# The Alkalinity Generation Potential of Olivine and Oyster Shell for Laboratory Experiments: Testing the Effects of Ocean Alkalinity Enhancement

Cale Miller, Fabrice Pernet

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Cale Miller, Fabrice Pernet. The Alkalinity Generation Potential of Olivine and Oyster Shell for Laboratory Experiments: Testing the Effects of Ocean Alkalinity Enhancement. Environmental Research Communications, 2025, 7 (7), 075025 (12p.). 10.1088/2515-7620/adf0cd hal-05206209

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# The alkalinity generation potential of olivine and oyster shell for laboratory experiments: testing the effects of ocean alkalinity enhancement

To cite this article: Cale A Miller and Fabrice Pernet 2025 *Environ. Res. Commun.* 7 075025

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# The alkalinity generation potential of olivine and oyster shell for laboratory experiments: testing the effects of ocean alkalinity enhancement

Cale A Miller¹,* and Fabrice Pernet² ID

¹ Department of Earth Sciences, Geosciences, Utrecht University, The Netherlands

² Ifremer, Université de Brest, CNRS, IRD, LEMAR, F-29840 Argenton, France

* Author to whom any correspondence should be addressed.

E-mail: c.a.miller@uu.nl

**Keywords:** ocean alkalinity enhancement, carbonate chemistry, olivine, dissolution

Supplementary material for this article is available [online](#)

## Abstract

Ocean alkalinity enhancement has emerged as a predominant line of marine carbon dioxide removal research. Of paramount importance associated to OAE application is the need to understand the biological impacts. Within this context, we present a framework for generating alkaline solutions, based on an alkalinity generation potential from the dissolution of olivine (Mg-silicate) and biogenic calcium carbonate (CaCO$_3$) in seawater that can be used for conducting biological experiments. Using established dissolution rates for both minerals as a scaling factor, we show that olivine dissolution can generate enriched seawater solutions of 9000 µmol kg$^{-1}$ above background alkalinity when dissolving at a pH between 5.5–6.5. Similarly, CaCO$_3$ dissolution from crushed oyster shell reached ~10000 µmol kg$^{-1}$ at a calcite saturation state of < 0.1. Further, we assessed the sensitivities of carbonate chemistry dissociation constants and the calcium carbonate solubility on subsequent enrichment of Mg$^{2+}$ and Ca$^{2+}$ from mineral dissolution. This was done by modifying the calculations in CO2SYS (Matlab v3). The results showed that increased [Ca$^{2+}$] raises pH by 0.4 units above non-enriched seawater, while enriched [Mg$^{2+}$] lowers pCO$_2$ values by 20 µatm. Thus, we demonstrate how to produce necessary experimental conditions for a wide range of applications when testing biological sensitivities to OAE while accounting for the modifications to the carbonate system.

## 1. Introduction

Since the industrial revolution, the ocean has taken up ~30% of anthropogenic CO$_2$ emissions with an increasing rate of 2.6 Pg C yr$^{-1}$ since the beginning of the 21st century [1, 2]. As emissions reductions alone are unlikely to limit warming to 1.5–2 °C [3], CO$_2$ removal (CDR) techniques are suggested to be deployed in congruence with emissions reduction [4–6]. Thus, leveraging the ocean’s natural sequestration potential to enhance CO$_2$ uptake is referred to as marine carbon dioxide removal (mCDR). Ocean alkalinity enhancement (OAE) is one mCDR method that has been deemed as a potential viable way to increase the uptake of CO$_2$ by the ocean [4, 7]. This involves increasing the buffering capacity of the ocean which is driven predominantly by silicate weathering—operating on timescales of tens to hundreds of thousands of years [8]. Enhancing the dissolution and, thus, total alkalinity (TA) of the ocean by dissolving alkaline minerals in seawater has the potential to increase the buffering capacity of the ocean. This process enhances the disequilibrium between oceanic and atmospheric pCO$_2$ facilitating ocean CO$_2$ uptake [9, 10]. However, many considerations remain regarding the application of OAE, including the potential effects on biological organisms, secondary precipitation (i.e., reprecipitation of dissolved alkaline minerals in situ), and the efficiency of CO$_2$ flux into the ocean [11–15].

