U.S. Department of Interior

Sediment Remobilization of Mercury

in South San Francisco Bay, California

U.S. GEOLOGICAL SURVEY 

Scientific Investigations Report 2004-5196

Historic Mercury Mining

Sediment Coring
Cover Graphics: A non-metallic sampling device 

(upper right insert) was used to collect sediment 

cores from South San Francisco Bay, down 

gradient of historic mercury mining (bottom left 

insert from Lanyon and Bulmore, 1967), for 

incubation experiments to measure the flux of 

dissolved-mercury species across the sedimentwater interface. 
Sediment Remobilization of Mercury 

in South San Francisco Bay, California 

U.S. GEOLOGICAL SURVEY 

Scientific Investigations Report 2004-5196 

1
Sediment Remobilization of Mercury in South San Francisco 

Bay, California 

By Brent R. Topping1

, James S. Kuwabara2, Mark C. Marvin-DiPasquale3, Jennifer L. Agee4, Le 

H. Kieu5

, John R. Flanders6, Francis Parchaso7, Stephen W. Hager8, Cary B. Lopez9, and 

David P. Krabbenhoft10 

U.S. GEOLOGICAL SURVEY 

Scientific Investigations Report 2004-5196 

1 btopping@usgs.gov, U.S. Geological Survey, Menlo Park, CA 

2 kuwabara@usgs.gov, U.S. Geological Survey, Menlo Park, CA 

3 mmarvin@usgs.gov, U.S. Geological Survey, Menlo Park, CA 

4 jlagee@usgs.gov, U.S. Geological Survey, Menlo Park, CA 

5 lhkieu@usgs.gov, U.S. Geological Survey, Menlo Park, CA 

6 jflander@usgs.gov, U.S. Geological Survey, Menlo Park, CA 

7 parchaso@usgs.gov, U.S. Geological Survey, Menlo Park, CA 

8 swhager@usgs.gov, U.S. Geological Survey, Menlo Park, CA 

9 cblopez@usgs.gov, U.S. Geological Survey, Menlo Park, CA 

10 dpkrabbe@usgs.gov, U.S. Geological Survey, Middleton, WI

2
U.S. DEPARTMENT OF THE INTERIOR 

GALE A. NORTON, Secretary 

U.S. GEOLOGICAL SURVEY

CHARLES G. GROAT, Director 

For additional information, contact: Copies of this report may be 

obtained from the authors or 

Brent R. Topping 

U.S. Geological Survey 

345 Middlefield Road, MS 439 

Menlo Park, CA 94025 

 

U.S. Geological Survey 

Information Center 

Box 25286, MS 517

Denver Federal Center 

Denver, CO 80225

3
TABLE OF CONTENTS

Executive Summary........................................................................................................................ 5 

Physical and Biological Characterizations.......................................................................... 5 

Chemical Characterizations................................................................................................ 6 

Remedial Implications........................................................................................................ 7 

Background..................................................................................................................................... 8 

Results and Discussion ................................................................................................................. 10 

Physical Data .................................................................................................................... 10 

Biological Data ................................................................................................................. 10 

Chemical Data................................................................................................................... 11 

Study Design and Methods........................................................................................................... 18 

Coring Operation .............................................................................................................. 18 

Core Incubations............................................................................................................... 18 

Physical Data .................................................................................................................... 19 

Biological Data ................................................................................................................. 19 

Chemical Parameters ........................................................................................................ 19 

References Cited ........................................................................................................................... 22 

Acknowledgments......................................................................................................................... 27 

Appendix 1: Comments on the Report Structure.......................................................................... 28 

Appendix 2: List of Figures.......................................................................................................... 29 

Appendix 3: List of Tables ........................................................................................................... 30

 

4
Sediment Remobilization of Mercury in 

South San Francisco Bay, California 

By Brent R. Topping, James S. Kuwabara, Mark C. Marvin-DiPasquale, 

Jennifer L. Agee, Le H. Kieu, John R. Flanders, Francis Parchaso, Stephen W. Hager, 

Cary B. Lopez and David P. Krabbenhoft 

Executive Summary 

Field and laboratory studies were conducted in April and November 2003 to provide the first direct 

measurements of the benthic flux of dissolved (0.2-micrometer filtered) mercury species (total and methylated

forms) between the bottom sediment and water column at two sampling locations within the southern component of

San Francisco Bay, California (hereafter referred to as South Bay): one within the main channel and the other in the 

western shoal area (Fig. 1). Because of interest in the effects of historic mercury mining (Fig. 2) within watersheds 

that drain into South Bay, the solutes of primary interest were dissolved-mercury species and the predominant

ligands that often control mercury speciation (dissolved sulfide and dissolved organic carbon). Benthic flux, 

sometimes referred to as internal recycling, is the transport of dissolved chemical species between the water column

and the underlying sediment. Because of the affinity of mercury to adsorb onto particle surfaces and to form

insoluble precipitates (particularly with sulfides), the mass transport of mercury in mining-affected watersheds is 

typically dominated by particles. As these enriched particles accumulate at depositional sites such as estuaries and 

reservoirs, benthic processes facilitate the repartitioning, transformation, and transport of mercury in dissolved, 

biologically reactive forms (dissolved methyl-mercury being the most bioavailable for trophic transfer). These are 

the forms of mercury examined in this study. 

During two sampling events, three replicate sediment cores (Coring methods; Fig. 3) from each of two 

South Bay locations (Station 29A, a deep, main-channel site; and Station 25, a western shoal site; Fig. 1) were used

in incubation experiments to provide flux estimates and benthic biological characterizations. Incubation of these 

cores provided “snapshots” of solute flux across the sediment-water interface in this component of the estuary, under 

environmental conditions representative of the time and place of collection. Ancillary data, including nutrient and

ligand fluxes, were gathered to provide a water-quality framework from which to compare the results for mercury. 

The following major observations from interdependent physical, biological, and chemical data were made: 

Physical and Biological Characterizations

1. Porosity: The surficial sediment at Station 29A was generally of higher porosity than that at Station

25 on both sampling dates. Station 29A porosities ranged from 0.77 to 0.92 (0.84 + 0.05), while those 

of Station 25 ranged from 0.73 to 0.82 (0.77 + 0.04). This difference, however, is not statistically 

significant at the 95% confidence interval. 

2. Benthic Biota: Macroinvertebrate densities varied temporally and spatially (Table 1), in a manner 

consistent with previous studies (Topping and others, 2001; see macroinvertebrate discussion). Given

that the first sampling event coincided with the annual spring phytoplankton bloom in the South Bay,

Chlorophyll and phaeophytin concentrations (Table 2) also exhibited temporal and spatial differences. 

See the results section for details.

5
6

Chemical Characterizations 

Note: The dissolved-mercury concentrations discussed in this section refer to samples filtered 

with 0.7-micrometer quartz-fiber filters pre-combusted at 500 o

C for 12 hours. 

1. Dissolved mercury in the water column: Dissolved methyl-mercury concentrations were below 

detection limits at all sites and dates. Total dissolved-mercury concentrations ranged from ~4 to 

~10 picomolar, so the undetectable methyl-mercury values were not surprising because total 

mercury concentrations are typically two or more orders of magnitude greater than methylmercury concentrations. Total dissolved-mercury concentrations were appreciably elevated at the 

western-shoal Station 25 relative to the main-channel Station 29A, and in spring relative to 

autumn. (Table 3, Mercury results). 

2. Benthic flux of dissolved forms of mercury: When the three cores for each site were averaged, benthic 

flux estimates for total dissolved-mercury showed no temporal change for Station 25, but showed 

higher flux in spring relative to fall for Station 29A (Table 4). Still, the averages for each site and 

date were within the same order of magnitude. When the average for all sites and dates (135 + 94 

g/day; Table 4) is extrapolated over the greater South Bay, the magnitude of the values is 

consistently comparable to or greater in magnitude than estimates of major riverine sources (Fig. 

4). Notably, benthic flux of dissolved mercury is of the same magnitude as particulate mercury 

inputs from the Guadalupe River watershed (318 + 88 g/day in 2003; McKee 2004, draft copy). 

Transport of dissolved-mercury species between the estuary bed and water column may therefore 

be a potentially critical process regulating the fate of mercury species in the water column 

(Mercury flux discussion). 

All twelve individual core incubations in the study resulted in positive total-mercury flux values 

(Table 4). In other words, at all sites and dates, each core indicated that dissolved total mercury 

was transported out of the sediment into the overlying water column. 

Dissolved methyl-mercury fluxes could not be directly calculated due to the undetectable values 

for all sites and dates (<0.5 picomolar in May, <0.2 picomolar in November). These undetectable 

values are common and have been observed in other studies (Conaway and others, 2003). 

However, when comparing loads of dissolved methyl-mercury into South Bay, benthic flux cannot 

be summarily discounted as a possible source due to analytical limitations (Load comparison 

discussion). 

Ancillary measurements characterizing the sediment were compared with water-column and 

benthic flux values. Four correlations were observed including sediment mercury’s correlation 

with benthic flux of dissolved mercury (Ancillary sediment characterization discussion). 

3. Benthic flux of mercury-binding ligands: 

Dissolved-sulfide benthic fluxes were similar at all dates and sites (Table 5), and consistently 

positive. Sulfides are associated with reducing conditions, so the similarities at all stations and 

dates might indicate reducing-oxidizing (redox) conditions were similar throughout the study, 

despite significantly higher dissolved oxygen (DO) consumption in May (DO discussion). Given 

that the South Bay water column is consistently oxic (that is, dissolved-sulfide species are only 

metastable), the relative consistency of the mercury fluxes maybe associated with the flux of 

sulfides, which have a strong affinity to complex with mercury. 

 

Dissolved organic carbon (DOC) fluxes were markedly different between sites and significantly so

between dates (Table 6; Fig. 5). Autumn fluxes were much higher than spring fluxes at both sites,
while Station 29A exhibited higher fluxes than Station 25 for both dates. Unlike sulfides, negative 

DOC fluxes (solute transport from the water column to the bottom sediment) were observed in

some cores. 

