Human exposure to mercury (Hg) is a cause of concern, due
to the biomagnification of the neurotoxic species monomethylmercury (MMHg)
in marine ecosystems. Previous research revealed that commercial fish
species in the Mediterranean Sea ecosystems are particularly enriched in Hg,
due to a combination of physical and ecological factors. Since the fate of
Hg depends on the interactions among several biogeochemical and physical
drivers, biogeochemical modeling is crucial to support the integration and
interpretation of field data. Here, we develop and apply a coupled
transport–biogeochemical–metal bioaccumulation numerical model
(OGSTM–BFM–Hg) to simulate the biogeochemical cycling of the main Hg
species (Hg
The anthropogenic alteration of the mercury (Hg) biogeochemical cycle has led to global enrichment of Hg concentrations in all the environmental compartments (Amos et al., 2015; UNEP, 2019; Zhang et al., 2014a, b) and concerns over human exposure to neurotoxic monomethylmercury (MMHg), which is produced in the ocean and biomagnifies in marine food webs (UNEP, 2019). The ocean has absorbed 50 % of anthropogenic Hg historical emissions, 35 % of which are currently stored in the water and the rest in the sediments (Zhang et al., 2014b): relative to pre-anthropogenic levels, the Hg enrichment is 230 % in surface ocean waters, 25 % in intermediate waters, and 12 % in deep waters (UNEP, 2019).
Models and observations (Lamborg et al., 2014; Zhang et al., 2014b) suggest
that the oceanic water column contains 280–370 Mmol of anthropogenic Hg
(equivalent to about 70 000 t), a large part of which is recycled within
surface and intermediate water due to the biological carbon pump and the
microbial loop (e.g., Zhang et al., 2018). Hg is scavenged from surface water
by organic particles through adsorption and uptake, transported downward via
particles sinking, and released in the dissolved phase following particle degradation. The locally increased microbial activity and availability of
inorganic Hg at the depth of particle remineralization are also thought to
promote Hg methylation (Cossa et al., 2009; Heimbürger et al., 2010;
Sunderland et al., 2009). Concurrent biological and photochemical
transformations occur in the water column, driving the interconversions among
the main mercury species in seawater (inorganic oxidized Hg, Hg
Methylmercury (MeHg; defined as the sum of MMHg and DMHg) is more frequently measured than
the individual methylated species. In oceanic and Mediterranean areas with
high primary production, the MeHg vertical distribution is characterized by
low concentrations at the surface due to photodegradation and
concentration maxima coincident with the maximum in apparent oxygen
utilization, a proxy for heterotrophic activity (Cossa et al., 2009;
Sunderland et al., 2009). These observations suggest that most oceanic MeHg
is produced in situ. This conclusion is also supported by estimates of MeHg
fluxes in the ocean (Mason et al., 2012; Zhang et al., 2020) and by studies
based on stable Hg isotopes (Blum et al., 2013; Motta et al., 2019). The
role of DMHg in controlling MMHg dynamics remains puzzling: recent
observations (Cossa et al., 2017) from the Northwestern Mediterranean Sea
support the idea that DMHg is produced from Hg
Tunas and other commercial fish species from the Mediterranean Sea are particularly enriched in Hg in comparison to the same species from other geographical areas (Cossa et al., 2012; Cossa and Coquery, 2005; Harmelin-Vivien et al., 2009; Tseng et al., 2021). It has been suggested that, along with other ecological features of the whole food web, this is due to a shallower occurrence of the MeHg concentration maxima compared to the ocean which results in higher phytoplankton exposure and bioaccumulation (Cossa et al., 2012). Available observations on MeHg distribution in the Mediterranean Sea suggest that concentrations are lower in the oligotrophic waters of the Ionian Sea than in the mesotrophic waters of the Northwestern Mediterranean (Cossa et al., 2009, 2022) and Adriatic Sea (Kotnik et al., 2015).
