Fates of vent CO2 and its impact on carbonate chemistry in the shallow-water hydrothermal field offshore Kueishantao Islet, NE Taiwan

Accepted Manuscript Fates of vent CO2 and its impact on carbonate chemistry in the shallow-water hydrothermal field offshore Kueishantao Islet, NE Taiwan

Yu-Shih Lin, Hon-Kit Lui, Jay Lee, Chen-Tung Arthur Chen, George S. Burr, Wen-Chen Chou, Fu-Wen Kuo PII: DOI: Reference:

S0304-4203(18)30257-3 https://doi.org/10.1016/j.marchem.2019.02.002 MARCHE 3632

To appear in:

Marine Chemistry

Received date: Revised date: Accepted date:

9 October 2018 19 January 2019 1 February 2019

Please cite this article as: Y.-S. Lin, H.-K. Lui, J. Lee, et al., Fates of vent CO2 and its impact on carbonate chemistry in the shallow-water hydrothermal field offshore Kueishantao Islet, NE Taiwan, Marine Chemistry, https://doi.org/10.1016/ j.marchem.2019.02.002

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ACCEPTED MANUSCRIPT Fates of vent CO2 and its impact on carbonate chemistry in the shallow-water hydrothermal field offshore Kueishantao Islet, NE Taiwan Yu-Shih Lin1, Hon-Kit Lui2, Jay Lee2, Chen-Tung Arthur Chen1, George S. Burr1, WenChen Chou3, and Fu-Wen Kuo4 Department of Oceanography, National Sun Yat-Sen University, 80424 Kaohsiung, Taiwan.

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Taiwan Ocean Research Institute, National Applied Research Laboratories, 80143 Kaohsiung,

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Taiwan.

Institute of Marine Environment and Ecology, National Taiwan Ocean University, 20224

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Keelung, Taiwan.

National Museum of Marine Biology and Aquarium, 99450 Pingtung, Taiwan.

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Corresponding author: Yu-Shih Lin ([email protected])

ACCEPTED MANUSCRIPT Abstract Increasing public awareness of anthropogenic CO2 emissions and consequent global change has stimulated the development of pragmatic approaches for the study of shallow-water CO2 vents and seeps as natural laboratories of CO2 perturbations. How CO2 propagates from the emission

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sites into surrounding environments (ocean and atmosphere), and its effects on seawater

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carbonate chemistry, have never been studied from a mechanistic perspective. Here, we combine experimental and modeling approaches to investigate the carbonate chemistry of a shallow-water

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hydrothermal field offshore Kueishantao Islet, NE Taiwan. A simple Si-based mixing model is used to trace hydrothermal fluid mixing with seawater along convection pathways. The estimated

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vent fluid component in the near-vent region is generally <1%. We further employed a modified

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bubble-plume model to examine gas bubble-aqueous phase interaction. We explain the dissolved inorganic carbon characteristics of the vertical plume as a synergistic interaction between CO2

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gas dissolution and fluid entrainment. The bubble-plume model provides a conservative estimate

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of the flushing time (tens of minutes) for water in the near-vent region. The acidic, dissolved inorganic carbon-rich water in the lateral buoyant plume readily releases CO2, but mixing with

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seawater rapidly quenches its degassing potential, so that hydrothermal carbon is retained in the

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ocean. Ebullition, governed by initial bubble size distribution, is the key mechanism for vent CO2 to exit the seawater carbonate system. Highlights: 

CO2 dissolution and fluid entrainment shape carbonate chemistry in vertical plumes.

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Fluids in the near-vent area have a short flushing time (tens of minutes).

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Mixing of vent fluids with seawater acts to retain vent carbon in ocean.

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Keywords: Shallow-water hydrothermal field; CO2 vents; carbonate chemistry; bubble-plume

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model

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Introduction

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Most hydrothermal fluids emanating from the axial zone of mid-ocean ridges (Charlou et

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al., 1996, 2000) and subduction zones (Konno et al., 2006; Lupton et al., 2006) are CO2-rich and acidic. Carbon dioxide vents and seeps provide natural laboratories to understand the ecosystem

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impacts by CO2 perturbations in the ocean (e.g., Hall-Spencer et al., 2008) and the possible

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consequences of CO2 leakage from seafloor capture and storage sites (IEA Greenhouse Gas R&D Programme, 2008). Although natural CO2 vents and seeps differ in many respects from

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anthropogenic CO2 sources (Barry et al., 2010; Tyler, 2003), these modern examples of

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prolonged CO2 exposure are arguably the best study sites available to elucidate chronic CO2

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perturbation effects on natural aquatic environments (Andersson et al., 2015). Carbonate system parameters—including pH, dissolved inorganic carbon (DIC), total

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alkalinity (TA), and the partial pressure of CO2 (pCO2) of seawater—are needed to constrain the effects of CO2 perturbations. In shallow-water CO2 seeps, carbonate system parameters of the plume area can be monitored to classify habitats (Hall-Spencer et al., 2008) or to assess spatiotemporal variability of water chemistry in response to hydrodynamic conditions (Agostini et al., 2018; Kerrison et al., 2011). In estuarine environments, carbonate chemistry is often combined with conservative tracers to isolate non-mixing processes (e.g., Cai et al., 2004; Huang et al., 2012). To our knowledge, such an approach has not been applied to shallow-water

ACCEPTED MANUSCRIPT hydrothermal fields, which are technically more challenging than estuaries on two counts. First, although shallow hydrothermal fluids have endmember compositions distinct from seawater, reliable tracers of physical mixing between emitted fluids and seawater in the plume area are rare. This is due in part to non-conservative behavior of hydrothermally enriched constituents

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(e.g., dissolved iron), or low resolving power of common conservative tracers. For example, an

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increase from 0 to 1% of a “zero-Mg” hydrothermal component only decreases plume water Mg

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from 52.70 (mean seawater level) to 52.17 mmol/kg. 3He, the most widely employed conservative tracer for the study of deep-sea hydrothermal plumes (e.g., Fitzsimmons et al., 2017;

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Lupton et al., 1980), is not an ideal tracer for aqueous mixing in shallow-water hydrothermal

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plumes because of two-phase flow (see below). So far, dissolved silica is the only tracer that has been used effectively to determine the distribution of hydrothermal components in convection

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cells above shallow-water seeps (Pichler et al., 1999). Second, shallow water depths (<200 m)

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result in two-phase flow, i.e., discrete gas bubble streams that discharge along with hot fluids. A one-phase mixing model may not suffice to explain a shallow hydrothermal plume system,

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particularly one rich in CO2.

