Frontiers in Marine Science (Sep 2021)
Air-Sea Gas Fluxes and Remineralization From a Novel Combination of pH and O2 Sensors on a Glider
Abstract
Accurate, low-power sensors are needed to characterize biogeochemical variability on underwater glider missions. However, the needs for high accuracy and low power consumption can be difficult to achieve together. To overcome this difficulty, we integrated a novel sensor combination into a Seaglider, comprising a spectrophotometric lab-on-a-chip (LoC) pH sensor and a potentiometric pH sensor, in addition to the standard oxygen (O2) optode. The stable, but less frequent (every 10 min) LoC data were used to calibrate the high-resolution (1 s) potentiometric sensor measurements. The glider was deployed for a 10-day pilot mission in August 2019. This represented the first such deployment of either type of pH sensor on a glider. The LoC pH had a mean offset of +0.005±0.008 with respect to pH calculated from total dissolved inorganic carbon content, c(DIC), and total alkalinity, AT, in co-located water samples. The potentiometric sensor required a thermal-lag correction to resolve the pH variations in the steep thermocline between surface and bottom mixed layers, in addition to scale calibration. Using the glider pH data and a regional parameterization of AT as a function of salinity, we derived the dissolved CO2 content and glider c(DIC). Glider surface CO2 and O2 contents were used to derive air-sea fluxes, Φ(CO2) and Φ(O2). Φ(CO2) was mostly directed into the ocean with a median of −0.4 mmol m–2 d–1. In contrast, Φ(O2) was always out of the ocean with a median of +40 mmol m–2 d–1. Bottom water apparent oxygen utilization (AOU) was (35±1) μmol kg–1, whereas apparent carbon production (ACP) was (11±1) μmol kg–1, with mostly insignificant differences along the deployment transect. This deployment shows the potential of using pH sensors on autonomous observing platforms such as Seagliders to quantify the interactions between biogeochemical processes and the marine carbonate system at high spatiotemporal resolution.
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