4. Benthic flux of other metals: 

Comparisons between this study and a previous one by the authors (Topping and others, 2001)

indicated that 2003 conditions may be less conducive to metal remobilization and release than in

previous years (Dissolved nickel and copper discussion). This indicates that estimates of longterm mercury flux could be incorrectly low if based only on 2003 sampling. 

Upgradient Remedial Implications 

Because the benthic flux of mercury appears to represent a dominant transport process for dissolved, more 

bioavailable forms, an important management implication is suggested. Remediation efforts and Total Maximum

Daily Load (TMDL) allocations along the Guadalupe River have dual objectives of decreasing concentrations and 

loads to down-gradient systems in an effort to reduce bioaccumulation of mercury in fish consumed by humans and

wildlife. Using preliminary mercury-flux estimates into the estuary, our results indicate that a significant (and

possibly predominant) percentage of dissolved mercury in the water column presently comes from the bay sediment

(Mercury flux discussion). If upstream sources are controlled, which is desirable even apart from estuary effects, the

change in inflow loads is likely to be compensated in part by increases in benthic flux (Fig. 6). 

Comment on the Report Structure

In contrast to typical scientific manuscripts, this report is formatted in a pyramid-like structure to serve the 

needs of diverse groups who may be interested in reviewing or acquiring information at various levels of technical

detail (Appendix 1). The report enables quick transitions between the initial summary information (figuratively at 

the top of the pyramid) and the later details of methods or results (figuratively towards the base of the pyramid)

using hyperlinks to supporting figures and tables, and an electronically linked Table of Contents. 

7
Background 

 South San Francisco Bay and the Guadalupe River watershed represent a CERCLA (Comprehensive 

Environmental Response Compensation and Liability Act) site affected by drainage from the New Almaden mines. 

Mercury at the New Almaden mines, and more generally in California coastal ranges, was hydrothermally deposited

under silica carbonate formations during the Cenozoic Era (Rytuba and Enderlin, 1999). These cinnabar (mercury

sulfide) ores were mined, heat-processed and distilled to acquire elemental mercury. The mines, a National Historic 

Landmark since 1975, are historically significant on many spatial scales. In full operation by 1850, it was the first 

large-scale mining operation in California. The New Almaden mines are the most productive mercury mines in the 

history of the United States with total production exceeding 30 million kilograms of elemental mercury. Globally, 

discovery of and production from this location, fortuitously timed just prior to the California gold rush (Alpers and 

Hunerlach, 2000), freed the United States from an existing monopoly of the mercury market by the House of 

Rothschild in England (Goss, 1958; Johnson, 1963; Lanyon and Bulmore, 1967; Schneider, 1992). Acknowledging

these important economic contributions to the burgeoning state, the New Almaden mines also leave a troublesome

legacy. Notably, 600,000 m3

 of calcine (heat-processed cinnabar) now resides within the freshwater and estuarine 

aquatic systems of the Santa Clara Valley watersheds. This legacy provides many reasons to suspect that sedimentwater interactions significantly affect the geochemical and biological distributions of mercury in South San 

Francisco Bay. 

Many fundamental processes affect the transport of dissolved-chemical species (for example, nutrients, 

metals, ligands) through and within aquatic systems. A conceptual model of these processes (Fig. 7) illustrates some

physically based processes that have been examined and carefully quantified in a number of previous studies (for 

example, advective transport and point source inputs; Fischer and others, 1979). 

There are, however, terms in the conceptual model that have until recently received little attention. A 

prime example is the benthic flux term. No direct measurements for dissolved-mercury species have heretofore 

been available for the study area, or for adjacent areas currently beginning extensive wetland-restoration of former 

salt ponds (website: http://www.southbayrestoration.org/). Benthic flux (sometimes referred to as internal recycling) 

represents the transport of dissolved chemical species between the water column and the underlying sediment. Flux 

of solutes can be either positive (into the water column from the sediment or atmosphere) or negative (out of the 

water column into the sediment or atmosphere) and can vary over multiple temporal and spatial scales (Kuwabara 

and others, 2002; Kuwabara and others, 2003a). 

As a result of physical, chemical, and biological processes operating near the sediment-water interface, 

geochemical gradients take on a variety of forms that have been previously reported (Kuwabara and others, 2000;

Fig. 6). Associated gradients in solute concentrations can thereby result in a benthic flux of that solute that may be

negative or consumed by the sediment, positive or released from the sediment, or insignificant when the gradient

is indistinguishable. When interdependent factors regulate the benthic flux of biologically reactive substances, the 

vertical gradient for one dissolved species may be dependent on the gradient of another chemical species. For 

example, an attenutated release may occur when solute concentrations increase below the sediment-water interface 

only when another solute is depleted. Redox-sensitive solutes like dissolved iron often behave in this manner when

suboxic conditions reduce it from ferric (Fe+3) to ferrous (Fe

+2) forms, increasing its solubility and releasing 

adsorbates. Macrofauna can also enhance benthic flux by irrigating or disturbing surficial sediment layers 

(bioirrigation, bioturbation, or biologically enhanced advection). Certain productive benthic communities can

enhance benthic flux by orders of magnitude beyond diffusive-control (Kuwabara and others, 1999a, Thibodeaux

and Bierman, 2003), while other communities are too sparse to generate this magnitude of enhancement (Kuwabara 

and others, 2003b). Therefore, vertical chemical gradients generated by a variety of interdependent biogeochemical 

processes can induce the transport of dissolved-mercury species across the sediment-water interface in estuarine

systems. 

Scientists and water-quality managers are only beginning to understand the importance of benthic flux in

many aquatic environments. Within the past decade or two, researchers have gradually realized that there are nonhydrologic processes (for example, benthic flux) that must be incorporated into water-quality models in order to 

generate physically meaningful information. Unfortunately, benthic-flux determinations are instrument and

manpower intensive, because each flux estimate requires complex sample collection procedures and a concentration 

time-series analysis or vertical-profile analysis. Benthic-flux studies have consequently lagged behind studies of

8
other transport processes, but are spurring interest in both the scientific and management communties (Kuwabara 

and others, 2003b). 

Water-quality managers often assess and prioritize remediation strategies for aquatic systems that have

been adversely affected by anthropogenic activities. In the case of South San Francisco Bay, directly down gradient

of the Guadalupe River, mercury associated with decades of productive mining at the historic New Almaden 

Quicksilver Mine has been fluvially transported and accumulated in the bottom sediments. Frequent demands have

been made by regional managers and the public to quantify the connections between fluxes of contaminants and the 

health, abundance, and distribution of biological resources (Kuwabara and others, 1999a). As part of ongoing

efforts to examine processes affecting trace-contaminant transport in San Francisco Bay, this study focuses on a 

poorly understood, yet potentially predominant, source of mercury to the estuary’s water column: internal recycling,

or benthic flux of mercury species and associated ligands. Mobilization, flux, and biological availability of mercury 

into the water column are affected by physical (for example, advection and diffusion), chemical (that is, oxidationreduction reactions, complexation and repartitioning) and biological processes (for example, bioirrigation and

bioturbation) (Flegal and others, 1991; Kuwabara and others, 1996; Grenz and others, 2000, Topping and others, 

2001).

The results described herein followed from the integration of current project studies with information needs 

identified by the San Francisco Estuary Institute to provide initial determinations of dissolved total and methylmercury fluxes from the sediments into the water column of South San Francisco Bay. Beyond the ecological status 

of the system, elevated mercury concentrations in fish require consumption advisories relating to human health

(http://www.oehha.ca.gov/fish.html). Quantifying and understanding the magnitude and variability of these fluxes is 

critical to the accurate assessment of contaminant sources and loads as well as to the development of appropriate 

water-quality models and remedial programs for this mining-affected system. 

To help enable science based programmatic decisions related to water and ecosystem quality in San

Francisco Bay, the purpose of this study is to quantify sources and sinks of dissolved total mercury and dissolved

methyl-mercury associated with the bottom sediment within the South Bay relative to major surface-water inputs 

from the major tributaries. Owing to past mercury mining, fluvial inputs need to be compared quantitatively to the 

internal source of mercury. Also, there is a growing body of evidence from other aquatic systems that benthic flux

of contaminants and nutrients is an important process to consider in developing appropriate ecosystem water-quality 

models (Wood and others, 1995; Rivera-Duarte and Flegal, 1997; Topping and Kuwabara, 2003). Thus, the need

clearly exists for more refined conceptual and numerical models describing mercury dynamics within the South Bay.

9
Results and Discussion 

Physical Data

Sediment texture and color were visually similar at both the western shoal site (Station 25) and the 

deep, main-channel site (Station 29A). At each site, the sediment is composed largely of finegrained silts and clays. This sediment composition facilitates core-tube penetration and sedimentcore retention. Main-channel porosities had a mean of 0.84 + 0.05, and a range of 0.77 to 0.92. 

Western shoal porosities had a mean of 0.77 + 0.04, and a range of 0.73 to 0.82. The difference in

means superficially favors Station 29A, but it is not statistically significant at the 95% confidence

interval shown. 

Biological Data

1. Benthic macroinvertebrates: In certain aquatic environments, bioturbation and bioirrigation by benthic 

macroinvertebrates can significantly affect the benthic flux of solutes (Charbonneau and others, 

1997; Kuwabara and others, 1999a). Thus, macroinvertebrate taxonomies (Table 1) provide useful

characterization of the benthic community. For example, Corophium sp. and Ampelisca abdita, 

which have been shown to enhance solute benthic flux by their feeding and sensing behaviors 

(Miller, 1984; Word, 1980), are the dominant crustaceans at both sites and dates. However, there 

is a scarcity of knowledge of species-specific data regarding biological effects on flux values. 

Aller and Aller (1998) showed how increased macroinvertebrate density led to exponentially

higher flux values for manganese, but these results can’t be assumed to translate to mercury or

other solutes. However, Choe and others (2004) found that estimated diffusive fluxes of mercury

were only a small portion of the directly measured benthic flux. Because it is difficult to quantify 

the effect of these biological activities, this macroinvertebrate density information only serves as a 

qualitative description of the benthic community’s potential impact on the benthic flux of solutes. 

Due to the compilation of a similar dataset in 1998/1999, which appears in Topping and others, 

2001, comparisons can be made regarding long-term, as well as short-term, temporal variability. 

