Development of a new deep-sea hybrid Raman insertion probe and its application to the geochemistry of hydrothermal vent and cold seep fluids

Self Cite

Carbon dioxide emitted from hydrothermal vents, as an important part of the global carbon cycle, can directly affect hydrothermal ecosystems. However, traditional chemical analysis methods cannot directly measure the concentrations of dissolved CO2 in high‐temperature hydrothermal fluids. Although in situ mass spectrometry has been applied to the measurements of deep sea, it cannot be used to detect high‐temperature fluids. In this study, an in situ Raman quantitative method for measuring dissolved CO2 suitable for a hydrothermal environment is established. The Raman relative intensity of CO2 displayed a linear relationship with increasing concentration of CO2 under the investigated conditions (up to 300°C and 40 MPa), allowing this in situ measurement method to be applied to most hydrothermal fields worldwide. Moreover, we find that the quantitative calibration curve for SO42− for high‐temperature and high‐pressure conditions is identical to that of SO42− for room temperature and atmospheric pressure. The concentrations of CO2 in mid‐Okinawa Trough hydrothermal fluids determined by in situ Raman measurement are 188.4–532.3 mmol/kg, which are about 3 times higher than those obtained by traditional sampling methods (59–198 mmol/kg). However, the concentrations of SO42− calculated from in situ Raman spectra were near zero, indicating that the in situ Raman measurement avoids hydrothermal fluids contaminated with seawater.

“…The Sea-Going System-RiP The details of the RiP system have been described in previous papers (Zhang et al, 2017a(Zhang et al, , 2017b. RiP System and Data Processing 3.1.1.…”

Section: Field Deploymentmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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In Situ Quantitative Raman Detection of Dissolved Carbon Dioxide and Sulfate in Deep‐Sea High‐Temperature Hydrothermal Vent Fluids

Zhang

Luan

et al. 2018

Self Cite

“…The authigenic carbonate and associated chemosynthetic communities near the active cold seep vents have also been discovered and reported at this site Feng & Chen, 2015;Lin et al, 2002;Machiyama et al, 2007;Wang et al, 2017;Zhang et al, 2017a). The authigenic carbonate samples and two bathymodiolin mussel species were taken back to laboratory to constrain the fluid sources, intensities of seepage, and to infer the biogeochemical process respectively Feng & Chen, 2015).…”

Section: Geological Settingmentioning

confidence: 81%

In situ Raman Quantitative Detection of the Cold Seep Vents and Fluids in the Chemosynthetic Communities in the South China Sea

Zhang

Luan

et al. 2018

Self Cite

Based on the previously developed deep-sea hybrid Raman insertion probe for cold seeps, the in situ detection of a cold seep vent and geochemistry analysis of fluids in chemosynthetic communities were conducted at the Formosa Ridge in the northern South China Sea. Three different methods were used to measure the components of the fluids erupting from the cold seep vent. The in situ Raman spectra of the cold seep fluids indicated the presence of gaseous CH 4 , C 3 H 8 , and H 2 S. The results indicate that the gases at this site are of biogenic origin; however, the presence of C 3 H 8 suggests that thermogenic methane should not be excluded. The conclusion is also supported by the results of gas chromatography and stable carbon isotope analysis. More significantly, we found that the concentration of SO 4 2À decreases with increasing depth, while the concentrations of CH 4 and S 8 increase in fluids in chemosynthetic communities, but without H 2 S. This finding indicates that the methane is oxidized by sulfate and that elemental sulfur is formed. This process usually occurs in marine sediments as the anaerobic oxidation of methane. Overall, the findings in this work provide a new insight into the geochemical analysis of cold seep fluids and in situ evidence of the oxidation of methane in the chemosynthetic communities near cold seeps.

“…We compile 33 unique data sources that quantitatively identify at least one of the anomalies of interest in the current iteration of the SEAFLEA database (Riedel et al, 2002;Mazurenko & Soloviev, 2003;MIMES, 2004;Levin & Mendoza, 2007;Paull et al, 2007;Sahling et al, 2008;Sellanes et al, 2008;Greinert et al, 2010;Olu et al, 2010;Riedel et al, 2010;Jessen et al, 2011;Batang et al, 2012;Jin et al, 2012;Pierre et al, 2012;Römer et al, 2012;Bowden et al, 2013;Han et al, 2013;Römer et al, 2014;Sahling et al, 2014;Seismic Water Bottom Anomalies Map Gallery, 2014;Skarke et al, 2014;Johnson et al, 2015;Paull et al, 2015;Ruff et al, 2015;Szpak et al, 2015;Åström et al, 2016;Merle & Embley, 2016;Hoshino et al, 2017;Michel et al, 2017;Zhang et al, 2017;Åström et al, 2018;Gafeira et al, 2018;Riedel et al, 2018). The SEAFLEA database is a community effort with multiple individuals and research groups contributing data .…”

Section: Seaflea Distributionmentioning

confidence: 99%

A Global Probabilistic Prediction of Cold Seeps and Associated SEAfloor FLuid Expulsion Anomalies (SEAFLEAs)

Phrampus

Lee

Wood

2020

A newly compiled, open-source database of focused fluid flow sites (e.g., cold seeps) and associated SEAfloor FLuid Expulsion Anomalies (SEAFLEAs) reveals a variable distribution of anomalies across global continental margins. The SEAFLEA distribution is heavily biased toward North American continental margins, with most observations between 100-and 200-m water depth globally, and with an equal distribution between active and passive margins. Using a machine learning classification methodology based on outlier detection algorithms, we predict the probability of encountering a SEAFLEA globally. Results show the highest probability in regions with multiple SEAFLEA observations and parametrically similar regions concentrated on continental margins. In general, geologic, biologic, and chemical predictors are the best predictors of SEAFLEAs. We validate our results using a random and geospatial validation technique that reveals our methods are robust to random variations in observations, but that certain margins, such as the Svalbard Margin, represent parametrically distinct locals. These distinct regions have control over the global distribution of predicted anomalies due to their unique features. Our final prediction on a global 5 × 5 arc minute grid reveals that the average probability of encountering a SEAFLEA is 33.1 ± 17.7% on active margins and 31.2 ± 18.9% on passive margins, showing equal likelihood of encountering fluid expulsion between passive and active margins. Therefore, the lateral compaction on active margins does not increase the likelihood of fluid expulsion relative to the predominantly vertical compaction on passive margins. These results however say nothing of the fluid flux rates or density of expulsion features.