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  • 1
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    (Table T2) Age vs. stable isotopes of planktic foraminifers for a spliced core of ODP Sites 184-1147 and 184-1148 (2004)
    PANGAEA
    Details
    Publication Date: 2024-01-09
    Keywords: 184-1147; AGE; COMPCORE; Composite Core; DEPTH, sediment/rock; Foraminifera, planktic δ13C; Foraminifera, planktic δ18O; Joides Resolution; Leg184; Mass spectrometer Finnigan MAT 252; Ocean Drilling Program; ODP; South China Sea
    Type: Dataset
    Format: text/tab-separated-values, 1950 data points
    Location Call Number Limitation Availability
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    DATA PANGAEA
  • 2
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    (Table T3) Oxygen and carbon isotope ratios of benthic foraminifers from ODP Sites 184-1147 and 184-1148 (2004)
    PANGAEA
    Details
    Publication Date: 2024-01-09
    Keywords: 184-1147A; 184-1147B; 184-1147C; 184-1148A; 184-1148B; Cibicidoides kullenbergi, δ13C; Cibicidoides kullenbergi, δ18O; Cibicidoides spp., δ13C; Cibicidoides spp., δ18O; Cibicidoides wuellerstorfi, δ13C; Cibicidoides wuellerstorfi, δ18O; Depth, composite; DEPTH, sediment/rock; DRILL; Drilling/drill rig; DSDP/ODP/IODP sample designation; Event label; Foraminifera, benthic δ13C; Foraminifera, benthic δ18O; Joides Resolution; Leg184; Mass spectrometer Finnigan MAT 252; Ocean Drilling Program; ODP; Oridorsalis spp., δ13C; Oridorsalis spp., δ18O; Sample code/label; Sample comment; South China Sea; Uvigerina spp., δ13C; Uvigerina spp., δ18O
    Type: Dataset
    Format: text/tab-separated-values, 11028 data points
    Location Call Number Limitation Availability
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    DATA PANGAEA
  • 3
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    (Table T1) Oxygen and carbon isotope ratios of planktic foraminifers from ODP Sites 184-1147 and 184-1148 (2004)
    PANGAEA
    Details
    Publication Date: 2024-01-09
    Keywords: 184-1147A; 184-1147B; 184-1147C; 184-1148A; 184-1148B; Depth, composite; DEPTH, sediment/rock; DRILL; Drilling/drill rig; DSDP/ODP/IODP sample designation; Event label; Globigerinoides ruber, δ13C; Globigerinoides ruber, δ18O; Globigerinoides sacculifer, δ13C; Globigerinoides sacculifer, δ18O; Joides Resolution; Leg184; Mass spectrometer Finnigan MAT 252; Ocean Drilling Program; ODP; Sample code/label; South China Sea
    Type: Dataset
    Format: text/tab-separated-values, 6250 data points
    Location Call Number Limitation Availability
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    DATA PANGAEA
  • 4
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    (Table T4) Age vs. stable isotopes of benthic foraminifers for a spliced core of ODP Sites 184-1147 and 184-1148 (2004)
    PANGAEA
    Details
    Publication Date: 2024-01-09
    Keywords: 184-1147; AGE; COMPCORE; Composite Core; DEPTH, sediment/rock; Foraminifera, benthic δ13C; Foraminifera, benthic δ18O; Joides Resolution; Leg184; Mass spectrometer Finnigan MAT 252; Ocean Drilling Program; ODP; South China Sea
    Type: Dataset
    Format: text/tab-separated-values, 3299 data points
    Location Call Number Limitation Availability
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    DATA PANGAEA
  • 5
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    Stable foraminifer isotope composition and age of ODP Sites 184-1147 and 184-1148, South China Sea (2004)