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The Kueishantao Islet (121°57’ E, 24°50’ N; Fig. 1), located at the extensional

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conjunction between Taiwan and the southern rifting end of the Okinawa Trough, has been volcanically active for at least 7 kyrs (Chen et al., 2001). The shelf off the south coast of the islet is dotted by >30 shallow-water chimneys over an area of 500,000 m2 (Chen et al., 2005). The venting activity was much more focused and turbulent than the seeping activities reported previously for other shallow-water CO2 seeps, such as that off Ischia (Hall-Spencer et al., 2008). The emanated fluids impart color to the surrounding surface waters, easily identifiable in satellite images (Fig. 1a). The vent gas, possessing a strong mantle component (Yang et al., 2005), is

ACCEPTED MANUSCRIPT comprised of >90 % CO2 (Chen et al., 2005). The geochemistry of the region has been wellstudied (e.g., Chen et al., 2016; Hung et al., 2018). The pH of the hydrothermal plumes ranges from 5.4 to 8.0 (total hydrogen ion concentration scale), and has been mapped by both discrete measurements (Yang et al., 2012) and pH sensors (Han et al., 2014). In-situ observational studies

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of low-pH stress on benthic fauna have been reported (e.g., Chen et al., 2015), but an in-depth

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examination of carbonate chemistry in the plume water has never been carried out. Here we discuss the processes that govern carbonate chemistry in the Kueishantao

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hydrothermal plume. We collected hydrographic data from the hydrothermal field to characterize the carbonate chemistry of the vent fluids and plume waters. We use observational and analytical

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results as constraints for mathematical models to explore the underlying mechanisms controlling

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mixing, gas sparging, and degassing. Our results show that gas bubbling plays a key role in governing carbonate chemistry of the vertical plumes, whereas mixing of hydrothermal fluids

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Site description

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Material and Methods

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with seawater controls the carbonate system in the lateral buoyant plume.

We sampled from two transects in the coastal region of the Kueishantao Islet (Fig. 1). Transect M includes the hydrothermal “White Vent” (WV; 10 m water depth) towards the nearshore, and extends eastward to the offshore station (site M1230) at a water depth of 58 m (Table S1, Figure 1b). Along Transect M there are two series of near-vent stations: (1) My, in the plume of “Yellow Vent” (YV; 7 m water depth), and (2) Mw, in the plume of WV. In this paper,

ACCEPTED MANUSCRIPT the term “near-vent” is used to refer to the region within 20 m of the vents. Transect B starts at the nearshore station B0 along the north coast of the islet, and follows a north-south path (Figure 1b). Transect B serves as a baseline to constrain the nearshore-offshore chemical gradient with minimal hydrothermal influence. The number after the alphabetical site code gives the horizontal

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distance from the nearshore end. The nearshore sites are: B0 for Transect B, My0 for the My

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series, and Mw0 for Transect M and the Mw series. Cruises and shipboard measurements

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Data collection and sampling were undertaken during two cruises (Table S1): OR2-2095

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(17‒18 May 2015) on the RV Ocean Researcher II, and one cruise that utilized fishing boats (25‒28 May 2015). During the cruise OR2-2095, wind speed data were recorded by a

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meteorological observation system, vertical profiles of water temperature and salinity were

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acquired by a conductivity, temperature, and depth probe, and current data were collected by a shipboard acoustic Doppler current profiler. Atmospheric pCO2 was monitored by an underway

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pCO2 system (Model AS-P2; Apollo SciTech LLC). Tidal level data were obtained from the

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nearby Wushi tidal station (Figs. 1a; data from the Central Weather Bureau of Taiwan). Bubbling

Sampling

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activity of the vents was filmed by divers using a waterproof digital camcorder.

Vent samples and near-vent waters were taken by scuba divers (Table S1). A thermocouple was used to determine the temperature within the vents and in the surface water. The flow rates of vent fluids were measured with a digital flow meter (Model 438-110; Hydro Bios). Vent fluids were collected by inserting a polytetrafluoroethylene tube into the chimneys, linked via a polytetrafluoroethylene valve to a pre-evacuated glass bottle. Fluids at the orifice or

ACCEPTED MANUSCRIPT in the near-vent area were retrieved by Niskin or glass bottles. To avoid confusion, the terms “YV” and “WV” refer to samples taken within the vents, whereas codes such as “My0” and “Mw0” represent samples taken in the vertical plumes (Table S1). The majority of water samples of Transects M and B were taken by a peristaltic pump or Niskin bottles. For stations at deeper

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water depths (M1230, B700 and B1560), water samples were taken by a Rosette water sampler

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fitted with twelve 20-L Niskin bottles. Except for samples from the near-vent Mw series, all vent

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and plume samples were retrieved during the flood phase (Table S1).

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Fluid samples were split into aliquots onboard. Samples for carbonate chemistry were transferred to glass containers, and nutrient samples were transferred into plastic containers. All

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samples were poisoned with a saturated mercury chloride (HgCl2) solution at a volume ratio of

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1000:1 and stored at 4°C in the dark until analysis.

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Analytical procedures

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pH was measured at 25±0.05°C (pH25) by a pH meter (ORION 3 STAR; Thermo Fisher Scientific). Seawater Tris (pH=8.089) and AMP (pH=6.786) buffer solutions, both prepared at a

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practical salinity of 35, were used to calibrate the pH electrode. The Certificated Reference

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Material seawater prepared by the Scripps Institution of Oceanography was used to check the precision (better than ±0.003 pH unit) and accuracy. All pH data were reported in the total hydrogen ion concentration scale. For comparison with modeling results, the pH25 values were converted to in-situ pH (pHin situ) using the CO2SYS algorithm (Pierrot et al., 2006; http://cdiac.ornl.gov/ftp/co2sys/) using the modeled temperature and in-situ pressure. We used the carbonic dissociation constants reported in Lueker et al. (2000), and included measured dissolved silica (Si(OH)4) and soluble reactive phosphate concentrations in our calculations. TA

ACCEPTED MANUSCRIPT (precision ±0.3%) was measured by a total alkalinity titrator (Model AS-ALK2; Apollo SciTech Inc.) and DIC (±0.1%) with a DIC analyzer (Model AS-C3; Apollo SciTech Inc.). Si(OH)4 (±2% at 5 μmol/L) was measured by the silicomolybdenum blue method (adapted from Fanning & Pilson, 1973, with a flow injection analyzer, as described by Pai et al. (1990)). Soluble reactive

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Riley, 1962; Pai et al., 1990) with a flow injection analyzer.

