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  • 2020-2024  (38)
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  • 1
    Publication Date: 2024-02-09
    Description: Tracing pathways and transformations of particulate organic carbon from landscape sources to oceanic sinks is commonly done using the isotopic composition or biomarker content of particulate organic matter (POM). However, similarity of source characteristics and complex mixing in rivers often preclude a robust deconvolution of individual contributions. Moreover, these approaches are limited in detecting organic matter transformations. This impedes understanding of carbon cycling. Fourier Transform Ion Cyclotron Resonance Mass Spectrometry (FT‐ICR‐MS) can simultaneously identify many molecular formulas from mixtures of organic matter, and provide direct information on its compositional variability. Here, we investigate how FT‐ICR‐MS can give insight into POM dynamics on a landscape scale, focusing on the trans‐Himalayan Kali Gandaki River, Nepal. Using molecular information, we identify source tracers in the solvent extractable lipid fraction of riverine POM, finding up to 102 indicative molecular formulas for individual sources. Further, we assess molecular transformations of the lipid fraction of POM during its transfer from litter into topsoil, and onwards into the river. A large number of shared mass formulas and a well‐preserved isoprenoidal patterns suggest efficient incorporation of litter into topsoil. In contrast, we observe a selective loss of mass formulas and a preferential export of formulas with low double bond equivalents and a low nominal oxidation state of carbon after organic matter entrainment in the river. Our results demonstrate the potential of FT‐ICR‐MS for source‐to‐sink studies, allowing detailed organic matter source characterization and discrimination, and tracking of molecular transformations along organic matter pathways spanning different spatial and temporal scales.
    Description: Plain Language Summary: The transfer of organic matter (OM) by rivers from landscape sources into the ocean followed by its burial in marine sediments is an important carbon sink. Therefore, OM is often traced along this journey using its isotopic or biomarker composition. But contributions of OM sources to river sediments can be difficult to estimate because of similar source characteristics, mixing of many sources and changes of the molecular composition along the way. Fourier Transform Ion Cyclotron Resonance Mass Spectrometry (FT‐ICR‐MS) is a novel method able to identify many molecular formulas from OM mixtures at once providing direct information about their molecular composition. Here, we investigate how FT‐ICR‐MS contributes to understanding the transport and transformation of particulate OM focusing on a Himalayan river in Nepal. We use the molecular information to identify tracers for individual OM sources in the landscape. We then assess molecular transformations during the transfer of litter into topsoil, and onwards into the river. Our data suggest efficient incorporation of litter into topsoil, but we observe a selective loss of molecular formulas upon entrainment of sources into the river. Our results reveal that FT‐ICR‐MS is useful for detailed source characterization and tracking of molecular transformations along OM pathways.
    Description: Key Points: Organic matter sourcing and transformations in a Himalayan river studied by FT‐ICR‐MS measurements of solvent extractable lipids. Identification of up to 102 indicator mass formulas for different organic matter sources in the landscape using indicator species analysis. Mass formulas preserved during incorporation of litter into topsoil but selectively lost during entrainment of sources into the river.
    Description: Helmholtz Impuls und Vernetzungsfond
    Description: GFZ expedition funding
    Description: http://doi.org/10.5880/GFZ.4.6.2022.002
    Keywords: ddc:551 ; particulate organic carbon ; solvent extractable lipids ; FT‐ICR‐MS ; Himalaya ; carbon cycling ; indicator species analysis
    Language: English
    Type: doc-type:article
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  • 2
    Publication Date: 2023-05-09
    Description: Abstract
    Description: This data publication contains a high resolution molecular dataset of a study aiming to trace variations in organic carbon sourcing along the Kali Gandaki River in Central Nepal. The data are on samples from different materials in the landscape (litter, soil, bedrock) and river sediments. On these samples we measured the extractable lipid fraction by measured by negative electrospray ionization Fourier transform ion cyclotron resonance mass spectrometry (ESI-FT-ICR-MS). The data was generated between 2015-05 and 2017-12. Please consult the associated data description and Menges et al. (2020) for more details.
