Trace metal stoichiometry of dissolved organic matter in the Amazon plume

Dissolved organic matter (DOM) is a distinct component of Earth’s hydrosphere and provides a link between the biogeochemical cycles of carbon, nutrients, and trace metals (TMs). Binding of TMs to DOM is thought to result in a TM pool with DOM-like biogeochemistry. Here, we determined elemental stoichiometries of aluminum, iron, copper, nickel, zinc, cobalt, and manganese associated with a fraction of the DOM pool isolated by solid-phase extraction at ambient pH (DOM SPE-amb ) from the Amazon plume. We found that the rank order of TM stoichiometry within the DOM SPE-amb fraction was underpinned by the chemical periodicity of the TM. Furthermore, the removal of the TM SPE-amb pool at low salinity was related to the chemical hardness of the TM ion. Thus, the biogeochemistry of TMs bound to the DOM SPE-amb component in the Amazon plume was determined by the chemical nature of the TM and not by that of the DOM SPE-amb . Metal chemistry controls biogeochemistry of metals bound to organic matter in the Amazon plume

Iron Speciation in Fram Strait and Over the Northeast Greenland Shelf: An Inter-Comparison Study of Voltammetric Methods

Competitive ligand exchange - adsorptive cathodic stripping voltammetry (CLE-AdCSV) is a widely used technique to determine dissolved iron (Fe) speciation in seawater, and involves competition for Fe of a known added ligand (AL) with natural organic ligands. Three different ALs were used, 2-(2-thiazolylazo)-p-cresol (TAC), salicylaldoxime (SA) and 1-nitroso-2-napthol (NN). The total ligand concentrations ([Lt]) and conditional stability constants (log K′Fe'L) obtained using the different ALs are compared. The comparison was done on seawater samples from Fram Strait and northeast Greenland shelf region, including the Norske Trough, Nioghalvfjerdsfjorden (79N) Glacier front and Westwind Trough. Data interpretation using a one-ligand model resulted in [Lt]SA (2.72 ± 0.99 nM eq Fe) > [Lt]TAC (1.77 ± 0.57 nM eq Fe) > [Lt]NN (1.57 ± 0.58 nM eq Fe); with the mean of log K′Fe'L being the highest for TAC (log ′KFe'L(TAC) = 12.8 ± 0.5), followed by SA (log K′Fe'L(SA) = 10.9 ± 0.4) and NN (log K′Fe'L(NN) = 10.1 ± 0.6). These differences are only partly explained by the detection windows employed, and are probably due to uncertainties propagated from the calibration and the heterogeneity of the natural organic ligands. An almost constant ratio of [Lt]TAC/[Lt]SA = 0.5 - 0.6 was obtained in samples over the shelf, potentially related to contributions of humic acid-type ligands. In contrast, in Fram Strait [Lt]TAC/[Lt]SA varied considerably from 0.6 to 1, indicating the influence of other ligand types, which seemed to be detected to a different extent by the TAC and SA methods. Our results show that even though the SA, TAC and NN methods have different detection windows, the results of the one ligand model captured a similar trend in [Lt], increasing from Fram Strait to the Norske Trough to the Westwind Trough. Application of a two-ligand model confirms a previous suggestion that in Polar Surface Water and in water masses over the shelf, two ligand groups existed, a relatively strong and relatively weak ligand group. The relatively weak ligand group contributed less to the total complexation capacity, hence it could only keep part of Fe released from the 79N Glacier in the dissolved phase.This study was supported by Royal Netherland Institute for Sea Research. Collection and analysis of samples were further supported by GEOMAR Helmholtz Centre for Ocean Research (the Helmholtz Association and the German Research Foundation (DFG Award Number AC 217/1-1 to EA). IA was supported by a doctoral scholarship from Indonesia Endowment Fund for Education (LPDP), and KZ was supported by a scholarship from the China Scholarship Council

Multidifferential study of identified charged hadron distributions in ZZ-tagged jets in proton-proton collisions at s=\sqrt{s}=13 TeV

Jet fragmentation functions are measured for the first time in proton-proton collisions for charged pions, kaons, and protons within jets recoiling against a $Z$ boson. The charged-hadron distributions are studied longitudinally and transversely to the jet direction for jets with transverse momentum 20 $< p_{\textrm{T}} < 100$ GeV and in the pseudorapidity range $2.5 < \eta < 4$. The data sample was collected with the LHCb experiment at a center-of-mass energy of 13 TeV, corresponding to an integrated luminosity of 1.64 fb$^{-1}$. Triple differential distributions as a function of the hadron longitudinal momentum fraction, hadron transverse momentum, and jet transverse momentum are also measured for the first time. This helps constrain transverse-momentum-dependent fragmentation functions. Differences in the shapes and magnitudes of the measured distributions for the different hadron species provide insights into the hadronization process for jets predominantly initiated by light quarks.Comment: All figures and tables, along with machine-readable versions and any supplementary material and additional information, are available at https://cern.ch/lhcbproject/Publications/p/LHCb-PAPER-2022-013.html (LHCb public pages

