Vanadium(V) adsorption onto goethite (α-FeOOH) at pH 1.5 to 12: a surface complexation model based on ab initio molecular geometries and EXAFS spectroscopy

We measured the adsorption of V(V) onto goethite (α-FeOOH) under oxic (P_O2 = 0.2 bar) atmospheric conditions. EXAFS spectra show that V(V) adsorbs by forming inner-sphere complexes as VO₂(OH)₂ and VO₃(OH). We predicted the relative energies and geometries of VO₂(O, OH)₂-FeOOH surface complexes using ab initio calculations of the geometries and energetics of analogue Fe₂(OH)₂(H₂O)₆O₂VO₂(O, OH)₂ clusters. The bidentate corner-sharing complex is predicted to be substantially (57 kJ/mol) favoured energetically over the hypothetical edge-sharing bidentate complex. Fitting the EXAFS spectra using multiple scattering shows that only the bidentate corner-sharing complex is present with Fe-V and V-O distances in good agreement with those predicted. We find it important to include multiple scattering in the fits of our EXAFS data otherwise spurious V-Fe distances near 2.8 Å result which may be incorrectly attributed to edge-sharing complexes. We find no evidence for monodentate complexes; this agrees with predicted high energies of such complexes. Having identified the Fe₂O₂V(OH)₂⁺ and Fe₂O₂VO(OH)⁰ surface complexes, we are able to fit the experimental vanadium(V) adsorption data to the reactions

     

Tracing iron-fueled microbial carbon production within the hydrothermal plume at the Loihi seamount

The Loihi hydrothermal plume provides an opportunity to investigate iron (Fe) oxidation and microbial processes in a system that is truly Fe dominated and distinct from mid-ocean ridge spreading centers. The lack of hydrogen sulfide within the Loihi hydrothermal fluids and the presence of an oxygen minimum zone at this submarine volcano’s summit, results in a prolonged presence of reduced Fe within the dispersing non-buoyant plume. In this study, we have investigated the potential for microbial carbon fixation within the Loihi plume. We sampled for both particulate and dissolved organic carbon in hydrothermal fluids, microbial mats growing around vents, and the dispersing plume, and carried out stable carbon isotope analysis on the particulate fraction. The δ¹³C values of the microbial mats ranged from −23‰ to −28‰, and are distinct from those of deep-ocean particulate organic carbon (POC). The mats and hydrothermal fluids were also elevated in dissolved organic carbon (DOC) compared to background seawater. Within the hydrothermal plume, DOC and POC concentrations were elevated and the isotopic composition of POC within the plume suggests mixing between background seawater POC and a ¹³C-depleted hydrothermal component. The combination of both DOC and POC increasing in the dispersing plume that cannot solely be the result of entrainment and DOC adsorption, provides strong evidence for in-situ microbial productivity by chemolithoautotrophs, including a likelihood for iron-oxidizing microorganisms.     

Disaggregating soil erosion processes within an evolving experimental landscape

Soil‐mantled landscapes subjected to rainfall, runoff events, and downstream base level adjustments will erode and evolve in time and space. Yet the precise mechanisms for soil erosion also will vary, and such variations may not be adequately captured by soil erosion prediction technology. This study sought to monitor erosion processes within an experimental landscape filled with packed homogenous soil, which was exogenically forced by rainfall and base level adjustments, and to define the temporal and spatial variation of the erosion regimes. Close‐range photogrammetry and terrain analysis were employed as the primary methods to discriminate these erosion regimes. Results show that (1) four distinct erosion regimes can be identified (raindrop impact, sheet flow, rill, and gully), and these regimes conformed to an expected trajectory of landscape evolution; (2) as the landscape evolved, the erosion regimes varied in areal coverage and in relative contribution to total sediment efflux measured at the outlet of the catchment; and (3) the sheet flow and rill erosion regimes dominated the contributions to total soil loss. Disaggregating the soil erosion processes greatly facilitated identifying and mapping each regime in time and space. Such information has important implications for improving soil erosion prediction technology, for assessing landscape degradation by soil erosion, for mapping regions vulnerable to future erosion, and for mitigating soil losses and managing soil resources. Copyright © 2017 John Wiley & Sons, Ltd.     

