2018
DOI: 10.3389/fmars.2018.00291
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Modeling the Influence of Eutrophication and Redox Conditions on Mercury Cycling at the Sediment-Water Interface in the Berre Lagoon

Abstract: This study presents a specifically designed Mercury module in a coupled benthic-pelagic reactive-transport model -Bottom RedOx Model (BROM) that allows to study mercury (Hg) biogeochemistry under different conditions. This module considers the transformation of elemental mercury (Hg(0)), divalent mercury (Hg(II)) and methylmercury (MeHg). The behavior of mercury species in the model is interconnected with changes of oxygen, hydrogen sulfide, iron oxides, organic matter, and biota. We simulated the transformati… Show more

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Cited by 17 publications
(13 citation statements)
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“…Oxygenation of an anoxic sediment leads to the appearance of Hg species in the water column and the potential bioaccumulation by organisms. However, as shown by Pakhomova et al (2018), any shifts in redox conditions in bottom water and upper sediment layer lead to the release of Hg species into the water column. The negative dependence between Hg concentration and redox potential was partly related to the station depth, which is confirmed by a statistically significant negative correlation between redox potential and depth (R Spearman = − 0.48, p = 0.003) ( Table A3).…”
Section: Surface Sedimentsmentioning
confidence: 99%
“…Oxygenation of an anoxic sediment leads to the appearance of Hg species in the water column and the potential bioaccumulation by organisms. However, as shown by Pakhomova et al (2018), any shifts in redox conditions in bottom water and upper sediment layer lead to the release of Hg species into the water column. The negative dependence between Hg concentration and redox potential was partly related to the station depth, which is confirmed by a statistically significant negative correlation between redox potential and depth (R Spearman = − 0.48, p = 0.003) ( Table A3).…”
Section: Surface Sedimentsmentioning
confidence: 99%
“…This integrated model also estimates the total amount of mercury present in biological species that occupy the lowest trophic level of the food chain, i.e., phytoplankton popu- lations. For this purpose, we incorporated the Phytoplankton MERLIN-Expo model (Pickhardt and Fischer, 2007;Radomyski and Ciffroy, 2015) to describe the mechanism of mercury uptake in phytoplankton cells. Moreover, we reproduced the spatiotemporal dynamics of phytoplankton communities in seawater using the Nutrient-Phytoplankton model (Dutkiewicz et al, 2009;Morozov et al, 2010;Valenti et al, 2012;Denaro et al, 2013a, b, c;Valenti et al, 2015Valenti et al, , 2016aValenti et al, , b, c, 2017Morozov et al, 2019).…”
Section: Discussionmentioning
confidence: 99%
“…Finally, the biogeochemical models introduced in previous works (Soerensen et al, 2016;Pakhomova et al, 2018) provided neither the NPP from the Nutrient-Phytoplankton model (Baines et al, 1994;Brunet et al, 2007;Zhang et al, 2014) nor the load of POM-released Hg D obtained using the Phytoplankton MERLIN-Expo model (Pickhardt and Fischer, 2007;Radomyski and Ciffroy, 2015) (see Sect. 3.1).…”
Section: Discussionmentioning
confidence: 99%
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“…The results demonstrate that production and consumption processes of such substances in the benthic layer do support such concentration gradients, despite turbulent mixing which tends to eliminate them. While the gradients' presence may be inferred from modeling studies (e.g., Pakhomova et al ), tools like Susane are helpful for their direct observation because they can collect the appropriate discrete samples. In the future, coupling such observations with hydrodynamics of the benthic layer will contribute to a better understanding of their biogeochemical fluxes near the SWI.…”
mentioning
confidence: 99%