Deployment methods for OAE involve the direct release of crushed alkaline minerals such as Forsterite which is a type of olivine (MgSiO$_4$), Brucite (Mg(OH)$_2$), Calcite (CaCO$_3$), or Portlandite (Ca(OH)$_2$) in surface
waters, or by injecting an alkaline solution from pre-dissolved minerals (i.e., accelerated weathering) [14, 16]. Despite the deployment approach, there lacks a significant understanding of the biological impacts at the physiological, ecological, and molecular levels under OAE conditions [17]. The limited studies investigating the effects of OAE on organisms have primarily focused on phytoplankton by creating alkaline solutions from research grade minerals (high quality, low impurities) and olivine leachates [18–22]. A spectrum of observations have been recorded from these experiments making direct effects difficult to assess. The effects on phytoplankton appear to be dependent on the culture strain and species, or the mineral type and or quality. Thus, a standard methodology may be needed to elucidate the results. For example, a neutral response to alkalinization from Na₂CO₃ and olivine for calcifying and silicate producing phytoplankton have been recorded [18, 19]. This was similar to observations for diatoms and cyanobacteria under NaOH alkalinization [21, 23]. However, growth as a metric decreased depending on the exposure period [23]. Finally positive, negative and neutral responses of cyanobacteria have been recorded when exposed to CaO, olivine, and NaOH, respectively [21]. We note that these studies only moderately increased TA to levels < 2700 µmol kg⁻¹, with the exception of one study which doubled ambient TA to 4800 µmol kg⁻¹. Important to biological assessments, however, is the need to determine threshold and tipping points over a gradient of conditions. Such approaches provide a clear picture of leachate differences from mineral impurities, and potential acute exposure periods to trace elements and high pH.

Equally important are considerations to the shifts of carbonate system constituents when enhancing alkalinity. That is, the individual carbonate system variables will speciate differently under alkalinization, and each variable (i.e., pH, pCO₂, saturation state) acts a specific driver of biological response [24]. Finally, considerations to changes in major ion concentrations (e.g., Ca, Mg) and trace metals (e.g., Ni) released from mineral dissolution need to be carefully monitored. Thus, when assessing biological responses and methodological approaches, a clear understanding of organismal sensitivities is crucial as is the behavior of mineral dissolution (i.e., full or partial dissolution, secondary precipitates, and release of impurities) in seawater [17]. To accommodate such research initiatives, a clear and formulated experimental approach for producing the geochemical conditions of alkaline enriched seawater is needed.

In this study, we present and assess a procedure for TA enrichment of seawater via enhanced weathering of alkaline minerals. We present a model framework for estimating the alkalinity generation potential using industrially produced olivine and ground oyster shell (CaCO₃) materials for the purpose of conducting OAE organismal experiments. The dissolution process occurs under high pCO₂ conditions to enhance mineral solubility and can be applied to other alkaline materials (e.g., MgOH, NaOH). We propose two simple models that describe the alkalinity generation potential derived from established mineral dissolution rates, the changes in major ion concentrations (Ca²⁺ and Mg²⁺), and the effects of mineral dissolution on carbonate chemistry. This analysis provides a set of conditions needed to produce high alkaline solutions and refinements to the thermodynamic carbonate chemistry calculations in CO₂SYS (Matlab v3) [25], which now accommodates changes to [Ca²⁺] and [Mg²⁺] in seawater [26].