    Keywords: organic carbon ; lipids ; EARTH SCIENCE 〉 LAND SURFACE 〉 EROSION/SEDIMENTATION 〉 SEDIMENT CHEMISTRY ; EARTH SCIENCE 〉 LAND SURFACE 〉 GEOMORPHOLOGY 〉 FLUVIAL LANDFORMS/PROCESSES ; In Situ/Laboratory Instruments 〉 Spectrometers/Radiometers 〉 MASS SPECTROMETERS
    Type: Dataset , Dataset
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  • 3
    Publication Date: 2023-11-10
    Description: Abstract
    Description: This data publication is supplementary to a study on the climatic controls on leaf wax hydrogen isotopes, by Gaviria-Lugo et al. (2023). The dataset contains hydrogen isotope ratios from leaf wax n-alkanes (δ2Hwax) taken from soils, river sediments and marine surface sediments along a climatic gradient from hyperarid to humid in Chile. In addition, for each sampling site the hydrogen isotope ratios from precipitation (δ2Hpre) from the grids produced by the Online Isotopes in Precipitation Calculator (OIPC) (Bowen and Revenaugh, 2003). Furthermore, for each sampling site we report mean annual data of precipitation, actual evapotranspiration, relative humidity, and soil moisture, all derived from TerraClimate (Abatzoglou et al., 2018). Also provide data of mean annual temperature and the annual average of maximum daily temperature derived from WorldClim (Fick and Hijmans, 2017). As a final climatic parameter, we also derived data of aridity index from the Consultative Group of the International Agricultural Research Consortium for Spatial Information (CGIARCSI) (Trabucco and Zomer, 2022). In addition to climatic variables, for each site we include land cover fractions of trees, shrubs, grasses, crops, and barren land. These land cover fractions were obtained from Collection 2 of the Copernicus Global Land Cover layers (Buchhorn et al., 2020) via Google Earth Engine. For further comparison here we provide δ2Hwax compiled from 26 publications (see references) that reported both the n-C29 and n-C31 n-alkanes homologues from soils and lake sediments. For each sampling site of the global compilation, we provide δ2Hpre and the same climatic and land cover parameters as for the Chilean data (i.e., precipitation, actual evapotranspiration, relative humidity, soil moisture, aridity index, temperature, fraction of trees, fraction of grasses, etc.), using the same sources. The data is provided here as one single .xlsx file containing 9 data sheets, but also as 9 individual .csv files, to be accessed using the file format of preference. Additionally, 5 supplementary figures that accompany the publication Gaviria-Lugo et al. (2023) are provided in one single .pdf file. The samples taken for this study were assigned International Geo Sample Numbers (IGSNs), which are included in the provided tables S4, S5 and S6.
