the organic fraction on particles or with dissolved organic matter (e.g., humic or fulvic
material) (Eadie et al. 1990; 1992; Baker et al. 1991; Bergen et al. 1993; Brownwell and
Farrington, 1986). As with inorganic contaminants, the distribution coefficient can be used to
help describe the fate of organic compounds. The partitioning is related to factors such as the
structure, composition, and concentration of both the contaminant and organic matrix on the
particle surface. For example, Karickhoff et al. (1979) and others have shown that as the fraction
of organic carbon on the particle (f^) increases, K* increases. By dividing K,, by f^. the organic
carbon distribution coefficient (K^.) is obtained, and this parameter has been shown to be useful in
modeling the behavior of hydrophobic organic contaminants (Di Toro et al. 1992).
Currently, there are hundreds to thousands of organic compounds that can have some type of
environmental impact. For many modeling efforts it useful to have a K^ for each compound. To
predict the K^. values, another parameter, the octanol-water partition coefficient (K^), is needed.
The KO,, is a laboratory- or empirically-derived parameter that describes the tendency of a
compound to partition in either octanol or water, and is a measure of its lipophilicity (i.e.,
tendency to dissolve in the organic or more non-polar fraction). Generally, the higher the K^ the
more hydrophobic the compound is and the greater the association with organic carbon; hence, a
higher K^. A linear relationship has been found between K^ and K^ enabling the prediction of
the phase distribution of many compounds (Karickhoff et al. 1979). Therefore, the octanol-water
coefficient can be applied to predict the partitioning behavior of organic contaminants in an
estuary.
The impact of dissolved organic matter (DOM) on the fate and effect of organic compounds
8
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and trace metals is also very important. A general observation is that dissolved organic matter
enhances the solubility of many organic contaminants to some degree. However, differences can
arise depending on the type of the DOM. Eadie et al. (1990; 1992) showed that specific organic
contaminants were not significantly bound to DOM derived from the Great Lakes. Boehm and
Quinn (1973) showed a reduction in the solubility of n-alkanes when riverine and estuarine DOM
were removed, but no change in solubility with the polycyclic aromatic hydrocarbons (PAHs)
phenanthrene and anthracene. However, the binding and solubility is most likely contingent on
the structure, composition, and concentration of DOM and the type of contaminant. The
solubility of specific aromatic hydrocarbons was significantly influenced by the presence of
naturally occurring DOM from terrestrial sources with little or no influence using DOM from
oceanic or coastal sources (Whitehouse, 1985). However, the data from Whitehouse (1985) also
showed that solubility enhancements were compound specific, with higher molecular weight
PAHs (e.g., benzo[a]pyrene) more soluble in marine DOM. Variations in the composition
between marine and terrestrial DOM could therefore have an important role in these results.
Terrestrial humic material are derived from lignin whereas marine humics are derived from
phytoplankton. Marine humics are thought to be less aromatic and more aliphatic in composition,
with a greater protein and carbohydrates character (Stuermer and Payne, 1976; Harvey et al.
1983). The modification of humic substances as river water mixes with seawater in the estuary
would most likely have a large role in the fate of contaminants (Fox, 1983; Sholkovitz, 1976).
This is especially true for contaminants that are introduced in the upper tributaries (near urban
centers) where the initial mixing of terrestrial, estuarine, and marine humics occurs.
Organic complex formation can also have an important role in the speciation and
bioavailability of many trace metals. Many metals like, lead (Pb), copper (£u), and mercury (Hg)
(e.g., type B metals) are biologically active and tend to associate with organic matter (Stumm and
Morgan, 1981). Organic-metal complex formation can either increase or decrease the adsorption
of metals onto particles. For example, recent studies by Godtfredsen and Stone (1994) showed
that copper bound to manganese (HI, IV) oxides can be released and complexed by the addition
of specific organic compounds and extracted natural organic matter. The extent of complex
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formation of metals by DOM (e.g., humic and fulvic acids) is dependent on the concentration of
DOM and the competition for available sites within the humic matrix between metals and major
cations (Reuter and Perdue, 1977). Mantoura et al. (1978) suggested that the stability of organic-
metal complexes follow the Irving-Williams order of stabilities of chelates with metal ions. This
sequence indicates that Cu and Hg should form the strongest complexes. In this regard, many
researchers have shown that organic complexes control the speciation of Cu in estuarine waters.
Preliminary studies by Donat (1995; preliminary results) in Chesapeake Bay suggest that over
90% of the dissolved Cu is complexed to dissolved organic matter and that at least two types of
organic ligands (i.e., a strong and weak fraction) are present. Similarly, the organic forms of
dissolved cadmium (Cd), which is low on the Irving-Williams order, accounted for between 25%
and 70% of the total dissolved Cd (Donat, 1995; preliminary results). His results indicate only
one major ligand class was involved with Cd complex formation. The importance of organic-
metal complex formation is that these complexes can be a dominant form of many metals affecting
their geochemistry and biological availability in the estuary.
For many organic contaminants such as polychlorinated biphenyls (PCBs) and polycyclic
aromatic hydrocarbons, air-water exchange (i.e., evaporation or volatilization) is an important
environmental pathway that cannot be ignored in a mass balance of Chesapeake Bay. The
exchange of a chemical across the air-water interface results from the transport of a particular
chemical to the interface from the bulk phase (either water or air) linked with its transport across
a water and air stagnant film (i.e., the stagnant film model; Liss and Slater, 1974). Generally, the
less soluble compounds with higher vapor pressure will have a greater tendency to be in the gas
phase than compounds that are more soluble (Mackay, 1991). The rate of transfer is related to
the compound of interest (i.e., its Henry's Law constant) and a combination of the liquid and gas
phase resistance (Liss and Slater, 1994; Mackay, 1991). For compounds that are very insoluble
with large Henry's Law constants the mass transfer is primarily related with the liquid film.
Environmental conditions such as wind speed and temperature also need to be taken into account
in a modeling exercise. Eisenreich (1987) and more recently Achman et al. (1992) showed that
volatilization is an important factor controlling the fate of PCBs in the Green Bay (Lake
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Michigan). For example, Jeremiason et al. (1994) calculated that volatilization, not
sedimentation, was the dominant loss mechanism for PCBs from the waters of Lake Superior.
Preliminary work by Dickhut et al. (1994) and Baker et al. (1994) indicates that this process can
be very important in the cycling and fate of both PCBs and PAHs in Chesapeake Bay and its
tributaries.
While volatilization would have little effect on the fate of most trace metals (e.g., Cu, Cd, or
Zn), it can be extremely important for metals or metalloids that have volatile organic forms such
as mercury (e.g., CH3Hg) or selenium (e.g., (Cl^Se). This is also true for elemental Hg (Hg°),
where air-water exchange can be an important sink or source for lakes (Fitzgerald et al. 1991;
Amyot et al. 1994) and estuaries (Mason et al. 1993).
Biological Processes
Biological activity within an estuary can have a large effect on the chemical speciation, phase
distribution, and overall fate of many contaminants, both trace metals and organic compounds.
Many trace metals, for example, are required elements for cellular metabolism (Lehninger, 1975).
Metals such as iron (Fe), manganese (Mn), zinc (Zn), Cu, and cobalt (Co) are incorporated into
specific organic molecules, such as chlorophyll and enzyme co-factors which enter into specific
photosynthetic reactions. Cobalt, for example, is the central metal atom in the core of vitamin B12
which is a growth factor for many aquatic plants (Raymount, 1980). Many organic compounds
(e.g., PCBs, DDTs, atrazine, and certain aromatic hydrocarbons) are anthropogenic and are not
needed for plant or animal growth. While many metals can be essential to life, most are toxic at
sufficiently high concentrations and for some there is a narrow concentration range between what
is required for growth and what is toxic.
Uptake of trace metals into plant or animal tissue can occur via both passive or active
mechanisms via solution, food, and sediment sources (Luoma, 1983). Some metals can be taken
up and used in cellular growth, biochemically altered to lesser or greater toxic forms (e.g.,
detoxification via metallothionein; Couillard et al. 1993), or can cause deleterious effects to
cellular growth. A major factor that affects the uptake and cellular incorporation of trace metals
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or metalloids (i.e., bioavailability) is the element's chemical form or speciation (i.e., oxidation
state). Factors that can affect the speciation of trace metals include salinity, inorganic and organic
complexation, reduction-oxidation potential, and pH. For many metals, it is the free metal ion
concentration or activity (Sunda and Guillard, 1976; Morel and Hering, 1993; Riedel and Sanders,
1988; Newman and Jagoe, 1994) and the amount of metal bound within the organic matrix (i.e.,
cytoplasm) of a cell (Luoma et al. 1992; Reinfelder and Fisher, 1994) that plays a major role in
bioavailability and trophic transfer, respectively. Recently, Phinney and Bruland (1994) showed
that low molecular weight, lipophilic organic Cu, Cd, and Pb complexes enter diatom cells (e.g.,
Thalassiosira sp.) by diffusion across the plasma membrane. Once inside the cell, the metals in
these complexes can become biologically available by binding with internal binding sites via
intercellular ligands. This passive mechanism acts in parallel to active transport of free metal ions.
Other metals such as mercury (Hg) and tin (Sn) form lipophilic organo-metallic complexes (e.g.,
methyl-Hg) that can accumulate in the food chain due to their greater lipid solubility (i.e.,
bioaccumulation).
Biological processes that affect organic contaminants include uptake (both passive and
active), trophic transfers, and microbial degradation (Hale and Huggett, 1988). Thousands of
anthropogenic organic compounds can be transported to and through the estuary. These include
organic contaminants that have low water solubilities and high octanol-water partition coefficients
(e.g., log K^ 2 3 compounds such as polychlorinated biphenyls) as well as many compounds with
high water solubilities (e.g., triazines). Many of the former compounds partition to the organic
fraction of particles and are transported with suspended matter or deposited to the sediments.
Organic contaminants, like polychlorinated biphenyls (PCBs), can be taken up passively by
phytoplankton via a two-step mechanism involving an initial surface adsorption phase then
transfer through the lipid bilayer (Swackhamer and Skoglund, 1991). At slow growth rates, the
. log K^, predicted the accumulation of lower molecular weight PCB into the phytoplankton cell,
whereas higher molecular weight compounds did not show a consistent relationship. Steric
hindrances slowed the transport of larger higher molecular weight compounds across the cell's
membrane and could account for the observed results (Stange and Swackhamer, 1994;
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Skoglund and Swackhamer, 1994).
Uptake of organic compounds by phytoplankton is an initial step in the bio-transfer of
contaminants through the estuarine food web. Up the food chain, these contaminants tend to
partition into the lipid fraction of organisms depending on factors such as the concentration of
dissolved organic carbon of the water (which affects bioavailability), the lipophilicity of the
compound, the size and shape of the compound (i.e., cell membrane effects), and the lipid content
of the organism (Knezovich, 1994; Landrum et al. 19S5). Many of these compounds can also be
degraded via chemical and biological mechanisms. Chemical degradation reaction processes
include photochemical degradation, reduction-oxidation (redox) reactions, and hydrolysis.
Hydrolysis reactions affect mainly esters, carboxylic acids or amides, while redox reactions
include, as an example, the reductive dehalogenation of DDT to DDD via electron transfer from
the bacterial oxidation of organic matter and iron reduction (Zoro et al. 1974; Kobayashi and
Rittmann, 1982). Photodegradation is a very important abiotic process that can affect the
concentration and forms of many organic contaminants. The suspended sediment concentration,
amount of humic substances in the water, and the water-solid partitioning are important factors in
the photodegradation of many compounds.
Biodegradation is one of the more important processes affecting the fate of petroleum
hydrocarbons in the marine environment (Gibson, 1977; Gerlach, 1981; Lee and Ryan, 1983;
DeLaune et al. 1990 and others). Degradation rates can vary depending on whether the
compound is an aliphatic or aromatic hydrocarbon and its specific structure (i.e., length of chain,
number of branches, number of aromatic ring groups) (Gerlach, 1981; Wild and Jones, 1993).
DeLaune et al. (1980) showed that specific sediment characteristics (e.g., pH, pE, temperature)
were important factors in the activity of hydrocarbon degrading microorganisms. Also, aromatic
hydrocarbon biodegradation is enhanced in sediments that have been previously contaminated
with hydrocarbons, implying that there is an adapted population of microorganisms that can
degrade aromatic hydrocarbons.
