Rare earth elements (REEs) and yttrium (Y), together known as REY, are extremely enriched in deep-sea pelagic sediments, attracting much attention as a promising new REY resource. To understand the influence of hydrothermal processes on the enrichment of REY in deep-sea sediments from the eastern South Pacific Ocean, we conducted detailed lithological, bulk sediment geochemical, and in situ mineral geochemical analyses on gravity core sample S021GC17 from the Yupanqui Basin of eastern South Pacific. The REY-rich muds of S021GC17 are dark-brown to black zeolitic clays with REY contents (ΣREY) ranging from 1057 to 1882 ppm (average 1329 ppm). The REY-rich muds display heavy rare earth elements (HREE) enriched patterns, with obvious depletions in Ce, and positive anomalies of Eu in Post-Archean Australian Shale (PAAS)-normalized REE diagrams. In contrast, the muds of S021GC17 show light rare earth elements (LREE) enriched patterns and positive anomalies of Ce and Eu in the seawater-normalized REE diagrams. Total REY abundances in the core show positive correlations with CaO, P₂O₅, Fe₂O₃, and MnO concentrations. In situ analyses of trace element contents by laser ablation-inductively coupled plasma–mass spectrometry (LA-ICP-MS) demonstrate that bioapatite fossils contain high REY concentrations (998 to 22,497 ppm, average 9123 ppm), indicating that they are the primary carriers of REY. The in situ Nd isotope values of bioapatites are higher than the average values of seawater in Pacific Ocean. Fe–Mn micronodules are divided into hydrogenetic and diagenetic types, which have average REY concentrations of 1586 and 567 ppm, respectively. The high contents of Fe-Mn-Ba-Co-Mo, the positive correlations between ΣREY and Fe-Mn, the ratios of Fe/Ti and Al/(Al + Fe + Mn), and the LREE-enriched patterns in the REY-rich muds, combined with high Nd isotope values shown by bioapatite fossils, strongly indicate that the hydrothermal fluids have played an important role in the formation of the REY-rich sediments in the eastern South Pacific Ocean.

Introduction: Cobalt is the most important critical element in ferromanganese crusts. Co concentration in the Fe-Mn crusts is one of the key parameters for determination of the Co resource. Thus, it is essential to clarify the controls on the variations of Co concentration of ferromanganese crusts.Methods: To clarify the controls on Co concentration of hydrogenetic nonphosphatized ferromanganese crusts, an equation was deduced based on Fick’s First Law: Co(%)=Mn02(%)·Dsw·cswδ·zGR·Ssp, and eight potential controls were gleaned from this equation, including dilution, diffusivity of Co ions in seawater (D_sw), temperature which controls the D_sw, Co ion concentration in seawater (C_sw), the diffusion distance of Co ions near the interface of seawater and Fe-Mn crusts (δ), thickness of one molecular layer (z), growth rate (GR), and specific surface area of Fe-Mn crusts (S_sp). To constrain the value of Co ion diffusion gradients (Csw¯/δ) and consequently verify the proposed equation, we determined the Co concentrations, growth rates, and specific surface area of the outermost layer of Fe-Mn crusts, and calculated diffusivity of Co²⁺.Results: The Csw¯/δ for the Fe-Mn crusts from Caiwei seamount (Magellan seamounts) was determined to be 295-496 pM/mm, which are reasonable for the Co ion concentrations and seawater mixing in the deep ocean.Discussion: According to the equation established in this study, the trend of decreasing Co concentrations in Fe-Mn crusts with increasing water depth is controlled mainly by dilution and to a lesser extent by seawater Co ion concentration, temperature of seawater, and consequently the diffusivity of Co ions in seawater.

Polymetallic nodules (nodules) are a predominant deep-sea mineral resource due to theirenrichment with critical metals, such as Co, Ni, and Cu, and rare earth elements (REEs). The loose and porous nature of nodules contributes to their adsorption and enrichment in trace metals from seawater and pore water. Consequently, the specific surface area (SSA) of nodules is a key factor requiring further study. However, controls on the SSA of nodules with various genetic types remain poorly characterized. This study aimed to investigate controls on nodule SSA by analyzing the transition metals, REEs, mineralogy, and SSA of nodules recovered from basins in the Atlantic, Indian, and Pacific oceans, including the Northwest Pacific Basin (NPB), Bauer Basin (BB), Tiki Basin (TB), Wharton Basin (WB), Central Indian Basin (CIB), and Angola Basin (AB). Nodule SSAs were compared among the various basins by calculating the BET SSA (based on the equation proposed by Brunauer, Emmett, and Teller, 1938). The results suggest thatnodules from the PNB, WB, CIB, and AB are mainly hydrogenetic, and those nodules have a relatively high SSA, high Co, low Ni and Cu, positive Ce anomalies, and low X-ray diffraction (XRD) intensities at ~10 Å. The nodules from the BB and TB are mainly diagenetic in origin, characterized by a relatively low SSA, low Co, high Ni and Cu, negative Ce anomalies, and high XRD intensities at ~10 Å. The SSAs of nodules were significantly positively correlated with Co, δCe, and light REEs (LREEs), and negatively correlated with the XRD intensity at ~10 Å, Ni, and Cu. The SSAs of nodules from the NPB ranged from 329.440 m²/g to 418.711 m²/g, comparable to the SSAs of Co-rich crusts on seamounts. This study proposes that nodule SAA is regulated by nodule genesis and that hydrogenetic nodules have a higher SSA.

The deep-sea camera is the most intuitive and effective detection tool for seabed investigation, and the accuracy of camera positioning can ensure its data value. A bundled ultra-short baseline (USBL) positioning system is generally employed to realize the spatial positioning of an underwater camera. The influence of the underwater acoustic environment and other factors cause USBL positioning data to become unstable, leading to abnormalities, or missing data, which creates difficulties for camera positioning. In order to solve the problem, this paper selects the seabed camera data of the “XunMei” mineralization area acquired from the China south Atlantic voyage. Moreover, the USBL positioning data, combined with high-precision terrain, bathymetry, and ship-borne GPS positioning data, were analyzed and mined comprehensively. In order to eliminate the abnormal data, a four-dimensional anomaly culling model of USBL positioning data is established based on the time and space scales through the ArcGIS tool. Then, modeling, simulation, and interpolation prediction are performed for the positioning data after anomaly elimination to achieve the geographic location correction of the hydrothermal sulfide near-bottom camera and its data. This method has achieved good results in practical applications. The corrected water depth profile of the camera survey line is compatible with the high-precision terrain detected at different times in the same area. The characteristics of the corrected video images are compatible with the sample characteristics of the TV grab sampling position. A set of high-quality positioning data (sampling test 5000 points) not participating in the correction model is compared with the corrected USBL data at the same position. The following results are obtained: in the case of a confidence interval of 95%, the correlation coefficient is 1, the significance is 0, there is no significant difference between the corrected data after the simulation and its original positioning data (not participating in the model), and the correction error is below 5 m. This shows that the problem of locating a submarine camera and its data can be solved using the proposed four-dimensional anomaly elimination model established based on the USBL positioning data, high precision terrain, bathymetry and GPS data, and the corresponding cubic polynomial least-squares correction model.