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phosphate (±3% at 0.1 μmol/L) was measured by the molybdenum blue method (Murphy and

Bubble-plume model

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A well-established bubble-plume model (McGinnis et al., 2004; Wüest et al., 1992) was

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employed to study the influence of bubbles, vent fluid and ambient water on carbonate chemistry in the vertical plume and near-vent water. The theory, assumptions and equations of the bubble-

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plume model have been detailed in Wüest et al (1992), who used it to describe the behavior of

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artificially generated O2, or air-bubble plumes in lakes (see review of McGinnis et al., 2004). The model was later adapted to simulate CO2 seeps on the continental shelf (McGinnis et al.,

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2011). Although our environmental conditions do not fully comply with model assumptions (see

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discussion below), we chose this model because of its straightforward solution procedure (Wüest et al., 1992; see Table 1 for flux variables and equations, and Table S2 for notation), which

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allowed us to incorporate the CO2SYS algorithm for computation of DIC, TA and pH. The combination is useful heuristically to understand the effect of CO2-dominant gas bubbles on carbonate chemistry in a shallow marine environment. A set of constitutive equations to describe seawater density and gas solubility as a function of temperature and salinity is provided in Table S3. In our model, CO2 transferred from gas bubbles was allowed to equilibrate with a coexisting parcel of water and undergo speciation.

ACCEPTED MANUSCRIPT The transferred CO2 was first pooled into DIC, instead of dissolved CO2. We then input DIC and TA, the latter being unaffected by CO2 dissolution, into the COS2SYS program (Pierrot et al., 2006) to compute the equilibrated dissolved CO2, which was used in the next round of the gas transfer algorithm. Without the speciation step, the dissolved CO2 concentration could be

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overestimated, resulting in underestimation of CO2 gas that could be transferred from bubbles to

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solution in the next iteration, and overestimation of CO2-related density change. To properly

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simulate the dynamics of rising bubbles, we also included other major vent gas components, such as N2, O2, CH4 and H2S (Chen et al., 2016), into the model. CO2SYS outputs equilibrium pHin situ

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and pCO2, which were compared to measured values and input into a degassing algorithm. We

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allowed the top water layer to degas according to an air-sea CO2 flux equation (Wanninkhof, 1992). The gas exchange coefficient was evaluated using the measured average wind speed and

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modeled sea-surface temperature (see Table S3 for the equation). Aside from dissolution and

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speciation, other chemical reactions (e.g., oxidation) were not included in the model because of

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the lack of rate data from field observations. Some plume variables and initial conditions were based on field observations and

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measurements (Table 2). We used average surface water compositions at M1230 and B1560 to

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represent the endmember of initial ambient seawater, and the measured composition of YV and WV to stand for the endmember of vent fluids. Taking advantage of the well-characterized chemistry in the near-vent region, we further coupled the plume model to an ambient water model. The basic equations for the coupling are conservation of water mass and conservation of scalar species (Wüest et al., 1992; Table S4). The temperature and salinity of the upper 20 m water column at site M1230 were used as initial values. For simplicity, we assumed Type 1 plumes (Socolofsky et al., 2002), i.e., plumes that debouch fluid in a surface jet radial to the

ACCEPTED MANUSCRIPT ambient water. We ran the simulations by alternating between plume waters and ambient waters over a short time interval, with one compartment supplying the other with the required input variables. For example, the concentration of solute i of the plume water (Ci; Table 1) was used to compute that of the ambient water (Ci,a; Table S4), which was then used to compute Ci in the

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next iteration. Such an approach, originally described in Wüest et al (1992), allowed us to

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introduce the temporal dimension into our model. In reality, the near-vent environment is not

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closed and exchanges fluid with waters further away from the plume; its chemistry is the product of dynamic equilibria between hydrothermal fluids and seawater. Therefore, the time scale

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provided by the model represents a conservative estimate of the time that a parcel of ambient

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water should remain near a vent in order to acquire near-vent water properties.

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The model was implemented using the software package MATLAB® (version R2014a). Preliminary model runs showed that three gas-related parameters—gas input flux, initial bubble

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radius, and initial CO2 proportion in the bubbles—largely control the shape of solute profiles. As

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the last parameter is well constrained (Chen et al., 2005, 2016), a Monte Carlo approach was employed to determine values for the other two parameters, and to estimate uncertainties. Gas

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input was randomly varied in the range of 0.005 to 0.12 m3/s, and initial bubble size from 1 to 25

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mm. These ranges were based on (1) values that resulted in a reasonable (eyeball) fit to the data during trial runs, (2) maintenance of a gas input flux that did not exceed 80% of the total input flux, and (3) rough estimates of bubble size according to video images. For either vent, a total of 1000 permutations were performed to find the best fits combinations, evaluated using average r2 values for modeled versus measured concentrations of Si(OH)4, DIC, TA and pHin situ. The model gave higher average r2 values for the WV plume than for the YV plume, making it difficult to apply a common threshold for selecting draws. Therefore, we ranked the results in decreasing

ACCEPTED MANUSCRIPT order of average r2 value and selected the top 5%. These have average r2 values of 0.75‒0.79 for the WV plume and 0.51‒0.52 for the YV plume. The sensitivity of carbonate chemistry to the aforementioned gas-related parameters was simulated. The range of input values tested in the sensitivity runs was 0‒0.11 m3/s for gas input

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flux, 1‒25 mm for initial bubble diameter, and 0.05‒0.75 for initial proportion of CO2 in the

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bubbles. The sensitivity tests modeled the WV vertical plume, and terminated after ~4000 s of mixing with ambient seawater. This simulation duration was based on the optimization results

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described above.

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Mixing-degassing model

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In the lateral buoyant plume, the carbonate chemistry is affected by two physical processes: fluid mixing and air-sea exchange. To assess how these processes contribute to our

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observational data, we developed a straightforward mixing-degassing model. The degassing

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algorithm was the same as that used in the bubble-plume model (Table S3), with the measured value of 399 μatm as the local atmospheric pCO2. Other factors that contribute to air-sea

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exchange, such as current shear, were not considered. To simulate physical mixing, we assumed

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a simple dilution process, in which a parcel (1 m thick) of plume-top water undergoes stepwise dilution by background seawater with a constant dilution factor in each iteration. The initial plume-top water was defined using the average surface-water composition of sites Mw0 and My0, with background seawater defined by site B0. The dilution factor was estimated from the plume-top fluid component (PF) using the Si(OH)4 data (binary mixing model), the horizontal distance (d) between the plume top and the distal site M1230 (1230 m), and the current velocity

ACCEPTED MANUSCRIPT (ω). Assuming that the horizontal volume transport is unidirectional with constant velocity, the dilution factor (DF) can be expressed as: DF = (PFM1230 / PFplume-top)ω/d

(1)

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Using mean current velocity during the flooding phase (0.155 m/s) yielded a DF of

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0.99955 s−1 for Transect M. Lower current velocities, as during slack tides, slow down mixing,

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with ω = 0 m/s (DF = 1 s−1) eventually switching off the mixing function in the model. A wind velocity (v) of 0 m/s results in zero gas transfer velocity (kwa in Table S3). In each iteration, the

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carbonate system parameters of the mixture were computed using the CO2SYS algorithm, the

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wind speed and difference between the calculated seawater pCO2 and atmospheric pCO2 values used to calculate the CO2 flux to the atmosphere, and the carbonate system parameters of the

Results

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Hydrographic conditions

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degassed water computed again before the next round of mixing.