Recently, there have been numerous studies on the biological degradation of PCBs and other
halogenated organic compounds. DeLaune et al. (1990) reviewed some aspects of biodegradation
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and stated that most organic contaminants degrade faster under aerobic conditions. However, for
compounds like DDT and PCBs, anaerobic reductive dechlorination is an important
transformation process. Studies of the anaerobic degradation of PCBs in non-marine systems
have shown extensive dehalogenation, mainly on the non-ortho substituted chlorines (Sokol et al.
1994; Rhee et al. 1993; Abramowicz et al. 1993). However, under marine conditions, with
abundant sulfate, reductive dechlorination of PCBs was shown not to occur (Alder et al. 1993).
It may be that the presence of sulfate could inhibit the dechlorination process, however, microbial
dechlorination of chlorophenols has been linked to bacterial sulfate reduction in marine systems.
Capone et al. (1994; 1995; preliminary results) showed that 2,4 - dichlorophenol was degraded in
sediments from the middle portion of the Chesapeake Bay. Alder et al. (1993) showed reductive
dechlorination of PCBs in methanogenic sediments (i.e., no sulfate present) from New Bedford
Harbor with no degradation under sulfate reducing conditions. However, Ofjord et al. (1994)
showed that anaerobic dechlorination of PCBs did occur in both the presence and absence of
sulfate, although specific rates were not presented.
The loss of many organic contaminants can be mediated by microbial processes within the
water column and, more importantly, the sediments. In many cases, the degradation products
have less biological activity than the parent compound, but in some cases (e.g., DDT) the
daughter compound is more biologically active (i.e., DDE). However, if an accurate accounting
of the fate of organic contaminants is needed within the Bay, an understanding of both chemical
and biological degradation is needed.
Physical and Biogeochemical Processing of Contaminants within the Bay
Contaminants can be retained in the system by many processes as well as be degraded to non-
toxic or even more toxic chemicals with time. Depending on the reactivity of a particular
contaminant (i.e., reaction half life) and the hydrodynamic residence time, a contaminant can also
be washed out of the estuary unaltered. Sharp et al. (1984) defined two zones, or filters, in an
estuary that can affect the fate of material. During estuarine transport geochemical and biological
reactions can remove material from the water column and these "filters" can be located in different
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regions of the Bay system. For example, geochemical filtering would occur in the areas of the
Bay where suspended paniculate concentrations are highest as there would be more sites for
dissolved-particle reactions and removal. Biological removal and transformations would be
located in areas of the Bay where turbidity is lower and greater microbial production (i.e., both
phytoplankton and bacteria) occurs due to increased light levels.
Many processes remove contaminants from the water column to the sediments only for a
certain time period before they are re-introduced back into the system. Therefore, the distinction
between permanent removal and temporary storage should be made. For example, particle-
reactive contaminants can be removed from the water column via sedimentation. A portion of the
sediment with bound contaminants may be carried upstream due to net upstream transport in the
bottom waters. However, many physical processes and geochemical reactions at the sediment-
water interface can re-introduce these contaminants back into the water column over various time
scales. Sediments and bound contaminants can be resuspended into the benthic boundary layer or
higher up in the water column by tidal and storm currents (Sanford et al. 1992; Sanford and
Halka, 1995; preliminary results). A portion of the suspended material will re-settle to the bottom
while the remainder may be carried upstream due to density-driven estuarine circulation.
Diagenetically controlled reactions can also mobilize or release particle-bound contaminants to the
pore waters where advection and diffusion processes can exchange these chemicals back into the
overlying water (Riedel et al. 1995; Cornwell et al. 1995; preliminary results). In addition,
benthic organisms can facilitate the exchange of contaminants between the benthos and overlying
water (Schaflher and Dickhut, 1995; preliminary results), for both dissolved and paniculate forms.
Only after a sufficient amount of time will contaminants be buried permanently within the
sediments. Also, during these exchange processes the form and speciation of contaminants can be
altered to either to a lesser or greater bioavailable form, thereby changing their overall effect to
the Bay's living resources.
For many contaminants, the air-water interface is equally important compared to the
sediment-water interface, and plays a major role in the fate and cycling of contaminants. In fact,
the surface area of the Bay in contact with the atmosphere is relatively similar to that in contact
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with the sediments. Given the physical mixing behavior of the Bay, there is most likely a short
transit time between chemical contaminants entering the Bay from the atmosphere and removal to
the bottom sediments. As discussed previously, atmospheric deposition can be an important
source of contaminants to the Bay. Also, the volatilization of many organic compounds from the
water to the atmosphere can be an important loss term from the estuary. This exchange of
material needs to be quantified in order to determine the net input (or output) of contaminants
from Chesapeake Bay.
The construction of a mass balance needs to account for the various fluxes between the
different interfaces within the Bay, including the air-water, Bay-ocean, and sediment-water
interfaces. Other sources and sinks would be combined with this information to provide an
indication of the relative magnitude of the Bay's various inputs and outputs and overall fate of
chemical contaminants. Understanding how similar classes of chemicals cycle through the Bay is
also needed to help make predictions concerning the fate of specific chemicals that may be too
costly to investigate.
Mass Balance Development for Chesapeake Bay
A mass balance model is defined here as an equation that describes a process where matter
entering a system, minus matter leaving the system, equals matter stored, transformed, or
degraded within the system. In this regard, a mass balance model establishes a process for
identifying and consistently evaluating all ways that chemical contaminants can enter and exit a
waterbody such as Chesapeake Bay. With a clear understanding of all inputs and outputs of a
given pollutant it is then possible to understand the relative importance of the various human-
influenced sources. At this point, Bay managers can focus on the source(s) with the largest
influence (by mass and bioavailability) to reduce the load (and effects) within a waterbody.
Overall, a mass balance can be a predictive tool that allows informal prioritization and allocation
of directed and basic research, remedial actions, and regulatory efforts for water quality
management.
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Modeling Framework
The development of a Bay mass balance for contaminants involves five steps. These steps
include: 1) the identification and prioritization of specific mass balance objectives, 2) the
identification of the important compartments within the Bay system, 3) the identification and
quantification of inputs to the various identified compartments, 4) the identification and
quantification of outputs from various compartments, and 5) the rates of transfer between the
interfaces of compartments. Inherent in the development of a Bay mass balance is the acquisition
of monitoring and research data and information. Therefore, an overriding area for a Bay mass
balance is proper data handling and quality assurance/control of individual programs to ensure
that data can be compared within and across media (i.e., air, water, sediments, and biota).
A mass balance model for the Bay can be constructed at different levels of complexity
depending on the objectives of the study. The complexity of a model would also rely on the
amount and quality of data available to run and validate the computations as well as the financial
resources available to complete the study. However, a simple preliminary model can be
developed, using existing data, to help point out data gaps and provide a rough idea of the relative
inputs, outputs, and compartment residence times within the Bay. Objectives of such a mass
balance study could include: 1) validation of the loading estimates, 2) calculation of the residence
time of contaminants within a compartment, 3) determination of the fate of contaminants, and 4)
would allow Bay managers to predict and evaluate the impact of specific management decisions
on the levels of chemical contaminants in different compartments. Further development of a Bay
mass balance, with additional compartments and interfacial transfers, can be accomplished as
objectives are modified and the necessary data requirements are met. A more complex model,
however, demands an increase in financial commitment. This involves not only possible computer
time to run the model, but monies for the collection of data to feed into the computational
framework. Furthermore, the development of a Bay mass balance should not be intended for
every possible chemical contaminant measured in one or more of the Bay's different compartments
(e.g., sediment, water, and biota). A few chemicals, which are representative of major classes of
chemical, should be focused on for initial model development. These chemicals could include
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select trace metals such as lead (Pb), copper (Cu), and arsenic (As), and organic contaminants like
polychlorinated biphenyls (PCBs) or polycyclic aromatic hydrocarbons (PAHs). These elements
and groups of compounds span a wide range of physical-chemical properties and biogeochemical
reactivity, would help to illustrate some of the processes controlling the fate of contaminants
within the Bay. Most importantly, an accurate and reliable base data source needs to be
developed that allows inter- and intra- comparisons between concentrations and fluxes with the
model.
Compartments of Chemical Contaminants in Chesapeake Bay
The development of an accurate understanding of the various inputs and outputs (i.e., mass
balance) to a system first entails the selection of the relevant and important compartments (i.e.,
boxes) and transfers (i.e., fluxes) of contaminants between compartments. In other words, a
simple mass balance model consists of well-mixed boxes connected to their environments by
various exchange processes (e.g., advective and diffusive transport, particle settling, biological
uptake to name a few). Most often these compartments are determined by the various physical-
geochemical interfaces in an estuary such as the air-water, sediment-water, river-Bay-ocean, and
land-water boundaries. For the Chesapeake Bay system, examples of the different compartments,
or boxes, include the bottom sediments, Bay water, atmosphere, above the fall-line watershed,
and the ocean. In some instances, a compartment may appear to be similar chemically (e.g., water
column and bottom sediments), but can be further separated due to physical (e.g., density
differences between surface water and deep water) or geochemical variations (e.g., oxic surface
sediments versus anoxic bottom sediments) into additional compartments. The selection of
compartments should be made to best meet the objectives of the study while still keeping
geochemical relevance to the system.
A number of different physical compartments or boxes can be identified for Chesapeake Bay.
As a starting point, three main compartments or boxes can be identified: the atmosphere above the
water surface, the water column, and the sediments. This simple division can be further
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Table 1. Potential compartments for the development of a Bay mass balance.
Major Compartments Sub-compartments1
Atmosphere2
Water column3
Sediment4
Ocean1
Groundwater2
Surface boundary layer (0 to -30 m)
Top of troposphere (> -30 m)
Surface water (0 to 10 m)
Bottom waters (> 10 m)
Biogeochemical active zone (0 to. 10 cm)
Burial zone (> 10 cm)
Surface water (0 to 10 m)
Bottom water (> 10 m)
Sub-surface aquifer (0 to 100 m)
Deeper aquifer (> 100 m)
'Sub-compartment depth ranges are for illustrative purposes only. 2z is negative
upwards from the air-water interface.3 z is positive downward from the air-water
interface.4 z is positive downward from the sediment-water interface.
sub-divided into additional compartments, if necessary (Table 1). These compartments may be
sufficient for fate and transport studies and simple residence time calculations, but depending on
the specific objectives of the study the number of sub-compartments with each box (e.g., water,
sediments, air) can be quite different. For example, if a goal is to understand the bioaccumulation
of contaminants in fish or benthic organisms, it is important to further subdivide the water
compartment to include dissolved and paniculate fractions. Only specific sub-fractions of the
dissolved and paniculate phases are bioavailable for uptake by organisms and must be taken into
account. Dependent on the objectives of the project, the relevant compartments need to be
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selected, the specificity of the chemical and biological analyses within each compartment will have
a direct effect on the cost for the program.
Transport Processes of Chemical Contaminants to Chesapeake Bay
Many important transport vectors or sources can bring chemical contaminants into tidal Bay
waters (Figure 1). These inputs of contaminants include: point sources, urban and agricultural
runoff (i.e., non-point sources), direct spills, atmospheric deposition, river transport, groundwater
flow, and ocean-Bay exchange. While some of these transport mechanisms for certain metals and
some organic compounds are part of background geochemical cycles within coastal areas (e.g.,
atmospheric deposition and river transport), all have been impacted to some degree by the
influence of human activities. For example, major ions and trace metals entering the Bay via river
transport are derived from atmospheric deposition and the physical and chemical weathering
within the watershed of the Bay (Troup and Bricker; 1975; Correll et al. 1981; Katz et al. 1985).
These inputs have been occurring since the Bays geologic formation. Added to this source are
point (e.g., municipal and industrial) and nonpoint (e.g., agricultural and urban runoff) sources
within the watershed. Also, due to near- and far-field atmospheric transport mechanisms,
atmospheric deposition may contain substantial amounts of anthropogenically-derived metals and
organic compounds (Baker et al. 1994). At present, it is difficult to determine how much of a
particular metal is derived from weathering processes or human activities in river transport or
other sources, although attempts have been made (see for example, Helz et al. 1985; Windom et
al. 1991). For specific organic chemicals tike polychlorinated biphenyls, atrazine, or DDTs,
however, all sources are anthropogenic as these chemicals are not produced naturally.
