ABSTRACT

Autonomous pH sensors are becoming increasingly common in Ocean Acidification and Carbon Cycle studies. However, the value of experimental results and conclusions from these studies hinges directly on the reliability of pH data collected. Drawing on terminology from the field of meteorology, marine chemists and biologists categorize pH measurement accuracy as "Weather Quality" or "Climate Quality," corresponding to a level of roughly 0.02 or 0.003 pH units, respectively. While necessary in order to detect climate scale changes in pH, achievement of "Climate Quality" pH data from sensors remains elusive. The researchers propose to develop a robust, low maintenance, user friendly system that will allow climate quality data to be routinely collected from pH sensors on research vessels and oceanographic moorings. In essence, this project involves developing an automated self-calibrating pH sensor package that can be deployed by researchers that may not hold the expertise to achieve a climate quality dataset. Field tests will generate data in support of ongoing research programs involving shipboard underway measurements (e.g. CalCOFI) as well as autonomous in situ measurements at coastal sites including a local lagoon (Agua Hedionda, Carlsbad, CA) and a remote coral reef (Palmyra Atoll). The addition of climate quality pH data in these studies will broaden our understanding of long-term climate scale effects on, for example, oyster shellfisheries and coral reefs.

Based on previous efforts to outline Best Practices and Quality Control protocols for in situ pH sensor data, a central theme has emerged: independent validation of autonomous pH sensor measurements is required in order to generate climate quality datasets. Historically, this has been accomplished through painstaking work involving repeat bottle samples in the field. Sustaining a bottle sampling program is expensive and beyond the capabilities of many research labs that wish to measure high-frequency pH in the field. Even the most thorough field programs haven't managed to fully eliminate spatiotemporal mismatch between sensor and bottle samples, leading to significant uncertainty in the calibration of the sensor. Directly addressing this challenge, the objective of this work is to improve the quality of future Durafet pH sensor datasets via a built-in self-calibration function. Specifically, the project will integrate on-board, standardized Tris buffers in artificial seawater for periodic validation of pH sensor performance. As a natural result, addition of this capability will improve data quality and substantially reduce the efforts required by operators during a field deployment, as they will no longer be required to collect and analyze bottle samples for pH validation. Similar protocols have been successfully adapted for climate quality pCO2 measurement.

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