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This is the data used to create the published study of the same name published in the Journal of Hydrology in 2022 (10.1016/j.jconhyd.2022.104068). Shallow (<30 m) reducing groundwater commonly contains abundant dissolved arsenic (As) in Bangladesh. We hypothesize that dissolved As in iron (Fe)-rich groundwater discharging to rivers is trapped onto Fe(III)-oxyhydroxides which precipitate in shallow riverbank sediments under the influence of tidal fluctuations. Therefore, the goal of this study is to compare the calculated mass of sediment-bound As that would be sequestered from dissolved groundwater As that discharges through riverbanks of the Meghna River to the observed mass of As trapped within riverbank sediments. To calculate groundwater discharge, a Boussinesq aquifer analytical groundwater flow model was developed and constrained by cyclical seasonal fluctuations in hydraulic heads and river stages observed at three sites along a 13 km reach in central Bangladesh. At all sites, groundwater discharges to the river year-round but most of it passes through an intertidal zone created by ocean tides propagating upstream from the Bay of Bengal in the dry season. The annualized groundwater discharge per unit width at the three sites ranges from 173 to 891 m2/yr (average 540 m2/yr). Assuming that riverbanks have been stable since the Brahmaputra River avulsed far away from this area 200 years ago and dissolved As is completely trapped within riverbank sediments, the mass of accumulated sediment As can be calculated by multiplying groundwater discharge by ambient aquifer As concentrations measured in 1969 wells. Across all sites, the range of calculated sediment As concentrations in the riverbank is 78–849 mg/kg, which is higher than the observed concentrations (17–599 mg/kg). This discovery supports the hypothesis that the dissolved As in groundwater discharge to the river is sufficient to account for the observed buried deposits of As along riverbanks. 

This is the data used to create the study that is currently under review in a peer-reviewed journal. This dataset contains groundwater chemistry data and groundwater level data across the Meghna riverbank field site near town called Nayapara in Bangladesh. Across the 131 m-wide transect oriented orthogonally to the river shoreline, three types of wells were installed: i) Drive-point piezometers (DP) (“DPa” wells (~0.5 m), “DPb” wells (~1.5 m), “DPc” wells (3 to 4.5 m)); ii) Fully screened shallow piezometers (PZ); iii) Monitoring wells (MW) wAll wells were numbered in descending order away from the river. For example, the DP well that is furthest from the river and has the shallowest depth is referred to as “DP1a”. 

Through biological activity, marine dissolved inorganic carbon (DIC) is transformed into different types of biogenic carbon available for export to the ocean interior, including particulate organic carbon (POC), dissolved organic carbon (DOC), and particulate inorganic carbon (PIC). Each biogenic carbon pool has a different export efficiency that impacts the vertical ocean carbon gradient and drives natural air–sea carbon dioxide gas (CO₂) exchange. In the Southern Ocean (SO), which presently accounts for ~40% of the anthropogenic ocean carbon sink, it is unclear how the production of each biogenic carbon pool contributes to the contemporary air–sea CO₂exchange. Based on 107 independent observations of the seasonal cycle from 63 biogeochemical profiling floats, we provide the basin-scale estimate of distinct biogenic carbon pool production. We find significant meridional variability with enhanced POC production in the subantarctic and polar Antarctic sectors and enhanced DOC production in the subtropical and sea-ice-dominated sectors. PIC production peaks between 47°S and 57°S near the “great calcite belt.” Relative to an abiotic SO, organic carbon production enhances CO₂uptake by 2.80 ± 0.28 Pg C y⁻¹, while PIC production diminishes CO₂uptake by 0.27 ± 0.21 Pg C y⁻¹. Without organic carbon production, the SO would be a CO₂source to the atmosphere. Our findings emphasize the importance of DOC and PIC production, in addition to the well-recognized role of POC production, in shaping the influence of carbon export on air–sea CO₂exchange. 

Abstract We use observations from the Southern Ocean (SO) biogeochemical profiling float array to quantify the meridional pattern of particle export efficiency (PE_eff) during the austral productive season. Float estimates reveal a pronounced latitudinal gradient of PE_eff, which is quantitatively supported by a compilation of existing ship‐based measurements. Relying on complementary float‐based estimates of distinct carbon pools produced through biological activity, we find that PE_effpeaks near the region of maximum particulate inorganic carbon sinking flux in the polar antarctic zone, where net primary production (NPP) is the lowest. Regions characterized by intermediate NPP and low PE_eff, primarily in the subtropical and seasonal ice zones, are generally associated with a higher fraction of dissolved organic carbon production. Our study reveals the critical role of distinct biogenic carbon pool production in driving the latitudinal pattern of PE_effin the SO. 

The importance of dissolved Fe (dFe) in regulating ocean primary production and the carbon cycle is well established. However, the large-scale distribution and temporal dynamics of dFe remain poorly constrained in part due to incomplete observational coverage. In this study, we use a compilation of published dFe observations (n=32,344) with paired environmental predictors from contemporaneous satellite observations and reanalysis products to build a data-driven surface-to-seafloor dFe climatology with 1°×1° resolution using three machine-learning approaches (random forest, supper vector machine and artificial neural network). Among the three approaches, random forest achieves the highest accuracy with overall R 2 and root mean standard error of 0.8 and 0.3 nmol L -1 , respectively. Using this data-driven climatology, we explore the possible mechanisms governing the dFe distribution at various depth horizons using statistical metrics such as Pearson correlation coefficients and the rank of predictors importance in the model construction. Our results are consistent with the critical role of aeolian iron supply in enriching surface dFe in the low latitude regions and suggest a far-reaching impact of this source at depth. Away from the surface layer, the strong correlation between dFe and apparent oxygen utilization implies that a combination of regeneration, scavenging and large-scale ocean circulation are controlling the interior distribution of dFe, with hydrothermal inputs important in some regions. Finally, our data-driven dFe climatology can be used as an alternative reference to evaluate the performance of ocean biogeochemical models. Overall, the new global scale climatology of dFe achieved in our study is an important step toward improved representation of dFe in the contemporary ocean and may also be used to guide future sampling strategies.