    PANGAEA
    In:  Supplement to: Cheng, Xinrong; Zhao, Quanhong; Wang, Jiliang; Jian, Zhimin; Xia, Peifen; Huang, Baoqi; Fang, Dianyong; Xu, Jian; Zhou, Zhen; Wang, Pinxian (2004): Data report: Stable isotopes from Sites 1147 and 1148. In: Prell, WL; Wang, P; Blum, P; Rea, DK; Clemens, SC (eds.) Proceedings of the Ocean Drilling Program, Scientific Results, College Station, TX (Ocean Drilling Program), 184, 1-12, https://doi.org/10.2973/odp.proc.sr.184.223.2004
    Details
    Publication Date: 2024-01-09
    Description: Sites 1147 (18°50.11'N, 116°33.28'E; water depth = 3246 m) and 1148 (18°50.17'N, 116°33.94'E; water depth = 3294 m) are located on the lowermost continental slope off southern China near the continent/ocean crust boundary of the South China Sea Basin. Site 1147 is located upslope ~0.45 nmi west of Site 1148. Three advanced piston corer holes at Site 1147 and two extended core barrel holes at Site 1148 were cored and combined into a composite (spliced) stratigraphic section, which provided a relatively continuous profile for the lower Oligocene to Holocene (Wang, Prell, Blum, et al., 2000, doi:10.2973/odp.proc.ir.184.2000; Jian, et al., 2001, doi:10.1007/BF02907088) for studying stratigraphy and paleoceanography. A total of 1047 planktonic foraminifers stable isotope measurements were performed on 975 samples covering the upper 409.58 meters composite depth (mcd) at ~42-cm intervals (Tables T1, T2), and a total of 1864 benthic foraminifers measurements were performed on 1650 samples in the upper 837.11 mcd at ~51-cm intervals (Tables T3, T4). We significantly improved the time resolution of the benthic stable isotope record in the upper 476.68 mcd by reducing the average sample spacing to ~29 cm. This translates into an average sampling resolution of ~16 k.y. for the Miocene sequence and ~8 k.y. for the Pliocene-Holocene interval, assuming a change in sedimentation rates from ~1.8 to ~3.5 cm/k.y., as suggested by shipboard stratigraphy. These data sets provide the basis for upcoming studies to establish an oxygen isotope stratigraphy and examine the Neogene evolution of deep and surface water signatures (temperature, salinity, and nutrients) in the South China Sea.
    Keywords: 184-1147; 184-1147A; 184-1147B; 184-1147C; 184-1148A; 184-1148B; COMPCORE; Composite Core; DRILL; Drilling/drill rig; Joides Resolution; Leg184; Ocean Drilling Program; ODP; South China Sea
    Type: Dataset
    Format: application/zip, 4 datasets
    Location Call Number Limitation Availability
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    DATA PANGAEA
  • 6
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    Depth profile of methanol in site D2 and site D6 in the northwest Pacific Ocean in May 2021 (2023)
    PANGAEA
    Details
    Publication Date: 2024-06-12
    Description: We investigated the seawater methanol abundance in the northwest Pacific Ocean (NWPO) area. Seawater samples were collected during May-June 2021 aboard the R/V “Dongfanghong 3” in the northwest Pacific Ocean. Seawater was sampled using a Seabird 911 CTD-Niskin rosette system equipped with conductivity, temperature and depth sensors. Methanol samples were collected directly without filters and then stored at -80℃ for laboratory analysis. Methanol concentrations were determined by a modified commercial purge and trap system combined with Agilent GC-8890 gas chromatograph with a flame ionization detector. This dataset includes two over 5000m depth profiles of methanol.