At Station 25, samples were taken in April and September, 1998, allowing for comparisons 

between spring and fall sampling. Paralleling 1998, Station 25 showed increases, from spring to

fall, in annelid and mollusc biomass, but showed a marked decrease in crustacean biomass in 

2003. Mollusc biomass fell precipitously from fall 1998 to fall 2003. 

Station 29A was sampled only in May, 1999 in the previous study, so comparisons can only be

made between spring dates. Total biomass of crustaceans and molluscs were similar in spring 

between 1999 and 2003, but annelid biomass was orders of magnitude higher in 2003. 

In terms of individuals per square meter, the colloquially-named “Bamboo worm”, Sabaco

elongatus, is the most abundant macroinvertebrate in fall 2003 at both sites. It is also relatively 

plentiful in the spring samples. Curiously, this invasive polychaete was nearly absent from all

samples in 1998/1999, despite being described as abundant at earlier dates (Nichols and 

Pamatmat, 1988). Conversely, notably absent from the 2003 sampling was the Asian clam

Potamocorbula amurensis, which was relatively numerous at Station 25 in 1998. 

2. Benthic chlorophyll-a: Chlorophyll-a (chl-a) concentrations in surficial sediments ranged from < 0.1 

up to 4.7 micrograms per square centimeter with the highest concentrations observed at the shoal

site during the spring sampling, and the lowest concentrations at the main-channel site during the 

fall sampling (Table 2). This data coincides with the spring phytoplankton blooms, which

deposits chl-a on the sediment as it settles gravitionally. The concentration ratio of chl-a to chl-a 

10
plus phaeo-pigments (CCP ratio) is used as a crude indicator of the extent of senescence in an

algal population (Thompson and others, 1981; Kuwabara and others, 1990). Ratios greater than

0.5 indicate active growth, and values less than 0.5 suggest enhanced pigment degradation 

associated with cell senescence or predation pressures that process the chlorophyll-a to

degradation products. Predictably, the benthic CCP ratio for the spring sampling (0.15 + 0.10, 

n=6) was significantly higher than the fall (0.02 + 0.02, n=6). This seasonal discrepancy is typical

for the South Bay due to its regular springtime phytoplankton blooms (Cloern, 1996). 

Chemical Data

For consistency with previous geochemical studies, mercury flux estimates are presented in massflux units, but were also tabulated in molar units. 

1. Dissolved oxygen (DO) benthic flux: While spatial differences were not apparent, seasonal differences 

were significant for dissolved oxygen consumption from the water column (Table 7). The cores

taken in spring averaged a dissolved oxygen flux of -4.6 + 0.3 millimoles per square meter per 

hour, while the autumn cores averaged -3.3 + 0.5 millimoles per square meter per hour. This 

difference could be caused by phytoplankton respiration since the benthic chl-a values were higher 

in the spring, and the experiment was conducted in near darkness. Oxygen consumption rates for

both sites were high relative to previous experiments at the same location by the authors (results 

unpublished). This could indicate a more active than normal bacterial population. In fact, the 

dissolved oxygen concentrations in the cores’ overlying water were all suboxic (~1 mg/L 

dissolved oxygen) in May 2003. These levels of oxygen could alter the redox (reductionoxidation) conditions, and may affect the flux of certain solutes from the sediment (Mercury flux

discussion) 

2. Dissolved mercury in South Bay bottom waters: (Note: Error values in this section reflect standard

deviations due to low sample replication) At both sampling sites, higher dissolved total-mercury 

concentrations (Table 3) were observed in May relative to November. At Station 25, which was 

only sampled at one depth due to its shallowness, samples measured 10.0 + 0.2 picomolar in May,

but only 5.7 + 0.9 picomolar in November. At Station 29A, a 3-point water-column profile was 

taken encompassing shallow, mid-depth, and bottom water samples. In the case of the shallow 

samples (7.0 + 0.1 picomolar in May; 4.7 + 0.1 picomolar in November) and the mid-depth 

samples (6.8 + 0.0 picomolar in May; 3.8 + 0.1 picomolar in November), this difference quite 

pronounced, as at Station 25. The bottom water samples (5.4 + 0.5 picomolar in May; 4.8 + 0.2 

picomolar in November) at Station 29A do not exhibit this seasonal difference at a statistically 

significant level. Conaway and others, 2003, analyzed surface-water samples for total-dissolved 

mercury at the three South Bay sites that are geographically near our stations. The authors 

observed a range in values from 0.9 to 6.8 picomolar for fourteen samples taken in 1999-2000. 

Within each Station 29A profile, the vertical concentration gradient can be investigated to reveal

benthic sources or sinks. In May, the lower concentrations at depth are counter-indicated with our 

positive mercury benthic flux data, which would suggest that bottom-water concentrations would

be elevated. However, the estuary is vertically well-mixed, and any gradients established by

benthic flux would not be maintained. In November, the concentration minimum was found at

mid-depth, but the shallow and deep samples were very similar. 

All methyl-mercury concentrations were below detection limits (reported as 0.5 picomolar in May 

and 0.2 picomolar in November). Conaway and others, 2003, also reported consistently low 

values at the aforementioned sites. Reporting a detection limit of 0.05 picomolar for dissolved 

methyl-mercury, the authors observed a range from <0.05 to 0.4 picomolar for eight samples taken 

in 1999-2000. 

11
3. Mercury benthic flux: In contrast to typical management strategies which focus on particulate mercury

that dominates total loads to the estuary, this study focused on dissolved, more bioavailable, 

species. Mercury has a very high affinity for binding with particles, but the mercury remaining in

solution has the potential to be bioaccumulated and biomagnified up the food chain, potentially

resulting in human-health fish-consumption advisories (Abu-Saba and Tang, 2000). 

Dissolved total-mercury fluxes were positive (that is, out of the bed sediment) in all six core 

incubations in May 2003 and all six core incubations in November 2003. Fluxes, averaged at each 

site/date, were greatest at Station 29A in May and lowest at the same station in November. 

However, site/date average fluxes were within the same order of magnitude (Table 4; values are

given in both molar and mass units). While the largest site/date average flux was seen at Station 

29A in May, this value is driven mostly by one elevated value (Core 5). In fact, all but three of 

the twelve core incubations produced calculated fluxes between 18 and 54 picomoles per square 

meter per hour, indicating a relatively consistent flux at all times and sites. For comparison, 

similar studies done for mercury-impacted Sierra Nevada reservoirs (Kuwabara and others, 2002;

Kuwabara and others, 2003a) produced a range of values from 80 to 1600 picomoles per square 

meter per hour.

Due to the elevated dissolved-oxygen consumption mentioned above (DO discussion), the final 

time-point (12 hours; see Methods) for all May cores was suboxic (~1 mg/L dissolved oxygen in

the water overlying the sediment core). This is atypical in the South Bay, where bottom waters are 

predominantly near DO saturation (Cloern and others, 2003). Thus, it is possible that mercury

fluxes could have been affected during the last interval of the incubations due to redox-driven 

dissolution or complexation dynamics. To address this concern, mercury fluxes were recalculated, 

excluding the final time-point in each May core, but the results were very similar to those using

the entire time series (Table 4). Also, others have found that mercury fluxes appeared higher 

under oxic conditions than suboxic (R. Mason – personal communication, Sept. 2004). 

Load comparisons: For purposes of comparison to loads from the Guadalupe River watershed, the 

South Bay flux values were converted to g/day (loading) by extrapolating these fluxes over the

entire South Bay (south of the Bay Bridge) surface area (554 km2

; Cheng and Gartner, 1985). 

Considering the relative consistency of the values, an average of all sites/dates was used for 

comparisons. Thus, it is estimated that 135 +/- 94 g/day of dissolved mercury fluxes into the bay 

from the sediment (Table 4).

Mercury concentrations and river discharges were measured in a dry-season scenario (TetraTech, 

2003) within the Guadalupe River watershed. The report calculated a range of 0.1-0.3 g/day of

dissolved mercury for a late-July, low-flow condition (Fig. 4). Although Hg measurements were 

not made during a high-flow storm in December 2002, assumptions were made based on the 3 

orders of magnitude increase in flow. While particulate concentrations increase exponentially 

with flow, dissolved-Hg concentrations remain steady (presumably due to the balanced effects of

dissolution, adsorption/desorption and dilution). Thus, if it’s assumed that dissolved-mercury 

loads would increase in proportion to river discharge, these assumptions lead to a loading estimate 

of 100-300 g/day for dissolved Hg from the Guadalupe River during a high-flow event (Fig. 4). 

Additionally, data from Thomas and others (2002) can be used to calculate a load of 1.2 g/day of

dissolved mercury during a lesser rain event in October 2000. 

Based on these preliminary loading estimates, this comparison indicates that benthic flux from the 

sediment is likely to be a dominant source of dissolved Hg to the water-column particularly during

the dry season (May-Oct). Furthermore, historic meteorological data (Goodridge, 2000) indicate 

12
that >90% of the days in the region are without significant precipitation, suggesting that the 

temporal importance of benthic flux could extend well beyond the dry season. Furthermore,

McKee and others (2004, draft copy) found that particulate mercury loading occurs episodically

(66% in one month for the study year), and that most days do not contribute appreciably to their

113 kg/year estimate of particulate mercury loading to lower South Bay.

Since all dissolved methyl-mercury concentrations were below detection limits, no methylmercury fluxes could be estimated. However, calculations were made that indicate that benthic 

flux could still provide a source similar to, or greater than, watershed inputs for dissolved methylmercury. Loading estimates (TetraTech, 2003) for dissolved methyl-mercury produce a range

from 0.002 to 0.005 g/day for a dry-season scenario. In order for the 12-hour core incubation to

produce a flux that would extrapolate to 0.005 g/day, dissolved methyl-mercury concentrations in

the incubated cores would only have needed to increase by 0.02 picograms per liter (0.0001 

picomolar), which is more than 3 orders of magnitude below the detection limit. To equal a wetseason estimate (5 g/day), the concentration change would need to be 0.02 nanograms per liter, 

which is near the detection limit. Therefore, given the low dissolved methyl-mercury

concentrations in the South Bay water column and inflowing major rivers like the Guadalupe, the 

analytical detection limits may mask the relative importance of the benthic flux of dissolved

methyl-mercury. Although the design of our incubation experiment raises the method detection 

limit through volume restrictions, Conaway and others, 2003, despite lower detection limits, also 

couldn’t observe the miniscule concentration difference required to produce a significant dryseason flux. 