## 2. Methods

### 2.1. Alkaline minerals

Olivine and oyster shell (CaCO₃) materials were selected as alkaline substances to increase seawater TA via accelerated weathering. Olivine is a common magnesium silicate in ultramafic rocks, while oyster shell is primarily composed of biogenic calcium carbonate—both materials are abundant and reactive under acidic conditions, making them suitable for OAE. The Mg-silicate mineral olivine can react with seawater undergoing acid hydrolysis to consume excess protons (H⁺) following the reaction:

$$Mg_2SiO_4 + 4H_2CO_3 \rightarrow 2Mg^{2+} + H_4SiO_4 + 4HCO_3^- \quad (1)$$

where one mole of olivine dissolves by reacting with four moles of H₂CO₃, effectively consuming four H⁺. While this process does not directly release alkalinity species like CO₃²⁻, it removes protons from solution, leading to an increase in HCO₃⁻ and TA.

To clarify the broader context, we note that CO₂ dissolution into seawater does not alter TA: the increase in dissolved inorganic carbon (DIC) is exactly offset by an equal increase in H⁺. However, when this process is coupled to olivine dissolution, the H⁺ generated from H₂CO₃ dissociation are consumed. This shifts the carbonate system equilibrium modifying both TA and DIC speciation:

(1) Olivine dissolution consumes excess H⁺ decreasing seawater pCO₂ →

(2) Lower pCO₂ promotes further CO₂ uptake from the atmosphere increasing DIC in seawater →
<table><caption>**Table 1.** Parameters for the olivine and oyster shell models, equation (8) in main text. The minimum (min.) and maximum (max.) rate columns are the dissolution rates at the highest pH and Ω threshold value (min. rate), and at the lowest value (max. rate). DIC step is the µmol kg⁻¹ increase per model step. Rate values used are reported in Hefmanská *et al* 2022 [32] for olivine, and Ries *et al* 2016 [33] and Cubillas *et al* 2005 [34] for CaCO₃.</caption><thead><tr><th>Model</th><th>TA initial<br>(µmol kg<sup>-1</sup>)</th><th>DIC initial<br>(µmol kg<sup>-1</sup>)</th><th>DIC Step<br>(µmol kg<sup>-1</sup>)</th><th>Thresholds</th><th>Min. rate<br>(mols cm<sup>-2</sup> s<sup>-1</sup>)</th><th>Max. rate<br>(mols cm<sup>-2</sup> s<sup>-1</sup>)</th></tr></thead><tbody><tr><td>Olivine</td><td>2300</td><td>2000</td><td>4</td><td>8.0, 7.5, 6.5,<br>5.5 (pH)</td><td>7.57 × 10<sup>-15</sup></td><td>4.23 × 10<sup>-14</sup></td></tr><tr><td>Oyster shell</td><td>2300</td><td>2000</td><td>4</td><td>1.5, 1.0, 0.8, 0.6, 0.4,<br>0.2 (Ω)</td><td>1.82 × 10<sup>-11</sup></td><td>1.36 × 10<sup>-9</sup></td></tr></tbody></table>

(3) The higher proportion of H₂CO₃ from CO₂ incursion increases [H⁺] →

(4) The H⁺ generated enhances olivine dissolution, which in turn dissolves more olivine increasing TA

This feedback loop needs to be considered when conducting experiments using an olivine-based mCDR method—given that the term enhancement by olivine is not precisely correct. Further, increases in Si and Mg from olivine dissolution will change the sensitivity of the carbonate system dissociation constants and the calcium carbonate solubility product by modifying the ion activity of CO₃²⁻, as Mg²⁺ potentially binds with excess CO₃²⁻ [27–30]. The thermodynamic effects of excess Si(OH)₄ are minor, but if at supersaturated conditions, high concentrations have been shown to potentially inhibit CaCO₃ precipitation [27, 31].