Listed in Table 2 are many of the transport processes of natural and anthropogenic chemicals
to Chesapeake Bay waters. Also, listed are many of the different removal mechanisms and
biogeochemical reactions that need to be understood. Most of these processes are difficult and
costly to quantify. An initial attempt to quantify the transport mechanisms of chemical
contaminants to the tidal Bay's waters was made by the Chesapeake Bay Program (1994a). While
there were many problems with this study, it does provide an understanding of the complexity of
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trying to quantify a diverse range of sources with data that were not necessarily collected for
source/loading information.
Along with the selection of various compartments and loadings information, the various
pathways and processes that can affect the mass transport between or within compartments need
to be identified. The various inputs, outputs, and processes that have been shown to occur or
could occur in the Bay system are listed in Table 2 and shown in Figure 1. The pathways listed in
Table 2 may not always be uni-directional in the movement of contaminants from one
compartment to another. For example, tidal exchange may transport material from the ocean to
Table 2. Potential sources, sinks, and processes of chemical contaminants in tidal Chesapeake Bay
waters.
Inputs
Outputs
Processes
River transport1
Atmospheric deposition2
Point Sources (i.e., pipes)3
Urban runoff
Agricultural runoff
Shoreline erosion
Boating activities
Oil spills
Groundwater
Ocean-bay exchange
Sediment-water exchange
Fish Migration
Sedimentation4
Burial5
Volatilization
Biotic degradation
Abiotic degradation
Ocean-bay exchange
Sediment-water exchange
Fish Migration
Fish/Shellfish harvest
Adsorption-desorption
Precipitation
Solubilization
Complexation
Flocculation
Volatilization
Resuspension
Biotic uptake/transformation
Biotic/Abiotic degradation
'River transport contains most sources above the fall line.
2 Both wet and dry deposition.
3 Municipal and industrial sources.
^Non-permanent removal of contaminant from the water column.
5"Permanent" removal of contaminant from water column.
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the Bay as well as from the Bay to the ocean. The net exchange rate is related to many factors
including the concentration difference between compartments and water exchange rate at the
ocean-estuary interface.
Another important bi-directional exchange is at the air-sea interface. The flux of organic
compounds and trace metals to land and water surfaces can be accomplished by wet (i.e.,water)
and dry (i.e., aerosol) deposition (Whitehead and Feth, 1964) as well as gas exchange (Atlas and
Giarn, 1986; Duce et al. 1991). The return flux of material from the water to the atmosphere can
also occur from processes such as bubble ejection of water and particles, and volatilization of
gaseous material from the water surface (e.g., Hg and PCBs) (see Baker et al. 1993 for a review).
Recent work by Achman et al. (1992) has shown that the volatilization of hydrophobic organic
compounds, such as PCBs, is an important removal mechanism from the waters of Green Bay in
Lake Michigan. Volatilization of organic material such as PCBs can also occur from land surfaces
as well. It is estimated that a substantial portion of the total PCB burden in southern England
soils has been lost via volatilization and long range transport (Alcock et al. 1995). The loss and
eventual transport of the PCB could then affect more remote areas (U.S. EPA, 1994).
The exchange at the sediment-water interface can be an important process controlling the fate
of contaminants in Chesapeake Bay. Deposition of particle-bound contaminants to the sediments
may temporally retain many contaminants. Certain trace metals and organic compounds can be
remobilized into the porewaters of the sediments creating concentration gradients that allow the
flux of dissolved contaminants from the sediments to the overlying water. This process has been
shown to be very important in the cycling of nitrogen in Chesapeake Bay (Kemp and Boynton,
1992) and can be equally important in the cycling of contaminants (Riedel et al. 1987; 1995;
preliminary results; Cornwell et al. 1995; preliminary results). These processes are generally
controlled by the oxidation-reduction state of sediments and have recently been shown to be
affected by the presence of benthic organisms (Riedel et al. 1987; 1995; preliminary results;
Schafiher and Dickhut, 1995; preliminary results).
Major assumptions in mass balance modeling are that each compartment is well-mixed and all
inputs and outputs are accounted for within the modeling framework. Conceptually, the variation
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in the concentration (C) of a contaminant over time in a well-mixed box of constant volume (V)
can be described as:
VdC/dt = QCin-QCout-R (1)
The terms on the right side of equation (1) include the total input (QQ,), output (QC^J and loss
or reaction (R) within a box, compartment, or system. In many simple cases, the reactions within
a compartment are described as first-order with respect to the concentration (i.e., kC; where k is
the first-order rate constant). If there is no change in the storage of a contaminant within each
box or compartment and the concentration remains unchanged, then the system is at steady-state.
For a first-level preliminary model however, steady-state conditions should be assumed.
Steady-state assumptions mean that the concentration and amount within each box or
compartment remains the same (i.e., V dc/dt = 0) over the time scale in question and that the sum
of all inputs to the tidal Bay ([SQ^Cd; where i is the identified sources) are equal to the sum of
the loss terms ([SQ^C^j; where j are the identified outputs). The use of a steady state system is
dependent on the spatial and temporal resolution of the model's output, which is related to the
objectives of the study. While steady state assumptions allow easier mathematical formulation
and calculations, they may not always be true.
Many assumptions underlie the use of mass balances in describing systems like Chesapeake
Bay. Some are related to the scale, both temporal and spatial, chosen for the formulation (see
Thomann, 1995). For example, in estuaries large concentration gradients exist within the water
and sediment structure for many contaminants. Also, many biogeochemical processes are
seasonal in nature due to their temperature dependence (e.g., microbial processes). For example,
the flux of specific trace elements from the water column into the biogeochemically active zone of
the sediments can be related to the oxygen concentrations within the sediments and overlying
water (Riedel et al. 1995; preliminary results), which can vary substantially in the Bay on time
scales of hours to months (Cutter et al. 1985; Sanford et al. 1990; Diaz et al. 1992). These types
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of processes can yield non-steady state conditions related to the time scale that is to be
represented by the model.
One aspect of any model formulation that needs to be considered is the scale (i.e., spatial and
temporal) required to meet the objectives and goals. The resolution of the model can be on length
scales of the entire Bay or specific tributaries over time scales of monthly to decadal changes.
Also, the scaling size of the various compartments will affect the model's output and data needs.
As a guide to how the Bay system responds and the relevant time scales that should be used in
data acquisition, the recent sediment core work by Owens and Comwell (1995) and Baker et al.
(unpublished data, see Chesapeake Bay Program, 1994d) provides some interesting information.
Their work showed substantial decreases in sediment concentrations of various contaminants over
the previous 10 to 30 years. The resolution of their data is on the order of 2 to 5 years using 210Pb
dating and suggests that loadings data encompassing the last five years is needed for an accurate
and relevant mass balance.
Other scaling problems that need to be addressed include the use of a few measurements in a
specific area of the Bay which are then applied or scaled up to the entire Bay water surface or
watershed. For example, the few benthic flux studies done in the Bay for contaminants are
generally located in a few areas (Riedel et al. 1995; preliminary results; Cornwell et al. 1995;
preliminary results). The fluxes determined from these studies may not be characteristic of the
entire Bay and will bias the overall flux given the different sediment types in the region (Hobbs,
1983; Hennessee et al. 1986; Kerhin et al. 1983; 1988). This problem (i.e., a few measurements
applied to the entire Bay) for many flux studies (e.g., benthic, air-sea, water fluxes) will hinder the
accuracy of any model. Also, the impact of storm events have only been partially studied for
some inputs. Only with a concerted effort (i.e., money) will more measurements be made to help
increase a Bay mass balance model's accuracy. However, in the initial modeling framework and
data input, the areas of greatest data needs can be pointed out so that the limited resources can be
focused properly and scientifically.
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Summary
Conceptual mass balance models are excellent tools to assess the dynamic behavior of
contaminants in Chesapeake Bay. These models combine system-specific processes with
properties of individual chemicals or classes of chemicals under investigation. Once in place they
help to predict concentrations resulting from different loading scenarios and can help understand
various impacts to living resources (see Chesapeake Bay Program, 1994b). Also, when model
results are compared to field data they can provide insights into unrecognized sources or
processes.
While mass balance modeling has been successfully applied to nitrogen and phosphorus
cycling in the Bay (see Chesapeake Bay Program, 1994b; Boynton et al. 1995), the sources,
pathways, and sinks for chemical contaminants are less well understood. A graphic description of
a representative model for Chesapeake Bay is presented in Figure 2. This framework includes a
food chain compartment to allow estimation of bioaccumulation for various living resources of the
Bay. Again, many of the processes, pathways, and transfer rates are not known for the Bay's
ecosystem and would hinder the development of this type of mass balance. It is, therefore,
necessary to focus the mass balance approach in two directions.
First, a pilot mass balance which includes a food chain component (Figure 2) could be started
in a smaller ecosystem of the Bay prior to expansion to the whole Bay. The selection of a specific
area would be determined on the amount and availability of high quality data and the need of
mangers to have specific questions answered concerning specific pollution control strategies that
may be implemented in an area. The integrated model will then be used to predict concentrations
in the various media in response to different management control actions. Second, a lower tiered
level mass balance (i.e., input-output balance) could be constructed for the whole Bay following
the outline described in Figure 1. This type of model would determine the major inputs and
outputs of contaminants to and from the Bay. A subset of the processes listed in Table 2 could be
quantified using best available data; and if the resources are available, projects could be initiated
to help fill in specific gaps.
The models shown in Figures 1 and 2 serve as an outline of the compartments and processes
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Atmosphere
Ataraphtric DcpodUon
Point and NMpotat InpuU
VoliUlluUofi
Water
Adwrption/DMorptlon
Dtfnditlon
AtraMphtrlcDcpotlUou
Suspended Particles
Eiport to Occtn
Bfoaccumulilfon
Food Chain ' o«conipoiiuon
Landward Tnniport
Surface Sediment
AdwrpUon/Dewrptlon
Deep Sediment
Adwrptlon/Dciorptlon
Burtal
Figure 2. Graphic description of a mass balance showing major processes and pathways for Chesapeake Bay
26
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that should be included in a contaminant mass balance for Chesapeake Bay. This particular model
is not inclusive of all possible processes and serves only as a starting point. One of the important
aspects of this framework is the accurate quantification of the sources of contaminants to the tidal
Bay. Inherent in this exercise is an understanding of the limitations and uncertainties in the
quantification of the various sources. The recently published Chesapeake BayBasimvide Toxics
Loading and Release Inventory (Chesapeake Bay Program, 1994a) is the second comprehensive
attempt in determining the loadings to the Bay. It is substantially more accurate and inclusive
then previous loading estimates (Chesapeake Bay Program, 1982). As a first-order approach, a
mass balance helps to serve as a check on the accuracy of the identified inputs and outputs used in
the mass balance. The model can then help to point out areas in need of better and more data or
additional compartments and sources that need to be included within the framework. In other
words, the construction of a simplified mass balance helps to put loadings information into a
realistic perspective, and provides a focus for future research projects (Chesapeake Bay Program,
1994a).
, LOADING ESTIMATES TO TIDAL CHESAPEAKE BAY: A SUMMARY
The calculation of input fluxes to Chesapeake Bay is a complex task. Problems inherent in these
types of calculations include: 1) a general lack of data, 2) comparability of chemical
measurements and forms for each source category, and 3) incomplete reporting of the various
sources. In many cases, the reporting programs in which data were collected were not set up with
the objective of calculating a load or flux, but rather for assessing the potential biological effects
via comparison with numerical water quality standards. Despite these limitations, initial load
estimates need to be established to assess the relative magnitude of point and non-point inputs and
where data needs are greatest to improve future load estimates.
Inputs that were quantified include point sources (municipal and industrial), non-point sources
(shoreline erosion and urban runoff), river transport, and atmospheric deposition. Sources of
contaminants from spills and coastal ocean-bay exchange were not quantified, although they
should not be overlooked in future budgets All estimates include only those below the fall-line
27
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(BFL) from Maryland, Virginia, and the District of Columbia. Also, these estimates are
considered edge-of-field loads in that they do not consider fate and transport processes that would
modify the actual input of a contaminant to a specific point within the tidal Bay. Data for these
loading calculations were obtained from the Chesapeake Bay Toxics Loading and Release
Inventory which included information from the Chesapeake Bay Fall-line Monitoring Program,
Chesapeake Bay Atmospheric Deposition Program, and various published and unpublished
reports (Chesapeake Bay Program, 1994a,c).
