PreprintPDF Available

Salinity-Driven Stratification Enhances Riverine Mercury Export to the Coastal Ocean

Authors:
Preprints and early-stage research may not have been peer reviewed yet.

Abstract and Figures

Rivers transport 300 to 5,000 Mg of mercury (Hg) annually to coastal oceans through estuaries, contributing 20–45% of total Hg input, with 100 to 1,500 Mg reaching the open ocean. However, the impact of estuarine circulation and stratification on Hg transport and methylation remains uncertain despite their known influence on other metal exports. This study developed three models to assess Hg transformation under different salinity-driven stratification regimes—well-mixed, slightly stratified, and highly stratified—using data from the Chesapeake Bay (CPB) and Hudson River Estuary (HRE), U.S.A. Results show that stratification increases riverine Hg export by 19% in CPB and 20% in HRE, with shorter Hg residence times promoting faster export. Unstratified estuaries favor Hg burial in sediments due to longer residence times and increased particle settling. Seasonal river discharge variations further influence stratification, with higher discharge enhancing stratification and Hg export. Methylmercury (MeHg) production and export also respond to stratification, with slightly stratified conditions in CPB increasing MeHg production by 11.5% and export by 16.4%. As climate change is expected to intensify stratification in many estuaries, these findings suggest potential increases in Hg and MeHg export to coastal oceans.
Content may be subject to copyright.
Page 1/24
Salinity-Driven Stratication Enhances Riverine
Mercury Export to the Coastal Ocean
Roland P. Ovbiebo
Scripps Institution of Oceanography, University of California San Diego https://orcid.org/0000-0002-
1889-7501
Cathryn D. Sephus
Scripps Institution of Oceanography, University of California San Diego
Amina T. Schartup
Scripps Institution of Oceanography, University of California San Diego https://orcid.org/0000-0002-
9289-8107
Research Article
Keywords: Methylmercury, River Discharge, Residence Time, Estuary Types, Biogeochemical
Transformations
Posted Date: March 24th, 2025
DOI: https://doi.org/10.21203/rs.3.rs-6276810/v1
License: This work is licensed under a Creative Commons Attribution 4.0 International License. 
Read Full License
Additional Declarations: The authors declare no competing interests.
Page 2/24
Abstract
Rivers transport 300 to 5,000 Mg of mercury (Hg) annually to coastal oceans through estuaries,
contributing 20–45% of total Hg input, with 100 to 1,500 Mg reaching the open ocean. However, the
impact of estuarine circulation and stratication on Hg transport and methylation remains uncertain
despite their known inuence on other metal exports. This study developed three models to assess Hg
transformation under different salinity-driven stratication regimes—well-mixed, slightly stratied, and
highly stratied—using data from the Chesapeake Bay (CPB) and Hudson River Estuary (HRE), U.S.A.
Results show that stratication increases riverine Hg export by 19% in CPB and 20% in HRE, with shorter
Hg residence times promoting faster export. Unstratied estuaries favor Hg burial in sediments due to
longer residence times and increased particle settling. Seasonal river discharge variations further
inuence stratication, with higher discharge enhancing stratication and Hg export. Methylmercury
(MeHg) production and export also respond to stratication, with slightly stratied conditions in CPB
increasing MeHg production by 11.5% and export by 16.4%. As climate change is expected to intensify
stratication in many estuaries, these ndings suggest potential increases in Hg and MeHg export to
coastal oceans.
Synopsis
River discharge carries mercury to the ocean via estuaries, where it can be converted to neurotoxic
methylmercury. We examine how estuary stratication inuences mercury in river discharge reaching the
ocean.
Introduction
Estuarine mercury (Hg) biogeochemical cycling is unique due to the dynamic mixing of riverine
freshwater and saline ocean water; thus, understanding the estuarine processes that regulate Hg export
to the ocean is important. These mixing processes inuence Hg speciation, behavior, and transport
across the land-ocean continuum, affecting regional and global Hg cycles.1,2 While much attention has
historically been given to Hg deposited to the ocean through atmospheric processes, recent studies
indicate that riverine sources contribute 1,000 Mg of Hg to the coastal ocean annually,3 which is three
times more than the 310 Mg of Hg deposited through atmospheric processes. Accurately quantifying the
riverine ux of Hg is challenging, as it is affected by numerous factors, including variations in river
discharge, sampling limitations, hydrodynamic processes, and the inuence of suspended sediment and
organic matter.3,4 Consequently, current global riverine Hg export estimates to the oceans vary widely,
ranging from 300 to 5,000 Mg annually.3–6
The behavior and fate of contaminants within estuaries, including Hg, are inuenced by the estuarine
circulation and stratication patterns, which vary among estuary types.7–9 Estuaries are typically
classied into three main types based on stratication: well-mixed, slightly stratied, and highly
stratied. These classications reect variations in vertical and horizontal water movement, signicantly
Page 3/24
affecting how contaminants are retained, ushed, or deposited, which has implications for water quality
and ecosystem health.10–12 Within these stratication regimes, physical and hydrodynamic processes
further impact Hg's speciation into its inorganic divalent (HgII) and elemental Hg (Hg0), and organic
forms – mono- and di- methylmercury (MMHg and DMHg, respectively). In highly stratied estuaries,
dense bottom water restricts vertical mixing, trapping Hg species in deeper waters and sediments,
where microbial activity in anoxic sediments converts inorganic Hg into methylmercury (MeHg; sum of
MMHg and DMHg), a bioaccumulating neurotoxicant,13–15 through various methylation processes.2,16–18
In slightly stratied systems, vertical and horizontal mixing disperses Hg throughout the water column,
and methylation processes can occur in the pycnocline,19 which is a layer within the water column where
there is a rapid change in water density with depth caused by variations in salinity, temperature, or both.
These systems also enhance Hg binding with organic matter, which promotes settling and subsequent
methylation in the benthic sediment.18,20,21 In well-mixed estuaries, Hg species are more evenly
distributed due to the absence of stratication, reducing localized accumulation between different
salinity layers. However, strong tidal forces in these systems can resuspend Hg-containing sediments,
releasing Hg into the water column, where it may undergo methylation if conditions permit.22,23
Considering these dynamics, we propose that incorporating the distinct stratication characteristics of
these estuarine types in modeling riverine Hg ux to the coastal ocean could help reduce uncertainties in
current global Hg ux estimates. To address this, we develop three empirically constrained models of Hg
cycling dynamics tailored to each stratication-specic estuarine system, aiming to rene estimates of
riverine Hg discharge into the coastal ocean. We use these models to examine the role of salinity-driven
stratication in modulating Hg speciation within a specic coastal framework. Our model was evaluated
using observational data from the Chesapeake Bay (CPB) and Hudson River Estuary (HRE) in the United
States. These two estuarine systems exhibit seasonal variability in stratication; CPB transitions from
slightly stratied to well-mixed, and HRE transitions from highly stratied to slightly stratied, reecting
uctuations in freshwater inow and tidal mixing. By modeling Hg dynamics across these stratication
scenarios, we offer new insights into the role of estuarine stratication in Hg transport and
transformation, with implications for better estimates of riverine Hg contributions to the coastal ocean
and an improved understanding of its global distribution.