Recent efforts to couple the dynamics of biological carbon pump and microbial loop with Hg dynamics, including bioaccumulation in the lower food web, provided global-scale assessments of MeHg production and bioaccumulation (Wu et al., 2020, 2021; Zhang et al., 2020). The only study modeling the Hg dynamics in the Mediterranean Sea (Žagar et al., 2007) did not include any biological component. Much of the current knowledge on the dynamics of MeHg in the open sea was acquired only afterwards (Bowman et al., 2016, 2015; Cossa et al., 2017, 2009; Heimbürger et al., 2010; Lehnherr et al., 2011; Monperrus et al., 2007; Munson et al., 2015, 2018; Ortiz et al., 2015; Sunderland et al., 2009).
Here, we couple a model for Hg biogeochemistry (Canu et al., 2019; Rosati et
al., 2018, 2020; Zhang et al., 2020) with the 3D transport biogeochemical
model OGSTM–BFM (Cossarini et al., 2021; Lazzari et al., 2010, 2021; Salon
et al., 2019) to investigate spatial and temporal variability of MeHg
dynamics in the Mediterranean Sea. The coupled model, which has a
The Mediterranean Sea (Fig. 1) is a semi-enclosed basin characterized by decreasing west–east gradient of primary production resulting from the superposition of biological pump and inverse estuarine circulation, as well as from the limited impact of riverine loads on the open-ocean dynamics (Crise et al., 1999, Crispi et al., 2001). Due to the formation of intermediate and deep water generating thermohaline circulation, the Mediterranean is considered a miniature of the ocean (Pinardi et al., 2019). The large-scale basin circulation (Pinardi et al., 2015, 2019; Pinardi and Masetti, 2000, and references therein) is composed of three thermohaline cells (Fig. 1). A zonal vertical circulation belt is associated with the inflow of shallow Atlantic Water (AW) at the Strait of Gibraltar that becomes progressively saltier due to evaporation moving eastward (MAW, Modified Atlantic Water) and eventually sinks at intermediate depths forming the Levantine Intermediate Water (LIW), outflowing at Gibraltar. The other cells are driven by dense water formation due to winter cooling, salting, and sinking of surface water. Western Mediterranean Deep Water (WMDW) originates in the Northwestern Mediterranean Sea, while Eastern Mediterranean Deep Water (EMDW) is formed in the Adriatic Sea but also in the Aegean and the Levantine Sea. The mixing between these deep water masses is inhibited by the shallowness of the Strait of Sicily (about 500 m). Long-term observations of ocean color (Bosc et al., 2004; Bricaud et al., 2002; D'Ortenzio and D'Alcalà, 2009) and coupled transport–biogeochemical models (Di Biagio et al., 2019, 2021, Lazzari et al., 2012, 2014, 2021) supported the characterization of different biogeoprovinces based on the seasonal, inter-annual, and high-frequency variability of biogeochemical processes in different areas (subbasins). Biogeochemical modeling also revealed the importance of subsurface plankton blooms, which are not captured by ocean color satellite observations, highlighting the existence of a deep chlorophyll maximum that becomes deeper with increasing water oligotrophy. The most productive areas are the mesotrophic western subbasins of the Alboran Sea (Alb), Northwestern and Southwestern Mediterranean (Nwm and Swm). The eastern Mediterranean is ultra-oligotrophic, apart from the Northern Adriatic Sea (Nad), which is a coastal sea, and other “intermittently blooming” areas (i.e., with high inter-annual variability) such as the Southern Adriatic Sea (Sad), the Aegean Sea (Aeg), and the Rhodes Gyre in the Levantine Sea (Lev).