The dissolution of CaCO₃ in seawater generates alkalinity at a net 2:1 ratio of TA to DIC when reacting with H₂CO₃:

$$CaCO_3 + H_2CO_3 \rightarrow Ca^{2+} + 2HCO_3 \quad (2)$$

where one mole of H₂CO₃ is consumed to produce two moles of HCO₃⁻. Dissolution of CaCO₃ has the added effect of increasing the [Ca²⁺] affecting the kₛₚ (solubility product) and saturation state of the CaCO₃ polymorph calcite (Ωₛₚ). Given that ocean surface waters are supersaturated with respect to CaCO₃, its dissolution is expressed as the thermodynamic stability of the mineral where Ωₛₚ > 1 favors precipitation, and an Ωₛₚ < 1 favors dissolution:

$$\Omega = \frac{[Ca^{2+}][CO_3^{2-}]}{k_{sp}} \quad (3)$$

where kₛₚ differs for the aragonite or calcite polymorph.

Active dissolution of both olivine and CaCO₃ minerals in seawater can be facilitated by acidic conditions or the undersaturation of the mineral. Thus, either acidic conditions from low pH or the undersaturation of calcium carbonate (as natural seawaters are found to be supersaturated with respect to CaCO₃) will impact the dissolution potential of olivine and CaCO₃, respectively.

## 2.2. Producing experimental alkaline solutions

A general approach for producing alkaline solutions must assess all dissolved mineral constituents from the produced effluent. This includes changes to major ion concentrations, increases in TA, modifications to carbonate chemistry, and trace metal enhancement. We focus primarily on the former three aspects. The adopted experimental method proceeds by:

(1) Collecting natural seawater (see table 1) pumped into the Ifremer (Institut Français de Recherche pour l'Exploitation de la Mer) experimental lab (Landunvez, France, 48° 31.2768' N, -4° 46.1016' W) filtered at 1 µm in an appropriate container based on the required media volume, and then stirred.

(2) Reducing the pH and Ω by vigorously bubbling with CO₂ gas until reaching CO₂ saturation (pH_T < 5.5, Ωₛₚ = 0.2).

(3) Add alkaline mineral to the continuously CO₂-bubbled and stirred seawater (open system at temperatures between 20 to 25 °C) enhancing dissolution.

(4) Bubble with air to equilibrate to background pH or pCO₂ once target alkalinity is achieved.

(5) Filtering the alkaline enriched seawater at ≤ 0.45 µm to remove undissolved and reprecipitated minerals.
This methodological approach was applied experimentally (Table S1) and used to create a model quantifying the production of high alkaline solutions from dissolved olivine (grain size 200–700 µm) and crushed oyster shell (grain size 200–300 µm) via acid hydrolysis. This was done by associating dissolution to changes in DIC, which in turn lowered seawater pH and Ω<sub>ca</sub>, thereby enhancing dissolution. The model construction assessed final stock solution values between 11000–15000 µmol kg<sup>-1</sup>, which align to those achieved experimentally in practice (Table S1). We report this range for the purposes of the presented model. The model formulation is a generic method applied when conducting OAE experiments under a wider range of conditions:

$$ \Delta TA = \begin{cases} 0, & \text{if pH} > \text{pH}_{\text{thres}}, \Omega_{\text{thres}}. \\ S_{\text{pH},\Omega}*(\text{DIC}_j - \text{DIC}_{\text{initial}}), & \text{if pH} \le \text{pH}_{\text{thres}}, \Omega_{\text{thres}}. \end{cases} \quad (4) $$

Parameterization requires a scalar (S) derived from known dissolution rates (as a proportion to a maximum rate), and threshold points of pH and Ω<sub>ca</sub>, for olivine and CaCO<sub>3</sub>, respectively. Thus, active dissolution commences at step j along with TA and DIC from given starting points (table 1, equation (8)).

