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Oceanic dissolved inorganic carbon (TC) is the largest pool of carbon that substantially interacts with the atmosphere on human timescales. Oceanic TC is increasing through uptake of anthropogenic carbon dioxide (CO2), and seawater pH is decreasing as a consequence. Both the exchange of CO2 between the ocean and atmosphere and the pH response are governed by a set of parameters that interact through chemical equilibria, collectively known as the marine carbonate system. To investigate these processes, at least two of the marine carbonate system's parameters are typically measured – most commonly, two from TC, total alkalinity (AT), pH, and seawater CO2 fugacity (fCO2; or its partial pressure, pCO2, or its dry-air mole fraction, xCO2) – from which the remaining parameters can be calculated and the equilibrium state of seawater solved. Several software tools exist to carry out these calculations, but no fully functional and rigorously validated tool written in Python, a popular scientific programming language, was previously available. Here, we present PyCO2SYS, a Python package intended to fill this capability gap. We describe the elements of PyCO2SYS that have been inherited from the existing CO2SYS family of software and explain subsequent adjustments and improvements. For example, PyCO2SYS uses automatic differentiation to solve the marine carbonate system and calculate chemical buffer factors, ensuring that the effect of every modelled solute and reaction is accurately included in all its results. We validate PyCO2SYS with internal consistency tests and comparisons against other software, showing that PyCO2SYS produces results that are either virtually identical or different for known reasons, with the differences negligible for all practical purposes. We discuss insights that guided the development of PyCO2SYS: for example, the fact that the marine carbonate system cannot be unambiguously solved from certain pairs of parameters. Finally, we consider potential future developments to PyCO2SYS and discuss the outlook for this and other software for solving the marine carbonate system. The code for PyCO2SYS is distributed via GitHub (https://github.com/mvdh7/PyCO2SYS, last access: 23 December 2021) under the GNU General Public License v3, archived on Zenodo , and documented online (https://pyco2sys.readthedocs.io/en/latest/, last access: 23 December 2021).

The sensitivity of the fugacity of carbon dioxide in seawater (fCO2) to temperature (denoted υ, reported in %°C-1) is critical for the accurate fCO2 measurements needed to build global carbon budgets and for understanding the drivers of air–sea CO2 flux variability across the ocean. However, understanding and computing υ have been restricted to either using empirical functions fitted to experimental data or determining it as an emergent property of a fully resolved marine carbonate system, and these two approaches are not consistent with each other. The lack of a theoretical basis and an uncertainty estimate for υ has hindered resolving this discrepancy. Here, we develop a new approach for calculating the temperature sensitivity of fCO2 based on the equations governing the marine carbonate system and the van 't Hoff equation. This shows that, to first order, ln⁡(fCO2) should be proportional to 1/tK (where tK is temperature in kelvin), rather than to temperature, as has previously been assumed. This new approach is, to first order, consistent with calculations from a fully resolved marine carbonate system, which we have incorporated into the PyCO2SYS software. Agreement with experimental data is less convincing but remains inconclusive due to the scarcity of direct measurements of υ, particularly above 25 °C. However, the new approach is consistent with field data, performing better than any other approach for adjusting fCO2 by up to 10 °C if spatiotemporal variability in its single fitted coefficient is accounted for. The uncertainty in υ arising from only measurement uncertainty in the main experimental dataset where υ has been directly measured is in the order of 0.04 %°C-1, which corresponds to a 0.04 % uncertainty in fCO2 adjusted by +1 °C. However, spatiotemporal variability in υ is several times greater than this, so the true uncertainty due to the temperature adjustment in fCO2 adjusted by +1 °C using the most widely used constant υ value is around 0.24 %. This can be reduced to around 0.06 % using the new approach proposed here, and this could be further reduced by more measurements. The spatiotemporal variability in υ arises mostly from the equilibrium constants for CO2 solubility and carbonic acid dissociation (K1∗ and K2∗), and its magnitude varies significantly depending on which parameterisation is used for K1∗ and K2∗. Seawater fCO2 can be measured accurately enough that additional experiments should be able to detect spatiotemporal variability in υ and distinguish between different parameterisations for K1∗ and K2∗. Because the most widely used constant υ was coincidentally measured from seawater with roughly global average υ, our results are unlikely to significantly affect global air–sea CO2 flux budgets, but they may have more important implications for regional budgets and studies that adjust by larger temperature differences.

