Plume Samples Research Articles

Large Isotopic Shift in Volcanic Plume CO2 Prior to a Basaltic Paroxysmal Explosion

AbstractCarbon dioxide is a key gas to monitor at volcanoes because its concentration and isotopic signature can indicate changes to magma supply and degassing behavior prior to eruptions, yet carbon isotopic fluctuations at volcanic summits are not well constrained. Here we present δ13C results measured from plume samples collected at Stromboli volcano, Italy, by Uncrewed Aerial Systems (UAS). We found contrasting volcanic δ13C signatures in 2018 during quiescence (−0.36 ± 0.59‰) versus 10 days before the 3 July 2019 paroxysm (−5.01 ± 0.56‰). Prior to the eruption, an influx of CO2‐rich magma began degassing at deep levels (∼100 MPa) in an open‐system fashion, causing strong isotopic fractionation and maintaining high CO2/St ratios in the gas. This influx occurred between 10 days and several months prior to the event, meaning that isotopic changes in the gas could be detected weeks to months before unrest.

Dissolved Cu isotope compositions in hydrothermal plumes over back-arc volcanoes in the Northeast Lau Basin, Southwest Pacific Ocean

Seafloor hydrothermal venting may be an important source of marine Cu and affect the biogeochemical cycling of Cu in the oceans. The distribution of Cu and its isotope compositions (δ65Cu) can provide insight into seafloor hydrothermal processes and their role in the mass balance of global Cu. To date, there are no published Cu isotope data for hydrothermal plumes and very few reports on Cu concentration distributions. This study presents both Cu concentrations and dissolved Cu isotope (δ65Cu) in hydrothermal plumes from back-arc volcanoes in the Northeast Lau Basin. The dissolved Cu (dCu) concentrations range from 2.14 to 5.66 nM most of which are higher than the deep seawater concentrations. However, the concentrations for some plume samples were lower than the deep seawater dCu concentrations due to adsorption onto particles in the plumes. The δ65Cu of hydrothermal plumes vary from 0.25 to 1.05 ‰. As plumes dispersed, the Cu isotopes from high-temperature Mata Fitu and Mata Ua vents shifted towards light values. In contrast, the δ65Cu in plumes from low-temperature East Mata and West Mata vents show increasingly higher values with plume dispersal. Rayleigh distillation models are built based on the adsorption of dCu onto Fe particles and complexation with organic ligands to describe the dCu isotope evolution in hydrothermal plumes. The results suggest that the adsorption and organic complexation may be the likely explanations for the observed dCu isotope compositions in plumes from high- and low-temperature venting, separately, besides the mixing with background seawater. Our measured δ65Cu in three fluid samples (0.08, 0.09 and 0.20 ‰) are lower than that of the characterized sinks (∼0.3 ‰) in the oceans, indicating that hydrothermal fluids might be a source of light Cu isotopes. However, the δ65Cu (0.53 ‰ on average) in plume samples are higher than 0.3 ‰ and these seafloor hydrothermal plumes do not seem to be a source of light Cu isotope of dCu, at least near the venting sites. Our study first reveals the Cu isotope compositions and evolution in hydrothermal plumes and provides new hints about the impact of seafloor hydrothermal venting on the modern oceanic Cu isotope budget.

Behavioral discrimination and olfactory bulb encoding of odor plume intermittency.

In order to survive, animals often need to navigate a complex odor landscape where odors can exist in airborne plumes. Several odor plume properties change with distance from the odor source, providing potential navigational cues to searching animals. Here, we focus on odor intermittency, a temporal odor plume property that measures the fraction of time odor is above a threshold at a given point within the plume and decreases with increasing distance from the odor source. We sought to determine if mice can use changes in intermittency to locate an odor source. To do so, we trained mice on an intermittency discrimination task. We establish that mice can discriminate odor plume samples of low and high intermittency and that the neural responses in the olfactory bulb can account for task performance and support intermittency encoding. Modulation of sniffing, a behavioral parameter that is highly dynamic during odor-guided navigation, affects both behavioral outcome on the intermittency discrimination task and neural representation of intermittency. Together, this work demonstrates that intermittency is an odor plume property that can inform olfactory search and more broadly supports the notion that mammalian odor-based navigation can be guided by temporal odor plume properties.