Comparison of the Various Fluxes to the Bay
The loads from the various sources to the entire tidal Bay are compared in Table 3. The
ranges presented for atmospheric deposition, river transport, urban runoff, and shoreline erosion
were not calculated similarly, and may be based upon as little as two estimates (Chesapeake Bay
Program, 1994a; Velinsky, unpublished data). Point sources are presented as a single point, and
may vary by a factor of 30 (Chesapeake Bay Program, 1994a; Warner et al. 1992).
Unfortunately, organic data for the various sources are lacking, as there is not a coherent program
to measure these parameters, except for the atmospheric and river monitoring studies.
For copper, zinc, and chromium, river transport fluxes are substantially higher than other
sources (Table 3). The second largest source of trace metals to the tidal Bay appears to be urban
runoff. This is especially true for the flux of cadmium and lead, in which urban runoff is up to 6
to 30 times higher than the other sources. However, the range of estimates for urban runoff is
large, and should be an area of future study to help constrain these values. Shoreline erosion,
along with river transport, appear to be important sources of chromium and zinc, most likely due
to their crustal abundance compared to the other metals. While the fluxes for rivers, urban runoff,
shoreline erosion, and point sources appear to be higher or of similar magnitude to atmospheric
inputs, the location of these inputs (i.e., along the coast or in specific tributaries) is markedly
different than atmospheric deposition which is distributed directly to the surface water of the Bay.
Each source, regardless of its overall magnitude however, may have a substantial biological effect
in the "local" area (i.e., tributaries).
28
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Generally, there is a lack of adequate data for the quantification of the inputs of most organic
contaminants. The river transport flux for total PCBs is approximately ten times greater than
atmospheric deposition (Table 3). Unfortunately, there are no data for the other possible sources
of these chemicals to the Bay. Urban runoff is the dominant source of the aromatic hydrocarbons,
chrysene and benzo[a]pyrene, to the Bay. While there is no estimate of the uncertainty or range
Table 3. Summary of contaminant loads to the entire tidal waters of Chesapeake Bay.
Chemical
Metals
Cadmium
Chromium
Copper
Lead
Zinc
Organics
Benzo[a]pyrene
Chrysene
Total PCBs
Atmospheric
Deposition
1.3-
2.2-
11-
9.5-
31-
0.054-
0.093 -
0.030 -
1.6
4.2
15
15
52
0.13
0.19
0.039
Urban
Runoff
0.95 - 5.3
5.4 - 30
15-84
190 - 360
84 - 460
0.094
0.24
ND
River
Transport
37-
200-
270-
310-
130-
0.19-
71
270
450
410
220
0.36
ND
0.37-
0.38
Shoreline
Erosion
1.0 - 1.9
83-90
28-29
27-28
96 - 120
ND
ND
ND
Point
Sources
0.62
19
37
5.3
160
0.044
0.007
ND
Loads are in metric tons per yr. Adapted from Chesapeake Bay Program (1994a), Baker et al.
(1994), and Velinsky (1994). ND - No Data.
in these fluxes, which may be substantial, studies from other areas (National Academy of
Sciences, 1975; Hoffman et al. 1983; 1984) also indicate that urban runoff is a significant source
of petroleum hydrocarbons to coastal urban areas. For both chrysene and benzo[a]pyrene,
atmospheric deposition is a slightly greater source to the tidal portion of the Bay than point
sources. However, the data available to determine the point source load are very limited and the
rates presented are most likely an underestimation of the "true" loadings.
29
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These data illustrate the current status of the loading information available as part of the
Chesapeake Bay Basinwide Toxics Loading and Release Inventory (Chesapeake Bay Program,
1994a). While there are many assumptions and problems with the current data set, this exercise
highlights areas that need further study in order to synthesize a more complete understanding and
quantification of the sources of potentially toxic chemicals to Chesapeake Bay. This will be
further illustrated in the next section. Recommendations for future loadings studies include: 1) for
all sources determine a consistent chemical fraction (e.g., total, total recoverable, dissolved), 2)
use lower detection limit methods for both dissolved and paniculate analyses, 3) include urban
stations in the atmospheric deposition network, 4) undertake a comprehensive sampling of major
point source dischargers, and 5) initiate site specific studies to better estimate the urban flux of
chemical contaminants. These studies should be coupled with the determination of the removal
rates (i.e., burial, gas exchange, degradation) from Chesapeake Bay to help understand the fate
and cycling with in this environment.
A PRELIMINARY MASS BALANCE FOR THE MARYLAND PORTION OF THE TIDAL CHESAPEAKE
BAY: AN ILLUSTRATIVE EXAMPLE
To illustrate some of the problems, pitfalls, and usefulness of constructing a simple input-
output mass balance, information and data from various sources were collected and compared for
the Maryland portion of tidal Chesapeake Bay. This balance considers only chemical
contaminants coming into this region from sources mentioned in the previous section and the
amount of contaminants buried in the sediment. Only specific trace metals (e.g., copper, lead, and
zinc) were quantified due to a larger existing database for these metals than for organic
contaminants (e.g., PCBs) or other trace metals. For this study, only the tidal area from the
mouth of the Susquehanna River (RM 156) to south of the Potomac River (RM 55) was selected
due to the greater amount of available data compared to the Virginia portion of the Bay. The
exchange of water and sediment from the southern portion of the Bay also were not considered in
these calculations. Additionally, microbial processes affecting metal speciation were not
30
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quantified because only bulk "total" concentrations were used. The approach to calculating the
sediment burial of trace metals is similar to that described in Officer et al. (1984) for sediments
and Nixon (1987) and Boynton et al. (1995) for nitrogen and phosphorus.
Inputs of Metals
Sources of copper, lead, and zinc were adapted from the data in Chesapeake Bay Program
(1994a). Shoreline erosion estimates were modified from Velinsky (1994) to adjust the loads for
the Maryland portion of the Bay and important tributaries (e.g., Potomac, Patuxent, and
Choptank rivers). While not all areas or tributaries were quantified directly, this exercise most
likely accounts for a majority of the inputs to the tidal waters of Maryland (Table 4).
The ranges listed in Table 4 for atmospheric deposition (wet+dry), urban runoff, and river
transport are derived differently. The ranges for atmospheric deposition were related to the
uncertainty in the dry deposition flux (see Baker et al. 1994), while the ranges for river transport
were the low and high fluxes over a four year time period (1990-1994) and are related mainly to
the variations in water discharge. While there are no ranges presented for either shoreline erosion
or point source loads, the data in Chesapeake Bay Program (1994a), Velinsky (1994), and Warner
et al. (1992) indicate that the fluxes could vary by an order of magnitude.
Similar to the inputs for the entire Chesapeake Bay, river transport and urban runoff are the
two dominant sources to the Maryland portion of the Bay. Inputs from atmospheric deposition
Table 4. Summary of trace metal loads to the Maryland portion of the tidal waters of
Chesapeake Bay. Loads are in metric tons per yr.
Chemical
Copper
Lead
Zinc
Atmospheric
Deposition
2.0 - 3.6
4.7 - 7.6
12- 14
Urban
Runoff
10-56
44-240
56-310
River
Transport
130 - 240
160 - 270
180- 780
Shoreline
Erosion
13
11
45
Point
Sources
31
4.7
140
Adapted from Chesapeake Bay Program (1994a), Baker et al. (1994), and Velinsky (1994).
31
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directly to the surface waters of the upper bay and shoreline erosion appear to be of similar
magnitude, but how and where these sources enter the Bay differ markedly. The sediments from
the headlands and shoreline of the Bay (e.g., Cah/ert Cliffs), derived from erosion, are not easily
transported and mixed throughout the Bay, yet atmospheric deposition occurs over the entire
Bay, even in remote waters. Point source loads, while most likely underestimated, are similar to
shoreline erosion in that they are introduced into specific areas and over a specific time period.
However, becasue a portion of the point source load may be in the dissolved phase, it will either
stay in the dissolved phase or partition to suspended material and be transported with the water
more rapidly than erosional sources.
Metals Burial in the Sediments
The inputs of these metals to the water column or suspended sediments are balanced against
the burial of paniculate metals in the sediments of the Bay (see previous discussion on particle-
reactivity of metals). The burial rate of a contaminant (B; kg metal/yr) can be determined by
using the concentration of a metal in the sediment that is buried (C; pg Metal/g dry weight), the
dry bulk sediment density (p,; g dry sediment/ cm3 of total sediment), and the vertical
sedimentation rate (co^ cm/year). From this information, the burial rate of a metal can be
determined via the following equation (Berner, 1980; B = C- p.-toj. Studies that provide a mass
sedimentation rate (o>m; g dry sediment/cm2-year) for a given area of the Bay can also be used
with concentrations of metals to provide a burial rate (B = C-co,J.
Additionally, areas within the Bay must be classified as depositional, erosional, or at
equilibrium. For each area or segment of the Maryland portion of the Bay, this type of
information is combined and summed to provide an estimate of the removal of a contaminant via
sediment burial. This method is similar to that for both nitrogen and phosphorus deposition as
described in Boynton et al. (1995).
To accomplish this calculation, data were obtained from many studies that spanned over 15
years. First, the surface area of the upper bay (Cronin and Pritchard, 1975; Boynton et al. 1995)
was broken into upper and lower Maryland segments, with the three major tributaries were
32
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treated separately (Table 5). The fraction of each segment or tributary that is depositional was
taken from Kerhin et al. (1983; 1988) and ranged from 0.8 in the tributaries to 0.5 in the lower
portion of the Maryland mainstem (Table 5). Area! mass depositional rates were obtained or
derived from the studies of Kerhin et al. (1983; 1988), Brush et al. (1982), Officer et al. (1984),
and Boynton et al. (1995). High and low mass depositional rates for the different areas are
presented in Table 6. The information presented in Table 5 was then used with the mass
sedimentation rates presented in Table 6 to derive a dry sediment flux in the Maryland portion of
Chesapeake Bay.
Next, sediment contaminant concentration data for Chesapeake Bay and its tributaries (Table
7) were applied to the sediment depositional rates for the given area and the burial of metals was
calculated. The contaminant data were obtained from the comprehensive report by Eskin et al.
(1995, unpublished report) and represent surface sediment concentrations from samples collected
over various years. If available, concentrations of contaminants below the surface layer should be
used to account for possible diagenetic remobilization of metals into the overlying waters;
however this is not always possible. Also, while median concentrations were used to calculate the
burial of trace metals, there is substantial spatial variability in the concentration of metals
throughout all areas (Eskin et al. 1995 unpublished report and references within).
In addition to the mainstem bay and the three tributary estimates, there are two recognized
areas within this study area, the Anacostia River and Pataspco/Back River system, that have
extremely elevated concentrations of trace metals (Velinsky et al. 1994; Eskin et al. 1995
unpublished report). These two areas have been declared as Regions of Concern by the
Chesapeake Executive Council and Regional Action Plans are being drafted to help manage and
remediate these areas (Chesapeake Executive Council, 1994). For each of these areas, a
preliminary assessment was made of the deposition rate of these metals to the sediments.
For the tidal Anacostia River, a similar technique as described above was used to determine
the burial of metals in the sediments. This was accomplished using recent surface sediment
concentrations (Velinsky et al. 1994; Sampou, 1990; Pinkney et al. 1993) and sediment deposition
rates from Scatena (1987). From this preliminary analysis, the sediment burial of copper, lead,
33
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Table 5. Surface areas and depositional fractions for Maryland portion of Chesapeake Bay.
Location
Total Bay
Maryland Mainstem"
Upper MD portion
Lower MD portion
Patuxent River
Potomac River
Choptank River
Surface Area (m2)
1.15 xlO10
5.15 xlO9
1.69 xlO9
3.82 x 10»
1.36x10"
1.13 xlO9
3.60 xlO8
Fraction Depositional
0.52
0.72
0.72
0.54
0.80
0.80
0.80
•Includes all tributaries from RM 55 to RM 156. Upper MD portion is from RM 125 to RM 156
and die lower portion is from RM 55 to RM 125. Data taken from Cronin and Pritchard (1975),
Officer et al. (1984), Kerhin et at. (1983; 1988), Hobbs et al. (1992), and Boynton et al. (1995).