### 2.3. Alkalinity generation potential

Producing high alkaline solutions via CaCO<sub>3</sub> or olivine dissolution for biological experimentation using the above formulation (equation (4)) is first approached by deriving an alkalinity generation potential (AGP) based on dissolution rates. Thus, we do not specifically consider the time it takes for dissolution following steps 1–5 (section 2.2), but rather, use dissolution rates specifically to define the potential for alkalinity generation. The majority of quantified olivine dissolution rates in aqueous solutions is limited to freshwater and artificial seawater; however, evidence of dissolution rates for olivine in natural seawaters are in agreement with those derived from other aqueous solutions [35]. The olivine dissolution rates used in this model were selected from Heřmanská et al (2022) [32] who report values as a function of pH normalized to grain surface area. Only rates at 25 °C were selected and then fit to a 2nd order polynomial (fig. S1, table S1). We define the AGP as a ratio of a dissolution rate (r) at a pH threshold value over the maximum dissolution rate at the lowest selected pH (equation (5)). Four nominal pH threshold values were selected (table S1), where maximum dissolution occurs at a pH of 5.5, the approximate pH value of saturated CO<sub>2</sub> in seawater (depending on the starting TA value).

$$ AGP_o = \frac{r_{\text{pH}_{\text{thres}}}}{r_{\text{pH}_{5.5}}} \quad (5) $$

describes the relative AGP for olivine (AGP<sub>o</sub>) at a given pH threshold, which is a scalar of a proportional dissolution rate (r mol cm<sup>-2</sup> s<sup>-1</sup>): rate at pH<sub>thres</sub> over the rate at pH<sub>5.5</sub>.

For CaCO<sub>3</sub> dissolution, the modeling approach for AGP used the dissolution rate equation for when Ω<sub>ca</sub> was < 1, and followed an exponential asymptote function (Ries et al 2016) [33] when Ω<sub>ca</sub> was > 1:

$$ r = \begin{cases} B_0 + B_2 * e^{(B_1 \Omega)} & \text{if } \Omega > 1 \\ k(1 - \Omega)^n & \text{if } \Omega \le 1. \end{cases} \quad (6) $$

The dissolution rate r (mol cm<sup>-2</sup> s<sup>-1</sup>) is derived using an experimentally derived rate constant (k = 1.82 × 10<sup>-10</sup>), Ω<sub>ca</sub>, and the reaction order (n). Experimental dissolution rates derived from crushed mussel shells at 25 °C from Cubillas et al (2005) [34] were used for calculating rates with an Ω<sub>ca</sub> < 1. All reported rates from Cubillas et al (2005) were pre-normalized to a geometric surface area. A reaction order of 2.93 was selected for seawater [36]. Dissolution rates for Ω<sub>ca</sub> > 1 were calculated using the B<sub>0–2</sub> coefficients from the model output provide by Ries et al (2016, table 4) [33] for the dissolution of Crassostrea virginica—with the caveat that rates are from whole-shell measurements.

The AGP for CaCO<sub>3</sub> dissolution was calculated as:

$$ AGP_c = \frac{r_{\Omega_{\text{thres}}}}{r_{\Omega_{0.2}}} \quad (7) $$

where the AGP<sub>c</sub> is the relative alkalinity generation potential for CaCO<sub>3</sub>.

Alkalinity generation for olivine and CaCO<sub>3</sub> was estimated using the following expression:

$$ TA_j = TA_{\text{initial}} + AGP_{o,c} * (DIC_j - DIC_{\text{initial}}) \quad (8) $$

which tracks how much alkalinity is generated at each step (j) as DIC increases, linking alkalinity increase directly to the pH-dependent alkalinity generation potential (AGP<sub>o,c</sub>) of the dissolving material. The starting point of DIC<sub>initial</sub> was set approximately equal to background ambient seawater level (table 1). The model step increased DIC by 4 µmol kg<sup>-1</sup> up to 8750 µmol kg<sup>-1</sup>, which produced low pH and Ω values at a constant TA simulating CO<sub>2</sub> invasion (i.e., experimental CO<sub>2</sub>-bubbling). TA<sub>j</sub> represents the total alkalinity at step j added to TA<sub>initial</sub> for either olivine or CaCO<sub>3</sub> (table 1). TA values were consistently 2300 ± 10 µmol kg<sup>-1</sup> and DIC ~2000 ± 15 µmol kg<sup>-1</sup> calculated from measured TA and pH of ambient seawater at Sité Experimental d'Argenton
(Ifremer) in summer of 2024. These TA and DIC starting points were input into CO2SYS using an ambient salinity of 35 and warmed seawater at 25 °C to generate pH and Ω values.

