Anomalies in the Carbonate System of Red Sea Coastal Habitats

Abstract. We use observations of dissolved inorganic carbon (DIC) and total alkalinity (TA) to assess the impact of ecosystem metabolic processes on coastal waters of the eastern Red Sea. A simple, single-end-member mixing model is used to account for the influence of mixing with offshore waters and evaporation/precipitation, and to model ecosystem-driven perturbations on the carbonate system chemistry of coral reefs, seagrass meadows and mangrove forests. We find that (1) along-shelf changes in TA and DIC exhibit strong linear trends that are consistent with basin-scale net calcium carbonate precipitation; (2) ecosystem-driven changes in TA and DIC are larger than offshore variations in > 85 % of sampled seagrass meadows and mangrove forests, changes which are influenced by a combination of longer water residence times and community metabolic rates; and (3) the sampled mangrove forests show strong and consistent contributions from both organic respiration and other sedimentary processes (carbonate dissolution and secondary redox processes), while seagrass meadows display more variability in the relative contributions of photosynthesis and other sedimentary processes (carbonate precipitation and oxidative processes).

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Anomalies in the carbonate system of Red Sea coastal habitats

Biogeosciences ◽

10.5194/bg-17-423-2020 ◽

2020 ◽

Vol 17 (2) ◽

pp. 423-439

Author(s):

Kimberlee Baldry ◽

Vincent Saderne ◽

Daniel C. McCorkle ◽

James H. Churchill ◽

Susana Agusti ◽

...

Keyword(s):

Red Sea ◽

Total Alkalinity ◽

Carbonate Precipitation ◽

Residence Times ◽

Mangrove Forests ◽

Sedimentary Processes ◽

Coastal Habitats ◽

Carbonate System ◽

Seagrass Meadows ◽

The Impact

Abstract. We use observations of dissolved inorganic carbon (DIC) and total alkalinity (TA) to assess the impact of ecosystem metabolic processes on coastal waters of the eastern Red Sea. A simple, single-end-member mixing model is used to account for the influence of mixing with offshore waters and evaporation–precipitation and to model ecosystem-driven perturbations on the carbonate system chemistry of coral reefs, seagrass meadows and mangrove forests. We find that (1) along-shelf changes in TA and DIC exhibit strong linear relationships that are consistent with basin-scale net calcium carbonate precipitation; (2) ecosystem-driven changes in TA and DIC are larger than offshore variations in >70 % of sampled seagrass meadows and mangrove forests, changes which are influenced by a combination of longer water residence times and community metabolic rates; and (3) the sampled mangrove forests show strong and consistent contributions from both organic respiration and other sedimentary processes (carbonate dissolution and secondary redox processes), while seagrass meadows display more variability in the relative contributions of photosynthesis and other sedimentary processes (carbonate precipitation and oxidative processes). The results of this study highlight the importance of resolving the influences of water residence times, mixing and upstream habitats on mediating the carbonate system and coastal air–sea carbon dioxide fluxes over coastal habitats in the Red Sea.

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New insights into nutrients dynamics and the carbonate system using a neural network approach in the Mediterranean Sea

10.5194/egusphere-egu2020-9520 ◽

2020 ◽

Author(s):

Marine Fourrier ◽

Laurent Coppola ◽

Fabrizio D'Ortenzio

Keyword(s):