PHORTEX: Physically-Informed Operational Robotic Trajectories for Scientific Expeditions

Mobile robots are increasingly used to collect valuable in situ samples during scientific expeditions. However, many phenomena of scientific interest—deep-sea hydrothermal plumes, algal blooms, warm-core eddies, and lava flows—are spatiotemporal distributions that evolve on spatial and temporal scales that complicate sample collection. Here, we consider the problem of charting the space-time dynamics of deep-sea hydrothermal plumes with the state-of-the-art autonomous underwater vehicle (AUV) Sentry. In the hydrothermal plume charting problem, the plume state is driven by complicated and unobserved dynamics in the deep sea. To effectively sample the moving plume, an autonomy system must infer plume dynamics from sparse, point observations, while respecting operational constraints of AUV Sentry that restrict the set of possible trajectories to nonadaptive, uniform-coverage patterns. We frame the plume charting problem as a sequential decision-making problem and formulate a mission planner PHORTEX (PHysically-informed Operational Robotic Trajectories for EXpeditions) that strategically designs full mission trajectories for Sentry, where each mission plan is informed by the observations of the last. PHORTEX is composed of a trajectory optimizer, which maximizes expected samples collected within a moving plume, and PHUMES (PHysically-informed Uncertainty Models for Environment Spatiotemporality), a modeling framework that leverages an embedded simulator of idealized plume physics as an inductive bias to enable dynamics learning from extreme partial observations and a few Sentry deployments. In both simulation and in field trials at a hydrothermal site in the Gulf of California, we demonstrate that Sentry using PHORTEX learns to track a moving hydrothermal plume and gather samples that significantly improve upon baseline spatial and temporal diversity for use in downstream science tasks.

Detection of intact amino acids with a hypervelocity ice grain impact mass spectrometer.

Astrobiology studies are a top priority in answering one of the most fundamental questions in planetary science: Is there life beyond Earth? Saturn's icy moon Enceladus is a prime target in the search for life in our solar system, identified by NASA as the second-highest priority site for a flagship mission in the next decade. The orbital sampling technique of impact ionization mass spectrometry indicated the presence of complex organics in the small icy plume particles ejected by Enceladus encountered previously by Cassini. However, high interaction velocities caused ambiguity as to the origin and identity of the organics. Laboratory validation of this technique is needed to show that biosignature molecules can survive an impact at hypervelocity speeds for detection. Here, we present results on the hypervelocity impact of organic-laden submicron ice grains for in situ mass spectrometric characterization with the first technique to accurately replicate this plume sampling scenario: the Hypervelocity Ice Grain Impact Mass Spectrometer. Our results show good agreement with Cassini data at comparable compositions. We show that amino acids entrained in ice grains can be detected intact after impact at speeds up to 4.2 km/s and that salt reduces their detectability, validating the predictions from other model systems. Our results provide a benchmark for this orbital sampling method to successfully detect signs of life and for the interpretation of past and future data. This work has implications not only for a potential Enceladus mission but also for the forthcoming Europa Clipper mission.

Fractionation of iron and chromium isotopes in hydrothermal plumes from the northern Mid-Atlantic Ridge

Hydrothermal venting impacts the global-scale biogeochemical cycles of many trace metals and their isotopes. Processes in hydrothermal plumes regulate the dispersal of vent-derived metals and may vary in response to differences in the geologic setting of vent fields and/or the geochemistry of the overlying ocean water. Here we present results of analyses of dissolved Fe and Cr concentrations, and dissolved Fe isotope (δ56Fe) and Cr isotope (δ53Cr) distributions, in seawater samples collected from above TAG and Rainbow vent sites on the Mid-Atlantic Ridge during the GEOTRACES GA13 cruise. We show that profiles of dissolved Fe and Cr isotopes through the near-field hydrothermal plumes are the mirror image of each other. Oxidation of Fe(II) and precipitation of Fe-(oxyhydr)oxides account for the low δ56Fe values of dissolved Fe, as low as −1.83 ‰ at TAG and −6.94 ‰ at Rainbow. Plume samples with low δ56Fe values are associated with elevated δ53Cr values of dissolved Cr compared to background seawater (by up to +0.14 ‰ and +0.69 ‰ at TAG and Rainbow, respectively), while particulate Cr is characterised by relatively low δ53Cr values (−1.02 to −1.22 ‰). This striking result suggests that seawater Cr(VI) is reduced to Cr(III) and precipitates on the surface of Fe(III) particles within the hydrothermal plume. Reduction of Cr(VI) and scavenging of Cr(III) by plume Fe-(oxyhydr)oxide particles mean that high-temperature hydrothermal systems are likely a net sink for seawater Cr at Rainbow (and also at TAG). As the removal flux of Cr is related to the flux of hydrothermal Fe(II) and the rate of Fe(II) oxidation in the hydrothermal plume, it may (i) vary across vent sites at a global scale and (ii) change over glacial-interglacial cycles.