    Keywords: Leaf-wax ; n-alkanes ; compound specific isotopes ; aridity ; evapotranspiration ; apparent fractionation ; hyperaridity ; Chile ; non-linear ; river sediment ; soils ; marine surface sediments ; chemical 〉 biochemical substance 〉 lipid ; chemical 〉 organic substance 〉 hydrocarbon 〉 alkane ; climate 〉 climate type 〉 desert climate ; EARTH SCIENCE 〉 ATMOSPHERE 〉 ATMOSPHERIC WATER VAPOR 〉 EVAPOTRANSPIRATION ; EARTH SCIENCE 〉 CLIMATE INDICATORS 〉 PALEOCLIMATE INDICATORS 〉 BIOLOGICAL RECORDS 〉 BIOMARKER ; EARTH SCIENCE 〉 CLIMATE INDICATORS 〉 PALEOCLIMATE INDICATORS 〉 PALEOCLIMATE RECONSTRUCTIONS 〉 DROUGHT/PRECIPITATION RECONSTRUCTION ; EARTH SCIENCE 〉 LAND SURFACE 〉 LAND USE/LAND COVER 〉 LAND COVER ; EARTH SCIENCE 〉 LAND SURFACE 〉 SOILS 〉 SOIL MOISTURE/WATER CONTENT ; EARTH SCIENCE 〉 PALEOCLIMATE 〉 LAND RECORDS 〉 ISOTOPES ; EARTH SCIENCE 〉 PALEOCLIMATE 〉 LAND RECORDS 〉 SEDIMENTS
    Type: Dataset , Dataset
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  • 4
    Publication Date: 2021-05-01
    Print ISSN: 0277-3791
    Electronic ISSN: 1873-457X
    Topics: Geography , Geosciences
    Published by Elsevier
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  • 5
    Publication Date: 2024-05-08
    Description: The Himalayan mountain range produces one of the steepest and largest rainfall gradients on Earth, with 〉3 m/yr rainfall difference over a ∼100 km distance. The Indian Summer Monsoon (ISM) contributes more than 80% to the annual precipitation budget of the central Himalayas. The remaining 20% falls mainly during pre-ISM season. Understanding the seasonal cycle and the transfer pathways of moisture from precipitation to the rivers is crucial for constraining water availability in a warming climate. However, the partitioning of moisture into the different storage systems such as snow, glacier, and groundwater and their relative contribution to river discharge throughout the year remains under-constrained. Here, we present novel field data from the Kali Gandaki, a trans-Himalayan river, and use 4-year time series of river and rain water stable isotope composition (δ18O and δ2H values) as well as river discharge, satellite Global Precipitation Measurement amounts, and moisture source trajectories to constrain hydrological variability. We find that rainfall before the onset of the ISM is isotopically distinct and that ISM rain and groundwater have similar isotopic values. Our study lays the groundwork for using isotopic measurements to track changes in precipitation sources during the pre-ISM to ISM transition in this key region of orographic precipitation. Specifically, we highlight the role of pre-ISM precipitation, derived from the Gangetic plain, to define the seasonal river isotopic variability across the central Himalayas. Lastly, isotopic values across the catchment document the importance of a large well-mixed groundwater reservoir supplying river discharge, especially during the non-ISM season.
    Repository Name: EPIC Alfred Wegener Institut
    Type: Article , peerRev
    Format: application/pdf
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  • 6
    Publication Date: 2023-06-21
    Description: To document distinct sources of particulate organic carbon (POC) to the Río Bermejo, we collected 15 soil and 13 leaf litter samples from the local floodplain, and 10 bedrock (predominantly outcroppings of fine-grained sedimentary bedrock) and 2 soil samples from the Río Bermejo headwaters. Leaf litter and soil were oven-dried at 40°C for 〉48 hours. We shredded leaf litter in an industrial blender, homogenized soil samples in an agate mortar and manually removed root and plant debris 〉1 cm, and pulverized bedrock samples to 〈63 µm.
