The Surface Ocean Aerosol Production (SOAP) voyage took place on the NIWA RV Tangaroa over the biologically productive frontal waters of Chatham Rise (44∘ S, 174–181∘ E), east of New Zealand in the southwest Pacific Ocean. The 23-day voyage took place during the austral summer in February–March 2012. The scientific aim was to investigate interactions between the ocean and atmosphere, and as such the measurement programme included comprehensive characterisation of ocean biogeochemistry, measurement of ocean–atmosphere gas and particle fluxes, and measurement of distribution and composition of trace gases and aerosols in the marine boundary layer (MBL) (Law et al., 2017). During the voyage, NASA MODIS ocean colour images and underway sensors were used to identify and map phytoplankton blooms. Three blooms were intensively targeted for measurement: (1) a dinoflagellate bloom with elevated Chl a, DMSsw and pCO2 drawdown, and high irradiance (bloom 1 – B1); (2) a coccolithophore bloom (bloom 2 – B2); and (3) a mixed community bloom of coccolithophores, flagellates, and dinoflagellates sampled before (bloom 3a – B3a) and after (bloom 3b – B3b) a storm. For further voyage and measurement details, see Law et al. (2017).

A high-sensitivity proton transfer reaction mass spectrometer (PTR-MS) (Ionicon Analytik) was used to measure DMS, acetone and methanethiol. The PTR-MS sampled from a 25 m 3/8 in. i.d. PFA (perfluoroalkoxy) inlet line, which drew air from the crow's nest of the vessel 28 m above sea level (a.s.l.) at 10 L min-1. A baseline switch based on relative wind speed and direction was employed to minimise flow of ship exhaust down the inlet (see Lawson et al., 2015).

The PTR-MS instrument parameters were as follows: inlet and drift tube temperature of 60 ∘C, a 600 V drift tube and 2.2 mbar drift tube pressure (E / N = 133 Td, townsend). The O2 signal was < 1 % of the primary ion H3O+ signal. DMS, acetone and MeSH were measured at m/z 63, m/z 59 and m/z 49, respectively, with a dwell time of 10 s. From day-of-year (DOY) 43–49, 19 selected ions including m/z 59 and m/z 63 were measured, resulting in 17 mass scans per hour; however, from DOY 49 the PTR-MS measured in scan mode from m/z 21 to 155, allowing three full mass scans per hour. As such, MeSH measurements (m/z 49) were made only from DOY 49 onward.

VOC-free air was generated using a platinum-coated glass wool catalyst heated to 350 ∘C; four times per day this air was used to measure the background signal resulting from interference ions and outgassing of materials. An interpolated background signal was used for background correction. Calibrations of DMS and acetone were carried out daily by diluting calibration gas into VOC-free ambient air (Galbally et al., 2007). Calibration gases used were a custom ∼ 1 ppm VOC mixture in nitrogen containing DMS and acetone (Scott Specialty Gases) and a custom ∼ 1 ppm VOC calibration mixture in nitrogen containing acetone (Apel Riemer). The calibration gas accuracy was ±5 %. A calibration gas for MeSH was not available during this voyage. The PTR-MS response to a given compound is dependent on the chemical ionisation reaction rate, defined by the collision rate constant and the mass dependent transmission of ions through the mass spectrometer. Given the similarity of the MeSH and DMS collision rate constants (Williams et al., 1998) and the very similar transmission efficiencies of m/z 63 and m/z 49, we applied the empirically derived PTR-MS response factor for DMS (m/z 63) to the MeSH signal at m/z 49. The instrument response to DMS and acetone varied by 2 % and 5 % throughout the voyage, respectively.

In this work m/z 59 is assumed to be dominated by acetone. Propanal could also contribute to m/z 59, although studies suggest that this signal is likely low (Beale et al., 2013; Yang et al., 2014a). Similarly, m/z 49 has been attributed to MeSH, based on a literature review (Feilberg et al., 2010; Sun et al., 2016), and a lack of likely other contributing species at m/z 49 in the MBL. As such m/z 59 and m/z 49 represent an upper limit for acetone and MeSH, respectively.

