Fong Michael, Takeshita Yuichiro, Easley Regina, Waters Jason
National Institute of Standards and Technology, Chemical Sciences Division, Gaithersburg, MD USA.
Monterey Bay Aquarium Research Institute, Moss Landing, CA USA.
Mar Chem. 2024 Feb;259. doi: 10.1016/j.marchem.2024.104362.
Accurate spectrophotometric pH measurements in seawater are critical to documenting long-term changes in ocean acidity and carbon chemistry, and for calibration of autonomous pH sensors. The recent development of purified indicator dyes greatly improved the accuracy of spectrophotometric pH measurements by removing interfering impurities that cause biases in pH that can grow over the seawater pH range to >0.01 above pH 8. However, some batches of purified indicators still contain significant residual impurities that lead to unacceptably large biases in pH for oceanic and estuarine measurements. While high-performance liquid chromatography (HPLC) is the standard method for verifying dye purity, alternative approaches that are simple to implement and require less specialized equipment are desirable. We developed a model to detect impurities in the pH indicator -cresol purple (CP) using a variant of the classification technique Soft Independent Modeling of Class Analogy (SIMCA). The classification model was trained with pure CP spectra (350 nm to 750 nm at 1 nm resolution) at pH 12 and tested on independent samples of unpurified and purified CP with varying levels of impurities (determined by HPLC) and measured on two different spectrophotometers. All the dyes identified as pure by the SIMCA model were sufficiently low in residual impurities that their apparent biases in pH were < 0.002 in buffered artificial seawater solutions at a salinity of 35 and over a pH range of 7.2 to 8.2. Other methods that can also detect residual impurities relevant to measurements include estimating the impurity absorption at 434 nm and assessing the apparent pH biases relative to a reference purified dye in buffered solutions or natural seawater. Laboratories that produce and distribute purified CP should apply the SIMCA method or other suitable methods to verify that residual impurities do not significantly bias pH measurements. To apply the SIMCA method, users should download the data and model developed in this work and measure a small number of instrument standardization and model validation samples. This method represents a key step in the development of a measurement quality framework necessary to attain the uncertainty goals articulated by the Global Ocean Acidification Observing Network (GOA-ON) for measurements (i.e., ±0.003 in pH).
在海水中进行准确的分光光度法pH测量对于记录海洋酸度和碳化学的长期变化以及校准自主pH传感器至关重要。纯化指示剂染料的最新发展通过去除干扰杂质极大地提高了分光光度法pH测量的准确性，这些干扰杂质会导致pH偏差，在海水pH范围内，该偏差在pH 8以上可能会增长到>0.01。然而，一些批次的纯化指示剂仍然含有大量残留杂质，导致海洋和河口测量中的pH偏差大到不可接受。虽然高效液相色谱法（HPLC）是验证染料纯度的标准方法，但需要简单实施且所需专业设备较少的替代方法是可取的。我们开发了一个模型，使用分类技术类比软独立建模（SIMCA）的变体来检测pH指示剂甲酚紫（CP）中的杂质。分类模型用pH 12时的纯CP光谱（分辨率为1 nm，350 nm至750 nm）进行训练，并在具有不同杂质水平（由HPLC测定）的未纯化和纯化CP的独立样品上进行测试，并在两种不同的分光光度计上进行测量。所有被SIMCA模型鉴定为纯的染料，其残留杂质含量足够低，以至于在盐度为35的缓冲人工海水溶液中，在7.2至8.2的pH范围内，其表观pH偏差<0.002。其他也能检测与测量相关的残留杂质的方法包括估计434 nm处的杂质吸收，以及评估在缓冲溶液或天然海水中相对于参考纯化染料的表观pH偏差。生产和分发纯化CP的实验室应应用SIMCA方法或其他合适方法，以验证残留杂质不会显著影响pH测量。要应用SIMCA方法，用户应下载本工作中开发的数据和模型，并测量少量仪器标准化和模型验证样品。该方法代表了开发测量质量框架的关键一步，该框架是实现全球海洋酸化观测网络（GOA-ON）对测量所阐明的不确定性目标（即pH值±0.003）所必需的。
