Ocean Acidification

The presented pilot for the Synthesis Product for Ocean Time Series (SPOTS) includes data from 12 fixed ship-based time-series programs. The related stations represent unique open-ocean and coastal marine environments within the Atlantic Ocean, Pacific Ocean, Mediterranean Sea, Nordic Seas, and Caribbean Sea. The focus of the pilot has been placed on biogeochemical essential ocean variables: dissolved oxygen, dissolved inorganic nutrients, inorganic carbon (pH, total alkalinity, dissolved inorganic carbon, and partial pressure of CO₂), particulate matter, and dissolved organic carbon. The time series used include a variety of temporal resolutions (monthly, seasonal, or irregular), time ranges (10–36 years), and bottom depths (80–6000 m), with the oldest samples dating back to 1983 and the most recent one corresponding to 2021. Besides having been harmonized into the same format (semantics, ancillary data, units), the data were subjected to a qualitative assessment in which the applied methods were evaluated and categorized. The most recently applied methods of the time-series programs usually follow the recommendations outlined by the Bermuda Time Series Workshop report (Lorenzoni and Benway, 2013), which is used as the main reference for “method recommendations by prevalent initiatives in the field”. However, measurements of dissolved oxygen and pH, in particular, still show room for improvement. Additional data quality descriptors include precision and accuracy estimates, indicators for data variability, and offsets compared to a reference and widely recognized data product for the global ocean: the GLobal Ocean Data Analysis Project (GLODAP). Generally, these descriptors indicate a high level of continuity in measurement quality within time-series programs and a good consistency with the GLODAP data product, even though robust comparisons to the latter are limited. The data are available as (i) a merged comma-separated file that is compliant with the World Ocean Circulation Experiment (WOCE) exchange format and (ii) a format dependent on user queries via the Environmental Research Division’s Data Access Program (ERDDAP) server of the Global Ocean Observing System (GOOS). The pilot increases the data utility, findability, accessibility, interoperability, and reusability following the FAIR philosophy, enhancing the readiness of biogeochemical time series. It facilitates a variety of applications that benefit from the collective value of biogeochemical time-series observations and forms the basis for a sustained time-series living data product, SPOTS, complementing relevant products for the global interior ocean carbon data (GLobal Ocean Data Analysis Project), global surface ocean carbon data (Surface Ocean CO₂ Atlas; SOCAT), and global interior and surface methane and nitrous oxide data (MarinE MethanE and NiTrous Oxide product).

Aside from the actual data compilation, the pilot project produced suggestions for reporting metadata, implementing quality control measures, and making estimations about uncertainty. These recommendations aim to encourage the community to adopt more consistent and uniform practices for analysis and reporting and to update these practices regularly. The detailed recommendations, links to the original time-series programs, the original data, their documentation, and related efforts are available on the SPOTS website. This site also provides access to the data product (DOI: https://doi.org/10.26008/1912/bco-dmo.896862.2, Lange et al., 2024) and ancillary data.

Highlights

• Development of an autonomous DIC analyzer based on Conductometric technique using a cell with 4 hollow brass electrodes.
• CO2 extraction from seawater using a gas diffusion cell with a “Tube In A Tube” configuration and a gas permeable membrane.
• Formulation of mathematical temperature and salinity correction to determine accurate DIC concentration.
• Demonstration of the analyzer performance in the southwest Baltic Sea.

Abstract

Background

The increase in anthropogenic CO₂ concentrations in the Earth’s atmosphere since the industrial revolution has resulted in an increased uptake of CO₂ by the oceans, leading to ocean acidification. Dissolved Inorganic Carbon (DIC) is one of the key variables to characterize the seawater carbonate system. High quality DIC observations at a high spatial-temporal resolution is required to improve our understanding of the marine carbonate system. To meet the requirements, autonomous DIC analyzers are needed which offer a high sampling frequency, are cost-effective and have a low reagent and power consumption.

Results

We present the development and validation of a novel analyzer for autonomous measurements of DIC in seawater using conductometric detection. The analyzer employs a gas diffusion sequential injection approach in a “Tube In A Tube” configuration that facilitates diffusion of gaseous CO₂ from an acidified sample through a gas permeable membrane into a stream of an alkaline solution. The change in conductivity in the alkaline medium is proportional to the DIC concentration of the sample and is measured using a detection cell constructed of 4 hollow brass electrodes. Physical and chemical optimizations of the analyzer yielded a sampling frequency of 4 samples h⁻¹ using sub mL reagent volumes for each measurement. Temperature and salinity effects on DIC measurements were mathematically corrected to increase accuracy. Analytical precision of ±4.9 μmol kg⁻¹ and ±9.7 μmol kg⁻¹ were achieved from measurements of a DIC reference material in the laboratory and during a field deployment in the southwest Baltic Sea, respectively.

Significance

This study describes a simple, cost-effective, autonomous, on-site benchtop DIC analyzer capable of measuring DIC in seawater at a high temporal resolution as a step towards an underwater DIC sensor. The analyzer is able to measure a wide range of DIC concentrations in both fresh and marine waters. The achieved accuracy and precision offer an excellent opportunity to employ the analyzer for ocean acidification studies and CO₂ leakage detection in the context of Carbon Capture and Storage operations.

Highlights

• We developed a chemometric model to detect impurities in a pH indicator dye.
• The model was developed for m-cresol purple, a widely used dye for seawater pH.
• The model can verify a dye is pure enough for “climate quality” pH measurements.
• Other spectrophotometric methods can also be used to assess dye purity.

Abstract

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 climate quality 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 m-cresol purple (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 nm to 750 nm at 1 nm resolution) at pH 12 and tested on independent samples of unpurified and purified 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 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 climate quality 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 mCP 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 climate quality measurements (i.e., ±0.003 in pH).

The strong control that the emissions of carbon dioxide (CO₂) have over Earth’s climate identifies the need for accurate quantification of the emitted CO₂ and its redistribution within the Earth system. The ocean annually absorbs more than a quarter of all CO₂ emissions and this absorption is fundamentally altering the ocean chemistry. The ocean thus provides a fundamental component and powerful constraint within global carbon assessments used to guide policy action for reducing emissions. These carbon assessments rely heavily on satellite observations, but their inclusion is often invisible or opaque to policy. One reason is that satellite observations are rarely used exclusively, but often in conjunction with other types of observations, thereby complementing and expanding their usability yet losing their visibility. This exploitation of satellite observations led by the satellite and ocean carbon scientific communities is based on exciting developments in satellite science that have broadened the suite of environmental data that can now reliably be observed from space. However, the full potential of satellite observations to expand the scientific knowledge on critical processes such as the atmosphere-ocean exchange of CO₂ and ocean acidification, including its impact on ocean health, remains largely unexplored. There is clear potential to begin using these observation-based approaches for directly guiding ocean management and conservation decisions, in particular in regions where in situ data collection is more difficult, and interest in them is growing within the environmental policy communities. We review these developments, identify new opportunities and scientific priorities, and identify that the formation of an international advisory group could accelerate policy relevant advancements within both the ocean carbon and satellite communities. Some barriers to understanding exist but these should not stop the exploitation and the full visibility of satellite observations to policy makers and users, so these observations can fulfil their full potential and recognition for supporting society.