    Keywords: AR15DS-001; AR15DS-005a; AR15DS-005b; AR15DS-008; AR15DS-010b; AR15DS-013; AR15DS-015; AR15DS-016; AR15DS-018; AR15DS-021; AR15DS-045-S; AR15DS-052-S; AR17MR-18; AR17MR-37; AR17MR-38; AR17MR-48; AR17MR-49; Argentina; biogeochemistry; Bucket, plastic; Calculated; Carbon, organic, total; Carbon, organic/Nitrogen, total ratio; DATE/TIME; DEPTH, sediment/rock; Distance; El Colgado; Element analyser (EA); Element analyser isotope ratio mass spectrometer (EA-IRMS); Element analyzer coupled to an accelerator mass spectrometer (EA-AMS); Event label; Fraction modern carbon; Latitude of event; Longitude of event; meandering river; Median, grain size; Nitrogen, total; Nitrogen, total/Carbon, organic ratio; organic carbon (OC); Particle size analyser (Retsch/Horiba LA-950V2); PLV_LL11032018; Puerto lavalle; Reserva Natural Formosa; river sediment; RNF_LL12_3_18; RSF-RB confluence; Sample comment; Sample ID; Sample type; ST15-52; ST15-71; StRATEGy; StRATEGy international research training group; SZ_LL12_3_18; Villa Rio Bermejito; WB; δ13C, organic carbon
    Type: Dataset
    Format: text/tab-separated-values, 222 data points
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  • 7
    Publication Date: 2023-06-21
    Description: These data were collected from the Río Bermejo in northern Argentina. To determine the seasonal variability in the particulate organic carbon composition of exported river sediment, we collected weekly suspended sediment samples (March 2016 to March 2018) at the Puente Lavalle (PLV) monitoring site, ~870 river km downstream of the mountain front (-25.655°S, -60.130°W). Surface water samples were collected from a bridge using a river-rinsed bucket and were filtered through a 0.22 µm polyethersulfone membrane. Samples were stored on site at ambient temperatures for up to one year, transferred to Germany and subsequently stored at ~4°C until processing. Suspended sediment was rinsed from filters into pre-combusted glass evaporating dishes using ultra-pure (18.2 M) water, oven-dried at 40°C for 〉48 hr, and homogenized in an agate mortar without crushing. Geochemical and grain size analyses required 0.8 g sediment; for samples 〈0.8 g, we combined consecutive weekly samples to create a new bulk sample of 〉0.8 g (Table S1). We split sediment samples into aliquots for grain size analysis via laser diffraction and geochemical analyses. Sediment particle size distributions were measured on ~0.2 g aliquots using a laser diffraction particle size analyzer (Retsch/Horiba LA-950V2). Aliquots for geochemical analyses were ground to 〈63 µm. The homogenized suspended sediment, bedrock, soil and leaf litter aliquots were further split for total nitrogen measurement (TN, wt%) and organic carbon analyses including total organic carbon (TOC, wt%), stable carbon isotope composition (δ13COC), and radiocarbon fraction modern (Fm). We decarbonated the aliquots for POC measurements using a liquid HCl leach following Galy et al., (2007). TOC and TN measurements were split between facilities at the German Research Centre for Geosciences (GFZ), Durham University, and University of Nevada Reno (UNR) using an elemental analyzer (EA). δ13COC was measured with a coupled EA-isotope ratio mass spectrometer (EA-IRMS). All isotopic compositions are reported using standard delta (δ) notation in per mil (‰) relative to Vienna PeeDee Belemnite (VPDB). Calibration and accuracy were monitored through analyses of in-house standards (Glutamic Acid, 40.82% C, 9.52% N at Durham; Boden3, HEKATECH at GFZ), which were calibrated against international standards (e.g., USGS 40, USGS 24, IAEA 600, IAEA CH3, IAEA CH7, IAEA N1, IAEA N2). Radiocarbon content was measured for a subset of 29 samples at ETH Zürich using a combined EA and accelerator mass spectrometer (EA-AMS) (Ruff et al. 2010; McIntyre et al., 2017). All 14C /12C ratios are reported as fraction modern (Fm, equivalent to F14C as defined by Reimer et al. (2004)) relative to 95% of the 14C activity of NBS Oxalic Acid II in 1950 (δ13COC = -17.8‰) and normalized to δ13COC = -25‰ of VPDB.\n\nThis geochemical dataset is supported by hydrologic measurements of daily water discharge at the El Colorado gauging station (river km 1086, SNIH, https://snih.hidricosargentina.gob.ar/) collected between 2016 and 2018.