The minimum detectable limit for a single 10 s measurement of a selected mass was determined using the principles of ISO 6879 (ISO, 1995). Average detection limits for the entire voyage were as follows: m/z 59 (acetone), 24 ppt; m/z 63 (DMS), 22 ppt; and m/z 49 (MeSH), 10 ppt. The percentages of 10 s observations above detection limits were as follows: m/z 59, 100 %; m/z 63, 98 %; and m/z 49, 63 %. Inlet losses were determined to be < 2 % for isoprene, monoterpenes, methanol and DMS. Acetone and MeSH losses were not determined during the voyage; however, acetone inlet losses were tested previously using a parts-per-billion level mixture of calibration gases with PFA inlet tubing and found to be < 5 %. MeSH has a similar structure and physical properties to DMS at pH < 10 (Sect. 3.2), and so inlet losses are likely to be similar. These small (< 5 %) losses could lead to a small underestimation in reported mixing ratios of DMSa, acetonea and MeSHa.

During the SOAP voyage, DMSa measurements were made using three independently calibrated instruments: atmospheric pressure ionisation chemical ionisation mass spectrometer (mesoCIMS) from the University of California Irvine (UCI) (Bell et al., 2013, 2015), an Ionicon PTR-MS operated by the Commonwealth Scientific and Industrial Research Organisation (CSIRO) (Lawson et al., 2015) and a HP gas chromatograph with sulfur chemiluminescence detector (GC-SCD) operated by the National Institute of Water and Atmospheric Research (NIWA) (Walker et al., 2016).

Details of the mesoCIMS and GC-SCD measurement systems are provided by Bell et al. (2015) and Walker et al. (2016) with a brief description provided here. The mesoCIMS instrument (Bell et al., 2013) ionises DMS to DMS-H+; m/z=63) by atmospheric pressure proton transfer from H3O+ by passing a heated air stream over a radioactive nickel foil (Ni-63). The mesoCIMS drew air from the eddy covariance set-up on the bow mast at approximately 12 m a.s.l. The inlet was a 1/2 in. i.d. PFA tube with a total inlet length of 19 m and a turbulent flow at 90 slpm (standard litres per minute). The mesoCIMS subsampled from the inlet at 1 L m-1. A gaseous tri-deuterated DMS standard (D3-DMS) was added to the air sample stream at the entrance to the inlet. The internal standard was ionised and monitored continuously in the mass spectrometer at m/z=66, and the atmospheric DMS mixing ratio was computed from the measured 63/66 ratio. The internal standard was delivered from a high-pressure aluminium cylinder and calibrated against a DMS permeation tube prior to and after the cruise (Bell et al., 2015).

The GC-SCD system included a semiautomated purge and trap system, a HP 6850 gas chromatograph with cryogenic pre-concentrator and thermal desorber, and sulfur chemiluminescence detection (Walker et al., 2016). The system was employed during the voyage for discrete DMS seawater measurements and gradient flux measurement bag samples (Smith et al., 2018). The system was calibrated using an internal methylethylsulfide (MES) permeation tube and external DMS permeation tube located in a Dynacalibrator^® with a twice daily five-point calibration and a running standard every 12 samples (Walker et al., 2016).

A DMS measurement intercomparison between the mesoCIMS, GC-SCD and PTR-MS was performed during the voyage on DOY 64 and DOY 65. Tedlar bags (70 L) with blackout polythene covers were filled with air containing DMS at sub-parts-per-billion levels, and they were sequentially distributed between all instruments for analysis within a few hours. On DOY 64, two bags were prepared including ambient air filled from the foredeck and a DMS standard prepared using a permeation device (Dynacalibrator) and dried compressed air (DMS range 384–420 ppt from permeation uncertainty). On DOY 65, two additional bags were prepared including one ambient air sample from the foredeck with tri-deuterated DMS added and a DMS standard prepared using the Dynacalibrator and dried compressed air (DMS range 331–363 ppt). MesoCIMS values are not available for DOY 64 due to pressure differences between bag and instrument calibration measurements; this was resolved by using an internal standard on DOY 65. For those analyses, the mesoCIMS and PTR-MS measured DMS at m/z 63 and tri-deuterated DMS at m/z 66, while the GC-SCD measured both DMS and deuterated DMS as a single peak.

Continuous seawater measurements were obtained from surface water sampled by an intake in the vessel's bow at a depth of ∼ 7 m during the SOAP voyage and included underway temperature and salinity (Sea-Bird thermosalinograph SBE-21), underway chlorophyll a (Chl a) and backscatter (Wetlabs (Sea-Bird) ECOtriplet), and dissolved DMS (DMSsw) (miniCIMS) (Bell et al., 2015). Quenching obscured the Chl a signal during daylight when irradiance was > 50 W m-2.