    Keywords: Agilent GC-8890 gas chromatograph with a flame ionization detector; air-sea exchange; CTD/Rosette; CTD-RO; DEPTH, water; Dong Fang Hong 3; Event label; Latitude of event; Longitude of event; methanol; Methanol; microbial metabolism; North Pacific Ocean; Northwest Pacific Integrated Research Cruise; Northwest Pacific Ocean; NWPIRC; NWPIRC_D2-1; NWPIRC_D2-2; NWPIRC_D6-1; NWPIRC_D6-2; source and sink
    Type: Dataset
    Format: text/tab-separated-values, 47 data points
    Location Call Number Limitation Availability
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    DATA PANGAEA
  • 7
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    Methane concentration and oxidation rate in the Yangtze River Estuary (July 2021) and East China Sea (April 2021) (2022)
    PANGAEA
    Details
    Publication Date: 2024-06-12
    Description: We investigated the dynamic of methane (CH4) concentration, saturation, and sea-to-air flux in the typical near-shore (Yangtze River Estuary) and outer shelf (East China Sea) areas. We further determined the dynamic of aerobic methanotrophic activity employing in vitro radiotracer assay. The data presented here are beneficial to advancing our understanding for the methane cycle in the estuarine and shelf regions. Water samples were collected from the Yangtze River Estuary and East China Sea aboard the R/V “Runjiang 1 and Zheyuke 2”, “Xiangyang hong 18” during three expeditions in July and March-April 2021. Methane samples were collected directly using a 12 L Niskin bottle deployed on a Seabird 911 CTD rosette system, from which seawater temperature, salinity and depth were recorded. Methane samples in seawater were measured using a cryogenic purge-and-trap setup connected to an Agilent GC-8890 gas chromatograph with a flame ionization detector according to the detailed methods given in (Zhang et al., 2004). We used a radiotracer approach and added 3H-CH4 to seawater samples to determine the methan oxidation (MOx) rate by quantifying 3H-CH4 oxidation to 3H-H2O (Rogener et al., 2020).
    Keywords: A1-1; A1-3; A1-5; A1-7; A1-8; A2-1; A2-3; A2-5; A2-7; A2-8; A3-1; A3-3; A3-5; A3-7; A3-8; A4-1; A4-3; A4-5; A4-7; A4-8; A5-1; A5-2; A5-3; A5-4; A5-5; A5-6; A5-7; A5-8; A6-1; A6-2; A6-3; A6-4; A6-5; A6-6; A6-7; A6-8; A7-1; A7-3; A7-5; A7-7; A7-8; Agilent GC-8890 gas chromatograph with a flame ionization detector; Area/locality; B1; B2; B3; C1; C2; C3; C4; C5; CTD, Sea-Bird, SBE 911; CTD/Rosette; CTD-RO; DATE/TIME; Depth, bathymetric; DEPTH, water; East China Sea; Event label; LATITUDE; LONGITUDE; Methane; methane concentrations; Methane flux; methane oxidation; Methane oxidation rate; Radiotracer; RJ-1_2021; RJ-1_2021_A1-1; RJ-1_2021_A1-3; RJ-1_2021_A1-5; RJ-1_2021_A1-7; RJ-1_2021_A1-8; RJ-1_2021_A2-1; RJ-1_2021_A2-3; RJ-1_2021_A2-5; RJ-1_2021_A2-7; RJ-1_2021_A2-8; RJ-1_2021_A3-1; RJ-1_2021_A3-3; RJ-1_2021_A3-5; RJ-1_2021_A3-7; RJ-1_2021_A3-8; RJ-1_2021_A4-1; RJ-1_2021_A4-3; RJ-1_2021_A4-5; RJ-1_2021_A4-7; RJ-1_2021_A4-8; RJ-1_2021_A7-1; RJ-1_2021_A7-3; RJ-1_2021_A7-5; RJ-1_2021_A7-7; RJ-1_2021_A7-8; RJ-1_2021_B1; RJ-1_2021_B2; RJ-1_2021_B3; RJ-1_2021_C1; RJ-1_2021_C2; RJ-1_2021_C3; RJ-1_2021_C4; RJ-1_2021_C5; Runjiang 1; S02-1; S02-2; S02-3; S02-4; S02-5; S02-6; S02-7; S02-8; S03-1; S03-2; S03-3; S03-4; S03-5; S03-6; S04-1; S04-2; S04-3; S04-4; S04-5; S05-1; S05-2; S05-3; S05-4; S23-1; S23-2; S34-1; S34-2; Salinity; Station label; Temperature, water; Vessel; Xiangyang hong 18; XYH-18_2021; XYH-18_2021_S02-1; XYH-18_2021_S02-2; XYH-18_2021_S02-3; XYH-18_2021_S02-4; XYH-18_2021_S02-5; XYH-18_2021_S02-6; XYH-18_2021_S02-7; XYH-18_2021_S02-8; XYH-18_2021_S03-1; XYH-18_2021_S03-2; XYH-18_2021_S03-3; XYH-18_2021_S03-4; XYH-18_2021_S03-5; XYH-18_2021_S03-6; XYH-18_2021_S04-1; XYH-18_2021_S04-2; XYH-18_2021_S04-3; XYH-18_2021_S04-4; XYH-18_2021_S04-5; XYH-18_2021_S05-1; XYH-18_2021_S05-2; XYH-18_2021_S05-3; XYH-18_2021_S05-4; XYH-18_2021_S23-1; XYH-18_2021_S23-2; XYH-18_2021_S34-1; XYH-18_2021_S34-2; Yangtze River Estuary; Zheyuke 2; ZY-2_2021; ZY-2_2021_A5-1; ZY-2_2021_A5-2; ZY-2_2021_A5-3; ZY-2_2021_A5-4; ZY-2_2021_A5-5; ZY-2_2021_A5-6; ZY-2_2021_A5-7; ZY-2_2021_A5-8; ZY-2_2021_A6-1; ZY-2_2021_A6-2; ZY-2_2021_A6-3; ZY-2_2021_A6-4; ZY-2_2021_A6-5; ZY-2_2021_A6-6; ZY-2_2021_A6-7; ZY-2_2021_A6-8