    Keywords: biogeochemistry; Bucket, plastic; Calculated; Carbon, organic, total; Carbon, organic/Nitrogen, total ratio; DATE/TIME; Element analyser (EA); Element analyser isotope ratio mass spectrometer (EA-IRMS); Element analyzer coupled to an accelerator mass spectrometer (EA-AMS); Event label; Fraction modern carbon; Latitude of event; Longitude of event; meandering river; Median, grain size; Nitrogen, total; Nitrogen, total/Carbon, organic ratio; organic carbon (OC); Particle size analyser (Retsch/Horiba LA-950V2); PLV_01042016; PLV_01062016; PLV_01062017; PLV_01122017; PLV_02012018; PLV_02092016; PLV_02122016; PLV_04052017; PLV_06012017; PLV_06052016; PLV_06072016; PLV_06082016; PLV_07022018; PLV_07042017; PLV_07102016; PLV_08042016; PLV_08052017; PLV_08122016; PLV_09062017; PLV_09082017; PLV_09112017; PLV_10062016; PLV_11122017; PLV_12012018; PLV_12042016; PLV_12062017; PLV_12072016; PLV_12072017; PLV_12082016; PLV_13012017; PLV_14042017; PLV_14052016; PLV_16022018; PLV_16092016; PLV_16122016; PLV_17062016; PLV_18012017; PLV_18032016; PLV_19012018; PLV_19052017; PLV_19082016; PLV_20052016; PLV_20122017; PLV_21022018; PLV_21042017; PLV_22042016; PLV_22072016; PLV_23122016; PLV_24012018; PLV_24032016; PLV_24032017; PLV_24062016; PLV_24102016; PLV_24112016; PLV_26072017; PLV_26082016; PLV_27012017; PLV_27052016; PLV_27062016; PLV_28042017; PLV_28062017; PLV_28122017; PLV_29042016; PLV_29072016; PLV_29092017; PLV_30032017; PLV_30122016; PLV_31012018; PLV_31082017; Puerto lavalle; River discharge, daily; river sediment; Sample comment; Sample ID; Sampling date; Season; StRATEGy; StRATEGy international research training group; WB; δ13C, organic carbon
    Type: Dataset
    Format: text/tab-separated-values, 696 data points
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  • 8
    Publication Date: 2023-06-21
    Description: To test the potential of meteoric 10Be (10Bem) as a river sediment transit time proxy, we measured 10Bem concentrations in river suspended sediment of the Rio Bermejo (northern Argentina), which is a river with a ~1300 km lowland flowpath void of tributaries. We collected fluvial suspended sediment in vertical depth profiles at five sampling locations along the length of the Rio Bermejo (northern Argentina) during near-bankfull conditions, when discharge varied between 675 and 1080 m**3/s and banks were actively eroding. Additionally, we collected one depth profile from Rio San Francisco (RSF) and one from the Rio Bermejo 10 km upstream of the RSF confluence. Combining these profiles and weighting them by the relative proportions of their total sediment load input to the mainstem Bermejo serves as an integrated headwater depth profile. In the thalweg, we collected water and suspended sediment from a boat using a weighted 8-liter horizontal sampling bottle (Wildco Beta Plus bottle) with an attached pressure transducer to measure sampling depth. We separated sediment from the water using a custom-built 5-liter pressurized filtration unit with a 293 mm diameter, 0.2 µm polyethersulfone filter. In the laboratory, we rinsed sediment off the filters directly into an evaporating dish with ultrapure 18.2 MΩ water (pH~7; when needed, we added NH3 solution to the water to maintain pH~7). Samples were dried in an oven at 40ºC, and subsequently homogenized. Sediment particle size distributions were measured on ~10 mg aliquots using a laser diffraction particle size analyzer (Horiba LA-950). Specific surface area (SSA) of bulk sediment samples was measured on ~4 g aliquots using a Quantachrome NOVAtouch LX gas sorption analyzer and the Brunauer, Emmett, and Teller (BET) theory (Brunauer et al., 1938). The total reactive phase, including amorphous oxyhydroxides and crystalline oxide grain coatings, was extracted from the sediment samples using a procedure adapted from Wittmann et al. (2012, doi:10.1016/j.chemgeo.2012.04.031). 10Bem was purified from the extracted material, spiked with a 9Be carrier solution containing 150 µg of 9Be, and packed into targets for AMS measurement at the University of Cologne Centre for Accelerator Mass Spectrometry (Cologne, Germany). 10Be /9Be measurements were normalized to the KN01-6-2 and KN01-5-3 standards (Dewald et al., 2013, doi:10.1016/j.nimb.2012.04.030) that are consistent with a 10Be half-life of 1.36 ± 0.07 x10^6 yrˉ¹ (Nishiizumi et al., 2007, doi:10.1016/j.nimb.2007.01.297). [10Be]m was calculated from the normalized and blank-corrected 10Be/9Be ratios. The reported 1σ uncertainties include counting statistics and the uncertainties of both standard normalization and blank correction. Stable 9Be concentrations were measured on a separate aliquot of the sample solution using inductively coupled plasma optical emission spectroscopy (ICP-OES). Uncertainty of ICP-OES measurements was 5%.