Study of the B−→Λc+Λˉc−K−B^{-} \to \Lambda_{c}^{+} \bar{\Lambda}_{c}^{-} K^{-} decay

The decay $B^{-} \to \Lambda_{c}^{+} \bar{\Lambda}_{c}^{-} K^{-}$ is studied in proton-proton collisions at a center-of-mass energy of $\sqrt{s}=13$ TeV using data corresponding to an integrated luminosity of 5 $\mathrm{fb}^{-1}$ collected by the LHCb experiment. In the $\Lambda_{c}^+ K^{-}$ system, the $\Xi_{c}(2930)^{0}$ state observed at the BaBar and Belle experiments is resolved into two narrower states, $\Xi_{c}(2923)^{0}$ and $\Xi_{c}(2939)^{0}$, whose masses and widths are measured to be $$m(\Xi_{c}(2923)^{0}) = 2924.5 \pm 0.4 \pm 1.1 \,\mathrm{MeV}, \\ m(\Xi_{c}(2939)^{0}) = 2938.5 \pm 0.9 \pm 2.3 \,\mathrm{MeV}, \\ \Gamma(\Xi_{c}(2923)^{0}) = \phantom{000}4.8 \pm 0.9 \pm 1.5 \,\mathrm{MeV},\\ \Gamma(\Xi_{c}(2939)^{0}) = \phantom{00}11.0 \pm 1.9 \pm 7.5 \,\mathrm{MeV},$$ where the first uncertainties are statistical and the second systematic. The results are consistent with a previous LHCb measurement using a prompt $\Lambda_{c}^{+} K^{-}$ sample. Evidence of a new $\Xi_{c}(2880)^{0}$ state is found with a local significance of $3.8\,\sigma$, whose mass and width are measured to be $2881.8 \pm 3.1 \pm 8.5\,\mathrm{MeV}$ and $12.4 \pm 5.3 \pm 5.8 \,\mathrm{MeV}$, respectively. In addition, evidence of a new decay mode $\Xi_{c}(2790)^{0} \to \Lambda_{c}^{+} K^{-}$ is found with a significance of $3.7\,\sigma$. The relative branching fraction of $B^{-} \to \Lambda_{c}^{+} \bar{\Lambda}_{c}^{-} K^{-}$ with respect to the $B^{-} \to D^{+} D^{-} K^{-}$ decay is measured to be $2.36 \pm 0.11 \pm 0.22 \pm 0.25$, where the first uncertainty is statistical, the second systematic and the third originates from the branching fractions of charm hadron decays.Comment: All figures and tables, along with any supplementary material and additional information, are available at https://cern.ch/lhcbproject/Publications/p/LHCb-PAPER-2022-028.html (LHCb public pages

Measurement of the ratios of branching fractions R(D∗)\mathcal{R}(D^{*}) and R(D0)\mathcal{R}(D^{0})

The ratios of branching fractions $\mathcal{R}(D^{*})\equiv\mathcal{B}(\bar{B}\to D^{*}\tau^{-}\bar{\nu}_{\tau})/\mathcal{B}(\bar{B}\to D^{*}\mu^{-}\bar{\nu}_{\mu})$ and $\mathcal{R}(D^{0})\equiv\mathcal{B}(B^{-}\to D^{0}\tau^{-}\bar{\nu}_{\tau})/\mathcal{B}(B^{-}\to D^{0}\mu^{-}\bar{\nu}_{\mu})$ are measured, assuming isospin symmetry, using a sample of proton-proton collision data corresponding to 3.0 fb${ }^{-1}$ of integrated luminosity recorded by the LHCb experiment during 2011 and 2012. The tau lepton is identified in the decay mode $\tau^{-}\to\mu^{-}\nu_{\tau}\bar{\nu}_{\mu}$. The measured values are $\mathcal{R}(D^{*})=0.281\pm0.018\pm0.024$ and $\mathcal{R}(D^{0})=0.441\pm0.060\pm0.066$, where the first uncertainty is statistical and the second is systematic. The correlation between these measurements is $\rho=-0.43$. Results are consistent with the current average of these quantities and are at a combined 1.9 standard deviations from the predictions based on lepton flavor universality in the Standard Model.Comment: All figures and tables, along with any supplementary material and additional information, are available at https://cern.ch/lhcbproject/Publications/p/LHCb-PAPER-2022-039.html (LHCb public pages

Impact of pH, temperature and dissolved organic matter on iron speciation and dissolved iron inventories in seawater