Quantifying the largest aggregation of giant trevally Caranx ignobilis (Carangidae) on record: implications for management

The giant trevally Caranx ignobilis (Forsskål) is an important apex predatory fish typically associated with coral reef communities. It is prized in recreational and commercial fisheries, yet little is known about its aggregation dynamics and susceptibility to fishing pressure. This study reports on a previously undocumented aggregation of mature giant trevally observed over a period of eight years (2010–2017) at Ponta do Ouro Partial Marine Reserve in southern Mozambique. The aggregation is one of the few recorded for this carangid in the western Indian Ocean and represents the first subtropical aggregation of giant trevally. The aggregation is also the largest recorded for this species, with up to 2 413 individuals representing an estimated biomass of approximately 30 tonnes. The size and predictability of this annual aggregation make it vulnerable to overexploitation and point towards the need for an appropriate conservation management strategy.     

Polychlorinated dibenzo-p-dioxins and polychlorinated dibenzofurans in sediments from Hong Kong

Concentrations of 2,3,7,8-substituted polychlorinated dibenzo-p-dioxins (PCDDs) and polychlorinated dibenzofurans (PCDFs) were determined in 14 sediment samples collected from four sites in the Mai Po Marshes Nature Reserve (within a RAMSAR Site) and from another six sites in Victoria Harbour and along the Hong Kong coastline. Elevated levels of PCDDs, and particularly OCDD, were detectable in all samples collected from the Mai Po Marshes and five of the six sites. In contrast to PCDDs, PCDFs were mainly found in sediment samples collected from industrial areas (Kwun Tong and To Kwa Wan) in Victoria Harbour. PCDD/F levels and congener profiles in the samples from the Mai Po Marshes Nature Reserve in particular show strong similarities to those reported in studies which have attributed similar elevated PCDD concentrations to nonanthropogenic PCDD sources.     

Rapid Holocene coastal change revealed by high-resolution micropaleontological analysis, Pamlico Sound, North Carolina, USA

Foraminiferal analyses of 404 contiguous samples, supported by diatom, lithologic, geochronologic and seismic data, reveal both rapid and gradual Holocene paleoenvironmental changes in an 8.21-m vibracore taken from southern Pamlico Sound, North Carolina. Data record initial flooding of a latest Pleistocene river drainage and the formation of an estuary 9000 yr ago. Estuarine conditions were punctuated by two intervals of marine influence from approximately 4100 to 3700 and 1150 to 500 cal yr BP. Foraminiferal assemblages in the muddy sand facies that accumulated during these intervals contain many well-preserved benthic foraminiferal species, which occur today in open marine settings as deep as the mid shelf, and significant numbers of well-preserved planktonic foraminifera, some typical of Gulf Stream waters. We postulate that these marine-influenced units resulted from temporary destruction of the southern Outer Banks barrier islands by hurricanes. The second increase in marine influence is coeval with increased rate of sea-level rise and a peak in Atlantic tropical cyclone activity during the Medieval Climate Anomaly. This high-resolution analysis demonstrates the range of environmental variability and the rapidity of coastal change that can result from the interplay of changing climate, sea level and geomorphology in an estuarine setting.     

A late Ordovician (Hirnantian) karstic surface in a submarine channel,recording glacio‐eustatic sea‐level changes: Meifod,central Wales