Table 6. Mass sedimentation rates for various areas of Chesapeake Bay.
Location
Mass Sedimentation
Reference
Total Bay (weighted average)
Upper MD portion
Lower MD portion
Upper Bay
Mid-Bay
Lower Bay
Upper Patuxent River
Lower Patuxent River
Upper Potomac River
Lower Potomac River
Upper Choptank River
Lower Choptank River
0.23
0.39
0.17
0.30 - 1.2
0.10-0.30
0.10-0.80
0.24 - 0.27
0.15 - 0.20
0.69 - 1.5
0.07 - 0.47
0.34
0.09
Officer etal. (1984)
Kerhin etal. (1983; 1988)
Kerhin etal. (1983; 1988)
Officer etal. (1984)
Officer etal. (1984)
Officer etal. (1984)
Khan and Brush (1994)
Brush (1984)
Brush etal. (1982)
Brush etal. (1982)
Yarboetal. (1983)
Yarbo etal. (1983)
Mass sedimentation rates in units of g dry sediment/cm2-yr.
34
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Table 7. Trace metal concentrations for areas within the Maryland portion of Chesapeake Bay
Location
Upper
Lower
Patuxent
Potomac
River
River
Choptank River
Copper
3.7-
2.5-
12-
28-
3.0-
56
48
34
43
31
(33)
(24)
(23)
(36)
(15)
13
6
8.0
15
2.0
Lead
-86
(61)
-76(35)
-52
-73
-55
(29)
(33)
(29)
19-
25-
99-
130-
29-
Zinc
500
350
172
(220)
(140)
(150)
270 (190)
170
(110)
Data from Eskin et al. (1995, unpublished report). Concentrations are low and high concentrations
with median values in ( ).
and zinc was estimated to be 3.8, 8.4, and 17 metric tons/year, respectively (Velinsky et al.
1993). These fluxes are within 1 to 3 times the loads for the Anacostia watershed (Velinsky,
unpublished data; Olsenholler, 1991).
For the Pataspco and Back River system, a similar approach was used. Using data from Eskin
et al. (1995 unpublished report) and Warner et al. (1992), sediment burial was estimated to range
from 9.6 - 43 metric tons/yr, 9.9 - 44 metric tons/yr, and 36 - 140 metric tons/yr for copper, lead,
and zinc, respectively. This range is based on the range in sedimentation rates and median
Baltimore Harbor metal concentrations from Eskin et al. (1995 unpublished report). However,
this estimate does not account the removal of sediments with elevated levels of trace metals from
the extensive dredging in the Baltimore Harbor area. These rates were compared to the loadings
calculated by Warner et al. (1992) for both point and nonpoint sources. They estimated copper
lead, and zinc loads to the harbor area of 26, 37, and 130 metric tons/yr, respectively. Helz
(1976) also estimated the annual input of zinc in 1970 to this area of 650 metric tons/yr; evidently
the annual load of zinc has decreased over the past 20 years (Sinex and Helz, 1982). These two
estimates (loads vs burial) are in reasonable agreement suggesting that most of the metals that
enter the system are retained in the sediments as proposed by Sinex and Helz (1982).
This method of calculating the removal of metals via sediment burial is fraught with many
problems. At each point in these calculations assumptions were made, usually involving temporal
and spatial scaling issues (i.e., taking short term data and applying them to longer and larger
35
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temporal and spatial scales). For example, while there have been many studies on the
sedimentation rate within the Bay, these studies have focused on specific areas and not a
systematic sampling of the entire Chesapeake Bay area. The study by Officer et al. (1984)
summarized a collection of about 20 cores taken throughout the Bay region. These studies used
geochemical tracers such as210Pb or 137Cs for sediment dating. Sedimentation rates derived using
210Pb or other geochemical tracers are usually averaged over an approximately 100 year time
period and do not separate short term episodic events that can be important in sediment
deposition. For example, Gross et al. (1978), using a sediment budget, estimated that the
majority of sediment introduced to the Bay from the Susquehanna River for a ten year period was
derived from two major storm events, Tropical Storm Agnes and Hurricane Eloise. Hirschberg
and Schubel (1979) further suggested that sediment profiles of 210Pb from their study indicate a
massive deposition of sediments derived from Agnes and other storms. These episodic events in
sedimentation are averaged out using tracer studies and could underestimate sediment
accumulation. Other methods for calculating sedimentation rates, such as sediment budgets and
bathymetric depth changes yield slightly different rates than geochemical tracer studies. Without a
systematic approach of sampling and measuring sedimentation rates within the Bay and
tributaries, mass balance budgets for contaminants will remain uncertain.
f
Comparison of Inputs and Burial
Using the above estimates, yearly burial rates of copper, lead, and zinc to the Maryland
portion of the Bay ranged from 220 to 680 metric tons/yr, 360 to 1,200 metric tons/yr, and 1,400
to 4,300 metric tons/yr, respectively. Interestingly, the burial of these metals in both the
Anacostia River and the Baltimore Harbor region accounts for between 4 and 7% of the total
deposition (using the mid-points of the ranges) even though these areas constitute only
approximately 2% of the total surface area of the Maryland portion of the Bay.
The midpoint of these ranges were compared to the total inputs to this region (Figure 3). For
both copper and lead there is a reasonable agreement between quantified inputs and burial, while
for zinc the output via sediment burial is approximately three times as high as the inputs. It is
36
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Z.8
Copper
Total In: 260
Total Out: 450
I Pomt Source.'
V x "
Chesapeake Bay
, Deposition
f I
R>mobililation J
Sediment
7T7
, Point Sources 7 SbmlbM: 13
UrkuRllMtT: 33
Burial: 450
Total In: 370
Total Out: 760
Zinc
Total In: 864
Total Out: 2,800
All fluxes are in Metric tons/yr
Figure 3. Inputs and outputs of trace metals to the Maryland portion of Chesapeake Bay.
37
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unclear why the burial of zinc is much higher than its input, compared to either copper and lead
(i.e., all sources and sinks were estimated similarly). Variations in the concentration of surficial
concentration of zinc may require further study. Conversely, there may be many unaccounted or
underestimated sources that also need to be assessed or re-assessed. It appears that the total load
introduced to this area can be balanced by what is lost or buried in the sediments, and very little is
transported to the southern portion of the Bay. However, while the closeness of these fluxes may
be real, there are many areas of uncertainty, both for sources and sinks, that prohibit any definitive
conclusions at this point.
Uncertainty in source estimates comes from several factors. First, there are currently no
estimates for the inputs of contaminants from groundwater, sediment/water transport, and the
coastal region to the Bay. These sources could be important for specific contaminants depending
on their mobility and transport rate. Studies by USGS, U.S. EPA and others indicate that nutrient
inputs via groundwater can be significant (Chesapeake Bay Program, 1993), and research by
Cerco (1994) and Boynton et al. (1995) suggests that the Bay is a net importer of phosphorus
from the coastal areas. However, depending on the reduction-oxidation potential within the
sediments and aquifer, many contaminants which are particle-reactive may not be transported
through the groundwater to the same extent as more water soluble contaminants. Second, there
are large uncertainties associated with load calculations for most of these sources. There are not
sufficient monitoring data of sufficient quality to evaluate annual concentrations and fluxes of
metals from many river systems. For example, only the Susquehanna River has sufficient data to
evaluate annual loads to the Maryland portion of the Bay. The Susquehanna River flux was then
extrapolated to the unmonitored Maryland portion of the Bay. While this river accounts for the
majority of the total flow, other smaller watersheds could have an impact on the Bay, especially
on the waters which directly receive the river's flow. Third, Warner et al. (1992) suggest that
point source loads can vary substantially depending on the calculation method. These estimates
can vary by orders of magnitude. Lastly, similar variations can be shown for estimates via urban
runoff and possibly shoreline erosion, both of which are major inputs to tributaries and the Bay.
The only output considered in this budget was the burial of contaminants in the sediments. As
38
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pointed out earlier, there are also many areas for uncertainty in these calculations. For example,
variations in trace metal concentrations within the northern Bay can be substantial (Eskin et al.
1995 unpublished report and references within). However, the majority of the uncertainty most
likely lies with the estimates of the depositional rates and the areas of the Bay that are
depositional. Kerhin et al. (1983; 1988) studied the pattern of erosion and deposition for the
mainstem northern Bay, giving little attention to some of the tributaries. Although these
tributaries are probably more depositional than the mainstem Bay, more information is needed.
There are different ways to compute the sedimentation rate of a given area; either by use of
geochemical tracers such as 210Pb (Officer et al. 1984; Owens and Cornwell, 1995) or use of a
sediment budget (Kerhin et al. 1983; 1988; Hobbs et al. 1992). Officer et al. (1984) showed a
trend of high sedimentation rates in the upper bay of 0.3-1.2 g/cm2-yr with lower rates in the mid-
Bay region of 0.1-0.3 g/cm2-yr. Mass sedimentation rates in the lower Bay were slightly higher
than mid-Bay sites. While there was substantial variation between areas, these sedimentation
rates are in general agreement with other studies (Hobbs et al. 1992; Helz et al. 1985; Cooper and
Brush, 1993; Owens and Cornwell, 1995). With better coverage of sedimentation rates of the
tributaries as well as the mainstem Bay, a more precise estimate can be derived for this sink of
metals.
TOWARDS A CHESAPEAKE BAY CHEMICAL CONTAMINANT MASS BALANCE
The simple input-output mass balance analysis for copper, lead and zinc appears to be
consistent in that there is a reasonable agreement between total inputs and the loss of these metals
via burial. Unfortunately, due to the lack of data it is impossible to quantify the uncertainty for
these estimates. However, while the amount of uncertainty in this analysis is most likely large, this
study does allow a focusing of monitoring efforts on specific sources and geographic areas that
would greatly improve and expand a mass balance. For example, in many areas urban runoff is a
dominant source. The method used to calculate the urban runoff load (Olsenholler, 1991) should
be updated carefully with newer chemical and land use data. Also, it became apparent during the
development of this input-output mass balance that there is little information available concerning
39
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the transport of organic contaminants into and within the Bay. If an expanded mass balance is
sought, especially for other inorganic or organic contaminants, much more monitoring is
warranted.
Overall, basic monitoring information is needed for almost all sources and sinks identified in
this document. While these monitoring data will not provide information as to the effects of
chemical contaminants, they do provide the needed information as to where and how much a
reduction in a particular source load is needed. Until both sources and sinks are better quantified,
future input-output balances will remain uncertain and of limited quantitative use.
The input-output model derived for the Maryland portion of the Bay is a simplistic form of a
time dependent mass balance. Other types of mass balances would be much more complex. For
example, a model could be developed to include a water transport component which would be
coupled to a nutrient-driven eutrophication model. This framework would then generate the
organic carbon-related solids information which would be coupled to a bulk solids transport
model. This section would be an input to a contaminant exposure/food chain model. This type of
modeling framework would be used if fish or benthic organism exposure is an endpoint. Once
verified, this model could be used to answer "what if questions such as; if specific sources are
reduced, how much reduction is needed and how long will it take to lower the concentration of a
specific contaminant in the water column or an organism to a given level? This type of modeling
is currently under development for specific areas within the Great Lakes for PCBs.
For a more complete mass balance model to be useful, its development must be driven by the
objectives that both managers and scientists decide upon. Also, there are many questions
concerning the feasibility of using a mass balance approach to manage or evaluate chemical
contaminants in Chesapeake Bay. For example, if a concerted effort is applied to determine the
absolute inputs and outputs from significant sources and sinks, will enough specific information
exist to help managers of the various sources of contaminants (e.g., point source regulators or
urban planners) determine the need for potential additional regulation of these sources? Also, if
additional regulatory actions are taken, will living resources that are affected by contaminants
respond and show some improvement (e.g., fewer fish advisories)?