    Keywords: Accelerator mass spectrometry (AMS); AR17DS-001; AR17MR-05; AR17MR-06; AR17MR-07; AR17MR-08; AR17MR-11; AR17MR-12; AR17MR-13; AR17MR-14; AR17MR-24; AR17MR-25; AR17MR-26; AR17MR-27; AR17MR-30; AR17MR-31; AR17MR-32; AR17MR-33; AR17MR-34; AR17MR-35; AR17MR-36; AR17MR-42; AR17MR-43; AR17MR-44; AR17MR-45; AR17MR-46; Beryllium-10; Beryllium-10, standard deviation; Beryllium-10/Beryllium-9; Beryllium-10/Beryllium-9, standard deviation; Beryllium-9; Beryllium-9, standard deviation; Calculated/normalized; CONFLUENCE; DEPTH, water; Distance; El Colgado; ELEVATION; Embarcacion; Event label; Gas sorption analyszer (Quantachrome NOVAtouch LX) and BET-method (Brunauer et al., 1938); General Mansilla; Grain Size; integrated; LATITUDE; LONGITUDE; Median, grain size; meteoric 10Be; OSL; pH; Puerto lavalle; Reserva Natural Formosa; Rio San Francisco; river sediment; Sample ID; Scattering Particle Size Distribution Analyzer LA-950 (Horiba); Size fraction 〈 0.063 mm, mud, silt+clay; Specific surface area; Suspended sediment concentration
    Type: Dataset
    Format: text/tab-separated-values, 401 data points
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  • 9
    Publication Date: 2023-06-21
    Description: These data were collected from the Río Bermejo in northern Argentina. To determine the seasonal variability in the particulate organic carbon composition of exported river sediment, we collected weekly suspended sediment samples (March 2016 to March 2018) at the Puente Lavalle (PLV) monitoring site, ~870 river km downstream of the mountain front (-25.655°S, -60.130°W). Surface water samples were collected from a bridge using a river-rinsed bucket and were filtered through a 0.22 µm polyethersulfone membrane. Samples were stored on site at ambient temperatures for up to one year, transferred to Germany and subsequently stored at ~4°C until processing. To document distinct sources of particulate organic carbon (POC) to the Río Bermejo, we collected 15 soil and 13 leaf litter samples from the local floodplain, and 10 bedrock (predominantly outcroppings of fine-grained sedimentary bedrock) and 2 soil samples from the Río Bermejo headwaters. Suspended sediment was rinsed from filters into pre-combusted glass evaporating dishes using ultra-pure (18.2 M) water, oven-dried at 40°C for 〉48 hr, and homogenized in an agate mortar without crushing. Leaf litter and soil were oven-dried at 40°C for 〉48 hours. We shredded leaf litter in an industrial blender, homogenized soil samples in an agate mortar and manually removed root and plant debris 〉1 cm, and pulverized bedrock samples to 〈63 µm. Geochemical and grain size analyses required 0.8 g sediment; for samples 〈0.8 g, we combined consecutive weekly samples to create a new bulk sample of 〉0.8 g (Table S1). We split sediment samples into aliquots for grain size analysis via laser diffraction and geochemical analyses. Sediment particle size distributions were measured on ~0.2 g aliquots using a laser diffraction particle size analyzer (Retsch/Horiba LA-950V2). Aliquots for geochemical analyses were ground to 〈63 µm. The homogenized suspended sediment, bedrock, soil and leaf litter aliquots were further split for total nitrogen measurement (TN, wt%) and organic carbon analyses including total organic carbon (TOC, wt%), stable carbon isotope composition (δ13COC), and radiocarbon fraction modern (Fm). We decarbonated the aliquots