Collaborative Research: Self-Calibrating pH Sensors for Autonomous Collection of Climate Quality Data

自主pH传感器在海洋酸化和碳循环研究中正变得越来越普遍。然而，这些研究的实验结果和结论的价值直接取决于收集的pH数据的可靠性。借鉴气象学领域的术语，海洋化学家和生物学家将pH测量精度归类为“天气质量”或“气候质量”，分别对应于大约0.02ph值单位或0.003 ph值单位的水平。虽然探测气候尺度的酸碱值变化是必要的，但从传感器获得“气候质量”酸碱值数据仍然难以实现。研究人员提议开发一种强大、维护成本低、用户友好的系统，允许从考察船和海洋系泊设备上的pH传感器定期收集气候质量数据。从本质上讲，这个项目涉及开发一种自动化的自我校准的pH传感器包，可能不具备实现气候质量数据集的专业知识的研究人员可以部署该传感器包。现场测试将产生数据，以支持正在进行的研究项目，这些项目涉及船上正在进行的测量(例如CalCOFI)以及沿海地点的自主现场测量，包括当地的泻湖(加利福尼亚州卡尔斯巴德的Agua Hedionda)和偏远的珊瑚礁(Palmyra Atoll)。在这些研究中加入气候质量pH数据将扩大我们对长期气候规模对牡蛎、贝类渔业和珊瑚礁影响的理解。基于以往概述现场pH传感器数据的最佳做法和质量控制协议的努力，出现了一个中心主题：为了生成气候质量数据集，需要对自主的pH传感器测量进行独立验证。从历史上看，这是通过艰苦的工作实现的，包括在现场重复瓶子样本。维持瓶子采样程序是昂贵的，而且超出了许多希望在现场测量高频PH值的研究实验室的能力。即使是最彻底的现场计划也未能完全消除传感器和瓶子样本之间的时空不匹配，这导致了传感器校准的重大不确定性。直接应对这一挑战，这项工作的目标是通过内置的自校准功能来提高未来Durafet pH传感器数据集的质量。具体地说，该项目将在人工海水中集成船上标准化的Tris缓冲器，以定期验证pH传感器的性能。作为一个自然的结果，这一能力的增加将提高数据质量，并大大减少操作员在现场部署期间所需的工作，因为他们将不再需要收集和分析瓶子样本以进行pH验证。类似的协议已经成功地用于气候质量二氧化碳测量。

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.