The following parameters were measured in surface waters (depths 2–10 m) in discrete samples from Niskin bottles on a conductivity–temperature–depth (CTD) rosette: nutrients according to methods described in Law et al. (2011), particulate nitrogen concentration (Nodder et al., 2016), phytoplankton speciation, groups and numbers (optical microscopy of samples preserved in Lugol's solution) (Safi et al., 2007), and flow cytometry (Hall and Safi, 2001). In addition, the organic parameters measured included high-molecular-weight (HMW) reducing sugars (Somogyi, 1926, 1952; for details see Burrell, 2015), DMSP (Walker et al., 2016) and CDOM measured using a liquid waveguide capillary cell (Gall et al., 2013). See Table S1 for measurement specifications and Law et al. (2017) for further details and results for these parameters.

This section describes a comparison of DMSa measurements from bag samples of ambient air and DMS standard mixtures (analysed by GC-SCD, PTR-MS and mesoCIMS; see Sect. 2), as well as comparison of ambient DMSa measurements (PTR-MS and mesoCIMS).

Atmospheric mixing ratios of MeSHa, DMSa and acetonea are shown along the voyage track in Fig. 3 with bloom locations highlighted. Figure 4 shows a time series of MeSHa, DMSa, acetonea and MeSHa / DMSa (all measured with PTR-MS), as well as DMSsw (miniCIMS) from Bell et al. (2015), Chl a, irradiance, wind speed, wind direction, and sea and air temperature. Note that MeSHa measurements started on DOY 49 (the last day of bloom B1). The fraction of backward trajectories arriving at the ship that had been in contact with land masses in the previous 10 days is also shown with a value of 0 indicating no contact with land masses in the preceding 10 days. This was calculated using the Lagrangian Numerical Atmospheric-dispersion Modelling Environment (NAME) for the lower atmosphere (0–100 m) as time-integrated particle density (g s m-3), every 3 h from the ship location (Jones et al., 2007) as shown in Law et al. (2017). Where air contacted land masses, this was the New Zealand land mass in almost all cases.

MeSHa ranged from below detection limit (< 10 ppt) to 65 ppt, DMSa ranged from below detection limit (∼ 22 ppt) up to 957 ppt, and acetonea ranged from 50 to 1500 ppt (Table 2). The ratio of MeSHa to DMSa ranged from 0.03 to 0.36 (mean 0.14) for measurements when both were above the minimum detectable limit. Periods of elevated DMSa generally correspond to periods of elevated DMSsw. Both DMSa and DMSsw were very high during B1, during the transect to B2, and the first half of B2 occupation. MeSHa variability broadly correlates with DMSa and DMSsw, with highest levels during B2 (no data available for B1). The highest acetonea levels observed occur during B2, and a broad acetone peak during B1 of 700 ppt (∼ DOY 49) overlaps with but is slightly offset from the largest DMSa peak during the voyage (∼ 957 ppt). DMSa, acetonea and MeSHa were somewhat lower during B3a and lowest during B3b (the post-storm part of that bloom B3) (see Law et al., 2017). In general, DMSa levels during B1 were at the upper range of those found in prior studies elsewhere (Lana et al., 2011; Law et al., 2017). MeSHa levels during B2 ranged from below detection limit (∼ 10 ppt) up to 65 ppt (mean 25 ppt), which is substantially higher than the only comparable measurements from the Drake Passage and the coastal and inshore waters west of the Antarctic Peninsula (3.6 ppt) (Berresheim, 1987). The average acetonea levels during this study were broadly comparable to those from similar latitudes reported in the South Atlantic and Southern Ocean (Williams et al., 2010) and at Cape Grim (Galbally et al., 2007). Acetonea during SOAP was generally lower than at similar latitudes at Mace Head (Lewis et al., 2005), the southern Indian Ocean (Colomb et al., 2009) and also the marine subtopics (Read et al., 2012; Schlundt et al., 2017; Warneke and de Gouw, 2001; Williams et al., 2004).