The growth and decay of the end‐Ordovician Gondwanan glaciation is globally reflected by facies changes in sedimentary sequences, which record a major eustatic fall and subsequent rise in the Hirnantian Stage at the end of the Ordovician. However, there are different reported estimates of the magnitude and pattern of sea‐level change. Particularly good evidence for end‐Ordovician sea‐level change comes from a sequence at Meifod in central Wales, which has a karstified limestone unit within a channel incised into marine shelf sediments. Pre‐glacial (Rawtheyan) mudstones have a diverse fauna suggesting a mid‐to‐deep‐shelf water depth of c. 60 m. The channel, 20 m deep, was incised into these mudstones and partially filled with a mixture of fine sand and detrital carbonate. The taphonomy of bioclasts and intraclasts indicates that many had a long residence time on the sea floor or suffered diagenesis after shallow burial before being resedimented into the channel. The presence of carbonates on the Welsh shelf is atypical and they are interpreted as having accumulated as patches during a minor regression prior to the main glacio‐eustatic fall. Comparison of the carbon stable‐isotopic values of the bioclast material with the global isotopic record confirms that most of the material is of Rawtheyan age, but that some is Hirnantian. The resedimented carbonates lithified rapidly and formed a limestone, several metres thick, in the deepest parts of the channel. As sea‐level fell, this limestone was exposed and eroded into karstic domes and pillars with a relief of over 2 m. The overall, glacio‐eustatic, sea‐level fall is estimated to be in excess of 80 m. A succeeding sea‐level rise estimated to be 40–50 m is recorded in the laminated crust that mantles the karstic domes and pillars. The crust is formed of encrusting bryozoans, associated cystoids, crinoid holdfasts and clusters of the brachiopod Paromalomena, which is normally associated with mid‐shelf environments. Fine sands buried the karst topography and accumulated to fill the channel. In the sandstones at the base of the channel there is a Hirnantia fauna, while in the sandstones high in the channel‐sequence there is cross‐stratification characteristic of mid‐shoreface environments. This would indicate a fall of sea‐level of c. 30 m. The subsequent major transgression marking the end of the glaciation is not recorded at the Meifod locality, but nearby exposures of mudstones suggest a return to mid‐to‐deep‐shelf environments, similar to those that prevailed before the Hirnantian regression. The Meifod sequence provides strong evidence for the magnitude of the Hirnantian sea‐level changes and by implication confirm larger estimates for the size of the ice sheets. Smaller oscillations in relative sea‐level seen at Meifod may be local phenomena or may reflect eustatic changes that have not been widely reported elsewhere. Copyright © 2005 John Wiley & Sons, Ltd.     

Acceleration of thermodynamic computations in fluid flow applications

Reservoir simulators model the highly nonlinear partial differential equations that represent flows in heterogeneous porous media. The system is made up of conservation equations for each thermodynamic species, flash equilibrium equations and some constraints. With advances in Field Development Planning (FDP) strategies, clients need to model highly complex Improved Oil Recovery processes such as gas re-injection and CO2 injection, which requires multi-component simulation models. The operating range of these simulation models is usually around the mixture critical point and this can be very difficult to simulate due to phase mislabeling and poor nonlinear convergence. We present a Machine Learning (ML) based approach that significantly accelerates such simulation models. One of the most important physical parameters required in order to simulate complex fluids in the subsurface is the critical temperature (T_crit). There are advanced iterative methods to compute the critical point such as the algorithm proposed by Heidemann and Khalil (AIChE J 26,769–799, 1980) but, because these methods are too expensive, they are usually replaced by cheaper and less accurate methods such as the Li-correlation (Reid and Sherwood 1966). In this work we use a ML workflow that is based on two interacting fully connected neural networks, one a classifier and the other a regressor, that are used to replace physical algorithms for single phase labelling and improve the convergence of the simulator. We generate real time compositional training data using a linear mixing rule between the injected and the in-situ fluid compositions that can exhibit temporal evolution. In many complicated scenarios, a physical critical temperature does not exist and the iterative sequence fails to converge. We train the classifier to identify, a-priori, if a sequence of iterations will diverge. The regressor is then trained to predict an accurate value of T_crit. A framework is developed inside the simulator based on TensorFlow that aids real time machine learning applications. The training data is generated within the simulator at the beginning of the simulation run and the ML models are trained on this data while the simulator is running. All the run-times presented in this paper include the time taken to generate the training data and train the models. Applying this ML workflow to real field gas re-injection cases suffering from severe convergence issues has resulted in a 10-fold reduction of the nonlinear iterations in the examples shown in this paper, with the overall run time reduced 2- to 10-fold, thus making complex FDP workflows several times faster. Such models are usually run many times in history matching and optimization workflows, which results in compounded computational savings. The workflow also results in more accurate prediction of the oil in place due to better single phase labelling.