for POC measurements using a liquid HCl leach following Galy et al. (2007, doi:10.1111/j.1751-908X.2007.00864.x)). TOC and TN measurements were split between facilities at the German Research Centre for Geosciences (GFZ), Durham University, and University of Nevada Reno (UNR) using an elemental analyzer (EA). δ13COC was measured with a coupled EA-isotope ratio mass spectrometer (EA-IRMS). All isotopic compositions are reported using standard delta (δ) notation in per mil (‰) relative to Vienna PeeDee Belemnite (VPDB). Calibration and accuracy were monitored through analyses of in-house standards (Glutamic Acid, 40.82% C, 9.52% N at Durham; Boden3, HEKATECH at GFZ), which were calibrated against international standards (e.g., USGS 40, USGS 24, IAEA 600, IAEA CH3, IAEA CH7, IAEA N1, IAEA N2). Radiocarbon content was measured for a subset of 29 samples at ETH Zürich using a combined EA and accelerator mass spectrometer (EA-AMS) (Ruff et al. (2010, doi:10.1017/S003382220005637X); McIntyre et al. (2017, doi:10.1017/RDC.2016.68)). All 14C /12C ratios are reported as fraction modern (Fm, equivalent to F14C as defined by Reimer et al. (2004)) relative to 95% of the 14C activity of NBS Oxalic Acid II in 1950 (δ13COC = -17.8‰) and normalized to δ13COC = -25‰ of VPDB. This geochemical dataset is supported by hydrologic measurements of daily water discharge at the El Colorado gauging station (river km 1086, SNIH, https://snih.hidricosargentina.gob.ar/) collected between 2016 and 2018.
    Keywords: biogeochemistry; meandering river; organic carbon (OC); river sediment; StRATEGy; StRATEGy international research training group
    Type: Dataset
    Format: application/zip, 2 datasets
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  • 10
    Publication Date: 2023-06-21
    Description: To study the transformation of organic carbon through long distance transport in rivers, we measured the composition of bulk organic carbon in river suspended sediment of the Rio Bermejo (northern Argentina). This river has a ~1300 km lowland flowpath with no significant tributaries. We collected fluvial suspended sediment in vertical depth profiles at five sampling locations along the length of the Rio Bermejo (northern Argentina) during near-bankfull conditions, when discharge varied between 675 and 1080 m3/s and banks were actively eroding. Additionally, we collected one depth profile from the Rio San Francisco (RSF) and one from the Rio Bermejo 10 km upstream of the RSF confluence. Combining these profiles and weighting them by the relative proportions of their total sediment load input to the mainstem Bermejo serves as a depth profile representing the headwaters. At each depth profile location, we collected water and suspended sediment from the channel thalweg by boat. We used a weighted 8-liter horizontal sampling bottle (Wildco Beta Plus bottle) with an attached pressure transducer to measure sampling depth. We separated sediment from the water using a custom-built 5-liter pressurized filtration unit with a 293 mm diameter, 0.2 µm polyethersulfone filter. In the laboratory, we rinsed sediment off the filters directly into an evaporating dish with ultrapure 18.2 MΩ water (pH~7). Samples were dried in an oven at 40ºC, and subsequently homogenized. Sediment particle size distributions were measured on ~10 mg aliquots using a laser diffraction particle size analyzer (Horiba LA-950). Specific