There were two occasions when elevated acetonea corresponded closely to an increased land influence – during B1 on DOY 48–49 (maximum land influence 12 %) and DOY 60 (maximum land influence 20 %) (Fig. 4). Both these periods corresponded to winds from the north, and back trajectories show that the land mass contacted was the southern tip of New Zealand's North Island (including the city of Wellington and the northern section of the South Island in both cases). The acetone measured during these periods may have been emitted from anthropogenic and biogenic sources as well as from photochemical oxidation of hydrocarbon precursors (Fischer et al., 2012). The acetone enhancement relative to the degree of land influence was higher on DOY 48–49 than DOY 60 possibly due to different degrees of dilution of the terrestrial plume or different terrestrial source strengths.

The period with the highest acetone levels during B2 (1508 ppt) corresponds with a period of negligible land influence (0.3 %), indicating a non-terrestrial, possibly local, source of acetonea. Neither MeSHa nor DMSa maxima corresponded with peaks in land influence, except for the latter part of the DMSa maximum on DOY 48–49; however, the source of DMSa during DOY 48–49 is attributed to local ocean emissions as shown by strong association between DMSsw and DMSa during this period (Fig. 4).

Correlations of DMSa, MeSHa and acetonea were examined to identify possible common marine sources or processes influencing atmospheric levels (Table 3). Only data above the minimum detectable limit were included in the regressions. Acetonea data likely influenced by terrestrial sources (DOY 48–49 and 60, described above) were removed from this analysis. A moderate correlation (R2=0.5, p<0.0001) was found between DMSa and MeSHa during B2 with a correlation of R2=0.3, (p<0.0001) between DMSa and MeSHa for all data (Fig. 5). During B2 the slope was 0.13 (MeSHa roughly 13 % of the DMSa mixing ratios), while for all data the slope was 0.07 (including blooms and transiting between blooms).

MeSHsw and DMSsw are produced from bacterial catabolism of DMSP via two competing processes, so the amount of DMSsw vs. MeSHsw produced from DMSP will depend on the relative importance of these two pathways at any given time. Additional sources of DMSsw, such as phytoplankton that cleave DMSP into DMS, will also influence the amount of DMSsw vs. MeSHsw produced. A phytoplankton-mediated source of DMSsw was likely to be an important contributor to the DMSsw pool during the SOAP voyage, either through indirect processes (zooplankton grazing, viral lysis and senescence) or direct processes (algal DMSP-lyase activity) (Lizotte et al., 2017). The relative loss rates of DMSsw and MeSHsw through oxidation, bacterial uptake or reaction with DOM will also influence the amount of each gas available to transfer to the atmosphere, with MeSHsw having a much faster loss rate in seawater than DMSsw (Kiene and Linn, 2000; Kiene et al., 2000). Differences between the gas transfer velocities of DMS and MeSH would also affect the atmospheric mixing ratios. Such differences are likely to be small, due to similar solubilities (Sander, 2015) and diffusivities (Johnson, 2010). A final factor that will influence the slope of DMSa vs. MeSHa is the atmospheric lifetime (Table 2). The average lifetimes of DMSa and MeSHa in this study are estimated at 24 and 9 h, respectively, with respect to OH, calculated using DMS reaction rate of OH from Berresheim et al. (1987), the MeSH reaction rate from Atkinson et al. (1997) and OH concentration calculated as described in Lawson et al. (2015). Hence, the correlation between DMSa and MeSHa reflects the common seawater source of both gases, while the differing slopes between B2 and all data probably reflect the different sources and atmospheric lifetimes. While a correlation between MeSH and DMS has been observed in seawater samples previously (Kettle et al., 2001; Kiene et al., 2017), to our knowledge this is the first time that a correlation between MeSHa and DMSa has been observed in the atmosphere over the remote ocean.

There were several weak (R2≤0.2) but significant correlations between DMSa and acetonea and acetonea and MeSHa (Table 3). The correlation of acetonea with DMSa may reflect elevated organic sources for photochemical production of acetone in regions of high dissolved sulfur species. A further discussion of drivers of DMSa, acetonea and MeSHa mixing ratios is provided in Sect. 3.3.

An additional factor which may influence the measured mixing ratios of DMSa, MeSHa and acetonea is entrainment of air from the free troposphere into the MBL. For short-lived DMS and MeSH (Table 2), free tropospheric air is most likely to be depleted in these gases compared to air sampled close to the ocean surface. Acetone is relatively long lived (Table 2) and has significant terrestrial sources (Fischer et al., 2012), and so, depending on the origin of the free tropospheric air, it could be enhanced or depleted relative to MBL air.