Bathymetric map of the Mediterranean Sea (from Ocean Data View, Schlitzer, 2014). The white contours indicate the subdivision of the model domain in subbasins: Alboran Sea (Alb), Southwestern Mediterranean (Swm1 and Swm2), Northwestern Mediterranean (Nwm), Tyrrhenian Sea (Tyr1 and Try2), Northern Adriatic Sea (Nad), Southern Adriatic Sea (Sad), Ionian Sea (Ion1, Ion2, and Ion3), Aegean Sea (Aeg), and Levantine Sea (Lev1, Lev2, Lev3, and Lev4). The light blue line shows the zonal cell driven by the surface inflow of Atlantic Water (AW) that moves eastward, forming Modified Atlantic Water (MAW) and Levantine Intermediate Water (LIW), outflowing at intermediate depths at the Strait of Gibraltar. The dark blue lines show the path of meridional cells related to winter convection in the Nwm, Nad, Sad, Aeg, and Lev originating the Western and Eastern Mediterranean Deep Water (WMDW and EMDW).
The Biogeochemical Flux Model (BFM; Vichi et al., 2015) is a model that
simulates the cycling of carbon, nitrogen phosphorus, and silica through
dissolved, living, and non-living particulate phases of the marine
environment. The description of the planktonic food web is based on the
plankton functional type (PFT) approach: the pool of species having similar
traits (nutrients affinities, light affinity, prey–predator relationships)
are described by a single variable. In the BFM, PFTs have variable
stoichiometry and simulate the lower trophic levels of marine food webs up
to carnivorous zooplankton (Sect. 2.2.1). The OGSTM–BFM model has been coupled offline to the ocean general circulation model (NEMO) to
investigate different issues related to the Mediterranean biogeochemistry
(Canu et al., 2015; Cossarini et al., 2015, 2021; Lazzari et al., 2021,
2012, 2014, 2016), and it is now routinely used as the backbone of the
biogeochemical component of the Copernicus CMEMS Mediterranean system
(
Overview of the coupling in the OGSTM–BFM–Hg model, which integrates the biogeochemistry and bioaccumulation of Hg species in the OGSTM–BFM model, previously coupled to the transport model NEMO and to a multispectral biotical model. The thick grey arrows with text highlight variables and fluxes read by the Hg biogeochemical model (Fig. 3).
The BFM model dynamically simulates nine plankton functional types (PFTs) representative of four phytoplankton groups (picophytoplankton, nanophytoflagellates, diatoms, and large phytoplankton), four zooplankton groups (heterotrophic nanoflagellates, microzooplankton, omnivorous mesozooplankton, and carnivorous mesozooplankton), and one group of heterotrophic bacteria (Vichi et al. 2015). The model reproduces the fluxes of carbon, nitrogen, phosphorous, and silicates from the inorganic nutrient pool to organisms (phytoplankton, zooplankton, and bacteria) and organic compounds pools (particulate and dissolved organic carbon, POC and DOC) with a variable stoichiometric formulation. Non-living organic matter includes one class of organic detritus (POC) and three classes of DOC (labile, semi-labile, and semi-refractory).
The Hg biogeochemical model (Canu and Rosati, 2017; Canu et al., 2019;
Melaku Canu et al., 2015; Rosati et al., 2018, 2020, 2022b, Zhang et al.,
2020) simulates the cycling of four mercury species in marine water (Fig. 3): inorganic divalent Hg (Hg
Hg dynamics in the coupled model OGSTM–BFM–Hg. The Hg model
simulates the cycling of inorganic (Hg
The gas-exchange flux of Hg
The bioaccumulation model simulates the MMHg uptake by the phytoplankton
PFTs of the BFM model assuming that the uptake flux (Eq. 10,
nmol
According to previous studies
(Schartup
et al., 2018; Zhang et al., 2020), MMHg bioaccumulation in zooplankton is
mostly driven by grazing (
To compare the model content of MMHg in phytoplankton and zooplankton
against experimental data, the output in nmol
Model initial conditions, boundary conditions, and physical forcings at
monthly resolution are set according to
Lazzari et al. (2021). Initial conditions
for Hg species (Table S5) in Mediterranean subbasins (Fig. 1) are
extrapolated from published data from different investigations in the
Mediterranean Sea
(Cossa
et al., 2017; Cossa and Coquery, 2005; Ferrara et al., 2003; Horvat et al.,
2003; Kotnik et al., 2007, 2015), and boundary conditions are set in
agreement with the observations from the GEOTRACES GA03 meridional transect
(Bowman et al., 2015).