Methods
Study Area Description
The CPB, the largest estuary in the United States, stretches about 322 km from the Susquehanna River in
Maryland to Cape Charles and Cape Henry in Virginia, with a surface area of about 11,600 km2 and a
watershed that spans over 165,000 km2 (Supplementary Fig. S1). The Susquehanna River signicantly
affects salinity levels in the estuary, providing approximately 62% of the freshwater supply and directly
feeding into the Bay's main stem. Other signicant rivers owing into the Bay include the Potomac,
James, York, and Rappahannock Rivers. With an average water depth of 7 m and an exchange rate of
Page 4/24
8000 m³ s− 1 with the ocean,24 the estuary features a two-layer circulation: fresh, lighter water ows
seaward on the surface, while denser, saltier water moves landward below. The pycnocline separates
these layers, resulting in slightly stratied conditions with seasonal variation. The stratication is
strongest in spring and mixing increases in fall due to seasonal changes in river discharge and wind-
driven mixing, creating well-mixed conditions in the summer months. The estuary experiences tidal
mixing, but large portions are brackish water (0.5–25 ppt). Tidal forces are modest, rarely exceeding a 1
m range,25 with wind and tidal mixing inuencing the estuary salinity and residual circulation.26,27
The HRE is a tidal estuary that spans 246 km from Battery at New York Harbor to the Federal Dam at
Troy, located on the northeastern coast of the United States (Supplementary Fig. S1). It is much smaller
in surface area (5,700 km2) than the CPB, with a watershed of about 34,700 km2. The Hudson River is the
primary water body, with smaller tributaries feeding into the estuary, such as the Mohawk Creek, Rondout
Creek, and Esopus Creek. The estuary has an average depth of roughly 10 m with a mean tidal ow of
around 12,040 m3 s− 1.28 It features a dynamic ecosystem shaped by freshwater inows, tides, and
varying salinity (5–30 ppt), with tidal ranges reaching 2 m and peak velocities of 1 m s− 1.29 Freshwater
from upstream ows into the Atlantic, while tidal forces push saltwater upstream, creating a salt-wedge
or highly stratied estuary.30 The estuary’s strong tides dominate the river’s ow patterns over much of
its length. The HRE is more stratied than the CPB, with salinity extending up to 140 km from the Battery
depending on freshwater ow.31
Model Framework
We constructed an empirically constrained mass budget for the four main Hg species based on the
stratication type of estuaries building on Sunderland et al.32 in Python (version 3.12.2). Our model
considers how the different physical, chemical, and hydrodynamic processes affect the speciation and
transformation of Hg species in estuaries and what this means for the export of riverine Hg to the ocean
and MeHg production in the water column and sediments (Fig.1). The various processes and uxes of
Hg species captured in the model include (1) external inputs from river discharge, atmospheric
deposition, and inow of tidal water from the ocean, (2) chemical transformation through inorganic HgII
and Hg0 redox reactions, methylation of HgII and MMHg, and demethylation of MMHg and DMHg, (3)
advective and diffusive mixing in the water column and outow into the ocean, (4) diffusion/bioturbation
from sediment porewater to the overlaying water through the sediment-water interface, (5) settling of
particulate HgII and MMHg in the water column and to sediments, the resuspension from and burial in
benthic sediments, and (6) evasion of Hg0 and DMHg from the water surface through air-sea gas
exchange (Fig.1).
Figure 1 illustrates Hg cycling within an estuary, highlighting the interactions between the atmosphere,
water column, and sediment. Hg enters the estuary through river discharge, tidal inow, and atmospheric
deposition, undergoes transformations (methylation, demethylation, redox reactions), and is transported
Page 5/24
through diffusion, advection, settling, and resuspension processes. Hg can also evade into the
atmosphere or be exported to the ocean. Physical factors like wind, shortwave solar radiation, and water
currents also inuence this cycling.
Mass budget model
The concentration of Hg species in each system is based on a review of measured concentrations and
uxes from the literature (Table1), which are used to calculate the species’ initial reservoir size
(Supplementary Tables S1-S2). Previous literature does not contain the measurements of all four
species of Hg needed to accurately model the biogeochemical, physical, and hydrodynamic processes
affecting Hg cycling in the two estuaries. Therefore, we separated the total Hg (THg) and MeHg
measurements into the four Hg species (HgII, Hg0, MMHg, and DMHg). Many studies report MeHg
concentrations without distinguishing between MMHg and DMHg. Based on average ratios from
previous studies, we estimated MMHg to be 60% and DMHg to be 40% of MeHg.33–36 The HgII
concentration was calculated as the difference between the THg and the sum of Hg0 and MeHg. The Hg0
concentration in CPB is assumed to be about the same concentration of dissolved gaseous Hg (the sum
of Hg0 and DMHg), and is estimated to contain > 90% of Hg0 in surface water.37 No published data for
Hg0 concentrations in HRE exist, so we assume the concentration of Hg0 in the water column to be
approximately 5% of THg concentrations based on literature, where Hg0 ranges between 1-9.3% in
various estuarine environments.19,38–40 Mass budgets for each Hg species are used to create a set of
coupled rst-order differential equations to simulate changes in chemical mass over time.32,40,41 THg
loading from external input into and export out of the system (Supplementary Tables S3) drives the
model to a steady state with a 12-hour time step using average HgII methylation and MMHg and DMHg
demethylation rate constants from literature. See Supplementary Tables S4-S16 for a detailed
description of how the ux rates of the different hydrodynamic and Hg species biogeochemical
processes are calculated.
Page 6/24
Table 1
Chesapeake Bay and Hudson River Estuary range (mean ± standard deviation) of mercury (Hg) species
concentrations, including inorganic (HgII), elemental (Hg0), and methylmercury (MeHg) in the water
column, porewater, and sediment from the literature. These values were used to establish reservoir sizes
and run the box model.
Hg species Chesapeake Bay Hudson River Estuary
Water (pM) HgII 5–20 (7.53 ± 10.61)a87–581 (220 ± 193)c
Hg00.1–0.25 (0.19 + 0.10)a4.35-29 (11.06 ± 9.64)c
MeHg 0.02-1 (0.26 ± 0.25)a0.22–0.65 (0.24 ± 0.20)c
Porewater (pM) HgII 5-23.6 (9.5 ± 5.38)b2.2–78.4 (37.49 ± 18.23)c
MeHg 0.24–2.4 (1.81 ± 0.64)b0-1.8 (0.89 ± 0.49)c
Sediment (pmol/g) HgII 100–850 (395 ± 385)b3000–9000 (4994 ± 
3491)c
MeHg 1–5 (2.13 ± 1.94)b3.1–12.5 (6.6 ± 1.41)c
aMeasurements in the surface waters of the Chesapeake Bay system.19
bBottom sediment measurement in the mainstem of the Chesapeake Bay and the mid-Atlantic
continental margins during four cruises: May 2005, July 2005, August–September 2005, and April
2006.42
cMeasurement in the estuarine turbidity maximum of the HRE between October 2000 and June
2001.22
Stratication and residence time
The stratication of the estuaries was used to separate each estuary's water column into different
compartments and estimate the sizes of Hg reservoirs and residence times in each system
(Supplementary Tables S4-S6). To identify the stratication class of each estuary, we use the estuary's
basin-wide average vertical salinity data from Xu et al.43 and the New York City Department of
Environmental Protection44 to calculate the stratication parameter (Δ). We chose the salinity scheme
method to estimate the stratication because there were multiple spatial salinity measurements along
the estuary transect45. Δ is computed as the tidally average salinity difference ratio between the surface
( ) and bottom water ( ) to the depth-averaged salinity ( ) (Eq.1).45,46
Δ =  Eq.1
Ssal Bsal Asal
Bsal
Ssal
Asal
Page 7/24
When Δ is less than 0.1, it is classied as well-mixed; when Δ is between 0.1 and 1, it is slightly/partially
stratied, and if larger than 1, it is highly/strongly stratied.45,46
The CPB stratication class varies seasonally from slightly stratied during the period coinciding with
higher river inow (> 2600 m3 s− 1) to well-mixed estuary under low river ow conditions (< 1400 m3 s− 1)
(Fig.2A). The system is more stratied in the winter (Δ = 0.11, December-February) and spring (Δ = 0.18,
March-May). The stratication persists into the summer (Δ = 0.16, June-August) as the surface water
warms up and transitions into well-mixed conditions in the fall (Δ = 0.07, September-November) as river
outow decreases.
The stratication types in HRE range from highly to slightly stratied. The strongest stratication occurs
at intermediate salinities (13.7–14.9 ppt) during the winter (Δ = 1.1) and spring (Δ = 1.29) due to higher
river outow (> 500 m3 s− 1) and increased precipitation runoff into the estuary from its 34,700 km2
watershed area (Fig.2B). The highly stratied conditions (Δ > 1) in the HRE are not solely due to
increased freshwater inow. The freshwater input rate must exceed the tidal mixing rate for stratication
to persist. This balance can result from strong freshwater inows, reduced tidal mixing, or a moderate
combination of both inuences, leading to the observed stratication.47
After determining the stratication type of each estuary, we used a hydrological budget equation
(Equations 2 and 3 below) to estimate the seasonal depth of each compartment, which we classied as
the mixed surface layer and stratied bottom layer. The calculations for the surface mixed layer and
stratied bottom layer depths in both highly and slightly stratied systems incorporated the estuary's
total freshwater volume, surface area, and mean central depth (Supplementary Table S5). This approach
enabled us to estimate the water volume in each system, which is necessary for calculating Hg
residence time. Monthly river discharge data for the CPB and HRE were sourced from the USGS Water
Data at the river mouths (Susquehanna, Potomac, Rappahannock, York, and James Rivers)48,49 and
Green Island (near Troy Dam)49,50, respectively (Fig. S1).