Marine dissolved inorganic carbon (DIC) is by far the largest pool of carbon in the Earth surface system that exchanges with the atmosphere on human-relevant timescales. Measurements of DIC are therefore necessary to study the changing marine carbon cycle. The most accurate routine DIC measurement method is coulometry. In this method, the signal detected by a coulometer for each measurement must be corrected for background noise, which is termed the blank. The current best practice recommendation is to measure the blank once per analysis session and use this constant value to correct all measurements. However, calculating the blank for each measurement separately shows that the blank sometimes changes during analysis sessions. Correcting measurements to a constant blank when the blank is actually changing leads to an apparent drift in DIC results and therefore lower accuracy. Here, we propose an alternative method for coulometer blank corrections in which the blank is calculated on a per-measurement basis. The per-measurement blank values are then fitted to a smoothing function to determine a set of fitted blank values with which the measurements are corrected. We test the three different approaches (constant, per-measurement and fitted) by applying them to 263 measurements of a laboratory internal standard conducted during 89 analysis sessions over ⼠7 years. Switching from the constant blank to either the per-measurement or fitted blank improves the precision from 1.85 to 1.31 µmol kg.sup.-1 . This improvement is statistically significant and important relative to the climate-quality uncertainty target for DIC measurements of ±2 µmol kg.sup.-1 . Using the fitted blank rather than per-measurement blank eliminates a number of outliers, notably reducing the total range and kurtosis of the residuals. A free and open source Python package (koolstof) has been made available to perform fitted blank corrections for some common coulometer data types. We recommend that in future coulometric DIC analyses, per-measurement blanks should be routinely calculated as part of the quality control process and the fitted blank method applied either as standard or when a changing blank is observed.

One important aspect of understanding ocean acidification is the nature and drivers of pH variability in surface waters on smaller spatial (i.e. areas up to 100 km2) and temporal (i.e. days) scales. However, there has been a lack of high-quality pH data at sufficiently high resolution. Here, we describe a simple optical system for continuous high-resolution surface seawater pH measurements. The system includes a PyroScience pH optode placed in a flow-through cell directly connected to the underway supply of a ship through which near-surface seawater is constantly pumped. Seawater pH is measured at a rate of 2 to 4 measurements min−1 and is cross-calibrated using discrete carbonate system observations (total alkalinity, dissolved inorganic carbon, and nutrients). This setup was used during two research cruises in different oceanographic conditions: the North Atlantic Ocean (December 2020–January 2021) and the South Pacific Ocean (February–April 2022). By leveraging this novel high-frequency measurement approach, our findings reveal fine-scale fluctuations in surface seawater pH across the North Atlantic and South Pacific oceans. While temperature is a significant abiotic factor driving these variations, it does not account for all observed changes. Instead, our results highlight the interplay between temperature, biological activity, and waters with distinct temperature–salinity properties and their impact on pH. Notably, the variability differed between the two regions, suggesting differences in the dominant factors influencing pH. In the South Pacific, biological processes appeared to be mostly responsible for pH variability, while in the North Atlantic, additional abiotic and biotic factors complicated the correlation between expected and observed pH changes. While our findings indicate that broader ocean-basin-scale analyses based on lower-resolution datasets can effectively capture surface ocean CO2 variability at a global scale, they also highlight the necessity of fine-scale observations for resolving regional processes and their drivers, which is essential for improving predictive models of ocean acidification and air–sea CO2 exchange.

The high-latitude oceans are key areas of carbon and heat exchange between the atmosphere and the ocean. As such, they are a focus of both modern oceanographic and palaeoclimate research. However, most palaeoclimate proxies that could provide a long-term perspective are based on calcareous organisms, such as foraminifera, that are scarce or entirely absent in deep-sea sediments south of 50∘ S in the Southern Ocean and north of 40∘ N in the North Pacific. As a result, proxies need to be developed for the opal-based organisms (e.g. diatoms) found at these high latitudes, which dominate the biogenic sediments recovered from these regions. Here we present a method for the analysis of the boron (B) content and isotopic composition (δ11B) of diatom opal. We apply it for the first time to evaluate the relationship between seawater pH, δ11B and B concentration ([B]) in the frustules of the diatom Thalassiosira weissflogii, cultured across a range of carbon dioxide partial pressure (pCO2) and pH values. In agreement with existing data, we find that the [B] of the cultured diatom frustules increases with increasing pH (Mejía et al., 2013). δ11B shows a relatively well defined negative trend with increasing pH, completely distinct from any other biomineral previously measured. This relationship not only has implications for the magnitude of the isotopic fractionation that occurs during boron incorporation into opal, but also allows us to explore the potential of the boron-based proxies for palaeo-pH and palaeo-CO2 reconstruction in high-latitude marine sediments that have, up until now, eluded study due to the lack of suitable carbonate material.