40
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As can be seen from the simple input-output model for Maryland, the data needs for any of
these tasks are enormous and would therefore be very expensive. However, the development of a
simple input-output mass balance could be a first step and would be less expensive while
providing useful information to Bay managers. For example, current load estimations to the Bay
could be evaluated and judged for accuracy by also estimating the outputs. This would help
managers and scientists determine any unrecognized source(s) to the Bay. When an accurate
assessment of the relative loading exists, the importance of each source can be determined, and a
determination can be made of the possible measures in controlling these sources in an overall
context. The results generated from such a project would also be a part of the initial data
requirements for a larger modeling framework, if developed. This information is needed to help
focus clean-up efforts and the limited dollars to areas and sources that will make the biggest
difference in the overall health of Chesapeake Bay.
41
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REFERENCES
Abramowicz, D.A., M.J. Brennan, H.M. Van Dort, and E.L. Gallagher. 1993. Factors influencing
the rate of polychlorinated biphenyl dechlorination in Hudson River sediments. Environ. Sci.
Technol 27:1125-1131.
Achman, D.R., K.C. Hornbuckle, and S.J. Eisenreich. 1992. Volatilization of polychlorinated
biphenyis from Green Bay, Lake Michigan. Environ. Sci, Technol. 27: 75-87.
Alcock, R.E., S.P. McGrath, and K.C. Jones. 1995. The influence of multiple sewage sludge
amendments on the PCB content of an agricultural soil over time. Environ. Tax. Ghent. 14: 553-
560.
AlderT A.C., MM. Haggblom, S.R. Oppenheimer, and L.Y. Young. 1993. Reductive
dechlorination of polychlorinated biphenyls in anaerobic sediments. Environ. Sci. Technol. 27:
530-538.
Amyot, M, G. Mierie, D.R.S. Lean, and D.J. McQueen. 1994. Sunlight-induced formation of
dissolved gaseous mercury in lake water. Environ. Sci. Technol. 28: 2366-2371.
Atlas, E.L. and C.S. Giam. 1986. Sea-air exchange of high molecular weight synthetic organic
compounds. In: The Role of Air-Sea Exchange in Geochemical Cycling (ed.: P. Buat-Menard).
D. Reidel, Norwell, MA, 295-330 pp.
Baker, J.E., D.J. Burdige, T.M. Church, G.A. Cutter, R.M. Dickhut, D.L. Leister, J.M. Ondov,
and J.R. Scudlark. 1994. Chesapeake Bay Atmospheric Deposition Study. Phase H July 1990-
December 1991. Final Report Year 2 Report to the U.S. EPA Chesapeake Bay Program,
CBP/TRS 118/94, U.S. EPA Chesapeake Bay Program Office, Annapolis, MD, July, 1994,
280pp.
Baker, J.E., T.M. Church, S. J. Eisenreich, W. F. Fitzgerald, and J.R. Scudlark. 1993. Relative
Atmospheric Loadings of Toxic Contaminants and Nitrogen to the Great Waters. Office of Air
Quality Planning and Standards, U.S. Environmental Protection Agency, Research Triangle Park,
NC.
Baker, J.E., S.J. Eisenreich, and B.J. Eadie. 1991. Sediment trap fluxes and benthic recycling of
organic carbon, polycyclic aromatic hydrocarbons, and polychlorinated congeners in Lake
Superior. Environ. Sci. Technol 25: 500-509.
42
-------
Bergen, B.J., W.G. Nelson, and R.J. Pruell. 1993. Partitioning of polychlorinated biphenyls
congeners in the seawater of New Bedford Harbor, Massachusetts. Environ. Sci. Technol. 27:
938-942.
Berner, R.A. 1980. Early Diagenesis, A Theoretical Approach. Princeton Series in Geochemistry,
Princeton University, N.J., 241 pp.
Boehm, P.D. and J.G. Quinn. 1973. Solubilization of hydrocarbons by dissolved organic matter
in seawater. Geochim. Cosmochim. Acta 37: 2459-2477.
Boyle, E., R. Collier, A.T. Dengler, J.M. Edmond, A.C. Ng, and R.F. Stallard. 1974. On the
chemical mass-balance in estuaries. Geochim. Cosmochim. Acta 38: 1719-1728.
Boynton, W.R., J.H. Garber, R. Summers, W.M. Kemp. 1995. Inputs, transformations, and
transport of nitrogen and phosphorus in Chesapeake Bay and selected tributaries. Estuaries 18:
285-314.
Brownwell, B.J. and J.W. Farrington. 1986. Biogeochemistry of PCBs in interstitial waters of a
coastal marine sediment. Geochim. Cosmochim. Acta 50: 157-169.
Brush, G.S. 1984. Patterns of recent sediment accumulation in Chesapeake bay (VA-MD, USA)
tributaries. Chem. Geol. 44: 227-242.'
Brush, G.S., E.A. Martin, R.S. DeFries, and C.A. Rice. 1982. Comparison of 210Pb and pollen
methods for determining rates of estuarine sediment accumulation. Quart. Res. 18: 196-217.
Capone, D.G., I.E. Baker, and J.W. Gooch. 1995. Ecosystem processes related to transport,
partitioning, and effects of organic contaminants in Chesapeake Bay: A simulation study.
Preliminary results. In: Chesapeake Bay Environmental Effects Studies, Toxics Research
Program 1994 Preliminary results, (eds.: E.J. Olmi HI, B. Hens, P. Hill, and J.G. Sanders).
NOAA Chesapeake Bay Office, Annapolis, MD.
Capone, D.G., J.E. Baker, and J.W. Gooch. 1994. Microbial degradataion of chlorinated
hydrocarbons under alternating redox conditions in Chesapeake Bay sediments. Preliminary
results. In: Chesapeake Bay Environmental Effects Studies, Toxics Research Program 1993
Preliminary results, (eds.: J.M. Jacobs). NOAA Chesapeake Bay Office, Annapolis, MD.
43
-------
Cerco, C.F. 1994. Past, present, and potential dissolved oxygen conditions and nutrients budgets.
In: Towards a Sustainable Coastal Watershed: The Chesapeake Experiment, (eds: P. Hill and S.
Nelson), Proceedings of a Conference, 1994 Chesapeake Research Conference, Norfolk, VA,
Chesapeake Research Consortium Pub. 149, CRC Edgewater, MD, 162 pp.
Chesapeake Bay Program. 1982. Chesapeake Bay Program Technical Studies: A Synthesis. U.S.
EPA Chesapeake Bay Program, Washington, D.C., September, 1982, 634 pp.
Chesapeake Bay Program. 1993. Chesapeake Bay Groundwater Toxics Loading Workshop
Proceedings. CBP/TRS 96/93, U.S. EPA Chesapeake Bay Program Office, Annapolis, MD,
July, 1993, llpp.
Chesapeake Bay Program. 1994a. Toxics Loading and Release Inventory, CBP/TRS 102/94, U.S.
EPA Chesapeake Bay Program Office., Annapolis, MD, March, 1994, 140 pp.
Chesapeake Bay Program. 1994b. Response of the Chesapeake Bay Water Quality Model to
Loading Senarios. Prepared by the Modeling Subcommittee. CBP/TRS 101/94, April, 1994.
Chesapeake Bay Program. 1994c. Chesapeake Bay Fall Line Toxics Monitoring Program 1992
Final Report. CBP/TRS 121/94, U.S. EPA Chesapeake Bay Program Office, Annapolis, MD,
July, 1994, 153 pp.
Chesapeake Bay Program. 1994d. Chesapeake Bay Basinwide Toxics Reduction Strategy
Reevaluation Report. CBP/TRS 117/94, U.S. EPA Chesapeake Bay Program Office, Annapolis,
MD, September, 1994, 192 pp.
Chesapeake Executive Council. 1994. Chesapeake Bay Basinwide Toxics Reduction and
Prevention Strategy. U.S. EPA Chesapeake Bay Program Office, Annapolis, MD, 6 pp.
Cifuentes, L.A., L.E. Schemel, and J.H. Sharp. 1990. Qualitative and numerical analyses of the
effects of river inflow variations on mixing diagrams in estuaries. Estuar. Coast. Shelf Sci. 30:
411-427.
Cooper, S.R and G.S. Brush. 1993. A 2,500 yr history of anoxia and eutrophication in
Chesapeake Bay. Estuaries 16: 617-626.
44
-------
Cornwall, J.C., D.J. Burdige, and W.R. Boynton. 1995. Direct measurements and biogeochemical
controls of sediment-water flux of trace metals from estuarine sediments. Preliminary results. In:
Chesapeake Bay Environmental Effects Studies, Toxics Research Program 1994 Preliminary
results, (eds.: E.J. Olmi JH, B. Hens, P. Hill, and J.G. Sanders). NOAA Chesapeake Bay Office,
Annapolis, MD.
Correll, D.L., N.M. Goff, and W.T. Peterjohn. 1981. Ion balances between precipitation inputs
and Rhode River watershed discharges. In: Geological Aspects of Acid Deposition, (ed.: O.P.
Bricker). Acid Precipitation Series, Volume 7., Butterworth Publishers, Boston, MA, 77-111 pp.
Couillard, Y., P.G.C. Campbell, and A. Tessier. 1993. Response of metallothionein
concentrations in a freshwater bivalve (Anodonta grandis) along an environmental cadmium
gradient. Limnol. Oceanogr. 38:299-313.
Cronin, W.B. and D.W. Pritchard. 1975. Additional Statistics on the Dimension of the
Chesapeake Bay and its Tributaries: Cross-section Widths and Segment Volumes Per Meter
Depth. Special Report 42. Chesapeake Bay Institute, The Johns Hopkins University, Ref. 75-3,
Baltimore, MD.
Cutter, G.A., D.J. Velinsky, C.H. Culberson, and T.M. Church. 1985. The redox environment of
the Chesapeake Bay. EOS 66: 1319.
DeLaune, R.D., R.P. Gambrell, J.H. Pardue, and W.H. Patrick, Jr. 1990. Fate of petroleum
hydrocarbons and toxic organics in Louisiana coastal environments. Estuaries 13: 72-80.
DeLaune, R.D., G.A. Hambrick HI, and W.H. Patrick, Jr. 1980. Degradation of hydrocarbons in
oxidized and reduced sediments. Mar. Pollut. Bull. 11: 103-106.
Di Toro, D.M., C. Zarba, D.J. Hansen, W. Berry, R.C. Swartz, C.E. Cowan, S.P. Pavlou, HE.
Allen, N.A. Thomas, and P.R. Paquin. 1992. Technical basis for establishing sediment quality
criteria for non-ionic organic chemicals using equilibrium partitioning. Environ. Tax. Chem. 10:
1541-1583.
Diaz, R.J., R.J. Neubauer, L.C. Schaffher, L. Phil, and S.P. Baden. 1992. Continuous monitoring
of dissolved oxygen in an estuary experiencing periodic hypoxia and the effect of hypoxia on
macrobenthos and fish. Sci. Total Environ. Supple. 1992: 1055-1067.
45
-------
Donat, J.R. 1995. The specation of dissolved copper and cadmium in Chesapeake Bay,
Preliminary results. In: Chesapeake Bay Environmental Effects Studies, Toxics Research
Program 1994 Preliminary results, (eds.: E.J. Olmi m, B. Hens, P. Hill, and J.G. Sanders).
NOAA Chesapeake Bay Office, Annapolis, MD.
Duce, R.A., P.S. Liss, and many others. 1991. The atmospheric input of trace species to the
world ocean. Global Biogeochem. Cycles 5: 193-259.
Eadie, B.J., N.R. Morehead, J.Val Klump, and P.F. Landrum. 1992. Distribution of hydrophobic
organic compounds between dissolved and paniculate organic matter in Green Bay waters. J.
Great Lakes Res. 18: 91-97.
Eadie, B.J., N.R Morehead, and P.P. Landrum. 1990. Three phase partitioning of hydrophobic
organic compounds in Great Lake waters. ChemospherelQ. 161-178.
Eisenreich, S.J. 1987. The chemical limnology of nonpolar organic contaminants. PCBs in Lake
Superior. In: Sources and Fates of Aquatic Pollutants, (eds.: R.A. Hites ad S.J. Eisenreich)
American Chemical Society, Adv. Chem. Ser. 126, Washington, D.C., 393-470 pp.
Eskffl, R.A., K. H. Rowland, D. Y. Alegre, and RE. Magnien. 1995. Contaminants in
Chesapeake Bay Sediments (1984-1991). Unpublished report to Chesapeake Bay Program.
Maryland Dept. Environ., Baltimore, MD.
