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 large pH-dependent biases in pH. However, some batches of purified indicators still contain significant residual impurities that lead to an unacceptably large bias in pH for oceanic measurements. We developed a model to detect impurities in mCP using a variant of the classification technique Soft Independent Modeling of Class Analogy (SIMCA). The classification model was trained with pure mCP spectra (350-750 nm) at pH 12 and tested on independent samples of mCP 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 biases in pH were <0.002 in buffered artificial seawater solutions. Laboratories can apply our model by measuring a small number of instrument standardization and model validation samples. We propose that this method be applied for verifying that residual impurities in batches of purified mCP do not significantly bias pH measurements and that 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 “climate quality” measurements (i.e., 0.003 in pH).

Primary Presenter: Michael Fong, National Institute of Standards and Technology (michael.fong@nist.gov)

Authors:

Michael Fong, National Institute of Standards and Technology  (michael.fong@nist.gov)

Yuichiro Takeshita, Monterey Bay Aquarium Research Institute  (yui@mbari.org)

Regina Easley, National Institute of Standards and Technology  (regina.easley@nist.gov)

Jason Waters, National Institute of Standards and Technology  (jason.waters@nist.gov)