Neural Network ◽

Mediterranean Sea ◽

Dissolved Inorganic Carbon ◽

In Situ Measurements ◽

Total Alkalinity ◽

Anthropogenic Pressure ◽

Carbonate System ◽

The Mediterranean ◽

The Impact

The semi-enclosed nature of the Mediterranean Sea, together with its small inertia which is due to the relatively short residence time of its water masses, make it highly reactive to external forcings and anthropogenic pressure. In this context, several rapid changes have been observed in physical and biogeochemical processes in recent decades, partly masked by episodic events and high regional variability. To better understand the underlying processes driving the Mediterranean evolution and, anticipate changes, the measurement, and integration of many biogeochemical variables are mandatory.The development of new BGC sensors implemented on in situ autonomous platforms allows to increase the acquisition of essential biogeochemical variables. However, the measurements carried out by in situ autonomous platforms (e.g. profiling floats, gliders, moorings) are not exhaustive.Recently, deep learning techniques and in particular neural networks have been developed. The CANYON-MED (for Carbonate system and Nutrients concentration from hYdrological properties and Oxygen using a Neural-network in the MEDiterranean Sea) neural network-based method provides estimations of nutrients (i.e. nitrates, phosphates, and silicates) and carbonate system variables (i.e. total alkalinity, dissolved inorganic carbon, pHT) from systematically measured oceanographic variables such as in situ measurements of pressure, temperature, salinity, and oxygen together with geolocation and date of sampling.This regional approach, therefore, using quality-controlled in situ measurements from more than 35 cruises. CANYON-MED obtains satisfactory results: accuracies of 0.73, 0.045, and 0.70 &#181;mol.kg-1 for the nitrates, phosphates and silicates concentrations respectively, and 0.016, 11 &#181;mol.kg-1 and 10 &#181;mol.kg-1 for pHT, total alkalinity and dissolved organic carbon respectively. CANYON-MED thus generates &#8220;virtual&#8221; data of parameters not yet measured by autonomous platforms, while ably reproducing the data already sampled, emphasizing its ability to fill the gaps in time-series.Hence, by applying it to the large and growing network of autonomous platforms in the Mediterranean Sea, this method allows us to gain new insights into nutrients and carbonate system dynamics in targeted areas. In particular, in the northwestern Mediterranean Sea, the impact of deep convection on biogeochemistry (e.g., nutrient replenishment and pHT variability) is highly variable over time and poorly covered by observing networks. In this case, CANYON-MED would improve our observations and understanding of the dynamic and coupled system.

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Organic and inorganic whole system metabolism in two acidified coastal systems in Ireland

10.5194/egusphere-egu2020-17499 ◽

2020 ◽

Author(s):

Maria Teresa Guerra ◽

Carlos Rocha

Keyword(s):

Ocean Acidification ◽

Dissolved Inorganic Carbon ◽

Total Alkalinity ◽

Carbonate System ◽

Net Community Production ◽

Coastal Acidification ◽

Autumn And Winter ◽

System Metabolism ◽

Internal Buffer ◽

Community Production

Organic and inorganic whole system metabolism for two Irish coastal areas were compared to evaluate carbonate system resilience to acidification. The two systems are characterized by contrasting watershed input types and composition. Kinvara Bay is fed by Submarine Groundwater Discharge (SGD) derived from a karstic catchment while Killary Harbour is fed by river discharge draining a siliciclastic catchment. Freshwater sources to sea have distinct Total Alkalinity (TA) and Dissolved Inorganic Carbon (DIC) concentrations, higher and lower than the open ocean, respectively, but both evidence seasonally variable low pH, ranging from 6.20 to 7.50. Retention of TA and DIC was calculated for the two areas using LOICZ methodology. In Kinvara bay, annually averaged retention of DIC was greater than for TA (5 &#215; 104 and 1.5 &#215; 105 mol d-1), suggesting the system is acidifying further. Conversely, Killary Harbour shows negative TA and DIC retention, with DIC:TA <1, suggesting an internal buffer against ocean acidification is operating.Net Community Production (NCP) was calculated for both systems using Dissolved Oxygen data. Subsequently, we estimated Net Community Calcification (NCC) from the ratio between TA and DIC. NCP was always positive in Killary Harbour with an average of 318 mmol O2 m-2 d-1 (equivalent to 89 mol C m-2 y-1). However, Kinvara Bay shows relatively lower positive NCP in spring and summer (average of 46 mmol O2 m-2 d-1), but negative NCP in autumn and winter. Therefore, Kinvara Bay&#8217;s Total Organic Carbon (TOC) production was low, at ~21 g m-2 y-1 and not enough to overcome acidification driven by the SGD source composition. These results emphasize the complexity of interactions between the drivers of coastal acidification rate, affecting our ability to accurately assess the resilience of the carbonate system in these areas to ocean acidification pressure in the future.