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The upper 20 m water column at site M1230 was rather homogeneous (mean temperature, 22.4°C; mean salinity, 34.5). The surface currents exhibited contrasting flow patterns over tidal cycles. During ebbing (Fig. 1c), the currents flowed west/northwestward with a mean velocity of 0.39 m/s. During flooding, the currents flowed east/southeastward (Fig. 1d) at 0.14−0.17 m/s off the south and north coasts, and at 0.30 m/s off the east coast. Our reconstructed flow patterns are consistent with buoy data (Chang et al., 2000). Northerly winds prevailed during our survey period, with an average wind speed of 2.8 m/s.

ACCEPTED MANUSCRIPT Fluid temperatures were 116°C at YV, 58°C at WV, and 24‒25°C in the surface water of sites My0 and Mw0. The hydrothermal fluids vented at flow rates of 29‒177 cm/s. Video footage of the vents are available at http://doi.org/10.5446/32347 (YV) and http://doi.org/10.5446/32348 (WV).

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Chemistry of the vent fluids and vertical plumes

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The YV fluid had a DIC concentration of 2452 μmol/kg, a pH25 value of 2.88, and a calculated TA content of ‒1327 μmol/kg (Figs. 2a and 2c; Table S5). The WV fluid was less

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acidic (pH25 = 4.51) and had measurable TA (131 μmol/kg; Figs. 2b and 2d). Because of the high

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DIC content (4337 μmol/kg) and low buffering capacity of CO2, the WV fluid had a pCO2 value ~0.07 atm higher than that of YV (Table S5). At the orifice, the fluids became distinctly more

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alkaline than the vent fluids, showing elevated TA and pH. The lowest DIC concentrations at

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both My0 (2405 μmol/kg) and Mw0 (2082 μmol/kg) occurred above the orifice at water depths of 5 and 10 m, respectively. At site Mw0, this minimum DIC coincides with maximum TA and

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pH25 values, but no such relationship was observed at site My0. The DIC profile at My0 is

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notable in that it had two depths (0 m and at the orifice) with DIC levels exceeding that of YV by

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400‒500 μmol/kg.

Vent fluids were substantially enriched in Si(OH)4 (YV, 112 μmol/kg; WV, 489 μmol/kg) compared to typical surface seawater (Figs. 2c and 2d). During their ascent, the Si(OH)4 concentrations decreased 3‒8 fold at the orifice and remained low in the vertical plume (7‒15 μmol/kg). At both My0 and Mw0, the minimum DIC corresponded to the lowest Si(OH)4 concentration. Chemistry of the near-vent waters

ACCEPTED MANUSCRIPT Selected carbonate system parameters and Si(OH)4 in the near-vent waters are displayed in Fig. 3. These transects represent composite snapshots of a highly dynamic system. The major difference between the My and Mw series is the spatial distribution of the two major water masses, the plume water (in warm-toned color) and near-vent ambient water (in cool-toned

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color). In Transect My, the water masses could be distinguished laterally based on the horizontal

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distance from site My0 (Fig. 3a), whereas in Transect Mw they showed a zonal distribution (Fig.

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3b). The transect characteristics are attributed to timing of sampling (Table S1). Transect My has a NE-SW orientation that does not appear to have captured the main buoyant plume, which tends

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to spread southeastward to the open ocean during flooding. In contrast, ebb tide conditions favor

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accumulation of plume water along the south coast (Figs. 1a and 1c), explaining the two-layer feature observed in Transect Mw. Vent fluids also exhibit higher temperatures during ebb tide

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(Chen et al., 2005), favoring vertical stratification in the near-vent water. Site My20 was affected

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by another plume, proximal to the WV vent field (Fig. 1b).

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These two transects have several features in common. First, DIC and Si(OH)4 exhibited similar spatial distributions along each transect. Second, DIC and TA distributions did not follow

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a common trend, especially in water with elevated plume components (e.g., at 0 m of site

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Mw14). Lastly, chemical properties of near-vent ambient waters differed from distal waters at station M1230 (Table S2), and the nearshore stations of Transect B (sites B0 to B20; DIC = 1966±3 μmol/kg; TA = 2279±17 μmol/kg; pH25 = 8.04±0.01; Si(OH)4 = 2.6±0.3 μmol/kg). The most significant difference was in TA, which was at least 50 μmol/kg lower in the near-vent waters compared to the above-mentioned reference sites. Simulated profiles of the vertical plumes and near-vent waters

ACCEPTED MANUSCRIPT Table 2 lists best-fit values of gas input flux and initial bubble radius, and Fig. 4 shows the simulated profiles for the WV and YV plumes, based on fitted values. The near-vent ambient waters for both plumes were simulated, but those for YV are not shown due to large discrepancies between model outputs and observations, in accord with our interpretation that

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Transect My did not capture the main buoyant plume (cf. Chemistry of the near-vent waters).

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The simulations for WV and its near-vent ambient water were obtained with a gas input flux of

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0.106±0.009 m3/s, an initial bubble radius of 5.5±1.6 mm, and an initial CO2 fraction of 50%

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(Figa. 4a to 4f).