Figure 6 shows the voyage-average diurnal cycles for DMSa, MeSHa and acetonea. The diurnal cycle of DMSa shows variations by almost a factor of 3 from morning (maximum at 08:00, ∼ 330 ppt) to late afternoon (minimum, 16:00, ∼ 120 ppt). A DMSa diurnal cycle with sunrise maximum and late afternoon minimum has been observed in many previous studies and is attributed to photochemical destruction by OH. This includes Cape Grim baseline station, which samples air from the Southern Ocean (average minimum and maximum ∼ 40–70 ppt) (Ayers and Gillett, 2000), over the tropical Indian ocean (average minimum and maximum ∼ 25–60 ppt (Warneke and de Gouw, 2001) and at Kiritimati in the tropical Pacific (average minimum and maximum 120–200 ppt) (Bandy et al., 1996). The higher atmospheric levels in this study are due to high DMSsw concentrations (> 15 nM). The amplitude of the DMS diurnal cycle is likely to have been influenced by stationing the vessel over blooms with high DMSsw from 08:00 each day and regional mapping of areas with lower DMSsw overnight (Law et al., 2017).

The diurnal cycle for MeSHa (Fig. 6b) shows similar behaviour to DMSa with the mixing ratios varying by a factor of ∼ 2 with the minimum mixing ratio occurring at around 16:00 (the same time as minimum DMSa). The most important sink of MeSHa is thought to be oxidation by OH (Lee and Brimblecombe, 2016), and the minima in late afternoon may be due to destruction by OH. The decoupling of the DMS and MeSH diurnal cycles between 04:00 and 08:00, with DMS increasing and MeSH decreasing, is likely due to the differing production pathways as well as the possibility of additional sinks for MeSH in the ocean during this time. This period may also have been influenced by mapping areas with lower DMSsw overnight and stationing the vessel over blooms with high DMSsw from 08:00 each day, as described above.

The acetonea diurnal cycle (Fig. 6c) with land-influenced data removed shows reasonably consistent mixing ratios from the early morning until midday, with an overall increase in acetone levels during the afternoon hours from 14:00 onwards, then decreasing again at night, which is the opposite to the behaviour of DMSa and MeSHa. Acetone is long lived (∼ 60 days – Table 2) with respect to oxidation by OH. The increase of acetonea mixing ratios in the afternoon may indicate photochemical production from atmosphere or sea surface precursors but there was no correlation between irradiance and acetonea during the voyage.

MeSH and DMS fluxes (F) were calculated according to the nocturnal accumulation method (Marandino et al., 2007). This approach assumes that nighttime photochemical losses are negligible and that sea surface emissions accumulate overnight within the well-mixed marine boundary layer (MBL). Horizontal homogeneity and zero flux at the top of the boundary layer are also assumed. The air–sea flux is calculated from the increase in MeSH and DMS. For example, 2F=∂[MeSH]∂t×h, where [MeSH] is the concentration of MeSH (mol m-3) and h is the average nocturnal MBL for the voyage of 1135 m ± 657 m, estimated from nightly radiosonde flights.

DMS and MeSH fluxes were calculated for three nights (DOY 52, 54 and 60) (Table 4) when linear increases in mixing ratios occurred over several hours (Fig. 4). The MeSH flux was lowest on DOY 52 prior to B2 (3.5±2 µmol-1 m-2 d-1), higher on DOY 60 during B3a (4.8±2.8 µmol-1 m-2 d-1) and highest on DOY 42 during B2 (5.8±3.4 µmol-1 m-2 d-1). There are no MeSH measurements during B1. The percentage of MeSH / (DMS + MeSH) emitted varied from 14 % for DOY 60 (B3a) up to 23 % and 24 % for DOY 54 (B2) and DOY 52 (prior to B2), respectively.

For comparison, the DMS fluxes measured using eddy covariance (EC) at the same time are given in Table 4 (Bell et al., 2015). DMS fluxes calculated using the nocturnal accumulation method are within the variability of the EC fluxes (Bell et al., 2015).