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OceanSODA-ETHZ: a global gridded data set of the surface ocean carbonate system for seasonal to decadal studies of ocean acidification

Earth System Science Data ◽

10.5194/essd-13-777-2021 ◽

2021 ◽

Vol 13 (2) ◽

pp. 777-808

Author(s):

Luke Gregor ◽

Nicolas Gruber

Keyword(s):

Ocean Acidification ◽

Total Alkalinity ◽

Global Ocean ◽

Carbonate System ◽

Data Set ◽

Saturation State ◽

Total Uncertainty ◽

Mean Squared Errors ◽

Surface Ocean ◽

Basin Scale

Abstract. Ocean acidification has profoundly altered the ocean's carbonate chemistry since preindustrial times, with potentially serious consequences for marine life. Yet, no long-term, global observation-based data set exists that allows us to study changes in ocean acidification for all carbonate system parameters over the last few decades. Here, we fill this gap and present a methodologically consistent global data set of all relevant surface ocean parameters, i.e., dissolved inorganic carbon (DIC), total alkalinity (TA), partial pressure of CO2 (pCO2), pH, and the saturation state with respect to mineral CaCO3 (Ω) at a monthly resolution over the period 1985 through 2018 at a spatial resolution of 1∘×1∘. This data set, named OceanSODA-ETHZ, was created by extrapolating in time and space the surface ocean observations of pCO2 (from the Surface Ocean CO2 Atlas, SOCAT) and total alkalinity (TA; from the Global Ocean Data Analysis Project, GLODAP) using the newly developed Geospatial Random Cluster Ensemble Regression (GRaCER) method (code available at https://doi.org/10.5281/zenodo.4455354, Gregor, 2021). This method is based on a two-step (cluster-regression) approach but extends it by considering an ensemble of such cluster regressions, leading to improved robustness. Surface ocean DIC, pH, and Ω were then computed from the globally mapped pCO2 and TA using the thermodynamic equations of the carbonate system. For the open ocean, the cluster-regression method estimates pCO2 and TA with global near-zero biases and root mean squared errors of 12 µatm and 13 µmol kg−1, respectively. Taking into account also the measurement and representation errors, the total uncertainty increases to 14 µatm and 21 µmol kg−1, respectively. We assess the fidelity of the computed parameters by comparing them to direct observations from GLODAP, finding surface ocean pH and DIC global biases of near zero, as well as root mean squared errors of 0.023 and 16 µmol kg−1, respectively. These uncertainties are very comparable to those expected by propagating the total uncertainty from pCO2 and TA through the thermodynamic computations, indicating a robust and conservative assessment of the uncertainties. We illustrate the potential of this new data set by analyzing the climatological mean seasonal cycles of the different parameters of the surface ocean carbonate system, highlighting their commonalities and differences. Further, this data set provides a novel constraint on the global- and basin-scale trends in ocean acidification for all parameters. Concretely, we find for the period 1990 through 2018 global mean trends of 8.6 ± 0.1 µmol kg−1 per decade for DIC, −0.016 ± 0.000 per decade for pH, 16.5 ± 0.1 µatm per decade for pCO2, and −0.07 ± 0.00 per decade for Ω. The OceanSODA-ETHZ data can be downloaded from https://doi.org/10.25921/m5wx-ja34 (Gregor and Gruber, 2020).

