Inclusion of uncertainty in the calcium-salinity relationship improves estimates of ocean acidification monitoring data quality

Highlights

• Marine carbonate system program seacarb was extended to include [Ca²⁺] uncertainty.

• The effect of deviations from the global [Ca²⁺]-salinity relationship on saturation state (Ω) was quantified.

• Variability associated with coastal systems can reduce data quality, exceeding monitoring guidelines.

• Direct measurement of [Ca²⁺] will increase ocean acidification monitoring data quality in coastal regions.

Abstract

The effects of Ocean Acidification (OA) and the resulting decrease of CaCO₃ saturation state (Ω) on marine organisms and biogeochemistry are observed through regionally dispersed monitoring programs. The standard of data collected by these programs is assessed based on the computed propagated uncertainties of [CO₃²⁻], with data quality regulated by thresholds defined by the Global Ocean Acidification Observing Network (GOA-ON). While these thresholds account for the adoption of lower-cost methods and technologies for carbonate parameter analysis (e.g. pH and total alkalinity), the impacts of salinity measurement and calcium concentration uncertainty on data quality are poorly understood. Currently, the publicly available marine carbonate chemistry uncertainty packages do propagate salinity uncertainty, but do not include [Ca²⁺] uncertainty. In this study, the uncertainty propagation methods in the R-based seacarb package were extended to include [Ca²⁺] uncertainty, and subsequently employed to examine the effects of uncertainty in salinity and [Ca²⁺] on carbonate system calculations. The results indicate that underestimation of uncertainty in [Ca²⁺] is of primary concern in variable coastal waters, where relatively small (<4%) deviations from the global [Ca²⁺]-salinity relationship leads to GOA-ON's quality standards being exceeded. In contrast, the uncertainty in salinity has a relatively minor impact on uncertainty in [CO₃²⁻] and Ω. Given the importance of Ω and its sensitivity to [Ca²⁺], coastal OA monitoring programs should consider whether their region conforms with the global [Ca²⁺]-salinity relationship, and if uncertain should directly measure [Ca²⁺] when calculating Ω.

Introduction

The anthropogenically driven increase of atmospheric pCO₂ from 280 μatm (pre-industrial) to approximately 410 μatm has had many impacts on the global environment (Le Quéré et al., 2015). However, this increase in the atmosphere represents only part of anthropogenic emissions, since the oceans have absorbed approximately 40% of CO₂ emissions since the beginning of the industrial era (Sabine et al., 2004; Zeebe et al., 2008). This oceanic uptake of CO₂ has led to a process known as ocean acidification (OA), whereby the chemical balance of the marine carbonate system has shifted towards the production of hydronium (H₃O⁺) and bicarbonate (HCO₃⁻) ions and the reduction of carbonate ions (CO₃²⁻) (Dickson et al., 2007). Although the full impact of these changes is still being explored, it is clear that the effects on ocean chemistry, physical properties, ocean ecosystems, and biogeochemical processes will be substantial and long-lasting (Guinotte and Fabry, 2008; Hofmann et al., 2010; Kroeker et al., 2013).

Our ability to monitor and assess the impacts of OA relies on an accurate representation of the marine carbonate system. The marine carbonate system can be characterized with knowledge of any two of the four carbonate parameters of an oceanographic water sample: pH, pCO₂, dissolved inorganic carbon concentration (DIC), and total alkalinity (A_T), along with the appropriate thermodynamic equilibrium constants and ancillary data, e.g. salinity, temperature, pressure, and total phosphorus and silicate concentrations. When characterising the marine carbonate system, the uncertainty of each output variable will depend on the measurement uncertainty of chemical and physical parameters (e.g. DIC, A_T, salinity, temperature), as well as the uncertainty in the thermodynamic equilibrium constants (Millero, 2007).

To estimate the uncertainty in output carbonate variables (e.g. [H⁺], [CO₃²⁻], Ω_A, Ω_C), Orr et al. (2018) recently expanded several of the open-source carbonate system software packages to allow routine propagation of uncertainty in both measurements and thermodynamic constants. The uncertainty estimation methods implemented in these widely used software packages are based on previous work, which introduced approaches based on Gaussian uncertainty propagation (Dickson and Riley, 1978; Millero, 1995) and Monte Carlo simulations (Fassbender et al., 2017; Williams et al., 2017). Both methods are included in the R-based seacarb package(Jean-Pierre Gattuso et al., 2020), which allows direct comparison between the approaches; the other packages only support Gaussian uncertainty propagation (Orr et al., 2018).