The average MeSH flux calculated from this study (4.7 µmol m-2 d-1) was more than 4 times higher than average MeSH fluxes from previous studies in the North Atlantic–South Atlantic transect (Kettle et al., 2001) and in the Baltic Sea, Kattegat, and North Sea (Leck and Rodhe, 1991) (Table 5). The MeSH fluxes calculated from this work are comparable to maximum values reported by Kettle et al. (2001), which were observed in localised coastal and upwelling regions. The average emission of MeSH compared to DMS (MeSH / (DMS + MeSH)) was higher in this study (20 %) compared to previous studies (Table 5) including the Baltic Sea, Kattegat, and North Sea (5 %, 4 % and 11 %); North Atlantic–South Atlantic (16 %); and a recent study from the northeast subarctic Pacific (∼ 15 %) (Kiene et al., 2017). Note that other sulfur species such as dimethyl disulfide (DMDS), carbon disulfide (CS2) and hydrogen sulfide (H2S) typically make a very small contribution to the total sulfur compared to DMS and MeSH (Leck and Rodhe, 1991; Kettle et al., 2001; Yvon et al., 1993), and so they are neglected from this calculation.

To investigate the influence of biogeochemical parameters on atmospheric mixing ratios of MeSHa, DMSa and acetonea, Spearman rank correlations were undertaken to identify relationships significant at the 95 % confidence interval (CI). Table 6 summarises the correlation coefficients and p values for significant correlations. MeSHa, DMSa and acetonea data were averaged for 1 h either side of the CTD water entry time for the analysis.

Sulfur gases MeSHa and DMSa are short lived and so the air–sea flux is controlled by the seawater concentration. By contrast, acetonea is much longer lived in the atmosphere (∼ 60 days), so the air–sea gradient can be influenced by both oceanic emissions and atmospheric transport from other sources. As such, the variability in acetonea mixing ratios may be driven by ocean–air exchange and/or input of acetonea to the boundary layer from terrestrial sources, the upper atmosphere or in situ production. This means that correlation analyses to explore ocean biogeochemical sources of acetonea may be confounded by atmospheric sources. Removal of land-influenced data reduces the likelihood of this, but observed increases in atmospheric acetone could still be from in situ processes such as oxidation of organic aerosol or mixing from above the boundary layer.

Both MeSHa and DMSa have a strong positive and highly significant relationship with DMSsw, and a moderate correlation with discrete measurements of DMSPt (total) and DMSPp (particulate). The correlation of DMSa with DMSsw can be attributed to the positive flux of DMS out of the ocean; however, the correlation of MeSHa with DMSsw is likely due to a common ocean precursor of both gases (DMSP), albeit via different production pathways. DMSa and MeSHa correlate with DMSPp (particulate) but not with DMSPd (dissolved). For DMSa, the correlation may reflect that a proportion of the DMS observed was derived directly from phytoplankton rather than being bacterially mediated, which is in agreement with findings by Lizotte et al. (2017); however, as demethylation of DMSPd represents the primary source of MeSH, the lack of correlation is surprising. The latter may reflect MeSH sinks in surface water associated with organics and particles (Kiene, 1996), and this could be confirmed via incubation experiments. DMSa also correlated with particulate nitrogen and showed a moderate negative correlation with silicate that may reflect lower DMS production in diatom-dominated waters.

Acetonea shows a positive correlation with temperature and negative correlation with nutrients. This is consistent with reported sources of acetonesw in warmer subtropical waters (Beale et al., 2013; Yang et al., 2014a; Tanimoto et al., 2014; Schlundt et al., 2017). The positive relationship with organic material including HMW sugars and CDOM may reflect a photochemical ocean source (Zhou and Mopper, 1997; Dixon et al., 2013; de Bruyn et al., 2012; Kieber et al., 1990) or possibly a biological source (Nemecek-Marshall et al., 1995, 1999; Schlundt et al., 2017; Sinha et al., 2007; Halsey et al., 2017) as indicated by the correlations with cryptophyte and picoeukaryote abundance. Correlation with particle backscatter suggests potential links between acetonea and coccolithophores (Sinha et al., 2007). Alternatively, the positive correlations of acetonea with these organic components of sea water may reflect acetone production in the atmosphere from photochemical oxidation of ocean-derived organic aerosols (Pan et al., 2009; Kwan et al., 2006; Jacob et al., 2002). Seawater acetone measurements would allow for further elucidation of the relationships between acetonea and biogeochemical parameters identified in this study. More generally, mesocosm or laboratory studies could be employed to identify the explicit sources and production mechanisms of these gases in Chatham Rise waters.