River Hg load is estimated based on dissolved Hg concentration, assuming 3 pM and 3.5 % of MMHg (Cossa et al., 2017), using a
higher concentration for three rivers that are known to be highly impacted
by mining (Isonzo-Soča river, 25 pM)
(Hines et al., 2000),
industrial activities (Po river, 6 pM)
(Vignati et al., 2008), or both of them
(Tiber river, 6 pM)
(Lanzillotta et
al., 2002; Rimondi et al., 2019), assuming MMHg is the 1 %
(Hines et al., 2000).
Further, a sensitivity simulation accounting for the load of particulate Hg
was carried out (Sect. 2.3.3) to investigate model uncertainty regarding
this source. The atmospheric Hg
A set of sensitivity simulations was implemented to investigate model
uncertainty and improve the fit against experimental observations, initially
showing substantial underestimation of MeHg concentration maxima. The
sensitivity simulations aimed at assessing the impacts of variations of the
values of the sinking velocity of organic detritus and associated Hg species
(Sect. 2.3.1) and of the coefficient for Hg methylation rates (Sect. 2.3.2), as well as the loading of Hg from rivers (Sect. 2.3.3), which is a
process poorly characterized by field observations (Liu et al., 2021). All
the analyses of model results focus on the same simulation, which adopts a
sinking velocity of 10 m d
A sensitivity analysis of POC sinking velocity was carried out,
hypothesizing that a change in this parameter would impact the vertical
distribution of all Hg species due to a change in the distribution and
remineralization of POC and in the transport of particulate Hg and MeHg. We
also speculate that a deeper occurrence of POC remineralization, leading to
deeper MeHg maximum, could result in a decreased amount of MeHg
photochemically degraded and thus in higher MeHg concentrations. The current
version of the BFM model includes only one class of non-living organic detritus
(POC) that is a sink for all the plankton state variables (Vichi et al.,
2015), resulting in a homogenous POC sinking velocity representative of an
ecosystem-averaged dynamic. In the field, organic particles and aggregates
that originate from a continuous size spectrum of planktonic cells of
various composition show a wide range of sinking speeds (Cael et al.,
2021). The reference model simulation was run by adopting the default POC
sinking velocity of 3 m d
Hg methylation was parameterized in the model by scaling the flux of POC
remineralization for a constant
The largest Mediterranean rivers are characterized by
proximal-accumulation-dominated dispersal system, i.e., deltaic systems with
fast and substantial (
The sensitivity analysis showed that the sinking rate of organic detritus
(POC) is an important control on the vertical distribution of MeHg (i.e.,
the shape of the vertical profile) along the water column but has little
effect on the values of MeHg concentration maxima and the distribution of
inorganic Hg species (Supplement Sect. S1.1 and Figs. S1 and S2). On the
other hand, the increase in sinking velocity from 3 to 10 m d
The inclusion of higher riverine Hg
The underestimation of MeHg in the model does not appear to be related to
inorganic Hg availability, since the concentrations of Hg
Modeled fluxes of Hg
The modeled export of Hg
All in all, a calibration of the parameter
The zonal and vertical gradients of MeHg concentrations reproduced by the OGSTM–BFM–Hg model show the highest concentrations in subsurface waters of the most productive subbasins of the Mediterranean Sea (Fig. 4), consistently with the available observations (Cossa et al., 2009). Modeled vertical profiles of MeHg concentrations (Fig. 5) are in good agreement with the observations in the Southern Adriatic Sea (Sad, Fig. 5a) and are in the lower range of the observations for the Northwestern Mediterranean (Nwm, Fig. 5b) and Ionian (Ion, Fig. 5c) subbasins. Seasonality affects the modeled distribution of MeHg (Figs. 4 and 5) with more marked effects in the Sad subbasin (Fig. 5a). The strong winter convection occurring in the Sad in 2017 caused remixing in the water column (Mihanović et al., 2021), leading to the disruption of the subsurface MeHg maximum from January to March and an increase in MeHg surface water concentrations, in spite of net demethylation prevailing at all depths during winter months (Fig. 6). A slighter increase in surface water MeHg concentrations during winter months is visible also for the other subbasins (Figs. 4, 5b, and c), but, in the absence of strong winter convection the variation is small, and the model predicts that the subsurface MeHg maximum is a permanent feature throughout the year. The Nwm is known to be an area of winter convection; however, other authors reported a recent decline of deep convection for this area that was weak in 2014 and never occurred in the period 2015–2017 (Margirier et al., 2020). Based on these model results, we speculate that in the long run the reduction of winter mixing can cause MeHg accumulation in the biologically active zone enhancing the exposure of marine organisms.