Fitzgerald, W.F., R.P. Mason, and G.M. Vandal. 1991. Atmospheric cycling and air-water
exchange of mercury over mid-continental lacustrine regions. Water, Air and Soil Pollution 56:
745-767.
Fox, L.E. 1983. The removal of dissolved humic acids during estuarine mixing. Estuar. Coast.
Shelf Sci. 16:4431-440.
Gerlach, S.A. 1981. Marine Pollution, Diagnosis and Therapy. Springer-Verlag, New York,
N.Y.
Gibson, D.T. 1977. Biodegradation of aromatic petroleum hydrocarbons. In: Fate and Effects of
Petroleum Hydrocarbons in Marine Ecosystems and Organisms (ed.: D.A. Wolfe), Pergamon
Press, New York, N.Y. 36 pp.
46
-------
Godtfredsen, K.L. and A.T. Stone. 1994. Solubilization of manganese dioxide-bound copper by
naturally occurring organic compounds. Environ. Sci. Technol. 28: 1450-1458.
Gross, M.G., M. Karweit, W.B. Cronin, and J.R. Schubel. 1978. Suspended sediment discharge
of the Susquehanna River to northern Chesapeake Bay. Estuaries 1: 106-110.
Hale, R.C. and R.J. Huggett. 1988. Bioavailability of organic pollutants to aquatic organisms. In:
Understanding the Estuary: Advances in Chesapeake Bay Research, (eds: M.P. Lynch and B.C.
Krone). Chesapeake Res. Consortium Pub. 129, CRC, Solomons, MD, 26-32 pp.
Harvey, G.R., D.A. Boran, L.A. Chesal, and J.M. Tokar. 1983. The structure of marine fluvic
and humic acids. Mar. Chem. 12: 119-132.
Helz, G.R. 1976. Trace element inventory for the northern Chesapeake Bay with emphasis on the
influence of man. Geochim. Cosmochim. Acta 40: 573-580.
Helz, G.R., S.A. Sinex, K.L. Fermi, and M. Nichols. 1985. Processes controlling Fe, Mn, and Zn
in sediments of northern Chesapeake Bay. Estuar. Coast. Shelf Sci. 21: 1-16.
Hennessee, E.L., P.J. Blakeslee, and J.M. Hill. 1986. The distribution of organic carbon and
sulfur in surficial sediments of the Maryland portion of Chesapeake Bay. Jour. Sea. Petrol. 56:
674-683.
Hirschberg, D.J. and J.R. Schubel. 1979. Recent geochemical history of flood deposits in the
norther Chesapeake Bay. Estuar. Coast Mar. Sci. 9: 771-784.
Hobbs, C.H. UJ. 1983. Organic carbon and sulfur in the sediments of the Virginia Chesapeake
Bay. Jour. Sed Petrol. 53: 383-393.
Hobbs, C.H. JH, J.P. Halka, R.T. Kerhin, and M.J. Carron. 1992. Chesapeake Bay sediment
budget. J. Coast. Res. 8: 292-300.
Hoffinan, E.J., G.L. Mills, J.S. Latimer, and J.G. Quinn. 1984. Urban Runoff as a Source of
Polycyclic Aromatic Hydrocarbons to Coastal Waters. Environ. Sci. Technol. 18: 580-587.
Hoffinan, E.J., G.L. Mills, J.S. Latimer, and J.G. Quinn. 1983. Annual input of petroleum
hydrocarbons to the coastal environment via urban runoff. Can. Jour. Fish. Aqua. Sci. 40: 41-53.
47
-------
Itsweire, E.G. and O.M. Phillips. 1987. Physical processes that control circulation and mixing in
estuarine systems. In: Perspective on the Chesapeake Bey: Recent Advances in Estuarine
Sciences. U.S. Environmental Protection Agency, Chesapeake Bay Program, Annapolis, MD.
Jannasch, H.W., B.D. Honeyman, L.S. Balistrieri, and J.W. Murray. 1988. Kinetics of trace
element uptake by marine particles. Geochim. Cosmochim. Acta 52: 567-577.
Jeremiason, J.D., K.C. Hornbuckle, and SJ. Eisenreich. 1994. PCBs in Lake Superior, 1978-
1992: Decreases in water concentrations reflect loss by volatilization. Environ. Sci. Technol 28:
903-914.
Karickhoff, S.W., D.S. Brown, and T.A. Scott. 1979. Sorption of hydrophobic pollutants on
natural sediments. Water Research 13: 241-248.
Katz, B.G., O.P. Bricker, and M.M. Kennedy. 1985. Geochemical mass-balance relationships for
selected ions in precipitation and stream water, Catoctin Mountains, MD. Amer. J. Sci. 285: 931-
962.
Kaul, L.W. and P.N Froelich. 1984. Modeling estuarine nutrient geochemistry in a simple system.
Geochim. Cosmochim. Acta 48: 1417-1433.
Kemp, W.M., J. Gooch, I.E. Baker, and J.R. Kuclick. 1995. Ecosystem processes related to
transport, partitioning, and effects of organic contaminants in Chesapeake Bay: A simulation
study. Preliminary results. In: Chesapeake Bay Environmental Effects Studies, Toxics Research
Program 1994 Preliminary results, (eds.: E.J. Olmi m, B. Hens, P. Hill, and J.G. Sanders).
NOAA Chesapeake Bay Office, Annapolis, MD.
Kemp, W.M. and J.E. Baker. 1994. Ecosystem processes related to transport, partitioning, and
effects of organic contaminants in Chesapeake Bay: A simulation study. Preliminary results. In:
Chesapeake Bay Environmental Effects Studies, Toxics Research Program 1993 Preliminary
results, (ed.: J.M. Jacobs). NOAA Chesapeake Bay Office, Annapolis, MD.
Kemp, W.M. and W.R. Boynton. 1992. Benthic-pelagic interactions: Nutrients and oxygen
dynamics. In; Oxygen Dynamics in the Chesapeake Bay-A Synthesis of Recent Results, (eds.:
D.E. Smith, M. Leffler, and G. Mackiernan). MD. Sea Grant, Univ. MD, College Park, MD, 149-
209pp.
48
-------
Kerhin, R.T., J.P. Halka, D.V. Wells, E.L. Hennessee, P.J. Blakeslee, N. Zoltan, and R.H.
Cuthbertson. 1988. The surficial sediments of Chesapeake Bay, Maryland: Physical
characteristics and sediment budget. Maryland Geological Survey, Final Report No. 48, 82 pp.
Kerhin, R.T., J.P. Halka, E.L. Hennessee, P.J. Blakeslee, D.V. Wells, N. Zoltan, and R.H.
Cuthbertson. 1983. Physical Characteristics and Sediment Budget for Bottom Sediments in the
Maryland Portion of Chesapeake Bay. Maryland Geological Survey, Final Report to U.S.
Environmental Protection Agency, 160 pp.
Khan, H. and G.S. Brush. 1994. Nutrient and metal accumulation in a freshwater tidal marsh.
Estuaries 17: 345-360.
Knezovich, J.P. 1994. Chemical and biological factors affecting bioavailability of contaminants in
seawater. In: Bioavailability', Physical, Chemical, and Biological Interactions, (eds: J.L.
Hmaelink, P.P. Landrum, H.L Bergman, W.H. Benson). CRC Press, Inc., Boca Raton, FL.
Chapter 2.
Kobayashi, H. and B.E. Rittmann. 1982. Microbial removal of hazardous organic compounds.
Environ. Sci. Technol. 16: 170A-83A.
Landrum, P.P., M.D. Reinhold, S.R. Nihart, and B.J. Eadie. 1985. Predicting the bioavailabiltiy of
organic xenobiotics to Pontopereia hoyi in the presence of humic and fluvic materials and natural
dissolved organic matter. Environ. Toxicol. Chem. 4: 459-467.
Lee, R.F. and C. Ryan. 1983. Microbial and photochemical degradation of poly cyclic aromatic
hydrocarbons in estuarine waters and sediments. Can. Jour. Fish. Aquatic Sci. 40: 86-94.
Lehninger, A.L. 1975. Biochemistry. 2nd Edition. Worth Publishers, New York, N.Y.
Liss, P.S. and P.O. Slater. 1974. Flux of gases across the air-water interface. Nature 247: 181-
184.
Loder, T.C. and R.P. Reichard. 1981. The dynamics of conservative mixing in estuaries. Estuaries
4: 64-69.
Luoma, S.N., C. Johns, N.S. Fisher, N.A. Steinberg, R.S. Oremland, and J.R. Reinfelder. 1992.
Determination of selenium bioavailability to a benthic bivalve from paniculate and solute
pathways. Environ. Sci. Technol. 26:485-491.
49
-------
Luoma, S.N. 1983. Bioavailability of trace metals to aquatic organisms—A review. Sci. Total
Environ. 28: 1-22.
Mackay, D. 1991. Multimedia Environmental Models. The Fugacity Approach. Lewis Publishers,
Chelsea, MI.
Madden, C.J., J.R. Kucklick, and I.E. Baker. 1994. Quantitative evaluation of contaminants in
Chesapeake Bay Region of Concern: A simulation model of exposure and bioaccumulation in
Baltimore Harbor. In: Environmental Effects Research on Chesapeake Bay: Toxics Research
Program June 1994. Maryland and Virginia Sea Grant College Program, NOAA Sea Grant
Program, Univ. of Maryland, Maryland Sea Grant Program, College Park, MD.
Mantoura, R.F.C., Dickerson, A., and J.P. Riley. 1978. The complexation of metals with humic
materials in natural waters. Estuar. Coast. Mar. Sci. 6: 387-408.
Mason, R.P., W.F. Fitzgerald, J. Hurley, A.K. Hanson, P.L. Donaghay, and J.M. Sieburth. 1993.
Mercury biogeochemical cycling in a stratified estuary. Limnol. Oceangr. 38: 1227-1241.
Morel, F. and J.G. Hering. 1993. Principles and Applications of Aquatic Chemistry. Wiley-
Interscience, New York.
National Oceanic and Atmospheric Administration. 1995. Chesapeake Bay Environmental Effects
Studies, Toxics Research Program J994 Preliminary results, (eds.: E.J. Olmi m, B. Hens, P.
Hill, and J.G. Sanders). NOAA Chesapeake Bay Office, Annapolis, MD.
National Oceanic and Atmospheric Administration. 1994. Chesapeake Bay Environmental Effects
Studies, Toxics Research Program J993 Preliminary results, (ed.: J.M. Jacobs). NOAA
Chesapeake Bay Office, Annapolis, MD.
National Oceanic and Atmospheric Administration. 1993. Chesapeake Bay Environmental Effects
Studies, Toxics Research Program J992 Preliminary results, (eds.: E.J. Olmi HJ and B. Hens).
NOAA Chesapeake Bay Office, AnnapoHs, MD.
National Academy of Sciences. 1975. Petroleum in the Marine Environment, Washington D.C.,
107 pp.
50
-------
Newman, M.C. and C.H. Jagoe. 1994. Ligands and the bioavailabiltiy of metals in aquatic
environments. In: Bioavailability, Phyical, Chemical, and Biological Interactions, (eds.: J.L.
Hamelink, P.P. Landrum, H.L. Bergman, and W.H. Benson). CRC Press, Inc., Lewis Publishers,
Boca Raton, 39-61 pp.
Nichols, M.M. 1986. Effects of fine sediment resuspension in estuaries. In: Estuarine Cohesive
Sediment Dynamics. Vol. 14. (ed.: A.J. Mehta). Springer-Verlag, Berlin, 5-42 pp.
Nixon, S.W. 1987. Chesapeake Bay nutrient budgets - A reassessment. Biogeochem. 4: 77-90.
Officer, C.B., D.R. Lynch, G.H. Setlock, and G.H. Helz. 1984. Recent sedimentation rates in
Chesapeake Bay. In: The Estuary as a Filter, (ed.: V.S. Kennedy), Academic Press, New York,
131-157 pp.
Officer, C.B. 1981. Physical dynamics of estuarine suspended sediments. Marine Geology 40: 1-
14.
Officer, C.B. and D.R. Lynch. 1981. Dynamics of mixing in estuaries. Estuar. Coast. Shelf Sci.
12: 525-533.
Officer, C.B. 1979. Discussion of the behavior of nonconservative dissolved constiuents in
estuaries. Estuar. Coast. Shelf Sci. 9: 91-94.