Geochemical characterization of volcanic gas emissions at Santa Ana and San Miguel volcanoes, El Salvador, using remote-sensing and in situ measurements

Volcanic degassing provides important information for the assessment of volcanic hazards. Santa Ana and San Miguel are open vent volcanoes along the Central American Volcanic Arc–CAVA, where the magmatism, basaltic to dacitic, is related to the near-orthogonal convergence of the Caribbean Plate and the subducting Cocos Plate. Both volcanoes are the most active ones in El Salvador with recent eruptive events in October 2005 (Santa Ana) and December 2013 (San Miguel), but still not much data on gas composition and emission are available today. At each volcano, SO2 emissions are regularly monitored using ground-based scanning Differential Optical Absorption Spectrometer (Scan-DOAS) instruments that are part of the global “Network for Observation of Volcanic and Atmospheric Change” (NOVAC). We used the data series from these NOVAC stations in order to retrieve SO2 and minimum bromine emissions, which can be retrieved from the same spectral data for the period 2006–2020 at Santa Ana and 2008–2019 at San Miguel. However, BrO was not detected above the detection limit. SO2 emission ranged from 10 to 7,760 t/d, and from 10 to 5,870 t/d for Santa Ana and San Miguel, respectively. In addition, the SO2 emissions are complemented with in situ plume data collected during regular monitoring surveys (2018–2020) and two field campaigns in El Salvador (2019 and 2020). MultiGAS instruments recorded CO2, SO2, H2S and H2 concentrations. We determined an average CO2/SO2 ratio of 2.9 ± 0.6 when peak SO2 concentration exceeded 15 ppmv at Santa Ana, while at San Miguel the CO2/SO2 ratio was 7.4 ± 1.8, but SO2 levels reached only up to 6.1 ppmv. Taking into account these ratios and the SO2 emissions determined in this study, the resulting CO2 emissions are about one order of magnitude higher than those determined so far for the two volcanoes. During the two field campaigns Raschig tubes (active alkaline trap) were used to collect plume samples which were analyzed with IC and ICP-MS to identify and quantify CO2, SO2, HCl, HF, and HBr. Additionally, also 1,3,5-trimethoxybenzene (TMB)-coated denuders were applied and subsequently analyzed by GC-MS to determine the sum of the reactive halogen species (RHS: including Cl2, Br2, interhalogens, hypohalous acids). The RHS to sulfur ratios at Santa Ana and San Miguel lie in the range of 10−5. Although no new insights could be gained regarding changes with volcanic activity, we present the most comprehensive gas geochemical data set of Santa Ana and San Miguel volcanoes, leading to a solid data baseline for future monitoring purposes at both volcanoes and their improved estimate of CO2, SO2 and halogens emissions. Determining the reactive fraction of halogens is a first step towards a better understanding of their effects on the atmosphere.