Spatial distribution of monthly averaged MeHg concentrations (pM) in the Mediterranean Sea at different depths in the water column (25, 90, 175, 270, and 710 m depth) simulated with the OGSTM–BFM–Hg model.
In the Sad subbasin, a progressive buildup of MeHg subsurface maxima (up to
0.18 pM) is predicted from April to September, driven by an increase in
primary production triggering higher POC remineralization and in turn higher
Hg methylation rate constants
Modeled vertical profiles of MeHg in the oligotrophic Ion subbasin (Fig. 5c) have lower maxima (up to 0.16 pM) and a smoother concentration gradient compared to the more productive waters of the Nwm (up to 0.24 pM). The west–east gradient is sustained by the highest methylation rates (Fig. S12) in the western Mediterranean, driven by higher primary productivity and remineralization of organic detritus, and it is further reinforced by high rates of both photochemical and biological MeHg degradation in the eastern subbasins (Fig. S12), due to the highest water temperature, irradiance, and deeper penetration of shortwave radiation caused by the low plankton biomass.
Vertical profiles of monthly averaged MeHg (MMHg
Monthly evolution of the net methylation fluxes (pmol m
The spatial and temporal distributions of modeled MMHg in phytoplankton
(MMHg
Spatial distribution of monthly averaged
The average MMHg
Indicators for MMHg bioaccumulation compared for the Alb
and Sad subbasins (Fig. 3). The average (
The highest concentrations of MMHg
Conceptual model of MMHg bioaccumulation in the plankton food web
of the OGSTM–BFM–Hg model, subdivided into a lower “herbivorous” (red
arrows) and upper “omnivorous” (blue arrows) food webs. The squares with
bold numbers show estimated values of the bioconcentration factors
(log(BCF)) for each PFT, calculated for the Sad subbasin from spatially
averaged model output at monthly resolution. The green circles indicate the
four phytoplankton PFTs (P1, P2, P3, and P4, representative respectively of
diatoms, autotrophic nanoflagellates, picophytoplankton, and large
phytoplankton), the light blue circles indicate the four zooplankton PFTs
(Z3, Z4, Z5, and Z6, representative respectively of carnivorous mesozooplankton,
omnivorous mesozooplankton, microzooplankton, and heterotrophic
nanoflagellates), the purple circle indicates bacteria (B1, representative of
all heterotrophic bacteria), and the grey circles indicate particulate
organic carbon (POC, representative of all organic detritus) and
semi-refractory dissolved organic matter (DOC
The mean MMHg quota (
The mean
The modeled zooplankton quotas compare well with the observations of MMHg in
mesozooplankton of the Gulf of Lion, which was 0.52
Modeled log(BCFs) values for phytoplankton PFTs of the Mediterranean Sea range 3.7–6.5, which is slightly lower than the range (4.3–6.8) reported for phytoplankton from the central Pacific (Gosnell and Mason, 2015) and is higher than the ranges for Long Island Sound (2.6–5.5) (Gosnell et al., 2017) and other coastal and shelf sites of the world (3.1–4.4) (Harding et al., 2018). Higher BCFs in open waters than in coastal areas are consistent with the enhanced Hg bioavailability in the open sea inferred by other authors (Gosnell and Mason, 2015; Schartup et al., 2015), which in the model is approximated through the inverse relationship between MMHg uptake and DOC (Eq. 10). Modeled zooplankton log(BCFs) values in the Mediterranean Sea span from 4.0–6.4, comparable to the range for mesozooplankton (4.0–6.5) in the Pacific Ocean (Gosnell and Mason, 2015).