## 2.4. Modifications to the carbonate system

The release of Mg²⁺ and Ca²⁺ when dissolving olivine and CaCO₃ shifts the acid–base equilibria in seawater requiring modifications to the thermodynamic calculations performed in programs like CO2SYS (Matlab, Excel, Python) and Seacarb (R). In small-scale laboratory experiments, the alkaline mineral additions are usually minor enough that the assumptions of seawater complexity and ionic strength remain valid. For example, at the oceanic scale, the vast volume and high baseline [Mg²⁺] and [Ca²⁺] mean that any relative perturbation is proportionally small (e.g., a 0.9 mmol kg⁻¹ increase in Ca²⁺ is < 0.3% annual change in surface ocean Ca²⁺) [14]. Nonetheless, the Kₛₚ and carbonic acid dissociation constants (K₁, K₂) are sensitive to shifts in [Mg²⁺] and [Ca²⁺], and must be accounted for when calculating carbonate chemistry parameters [29].

Modifications to the CO2SYS program (Matlab v3, [26]) have been made to account for carbonic acid dissociation constant sensitivity to Mg²⁺ and Ca²⁺ based minerals utilizing the coefficients from Ben-Yaakov & Goldhaber [27]. Here, we used the measured changes (section 3.2) in [Mg²⁺] and [Ca²⁺] from our associated experimental work (steps 1–5 in section 2.2) to derive carbonate chemistry parameters for both olivine and CaCO₃ dissolution at two constant TA values: 5000 and 11000 µmol kg⁻¹. Concentrations of Mg²⁺ and Ca²⁺ were measured on an AVIO500 ICP-OES (Perkin Elmer) at the Utrecht University Geolab. The sensitivity factors for Mg²⁺ and Ca²⁺ were calculated based on the measured increase, Δnᵢ, from a baseline (nᵢ) concentration as:

$$ \frac{\Delta n_i}{n_i} = \frac{Mg, \quad Ca_{measured}}{Mg, \quad Ca_{background}} - 1 \qquad (9) $$

where

$$ \frac{\Delta k_{1,2}}{k_{1,2}} = S_i * \frac{\Delta n_i}{n_i}, \qquad (10) $$

and Sᵢ is the sensitivity factor presented from Ben-Yaakov and Goldhaber [27] for the K₁, K₂ dissociation constants. Measured [Mg²⁺] and [Ca²⁺] have been made as input arguments in CO2SYS to be entered as ppt (g/ kg) [26]. For the Ca²⁺ based script, the measured input data overwrites the current derivation of [Ca²⁺] from salinity. The calcium carbonate Kₛₚ sensitivity to the Mg:Ca ratio was modified as:

$$ K_{sp} (Mg: Ca_{meas.}) = K_{sp} (Mg: Ca_{back}) - \alpha * (Mg: Ca_{back} - Mg: Ca_{meas.}), \qquad (11) $$

which is provided by Tyrrell and Zeebe [30], where α is the scalar presented in Mucci & Morse [37]. For the Ca²⁺ based script, the final output Ωₐₐₐᵣ value uses the overwritten [Ca²⁺] from the input argument [26]. The measured Mg:Caₘₐₙₐ. ratio has been added as an input argument to the function as a molar ratio (mol kg⁻¹). The background ratio (Mg:Caₐₙₐ) uses the chlorinity-salinity relationship (already utilized in the original CO2SYS version to calculate [Ca²⁺] from salinity) as described in Riley & Tongudai [38]. We note that this modification is specific to calcite Kₛₚ but was applied in the modified scripts to both aragonite and calcite Kₛₚ given that the sensitivities [26] should be proportional for both mineral polymorphs.