Sulfur cycling connects microbiomes and biogeochemistry in deep-sea hydrothermal plumes

In globally distributed deep-sea hydrothermal vent plumes, microbiomes are shaped by the redox energy landscapes created by reduced hydrothermal vent fluids mixing with oxidized seawater. Plumes can disperse over thousands of kilometers and their characteristics are determined by geochemical sources from vents, e.g., hydrothermal inputs, nutrients, and trace metals. However, the impacts of plume biogeochemistry on the oceans are poorly constrained due to a lack of integrated understanding of microbiomes, population genetics, and geochemistry. Here, we use microbial genomes to understand links between biogeography, evolution, and metabolic connectivity, and elucidate their impacts on biogeochemical cycling in the deep sea. Using data from 36 diverse plume samples from seven ocean basins, we show that sulfur metabolism defines the core microbiome of plumes and drives metabolic connectivity in the microbial community. Sulfur-dominated geochemistry influences energy landscapes and promotes microbial growth, while other energy sources influence local energy landscapes. We further demonstrated the consistency of links among geochemistry, function, and taxonomy. Amongst all microbial metabolisms, sulfur transformations had the highest MW-score, a measure of metabolic connectivity in microbial communities. Additionally, plume microbial populations have low diversity, short migration history, and gene-specific sweep patterns after migrating from background seawater. Selected functions include nutrient uptake, aerobic oxidation, sulfur oxidation for higher energy yields, and stress responses for adaptation. Our findings provide the ecological and evolutionary bases of change in sulfur-driven microbial communities and their population genetics in adaptation to changing geochemical gradients in the oceans.

An emerging plume head interacting with the Hawaiian plume tail

The Hawaiian-Emperor seamount chain has shown two subparallel geographical and geochemical volcanic trends, Loa and Kea, since ∼5 Ma, for which numerous models have been proposed that usually involve a single mantle plume sampling different compositional sources of the deep or shallow mantle. However, both the dramatically increased eruption rate of the Hawaiian hotspot since ∼5 Ma and the nearly simultaneous southward bending of the Hawaiian chain remain unexplained. Here, we propose a plume-plume interaction model where the compositionally depleted Kea trend represents the original Hawaiian plume tail and the relatively enriched Loa trend represents an emerging plume head southeast of the Hawaiian plume tail. Geodynamic modeling further suggests that the interaction between the existing Hawaiian plume tail and the emerging Loa plume head is responsible for the southward bending of the Hawaiian chain. We show that the arrival of the new plume head also dramatically increases the eruption rate along the hotspot track. We suggest that this double-plume scenario may also represent an important mechanism for the formation of other hotspot tracks in the Pacific plate, likely reflecting a dynamic reorganization of the lowermost mantle.

New insights into carbon isotope systematics at Poás volcano, Costa Rica

In April 2017, an intense phreatomagmatic eruptive phase took place at Poás volcano in Costa Rica. This was the most significant eruptive activity at the volcano since the 1950's. Unlike previous eruptions, gas ratios were closely monitored during this event with the use of both ground-based MultiGAS and uncrewed aerial system (UAS) real-time monitoring, providing valuable insight into the nature of the eruption. This well-studied eruption presents a unique opportunity to examine hydrothermal and magmatic processes occurring at Poás during periods of unrest versus quiescent periods. Here, we present stable carbon isotopic results of volcanic CO2 at Poás spanning the pre-eruptive as well as eruptive and post-eruptive phases in 2017 through 2019. Samples were collected by a combination of direct sampling (analyzed by Isotope Ratio Mass Spectrometry [IRMS] or Cavity Ring Down Spectroscopy [CRDS]), as well as UAS and ground-based plume sampling (analyzed by CRDS). Direct samples range from −6.17 to −3.73 ‰ during 2017 to 2019. Using the Keeling approach, we calculate δ13C magmatic source values of −3.97 ± 1.94 ‰ and − 3.64 ± 0.48 ‰ using UAS sampling and ground-based sampling, respectively, for April 2019. We propose that these values for δ13C are being governed by a combination of magmatic and hydrothermal fluctuations related to sealing and unsealing of the upper magma carapace. This process results in comparatively heavy values when the system is being buffered by fluid-gas interaction as the hydrothermal system seals and expands, while lightest values are predominant during unsealed phases where degassed magma supplies the volatiles along with phreatic or phreatomagmatic activity. The significance of this work is two-fold: it demonstrates the use of a rapid volcanic gas sampling strategy applicable for monitoring at other volcanoes prone to phreatomagmatic and/or phreatic eruptions, and it provides a new conceptual model to interpret the phreatic/phreatomagmatic eruptive activity at Poás over the last 20 years.