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The impact on atmospheric CO2 of iron fertilization induced changes in the ocean's biological pump

Biogeosciences Discussions ◽

10.5194/bgd-4-3863-2007 ◽

2007 ◽

Vol 4 (5) ◽

pp. 3863-3911 ◽

Cited By ~ 1

Author(s):

X. Jin ◽

N. Gruber ◽

H. Frenzel ◽

S. C. Doney ◽

J. C. McWilliams

Keyword(s):

Dissolved Inorganic Carbon ◽

Light Availability ◽

Co2 Flux ◽

Surface Patch ◽

Biological Pump ◽

Small Surface ◽

Uptake Efficiency ◽

Iron Fertilization ◽

Basin Scale ◽

The Impact

Abstract. Using numerical simulations, we quantify the impact of changes in the ocean's biological pump on the air-sea balance of CO2 by fertilizing a small surface patch in the high-nutrient, low-chlorophyll region of the eastern tropical Pacific with iron. Decade-long fertilization experiments are conducted in a basin-scale, eddy-permitting coupled physical biogeochemical ecological model. In contrast to previous studies, we find that most of the dissolved inorganic carbon (DIC) removed from the euphotic zone by the enhanced biological export is replaced by uptake of CO2 from the atmosphere. Atmospheric uptake efficiencies, the ratio of the perturbation in air-sea CO2 flux to the perturbation in export flux across 100 m, are 0.75 to 0.93 in our patch size-scale experiments. The atmospheric uptake efficiency is insensitive to the duration of the experiment. The primary factor controlling the atmospheric uptake efficiency is the vertical distribution of the enhanced biological production. Iron fertilization at the surface tends to induce production anomalies primarily near the surface, leading to high efficiencies. In contrast, mechanisms that induce deep production anomalies (e.g. altered light availability) tend to have a low uptake efficiency, since most of the removed DIC is replaced by lateral and vertical transport and mixing. Despite high atmospheric uptake efficiencies, patch-scale iron fertilization of the ocean's biological pump tends to remove little CO2 from the atmosphere over the decadal timescale considered here.

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The Sensitivity of the Marine Carbonate System to Regional Ocean Alkalinity Enhancement

Frontiers in Climate ◽

10.3389/fclim.2021.624075 ◽

2021 ◽

Vol 3 ◽

Author(s):

Daniel J. Burt ◽

Friederike Fröb ◽

Tatiana Ilyina

Keyword(s):

Southern Ocean ◽

Dissolved Inorganic Carbon ◽

Ocean Model ◽

Total Alkalinity ◽

Surface Pattern ◽

Carbon Uptake ◽

Max Planck ◽

Carbonate System ◽

Carbon Cycle Model ◽

Marine Carbonate

Ocean Alkalinity Enhancement (OAE) simultaneously mitigates atmospheric concentrations of CO2 and ocean acidification; however, no previous studies have investigated the response of the non-linear marine carbonate system sensitivity to alkalinity enhancement on regional scales. We hypothesise that regional implementations of OAE can sequester more atmospheric CO2 than a global implementation. To address this, we investigate physical regimes and alkalinity sensitivity as drivers of the carbon-uptake potential response to global and different regional simulations of OAE. In this idealised ocean-only set-up, total alkalinity is enhanced at a rate of 0.25 Pmol a-1 in 75-year simulations using the Max Planck Institute Ocean Model coupled to the HAMburg Ocean Carbon Cycle model with pre-industrial atmospheric forcing. Alkalinity is enhanced globally and in eight regions: the Subpolar and Subtropical Atlantic and Pacific gyres, the Indian Ocean and the Southern Ocean. This study reveals that regional alkalinity enhancement has the capacity to exceed carbon uptake by global OAE. We find that 82–175 Pg more carbon is sequestered into the ocean when alkalinity is enhanced regionally and 156 PgC when enhanced globally, compared with the background-state. The Southern Ocean application is most efficient, sequestering 12% more carbon than the Global experiment despite OAE being applied across a surface area 40 times smaller. For the first time, we find that different carbon-uptake potentials are driven by the surface pattern of total alkalinity redistributed by physical regimes across areas of different carbon-uptake efficiencies. We also show that, while the marine carbonate system becomes less sensitive to alkalinity enhancement in all experiments globally, regional responses to enhanced alkalinity vary depending upon the background concentrations of dissolved inorganic carbon and total alkalinity. Furthermore, the Subpolar North Atlantic displays a previously unexpected alkalinity sensitivity increase in response to high total alkalinity concentrations.