The simulated profiles have the following features: (1) Modeled plume Si(OH)4 contents

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decrease steeply upward and fit the measured values well, but failed to reproduce the observed

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minimum value at ~10 m (Fig. 4c). (2) Model-generated plume DIC curves reach their lowest value at ~10 m and increase in concentration with shoaling depth (Figs. 4d), in overall agreement

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with the observational data. (3) Simulated near-vent Si(OH)4 and DIC profiles both exhibit high

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concentrations in the surface and low concentrations at the bottom, and fit the measured values well. (4) Modeled TA and pHin situ values of the plume and near-vent waters substantially exceed

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the observational values (Figs. 4e and 4f). Simulated profiles of YV plume water (gas input flux

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= 0.070±0.025 m3/s; initial bubble radius = 3.1±0.7 mm; initial CO2 fraction = 80 %; Figs. 4g to 4l) share the same basic features as the modeled WV plume water, but the high Si(OH)4 concentration observed at the surface of the YV plume could not be reproduced in the model (Fig. 4i). In the sensitivity tests (Figs. 5a to 5c), all model runs produced Si(OH)4 and TA profiles comparable to those of Fig. 4 (data not shown), but the DIC profiles of the plume varied substantially. Within the range of input values, low gas input fluxes (<0.06 m3/s), large initial

ACCEPTED MANUSCRIPT bubble diameters (25 mm) and low initial CO2 fractions in bubbles (<0.25) resulted in concave up DIC profiles with a plume-top DIC concentration of ~ 2 mmol/kg, whereas a gas input flux of 0.06−0.11 m3/s, an initial bubble diameter of 1−5.5 mm and a high initial fraction of CO2 (0.25−0.75) in bubbles generated a concentration minimum at ~10 m and higher plume-top DIC

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levels (2.5‒3.5 mmol/kg). The pHin situ profiles all showed an exponential increase with shoaling

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depth, with low values corresponding to high DIC at the plume top (data not shown). Chemistry of the lateral buoyant plume

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Carbonate system parameters versus Si(OH)4 concentration for the lateral buoyant plume

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are shown in Fig. 6. Compared with Transect B, the buoyant plume showed elevated DIC and acidity, and lowered TA, in plume water as far as 700 m from the vents (Table S5). The high

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DIC/TA ratio results in low buffering capacity and high surface water pCO2, which decreased

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from 10,000−50,000 μatm in the near-vent area, to 7,000−21,000 μatm in the region between sites M40 and M700, and to ~330 μatm at the distal site M1230. The surface water of site M300

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deviates from the general trend with distance, and its Si(OH)4 concentration is comparable to that

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of sites My0 and Mw0 (Table S5). In Fig. 6, M300 plots closer to the two plume-top sites than to the other buoyant plume stations. Therefore, site M300 is considered as a plume top of an

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offshore vent. DIC and TA showed excellent linear relationships with Si(OH)4 for other buoyant plume stations, whereas pH25 varied non-linearly with Si(OH)4 as expected from the logarithmic pH scale. pCO2 also showed a non-linear decreasing trend with Si(OH4). Simulated distribution of DIC in the lateral buoyant plumes Simulated DIC concentrations in the buoyant plumes under selected mixing and degassing conditions are displayed in Fig. 7a. Degassing caused a nearly linear decrease in

ACCEPTED MANUSCRIPT plume-water DIC with transport distance, and the decrease was proportional to wind velocity (Fig. 7a). Physical mixing is much more efficient than degassing in lowering the DIC content, as the decrease is exponential. Physical mixing is weakly influenced by wind (up to 10 m/s). Curves created under mixing conditions fit broadly with the observational DIC data, but the near-vent

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data display substantial scatter, implying either varying levels of mixing and/or degassing.

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Discussion

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Hydrothermal convection and mixing

The near-vent Si(OH)4 distribution in Transect Mw (Fig. 3) reflects hydrothermal

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circulation set up by focused fluid discharge (Campbell & Gieskes, 1984; Pichler et al., 1999):

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the low-density hydrothermal fluid is ejected into the surface ocean and spreads outwards, while bottom water flows in to replace water entrained in the hydrothermal plume. Following the

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approach of Pichler et al. (1999), we used Si(OH)4 to quantify the hydrothermal component (fHT)

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in the plumes and near-vent waters using the mass balance equation: (2)

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SiPNW = fHT SiHT + (1− fHT) SiBKG

where SiPNW, SiHT, and SiBKG denote the Si(OH)4 concentration of the plume and near-vent water, the hydrothermal endmember, and the background seawater, respectively. Pichler et al. (1999) used the Si(OH)4 concentration of pristine hydrothermal fluids, based on an assumption of zero Mg, to represent SiHT. For our study site, the reported Si(OH)4 concentration of the pristine hydrothermal fluid is 1.28‒1.34 mmol/kg (Chen et al., 2017), and the SiBKG is 2.7 μmol/kg (average surface-water value of M1230 and B1560). We obtained fHT values (“Scenario I” in

ACCEPTED MANUSCRIPT Table S5) of <1%, except for the fluid collected at the WV orifice (13.5%). Our estimates are comparable to those reported in Pichler et al. (1999). Chen et al. (2017) pointed out that the assumption of a zero-Mg pristine hydrothermal endmember remains speculative for the Kueishantao hydrothermal field, and Mg-rich pristine

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hydrothermal fluids are known to exist at other hydrothermal fields (e.g., Gamo et al., 1997). To account for this possibility, we used measured vent-fluid Si(OH)4 concentrations as an

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alternative SiHT. The resulting fHT values remained low (3.7−11.5% for Series My and 0.3−35.6%

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for Series Mw; “Scenario II” in Table S5), indicating substantial dilution of vent fluids by

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seawater in the vertical plume and near-vent region.

Scenario II fHT values were used to assess the effect of aqueous mixing on carbonate

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chemistry. The results show that compared to model predictions, the vertical plume and near-

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vent water are relatively enriched in DIC and protons, and depleted in TA (data not shown). The deviation indicates the presence of other processes that govern carbonate chemistry, as discussed

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next.

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Gas transfer process in the vertical plumes

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Modeled Si(OH)4 plume water profiles (Fig. 4) reflect the dilution of vent fluids during fluid entrainment. The dilution was strongest above the orifice and diminished upward, due to the growing size of the plume body at shallower depths (a “top hat” plume geometry; Wüest et al., 1992). Such an effect is also visible in simulated profiles of plume temperature (data not shown) and TA. The plume DIC profiles are intriguing exceptions and show a marked change in curvature with depth. Detailed examination of the DIC profiles in the model suggests that they were created by synergistic interactions between gas dissolution and fluid entrainment. The

ACCEPTED MANUSCRIPT plume was capable of maintaining a strong CO2 flux from bubbles to the aqueous phase (positive and high KCO2pCO2 – CCO2 values; see dDi/dz in Table 1) throughout the whole depth. This condition was met because of the high CO2 fraction in the bubbles (Figs. 4b and 4h) and low CO2(aq) after speciation. Consequently, DIC showed a concentration excess relative to that

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governed by mixing alone. At the lower part of the plume, where entrainment-induced dilution

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was strong, excess DIC had negligible effects on the profile shape. With shoaling depth and a

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mitigated dilution effect, excess DIC started to exert its influence. In the near-vent region, excess DIC entered the upper water column when the plume debouched at the sea surface, and

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propagated slowly downward. This resulted in decreased DIC concentrations with depth. This is

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also observed in the near-vent WV Si profile (Fig. 4c), but it is the excess DIC that steepens the concentration gradient. After numerous iterations, the plume was surrounded by water with a

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increasing DIC concentration trend.