Strontium, Hydrogen and Oxygen Behavior in Vent Fluids and Plumes from the Kueishantao Hydrothermal Field Offshore Northeast Taiwan: Constrained by Fluid Processes

Strontium (Sr), hydrogen (H) and oxygen (O) in vent fluids are important for understanding the water–rock interaction and hydrothermal flux in hydrothermal systems. We have analyzed the Sr, H and O isotopic compositions of seawater, vent fluid and hydrothermal plume samples in the Kueishantao hydrothermal field, as well as their calcium (Ca), total sulfur (S), Sr, arsenic (As), stibium (Sb), chlorine (Cl) and manganese (Mn) concentrations for understanding the origin and processes of fluids. The results suggest that most As, Sb and Mn are leached from andesitic rocks into the fluids, and most Ca and Cl remained in the deep reaction zone during the fluid–andesitic rock interaction. The ranges of 87Sr/86Sr, δDV-SMOW and δ18OV-SMOW values in the yellow spring, white spring and plumes are small. The 87Sr/86Sr, δDV-SMOW and δ18OV-SMOW values of fluids and plumes are like those of ambient seawater, indicating that the Sr, H and O of vent fluids and hydrothermal plumes are derived primarily from seawater. This suggests that the interaction of andesite and subseafloor fluid is of short duration and results in the majority of As, Sb and Mn being released into fluids, while most Ca and Cl remained in the deep reaction zone. In addition, there was no significant variation of Sr, H and O isotopic compositions in the upwelling fluid, keeping the similar isotopic compositions of seawater. There are obvious correlations among the pH values, As and Sb concentrations, and H isotopic compositions of the vent fluids and hydrothermal plumes, implying that the As and Sb concentrations and H isotopic compositions can trace the dispersion of plumes in the ambient seawater. According to the Sr concentrations and 87Sr/86Sr values, the water/rock ratios are 3076~8124, which is consistent with the idea that the interaction between fluid and andesite at the subseafloor is of short duration. The hydrothermal flux of Sr discharged from the yellow spring into the seawater is between 2.06 × 104 and 2.26 × 104 mol/yr, and the white spring discharges 1.18 × 104~1.26 × 104 mol/yr Sr if just andesites appear in the reaction zone.

A comprehensive review of domestic-open waste burning: recent trends, methodology comparison, and factors assessment.

Open burning is a waste management practice performed by many people worldwide, especially in developing countries. Lack of detailed data of open burning practices may lead to a misinterpretation during data analysis, especially when estimating global/local emissions and assessing risks. This study presents a comprehensive review of current research trends, methodological assessments, and factors behind open waste burning practices from published literature. This review used systematic methods such as PRISMA 2020 methodology, a bibliometric approach, and qualitative content analysis to determine and assess 84 articles related to open burning. The results show that environmental risks and emission factors related to open burning incidents at the landfill or residential level are preferable topics that will be rising in the years to come. Coupling methods such as a transect-based approach with a questionnaire survey and mobile-static plume sampling to determine the activities and incidents as baseline data for risk assessment will help researchers gain a robust dataset of open burning emission inventory. In addition, it was found that environmental knowledge and awareness levels influence open burning practices, thereby opening up opportunities for future research.Supplementary InformationThe online version contains supplementary material available at 10.1007/s10163-022-01430-9.

Distortion of passive scalar structure during suction-based plume sampling

Studies of plume dynamics and olfaction often rely on photoionization detectors (PID) to quantify spatiotemporal distributions of passive scalars (gases, vapors, odors). However, the potential for PID suction to distort filaments and to modify the resulting sensed time record remains unclear. We used computational fluid dynamics to model a widely-used PID to quantify and parameterize suction distortion by considering how sensed concentration records compare to those registered by an ideal probe absent distorting effects. Models cover a range of realistic plume conditions, and we show that PID can modify the peak concentration and pulse shape of sensed records, with peak amplitude reduced by up to 45% and pulse width increased by up to 100% for the cases considered here. We quantified how distortion varies in three key nondimensional parameters describing PID geometry and plume sampling conditions: relative suction rate, relative filament size, and ambient flow Reynolds number. We combined analytical and numerical tools with dimensional analysis and scaling arguments to interpret results and discuss when distortion is likely and what drives it. We built a dimensionless distortion scaling parameter and simple regressions capable of predicting distortion levels, and our results enable PID users to estimate distortion levels and to employ mitigation strategies through suction velocity tuning. We show that an ideal relative suction rate (ratio of suction-to-ambient velocities) near 30 minimizes distortion universally for the Aurora Scientific miniPID. The findings and discussion herein can inform distortion-mitigating design principles and best sampling practices for other suction-based passive scalar sensing schemes.