Previous work has not led to a clear understanding of the causes of spatial pattern in global surface ocean dissolved inorganic carbon (DIC), which generally increases polewards. Here, we revisit this question by investigating the drivers of observed latitudinal gradients in surface salinity-normalized DIC (nDIC) using the Global Ocean Data Analysis Project version 2 (GLODAPv2) database. We used the database to test three different hypotheses for the driver producing the observed increase in surface nDIC from low to high latitudes. These are (1) sea surface temperature, through its effect on the CO2 system equilibrium constants, (2) salinity-related total alkalinity (TA), and (3) high-latitude upwelling of DIC- and TA-rich deep waters. We find that temperature and upwelling are the two major drivers. TA effects generally oppose the observed gradient, except where higher values are introduced in upwelled waters. Temperature-driven effects explain the majority of the surface nDIC latitudinal gradient (182 of the 223 µmol kg−1 increase from the tropics to the high-latitude Southern Ocean). Upwelling, which has not previously been considered as a major driver, additionally drives a substantial latitudinal gradient. Its immediate impact, prior to any induced air–sea CO2 exchange, is to raise Southern Ocean nDIC by 220 µmol kg−1 above the average low-latitude value. However, this immediate effect is transitory. The long-term impact of upwelling (brought about by increasing TA), which would persist even if gas exchange were to return the surface ocean to the same CO2 as without upwelling, is to increase nDIC by 74 µmol kg−1 above the low-latitude average.

We introduce a time-dependent, one-dimensional model of early diagenesis that we term RADI, an acronym accounting for the main processes included in the model: chemical reactions, advection, molecular and bio-diffusion, and bio-irrigation. RADI is targeted for study of deep-sea sediments, in particular those containing calcium carbonates (CaCO3). RADI combines CaCO3 dissolution driven by organic matter degradation with a diffusive boundary layer and integrates state-of-the-art parameterizations of CaCO3 dissolution kinetics in seawater, thus serving as a link between mechanistic surface reaction modeling and global-scale biogeochemical models. RADI also includes CaCO3 precipitation, providing a continuum between CaCO3 dissolution and precipitation. RADI integrates components rather than individual chemical species for accessibility and is straightforward to compare against measurements. RADI is the first diagenetic model implemented in Julia, a high-performance programming language that is free and open source, and it is also available in MATLAB/GNU Octave. Here, we first describe the scientific background behind RADI and its implementations. Following this, we evaluate its performance in three selected locations and explore other potential applications, such as the influence of tides and seasonality on early diagenesis in the deep ocean. RADI is a powerful tool to study the time-transient and steady-state response of the sedimentary system to environmental perturbation, such as deep-sea mining, deoxygenation, or acidification events.

One important aspect of understanding ocean acidification is the nature and drivers of pH variability in surface waters on smaller spatial (i.e. areas up to 100 km2) and temporal (i.e. days) scales. However, there has been a lack of high-quality pH data at sufficiently high resolution. Here, we describe a simple optical system for continuous high-resolution surface seawater pH measurements. The system includes a PyroScience pH optode placed in a flow-through cell directly connected to the underway supply of a ship through which near-surface seawater is constantly pumped. Seawater pH is measured at a rate of 2 to 4 measurements min−1 and is cross-calibrated using discrete carbonate system observations (total alkalinity, dissolved inorganic carbon, and nutrients). This setup was used during two research cruises in different oceanographic conditions: the North Atlantic Ocean (December 2020–January 2021) and the South Pacific Ocean (February–April 2022). By leveraging this novel high-frequency measurement approach, our findings reveal fine-scale fluctuations in surface seawater pH across the North Atlantic and South Pacific oceans. While temperature is a significant abiotic factor driving these variations, it does not account for all observed changes. Instead, our results highlight the interplay between temperature, biological activity, and waters with distinct temperature–salinity properties and their impact on pH. Notably, the variability differed between the two regions, suggesting differences in the dominant factors influencing pH. In the South Pacific, biological processes appeared to be mostly responsible for pH variability, while in the North Atlantic, additional abiotic and biotic factors complicated the correlation between expected and observed pH changes. While our findings indicate that broader ocean-basin-scale analyses based on lower-resolution datasets can effectively capture surface ocean CO2 variability at a global scale, they also highlight the necessity of fine-scale observations for resolving regional processes and their drivers, which is essential for improving predictive models of ocean acidification and air–sea CO2 exchange.