If management directives focus solely on the inputs of particulate mercury, the effect of such

policies on mercury accumulation in fish, and other higher trophic level organisms consumed by 

humans, would not account for dissolved mercury contributed by benthic flux. It has been shown 

that sediment mercury concentrations are decoupled from bioavailability and thus bioaccumulation

in organisms (Mason and Lawrence, 1999; Watras and others, 1998). Reducing all point-source

inputs of Hg to the estuary may provide a very limited solution because 1) the benthic source has

accumulated for over a century could remain indefinitely, and 2) even pristine aquatic 

environments with no point source Hg inputs (U.S. EPA, 1997) have mercury-related fish

consumption advisories. Consistent with that finding, San Francisco Bay has similar advisories 

(Abu-Saba and Tang, 2000) despite dissolved methyl-Hg concentrations that are at times below 

detection limits (Conaway and others, 2003), as observed in our study. Also, Looker and Johnson 

(2003) estimate a long-term average load of 252 g/day of particulate mercury from the Guadalupe

River watershed into the South Bay (Fig. 4), which is of the same order of magnitude as the 

estimate for benthic flux of dissolved mercury (135 g/day). 

4. Dissolved sulfide: Sulfide flux was consistently positive (that is, from the sediment to the overlying

water column) and ranged from 564 to 786 nanomoles per square meter per hour (average of three 

replicates per site per date; Table 5). At each date, the sulfide flux was appreciably higher at 

Station 29A, but the temporal changes are not strongly apparent at each station. These fluxes are

significantly higher for two of the three matching station/season measurements done by Topping

and others, 2001. 

Dissolved-sulfide concentrations were below detection limits (<4 nanomolar) in the bottom water. 

A less sensitive method (ion-selective electrode; detection limit: 0.2 micromolar) used for 

porewater found detectable sulfides at only one site date: 0.58 micromolar at Station 29A in

spring. Using this concentration, and assuming a 4 nanomolar bottom water concentration, a 

diffusive flux from the benthos was calculated with a diffusion coefficient of 1x 10-5 square 

centimeters per second (Li and Gregory, 1974). The calculated diffusive-flux estimate was 104

nanomoles per square meter per hour, while the directly measured sulfide flux at Station 29A 

13
(Table 5) in spring averaged 751 nanomoles per square meter per hour. This large difference 

between a measured and a calculated flux suggest that bioturbation or bioirrigation have enhanced

the flux beyond what would be expected from diffusion alone. Benthic macroinvertebrate 

densities have been linked to relative enhancement of benthic flux in other mining-affected aquatic 

systems (Caffrey and others, 1996; Kuwabara and others, 1999a; Kuwabara and others 2003a;

Thibodeaux and Bierman, 2003). 

Dissolved sulfide is a metastable ligand in most surficial environments and has a high affinity to

complex most divalent metals. This sulfide-complexing effect is particularly strong for mercury,

which has a logarithmic mercuric-sulfide solubility product of approximately –50 (Hogfeldt, 

1983). At thermodynamic equilibrium, the product of the molar concentrations of uncomplexed

mercury and uncomplexed sulfide ions is therefore expected to be very low (of the order of 10-50) 

due to the formation of mercuric sulfide. As the presence of DOC facilitates the dissolution or

desorption of particle-associated mercury, and subsequent flux of dissolved mercury species, the

presence of sulfides can conversely facilitate precipitation and decreased solubility of mercury, 

inhibiting benthic flux. 

5. Dissolved organic carbon (DOC): DOC concentrations serve as an indicator of the presence of organic 

ligands that can complex and enhance the solubility of trace metals including mercury (Kuwabara 

and others, 2003a). The partitioning and speciation of certain metals in aquatic systems are 

significantly affected by organic complexation (Mantoura and others, 1978; McKnight and others, 

1983), and this effect is particularly important for mercury. Ligands represented by dissolved 

organic carbon can compete with sulfide to regulate mercury solubility and hence mobility (see 

section 7 below, Ravichandran and others, 1998) and can also decrease the bioavailability of

mercury to certain aquatic biota (Sjoblom and others, 2000). 

The benthic flux of DOC was dramatically different between seasons with November values much 

higher than those in May (Table 6; Fig. 5). This difference was most dramatic at Station 29A 

where May values averaged 27 micromoles per square meter per hour, while in November this

value averaged 1302. At Station 25, these values were -135 and 371, respectively. Despite this 

dramatic change in values, and the afore-mentioned potential DOC regulation of mercury

solubility, the mercury flux values were relatively consistent (mercury discussion). Negative 

DOC fluxes (that is DOC consumed by the sediment), as observed at Station 25 in May, have been

reported, but are atypical (Caffrey and others, 1996). However, individual cores, but not site 

averages, showed negative DOC fluxes in Topping and others, 2001. 

DOC bottom-water concentrations varied little temporally at Station 25. At Station 29A, while 

they did not exhibit a water-column concentration gradient in either season, the bottom-water 

concentration was much lower in November (154 micromolar) than May (219 micromolar). If

sediment porewater concentrations remained the same, the low November value would have

created a larger concentration gradient, and this could account for the increased DOC flux at 

Station 29A in November. Although the relationship was not linear, the highest bottom-water 

DOC concentration corresponded to the highest dissolved total mercury concentration (Station 25

in May). 

6. Benthic flux of other dissolved metals: Additional dissolved metals, nickel and copper, were analyzed 

and compared to previous measurements to determine how 2003 compares in terms of metal 

mobilization. Dissolved-metal concentrations for nickel (Ni) in the water column did not indicate 

a vertical concentration gradient (Table 8). For nickel, concentrations in the bottom water were 

generally lower in 2003 than 1998/1999 (Topping and others, 2001). At Station 25, this was most

pronounced in the fall (23 nanomolar in 2003, 43 in 1998/99) but was also witnessed in the spring

14
samplings (30; 34). Station 29A, with only a spring comparison possible, reflected this trend as 

well (25; 28). 

Copper (Cu) concentrations (Table 8) weren’t previously published in Topping and others, 2001,

so no semi-decadal comparisons can be made. However, copper concentrations were significantly 

lower in the bottom water relative to the surface and mid-depth at Station 29A in May 2003. This 

is indicative of either a benthic sink or a water-column source. This vertical gradient was not

observed in November 2003.

Dissolved-nickel benthic flux in 2003 was anomalous relative to values from the previous five

years using the same methods at the same stations (Topping and Kuwabara, 2003). From 1998

through spring 2002, only 4 individual cores out of 34 exhibited a negative flux. In 2003, 5 of 12

values were below zero, with all five occurring from Station 25 samples. In fact, the average for

all Station 25 flux estimates in 2003 was -10 + 22 (n=6) nanomoles per square meter per hour,

while at Station 29A this value was 62 + 47 (n=6). This higher nickel flux at Station 29A relative 

to Station 25 was also observed from 1998 through spring 2002, but to a lesser extent. 

Dissolved-copper benthic flux was also somewhat unusual in 2003. Although copper fluxes were

variable in direction, the majority were negative, and the mean of all 2003 values (-35 + 37

nanomoles per square meter per hour, n=12) is appreciably lower than those observed in Topping

and others, 2001 (approximately 3 nanomoles per square meter per hour).

Combined, these data suggest that conditions during our sampling events in 2003 were less 

conducive to metal remobilization and release from bed sediments than previously observed. This

indicates that estimates of long-term mercury flux could be incorrectly low if based only on 2003

sampling. However, others have found little relationship between mercury flux and the flux of 

other trace metals (R. Mason – personal communication, Sept. 2004).

7. Nutrient benthic flux: Dissolved nutrients exhibited interesting trends with regards to benthic flux. 

Ammonia flux was noticeably higher in May relative to November (Table 9), and this temporal 

shift was most prominent at Station 25. Higher ammonia flux is often associated with more

reducing conditions; however, this is not consistent with ancillary sediment characterization data 

(Table 10) which showed both stations to be more reducing in November.

Orthophosphate fluxes, which are often linked to adsorption-desorption reactions onto ferric oxide 

surfaces, showed no significant temporal change, but did show a prominent spatial difference. 

Fluxes were all below zero at Station 29A, but all positive at Station 25. The negative values at 

Station 29A are not necessarily indicative of regular conditions: Topping and others, 2001, found

positive orthophosphate fluxes at Station 29A in May 1999 (no nutrient flux data was available for 

Station 25). 

 

In aquatic systems where phytoplankton assemblages are dominated by diatoms, benthic fluxes of

silica are used to estimate the dissolution of biogenic bed material. The conventional assumption 

is that diatom frustules are the major silica source to the surficial bed sediment. Our data appears 

to corroborate this since silica fluxes were higher for May samples, which were taken following

the spring phytoplankton bloom. The subsequent gravitational settling and degradation of these 

siliceous frustules leads to an increased silica flux. 

15
Ancillary Sediment Characterization

The following data, which were not part of the original study, are included for two reasons: 1) To

increase our understanding of the sediment at these sites and dates, and 2) To exhibit the suite of 

parameters that can be studied at a given site. 

Sediment Dynamics: Using a technique which compares historical bathymetry data, Foxgrover 

and others (2004) have concluded that both stations in this study are likely to be sites of relatively

recent deposition. Station 25 was apparently depositional from 1956 until 1983, the date of the 

last complete bathymetric survey, while station 29A appeared to be depositional from 1898 

through 1983. Thus, all the current sediment is presumed to be relatively new. However, this new 

sediment is of unknown origin. In other words, it could be from the riverine inputs, or it could be 

from hydrodynamic resuspension in other regions of the estuary (potentially nearby areas which 

are considered likely to erode). 

Sediment Chemistry: Since the focus of this project was benthic-flux measurements and 

overlying water characterization, this report does not provide a detailed explanation of all ancillary 

sediment results. However, Table 10 provides general characterization of the temporal and spatial 

sediment conditions for a number of relevant parameters (e.g. sulfur and iron speciation data). 