Controlled-release experiment to investigate uncertainties in UAV-based emission quantification for methane point sources

Abstract. Mapping trace gas emission plumes using in situ measurements from unmanned aerial vehicles (UAVs) is an emerging and attractive possibility to quantify emissions from localized sources. Here, we present the results of an extensive controlled-release experiment in Dübendorf, Switzerland, which was conducted to develop an optimal quantification method and to determine the related uncertainties under various environmental and sampling conditions. Atmospheric methane mole fractions were simultaneously measured using a miniaturized fast-response quantum cascade laser absorption spectrometer (QCLAS) and an active AirCore system mounted on a commercial UAV. Emission fluxes were estimated using a mass-balance method by flying the UAV-based system through a vertical cross-section downwind of the point source perpendicular to the main wind direction at multiple altitudes. A refined kriging framework, called cluster-based kriging, was developed to spatially map individual methane measurement points into the whole measurement plane, while taking into account the different spatial scales between background and enhanced methane values in the plume. We found that the new kriging framework resulted in better quantification compared to ordinary kriging. The average bias of the estimated emissions was −1 %, and the average residual of individual errors was 54 %. A Direct comparison of QCLAS and AirCore measurements shows that AirCore measurements are smoothed by 20 s and had an average time lag of 7 s. AirCore measurements also stretch linearly with time at an average rate of 0.06 s for every second of QCLAS measurement. Applying these corrections to the AirCore measurements and successively calculating an emission estimate shows an enhancement of the accuracy by 3 % as compared to its uncorrected counterpart. Optimal plume sampling, including the downwind measurement distance, depends on wind and turbulence conditions, and it is furthermore limited by numerous parameters such as the maximum flight time and the measurement accuracy. Under favourable measurement conditions, emissions could be quantified with an uncertainty of 30 %. Uncertainties increase when wind speeds are below 2.3 m s−1 and directional variability is above 33∘, and when the downwind distance is above 75 m. In addition, the flux estimates were also compared to estimates from the well-established OTM-33A method involving stationary measurements. A good agreement was found, both approaches being close to the true release and uncertainties of both methods usually capturing the true release.

Sampling Volcanic Plume Using a Drone-Borne SelPS for Remotely Determined Stable Isotopic Compositions of Fumarolic Carbon Dioxide

Both chemical and isotopic compositions of concentrated volcanic plumes are highly useful in evaluating the present status of active volcanoes. Monitoring their temporal changes is useful for forecasting volcanic eruptions as well. Recently, we developed a drone-borne automatic volcanic plume sampler, called SelPS, wherein an output signal from a sulfur dioxide (SO2) sensor triggered a pump to collect plume samples when the SO2 concentration exceeded a predefined threshold. In this study, we added a radio transmission function to the sampler, which enabled our operator to monitor real-time SO2 concentration during flights and thus obtain more concentrated volcanic plume samples through precise adjustment of the hovering position. We attached the improved SelPS to a drone at Nakadake crater, Aso volcano (Japan), and successfully obtained volcanic plume samples ejected from the crater more concentrated than those obtained by using previous version of SelPS in 2019. Additionally, we found a significant linear correlation between the reciprocal of the concentration and isotopic ratios for the 2H/1H ratios of H2, 18O/16O ratios of CO2, and 13C/12C ratios of CO2 within the plume samples. Based on the isotopic ratios of fumarolic H2 (δ2H = −239 ± 6‰) and fumarolic CO2 (δ13C = −3.58 ± 0.85‰ and δ18O = +22.01 ± 0.68‰) determined from the linear correlations, we estimated the apparent equilibrium temperatures (AETs) with magmatic H2O simultaneously and precisely for the first time in erupting volcanoes, assuming hydrogen isotope exchange equilibrium between H2 and H2O (AETD = 629 ± 32°C) and oxygen isotope exchange equilibrium between CO2 and H2O (AET18O = 266 ± 65°C). We found that the AET18O was significantly lower than the AETD in the crater. While the temperature of the magmatic gases was originally 600°C or more, most of the gases cooled just beneath the crater to temperatures around the boiling point of water. The improved SelPS enable us to determine both AETD and AET18O in eruptive volcanoes, wherein fumaroles are inaccessible. Simultaneous and precise determination of both the AET18O and AETD can provide novel information on each volcano, such as the physicochemical conditions of magma degassing and the development of fluid circulation systems beneath each volcano.