surface area (SSA) of bulk sediment samples was measured on ~4 g aliquots using a Quantachrome NOVAtouch LX gas sorption analyzer and the Brunauer, Emmett, and Teller (BET) theory (Brunauer et al., 1938). Aliquots for organic carbon measurements were first treated with 4% HCl solution to remove inorganic carbon, following Galy et al. (2007, doi:10.1111/j.1751-908X.2007.00864.x). Total organic carbon (TOCPOC) and δ13C of POC was measured in duplicate at Durham University using a Costech elemental analyzer (EA) coupled to a CONFLO III and Thermo Scientific Delta V Advantage isotope ratio mass spectrometer (IRMS). Radiocarbon content was measured using an EA coupled to an accelerator mass spectrometer (EA-AMS) at ETH Zurich. We report 14C content as fraction modern (F14C), by normalizing measurements to 95% of the 1950 NBS Oxalic Acid II standard (δ13C = -17.8‰) and correcting for mass-dependent fractionation using a common δ13C value of -25‰. OC loading is the mass of organic carbon in a sample normalized by the sample's specific surface area (SSA). Reactive metals in the amorphous oxyhydroxide and crystalline oxide grain coatings, were extracted from the sediment samples using a procedure adapted from Wittmann et al. (2012, doi:10.1016/j.chemgeo.2012.04.031). The extracted oxyhydroxides and oxides were dried down and diluted in 3M HNO3. A 100 μl aliquot was taken for measurement of metal concentrations. Al, Fe, Mg, and Mn concentrations were measured using inductively coupled plasma optical emission spectroscopy (ICP-OES). Uncertainty of ICP-OES measurements was 〈5%. All depth-integrated values are calculated as a function of the suspended sediment concentration relative to the depth-averaged suspended sediment concentration.
    Keywords: Aluminium, reactive; AR17MR-05; AR17MR-06; AR17MR-07; AR17MR-08; AR17MR-11; AR17MR-12; AR17MR-13; AR17MR-14; AR17MR-24; AR17MR-25; AR17MR-26; AR17MR-27; AR17MR-30; AR17MR-31; AR17MR-32; AR17MR-33; AR17MR-34; AR17MR-35; AR17MR-36; AR17MR-42; AR17MR-43; AR17MR-44; AR17MR-45; AR17MR-46; Carbon, organic, loading; Carbon, organic, loading, standard error; Carbon, organic, total; Carbon, organic, total, standard error; CONFLUENCE; DATE/TIME; Depth, relative; Depth comment; Distance; El Colgado; Element analyser CHN (Costech) coupled to a CONFLO III and Thermo Scientific Delta V Advantage isotope ratio mass spectrometer (IRMS); Element analyzer coupled to an accelerator mass spectrometer (EA-AMS); ELEVATION; Embarcacion; Event label; Fraction modern carbon; Fraction modern carbon, standard error; Gas sorption analyszer (Quantachrome NOVAtouch LX) and BET-method (Brunauer et al., 1938); General Mansilla; Grain Size; ICP-OES, Inductively coupled plasma - optical emission spectrometry; Iron, reactive; LATITUDE; LONGITUDE; Magnesium, reactive; Manganese, reactive; Median, grain size; Normalized; oxyhydroxide; Particulate organic carbon; Puerto lavalle; radiocarbon; Reactive minerals, total; Reserva Natural Formosa; Rio San Francisco; river sediment; Sample ID; Scattering Particle Size Distribution Analyzer LA-950 (Horiba); Sediment transit time; Sediment transit time, uncertainty; Size fraction 〈 0.030 mm; Specific surface area; surface area; Suspended sediment concentration; TOC; Weighted average; δ13C; δ13C, standard error
    Type: Dataset
    Format: text/tab-separated-values, 528 data points
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