= Eq.2
= Eq.3
where is the mixed surface layer depth (m), is the river discharge (m3 s− 1), is the
precipitation inow into the estuary (m3 s− 1), is the water surface area (m2), is central
channel average depth (m), and is the stratied bottom layer depth (m).
The time spent by Hg species in each system was determined using the water residence time in the
estuary. The residence time (τ) in days was calculated using the freshwater method.51–53 This method
uses the salinity of the water volume ( ), freshwater fraction (
FWF
), and freshwater inow rate (
) to estimate the estuary turn-over time (Eq.4–5 and Supplementary Table S6). This calculation
was done for the 12 months of the year based on changes in the monthly river inow and salinity.
Mdep Rivfl
+
Pre
SAw
Sdep Wdep
Mdep
Mdep Rivfl Pre
SAw Wdep
Sdep
V olw
FWfl
Page 8/24
= + Eq.4
τ = *
FWF
* Eq.5
Seasonally, the residence times in the CPB range from 63 to 280 days, whereas those in the HRE are
shorter, ranging from 12 to 20 days. These values are consistent with ndings from previous studies in
the two estuaries.45,54–60 The longer residence times in CPB can be attributed to its larger size and lower
ushing rates, while the shorter residence times in HRE are due to its smaller size and strong tidal
ushing dynamics.61
Results and Discussion
Water column stratication impacts riverine Hg ux to the coastal ocean and Hg removal in estuarine
systems
We compare two estuary model simulations: one that is stratied, where the water column is divided into
layers based on the salinity gradient, and another that is unstratied, where the salinity is uniform
throughout the entire water column. Both models use the same physical, hydrodynamic, and Hg
transformation processes to evaluate how stratication affects Hg removal in the estuaries and,
ultimately, the amount of Hg that reaches the coastal ocean.
Model results indicate that stratication enhances the export of Hg from rivers to the ocean. This trend
is seen for both systems modeled in Fig.3A, where we observe a 19% increase in Hg export in the CPB
and 20% in the HRE as the system becomes more stratied. These results align with prior studies; for
example, Mason
et al
. (1999)19 reported that 29% of the riverine Hg is exported to the ocean from CPB,
which overlaps with our ndings (25–44%). However, the prior study did not include stratication in
estimating this Hg export. To our knowledge, no comparable analysis has been performed on the HRE.
Our model suggests that the development of a pycnocline is key to controlling Hg export in stratied
systems. In a stratied system, riverine THg remains in the surface water above the pycnocline, resulting
in a shorter residence time within the estuary, and is more readily exported to the ocean.
We used the model to evaluate how water column stratication changes the Hg removal processes;
these ndings are summarized in Fig.3B. We see that when a system is well-mixed, the fraction of THg
removed by burial in sediments increases. We attribute this to the longer residence time of Hg species in
unstratied conditions, which allows for more particle-bound Hg to settle out of the water column and be
sequestrated in the sediment. Our ndings regarding the higher fraction of THg buried in unstratied
systems align with other studies that assumed well-mixed conditions in their modeling of Hg in
estuaries. These studies have reported that over 70% of riverine Hg is ultimately buried in estuarine
sediment.4,23,6265 We also see that evasion of Hg decreases by 23 and 13% in CPB and HRE,
respectively, when the systems are unstratied (Fig.3B). The observed changes can largely be attributed
to longer residence time and the absence of a pycnocline. The longer residence time leads to a higher
settling of Hg in unstratied conditions, leaving less Hg in the water column and decreasing the pool
FWfl Rivfl Pre
V olwFWfl
Page 9/24
available for evasion. The absence of pycnocline in the unstratied system enhances tidal mixing of the
large surface riverine Hg pool delivered to the estuary surface with the entire water column, leaving a
lower concentration of Hg in the surface water for evasion. In unstratied estuaries, the mixing of
riverine freshwater with seawater results in a shoaling of the euphotic depth, which occurs due to
particles in the water that decrease the intensity of ultraviolet solar radiation. As a result, the euphotic
depth decreases by 6% in CPB and by 32% in HRE, lowering the production and evasion of volatile Hg0.
Our model results show that the absence of stratication in the estuary water column will increase the
amount of Hg buried in estuarine sediment while decreasing evasion to the atmosphere and export to
the coastal ocean.
Hg removal processes in estuaries respond to seasonal
variability in Hg sources and stratication type
In the previous section, we tested how estuaries respond to changes in stratication while keeping
conditions constant over a year. However, the presence and strength of stratication vary by estuary and
season. For example, CPB and HRE transition to more stratied states as river discharge increases
(Fig.2). Here, we model how seasonal variations in stratication inuence Hg cycling in HRE and CPB.
Figures 4A and 4B show that CPB transitions from well-mixed to slightly stratied conditions when river
discharge increases, resulting in a 20% increase in THg export to the coastal ocean. This is because river
discharge accounts for 71–85% of the annual THg input to CPB, while tidewater inow and atmospheric
deposition contribute less than 30% of the annual THg input. The fraction of THg removed through burial
in sediment also varies with stratication, with well-mixed conditions leading to 25% more THg being
buried in estuarine sediments compared to slightly stratied conditions. This is again due to increased
residence time in well-mixed conditions, which enhances sedimentation eciency for particle-bound Hg
and improves sediment mixing from wave action and tidal forces. Our model's sensitivity to particle
settling indicates that these processes effectively lower Hg concentrations in the water column and
enhance its burial in estuarine sediment. This aligns with ndings in other coastal environments, such as
the Gulf of Trieste, where Hg concentrations in the settling sediment particles were found to be of the
same order of magnitude as the amount of Hg observed in the surface sediments,66 further showing
that settling processes play a crucial role in the transfer of particle-bound Hg from the water column to
the sediment. The evasion ux in CPB is highest under slightly stratied conditions due to a larger pool
of Hg0 and DMHg in the surface water, higher wind speeds, and an increased reduction of HgII to Hg0
(Fig.4A). Slight stratication allows for the input of Hg0 and DMHg from depth to advect to the surface,
where it can easily evade into the atmosphere under suitable conditions. This advective transport
process is absent in well-mixed conditions due to the uniform salinity of the water column. In addition,
tidal circulation inuences the vertical and horizontal distribution of this Hg species in the slightly
stratied systems, with diffusive and advective transport processes redistributing Hg throughout the
water column, allowing for more frequent exchanges between the surface and bottom water layers.67,68
Page 10/24
In contrast, we see that HRE transitions from slightly stratied to highly stratied conditions as river
discharge increases (Fig.4C and 4D), resulting in a 9% increase in THg export to the coastal ocean. Like
CPB, river discharge constitutes 71–88% of the annual THg input to HRE, while tidewater inow and
atmospheric deposition account for less than 30% of the annual THg input. The fraction of THg removed
through burial in sediment is also inuenced by stratication, with slightly stratied conditions leading to
6% more THg being buried compared to highly stratied conditions. This variation arises from the strong
pycnocline in highly stratied conditions. This pycnocline limits vertical mixing, causing Hg species that
settle to the bottom layer to remain trapped in the bottom layer, extending their residence time and
enhancing particle-bound Hg deposition69. The evasion ux of gaseous Hg in HRE mirrors that of CPB,
with the highest ux observed under slightly stratied conditions due to the accumulation and
subsequent release of Hg0 and DMHg from the surface waters (Fig.4D). Observations from Long Island
Sound,70 an estuary 28 km from HRE, further support these ndings, as higher concentrations of
dissolved gaseous Hg and saturation levels were recorded in the surface waters of Long Island Sound
during summer when HRE was also slightly stratied. These further show that the local hydrodynamics
and climatic conditions that inuence stratication in HRE contribute to higher evasion of Hg0 and DMHg
during periods of slight stratication.
Our ndings highlight the important role that river discharge plays in controlling Hg input and
stratication dynamics, which in turn inuences Hg export and other removal processes in estuarine
systems. In a changing climate, increasing storm runoff and freshwater input into estuaries are expected
to enhance stratication, increasing Hg export to the coastal ocean. Land use changes, such as
deforestation, can further exacerbate this process by remobilizing previously deposited Hg in the
terrestrial environment globally (170–300 Mg yr-1).71,72 It is estimated that 1088 ± 379 Gg of Hg is stored
in the global surface soil,73 and land use changes can remobilize this stored Hg and result in elevated
concentrations in river discharge. Moreover, estuaries deliver signicant amounts of nutrients and
organic matter to the coastal ocean,74 which can stimulate biological activity75 and MeHg formation,
potentially contributing to higher Hg burdens in coastal communities. Our model demonstrates that
while well-mixed conditions in CPB act as a substantial sink for riverine Hg, highly and slightly stratied
conditions in both estuaries enhance Hg export to the coastal ocean, potentially elevating coastal Hg
concentrations and posing risks to marine ecosystems and human health.