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DIC gradient, and repeated entrainment of this near-vent water resulted in an eventual upward-

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The sensitivity of the simulated DIC profiles to gas-related parameters (Figs. 5a to 5c) also supports the foregoing interpretation. Conditions favoring gas dissolution and buildup of

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excess DIC, such as a higher gas input flux, a smaller initial bubble radius, or a higher initial

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proportion of CO2 in the bubbles, are all conducive to the formation of profiles with distinct curvature, whereas the reverse drives the DIC curves toward a shape similar to the Si(OH)4 profiles. Since natural CO2 venting is temporally variable (Chen et al., 2005), the DIC distribution in vertical plumes is subject to change from one sampling campaign to another. The model indicates that the proportion of vent CO2 emitted to the atmosphere is also sensitive to initial bubble radius and, to a lesser extent, to gas input flux (Fig. 5d). Up to 90% of vent CO2 could be kept in the ocean with an initial bubble radius of 1 mm, whereas larger bubbles can

ACCEPTED MANUSCRIPT transport most of the CO2 directly to the atmosphere. Based on Monte Carlo simulations, atmospheric CO2 emission via ebullition is as high as 65±9% (WV site) and 62±13% (YV site). These values should be interpreted with caution, as the bubble-plume model can only simulate a single bubble size at one time, whereas bubbles at natural vents likely cover a range of diameters.

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Discrepancies between the bubble-plume model and observations

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One of two major discrepancies between the model results and observations is the mismatch in TA and pHin situ. This implies that the acidity provided by dissociated carbonic acid

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was not sufficient to explain the proton surplus in the plume and near-vent waters. To reconcile

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the disparity between Si(OH)4-DIC and TA-pH, additional sources of acidity are required. Multiple processes in the vertical plumes could generate the necessary protons (Table S6). For

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example, the vent gas contained HCl (up to 49 ppm) and SO2 (up to 271 ppm; Yang et al., 2005),

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both precursors of mineral acids. Plume waters are also enriched in reduced sulfur, which could undergo abiotic and biological sulfur oxidation to release protons (see review of Pokorna &

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Zabranska, 2015). The presence of sulfur-oxidizing bacteria in the plume water has been

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confirmed by microbiological studies (Tang et al., 2013; Zhang et al., 2012). In addition, oxidation-precipitation reactions involving dissolved manganese and iron (up to 23 and 177

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μmol/L, respectively, in the vent fluids; Chen et al., 2005) also supply protons. Further field studies could be conducted to confirm which of these reaction best account for the TA and pHin situ

mismatch between our model results and observations. The other discrepancy is seen in some measured Si(OH)4 and DIC values that could not

be explained by the smooth simulated curves. This feature is likely caused by temporally variable bubble and fluid fluxes over short time scales, of seconds to minutes. Such behavior is

ACCEPTED MANUSCRIPT evident in the video footage of the YV plume. If the fluid is released intermittently or has highly variable flux, ambient waters may intrude between pulses of vent fluids into the vertical plume and create zones with low hydrothermal components. If the release of bubbles is highly variable, the entrainment factor, which is dependent on bubble size and gas flux (Seol et al., 2007), could

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also vary, thereby changing the extent of dilution. As the model was originally developed to

simulation capability in its current form.

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Constraint on the flushing time for the near-vent region

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describe artificial bubble plumes (Wüest et al., 1992), variability in fluxes is beyond its

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The overall similarity between the model and the Si(OH)4 and DIC profiles argues for its applicability to natural CO2 vents. The profiles represent a suite of transient states between

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steady states established by the flow over a period of time (Socolofsky et al., 2002), which, in

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our case, was at least 67±19 min for the WV plume and 57±13 min for the YV plume. This time scale estimate has implications for the dynamics of the hydrothermal field. On the one hand,

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judging from the unsheltered topography of the vent sites and their proximity to the main path of

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the Kuroshio Current, one might presume that the hydrothermal fluids are rapidly flushed away. Our work shows however that the flushing is not as efficient as expected, otherwise no chemical

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anomalies in the near-vent would be observed. Instead, the flushing time (cf. Monsen et al. (2002) for definition) for the water within the small near-vent region is at least tens of minutes. On the other hand, a short flushing time in the near-vent region appears to prohibit the development of a standing planktonic community. This is clearly at odds with published studies on the planktonic prokaryotes (Tang et al., 2013; Zhang et al., 2012), with distinct communities dominated by chemolithoautotrophs, i.e., microbes not typically found in the surface ocean. This apparent

ACCEPTED MANUSCRIPT contradiction warrants further study, taking into account time constraints based on water movement. Mixing and degassing in the buoyant plume

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Field observations and modeling results both indicate that the plume top water is enriched

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in DIC relative to the vent fluids. The distinction is important for understanding the mixing

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processes in the buoyant plume. All buoyant plume data deviate from binary mixing trajectories between the vent fluids and background seawater (Fig. 6). Instead, they dot the region defined by

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mixing lines of background seawater to the three plume top sites (My0, Mw0 and M300), and

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suggest that the CO2-sparged fluids are the pertinent hydrothermal endmembers.

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The mixing-degassing model suggests that for Transect M, physical mixing between plume fluids and background seawater is the dominant mechanism in lowering surface seawater

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DIC concentrations (Fig 7a), but near-vent samples deviate from the general mixing trend. Such

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deviations are not observed in the DIC-Si(OH)4 plot (Fig. 7b). Because Si(OH)4 concentration is not affected by degassing, these data suggest the influence of vortices that facilitate

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heterogeneous DIC distributions with distance from the vents. This interpretation agrees with

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Han et al. (2014), who identified vortices using temperature measurements. Vortices would also prolong water residence times in the near-vent region, but the degassing effect on DIC is easily obscured by mixing, as demonstrated by the temporal evolution of the CO2 flux (Fig. 7c). In the presence of mixing, the degassing potential was efficiently quenched by two orders of magnitude within the first 50−100 min, coincident with the estimated flushing time of water in the near-vent region (cf. Constraint on the flushing time for the near-vent region). By the time the simulated plume water approaches the chemical composition of site M1230 (155−165 min), the proportion

ACCEPTED MANUSCRIPT of plume CO2 that has escaped to the atmosphere amounts to 1.4−18% of the original plume-top DIC (assuming no mixing), but drops to 0.2−3.5% with mixing (Fig. 7d). In other words, mixing acts to retain plume DIC in the ocean via the relatively high buffering capacity of background seawater. The rapidly suppressed degassing potential of plume water underlines the importance

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of ebullition, which in turn is governed by initial bubble size distribution, as the key mechanism

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for vent CO2 to exit the seawater carbonate system.