As noted in the methods section, the spring 2003 sediment was collected eight days earlier than

the whole cores and overlying water collected for mercury flux measurements and water-column 

data. The site locations were identical, however, and the comparisons should be relevant given the 

seasonal comparison. 

- Loss on ignition analysis (loss of organic matter upon application of heat) showed a higher 

amount of organic matter was present in the spring sediment than the autumn sediment at

both stations (Table 10). 

- Sediment Eh (a measurement of reducing/oxidizing conditions) showed that sediment at both 

stations was more reducing in the autumn than in the spring, and that Station 29A was more 

reducing than Station 25 in both seasons (Table 10). However, all values were positive, 

indicating oxidizing conditions. 

Below, four relationships between aqueous and sediment data are discussed in detail. 

1. Sediment mercury concentration vs. Mercury flux: The consistently positive 

dissolved mercury flux (Table 4) exhibited a strong positive correlation (r2

=0.69; Fig. 8) 

to the concentration of mercury in the sediment (Table 10). Through dissolution and

sorption reactions, accumulated mercury is partitioned between the bed sediment and

interstitial waters. The dissolved-concentration gradient between the porewater and the 

overlying water drives a benthic flux of dissolved mercury out of or into the sediment. 

Acknowledging that only six flux measurements for dissolved mercury are involved in

this one-year study, this correlation provides direct, supporting evidence for increased

benthic flux of dissolved mercury due to elevated concentrations of mercury in the 

sediment. 

2. Net methylation potential vs. Sulfide flux: Sulfide flux (Table 5) showed a strong 

positive correlation (r2

=0.72; Fig. 8) to the ratio of the potentials for methylation and

demethylation of mercury by microbes (Table 10). Methylation and sulfate reduction

both occur as a result of transformations by taxonomically related bacteria in the 

sediment and under anoxic conditions. Sulfate reduction would increase sulfide 

16
concentrations, and the resulting stronger concentration gradient would propagate the 

flux of sulfides into the water-column.

3. Porewater sulfide vs. Mercury flux: Although only one measurement for porewater

sulfide (Table 10) was above detection limits (Station 29A, April), this corresponded to 

the site/date with the highest dissolved mercury flux value (Table 4). This correlation 

represents the high binding affinity between mercury and sulfide. Even with limited data, 

such significant correlations can be used as a screening tool to guide future management

and research efforts. 

4. Porewater DOC vs. DOC flux: The strong positive correlation (r2

=0.94; Fig. 8) 

between dissolved organic carbon (DOC) concentrations in the porewater (Table 10) and

DOC fluxes (Table 6) illustrates how concentration gradients drive benthic flux. 

17
Study Design and Methods 

The protocol described in this section focuses on method applications in this series of two core-incubation 

experiments. Details (for example, quality control specifications) for each analysis have been previously 

documented (Woods and others, 1999; Praskins and others, 2001; Kuwabara and others, 2003a). 

Sampling was performed at two U.S. Geological Survey (USGS) designated stations (Fig. 1) in the South 

Bay: numbers 25 (a western shoal station with fine silt/clay-textured bottom sediment) and 29A (a main channel 

station with sediment texture similar to Station 25). The stations are located 10.3 and 1.4 km south of the San Mateo 

Bridge, respectively (all stations are north of the Dumbarton Bridge). Samples were collected near slack tide before 

ebb. Therefore, the depths of the shoal station (25) was <2 m, and the main-channel station (29A) depth varied 

between 13 and 14 m. 

Coring Operation 

On both sampling days (May 6 and November 12, 2003), three cores were collected at each of the two sites 

using a 28-kilogram coring device fabricated from non-metallic parts (Fig. 3) produced by Savillex Corporation, 

Minnetonka, Minnesota. To avoid sample contamination, wetted surfaces of the coring device and core tubes were 

acid-washed polypropylene or fluoroethylene polymer. Cores were collected in 10-centimeter diameter 

fluoroethylene polymer tubes 28-centimeters long. A tube, mounted on the coring device, was dropped onto the 

sediment by gravity, impacting the surface at about 0.2 meters per second and penetrating about 10 centimeters 

(depending on the porosity). Excessive penetration by the core was mitigated by four radially positioned, cylindrical 

weights that acted as stabilizers (or feet) for the device. This sampling protocol was designed to provide minimal 

disturbance or compression of soft sediments as visually verified by: (1) the presence of oxic sediment, (2) the 

presence of macroinvertebrates and their tubes, and (3) minimal resuspension of surficial sediment in the overlying 

water when the core was retrieved. If the sampler captured at least 2 centimeters of compacted silt or clay below the 

surficial layer, the sampler generally could be retrieved with the core and overlying water intact. Some samples 

were lost during retrieval, probably because the lowest sampled material was sandy or otherwise unconsolidated. 

Immediately after retrieval, the bottom and top of the sample tube were capped with an insert on the bottom 

and a screw cap on the top (both made of fluoroethylene polymer). The tubes were stored upright in a padded plastic 

bin. To maintain ambient temperature, the bins were partially filled with bay water and covered with opaque plastic 

sheeting. 

Core Incubations 

After cores were collected, samples were taken to nearby Menlo Park, California for processing in a 

constant-temperature room set to the ambient temperature. Cores were left overnight to equilibrate with wetted 

surfaces. Core incubations (Fig. 7) then began with the replacement of overlying water with bottom water that had 

been pumped from each site. Disturbance of the cores during handling was monitored by comparison of the 

chemical composition of the overlying water at the beginning of the incubation with bottom waters. Significant 

deviations in the composition of these water samples would indicate substantial disturbance of the core during 

processing. 

Bottom water was aerobic on both sampling dates at both sites. The twelve cores taken at those sites were 

aerated overnight to condition wetted surfaces before the incubation period (Topping and others, 2001). Three of 

the four cores per site were selected for incubation on the basis of visual inspection of the sediment-water interface 

for any disturbances. Water overlying the sediment in the selected cores was sampled at four time intervals during 

a12-hour incubation at the bottom-water temperature. Overlying water sampled from the cores was replaced by 

pumped bottom water from the site where the core was collected. A linear regression of the time series of solute 

concentrations was used to determine the benthic flux (slope of the time series) from each of the incubated cores. 

This regression generates a correlation (r2

) of the solute concentration versus time. 

When used to discuss data, the term “significant” is used in the text to indicate that two values were 

separated by more than their error (standard deviation or confidence interval). 

18
Physical Data 

Sediment Porosity: After core incubations, approximately 10 milliliters of surficial sediment was 

collected from each core (top 3 centimeters) using a modified 10-cubic centimeter syringe. Wet 

weight and dry weight after lyophilization were measured to calculate porosity. 

Biological Data 

1. Benthic Macroinvertebrates: After core incubations, each core was sieved (500-micrometer mesh). 

The sieved samples were fixed with 10-percent buffered formalin, later transferred to 70-percent 

ethanol, then sorted at 10× magnification and identified to the lowest practicable taxonomic level 

employing the appropriate literature (Fig. 10). Samples were stained with rose bengal to facilitate 

sorting. No subsampling was used. 

2. Benthic Chlorophyll-a: Each incubated core was sub-sampled in triplicate for benthic chlorophyll-a. 

Surficial sediment (top 0.5 centimeters) was collected on a glass-fiber filter and buffered with 

magnesium carbonate. Samples were then frozen in darkness for preservation until 

spectrophotometrically analyzed by methods described in Thompson and others (1981) and 

Franson (1985) (Fig. 11). 

Chemical Parameters 

1. Bottom-water sampling: Prior to coring at each sampling site, bottom-water samples (approximately 1 

meter above the sediment-water interface) were collected for subsequent analysis of dissolvedmercury speciation by cold-vapor atomic fluorescence spectroscopy (CVAFS) using a highdisplacement peristaltic pump and a tethered length of rigid fluoroethylene polymer tubing. These 

samples were also used to replace overlying water in cores collected from each site for incubation. 

2. Dissolved Oxygen (DO): Concentrations of dissolved oxygen were monitored for each incubated core 

using a micro-Winkler titration method (Fig. 12; Kuwabara and others, 2000). 

3. Dissolved Mercury and Methyl Mercury: Dissolved-mercury and methyl-mercury samples were 

processed in a Class-100 laminar-flow hood. Samples from water-column sampling, and core 

incubations were filtered with 0.7-micrometer quartz membranes that had been baked for 6 hours 

at 500 degrees centigrade to remove residual organics. Filtered samples were acidified with 

quartz-distilled nitric acid (pH less than 2), and refrigerated in darkness until analyzed by CVAFS 

(Fig. 13, Krabbenhoft and others, 1998). Methodological details were reported by DeWild and 

others (2002). 

4. Dissolved Trace Metals by ICP-MS: Water-column samples were also collected, filtered (0.2-

micrometer polycarbonate membrane) and acidified to provide dissolved trace-metal information 

for the estuary by flow-injection inductively coupled plasma mass spectrometry (Topping and 

Kuwabara, 1999; Fig. 14). 

5. Dissolved nutrients: Nutrient samples were filtered (0.2-micron polycarbonate membranes) and 

immediately refrigerated in darkness. Unlike trace-metal samples, nutrient samples were not 

acidified. Concentrations for dissolved (0.2-micron filtered) nitrate, ammonia, orthophosphate 

and silica were determined by automated spectrophotometry (Fig. 15). 

6. Dissolved organic carbon (DOC): Dissolved organic carbon was determined by high-temperature, noncatalytic combustion (Qian and Mopper, 1997). Potassium phthalate was used as the standard. 

19
Low-DOC water (blanks <40 micrograms-organic carbon per liter) was generated from a doubledeionization unit with additional ultraviolet treatment (Milli-Q Gradient, Millipore Corporation)

(Fig. 16). 

7. Dissolved Sulfides: Dissolved sulfides in overlying-water samples were analyzed by square-wave 

voltammetry (Fig. 17; Kuwabara and Luther, 1993). 

Ancillary Sediment Characterization

1. Sediment sampling: Sediment was taken from both sites on April 28th 2003 and November 12th 2003

to generate ancillary data (Table 10) for comparisons to the benthic flux and water-column data. 

