Search for: All records

Abstract. Barium is widely used as a proxy for dissolved silicon and particulateorganic carbon fluxes in seawater. However, these proxy applications arelimited by insufficient knowledge of the dissolved distribution of Ba([Ba]). For example, there is significant spatial variability in thebarium–silicon relationship, and ocean chemistry may influence sedimentaryBa preservation. To help address these issues, we developed 4095 models forpredicting [Ba] using Gaussian process regression machine learning. Thesemodels were trained to predict [Ba] from standard oceanographic observationsusing GEOTRACES data from the Arctic, Atlantic, Pacific, and Southernoceans. Trained models were then validated by comparing predictions againstwithheld [Ba] data from the Indian Ocean. We find that a model trained usingdepth, temperature, and salinity, as well as dissolved dioxygen, phosphate,nitrate, and silicate, can accurately predict [Ba] in the Indian Ocean with amean absolute percentage deviation of 6.0 %. We use this model tosimulate [Ba] on a global basis using these same seven predictors in theWorld Ocean Atlas. The resulting [Ba] distribution constrains the Ba budgetof the ocean to 122(±7) × 1012 mol and revealsoceanographically consistent variability in the barium–silicon relationship. We then calculate the saturation state of seawater with respect to barite. This calculation reveals systematic spatial and vertical variations in marine barite saturation and shows that the ocean below 1000 m is at equilibrium with respect tobarite. We describe a number of possible applications for our model outputs, ranging from use in mechanistic biogeochemical models to paleoproxy calibration. Ourapproach demonstrates the utility of machine learning in accurately simulatingthe distributions of tracers in the sea and provides a framework that couldbe extended to other trace elements. Our model, the data used in training and validation, and global outputs are available in Horner and Mete (2023, https://doi.org/10.26008/1912/bco-dmo.885506.2). 

North African dust is known to be deposited in the Gulf of Mexico, but its deposition rate and associated supply of lithogenic dissolved metals, such as the abiotic metal thorium or the micronutrient metal iron, have not been well‐quantified.²³²Th is an isotope with similar sources as iron and its input can be quantified using radiogenic²³⁰Th. By comparing dissolved²³²Th fluxes at three sites in the northern Gulf of Mexico with upwind sites in the North Atlantic, we place an upper bound on North African dust contributions to²³²Th and Fe in the Gulf of Mexico, which is about 30% of the total input. Precision on this bound is hindered by uncertainty in the relative rates of dust deposition in the North Atlantic and the northern Gulf of Mexico. Based on available radium data, shelf sources, including rivers, submarine groundwater discharge, and benthic sedimentary releases are likely as important if not more important than dust in the budget of lithogenic metals in the Gulf of Mexico. In other words, it is likely there is no one dominant source of Th and Fe in the Gulf of Mexico. Finally, our estimated Fe input in the northern Gulf of Mexico implies an Fe residence time of less than 6 months, similar to that in the North Atlantic despite significantly higher supply rates in the Gulf of Mexico.

 

Coastal ecosystems are highly dynamic areas for carbon cycling and are likely to be negatively impacted by increasing ocean acidification. This research focused on dissolved inorganic carbon (DIC) and total alkalinity (TA) in the Mississippi Sound to understand the influence of local rivers on coastal acidification. This area receives large fluxes of freshwater from local rivers, in addition to episodic inputs from the Mississippi River through a human‐built diversion, the Bonnet Carré Spillway. Sites in the Sound were sampled monthly from August 2018 to November 2019 and weekly from June to August 2019 in response to an extended spillway opening. Prior to the 2019 spillway opening, the contribution of the local, lower alkalinity rivers to the Sound may have left the study area more susceptible to coastal acidification during winter months, with aragonite saturation states (Ω_ar) < 2. After the spillway opened, despite a large increase in TA throughout the Sound, aragonite saturation states remained low, likely due to hypoxia and increased CO₂concentrations in subsurface waters. Increased Mississippi River input could represent a new normal in the Sound's hydrography during spring and summer months. The spillway has been utilized more frequently over the last two decades due to increasing precipitation in the Mississippi River watershed, which is primarily associated with climate change. Future increases in freshwater discharge and the associated declines in salinity, dissolved oxygen, and Ω_arin the Sound will likely be detrimental to oyster stocks and the resilience of similar ecosystems to coastal acidification.