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PyCO2SYS v1.7: marine carbonate system calculations in Python

10.5194/gmd-2021-159 ◽

2021 ◽

Author(s):

Matthew P. Humphreys ◽

Ernie R. Lewis ◽

Jonathan D. Sharp ◽

Denis Pierrot

Keyword(s):

Automatic Differentiation ◽

Dissolved Inorganic Carbon ◽

Total Alkalinity ◽

Carbonate System ◽

Chemical Equilibria ◽

Ph Response ◽

Carbonate Ion ◽

Seawater Ph ◽

Marine Carbonate ◽

Carbon Dioxide Co2

Abstract. Oceanic dissolved inorganic carbon (TC) is the largest pool of carbon that interacts considerably 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 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 was previously available for Python, a popular scientific programming language. 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 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 new insights that arose during the development process, for example that the marine carbonate system cannot be unambiguously solved from the total alkalinity and carbonate ion parameter pair. 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) under the GNU General Public License v3, archived on Zenodo (Humphreys et al., 2021), and documented online (https://PyCO2SYS.readthedocs.io).

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Underestimation of surface pCO2 and air-sea CO2 fluxes due to freshwater stratification in an Arctic shelf sea, Hudson Bay

Elem Sci Anth ◽

10.1525/elementa.084 ◽

2020 ◽

Vol 8 (1) ◽

Author(s):

Mohamed M. M. Ahmed ◽

Brent G. T. Else ◽

David Capelle ◽

Lisa A. Miller ◽

Tim Papakyriakou

Keyword(s):

Sea Ice ◽

River Runoff ◽

Dissolved Inorganic Carbon ◽

Stable Isotope Ratio ◽

Total Alkalinity ◽

Hudson Bay ◽

Co2 Fluxes ◽

Ancillary Data ◽

Ice Melt ◽

The Impact

The objective of this study is to quantify the impact of freshwater stratification on the vertical gradients of partial pressure of CO2 (pCO2) and estimates of air-sea CO2 exchange in Hudson Bay during peak sea-ice melt and river runoff. During the spring of 2018, we sampled water in Hudson Bay and Hudson Strait for dissolved inorganic carbon, total alkalinity, salinity, the oxygen stable isotope ratio in the water (δ18O), and other ancillary data. The coastal domain and regions close to the ice edge had significant vertical concentration gradients of pCO2 across the top meters of the ocean due to the presence of a stratified fresh layer at the surface. The pCO2 and salinity in the central (where sea-ice melt was significant) and the southeast (where river runoff and sea-ice melt were significant) side of the bay generally increased with depth, with average gradients of 4.5 μatm m–1 and 0.5 m–1, respectively. Ignoring these gradients causes a significant error in calculating air-sea CO2 fluxes, especially when using shipboard underway systems that measure pCO2 at several meters below the sea surface. We found that the oceanic CO2 sink in Hudson Bay is underestimated by approximately 50% if underway pCO2 system measurements are used without correction. However, we observed that these gradients do not persist for more than 5 weeks following ice melt. We have derived a linear correction for underway pCO2 measurements to account for freshwater stratification during periods of 1–5 weeks after ice breakup. Given the lack of measurements in stratified Arctic waters, our results provide a road map to better estimates of the important role of these regions in global carbon cycles.