The presence of stratication in the water column enhances the production and export of estuarine
MeHg to the coastal ocean.
Similarly, as in the previous section, we use the model to investigate how seasonal changes in the
strength of stratication affect the production of MeHg in CPB and HRE. Additionally, we examine how
these changes inuence the quantity of MeHg exported to the coastal ocean from the two estuaries.
In CPB, as the system transitions from slightly stratied to well-mixed conditions, the MeHg production
decreases by 11.5%, leading to a 16.4% decrease in the quantity of MeHg exported to the coastal ocean
annually (Fig.5). We attribute the higher MeHg production under slightly stratied conditions to greater
Page 11/24
river discharge (Fig.2A), which delivers 14.5% more inorganic Hg to the slightly stratied system (Fig.4A
& 5). This higher river inux increases the bioavailable pool of dissolved HgII, the primary substrate for
MeHg formation,76,77 as stratication intensies within the water column. This is consistent with
ndings from Mason
et al.
(2012),78 which highlight the importance of riverine Hg loading in controlling
MeHg concentrations in estuarine and coastal environments. Moreover, the increase in net primary
production under slightly stratied conditions, which we used to parameterize HgII biotic reduction rates
(Supplementary Table16), supports greater HgII formation and subsequent methylation, thereby
facilitating MeHg production.19 Earlier studies have also shown that increased primary production
boosts the availability of organic matter,79 which, when decomposed, consumes oxygen and contributes
to the formation of anoxic zones, thus promoting the methylation of HgII.
In the HRE, the transition from slightly stratied to highly stratied conditions leads to a 1.6% decrease in
MeHg production. This shift results in a 0.7% decrease in the amount of MeHg exported to the coastal
ocean annually (Fig.5). The decrease in MeHg production in the highly stratied conditions, despite a
9.4% increase in inorganic Hg input from river discharge, can be attributed to the shorter residence time
of the water in the surface mixed layer. This leads to a higher ushing rate,11,51,58 resulting in less time
for HgII to undergo methylation within the estuary. The increase in MeHg export to the coastal ocean
under slightly stratied conditions is also attributed to the advective and diffusive mixing between the
surface mixed layer and the stratied bottom layers. This mixing allows some of the MeHg produced at
greater depths to reach the surface,80 where it can be readily exported to the coastal ocean. In contrast,
during highly stratied conditions, strong pycnoclines restrict the mixing of MeHg produced in the
bottom layers, preventing it from reaching the surface. As a result, MeHg accumulates in the stratied
bottom layers, where it undergoes further demethylation and a portion of it is eventually deposited into
the sediment (Fig.4C).19 This means that when stratication is high, there is less MeHg available in the
highly productive surface waters, which may lead to less biological uptake depending on the depth of the
euphotic zone, the location of phytoplankton, and other estuarine mixing processes, possibly resulting in
lower MeHg accumulation in organisms at the base of the food chain. Despite this, MeHg accumulation
in the more stratied bottom layer remains available to deep-dwelling organisms.
Our study highlights the roles of stratication and estuarine mixing in the formation of MeHg from Hg
species entering estuaries via river discharge. Studies show that many estuaries may experience
enhanced water column stratication in the coming decades due to climate change. While exact gures
have not yet been published, modeling studies using regional conditions and specic climate scenarios
suggest that estuaries—particularly those in temperate regions—could exhibit increased stratication as
a result of rising sea levels, warming surface waters, reduced wind mixing, and altered freshwater
inows.8187 Increased freshwater input into estuaries is likely to enhance stratication due to the
difference in density between freshwater (less dense) and seawater (more dense);45,88,89 this density
gradient (pycnocline) separates the less dense freshwater in the surface layer and the denser, saline
water below.45,90,91 This strong pycnocline weakens vertical oxygen exchange and can lead to the
Page 12/24
development of near-bed hypoxia,82,88,92 a condition known to favor the formation of MeHg.19,76 Our
ndings reveal that MeHg production and export to the coastal ocean increased by 11.5% and 16.4%,
respectively, when the stratication conditions in CPB shifted from well-mixed to slightly stratied. This
indicates that many estuaries may experience an increased export of MeHg to the coastal ocean as the
climate changes.
Declarations
Acknowledgments
We acknowledge the National Science Foundation Division of Ocean Sciences (grant 2023046 and
2414798 to A.T.S.), the National Institute of Environmental Health Sciences (Project 1P01ES035541–01
7782), the National Aeronautics and Space Administration (grant 80NSSC21K0713 to J.T. Farrar and
subaward to A.T.S.). We thank J. Farrar, J. West, and H. Adams for their valuable feedback on this
manuscript.
Competing Interests
The authors declare no competing interests.
Supplementary Information
The study area is illustrated in the map (Supplementary Figure S1), data used to run the model to a
steady state (Supplementary Tables S1-S16), parameterization of the physical and biogeochemical
processes controlling mercury cycling in the estuary (Supplementary Tables S1-S16 and Equations S1-
S31), and a detailed description of mercury species transport and biogeochemical transformation
processes in estuary as conceptualized in our model (Supplementary Texts S1-S2).
References
1. Fitzgerald, W. F., Lamborg, C. H. & Hammerschmidt, C. R. Marine Biogeochemical Cycling of
Mercury.
Chem. Rev.
107, 641–662 (2007).
2. Mason, R. P.
et al.
Mercury biogeochemical cycling in a stratied estuary.
Limnol. Oceanogr.
38,
1227–1241 (1993).
3. Liu, M.
et al.
Rivers as the largest source of mercury to coastal oceans worldwide.
Nat. Geosci.
14,
672–677 (2021).
4. Amos, H. M.
et al.
Global Biogeochemical Implications of Mercury Discharges from Rivers and
Sediment Burial.
Environ. Sci. Technol.
48, 9514–9522 (2014).
5. Cossa, D., Coquery, M., Gobeil, C. & Martin, J.-M. Mercury Fluxes at the Ocean Margins. in
Global and
Regional Mercury Cycles: Sources, Fluxes and Mass Balances
(eds. Baeyens, W., Ebinghaus, R. &
Vasiliev, O.) 229–247 (Springer Netherlands, Dordrecht, 1996). doi:10.1007/978-94-009-1780-4_11.
Page 13/24
. Outridge, P. M., Mason, R. P., Wang, F., Guerrero, S. & Heimbürger-Boavida, L. E. Updated Global and
Oceanic Mercury Budgets for the United Nations Global Mercury Assessment 2018.
Environ. Sci.
Technol.
52, 11466–11477 (2018).
7. Costa, I., Bordalo, A. & Duarte, P. Inuence of River Discharge Patterns on the Hydrodynamics and
Potential Contaminant Dispersion in the Douro Estuary (Portugal).
Water Res.
44, 3133–46 (2010).
. Iglesias, I.
et al.
Linking contaminant distribution to hydrodynamic patterns in an urban estuary: The
Douro estuary test case.
Sci. Total Environ.
707, 135792 (2019).
9. Papaslioti, E.-M.
et al.
Temporal dynamics of contaminants in an estuarine system affected by acid
mine drainage discharges.
Sci. Total Environ.
947, 174683 (2024).
10. Chen, Z., Li, G., Bowen, M. & Coco, G. Retention of buoyant plastic in a well-mixed estuary due to
tides, river discharge and winds.
Mar. Pollut. Bull.
194, 115395 (2023).
11. Marsooli, R., Orton, P. M., Fitzpatrick, J. & Smith, H. Residence Time of a Highly Urbanized Estuary:
Jamaica Bay, New York.
J. Mar. Sci. Eng.
6, 44 (2018).
12. Williamson, R. B. & Morrisey, D. J. Stormwater Contamination of Urban Estuaries. 1. Predicting the
Build-Up of Heavy Metals in Sediments.
Estuaries
23, 56–66 (2000).
13. Carrasco, L., Benejam, L., Benito, J., Bayona, J. M. & Díez, S. Methylmercury levels and
bioaccumulation in the aquatic food web of a highly mercury-contaminated reservoir.
Environ. Int.
37, 1213–1218 (2011).
14. Chen, C. Y.
et al.
Benthic and Pelagic Pathways of Methylmercury Bioaccumulation in Estuarine
Food Webs of the Northeast United States.
