Evaluating Data Quality of Coastal Spectrophotometric pH Measurements: Implications for Ocean Acidification and Ocean Alkalinity Enhancement Research

Abstract

pH, which reflects the thermodynamic balance of acid-base systems in seawater, serves as a key indicator of the interplay between acidic and basic components in marine environments. When combined with another parameter, such as TA, DIC, or pCO2 the entire inorganic carbon system can be derived. However, each parameter presents methodological challenges that may introduce random or systematic errors, which then propagate through subsequent calculations. In coastal and estuarine environments, errors can become more pronounced, as standard operating procedures (SOPs) developed for open-ocean conditions may not adequately address the complexities unique to these regions. Measuring more than two parameters enables further insight into systematic errors through the evaluation of internal consistency, where existing data products often reveal pH-dependent offsets between measured pH and pH calculated from measured TA and DIC. These offsets may arise from errors in pH measurements, TA and DIC measurements, or the equilibrium constants used in the calculations, and are therefore difficult to tease apart. Comparing measurements from different research groups can help identify the specific measurement biases responsible for these offsets; however, the lack of inter-comparison studies, particularly in field settings, hinders our understanding. This work advocates for integrating internal consistency and inter-comparison studies in field conditions, as conducting them at sea provides a realistic evaluation of reproducibility between research groups. Chapter 2 utilizes this method by comparing at-sea spectrophotometric pH (pHspec) measurements from two research groups aboard the R/V Coriolis in June 2022 in the Gulf of St. Lawrence and the Lower St. Lawrence Estuary during the Tracer Release Deep Experiment 2 (TReX2) cruise. This combined analysis of reproducibility and internal consistency highlights how even minor methodological differences can substantially affect data quality, and in turn, shape data interpretation. These impacts are particularly pronounced when estimating potential bias from unidentified, excess components of TA (TAx), expected to be non-negligible in estuarine environments, where the two groups had notably different estimates. Chapter 3 draws conclusions from the discussion of data quality in estuarine environments from Chapter 2, focusing on the potential role of pHspec in Monitoring, Reporting, and Verification (MRV) frameworks for ocean alkalinity enhancement (OAE), a proposed marine carbon dioxide removal (mCDR) strategy. It incorporates insights from OAE field trial work in the Bedford Basin, Halifax, a fjord-like estuarine system, to assess the quality of pHspec, TA, and DIC data, offering an assessment of the reliability of these measurements for interpreting potential carbon dioxide removal. This chapter also includes suggestions for a future protocol for observational components of MRV frameworks.