Phytoplankton growth has been shown to be limited by a low supply of iron (Fe) in large parts of the world’s surface ocean. In oxic seawater, the thermodynamically favored Fe form is Fe(III), which is rapidly precipitated and scavenged out of solution. Iron bound to organic matter has been shown to dominate Fe speciation and to buffer dissolved Fe (DFe) concentrations over the solubility of inorganic Fe (Fe´). Our current knowledge of Fe speciation suggests that an excess binding capacity of organic matter relative to Fe typically exists in seawater, but the sources, nature and residence time of the Fe-binding ligand pool are still largely unclear. Organic speciation of Fe is usually determined via competitive ligand exchange-adsorptive cathodic stripping voltammetry (CLE-AdCSV), but its data interpretation has some limitations, e.g. the absence of pH and temperature dimensions. The oceans are currently experiencing acidification, warming, deoxygenation and stratification, and therefore it is important to understand the impact of changing seawater chemistry conditions (e.g. decreasing pH) on Fe speciation. Therefore, I applied an ion paring-organic matter model (NICA-Donnan), to thermodynamically calculate ambient Fe speciation and derive the apparent Fe(III) solubility (SFe(III)app). Iron speciation is calculated by the competition between inorganic complexes and organic complexation with the NICA-Donnan model, using DFe concentrations from various seawater samples. The SFe(III)app is calculated in a oversaturated system by setting an input of DFe(III) to 10 nmol L-1, at ambient ocean pH, temperature and dissolved organic carbon (DOC) concentrations. This will result in the precipitation of Fe hydroxide, as ferrihydrite assumed in our system. The SFe(III)app is defined as the sum of all aqueous inorganic species and Fe bound to organic matter at a free Fe (Fe3+) concentration equal to the limiting solubility of Fe hydroxide (Fe(OH)3(s)). I combined these predictions with observational DFe as well as Fe(II) data, to build a comprehensive picture on Fe speciation and DFe inventory in the ambient oceanic water column, with further feedbacks on primary productivity. In Chapter 3, I first calibrated predictions of Fe speciation with four different NICA parameter sets representing a range of binding sites strengths and heterogeneities, by comparing those predictions to determinations of Fe speciation via CLE-AdCSV in samples collected from the Celtic Sea. The results showed a constant low DOC concentration resulted in a slight improvement in the fit of titration data to the simulated titrations, suggesting that the changes in dissolved organic matter composition that occur alongside changes in DOC concentration dilute the Fe binding site pool. Using the optimized parameters, the calculated SFe(III)app was within the range of DFe concentrations observed after winter mixing on the shelf and in waters >1500 m depth at the furthest offshore stations. This supports the hypothesis that the ocean dissolved Fe inventory is controlled by the interplay between Fe solubility and Fe binding to organic matter. In Chapter 4, I further derived Fe(III) NICA constants for marine DOM from samples collected across the Peruvian shelf and slope, via the approach PEST-ORCHESTRA. Using the constants, the modelled SFe(III)app showed a ca. 2 fold increase in the oxygen minimum zone compared to surface waters. The increase results from a one order of magnitude decrease in H+ concentrations which impacts both Fe(III) hydroxide solubility and organic complexation. Using the Fe(II) measurements, I calculated the dissolved Fe(III) concentrations (DFe-FeII). The results highlight that the underlying distribution of ambient DFe(III) largely reflected the modelled SFe(III)app and an important role of ambient pH and temperature on the speciation and solubility of Fe. Finally, I investigated correlations of predicted SFe(III)app and measured DFe at ocean basin scales, using data obtained during a series of GEOTRACES cruises (Chapter 5). A similar trend was observed in the vertical distributions of horizontally averaged SFe(III)app and DFe. Combining the regression analysis and proportions of DFe relative to predicted SFe(III)app at the basin scale, the results suggest the distribution of DFe is not solely a function of sinking organic matter remineralization processes, but also regulated by relative changes in ambient pH and temperature. pH has a larger impact on SFe(III)app than DOM at basin scales, based on a solubility gradient of Fe hydroxide that is driven by ambient temperature. Therefore, consideration of the impact of pH and temperature on organic Fe complexation is as important for the speciation and solubility of Fe as the characterization of Fe-binding ligands, since the global distributions Fe-binding ligand (and DOC concentrations) are relatively invariant at the basin scale