Niche differentiation of sulfur-oxidizing bacteria (SUP05) in submarine hydrothermal plumes

Hydrothermal plumes transport reduced chemical species and metals into the open ocean. Despite their considerable spatial scale and impact on biogeochemical cycles, niche differentiation of abundant microbial clades is poorly understood. Here, we analyzed the microbial ecology of two bathy- (Brothers volcano; BrV-cone and northwest caldera; NWC) and a mesopelagic (Macauley volcano; McV) plumes on the Kermadec intra-oceanic arc in the South Pacific Ocean. The microbial community structure, determined by a combination of 16S rRNA gene, fluorescence in situ hybridization and metagenome analysis, was similar to the communities observed in other sulfur-rich plumes. This includes a dominance of the vent characteristic SUP05 clade (up to 22% in McV and 51% in BrV). In each of the three plumes analyzed, the community was dominated by a different yet uncultivated chemoautotrophic SUP05 species, here, provisionally named, Candidatus Thioglobus vadi (McV), Candidatus Thioglobus vulcanius (BrV-cone) and Candidatus Thioglobus plumae (BrV-NWC). Statistical analyses, genomic potential and mRNA expression profiles suggested a SUP05 niche partitioning based on sulfide and iron concentration as well as water depth. A fourth SUP05 species was present at low frequency throughout investigated plume samples and may be capable of heterotrophic or mixotrophic growth. Taken together, we propose that small variations in environmental parameters and depth drive SUP05 niche partitioning in hydrothermal plumes.

Isotopic Signatures of Methane Emissions From Dairy Farms in California’s San Joaquin Valley

AbstractIn this study, we present seasonal atmospheric measurements of δ13CCH4 from dairy farms in the San Joaquin Valley of California. We used δ13CCH4 to characterize emissions from enteric fermentation by measuring downwind of cattle housing (e.g., freestall barns, corrals) and from manure management areas (e.g., anaerobic manure lagoons) with a mobile platform equipped with cavity ring‐down spectrometers. Across seasons, the δ13CCH4 from enteric fermentation source areas ranged from −69.7 ± 0.6 per mil (‰) to −51.6 ± 0.1‰ while the δ13CCH4 from manure lagoons ranged from −49.5 ± 0.1‰ to −40.5 ± 0.2‰. Measurements of δ13CCH4 of enteric CH4 suggest a greater than 10‰ difference between cattle production groups in accordance with diet. Isotopic signatures of CH4 were used to characterize enteric and manure CH4 from downwind plume sampling of dairies. Our findings show that δ13CCH4 measurements could improve the attribution of CH4 emissions from dairy sources at scales ranging from individual facilities to regions and help constrain the relative contributions from these different sources of emissions to the CH4 budget.

Deep learning inversion of gravity data for detection of CO2 plumes in overlying aquifers

We developed an effective U-Net based deep learning (DL) model for inversion of surface gravity data on a rectangular grid to predict 2-D high-resolution subsurface CO2 distribution along a vertical cross-section due to CO2 leakage through a wellbore within a deep CO2 storage reservoir. We used synthetic data to model two types of CO2 leakage scenarios: one CO2 plume in a shallow aquifer (single plume case), and two plumes present at different depths (double plume case). The 3-D synthetic plume samples were created by sampling among predetermined CO2 plume depths, saturations, and volumes. The corresponding surface gravity data on a rectangular grid were generated by a 3-D forward model. The U-Net model detected 72% of single-plume samples, and one or both plumes in 75% of double-plume samples. Most of the undetected single plumes have small gravity field strengths below the typical noise level of 5 μGal. This model generated reproducible, reliable predictions with acceptable errors and demonstrated improved spatial resolution over the conventional least-squares inversion. In contrast to the conventional least-squares inversion, which often overestimates the size of its target and underestimates its density, this U-Net model accurately delineated the boundary of a target. Furthermore, this DL inversion detected deep, small, or low saturation CO2 plumes that are often more difficult to resolve with conventional gravity inversion methods. We note the limitations of this feasibility study, including the use of synthetic data with regular CO2 plume shapes, and the prediction of a 2-D plume cross-section rather than the full 3-D plume, as well, we recognize the lower detection fraction for double-plume scenarios. Nevertheless, this study demonstrates that DL gravity inversion is a promising and potentially superior method to conventional least-squares inversion. Our U-Net based deep learning inversion approach may be adapted for inversion of other types of geophysical data. DL inversion can facilitate near real-time monitoring of geologic carbon sequestration to provide site operators with prompt information about subsurface CO2 distribution for risk management and mitigation.