PLoS ONE
9, e89305 (2014).
15. Harding, G., Dalziel, J. & Vass, P. Bioaccumulation of methylmercury within the marine food web of
the outer Bay of Fundy, Gulf of Maine.
PLoS ONE
13, e0197220 (2018).
1. Chen, C.-F., Ju, Y.-R., Chen, C.-W. & Dong, C.-D. The distribution of methylmercury in estuary and
harbor sediments.
Sci. Total Environ.
691, 55–63 (2019).
17. Merritt, K. A. & Amirbahman, A. Methylmercury cycling in estuarine sediment pore waters
(Penobscot River estuary, Maine, USA).
Limnol. Oceanogr.
53, 1064–1075 (2008).
1. Schartup, A. T., Mason, R. P., Balcom, P. H., Hollweg, T. A. & Chen, C. Y. Methylmercury Production in
Estuarine Sediments: Role of Organic Matter.
Environ. Sci. Technol.
47, 695–700 (2013).
19. Mason, R. P.
et al.
Mercury in the Chesapeake Bay.
Mar. Chem.
65, 77–96 (1999).
20. Chakraborty, P., Sarkar, A., Vudamala, K., Naik, R. & Nath, B. N. Organic matter — A key factor in
controlling mercury distribution in estuarine sediment.
Mar. Chem.
173, 302–309 (2015).
21. Mazrui, N. M., Jonsson, S., Thota, S., Zhao, J. & Mason, R. P. Enhanced availability of mercury bound
to dissolved organic matter for methylation in marine sediments.
Geochim. Cosmochim. Acta
194,
153 (2016).
22. Heyes, A., Miller, C. & Mason, R. P. Mercury and methylmercury in Hudson River sediment: impact of
tidal resuspension on partitioning and methylation.
Mar. Chem.
90, 75–89 (2004).
Page 14/24
23. Liu, M.
et al.
Riverine Discharge Fuels the Production of Methylmercury in a Large Temperate
Estuary.
Environ. Sci. Technol.
57, 13056–13066 (2023).
24. Austin, J. A. Estimating the mean ocean-bay exchange rate of the Chesapeake Bay.
J. Geophys. Res.
Oceans
107, 13-1-13–8 (2002).
25. Browne, D. R. & Fisher, C. W. Tide and tidal currents in the Chesapeake Bay.
U. S. Natl. Ocean Serv.
Off. Oceanogr. Mar. Assess.
(1988).
2. Li, M., Zhong, L. & Boicourt, W. C. Simulations of Chesapeake Bay estuary: Sensitivity to turbulence
mixing parameterizations and comparison with observations.
J. Geophys. Res. Oceans
110, (2005).
27. Wilson, R. E. Dynamics of Partially Mixed Estuaries. in
Hydrodynamics of Estuaries
(CRC Press,
1988).
2. Cooper, J. C., Cantelmo, F. R. & Newton, C. E. Overview of the Hudson River Estuary. in
Science, Law,
and Hudson River Power Plants
vol. 4 11–24 (American Fisheries Society Monograph, 1988).
29. Warner, J. C., Geyer, W. R. & Lerczak, J. A. Numerical modeling of an estuary: A comprehensive skill
assessment.
J. Geophys. Res. Oceans
110, (2005).
30. National Oceanic and Atmospheric Administration (NOAA). Classifying Estuaries: By Water
Circulation. https://oceanservice.noaa.gov/education/tutorial_estuaries/est05_circulation.html.
31. Wells, A. & Young, J. Long-term variability and predictability of Hudson River physical and chemical
characteristics. in 29–58 (1992).
32. Sunderland, E. M.
et al.
Response of a macrotidal estuary to changes in anthropogenic mercury
loading between 1850 and 2000.
Environ. Sci. Technol.
44, 1698–1704 (2010).
33. Bieser, J.
et al.
The 3D biogeochemical marine mercury cycling model MERCY v2.0 – linking
atmospheric Hg to methylmercury in sh.
Geosci. Model Dev.
16, 2649–2688 (2023).
34. Lehnherr, I., St. Louis, V. L., Hintelmann, H. & Kirk, J. L. Methylation of inorganic mercury in polar
marine waters.
Nat. Geosci.
4, 298–302 (2011).
35. Mason, R. P. & Sullivan, K. A. The distribution and speciation of mercury in the South and equatorial
Atlantic.
Deep Sea Res. Part II Top. Stud. Oceanogr.
46, 937–956 (1999).
3. Munson, K. M., Lamborg, C. H., Swarr, G. J. & Saito, M. A. Mercury species concentrations and uxes
in the Central Tropical Pacic Ocean.
Glob. Biogeochem. Cycles
29, 656–676 (2015).
37. Mason, R. P., Rolfhus, K. R. & Fitzgerald, W. F. Mercury in the North Atlantic.
Mar. Chem.
61, 37–53
(1998).
3. Baeyens, W. & Leermakers, M. Elemental mercury concentrations and formation rates in the Scheldt
estuary and the North Sea.
Mar. Chem.
60, 257–266 (1998).
39. Benoit, J. M., Gilmour*, C. C., Mason, R. P., Riedel, G. S. & Riedel, G. F. Behavior of mercury in the
Patuxent River estuary.
Biogeochemistry
40, 249–265 (1998).
40. Schartup, A. T.
et al.
Freshwater discharges drive high levels of methylmercury in Arctic marine
biota.
Proc. Natl. Acad. Sci. U. S. A.
112, 11789–11794 (2015).
Page 15/24
41. Soerensen, A. L.
et al.
A mass budget for mercury and methylmercury in the Arctic Ocean: ARCTIC
OCEAN HG AND MEHG MASS BUDGET.
Glob. Biogeochem. Cycles
30, 560–575 (2016).
42. Hollweg, T. A., Gilmour, C. C. & Mason, R. P. Methylmercury production in sediments of Chesapeake
Bay and the mid-Atlantic continental margin.
Mar. Chem.
114, 86–101 (2009).
43. Xu, J.
et al.
Climate Forcing and Salinity Variability in Chesapeake Bay, USA.
Estuaries Coasts
35,
237–261 (2012).
44. New York City Department of Environmental Protection. Harbor Water Quality, 2015. Data accessed
from NYC website: https://data.cityofnewyork.us/widgets/5uug-f49n; accessed 06/04/2024.
45. Shen, X., Detenbeck, N. & You, M. Spatial and temporal variations of estuarine stratication and
ushing time across the continental U.S.
Estuar. Coast. Shelf Sci.
279, 108147 (2022).
4. Hansen, D. & Rattray, M. Gravitational circulation in straits and estuaries.
J. Mar. Res.
23, (1965).
47. Geyer, W. R. & Ralston, D. K. 2.03 - The Dynamics of Strongly Stratied Estuaries. in
Treatise on
Estuarine and Coastal Science
(eds. Wolanski, E. & McLusky, D.) 37–51 (Academic Press, Waltham,
2011). doi:10.1016/B978-0-12-374711-2.00206-0.
4. U.S. Geological Survey. Water Data for the Chesapeake Bay, accessed April 12, 2024, at
https://www.usgs.gov/centers/chesapeake-bay-activities/science/freshwater-ow-chesapeake-bay.
49. U.S. Geological Survey. Water Data for the Nation, accessed March 25, 2024, at
http://waterdata.usgs.gov/nwis/.
50. U.S. Geological Survey. Water Data for the Hudson River at Green Island NY, accessed July 14, 2024,
at https://waterdata.usgs.gov/monitoring-location/01358000/#dataTypeId=continuous-00065-
0&period=P7D&showMedian=false.
51. Lemagie, E. & Lerczak, J. A Comparison of Bulk Estuarine Turnover Timescales to Particle Tracking
Timescales Using a Model of the Yaquina Bay Estuary.
Estuaries Coasts
38, (2014).
52. Sheldon, J. E. & Alber, M. The calculation of estuarine turnover times using freshwater fraction and
tidal prism models: A critical evaluation.
Estuaries Coasts
29, 133–146 (2006).
53. Dyer, K.R., 1973. Estuaries: A Physical Introduction. Wiley, London.
54. Du, J. & Shen, J. Water residence time in Chesapeake Bay for 1980-2012.
J. Mar. Syst.
164, 101–111
(2016).