For both samplings, the surface 0-4 cm depth interval of sediment was collected and transferred 

into glass mason jars, which were filled to the top to exclude oxygen and stored on ice during

transit and later refrigerated (5 o

C) until sub-sampling the following day. All sampling equipment 

was acid cleaned prior to use. All initial sediment processing for microbial assays and ancillary 

sediment characterization was conducted in a nitrogen gas (N2) flushed glove bag to maintain

anaerobic conditions. Sediment from a single site was transferred to a clean zip-lock bag and 

manually homogenized. Sub-samples, for each process or analyte, were taken from this composite

sample. Sediment pore water was collected via centrifugation under anoxic conditions. 

2. Microbial Rate Assays: The addition of radio-labeled inorganic mercury (203Hg(II)) and methylmercury

(

14CH3MeHg+

) to whole sediment was used to measure potential rates of methyl mercury

production and degradation, respectively (Marvin-DiPasquale and others, 2003; MarvinDiPasquale and Oremland 1998). Microbial sulfate reduction was similarly assayed in whole 

sediment using the radioactive sulfate (

35SO4

2-) amendment method (Jørgensen 1978). All samples 

were incubated for four hours at in situ temperatures (April 2003 = 15 o

C, November 2003 = 21 oC). 

3. Sediment Mercury Speciation: Sediment total mercury was assayed by nitric/sulfuric acid digestion, 

bromine chloride (BrCl) oxidation to Hg(II), tin chloride (SnCl2) reduction to gaseous Hg0

, purge 

and trapping of Hg0 on gold coated glass beads, and finally Hg0

 quantification via cold vapor 

atomic fluorescence spectroscopy (Gill and Fitzgerald 1987, Bloom and Fitzgerald, 1988). 

Reactive Hg(II) was assayed as per total mercury, except without pre-digestion of the sample with

nitric/sulfuric acid, followed by BrCl oxidation. SnCl2 was added to a 0.3 g sediment sample

diluted in 50 ml trace clean anoxic water. The amount of Hg(II) chemically reduced to Hg0

 and 

captured on the gold trap after 30 minutes of purging with helium, was operationally defined as 

the “reactive” Hg(II) fraction. 

4. Sediment Organic Content: Measured by weight loss on ignition to 500 o

C for 4 hours (APHA, 1981). 

5. Sediment Acid Volatile Reduced Sulfur: Measured by the addition of 6 molar hydrochloric acid (6M 

HCl) to whole sediment, with the subsequent trapping of liberated gaseous sulfide in 10% zinc 

acetate solution. Sulfide was then assayed colormetrically (Cline 1969). This primarily represents 

the solid phase iron sulfide (FeS) mineral fraction.

6. Sediment Total Reduced Sulfur: Measured by the addition of 6 molar HCl and 1 molar chromium (II)

(1 M Cr(II)) to whole sediment, with the subsequent heated distillation and trapping of liberated

gaseous sulfide in 10% zinc acetate solution. Sulfide was then assayed spectrophotometrically 

(Cline 1969). This primarily represents the combined solid phase FeS and pyrite (FeS2) mineral 

fractions, as well as elemental sulfur (S0

). 

20
7. Sediment Ferrous Iron: Measured by extraction of iron (II) (Fe(II)) using 0.5 molar HCl followed by

quantification with ferrozine (Lovley and Phillips, 1987). 

8. Sediment Amorphous Ferric Iron: Measured by extraction of Fe(II) using 0.5 molar HCl followed by

reduction of Fe(III) to Fe(II) with hydroxylamine, and quantification with ferrozine (Lovley and 

Phillips, 1987). This is the fraction of Fe(III) that is most available to iron-reducing bacteria. 

9. Sediment Crystalline Ferric Iron: Measured by the reductive dissolution of Fe(III)-oxide mineral 

phases with citrate-dithionite extraction, followed quantification with ferrozine (Roden and 

Zachara, 1996). 

10. Sediment pH and Redox: Both parameters measured both via electrode inserted directly into sediment. 

11. Pore-water Ferrous Iron: Measured spectrophotometrically with ferrozine (USEPA, 1996). This 

provides and indication of microbial Fe(III)-reduction activity. 

12. Pore-water Sulfate and Chloride: Assayed via ion chromatography (Dionex, 1992). 

13. Pore-water Dissolved Organic Carbon (DOC): Measured via high temperature oxidation with IR 

detection (Qian and Mopper, 1996). 

14. Pore-water Sulfide: Samples preserved with sulfide anti-oxidizing buffer and assayed via ion specific 

electrode (Gilmour, 1998). 

21
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26
Acknowledgments 

 

The authors thank M. Olson, J. DeWild, and S. Olund (USGS, Madison, WI) for mercury-speciation

analyses and J. Carter (USGS, Menlo Park, CA) for discussions regarding macroinvertebrates. The San Francisco

Estuary Institute (SFEI Project Number RMP-440 / USGS Agreement 03H44559WFO003) and the USGS Toxic 

Substances Hydrology Program are gratefully acknowledged for support of this work, as is T. Mulvey for tireless efforts 

in support of water quality in San Francisco Bay. Helpful and thorough reviews by A. Foster and M. Hornberger (USGS, 

Menlo Park, CA) were appreciated. 

Product names are provided for identification purposes only and do not constitute endorsement by the U.S. 

Geological Survey. 

27
Appendix 1: Comments on the Report Structure 

A major objective of this electronic document is to provide a structure that is easily accessible to a wide 

range of interest groups. Therefore, pathways within this document have been constructed to be both logical and

intuitive. In contrast to typical scientific manuscripts, this report is formatted in a pyramid-like structure to serve the 

needs of diverse groups who may be interested in reviewing or acquiring information at various levels of technical

detail. The report enables quick transitions between the initial summary information (figuratively at the top of the 

pyramid) and the later details of methods or results (figuratively towards the base of the pyramid) using hyperlinks 

to supporting figures and tables, and an electronically linked Table of Contents. In addition to hyperlinks within the 

document to supporting figures and tables, links in Appendices 2 and 3 provide a quick way to directly review and 

examine all figures and tables. 

Although hard copies of this report are available on request, the advantages of the electronic version 

relative to the hard copy are substantial in many respects, but particularly in the rapid access of information at 

multiple levels of detail. 

Your comments about how this type of Web-based product may be improved to better serve readers are 

most welcome and may be directed to the major author (btopping@usgs.gov) so that they may be compiled for 

future revisions and reports. 

28
Appendix 2: List of Figures

Fig. 1 – Site map of the study area 

Fig. 2 – Photos of historic mercury mining areas 

Fig. 3 – Photos of the coring operation 

Fig. 4 – Comparison of fluxes and riverine inputs of dissolved mercury

Fig. 5 – Strong seasonal changes in the benthic flux of DOC

Fig. 6 – Conceptual model of solute transport through a reservoir

Fig. 7 – Processes regulating benthic flux of solutes 

Fig. 8 – Correlations between aqueous and sediment data

Fig. 9 – Incubation core design 

Fig. 10 – Photo of macroinvertebrate taxonomy methods 

Fig. 11 – Photo of benthic chlorophyll analyses 

Fig. 12 – Photo of dissolved oxygen analyses 

Fig. 13 – Photo of dissolved mercury analyses 

Fig. 14 – Photo of dissolved metal analyses 

Fig. 15 – Photo of dissolved nutrient analyses 

Fig. 16 – Photo of dissolved organic carbon (DOC) analyses 

Fig. 17 – Photo of dissolved sulfide analyses 

29
 

Appendix 3: List of Tables 

Table 1 – Benthic-invertebrate taxonomy

Table 2 – Benthic-chlorophyll analyses 

Table 3 – Water-column concentrations for mercury species 

Table 4 – Dissolved mercury benthic fluxes 

Table 5 – Dissolved sulfide benthic fluxes 

Table 6 – Dissolved organic carbon (DOC) benthic fluxes and water-column concentrations 

Table 7 – Dissolved oxygen consumption

Table 8 – Dissolved nutrient benthic fluxes 

Table 9 – Dissolved-copper and nickel benthic fluxes and water-column concentrations 

Table 10 – Ancillary sediment characterization

30
122o30 W’ 122o15’ 12

37

o30’

Figure 1. Benthic-flux Coring Sites

37

o45 N’
Figure 2. Photos of Historic Mercury Mining Areas, Almaden-Qu

Entrance to San Cristobal Tunnel; opened in 1866

Cinnabar ore within the mine Rotary Furnace installe

to increase output of m
Figure 3. Coring Operation

Coring apparatus with newly acquired core Co
Figure 4. Comparison of Benthic Flux to Riverine Inputs for Dis

Dissolved riverine loads estimated from Tetra Tech (2003); Particulate loads from LoSymbols represent individual core flux estimates, with station number enclosed

and color/shape representing season (green/circle: spring; orange/trian

292929

252525 2525

25

2929

29
Figure 5. Strong Seasonal Changes in the Benthic Flux of DOC

Error bars represent standard deviations of individual flux cores
Figure 6.
Figure 7.
Figure 8. Correlations between Aqueous and Sediment Data

Including approximate linear fit and correlation coefficient; sediment data is plotted on the x-axis; aqueous data, y-axis;

see Ancillary Sediment Characterization
Figure 9. Incubation Core Design
Figure 10. Benthic Macroinvertebrate Taxonomy
Figure 11. Benthic Chlorophyll Analyses