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Conclusions

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This study combined experimental and modeling approaches to explore the main

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processes controlling the propagation of CO2 and carbonate chemistry in the Kueishantao shallow-water hydrothermal field. The Si-based mixing model suggests substantial dilution of

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the discharged fluids in the vertical plume and near-vent region, but fails to explain the carbonate

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chemistry. With the help of a bubble-plume model, we suggest that DIC profiles of the vertical plumes can be understood as a synergistic interaction between CO2 gas dissolution and fluid

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entrainment. We also demonstrated how initial bubble radius governs CO2 emission to the

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atmosphere, and provided a conservative estimate of the flushing time (tens of minutes) for water in the near-vent region. The CO2-sparged plume-top water was found to be a better endmember than the vent fluids, to explain mixing process in the buoyant plume. The acidic, DIC-rich plume water has a propensity to release CO2, but mixing with surrounding seawater quickly quenches its degassing potential and acts to retain hydrothermal carbon in the ocean. Ebullition, governed by initial bubble size distribution, is the key mechanism for vent CO2 to exit the seawater carbonate system.

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Appendix. Alphabetical list of abbreviations AMP - (2-aminopyride) buffer used for pH measurements

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DF - dilution factor

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DIS - dissolved inorganic sulfide

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Mw - code of the sites near WV My - code of the sites near YV

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pCO2 - partial pressure of CO2

pH25 - pH value at 25 °C and 1 atmosphere

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PF - plume-top fluid component

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pHin situ - pH value at in situ temperature and pressure

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TA - total alkalinity

Tris - (2-amino-2-hydroxymethyl-propane-1,3-diol) buffer used for pH measurements

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WV - white vent

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YV - yellow vent

Acknowledgments

We thank the expert support of Seawatch Co. during the cruises to the Kueishantao Islet. We also thank the captains and crews of the FV Jin-Ling-Da-Fa, FV Sheng-Yu-Man, FV HongYi-Fu, and RV Ocean Researcher II for their competent work. We thank the Marine Research Station, Institute of Cellular and Organismic Biology, Academia Sinica for providing lab space for sample processing, the National Space Organization, National Applied Research Laboratories

ACCEPTED MANUSCRIPT for providing the satellite image, and the Office of Library and Information Services, National Sun Yat-Sen University for providing the computing facility. We are grateful to Bing-Jye Wang for generating most of the chemical data discussed in this study, and Yu-Nung Nina Lin for helping with parallel computing using MATLAB. We thank Ai-Lin Lyu for logistic support, and

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Jung-Tai Lu, Ruei-Long Guo, Ya-Ling Guo, Kuang-Ting Hsiao and Ya-Fang Cheng for their

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hard work in the field. We thank the editor and two anonymous reviewers for their constructive

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comments. This work was financed by the Ministry of Science and Technology to YSL [Grant # 104-2611-M-110-013, 104-2911-1-110-507-MY2 and 105-2611-M-110-015] and the “Aim for

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the Top” University Program of Taiwan. Experimental data are available in the Supplementary

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Material. Computer codes and calculated data can be obtained upon request to the corresponding

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author.

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Author Contributions

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Y.S.L. designed the experiments, Y.S.L., H.K.L. and J.L. performed numerical modeling, Y.S.L., C.T.A. and G.S.B. wrote the manuscript, W.C.C. and F.W.K. performed research, and all authors

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reviewed and approved the manuscript.

Conflict of Interest

The authors declare that they have no conflict of interest.

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Seol, D.G., Bhaumik, T., Bergmann, C., Socolofsky, S.A., M.ASCE, 2007. Particle image velocimetry measurements of the mean flow characteristics in a bubble plume. J. Engin. Mech. 133, 665–676. https://doi.org/10.1061/(ASCE)0733-9399(2007)133:6(665). Socolofsky, S.A., Crounse, B.C., Adams, E.E., 2002. Multi-phase plumes in uniform, stratified and flowing environments, in: Shen, K., Cheng, A., Wang, K.H., Teng, M.H., Lin, C. (Eds.), Environmental Fluid Mechanics—Theories and Applications. ASCE/Fluids Committee, Reston, VA, pp. 84–125. Tang, K., Liu, K., Jiao, N., Zhang, Y., Chen, C.T.A., 2013. Functional metagenomics investigations of microbial communities in a shallow-sea hydrothermal system. PLoS One 8, e72958. https://doi.org/10.1371/journal.pone.0072958. Tyler, P.A., 2003. Disposal in the deep sea: analogue of nature or faux ami? Environ. Conserv. 30, 26–39. https://doi.org/10.1017/S037689290300002X. UNESCO, 1981. Background papers and supporting data on the International Equation of State of Seawater 1980. UNESCO Technical Papers in Marine Science, No. 38. United Nations Educational, Place de Fontenoy, Paris. http://unesdoc.unesco.org/images/0004/000479/047932eb.pdf. Wanninkhof, R., 1992. Relationship between wind speed and gas exchange over the ocean. J. Geophys. Res. Oceans 97, C5, 7373–7382. https://doi.org/10.1029/92JC00188. Weiss, R.F., 1970. The solubility of nitrogen, oxygen and argon in water and seawater. Deep Sea Res. Oceanogr. Abstr. 17, 721–735. https://doi.org/10.1016/0011-7471(70)90037-9. Weiss, R.F., 1974. Carbon dioxide in water and seawater: the solubility of a non-ideal gas. Mar. Chem. 2, 203–215. https://doi.org/10.1016/0304-4203(74)90015-2. Wüest, A., Brooks, N.H., Imboden, D.M., 1992. Bubble plume modeling for lake restoration. Water Resour. Res. 28, 3235–3250. https://doi.org/10.1029/92WR01681. Yamamoto, S., Alcauskas, J.B., Crozier, T.E., 1976. Solubility of methane in distilled water and seawater. J. Chem. Engin. Data 21, 78–80. https://doi.org/10.1021/je60068a029. Yang, L., Hong, H., Guo, W., Chen, C.T.A., Pan, P.I., Feng, C.C., 2012. Absorption and fluorescence of dissolved organic matter in submarine hydrothermal vents off NE Taiwan. Mar. Chem. 128–129, 64–71. https://doi.org/10.1016/j.marchem.2011.10.003. Yang, T.F., Lan, T.F., Lee, H.F., Fu, C.C., Chuang, P.C., Lo, C.H., Chen, C.H., Chen, C.T.A., Lee, C.S., 2005. Gas compositions and helium isotopic ratios of fluid samples around Kueishantao, NE offshore Taiwan and its tectonic implications. Geochem. J. 39, 469– 480. http://doi.org/10.2343/geochemj.39.469. Zhang, Y., Zhao, Z., Chen, C.T.A., Tang, K., Su, J., Jiao, N., 2012. Sulfur metabolizing microbes dominate microbial communities in andesite-hosted shallow-water hydrothermal systems. PLoS One 7, e44593. http://doi.org/10.1371/journal.pone.0044593.