55. Howarth, R. W., Marino, R., Swaney, D. P. & Boyer, E. W. Wastewater and Watershed Inuences on
Primary Productivity and Oxygen Dynamics in the Lower Hudson River Estuary. in
The Hudson River
Estuary
(eds. Levinton, J. S. & Waldman, J. R.) 121–139 (Cambridge University Press, Cambridge,
2006). doi:10.1017/CBO9780511550539.012.
5. Shen, J., Du, J. & Lucas, L. V. Simple relationships between residence time and annual nutrient
retention, export, and loading for estuaries.
Limnol. Oceanogr.
67, 918–933 (2022).
57. Shen, J. & Wang, H. V. Determining the age of water and long-term transport timescale of the
Chesapeake Bay.
Estuar. Coast. Shelf Sci.
74, 585–598 (2007).
Page 16/24
5. Zhang, W. G., Wilkin, J. L. & Schoeld, O. M. E. Simulation of Water Age and Residence Time in New
York Bight. (2010) doi:10.1175/2009JPO4249.1.
59. Warner, J. C., Rockwell Geyer, W. & Arango, H. G. Using a composite grid approach in a complex
coastal domain to estimate estuarine residence time.
Comput. Geosci.
36, 921–935 (2010).
0. Andutta, F. P., Ridd, P. V., Deleersnijder, E. & Prandle, D. Contaminant exchange rates in estuaries –
New formulae accounting for advection and dispersion.
Prog. Oceanogr.
120, 139–153 (2014).
1. Geyer, W. R. & Chant, R. The Physical Oceanography Processes in the Hudson River Estuary. in
The
Hudson River Estuary
(eds. Levinton, J. S. & Waldman, J. R.) 24–38 (Cambridge University Press,
Cambridge, 2006). doi:10.1017/CBO9780511550539.005.
2. Buck, C. S., Hammerschmidt, C. R., Bowman, K. L., Gill, G. A. & Landing, W. M. Flux of Total Mercury
and Methylmercury to the Northern Gulf of Mexico from U.S. Estuaries.
Environ. Sci. Technol.
49,
13992–13999 (2015).
3. Meng, M.
et al.
An Integrated Model for Input and Migration of Mercury in Chinese Coastal
Sediments.
Environ. Sci. Technol.
53, 2460–2471 (2019).
4. Molina, A., Duque, G. & Cogua, P. Effect of environmental variables on mercury accumulation in
sediments of an anthropogenically impacted tropical estuary (Buenaventura Bay, Colombian
Pacic).
Environ. Monit. Assess.
195, 1316 (2023).
5. Zhang, Y.
et al.
Biogeochemical drivers of the fate of riverine mercury discharged to the global and
Arctic oceans.
Glob. Biogeochem. Cycles
29, 854–864 (2015).
. Pavoni, E.
et al.
Fluxes of settling sediment particles and associated mercury in a coastal
environment contaminated by past mining (Gulf of Trieste, northern Adriatic Sea).
J. Soils
Sediments
23, 4098–4109 (2023).
7. Huguenard, K. D., Valle-Levinson, A., Li, M., Chant, R. J. & Souza, A. J. Linkage between lateral
circulation and near-surface vertical mixing in a coastal plain estuary.
J. Geophys. Res. Oceans
120,
4048–4067 (2015).
. Zou, T., Zhang, H., Meng, Q. & Li, J. Seasonal Hydrodynamics and Salt Exchange of a Shallow Estuary
in Northern China.
J. Coast. Res.
74, 95–103 (2016).
9. Dellapenna, T. M., Hoelscher, C., Hill, L., Al Mukaimi, M. E. & Knap, A. How tropical cyclone ooding
caused erosion and dispersal of mercury-contaminated sediment in an urban estuary: The impact of
Hurricane Harvey on Buffalo Bayou and the San Jacinto Estuary, Galveston Bay, USA.
Sci. Total
Environ.
748, 141226 (2020).
70. Rolfhus, K. R. & Fitzgerald, W. F. The evasion and spatial/temporal distribution of mercury species in
Long Island Sound, CT-NY.
Geochim. Cosmochim. Acta
65, 407–418 (2001).
71. Lacerda, L. D., de Souza, M. & Ribeiro, M. G. The effects of land use change on mercury distribution
in soils of Alta Floresta, Southern Amazon.
Environ. Pollut.
129, 247–255 (2004).
72. Obrist, D.
et al.
A review of global environmental mercury processes in response to human and
natural perturbations: Changes of emissions, climate, and land use.
Ambio
47, 116–140 (2018).
Page 17/24
73. Wang, X.
et al.
Climate and Vegetation As Primary Drivers for Global Mercury Storage in Surface
Soil.
Environ. Sci. Technol.
53, 10665–10675 (2019).
74. Cloern, J. Our evolving conceptual model of the coastal eutrophication problem.
Mar. Ecol. Prog.
Ser.
210, 223–253 (2001).
75. Cloern, J. E., Foster, S. Q. & Kleckner, A. E. Phytoplankton primary production in the world’s estuarine-
coastal ecosystems.
Biogeosciences
11, 2477–2501 (2014).
7. Bravo, A. G. & Cosio, C. Biotic formation of methylmercury: A bio–physico–chemical conundrum.
Limnol. Oceanogr.
65, 1010–1027 (2020).
77. Munson, K. M., Lamborg, C. H., Boiteau, R. M. & Saito, M. A. Dynamic mercury methylation and
demethylation in oligotrophic marine water.
Biogeosciences
15, 6451–6460 (2018).
7. Mason, R. P.
et al.
Mercury biogeochemical cycling in the ocean and policy implications.
Environ.
Res.
119, 101–117 (2012).
79. Eckley, C. S., Luxton, T. P., Knightes, C. D. & Shah, V. Methylmercury Production and Degradation
under Light and Dark Conditions in the Water Column of the Hells Canyon Reservoirs, USA.
Environ.
Toxicol. Chem.
40, 1827–1837 (2021).
0. Adams, H. M., Cui, X., Lamborg, C. H. & Schartup, A. T. Dimethylmercury as a Source of
Monomethylmercury in a Highly Productive Upwelling System.
Environ. Sci. Technol.
58, 10591–
10600 (2024).
1. Lupiola, J., Bárcena, J. F., García-Alba, J. & García, A. A numerical study of the mixing and
stratication alterations in estuaries due to climate change using the potential energy anomaly.
Front. Mar. Sci.
10, (2023).
2. Hong, B. & Shen, J. Responses of estuarine salinity and transport processes to potential future sea-
level rise in the Chesapeake Bay.
Estuar. Coast. Shelf Sci.
104–105, 33–45 (2012).
3. Khojasteh, D., Glamore, W., Heimhuber, V. & Felder, S. Sea level rise impacts on estuarine dynamics:
A review.
Sci. Total Environ.
780, 146470 (2021).
4. Liu, W.-C. & Liu, H.-M. Assessing the Impacts of Sea Level Rise on Salinity Intrusion and Transport
Time Scales in a Tidal Estuary, Taiwan.
Water
6, 324–344 (2014).
5. Krvavica, N. & Ružić, I. Assessment of sea-level rise impacts on salt-wedge intrusion in idealized and
Neretva River Estuary.
Estuar. Coast. Shelf Sci.
234, 106638 (2020).
. Cloern, J. E.
et al.
Projected Evolution of California’s San Francisco Bay-Delta-River System in a
Century of Climate Change.
PLOS ONE
6, e24465 (2011).
7. Najjar, R. G.
et al.
Potential climate-change impacts on the Chesapeake Bay.
Estuar. Coast. Shelf Sci.
86, 1–20 (2010).
. Duvall, M. S., Jarvis, B. M. & Wan, Y. Impacts of climate change on estuarine stratication and
implications for hypoxia within a shallow subtropical system.
Estuar. Coast. Shelf Sci.
279, 1–14
(2022).
Page 18/24
9. Ni, W., Li, M., Ross, A. C. & Najjar, R. G. Large Projected Decline in Dissolved Oxygen in a Eutrophic
Estuary Due to Climate Change.
J. Geophys. Res. Oceans
124, 8271–8289 (2019).
90. Geyer, W. R. Estuarine salinity structure and circulation.
Contemp. Issues Estuar. Phys.
12–26 (2010)
doi:10.1017/CBO9780511676567.003.
91. Geyer, W. R. & Ralston, D. K. 2.03 - The Dynamics of Strongly Stratied Estuaries. in
Treatise on
Estuarine and Coastal Science
(eds. Wolanski, E. & McLusky, D.) 37–51 (Academic Press, Waltham,
2011). doi:10.1016/B978-0-12-374711-2.00206-0.
92. Pein, J.
et al.