Ofjord, G.D., J.A. Puhakka, and J.F. Ferguson. 1994. Reductive dechlorination of Aroclor 1254
by marine sediment cultures. Environ. Sci. Technol. 28: 2286-2294.
Olsenholler, S.M. 1991. Annual Loading Estimates of Urban Toxic Pollutants in the Chesapeake
Bay Basin. Final Report to U.S. EPA, Chesapeake Bay Program, Metropolitan Washington
Council of Governments, Washington, D.C., 74 pp.
Owens, M. and J.C. Cornwell. 1995. Sedimentary evidence for decreased heavy-metal inputs to
the Chesapeake Bay. Ambio 24: 24-27.
Phinney, J.T. and K.W. Bruland. 1994. Uptake of lipophillic organic Cu, Cd, and Pb complexes in
the coastal diatom Thalassiosira weissflogii. Environ. Sci. Technol. 28: 1781-1790.
51
-------
Pinkney, A.E., W.H. Burton, L.C. Scott, and J.B Frithsen 1993. An assessment of the potential
residual effects of the January 1992 oil spill in the Anacostia River. Versar, Inc., Columbia, MD.
Pritchard, D.W. 1967. Observation of circulation in coastal plain estuaries. In: Estuaries.(ed.:
Lauff), American Association for the Advancement of Science, Washington, D.C., 37-44 pp.
Pritchard, D.W. 1952. Salinity distribution and circulation in the Chesapeake Bay estuarine
system. J. Mar. Res. 11: 106-123.
Raymount, J.E.G. 1980. Plankton and Productivity in the Oceans. 2nd Edition. Pergamon Press,
New York, NY.
Reinfelder, J.R. and N.S. Fisher. 1994. The assimilation of elements ingested by marine planktonic
bivalve larvae. LimnoL Oceangr. 39: 12-20.
Reuter, J.H. and E.M. Perdue. 1977. Importance of heavy metal-organic matter interactions in
natural waters. Geochim. Cosmochim. Acta4\: 325-334.
Rhee, G.Y., B. Bush, C.M. Bethoney, A. DeNucci, H.-M. Oh, and R.C. Sokol. 1993. Reductive
dechlorination of Aroclor 1242 in anaerobic sediments: Pattern, rate, and concentration
dependence. Environ. Tax. Chem. 12: 1025-1032.
Riedel, G.F., J.G. Sanders, and R.W. Osman. 1995. The role of benthic infauna and fluctuating
oxygen concentrations in the flux of toxic trace elements from Chesapeake Bay sediments.
Preliminary results. In: Chesapeake Bay Environmental Effects Studies, Toxics Research
Program 1994 Preliminary results, (eds.: E. J. Olmi ffl, B. Hens, P. Hill, and J.G. Sanders).
NOAA Chesapeake Bay Office, Annapolis, MD.
Riedel, G.F. and J.G. Sanders. 1988. Factors affecting the bioavailability of toxic trace elements
to estuarine organisms. In: Understanding the Estuary: Advances in Chesapeake Bay Research.
(eds: M.P. Lynch and E.C. Krone). Chesapeake Res. Consortium Pub. 129, CRC, Solomons,
MD, 14-25 pp.
Riedel, G.F., Sanders, J.G., and R.W. Osman. 1987. The effects of biological and physical
disturbances on the transport of arsenic from contaminated estuarine sediments. Estuar. Coast.
Shelf Sri. 25: 693-706,
52
-------
Sampou, P. 1990. Sediment/water Exchanges and Biogenesis ofAnacostia River Sediments.
Report prepared for: Metropolitan Washington Council of Governments, Grant # 90-040-PE-
4845, Washington, D.C., 25 p.
Sanford, L.P. and J.P. Halka. 1995. Resuspension and transport of sediment associated toxics in
the northern Chesapeake Bay. Preliminary results. In: Chesapeake Bay Environmental Effects
Studies, Toxics Research Program 1994 Preliminary results, (eds.: E.J. Olmi m, B. Hens, P.
Hill, and J.G. Sanders). NOAA Chesapeake Bay Office, Annapolis, MD.
Sanford, L.P. 1994. Wave-forced resuspension of upper Chesapeake Bay muds. Estuaries 17:
148-165.
Sanford, L.P., D.J. Conley, J.C. Cornwell, J.E. Baker, W.R. Boynton, H.R. Harvey, J.P. Halka,
J.M. Hill, and F. Mohlenberg. 1992. Resuspension and sediment-water exchange in mid-
Chesapeake Bay. Trans. Am. Geophy. Union EOS. 73: 220.
Sanford, L.P., W. Panageotou, and J.P. Halka. 1991. Tidal Resuspension of sediments in northern
Chesapeake Bay. Mar. Geol. 97: 87-103.
Sanford, L.P., K.G. Sellner, and D.L. Breitburg. 1990. Covariability of dissolved oxygen with
physical processes in the summertime Chesapeake Bay. J. Mar. Res. 48: 567-590.
Scatena, F.N. 1987. Sediment Budgets and Delivery in a Suburban Watershed: Anacostia
Watershed., Ph.D Dissertation; The Johns Hopkins University, Baltimore, MD.
Schaffiier, L.C. and R.M. Dickhut. 1995. Role of benthic communities in sediment-associated
toxic organic chemical fate and transport in lower Chesapeake Bay. Preliminary results. In:
Chesapeake Bay Environmental Effects Studies, Toxics Research Program 1994 Preliminary
results, (eds.: E.J. Olmi HI, B. Hens, P. Hill, and J.G. Sanders). NOAA Chesapeake Bay Office,
Annapolis, MD.
Schubel, J.R. 1968. Suspended sediment of Northern Chesapeake Bay. Chesapeake Bay Inst.
Tech. Kept. 35, Johns Hopkins Univ., 269 pp.
Sharp, J.H., J.H. Pennock, T.M. Church, J.M. Tramontane, and L.A. Cifuentes. 1984. The
estuarine interaction of nutrients, organics, and metals: A case study in the Delaware estuary. In:
The Estuary as a Filter (ed.: V.S.Kennedy), Academic Press, New York, NY, 241-257 pp.
53
-------
Sholkovitz, E.R. 1976. Flocculation of dissolved organic and inorganic matter during the mixing
of riverwater and seawater. Geochim. Cosmochim. Acta 40: 831-845.
Sinex, S.A. and G.R. Helz. 1982. Entrapment of zinc and other trace elements in a rapidly flushed
industrialized harbor. Environ, Set. Technol 16: 820-825.
Skoghind, R.S. and D. L. Swackhamer. 1994. Fate of hydrophobic organic contaminants. In:
Environmental Chemistry of Lakes and Reservoirs (ed.: L.A. Baker), ACS Adv. Chem. Ser. 237,
American Chemical Society, Washington DC., 559-573 pp.
Sokol R.C., O-S. Kwon, C.M. Bethoney, and G.Y. Rhee. 1994. Reductive dechlorination of
polychlorinated biphenyls in St. Lawrence River sediments and variations in dechlorination
characteristics. Environ. Sci. Technol. 28: 2054-2064.
Stange, K. and D.L. Swackhamer. 1994. Factors affecting phytoplankton species-specific
differences in accumulation of 40 polychlorinated biphenyls (PCBs). Environ. Tax. Chem. 13:
1849-1860.
Stuermer, D.H. and J.R. Payne. 1976. Investigation of seawater and terrestrial humic substances
with 13C and 'HNMR. Geochim. Cosmochim. Acta 40: 1109-1114.
Stumm, W. and J.J. Morgan. 1981. Aquatic Chemistry. 2nd. Edition. Wiley-Interscience
Publications, New York, N.Y.
Swackhamer, D.L. and R.S. Skoglund. 1991. The role of phytoplankton in the partitioning of
hydrophobic organic contaminants in water. In: Organic Substances and Sediments in Water.
(ed.: R Baker). Lewis, Chelsea, MI, 91-105 pp.
Swift, D.J.P., A.W. Niedoroda, G.T.F. Wong, and D. Dauer. 1995. Residence time of particle
reactive pollutants in the coastal sea bed: Control by resuspension and sea bed mixing processes.
Worshop Report In: Chesapeake Bay Environmental Effects Studies, Toxics Research Program
1994 Preliminary results, (eds.: E.J. Olmi m, B. Hens, P. Hill, and J.G. Sanders). NOAA
Chesapeake Bay Office, Annapolis, MD.
Sunda, W.G. and R.R.L. Guillard. 1976. The relationship between cupric ion activity and the
toxichy of copper to phytoplankton. J. Mar. Res. 34: 511-529.
54
-------
Thomann, R.V. 1995. The significance of resource scale in water quality and ecosystem modeling
and decision making. In: Toward a Sustainable Coastal Watershed: The Chesapeake
Experiment, (eds.: P. Hill and S. Nelson) Proceedings of a Conference 1-3 June 1994, Norfolk,
VA. Chesapeake Reserach Consortium Pub. No. 149, CRC, Edgewater, MD.
Thomann, R.V., J.P. Connolly, and T.F. Parkerton. 1992. An equilibrium model of organic
chemical accumulation in aquatic food webs with sediment interaction. Environ. Tax. Chem. 11:
615-629.
Thomann, R.V. 1989. Bioaccumulation model of organic chemical distribution in aquatic food
chains. Environ. Sci. Technol. 23: 699-707.
Troup, B.N. and O.P. Bricker. 1975. Processes affecting the transport of materials from
continents to oceans. In: Marine Chemistry in the Coastal Environment (ed.: T.M. Church), ACS
Sym. Ser. 18, American Chemical Society, Washington, D.C., 133-151 pp.
U.S. Environmental Protection Agency. 1994. Deposition of Air Pollutants to the Great Waters.
EPA-453/R-93-055, Office of Air Quality Planning and Standards, Research Triangle Park, NC.
Velinsky, D.J. 1994. Loading estimates for specific chemical contaminants in Chesapeake Bay. In:
Chesapeake Bay Environmental Effects Studies: Toxics Research Program 1993 Workshop
Solomons, Maryland, (ed.: J.M. Jacobs). NOAA Chesapeake Bay Office, Annapolis, Maryland.
Velinsky, D.J., T.L. Wade, C. Schlekat and B.J. Presley. 1994. Tidal river sediments in the
Washington, D.C. area. I. Distribution and sources of trace metals. Estuaries 17: 305-320.
Velinsky, D.J., S. Schwartz, T.L. Wade, B.J Presley, and J. Cornwell. 1993. Sources and fluxes
of trace metals to the sediments of the tidal Anacostia River in Washington, D.C.. Presented at the
Estuarine Research Federation's 12th International Conference, Hilton Head, SC.
Warner, K.A., S. I. Hartwell, J.A. Mihursky, C. F. Zimmermann, and A. Chancy. 1992. The
Lower Patapsco River/Baltimore Harbor Contaminant Data Base Assessment Project-1991.
Bolt. Region. Council Govern., Baltimore, MD., 90 pp.
Whitehead, H.C. and J.H. Feth. 1964. Chemical composition of rain, dry fallout, and bulk
precipitation at Menlo Park, California, 1957-1959. J. Geophys. Res. 69: 3319-3330.
55
-------
Whitehouse, B. 1985. The effects of dissolved organic matter on the aqueous partitioning of
polynuclear aromatic hydrocarbons. Estuar. Coast. Shelf Sci. 20: 393-402.
Wild, S.R. and K.C. Jones. 1993. Biological and abiotic losses of polyaromatic hydrocarbons
(PAHs) from soils freshly amended with sewage sludge. Environ. Tax. Chem. 12: 5-12.
Windom, H.L., J.T. Byrd, R.G. Smith Jr., and F. Huan. 1991. Inadequacy of NASQAN data for
assessing metal trends in the nation's rivers. Environ. Sci. Technol. 25:1137-1142.
Yarbo, L.A., P.R. Carlson, T.R. Fisher, J.P. Chanton, and W.M. Kemp. 1983. A sediment budget
for the Choptank River estuary in Maryland, USA. Estoar. Coast. Shelf Sci. 17: 555-570.
Zoro, J.A., J.M. Hunter, G. Eglington, and G.C. Ware. 1974. Degradation of p,p-DDT under
reducing environments. Nature. 247: 235-237.
56
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