Soluble, Colloidal, and Particulate Iron Across the Hydrothermal Vent Mixing Zones in Broken Spur and Rainbow, Mid-Atlantic Ridge.

The slow-spreading Mid-Atlantic Ridge (MAR) forms geological heterogeneity throughout the ridge system by deep crustal faults and their resultant tectonic valleys, which results in the existence of different types of hydrothermal vent fields. Therefore, investigating MAR hydrothermal systems opens a gate to understanding the concentration ranges of ecosystem-limiting metals emanating from compositionally distinct fluids for both near-field chemosynthetic ecosystems and far-field transport into the ocean interiors. Here, we present novel data regarding onboard measured, size-fractionated soluble, colloidal, and particulate iron concentrations from the 2018 R/V L’Atalante – ROV Victor research expedition, during which samples were taken from the mixing zone of black smokers using a ROV-assisted plume sampling. Iron size fractionation (<20, 20–200, and >200nm) data were obtained from onboard sequential filtering, followed by measurement via ferrozine assay and spectrophotometric detection at 562nm. Our results showed the persistent presence of a nanoparticulate/colloidal phase (retained within 20–200nm filtrates) even in high-temperature samples. A significant fraction of this phase was retrievable only under treatment with HNO3 – a strong acid known to attack and dissolve pyrite nanocrystals. Upon mixing with colder bottom waters and removal of iron in the higher parts of the buoyant plume, the larger size fractions became dominant as the total iron levels decreased, but it was still possible to detect significant (micromolar) levels of nanoparticulate Fe even in samples collected 5m above the orifice in the rising plume. The coolest sample (<10°C) still contained more than 1μM of only nitric acid-leachable nanoparticle/colloidal, at least 200 times higher than a typical Fe concentration in the non-buoyant plume. Our results support previous reports of dissolved Fe in MAR vent plumes, and we propose that this recalcitrant Fe pool – surviving immediate precipitation – contributes to maintaining high hydrothermal iron fluxes to the deep ocean.

Quantitative evaluation of the feasibility of sampling the ice plumes at Enceladus for biomarkers of extraterrestrial life

Enceladus, an icy moon of Saturn, is a compelling destination for a probe seeking biosignatures of extraterrestrial life because its subsurface ocean exhibits significant organic chemistry that is directly accessible by sampling cryovolcanic plumes. State-of-the-art organic chemical analysis instruments can perform valuable science measurements at Enceladus provided they receive sufficient plume material in a fly-by or orbiter plume transit. To explore the feasibility of plume sampling, we performed light gas gun experiments impacting micrometer-sized ice particles containing a fluorescent dye biosignature simulant into a variety of soft metal capture surfaces at velocities from 800 m ⋅ s-1 up to 3 km ⋅ s-1 Quantitative fluorescence microscopy of the capture surfaces demonstrates organic capture efficiencies of up to 80 to 90% for isolated impact craters and of at least 17% on average on indium and aluminum capture surfaces at velocities up to 2.2 km ⋅ s-1 Our results reveal the relationships between impact velocity, particle size, capture surface, and capture efficiency for a variety of possible plume transit scenarios. Combined with sensitive microfluidic chemical analysis instruments, we predict that our capture system can be used to detect organic molecules in Enceladus plume ice at the 1 nM level-a sensitivity thought to be meaningful and informative for probing habitability and biosignatures.