Studies into uncertainty estimates using these revised software packages have focused on the contribution of the carbonate input pair (e.g. A_T – DIC, pH – A_T) and the thermodynamic constants (Orr et al., 2018). However, there has been little consideration into the effects of uncertainty in salinity measurements and calcium ion concentration upon the standard uncertainty of carbonate system calculations. Salinity is a fundamental property of the marine carbonate system, affecting thermodynamic equilibrium constants and physical properties of seawater (e.g. density). Although uncertainty in salinity is included as an input parameter in the uncertainty packages, the effect of salinity uncertainty has been largely ignored because measurements made with the high quality salinometers or CTD instruments used by experienced laboratories are generally considered to have an uncertainty of only ±0.002 (or 0.005% at S = 35) on the Practical Salinity Scale (PSU) (Le Menn, 2011). However, the measurement uncertainty of the salinometers and conductivity meters which are commonly used in coastal studies and by emerging laboratories can be much higher, e.g. 1% for the YSI Pro30 (YSI, USA) and 2% for HI 98194 (HANNA instruments, Italy). These relative uncertainties eclipse the typical uncertainties associated with the other carbonate parameters (Table 1). Thus, the impact of salinity uncertainty on carbonate system characterisation must be determined in order to properly assess the impacts of OA.

Another source of uncertainty in carbonate system characterisation that has received little consideration is the effect of uncertainty in the calcium ion concentration, [Ca²⁺], which is required for determination of the saturation state of aragonite (Ω_A) and calcite (Ω_C), the two common polymorphs of CaCO₃ found in marine systems. In most carbonate system characterisation software packages, [Ca²⁺] is calculated from the conservative [Ca²⁺]-salinity relationship empirically determined by Riley and Tongudai (1967), which found the [Ca²⁺]-salinity ratio to be 2.938 × 10⁻⁴ mol kg⁻¹ PSU⁻¹ when averaged across all major ocean basins and depths. Two sources of [Ca²⁺] uncertainty can be derived from the use of this relationship: the direct impact of salinity measurement uncertainty on [Ca²⁺] calculation, and unknown deviations from the expected ratio. In the open ocean, deviations from this global mean [Ca²⁺]-salinity relationship are generally small (≈0.2%), so it is deemed unnecessary to consider localised variability in [Ca²⁺] in Ω uncertainty estimations (Atwood et al., 1973; Besson et al., 2014; Culkin and Cox, 1966; Krumgalz, 1982). However, some studies have demonstrated greater spatial and temporal divergence from the global oceanic mean [Ca²⁺]-salinity relationship (Rosón et al., 2016; Sharp and Byrne, 2019; Tsunogai et al., 1968). In an extreme case, temporal variations in the [Ca²⁺]-salinity ratio of up to 10% of the global mean was measured in the Sargasso Sea (Billings et al., 1969). Temporal variations in the chemistry of coastal waters, which are affected by riverine inputs, geological weathering of calcium–rich environments, the production or dissolution of CaCO₃, and upwelling of deep water have also been observed (Beckwith et al., 2019; Jiang et al., 2014; Mathis et al., 2011). In coastal waters of the Bay of Bengal the average [Ca²⁺]-salinity ratio of coastal waters was approximately 5–8% higher than the global open ocean relationship (Das and Sahoo, 1996; Sen Gupta et al., 1978). Nessim et al. (2015) found the [Ca²⁺]-salinity ratio in waters of the Egyptian Mediterranean coastline varied seasonally, and were on average 18% lower than the global average. Clearly, because of the direct proportionality between [Ca²⁺] and Ω, consideration and accommodation of variability in the [Ca²⁺]-salinity ratio in carbonate system characterisation would improve the accuracy and reliability of OA monitoring efforts in coastal waters.

Although the implications of [Ca²⁺]-salinity variabilities on Ω determinations and carbonate system monitoring have been noted in previous studies (Wanninkhof et al., 2015), [Ca²⁺] uncertainty is not an included variable in any of the uncertainty propagation packages. This exclusion leads to inaccuracies in Ω calculations and underestimation of relative standard uncertainty of Ω. Here, we examine the effects of uncertainty in salinity and the [Ca²⁺]-salinity relationship on carbonate system calculations using seacarb's Gaussian uncertainty propagation and Monte Carlo simulations. The published routines were updated to accurately simulate the effect of larger salinity measurement uncertainties and, for the first time, these routines include the effect of [Ca²⁺] uncertainty. Salinity and [Ca²⁺] uncertainties of up to 5% were shown to increase the propagated combined uncertainties of [CO₃²⁻] and Ω_A by approximately 20% and 50%, respectively. These increases in carbonate system output uncertainties have substantial implications on OA monitoring data quality. Incorporation of [Ca²⁺] uncertainty into the updated routines provides more accurate carbonate system characterisation.