    Type: Dataset
    Format: text/tab-separated-values, 585 data points
    Location Call Number Limitation Availability
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    DATA PANGAEA
  • 8
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    Methane production in the Yangtze River Estuary and East China Sea in 2019/2020 (2022)
    PANGAEA
    Details
    Publication Date: 2024-06-12
    Description: We investigated the dynamic of methane concentration, saturation, and sea-to-air flux in the typical near-shore (Yangtze River Estuary) and outer shelf (East China Sea) areas. We further determined microbial methane production and the dynamic of aerobic methanotrophic activity employing in vitro radiotracer assay. The data presented here are beneficial to advancing our understanding for the methane cycle in the estuarine and shelf regions. This dataset includes the CH4 production during incubations with additions of methanogenic substrates in nearshore and offshore waters of the Yangtze River Estuary and East China Sea. Water samples of methane production experiments were collected from the Yangtze River Estuary and East China Sea aboard the R/V “Dongfang hong 3”and “Xiangyang hong 18” during two expeditions in December 2019 to January 2020 and May to June 2020. Seawater samples were collected directly using a 12 L Niskin bottle deployed on a Seabird 911 CTD rosette system, from which seawater temperature, salinity and depth were recorded. Methane production culture experiments were conducted in 125 mL acid-washed and sterilized serum vials filled with seawater and methane samples were measured using the headspace method. Each sample was shaken on a vortex mixer for 2 min to equilibrate the gas-liquid prior to gas extraction and 0.1-1 mL subsamples from the headspace were injected into GC-8890 using a gas-tight syringe.
    Keywords: CTD/Rosette; CTD-RO; DFH-3_2019-20; Dong Fang Hong 3; East China Sea; ECS_S2; ECS_S3; ECS_S4; methane concentrations; Methane flux; methane oxidation; P1; P5; S2; S3; S4; Xiangyang hong 18; XYH-18_2020; Yangtze River Estuary; YRE_P1; YRE_P5
    Type: Dataset
    Format: application/vnd.openxmlformats-officedocument.spreadsheetml.sheet, 17.2 kBytes
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    DATA PANGAEA
  • 9
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    Methanol distribution and metabolic rate in the northwest Pacific Ocean in May/June 2021 (2023)
    PANGAEA
    Details
    Publication Date: 2024-06-12
    Description: We investigated the seawater methanol abundance, the dynamic of microbial methanol (MeOH) metabolism and the geochemical parameters in the northwest Pacific Ocean (NWPO) area. Seawater samples were collected during May-June 2021 aboard the R/V “Dongfanghong 3” in the northwest Pacific Ocean. Seawater was sampled using a Seabird 911 CTD-Niskin rosette system equipped with conductivity, temperature and depth sensors. Methanol samples were collected directly without filters and then stored at -80℃ for laboratory analysis. Methanol concentrations were determined by a modified commercial purge and trap system combined with Agilent GC-8890 gas chromatograph with a flame ionization detector. Microbial methanol assimilation and oxidation rates were determined by quantifying 14C-MeOH incorporation into biomass and oxidation to CO2 (Zhuang et al., 2018). Nutrients were measured using Seal Analytical Quaatro nutrient autoanalyzer except for ammonium which was analyzed by a fluorometric method on board (Ning et al., 2013). Chlorophyll-a was measured by fluorometric method (Parsons et al., 1984).
