A data processing method for MAPR hydrothermal plume turbidity data and its application in the Precious Stone Mountain hydrothermal field

Hydrothermal plume is an important constituent of seabed hydrothermal circulation and is also one of the characteristics of active hydrothermal vents. Portable Miniature Autonomous Plume Recorders （MAPR） attached to a towed deep-sea instrument was used to search for hydrothermal plumes and hydrothermal vents. We introduced the basic principle of MAPR based on deep towing technology to detect plumes, then analyzed the factors affecting the quality of the MAPR data and presented a data correction method for MAPR, including instrument location correction, noise reduction processing, system error elimination and seawater background reduction. Finally we applied the method to analyze MAPR data obtained during the Chinese DY115-21 cruise on R/VDayang Iin the “Precious Stone Mountain” hydrothermal field on the Gala-pagos Microplate. The results provided a better understanding of the distribution of the hydrothermal activ-ity in this field, indicating the presence of a new hydrothermal vent.

A Lagrangian Particle Random Walk Model for Simulating A Deep-Sea Hydrothermal Plume with both Buoyant and Non-Buoyant Features

This paper presents a computational model of simulating a deep-sea hydrothermal plume based on a Lagrangian particle random walk algorithm. This model achieves the efficient process to calculate a numerical plume developed in a fluid-advected environment with the characteristics such as significant filament intermittency and significant plume meander due to flow variation with both time and location. Especially, this model addresses both non-buoyant and buoyant features of a deep-sea hydrothermal plume in three dimensions, which significantly challenge a strategy for tracing the deep-sea hydrothermal plume and localizing its source. This paper also systematically discusses stochastic initial and boundary conditions that are critical to generate a proper numerical plume. The developed model is a powerful tool to evaluate and optimize strategies for the tracking of a deep-sea hydrothermal plume via an autonomous underwater vehicle （AUV）.

Utilizing ^(234)Th/^(238)U disequilibrium to constrain particle dynamics in hydrothermal plumes in the Southwest Indian Ocean

Metal-enriched minerals have been widely observed near hydrothermal vent fields.However,the dynamics of particulate metals influenced by hydrothermal activities is poorly constrained.Here,radioactive 234Th in both dissolved and particulate phases were used to examine the kinetics of particle-reactive metal adsorption,removal,and residence in a newly found hydrothermal plume over the Southwest Indian Ridge.The results showed a relatively low value on ^(234)Th/^(238)U ratios(i.e.,0.73-0.88)compared to the deep oceans,indicating an enhanced adsorption of particle-reactive metals onto particulate matter in the plume.Based on the 234Th-238U disequilibria,the adsorption and sinking rate constants of 234Th averaged(0.009±0.001)d^(-1) and(0.113±0.024)d^(-1) in the hydrothermal plume,corresponding to the residence times of(115±19)d and(16±5)d for dissolved and particulate 234Th,respectively.This timescale allows vent-discharged particle-reactive metals to disperse hundreds to thousands of miles away.Thus,hydrothermal activities might influence the metal distribution in deep ocean over a very large scope.Also,a high sinking flux of(36.2±5.4)B q/(m^(2)·d)for 234Th was observed for the plume,suggesting an enrichment of metal in particles deposited close to the vent.The enhancement of particle sinking could also benefit the transport of organic carbon and nitrogen and fuel the benthic ecosystems under the plume regimes.Thus,hydrothermal plumes may have an impact on both the elemental geochemistry and/or ecosystem to the deep oceans interior than previous expectation.