 

Metal cations are potent environmental pollutants that negatively impact human health and the environment. Despite advancements in sensor design, the simultaneous detection and discrimination of multiple heavy metals at sub‐nanomolar concentrations in complex analytical matrices remain a major technological challenge. Here, the design, synthesis, and analytical performance of three highly emissive conjugated polyelectrolytes (CPEs) functionalized with strong iminodiacetate and iminodipropionate metal chelates that operate in challenging environmental samples such as seawater are demonstrated. When coupled with array‐based sensing methods, these polymeric sensors discriminate among nine divalent metal cations (Cu^II, Co^II, Ni^II, Mn^II, Fe^II, Zn^II, Cd^II, Hg^II, and Pb^II). The unusually high and robust luminescence of these CPEs enables unprecedented sensitivity at picomolar concentrations in water. Unlike previous array‐based sensors for heavy metals using CPEs, the incorporation of distinct π‐spacer units within the polymer backbone affords more pronounced differences in each polymer's spectroscopic behavior upon interaction with each metal, ultimately producing better analytical information and improved differentiation. To demonstrate the environmental and biological utility, a simple two‐component sensing array is showcased that can differentiate nine metal cation species down to 500 × 10⁻¹² min aqueous media and to 100 × 10⁻⁹ min seawater samples collected from the Gulf of Mexico.

 

Determining the proportions of Atlantic and Pacific Ocean seawater entering the Arctic Ocean is important both for understanding the mass balance of this basin as well as its contribution to formation of North Atlantic deep water. To quantify the distribution and amount of Pacific and Atlantic origin seawater in the western Arctic Ocean, we used dissolved Ga in a four‐component linear endmember mixing model. Previously, nutrients, combined in their Redfield ratios, have been used to separate Pacific‐ and Atlantic‐derived waters. These nutrient tracers are not conservative in practice, and there is a need to find quantities that are conserved. Dissolved Ga concentrations show measurable contrast between Atlantic and Pacific source waters, shelf‐influenced waters show little impact of shelf processes on the dissolved Ga distribution, and dissolved Ga in the Arctic basins is conserved along isopycnal surfaces. Thus, we explored the potential of Ga as a new parameter in Arctic source water deconvolution. The Ga‐informed deconvolution was compared to that generated with the NO₃:PO₄relationship. While distributions of the water masses were qualitatively similar, the Ga‐based deconvolution predicted higher amounts of Pacific water at depths between 150 and 300 m. The Ga‐based decomposition yields a smoother transition between the halocline and Atlantic layers, while nutrient‐based solutions have sharper transitions. A 1‐D advection‐diffusion model was used to constrain estimates of vertical diffusivity (K_z). The Ga‐based K_zestimates agreed better with those from salinity and temperature than the nutrient method. The Ga‐based approach implies greater vertical mixing between the Pacific and Atlantic waters.

 

Atmospheric deposition represents a major input for micronutrient trace elements (TEs) to the surface ocean and is often quantified indirectly through measurements of aerosol TE concentrations. Sea spray aerosol (SSA) dominates aerosol mass concentration over much of the global ocean, but few studies have assessed its contribution to aerosol TE loading, which could result in overestimates of “new” TE inputs. Low‐mineral aerosol concentrations measured during the U.S. GEOTRACES Pacific Meridional Transect (GP15; 152°W, 56°N to 20°S), along with concurrent towfish sampling of surface seawater, provided an opportunity to investigate this aspect of TE biogeochemical cycling. Central Pacific Ocean surface seawater Al, V, Mn, Fe, Co, Ni, Cu, Zn, and Pb concentrations were combined with aerosol Na data to calculate a “recycled” SSA contribution to aerosol TE loading. Only vanadium was calculated to have a SSA contribution averaging >1% along the transect (mean of 1.5%). We derive scaling factors from previous studies on TE enrichments in the sea surface microlayer and in freshly produced SSA to assess the broader potential for SSA contributions to aerosol TE loading. Maximum applied scaling factors suggest that SSA could contribute significantly to the aerosol loading of some elements (notably V, Cu, and Pb), while for others (e.g., Fe and Al), SSA contributions largely remained <1%. Our study highlights that a lack of focused measurements of TEs in SSA limits our ability to quantify this component of marine aerosol loading and the associated potential for overestimating new TE inputs from atmospheric deposition.