    Keywords: 14C radioactive tracer incubation (Zhuang et al., 2018); Agilent GC-8890 gas chromatograph with a flame ionization detector; air-sea exchange; Ammonium; Chlorophyll a; Continuous Segmented Flow Analyzer, SEAL Analytical, QuAAtro39; CTD, Sea-Bird, SBE 911; CTD/Rosette; CTD-RO; DATE/TIME; Depth, bathymetric; DEPTH, water; Dong Fang Hong 3; Event label; Fluorometric method (Ning et al., 2013); Fluorometric method (Parsons et al., 1984); LATITUDE; LONGITUDE; methanol; Methanol; Methanol, assimilation rate; Methanol, assimilation rate, standard deviation; Methanol, oxidation rate; Methanol, oxidation rate, standard deviation; Methanol, total uptake rate; Methanol, total uptake rate, standard deviation; microbial metabolism; Nitrate; Nitrite; North Pacific Ocean; Northwest Pacific Integrated Research Cruise; Northwest Pacific Ocean; NWPIRC; NWPIRC_D1; NWPIRC_D2-1; NWPIRC_D3; NWPIRC_D4; NWPIRC_D5; NWPIRC_D6-1; NWPIRC_E1; NWPIRC_E10; NWPIRC_E11; NWPIRC_E12; NWPIRC_E2; NWPIRC_E3; NWPIRC_E4; NWPIRC_E5; NWPIRC_E6; NWPIRC_E7; NWPIRC_E8; NWPIRC_E9; Phosphate; Salinity; Ships weather station; Site; source and sink; Temperature, water; Wind speed
    Type: Dataset
    Format: text/tab-separated-values, 248 data points
    Location Call Number Limitation Availability
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    DATA PANGAEA
  • 10
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    Improving crosshole ground‐penetrating radar full‐waveform inversion results by using progressively expanded bandwidths of the data (2021)
    Details
    Publication Date: 2021-07-21
    Description: In the last decade, time‐domain crosshole ground‐penetrating radar full‐waveform inversion has been applied to several different test sites and has improved the resolution and reconstruction of subsurface properties. The full‐waveform inversion requires several diligent executed pre‐processing steps to guarantee a successful inversion and to minimize the risk of being trapped in a local minimum. Thereby, one important aspect is the starting models of the full‐waveform inversion. Generally, adequate starting models need to fulfil the half‐wavelength criterion, which means that the modelled data based on the starting models need to be within half of the wavelength of the measured data in the entire investigation area. Ray‐based approaches can provide such starting models, but in the presence of high contrast layers, such results do not always fulfil this criterion and need to be improved and updated. Therefore, precise and detailed data processing and a good understanding of experimental ground‐penetrating radar data are necessary to avoid erroneous full‐waveform inversion results. Here, we introduce a new approach, which improves the starting model problem and is able to enhance the reconstruction of the subsurface medium properties. The new approach tames the non‐linearity issue caused by high contrast complex media, by applying bandpass filters with different passband ranges during the inversion to the modelled and measured ground‐penetrating radar data. Thereby, these bandpass filters are considered for a certain number of iterations and are progressively expanded to the selected maximum frequency bandwidth. The resulting permittivity full‐waveform inversion model is applied to update the effective source wavelet and is used as an updated starting model in the full‐waveform inversion with the full bandwidth data. This full‐waveform inversion is able to enhance the reconstruction of the permittivity and electrical conductivity results in contrast to the standard full‐waveform inversion results. The new approach has been applied and tested on two synthetic case studies and an experimental data set. The field data were additionally compared with cone penetration test data for validation.
    Keywords: 550.83 ; 2D ; Data processing ; Ground‐penetrating radar ; Inversion
    Type: article
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    CITATION GEO-LEO
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