The Global Ocean Data Analysis Project (GLODAP) is a synthesis effort providing regular compilations of surface-to-bottom ocean biogeochemical bottle data, with an emphasis on seawater inorganic carbon chemistry and related variables determined through chemical analysis of seawater samples. GLODAPv2.2022 is an update of the previous version, GLODAPv2.2021 (Lauvset et al., 2021). The major changes are as follows: data from 96 new cruises were added, data coverage was extended until 2021, and for the first time we performed secondary quality control on all sulfur hexafluoride (SF6) data. In addition, a number of changes were made to data included in GLODAPv2.2021. These changes affect specifically the SF6 data, which are now subjected to secondary quality control, and carbon data measured on board the RV Knorr in the Indian Ocean in 1994–1995 which are now adjusted using certified reference material (CRM) measurements made at the time. GLODAPv2.2022 includes measurements from almost 1.4 million water samples from the global oceans collected on 1085 cruises. The data for the now 13 GLODAP core variables (salinity, oxygen, nitrate, silicate, phosphate, dissolved inorganic carbon, total alkalinity, pH, chlorofluorocarbon-11 (CFC-11), CFC-12, CFC-113, CCl4, and SF6) have undergone extensive quality control with a focus on systematic evaluation of bias. The data are available in two formats: (i) as submitted by the data originator but converted to World Ocean Circulation Experiment (WOCE) exchange format and (ii) as a merged data product with adjustments applied to minimize bias. For the present annual update, adjustments for the 96 new cruises were derived by comparing those data with the data from the 989 quality-controlled cruises in the GLODAPv2.2021 data product using crossover analysis. SF6 data from all cruises were evaluated by comparison with CFC-12 data measured on the same cruises. For nutrients and ocean carbon dioxide (CO2) chemistry comparisons to estimates based on empirical algorithms provided additional context for adjustment decisions. The adjustments that we applied are intended to remove potential biases from errors related to measurement, calibration, and data handling practices without removing known or likely time trends or variations in the variables evaluated. The compiled and adjusted data product is believed to be consistent to better than 0.005 in salinity, 1 % in oxygen, 2 % in nitrate, 2 % in silicate, 2 % in phosphate, 4 µmol kg−1 in dissolved inorganic carbon, 4 µmol kg−1 in total alkalinity, 0.01–0.02 in pH (depending on region), and 5 % in the halogenated transient tracers. The other variables included in the compilation, such as isotopic tracers and discrete CO2 fugacity (fCO2), were not subjected to bias comparison or adjustments. The original data, their documentation, and DOI codes are available at the Ocean Carbon and Acidification Data System of NOAA NCEI (https://www.ncei.noaa.gov/access/ocean-carbon-acidification-data-system/oceans/GLODAPv2_2022/, last access: 15 August 2022). This site also provides access to the merged data product, which is provided as a single global file and as four regional ones – the Arctic, Atlantic, Indian, and Pacific oceans – under https://doi.org/10.25921/1f4w-0t92 (Lauvset et al., 2022). These bias-adjusted product files also include significant ancillary and approximated data, which were obtained by interpolation of, or calculation from, measured data. This living data update documents the GLODAPv2.2022 methods and provides a broad overview of the secondary quality control procedures and results.

The stable isotopic composition of particulate organic carbon (δ13CPOC) in the surface waters of the global ocean can vary with the aqueous CO2 concentration ([CO2(aq)]) and affects the trophic transfer of carbon isotopes in the marine food web. Other factors such as cell size, growth rate and carbon concentrating mechanisms decouple this observed correlation. Here, the variability in δ13CPOC is investigated in surface waters across the south subtropical convergence (SSTC) in the Atlantic Ocean, to determine carbon isotope fractionation (εp) by phytoplankton and the contrasting mechanisms of carbon uptake in the subantarctic and subtropical water masses. Our results indicate that cell size is the primary determinant of δ13CPOC across the Atlantic SSTC in summer. Combining cell size estimates with CO2 concentrations, we can accurately estimate εp within the varying surface water masses in this region. We further utilize these results to investigate future changes in εp with increased anthropogenic carbon availability. Our results suggest that smaller cells, which are prevalent in the subtropical ocean, will respond less to increased [CO2(aq)] than the larger cells found south of the SSTC and in the wider Southern Ocean. In the subantarctic water masses, isotopic fractionation during carbon uptake will likely increase, both with increasing CO2 availability to the cell, but also if increased stratification leads to decreases in average community cell size. Coupled with decreasing δ13C of [CO2(aq)] due to anthropogenic CO2 emissions, this change in isotopic fractionation and lowering of δ13CPOC may propagate through the marine food web, with implications for the use of δ13CPOC as a tracer of dietary sources in the marine environment.