Detection limit for chlorophyll analysis

0.3 ug/cm2
Figure 12. Micro-Winkler Titration Method for Dissolved-Oxyge

Detecti

on limit for dissolved-oxygen analys

0.5 m

g/L
Figure 13. Cold-Vapor Atomic Absorption Spectroscopy

Typical method detection limit for dissolved-me

0.2 pM
Figure 14. Dissolved-Metal Analysis by ICP-MS

Detection limit for metals analysis

Cu 0.01 ug/L

Ni 0.05 ug/L
Figure 15. Dissolved-Nutrient Analysis by Automated Spectrop

Detection limit for nutrient analysis

Ortho-P 2.5 ug/L
Figure 16. Dissolved Organic Carbon (DOC) Analyses 

by High-Temperature, Non-Catalytic Oxidation

Detection limit for DOC analysis

0.1 m

g/L
Figure 17. Dissolved-Sulfide Analysis by Square-wave Voltamm

Detection limit for sulfide analysis

0.1 ug/L (4 nM)
Phylum Mollusca

Class Pelecypoda

Theora lubrica 43 43 87 43

Venerupis philippinarum 43

Phylum Arthropoda

Class Crustacea

Order Cumacea

Nippoleucon hinumensis 43

Order Isopoda

Paranthura elegans 43 87

Order Amphipoda

Family Ampeliscidae

Ampelisca abdita 1602 43 260 87

Family Corophidae

Corophium heteroceratum 43 476 173

Phylum Annelida

Class Oligochaeta

Tubificidae 43 476 216

Class Polychaeta

Family Capitellidae

Heteromastus filiformis 87 260 130

Family Cirratulidae

Cirriformia spirabrancha 43 87

Unid. Cirratulidae juvenile 43

Family Dorvilleidae

Dorvillea rudolphi 43 87

Family Eunicidae

Marphysa nr. Sanguinea 43

Family Goniatdidae

Glycinde polygnatha 43 87

Glycinde sp. SF1 43

Glycinde spp. 43 173

Family Maldanidae

Sabaco elongatus 823 1688 476 1429

Family Phyllodocidae

Eumida longicornuta 43

Family Polynoidae

Harmothoe imbricata 173 43 260

Family Sabellidae 130

Euchone limnicola 130

Family Spionidae

Dipolydora socialis 173 260

Polydora brachycephala 43

Polydora cornuta (=ligni) 87 173

Pseudopolydora paucibranchiata 87 216 43

Unid. Spionidae* 87

Family Syllidae

Exogone lourei 87

Sphaerosyllis spp. 43

Typosyllis sp. A 130

Family Terebellidae

Ameana sp. SF1 43

Pista elongata 43

Polycirrus spp.? (damaged) 130

Unid. Terebellidae 43

Misc. groups

Phylum Cnidaria

Class Anthozoa 43 216 43 130

Phylum Chordata

Molgula manhattensis 43 173 43

Phylum Nematoda 87 693 736

Phylum Ectoprocta X X X

* Lost - not included in weight

X Present in sample but not weighed or counted

Wet weight (mean of 3 cores) (grams) Station 25 Station 29A

May-03 Nov-03 May-03 Nov-03

Phylum Mollusca 0.000 0.208 0.000 0.003

Class Crustacea 0.011 0.001 0.014 0.003

Phylum Annelida 0.599 1.219 0.258 1.471

Misc. groups 0.051 0.004 0.000 0.006

Note: Mean number (n=3 cores) of individuals per square meter, based on core surface area of 77 cm2
Table 2. Discrete Benthic Chlorophyll and Phaeophytin Analys

May-03 Individual Cores Site Average

ChlA Phaeo ChlA error Pha

Station Core ug/cm2 ug/cm2 

25 2 1.1 14.0 2.5 5.9 11

25 3 4.7 9.925 4 1.7 9.9

29A 5 1.4 9.1 1.2 0.9 8

29A 6 0.9 9.5

29A 7 1.2 7.8

Nov-03 Individual Cores Site Average

ChlA Phaeo ChlA error Pha

Station Core ug/cm2 ug/cm2 

25 5 0.5 14.5 0.4 0.1 13

25 7 0.5 14.825 8 0.4 10.8

29A 1 0.1 8.5 0.2 0.2 9

29A 2 <0.1 12.1

29A 3 0.2 6.5

Notes: Errors shown represent 95% confidence intervals.
Table 3. Water-Column Mercury Concentrations

May-03

St. 25 Total Dissolved Hg (pM)

depth mean stdev

1 m 10.0 0.2

St. 29a

depth mean stdev

1 m 7.0 0.1

Mid 6.8 0.0

12 m 5.4 0.5

Nov-03

St. 25 Total Dissolved Hg (pM)

depth mean stdev

1 m 5.7 0.9

St. 29a

d
Table 4. Benthic Flux of Total Dissolved Mercury

May-03Calculated from all available data Site Averages A

Mercury Flux Mercury Flux Mercury Flux 

Sta. Core (pmoles/m2-h)a (ng/m2-day)b r2 n Comments (ng/m2-day)b 

25 2 40 +/- 6 194 +/- 29 0.97 7 203 +/- 51 25 3 33 +/- 33 158 +/- 159 0.41 8

25 4 54 +/- 9 258 +/- 43 0.94 8

29A 5 208 +/- 31 999 +/- 152 0.95 8 Potential outlier c 429 +/- 497 

29A 6 42 +/- 18 203 +/- 86 0.73 829A 7 18 +/- 23 87 +/- 112 0.34 8

Calculated without end points due to potentially anoxic conditions

Mercury Flux Mercury Flux

Sta. Core (pmoles/m2-h)a (ng/m2-day)b r2 n 

25 2 24 +/- 12 117 +/- 58 1.00 4 A25 3 82 +/- 111 396 +/- 534 0.99 4 25 4 23 +/- 19 113 +/- 89 1.00 4 

29A 5 83 +/- 30 401 +/- 142 1.00 4 1

29A 6 107 +/- 29 517 +/- 141 1.00 429A 7 37 +/- 82 177 +/- 396 1.00 4

Nov-03Calculated from all available data Site Averages A

Mercury Flux Mercury Flux Mercury Flux 

Sta. Core (pmoles/m2-h)a (ng/m2-day)b r2 n Comments (ng/m2-day)b 

25 5 38 +/- 3 184 +/- 15 0.99 6 225 +/- 137 25 7 23 +/- 54 112 +/- 261 0.95 5 Final time point sample was lost25 8 78 +/- 1174 378 +/- 5652 0.77 3 Initial time point sample was contaminated

29A 1 6 +/- 4 29 +/- 17 0.80 6 120 +/- 101 29A 2 21 +/- 17 102 +/- 82 0.83 529A 3 47 +/- 12 228 +/- 60 0.91 7

Notes: All methyl mercury samples were below detection limits, so no methyl mercury fluxes can be directly estimated (see discussion).

Errors shown for individual cores and for "all sites/dates" average represent 95% confidence intervals.Errors shown for site averages and areal averages represent standard deviations of the values used in the mean.r2 represents the correlation coefficient of the regression of concentration versus time

a Total dissolved mercury flux (molar units) is presented in picomoles per square meter per hour.b Total dissolved mercury flux (mass units) is presented in nanograms per square meter per day.c Flux values were extrapolated over the entire South Bay (south of the Bay Bridge) using an area of 554 km2 (Cheng and Gartner, 1985)d The concentration of the final time point at this site was the highest of all values, so it is possibly an outlier due to

contamination. If the flux is calculated without this point, the result is 83.3 +/- 25.1 pmoles/m2-h.
Table 5. Dissolved Sulfide Flux

May-03 Site Averages

Sulfide Flux Sulfide Flux

Sta. Core (nmoles/m2 r2 -h) n (nmoles/m2-h)

25 2 507 +/- 63 0.93 8 653 +/- 127

25 3 711 +/- 96 0.92 8

25 4 739 +/- 90 0.93 8

29A 5 708 +/- 32 0.99 8 786 +/- 86

29A 6 771 +/- 89 0.94 8

29A 7 878 +/- 57 0.98 8

Nov-03 Site Averages

Sulfide Flux Sulfide Flux

Sta. Core (nmoles/m2 r2 -h) n (nmoles/m2-h)

25 5 466 +/- 41 0.96 8 564 +/- 98

25 7 563 +/- 57 0.95 8

25 8 662 +/- 44 0.98 8

29A 1 778 +/- 79 0.95 8 751 +/- 72

29A 2 805 +/- 32 0.99 8

29A 3 670 +/- 57 0.97 8

Notes: Errors shown for individual cores represent 95% confidence interva

Errors shown for site averages represent standard deviations of the r2 represents the correlation coefficient of the regression of concent
Table 6. Dissolved Organic Carbon Fluxes and Water-Column 

Concentrations in South San Francisco Bay, CA

May-03 Site Averages

DOC Flux DOC Flux

Core Sta. (umoles/m2 r2 -h) n (nmoles/m2-h)

25 2 -129 +/- 24 0.50 15 -135 +/- 29

25 3 -167 +/- 27 0.57 15

25 4 -109 +/- 64 0.09 15

29A 5 101 +/- 38 0.20 15 27 +/- 158

29A 6 134 +/- 35 0.38 14

29A 7 -155 +/- 29 0.46 16

Water Column DOC (uM)Sta. 25 Bottom 263 +/- 1

Sta. 29a Surface 215 +/- 3

Mid-depth 221 +/- 1

Bottom 219 +/- 2

Nov-03 Site Averages

DOC Flux DOC Flux

Core Sta. (umoles/m2 r2 -h) n (nmoles/m2-h)

25 5 85 +/- 115 0.02 14 371 +/- 255

25 7 575 +/- 50 0.82 1525 8 453 +/- 164 0.24 14

29A 1 1264 +/- 226 0.57 14 1302 +/- 16829A 2 1156 +/- 232 0.51 14

29A 3 1486 +/- 160 0.75 15

Water Column DOC (uM)Sta. 25 Bottom 242 +/- 1

Sta. 29a Surface 156 +/- 2

Mid-depth 156 +/- 3

Bottom 154 +/- 1

Notes: Errors shown for individual cores represent 95% confidence intervals.