ACCEPTED MANUSCRIPT Figure Captions Figure 1. (a) Location map and satellite image of Kuishantao Islet. The islet is located offshore NE Taiwan. The shallow-water hydrothermal activity creates a surface seawater color change that is visible in a satellite image, taken at 10 AM, May 18, 2015 (ebbing phase). Image

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sources: National Space Organization and Google® Map (inset). (b) Bathymetric and site map;

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depth contours in m. The inset shows the distribution of sampling sites near the vents. Mw

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and My both include three sites, with a horizontal distance of 6 (sites Mw6 and My6), 14

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(Mw14 and My14) and 20 (Mw20 and My20) m from the vents. (c) and (d): Surface (8.3 m) currents in the vicinity of Kueishantao Islet during the ebbing and flooding phases. The data

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were compiled from three tidal cycles during May 17−18, 2015. The thick gray lines denote

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trajectories of the research vessel. The currents along the coast, determined via buoys (Chang et al., 2000), are also plotted (dash arrows) for comparison. Note that Chang et al. (2000) did

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not provide the velocity scale of coastal currents.

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Figure 2. Vertical distribution of carbonate system parameters and dissolved silica in the hydrothermal fluids and vertical plumes of the (a, c) YV plus My0 and (b, d) WV plus Mw0.

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The gray lines designate depth of the orifice. The TA values marked with * were obtained

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using the CO2SYS algorithm (Pierrot et al., 2006). Figure 3. Near-vent distribution of DIC, TA, pH25, and Si(OH)4 across Series (a) My and (b) Mw.

Figure 4. Model profiles for (a to f) the bubble plumes and near-vent (NV) ambient waters of WV and (g to l) the YV bubble plumes. Results are presented as the means (lines) and standard errors (shaded areas) of the best fits from Monte Carlo simulations. Profiles of nearvent ambient waters of YV were not displayed due to great discrepancies between model

ACCEPTED MANUSCRIPT results and observations, which were attributed to the failure of Series My to capture the main buoyant plume. The red and blue dots designate the measured values for the plume and nearvent ambient waters, respectively. The error bars represent the range of values from the three near-vent sites (Mw6, Mw14 and Mw20). (a) to (f): gas input flux, 0.106±0.009 m3 s−1; initial

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bubble diameter, 5.5±1.6 mm; iteration time step, 1 s; simulated duration, 4032±1140 s. (g) to

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(l): gas input flux, 0.070±0.025 m3 s−1; initial bubble diameter, 3.1±0.7 mm; iteration time

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step, 1 s; simulated duration, 3426±777 s.

Figure 5. Distribution of DIC in the vertical plume of WV as a function of (a) gas input flux (in

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m3 s−1), (b) initial bubble diameter (in mm), and (c) initial fraction of CO2 in bubbles. The

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mean of best fits displayed in Figure 4d is plotted as the thick line. (d) Percentage of vent CO2 emitted to the atmosphere as a function of initial fraction of CO2 in bubbles (fCO2), gas input

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flux (Q), and initial bubble diameter (r). The simulation duration was 4032 s for all runs.

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Figure 6. (a) DIC, (b) TA, (c) pH25, and (d) pCO2 versus Si(OH)4 in the surface water (0 and 5 m water depth) of Transect B and the buoyant plume. In (c) and (d), the mixing lines to YV, WV

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and three plume tops (Mw0, My0 and M300) were calculated using the CO2SYS algorithm

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with the input of end-member DIC and TA values. Figure 7. Results of the mixing-degassing model (v = wind speed). The measured data are the

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surface (water depth = 0 m) samples of the buoyant plume. Panel (d) summarizes the percentage of plume DIC emitted to the atmosphere in the form of CO2 by the time the plume water approaches the chemical composition of site M1230.

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Table 1. Flux variables and the respective differential equations of the bubble-plume model. Variable Water volume flux

Formula μ = πb2w

Momentum flux

M = πb2w2

Differential equation dμ 2 (π )1⁄2 d 2 d a p 2μ d p

FT = μT

Salinity flux

FS = μS

Dissolved species flux

Di = μCi i = Si(OH)4, DIC, TA, CO2 (output from CO2SYS), N2, O2, CH4, DISa, H2S

Undissolved gas flux

Gi = πb2 2(w+wb)mi i = CO2, N2, O2, CH4, H2S

(1

2

)

p

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M ED PT CE

μ2

d T 2 (π )1⁄2 a d d S 2 (π )1⁄2 a a d d i 2 (π )1⁄2 i,a i TA d d i 4π 2 2 (π )1⁄2 i,a ( ) ( ⁄μ ) b d μ (i, j) = (Si(OH)4, Si(OH)4), (DIC, CO2), (N2, N2), (O2, O2), (CH4, CH4), (DIS, H2S) d i 4π 2 i ( i i ) ( ⁄μ ) b d μ i = CO2, N2, O2, CH4, H2S

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w

DIS = dissolved inorganic sulfide.

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a.

w

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Temperature flux

a

ACCEPTED MANUSCRIPT Table 2. Plume variables and the initial conditions. WV 10.5 0.4

YV 8 0.25

Unit m m

Initial velocity of plume water Gas input flux

w

0.29

1.77

m/s

Q

0.106±0.009

0.070±0.025

m3/s

Initial bubble radius

r

5.5±1.6

3.1±0.7

mm

0.15 0.8

0.12 0.8

unitless unitless

Adjusted to fit the profiles; best fits from Monte Carlo simulations Adjusted to fit the profiles; best fits from Monte Carlo simulations Calculated based on Seol et al. (2007) Wüest et al. (1992)

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Entrainment factor Plume diameter ratio

Note Measured; water depth at the orifice Approximate estimate based on underwater video Measured

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Symbol z b

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Variable Depth Initial plume radius

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Highlights:

CO2 dissolution and fluid entrainment shape carbonate chemistry in vertical plumes.

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Fluids in the near-vent area have a short flushing time (tens of minutes).

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Mixing of vent fluids with seawater acts to retain vent carbon in ocean.

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M

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

Figure 1

Figure 2

Figure 3

Figure 4

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Figure 6

Figure 7