The trophic interactions among PFTs simulated by the model can be subdivided into a lower herbivorous part of the food web and an upper omnivorous part of the food web (Fig. 8).
In the lower part of the food web, heterotrophic nanoflagellates (2–20
Trophic magnification factor (TMF, unitless) for the
Trophic magnification factors (TMFs) were calculated for each subbasin of
the Mediterranean Sea for the lower and upper parts of the food web. Low
TMFs (range 0.05–0.38) were estimated for the lower food web, indicating the
absence of biomagnification (Fig. 9a), and higher TMFs (range 0.15–2.60)
were estimated for the upper food web (Fig. 9b), in agreement with previous
modeling studies suggesting that MMHg biomagnification between small
zooplankton groups and phytoplankton is unlikely to happen (Wu et al., 2021,
2020; Zhang et al., 2020). Biomagnification (TMF
We developed and released the OGSTM–BFM–Hg model, a numerical state-of-the-art model tracking the biogeochemistry of the main marine Hg species
(Hg
Sensitivity simulations on river Hg loadings corroborate the idea that in the Mediterranean Sea most of the inputs of particulate Hg (and POC) from rivers sink in coastal and shelf areas and have a limited impact on open-sea dynamics. However, as pointed out in a recent reassessment of global river inputs, there is a need to better assess the spatial and temporal variability of riverine loadings, especially in relation to extreme events and their increasing occurrence driven by climate changes. The net Hg exchange from Mediterranean waters to the atmosphere is lower than in a previous budget but in line with findings from a recent Hg isotopes study.
Model results highlight that summer stratification of the water column is an important process for the buildup of a subsurficial maximum of MeHg concentrations, while the occurrence of deep convection in winter results in substantial redistribution of MeHg smoothing the vertical profiles. A decrease in winter convection events linked to increasing water temperature, which has already been observed in recent years in the Mediterranean Sea, seems to limit MeHg redistribution in the water column, causing higher water MeHg concentrations in the biologically active zone and, in turn, higher plankton exposure. In fact, spatial and temporal variability of plankton bioaccumulation in the model is controlled by plankton phenology and by the availability of MMHg at the depths at which plankton blooms occur. The biomagnification potential is stronger in productive areas of the Mediterranean Sea characterized by high biodiversity and longer food web length with a significant presence of carnivorous zooplankton, such as the Alb and Swm subbasins.
The OGSTM–BFM–Hg model code is publicly available in the Zenodo repository at
The data used for model implementation and validation are available upon request.
The supplement related to this article is available online at:
The conceptualisation and investigation were carried out by GR, DC, PL, and CS. The software and methodology was developed by GR, DC, PL, and CS. The formal analysis, validation, and visualization were performed by GR and PL. Funding acquisition and project administration were carried out by DC and CS. Supervision and resources were provided by DC and CS. Writing of the original draft was performed by GR. Review and editing were performed by GR, DC, PL, and CS.
The contact author has declared that none of the authors has any competing interests.
Publisher's note: Copernicus Publications remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
We thank the reviewers for their constructive comments that improved the quality of the work.
The research has been partially supported by the PRIN project ICCC (Impacts of climate change on the biogeochemistry of contaminants in the Mediterranean Sea), funded by the Ministero dell'Istruzione, dell'Università e della Ricerca (grant no. 2017ZRPNKX_001), and by the Interreg MED Strategic Project SHAREMED, co-financed by the European Regional Development Fund under the Funding Programme Interreg MED 2014–2020.
This paper was edited by Gwenaël Abril and reviewed by Yanxu Zhang and Gwenaël Abril.