Errors shown for site averages represent standard deviations of the values used in the mean.r2 represents the correlation coefficient of the regression of concentration versus time
Table 7. Dissolved Oxygen Flux (i.e. Consumption) in South San Francisco Bay, CA

May-03 Site Averages

DO Flux DOC Flux

Core Sta. (mmoles/m2-h) r2 n (nmoles/m2-h)

2 25 -4.4 +/- 3.0 0.93 4 -4.5 +/- 0.4

3 25 -4.3 +/- 3.0 0.93 44 25 -5.0 +/- 2.4 0.96 45 29A -4.5 +/- 0.4 1.00 4 -4.6 +/- 0.2

6 29A -4.8 +/- 3.8 0.91 4

7 29A -4.4 +/- 1.9 0.97 4

Spring Average -4.6 +/- 0.3

Nov-03 Site Averages

DO Flux DOC Flux

Core Sta. (mmoles/m2-h) r2 n (nmoles/m2-h)

5 25 -2.5 +/- 2.3 0.88 4 -3.1 +/- 0.6

7 25 -3.2 +/- 2.4 0.92 48 25 -3.6 +/- 2.7 0.92 41 29A -3.5 +/- 2.1 0.95 4 -3.5 +/- 0.3

2 29A -3.2 +/- 4.5 0.77 4

3 29A -3.7 +/- 1.4 0.98 4

Autumn Average -3.3 +/- 0.5

Notes: Errors shown for individual cores/ seasonal averages represent 95% confid

Errors shown for site averages represent standard deviations of the values r2 represents the correlation coefficient of the regression of concentration v
Table 8. Benthic Flux and Water-column Concentrations for Dissolved Nickel and Copper

Nickel Copper

May-03 May-03

Ni Flux Cu Flux

Sta. Core (nmoles/m2-h) r2 n Sta. Core (nmoles/m2-h) 

25 2 -11 +/- 4 0.13 17 2 25 -41 +/- 12 

25 3 26 +/- 4 0.49 17 3 25 5 +/- 3 25 4 -21 +/- 9 0.21 14 4 25 -48 +/- 5 

29A 5 13 +/- 4 0.22 17 5 29A -62 +/- 4 29A 6 24 +/- 4 0.52 15 6 29A -81 +/- 10 

29A 7 49 +/- 6 0.67 16 7 29A -19 +/- 4 

Water Column Ni (nM) Water Column Cu (nM)Sta. 25 Bottom 29.8 +/- 0.2 Sta. 25 Bottom 29.7 +/- 0.4

Sta. 29a Surface 25.2 +/- 0.5 Sta. 29a Surface 27.1 +/- 0.1

Mid-depth 24.8 +/- 0.1 Mid-depth 28.3 +/- 0.6

Bottom 24.8 +/- 0.5 Bottom 23.7 +/- 0.2

Nov-03 Nov-03

Ni Flux Cu Flux

Sta. Core (nmoles/m2-h) r2 n Sta. Core (nmoles/m2-h) 

25 5 -9 +/- 9 0.05 13 5 25 -9 +/- 3 

25 7 -29 +/- 7 0.46 13 7 25 -3 +/- 9 25 8 -18 +/- 12 0.10 13 8 25 28 +/- 22 

29A 1 114 +/- 5 0.96 14 1 29a -82 +/- 12 29A 2 73 +/- 4 0.92 16 2 29a -97 +/- 8 

29A 3 102 +/- 5 0.94 15 3 29a -8 +/- 2 

Water Column Ni (nM) Water Column Cu (nM)Sta. 25 Bottom 23.4 +/- 0.2 Sta. 25 Bottom 29.0 +/- 0.2

Sta. 29a Surface 22.7 +/- 1.2 Sta. 29a Surface 25.5 +/- 0.0

Mid-depth 23.5 +/- 0.5 Mid-depth 26.4 +/- 0.5

Bottom 22.1 +/- 0.5 Bottom 25.1 +/- 0.4

Notes: Errors shown for individual cores represent 95% confidence intervals.

r2 represents the correlation coefficient of the regression of concentration versus time
Table 9. Macronutrient benthic flux

May-03 Nov-03

NITRATE PLUS NITRITE NITRATE PLUS NITRITE

NO3 Flux NO3 Flux 

Sta. Core (umoles/m2-h) r2 n Sta. Core (umoles/m2-h) r2 n

25 2 -1 +/- 9 0.04 4 25 5 6 +/- 8 0.65 425 3 -7 +/- 29 0.03 6 25 7 1 +/- 15 0.01 425 4 -17 +/- 17 0.25 7 25 8 30 +/- 45 0.58 4

29A 5 40 +/- 52 0.92 4 29A 1 -20 +/- 6 0.98 4

29A 6 32 +/- 8 0.99 4 29A 2 -26 +/- 9 0.96 4

29A 7 32 +/- 20 0.98 4 29A 3 -14 +/- 9 0.88 4

AMMONIA AMMONIA

NH4+ Flux NH4+ Flux

Sta. Core (umoles/m2-h) r2 n Sta. Core (umoles/m2-h) r2 n

25 2 9 +/- 2 0.98 5 25 5 -18 +/- 6 0.96 4

25 3 42 +/- 3 0.99 7 25 7 -14 +/- 10 0.87 425 4 47 +/- 6 0.95 7 25 8 9 +/- 4 0.93 4

29A 5 17 +/- 40 0.54 4 29A 1 23 +/- 10 0.94 4

29A 6 12 +/- 42 0.34 4 29A 2 -26 +/- 16 0.9 4

29A 7 11 +/- 2 0.99 4 29A 3 24 +/- 14 0.91 4

ORTHOPHOSPHATE ORTHOPHOSPHATE

PO4 Flux PO4 Flux

Sta. Core (umoles/m2-h) r2 n Sta. Core (umoles/m2-h) r2 n

25 2 1 +/- 9 0.02 5 25 5 9 +/- 4 0.94 4

25 3 15 +/- 16 0.31 7 25 7 4 +/- 2 0.87 425 4 2 +/- 9 0.02 7 25 8 7 +/- 3 0.93 4

29A 5 0 +/- 30 0.01 4 29A 1 -16 +/- 7 0.93 4

29A 6 -12 +/- 16 0.79 4 29A 2 -8 +/- 60 0.05 4

29A 7 -2 +/- 1 0.99 4 29A 3 -15 +/- 6 0.94 4

SILICA SILICA

Si Flux Si Flux

Sta. Core (umoles/m2-h) r2 n Sta. Core (umoles/m2-h) r2 n

25 2 277 +/- 277 0.74 4 25 5 171 +/- 59 0.96 4

25 3 473 +/- 187 0.76 7 25 7 193 +/- 79 0.95 4

25 4 200 +/- 79 0.70 7 25 8 285 +/- 133 0.93 4

29A 5 531 +/- 774 0.75 4 29A 1 243 +/- 120 0.93 4

29A 6 368 +/- 158 0.97 4 29A 2 178 +/- 94 0.92 4

29A 7 342 +/- 74 0.99 4 29A 3 168 +/- 83 0.93 4

Notes: Errors shown for individual cores represent 95% confidence intervals.

r2 represents the correlation coefficient of the regression of concentration versus time
Table 10. Ancillary sediment characterization data

Apr-03 Nov-03

Sediment Parameter Units Sta. 25 Sta. 29A Sta. 25 Sta. 29A Explanation

MeHg Prod Potential ng/g dry sed/d 4.1 7.2 < 0.70 6.3 Methyl-mercury production potential rate

deva 2.2 2.3 0.7 in nanograms per gram dry sediment per day

MeHg Degrad Potential ng/g dry sed/d 8.7 7.3 4.0 4.1 Methyl-mercury degradation potential rate

deva 0.2 0.2 0.2 0.0 in nanograms per gram dry sediment per day

M/D Ratio unitless 0.47 0.98 < 0.18 1.54 Production(methylation)/degradation(demethylatioMicrobial Sulfate Red. nmol/g dry sed/d 7.8 4.8 1.6 1.4 Microbial sulfate reduction rate

deva 2.4 2.3 0.0 0.0 in nanomoles per gram dry sediment per day

Total Hg ng/g dry sed 256 293 233 247 Total mercury concentration in sediment

deva 9 33 4 5 in micrograms per gram dry sediment

Reactive Hg(II) ng/g dry sed 1.41 1.96 1.24 0.38 Reactive mercury in sediment, operationally defin

deva 0.97 0.29 0.46 0.01 SnCl2 reducible Hg(II), in nanomoles per gram d

Percent Reactive Hg(II) % 0.55 0.67 0.53 0.16 Percent of total Hg recovered as reactive Hg(II)

deva 0.38 0.10 0.20 0.00

Loss on Ignition % 5.83 6.08 4.32 4.75 Loss of organics on heat application

deva 0.3 0.3 1.1 0.2

Acid Volatile Sulfur umol/g dry sed 1.9 17.0 10.5 33.4 Acid volatile sulfur concentration

deva 1.0 2.7 0.0 0.0 in micromoles per gram dry sediment

Total Reduced Sulfur umol/g dry sed 72.4 64.7 69.5 172.8 Total reduced sulfur concentration

deva 1.8 5.9 0.0 0.4 in micromoles per gram dry sediment

Sediment Fe(II) mg/g dry sed 5.14 8.49 9.09 11.46 Concentration of iron in oxidation state (II)

deva 0.03 0.04 0.11 1.12 in milligrams per gram dry sediment

Amorphous Fe(III) mg/g dry sed 2.95 0.05 0.35 -0.48 Concentration of amorphous iron in oxidation state 

deva 0.10 0.01 0.10 0.41 in milligrams per gram dry sediment

Crystalline Fe(III) mg/g dry sed 2.15 1.18 7.02 3.10 Concentration of crystalline iron in oxidation state 

deva 0.52 0.20 0.26 0.72 in milligrams per gram dry sediment

Fe(II)/Fe ratio % 50.2 87.3 55.2 81.4 Percent of total iron as Fe(II) Porewater Fe(II) mg/liter 0.03 0.50 0.02 1.32 Porewater concentration of Fe(II)

deva (n=1) 0.05 (n=1) (n=1) in milligrams per liter of porewater

Porewater Sulfate mM 19.8 19.3 20.0 18.8 Porewater concentration of sulfate

deva 0.9 1.0 (n=1) (n=1) in millimoles per liter of porewater

Porewater Cloride mM 443 444 438 451 Porewater concentration of chloride

deva 6 14 (n=1) (n=1) in millimoles per liter of porewater

Sulfate/Chloride ratio unitless 0.04 0.04 0.05 0.04 Molar concentration ratio in porewaterPorewater Sulfide uM < 0.2 0.58 < 0.2 < 0.2 Porewater concentration of sulfide

deva 0.09 in micromoles per liter of porewater

Porewater DOC mg-C/L 37.5 35.2 62.1 86.7 Porewater concentration of dissolved organic carb

deva 2.0 0.5 (n=1) (n=1) in milligrams of carbon per liter of porewater

Sediment Eh redox (n=1) mV 171.8 63.5 71.6 38.7 Reducing potential at time of incubation

a All deviations (dev) are based on two replicates (n=2) unless otherwise indicated