Chemical and Microbial Processes for Rhodium Recovery

This is the first report that demonstrates the ability of anaerobic methanogenic granular sludge to reduce Rh(III) to Rh(0). Recovery of rhodium(Rh) during anaerobic incubations under abiotic and biotic condition with different electron donors was studied. H2 and formate reduced Rh(III) to Rh(0) nanoparticles(NPs) in the absence of microorganisms. However, the presence of microorganism was crucial for Rh(III) reduction with ethanol. Results of X-ray powder diffraction (XRD) and transmission electron microscopy (TEM) confirmed the formation of Rh(0) NPs and indicated the localization and morphology of the formed Rh(0) NPs varied with electron donor utilized. Rh(III) reduction with H2 and ethanol obeyed 1st order kinetics. Rh(III) caused a moderate inhibition to methanogenesis. Rh(III) reduction often ceased before coming to completion but this effect is not due to unfavorable thermodynamics. A hypothesis was developed which ascribes the biological reduction of Rh(III) with ethanol as being due to the biological formation of H2 (that subsequently chemically reacts with Rh). The results obtained indicate the potential of utilizing anaerobic granular sludge bioreactor technology as a practical and promising option in Rh(III) recovery.Release after 15-Jul-201

Voltammetry — Cathodic Stripping

Cathodic stripping voltammetry (CSV) is an analytical technique used for the analysis of low levels of analytes (principally trace metals and sulfur containing organic compounds) in aqueous solutions, and is based on the measurement of a reductive current response as a function of a potential scan toward more negative potentials. The technique is highly sensitive (limits of detection of 10− 10–10− 12 mol L− 1) because of the application of a preconcentrations step prior to the stripping step. During the preconcentration the analyte is collected on the surface of the working electrode (typically a mercury drop), often in the presence of an added electro-active ligand. The CSV technique has been used for automated measurements of trace metals in marine waters, but a key strength of CSV is in its use in trace metal speciation measurements in natural waters, in particular dissolved iron in marine waters. Recently, iron ligand observations have been made extensively in the global oceans

Influence of pH and Dissolved Organic Matter on Iron Speciation and Apparent Iron Solubility in the Peruvian Shelf and Slope Region

The chemical speciation of iron (Fe) in oceans is influenced by ambient pH, dissolved oxygen, and the concentrations and strengths of the binding sites of dissolved organic matter (DOM). Here, we derived new nonideal competitive adsorption (NICA) constants for Fe(III) binding to marine DOM via pH-Fe titrations. We used the constants to calculate Fe(III) speciation and derive the apparent Fe(III) solubility (SFe(III)app) in the ambient water column across the Peruvian shelf and slope region. We define SFe(III)app as the sum of aqueous inorganic Fe(III) species and Fe(III) bound to DOM at a free Fe (Fe3+) concentration equal to the limiting solubility of Fe hydroxide (Fe(OH)3(s)). A ca. twofold increase in SFe(III)app in the oxygen minimum zone (OMZ) compared to surface waters is predicted. The increase results from a one order of magnitude decrease in H+ concentration which impacts both Fe(III) hydroxide solubility and organic complexation. A correlation matrix suggests that changes in pH have a larger impact on SFe(III)app and Fe(III) speciation than DOM in this region. Using Fe(II) measurements, we calculated ambient DFe(III) and compared the value with the predicted SFe(III)app. The underlying distribution of ambient DFe(III) largely reflected the predicted SFe(III)app, indicating that decreased pH as a result of OMZ intensification and ocean acidification may increase SFe(III)app with potential impacts on surface DFe inventories

Competitive Interactions Between Microbial Siderophores and Humic-Like Binding Sites in European Shelf Sea Waters

Siderophores are low molecular weight high affinity iron chelates found at low concentrations in seawater. In this study we determined the total concentrations and identities of siderophores in extracts isolated from a shelf sea environment on the Northwest European shelf by high performance liquid chromatography coupled to high resolution inductively coupled plasma mass spectrometry (ICP-MS) in parallel to high resolution electrospray ionisation mass spectrometry (ESI-MS). We identified a total of 24 different siderophores in our samples via metal isotope profiling of masses detected by ESI-MS. Twenty three of the identified siderophores could be assigned to three siderophore families – ferrioxamines, amphibactins and marinobactins. In contrast, only 12 peaks could be resolved in iron chromatograms obtained via ICP-MS analysis. Comparison of results obtained by the two mass spectrometry detectors showed that neither method was able to detect and identify all siderophores present in the samples on its own. We assessed the impact of our observed total siderophore concentrations on iron speciation by calculating the distribution of iron species as a function of total siderophore concentrations at different iron concentrations representative of our study area. We considered competition for iron between siderophores, a humic like dissolved organic matter (DOM) fraction and hydroxide ions by combining an ion-pair model with a non-ideal competitive interaction (NICA)-Donnan model. We found that the overall impact of siderophores on iron biogeochemistry is low at concentrations of siderophore <100 pmol L-1, and that the dominant iron species present at siderophore concentrations of the order of a few tens of pmol L-1 will be iron bound to the humic like DOM fraction. Furthermore the heterogeneity of binding sites in the humic like DOM fraction means that other binding sites present in organic matter could be effective competitors for siderophores, especially at low iron concentrations. Our findings highlight the importance of binding site heterogeneity when considering the influence of different iron binding groups on iron speciation in the marine environment