Seasonal Stratication and Biogeochemical Turnover in the Freshwater Reach of a
Partially Mixed Dredged Estuary.
Front. Mar. Sci.
8, (2021).
Figures
Figure 1
Conceptual diagram of estuarine mercury (Hg) cycling processes considered in the model. Each arrow
color highlights a distinct pathway in the Hg cycling process; orange arrows represent external inputs
into the water column, purple arrows show outputs from the water column, green arrows represent
biogeochemical transformations between the four main Hg species (divalent: HgII, elemental: Hg0,
monomethylmercury: MMHg, and dimethylmercury: DMHg), and yellow arrows show the physical forcing
and estuarine mixing mechanisms.
Page 19/24
Figure 2
Basin-wide long-term seasonal variation in water column stratication and river discharge in (A)
Chesapeake Bay (CPB) and (B) Hudson River Estuary (HRE). In both systems, the black lines represent
the calculated stratication parameter, and the green bars show the average river discharge across four
seasons: winter (December-February), spring (March-May), summer (June-August), and fall (September-
November). The background shading indicates different levels of stratication, with light blue
Page 20/24
representing well-mixed conditions and dark blue representing slightly stratied conditions in CPB, while
in HRE, light green shows slightly stratied conditions and dark green indicating highly stratied
conditions.
Figure 3
Effect of stratication on mercury (Hg) removal processes in the Chesapeake Bay and Hudson River
Estuary. (A) Illustrates the total Hg (THg) percentage in river discharge reaching the coastal ocean. (B)
Page 21/24
The relative contribution of THg removal processes from stratied and unstratied estuaries. The light
colors in the bar chart in Figure A and the background shading in the pie chart in Figure B represent
unstratied estuaries, and the dark colors represent stratied estuaries. The color-coded segments in the
pie charts represent different processes; the white color represents the evasion of gaseous Hg to the
atmosphere, the yellow color represents the burial of THg in the sediment, and the dark blue color
represents the export of THg from the estuary to the ocean.
Figure 4
Page 22/24
Mass budget of mercury (Hg) cycling in the estuaries under different stratication conditions at steady
state. A) Chesapeake Bay (CPB) under slightly stratied conditions during periods of increased river
discharge. B) Chesapeake Bay (CPB) under well-mixed conditions during periods of decreased river
discharge. C) Hudson River Estuary (HRE) under highly stratied conditions during periods of increased
river discharge. D) Hudson River Estuary (HRE) under slightly stratied conditions during periods of
decreased river discharge. The inorganic Hg reservoirs are in kmol, and the organic Hg reservoirs are in
mol. Each arrow color highlights a distinct pathway in the Hg cycling process, with orange arrows
representing external inputs into the water column, purple arrows representing outputs from the water
column, green arrows representing biogeochemical transformations between the four main Hg species,
and yellow arrows representing the estuarine mixing mechanisms.
Page 23/24
Figure 5
Changes in biogeochemical mercury (Hg) processes under different estuary stratication conditions.
The bar chart illustrates the variations in MeHg production, dimethylmercury (DMHg) evasion, the export
of methylmercury (MeHg) to the coastal ocean, and the input of riverine inorganic Hg between the
Hudson River Estuary (shown in dark green) and Chesapeake Bay (shown in light blue) as the systems
transition from slightly stratied to other stratication conditions (well-mixed and highly stratied).
Page 24/24
Supplementary Files
This is a list of supplementary les associated with this preprint. Click to download.
SupplementalInformation.docx
oatimage1.png
ResearchGate has not been able to resolve any citations for this publication.
Article
Full-text available
Mercury (Hg) is a pollutant of global concern. Due to anthropogenic emissions, the atmospheric and surface ocean Hg burden has increased substantially since preindustrial times. Hg emitted into the atmosphere gets transported on a global scale and ultimately reaches the oceans. There it is transformed into highly toxic methylmercury (MeHg) that effectively accumulates in the food web. The international community has recognized this serious threat to human health and in 2017 regulated Hg use and emissions under the UN Minamata Convention on Mercury. Currently, the first effectiveness evaluation of the Minamata Convention is being prepared, and, in addition to observations, models play a major role in understanding environmental Hg pathways and in predicting the impact of policy decisions and external drivers (e.g., climate, emission, and land-use change) on Hg pollution. Yet, the available model capabilities are mainly limited to atmospheric models covering the Hg cycle from emission to deposition. With the presented model MERCY v2.0 we want to contribute to the currently ongoing effort to improve our understanding of Hg and MeHg transport, transformation, and bioaccumulation in the marine environment with the ultimate goal of linking anthropogenic Hg releases to MeHg in seafood. Here, we present the equations and parameters implemented in the MERCY model and evaluate the model performance for two European shelf seas, the North and Baltic seas. With the model evaluation, we want to establish a set of general quality criteria that can be used for evaluation of marine Hg models. The evaluation is based on statistical criteria developed for the performance evaluation of atmospheric chemistry transport models. We show that the MERCY model can reproduce observed average concentrations of individual Hg species in water (normalized mean bias: HgT 17 %, Hg0 2 %, MeHg -28 %) in the two regions mentioned above. Moreover, it is able to reproduce the observed seasonality and spatial patterns. We find that the model error for HgT(aq) is mainly driven by the limitations of the physical model setup in the coastal zone and the availability of data on Hg loads in major rivers. In addition, the model error in calculating vertical mixing and stratification contributes to the total HgT model error. For the vertical transport we find that the widely used particle partitioning coefficient for organic matter of log(kd)=5.4 is too low for the coastal systems. For Hg0 the model performance is at a level where further model improvements will be difficult to achieve. For MeHg, our understanding of the processes controlling methylation and demethylation is still quite limited. While the model can reproduce average MeHg concentrations, this lack of understanding hampers our ability to reproduce the observed value range. Finally, we evaluate Hg and MeHg concentrations in biota and show that modeled values are within the range of observed levels of accumulation in phytoplankton, zooplankton, and fish. The model performance demonstrates the feasibility of developing marine Hg models with similar predictive capability to established atmospheric chemistry transport models. Our findings also highlight important knowledge gaps in the dynamics controlling methylation and bioaccumulation that, if closed, could lead to important improvements of the model performance.
Article
Full-text available
Monomethylmercury (MMHg) is a neurotoxicant that biomagnifies in marine food webs, reaching high concentrations in apex predators. To predict changes in oceanic MMHg concentrations, it is important to quantify the sources and sinks of MMHg. Here, we study mercury speciation in the California Current System through cruise sampling and modeling. Previous work in the California Current System has found that upwelling transports mercury-enriched deep waters to productive surface waters. These upwelled waters originate within the California Undercurrent water mass and are subsequently advected as a surface water parcel to the California Current. Between the two major water masses, we find that compared to the California Current, the California Undercurrent contains elevated dissolved total mercury (THg) and dimethylmercury (DMHg) concentrations by 59 and 69%, respectively. We explain that these differences result from losses during advection, specifically scavenging of THg and DMHg demethylation. We calculate a net DMHg demethylation rate of 2.0 ± 1.1% d–1 and build an empirically constrained mass budget model to demonstrate that net DMHg demethylation accounts for 61% of surface MMHg sources. These findings illustrate that DMHg is a significant source of MMHg in this region, challenging the current understanding of the major sources of marine MMHg.
Article
Full-text available
Estuaries are the main entry areas of mercury to the marine environment and are important to understand the effect of this contaminant on marine organisms, since it accumulates in the sediments becoming available to enter the food trophic chain. This study aims to determine the environmental variables that mainly influence the spatiotemporal dynamics of total mercury accumulation in sediments of tropical estuaries. Sediment samples were collected from interior and exterior areas of the estuary during the dry and rainy seasons, representing the spatiotemporal gradients of the estuary. The grain size, organic matter content (OM), and total mercury concentration (THg) of the sediment samples were determined. In addition, salinity, temperature, dissolved oxygen, and pH of the water column associated with each sediment sample were assessed. The variations in environmental conditions, OM and THg in sediment were in accordance with a gradient which goes from conditions influenced by fresh water in the inner estuary to conditions influenced by sea water in the outer part of the estuary. The OM and THg in sediments presented similar variation patterns; they were higher in the rainy season than in the dry season and in the interior area of the estuary than in the exterior area. Despite the complex dynamic observed in the distribution and accumulation processes of mercury in sediments, these processes could be modeled from OM and salinity parameters. Due to the correlations found, in the process of accumulation of mercury in sediments the OM could represents the pathway of transport and accumulation of THg, and salinity could represent the influence of the hydroclimatic variations and environmental gradients of the estuary. Supplementary Information The online version contains supplementary material available at 10.1007/s10661-023-11721-9.