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Intercomparison of carbonate chemistry measurements on a cruise in northwestern European shelf seas

Biogeosciences Discussions ◽

10.5194/bgd-11-2793-2014 ◽

2014 ◽

Vol 11 (2) ◽

pp. 2793-2822 ◽

Cited By ~ 3

Author(s):

M. Ribas-Ribas ◽

V. M. C. Rérolle ◽

D. C. E. Bakker ◽

V. Kitidis ◽

G. A. Lee ◽

...

Keyword(s):

Degrees Of Freedom ◽

Dissolved Inorganic Carbon ◽

Maximum Amplitude ◽

Total Alkalinity ◽

Carbonate Chemistry ◽

Carbonate System ◽

European Shelf ◽

Shelf Seas ◽

The Difference ◽

System Variables

Abstract. Four carbonate system variables were measured in surface waters during a cruise traversing northwestern European shelf seas in the summer of 2011. High resolution surface water data were collected for partial pressure of carbon dioxide (pCO2; using two independent instruments) and pHT, in addition to discrete measurements of total alkalinity and dissolved inorganic carbon. We thus overdetermined the carbonate system (four measured variables, two degrees of freedom) which allowed us to evaluate the level of agreement between the variables. Calculations of carbonate system variables from other measurements generally compared well (Pearson's correlation coefficient always &geq; 0.94; mean residuals similar to the respective uncertainties of the calculations) with direct observations of the same variables. We therefore conclude that the four independent datasets of carbonate chemistry variables were all of high quality, and as a result that this dataset is suitable to be used for the evaluation of ocean acidification impacts and for carbon cycle studies. A diurnal cycle with maximum amplitude of 41 μatm was observed in the difference between the pCO2; values obtained by the two independent analytical pCO2; systems, and this was partly attributed to irregular seawater flows to the equilibrator and partly to biological activity inside the seawater supply and one of the equilibrators. We discuss how these issues can be addressed to improve carbonate chemistry data quality on research cruises.

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Current estimates of K1* and K2* appear inconsistent with measured CO2 system parameters in cold oceanic regions

Ocean Science ◽

10.5194/os-16-847-2020 ◽

2020 ◽

Vol 16 (4) ◽

pp. 847-862 ◽

Cited By ~ 1

Author(s):

Olivier Sulpis ◽

Siv K. Lauvset ◽

Mathilde Hagens

Keyword(s):

Surface Water ◽

Ocean Acidification ◽

Carbonic Acid ◽

Dissolved Inorganic Carbon ◽

Dissociation Constants ◽

Total Alkalinity ◽

Global Ocean ◽

Polar Regions ◽

Carbonate System ◽

System Variables

Abstract. Seawater absorption of anthropogenic atmospheric carbon dioxide (CO2) has led to a range of changes in carbonate chemistry, collectively referred to as ocean acidification. Stoichiometric dissociation constants used to convert measured carbonate system variables (pH, pCO2, dissolved inorganic carbon, total alkalinity) into globally comparable parameters are crucial for accurately quantifying these changes. The temperature and salinity coefficients of these constants have generally been experimentally derived under controlled laboratory conditions. Here, we use field measurements of carbonate system variables taken from the Global Ocean Data Analysis Project version 2 and the Surface Ocean CO2 Atlas data products to evaluate the temperature dependence of the carbonic acid stoichiometric dissociation constants. By applying a novel iterative procedure to a large dataset of 948 surface-water, quality-controlled samples where four carbonate system variables were independently measured, we show that the set of equations published by Lueker et al. (2000), currently preferred by the ocean acidification community, overestimates the stoichiometric dissociation constants at temperatures below about 8 ∘C. We apply these newly derived temperature coefficients to high-latitude Argo float and cruise data to quantify the effects on surface-water pCO2 and calcite saturation states. These findings highlight the critical implications of uncertainty in stoichiometric dissociation constants for future projections of ocean acidification in polar regions and the need to improve knowledge of what causes the CO2 system inconsistencies in cold waters.

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Anomalies in the Carbonate System of Red Sea Coastal Habitats