Article
Full-text available
The competition between mixing and stratification in estuaries determines the quality of their waters, living conditions, and uses. These processes occur due to the interaction between tidal and fluvial contributions, which significantly vary depending on the estuarine characteristics. For the study of mixing and stratification alterations in estuaries due to climate change, a new methodology is proposed based on high-resolution 3D hydrodynamic modeling to compute the Potential Energy Anomaly (PEA). Regarding the model scenarios, first, a base case is analyzed with the realistic forcings of the year 2020. Subsequently, the forecasts of anomalies due to climate change for sea conditions (level, temperature, and salinity), atmosphere conditions (precipitation, air temperature, relative humidity, and solar irradiance), and river conditions (flow and temperature) are projected for the year 2020. The selected scenarios to analyze hydrodynamic changes are RCP 4.5 and 8.5 for the years 2050 and 2100. The proposed methodology has been applied to the Suances estuary. Independently of the climate change scenario, the stratification intensity increases and decreases upstream and downstream of the estuary, respectively. These results indicate that unlike the 2020 base scenario, in which the stratification zone has been mainly centered between km 4 and 8, for the new climate change scenarios, the stratification zone will be displaced between km 2 and 8, attenuating its intensity from km 4 onwards. The Suances estuary presents and will present under the considered scenarios a high spatiotemporal variability of the mixing and stratification processes. On the one hand, sea level rise will pull the stratification zones back inland from the estuary. On the other hand, climate change will generate lower precipitations and higher temperatures, decreasing runoff events. This phenomenon will decrease the freshwater input to the estuary and increase the tidal excursion along the estuary, producing a displacement of the river/estuarine front upstream of the areas.
Article
Full-text available
Purpose As the result of historical mining at Idrija (Slovenia), mercury (Hg) contamination in the Gulf of Trieste (northern Adriatic Sea) is still an issue of environmental concern. The element has been conveyed into the coastal area by the Isonzo/Soča River inputs of freshwater and suspended particles for centuries. This research aims to investigate the occurrence of Hg bound to the settling sediment particles (SSP) in the coastal water and to assess the sedimentary Hg fluxes. Methods Settling sediment particles were collected at four sites located in the innermost sector of the Gulf, a shallow and sheltered embayment where the accumulation of fine sediments is promoted. Six sampling campaigns were performed under different environmental conditions in terms of discharge from the Isonzo River and 12 sediment traps were installed in the upper and bottom water column for SSP collection. Settling sediment particles (SSP) were collected approximately every 2 weeks and analysed for grain size and total Hg. Results Settling sediment particles (SSP) consisted predominantly of silt (77.7 ± 10.1%), showing a concentration of Hg ranging overall between 0.61 and 6.87 µg g⁻¹. Regarding the daily SSP fluxes, the minimum (7.05 ± 3.26 g m⁻² day⁻¹) and the maximum (92.4 ± 69.0 g m⁻² day⁻¹) values were observed under conditions of low and high river discharge, respectively. The daily Hg fluxes displayed a notable variability, up to an order of magnitude, both in the surface water layer (3.07–94.6 µg m⁻² day⁻¹) and at the bottom (11.3–245 µg m⁻² day⁻¹), reaching the maximum values following periods of high river flow. Conclusions The Isonzo River inputs of suspended particulate matter continue to convey Hg into the Gulf of Trieste, especially following river flood events, which represent one of the most relevant natural factors affecting the variations of the Hg flux in the investigated area.
Article
Full-text available
Vertical density stratification often plays an important role in the formation and expansion of coastal hypoxic zones through its effect on near-bed circulation and vertical oxygen flux. However, the impact of future climate change on estuarine circulation is widely unknown. Here, we developed and calibrated a three-dimensional hydrodynamic model for Pensacola Bay, a shallow subtropical estuary in the northeastern Gulf of Mexico. Model simulations based on years 2013–2017 were applied to examine changes in salinity, temperature, and density under future climate scenarios, including increased radiative forcing (IR) and temperature (T), increased freshwater discharge (D), sea level rise (SLR), and wind intensification (W). Simulations showed that the impacts of climate change on modeled state variables varied over time with external forcing conditions. The model demonstrated the potential for sea level rise and increased freshwater discharge to episodically increase vertical density gradients in the Bay. However, increased wind forcing destabilized vertical gradients, at times reducing the spatial extent and duration of stable stratification. For time periods with low freshwater discharge, moderate increases in wind speed (10%) can destabilize density gradients strengthened by increased discharge (10%) and sea level rise (0.48 m). In contrast, destruction of strong density gradients that form near the mid-Bay channel following flood events requires stronger wind forcing. These results highlight the importance of considering natural variability in freshwater and wind forcing, as well as local phenomena that are generally unresolved by global climate models.
Article
Estuaries can act as plastic retention hotspots, but the hydrodynamic controls on retention are not well understood. This study investigates the retention of river-sourced buoyant plastics in a well-mixed estuary, the Waitematā Estuary, using validated numerical simulations of floats with different tides, winds, and freshwater discharge. The proportion of floats grounded on the shore in all seven simulations is higher than 60 % and over 90 % in five simulations after ten days. <20 % of the floats leave the estuarine mouth in any of the simulations. An increase of two orders of magnitude in freshwater discharge doubles the likelihood for floats to reach the lower estuary. However, we find increased freshwater discharge doubles the lateral circulation towards the shore and results in similar proportions of grounding (90 %) as the low discharge cases. These findings challenge the conventional view that plastics preferentially enter the open ocean after high river discharge.
Article
Estuaries are an important food source for the world's growing population, yet human health is at risk from elevated exposure to methylmercury (MeHg) via the consumption of estuarine fish. Moreover, the sources and cycling of MeHg in temperate estuarine ecosystems are poorly understood. Here, we investigated the seasonal and tidal patterns of mercury (Hg) forms in Long Island Sound (LIS), in a location where North Atlantic Ocean waters mix with the Connecticut River. We found that seasonal variations in Hg and MeHg in LIS followed the extent of riverine Hg delivery, while tides further exacerbated the remobilization of earlier deposited riverine Hg. The net production of MeHg near the river plume was significant compared to that in other locations and enhanced during high tide, possibly resulting from the enhanced microbial activity and organic carbon remineralization in the river plume. Statistical models, driven by our novel data, further support the hypothesis that the river-delivered organic matter and inorganic Hg drive net MeHg production in the estuarine water column. Our study sheds light on the significance of water column biogeochemical processes in temperate tidal estuaries in regulating MeHg levels and inspires new questions in our quest to understand MeHg sources and dynamics in coastal oceans.
Article
Estuarine circulation attributes such as stratification and flushing time significantly influence estuarine ecological processes. Stratification reflects how much vertical mixing occurs in an estuary, while flushing time can describe the exchange rate of pollutants between the estuary and ocean. A recently developed estuarine characterization framework used estuarine geophysical attributes and water exchange datasets to characterize estuarine circulation for 360 estuaries in the continental U.S. between 1950 and 2015. The estuaries were grouped into nine ecoregions according to the Marine Ecoregions of the World. In the Gulf of Mexico and along the East Coast, most estuaries were well-mixed (63–93%), with 3–5% strongly-stratified estuaries. Along the West Coast, strongly-stratified estuaries dominated (46–63%), with the exception of the Puget Trough basin and the southern CA ecoregion with 83% and 75% well-mixed estuaries. The stratification type of some estuaries varied seasonally. Generally, they were more stratified winter through spring, then mixed during the summer, with the exception of southern FL, which had a reverse pattern due to the positive correlation between the stratification parameter and freshwater inflow (97% estuaries with R² > 0.9). The flushing times of the 300 well-mixed and partially-stratified estuaries were estimated using Tidal Prism (TPM) and Freshwater Fraction Methods (FFM). Flushing time seasonal variation exhibited a negative correlation with freshwater inflow (R² > 0.8 for 50% of estuaries using TPM). Generally, estuarine flushing times were short in winter and long in summer (reversed in FL and a portion of the Gulf of Mexico). On the West Coast, estuaries tended to flush quickly compared with estuaries in other regions, even though they usually had low freshwater inflows, since other factors, e.g., the estuarine volume, affected the flushing time as well. To ensure appropriate interpretation of responses to change in nutrient loading, the significant intra- and interannual variations in stratification and flushing time need to be incorporated into management and assessment of estuaries.