# 3. Results

## 3.1. Model results for AGP

The olivine dissolution model projected limited alkalinity generation at a pHₜ (total scale) threshold of 8.0 where AGP reached ~3000 µmol kg⁻¹ (figure 1). The limited dissolution occurring at pHₜ > 6.5 indicates a low dissolution rate relative to those below a pHₜ of 6.5. In contrast, a low pH threshold enhanced the dissolution rate between pHₜ 5.5–6.5 as the AGP increased 3x compared to higher pHₜ thresholds. At the lowest pHₜ threshold of 5.5, the estimated mean increase in TA was 0.45 µmol kg⁻¹ for each stepwise DIC addition (+4 µmol kg⁻¹). This reflects a several fold increase in AGP compared to scenarios with higher pH thresholds, highlighting the enhanced dissolution efficiency under more acidic conditions (figure 1). Thus, the TA increase predicted by olivine dissolution is not strictly additive over time, as dissolution primarily acts to buffer excess H⁺ rather than continuously introducing alkalinity into the system. This buffering process means that alkalinity generation is self-limiting and tied to the continued acidification caused by CO₂ uptake, rather than representing a constant source of alkalinity. The high DIC values (> 8000 µmol kg⁻¹) characteristic of the highest potential generation of TA demonstrate this phenomenon, which contrasts with CaCO₃ AGP (figure 2). We note that such low pH values carry large uncertainty when using CO2SYS to predict carbonate chemistry values. This does not, however, disaffirm the clear differences between the olivine and CaCO₃ end points during mineral dissolution for both models as the uncertainties lie in pCO₂ and pH values, not the overall DIC (figures 1, 2).
<figure><img src="image_5.png" /><figcaption>**Figure 1.** Model estimates of alkalinity generation from olivine dissolution at four different pH~T~ threshold values. Bar plot shows the mean rate of TA generation per model step (+4 DIC µmol kg⁻¹).</figcaption></figure>

The CaCO₃ dissolution model displayed an additive AGP due to the applied dissolution rate function and addition of TA at a 2:1 ratio, which contrasts with the olivine model that employed a hard threshold pH cutoff (figures 1, 2). The pH~T~ from the model output ranged from 5.4 to 9.64 with concomitant increases in Ω~ca~ from 0.02 to 18.3 (figure 2). At the highest dissolution threshold (Ω~ca~ = 1.5; pH~T~ = 7.42), the AGP proceeded at a tenfold slower rate compared to when Ω~ca~ was between 0.8–1.0 (figure 2). Thus, lowering the dissolution threshold to Ω~ca~ values between 0.2 and 0.4 resulted in an ~ twofold increase in AGP compared to a threshold between 1.5 and 1.0 (figure 2). Further reduction of Ω~thres~ led to an exponential increase in AGP, with values approaching 10000 µmol kg⁻¹. This response highlights the non-linear sensitivity of CaCO₃ dissolution to undersaturation, where increasingly acidic conditions accelerate mineral breakdown and associated alkalinity release. Such estimates underscore the critical role of dissolution thresholds in controlling the efficiency, particularly under elevated CO₂ scenarios. The model estimates of projected AGP align well with the associated experimental work. That is, TA generation following the steps in section 2.2 from CaCO₃ and olivine dissolution produced values between 11000–15000 µmol kg⁻¹ whereas the model estimates display an AGP at ~10000 µmol kg⁻¹ for both minerals.
<figure><img src="image_6.png" /></figure>

## 3.2. Mineral driven effects on carbonate chemistry

The modified CO2SYS calculations for either $Mg^{2+}$ or $Ca^{2+}$ enriched stock solutions at TA values of 5000 and 11000 $\mu$mol kg$^{-1}$ resulted in slightly divergent variable estimates between olivine and $CaCO_3$, due to the distinct release of major cations (figure 3). The dissolution of oyster shell and olivine increased $[Ca^{2+}]$ and $[Mg^{2+}]$ from 400 to 600 ppm (10 mmol kg$^{-1}$ to 15 mmol kg$^{-1}$) and from 1225 to 1310 ppm (50.5 mmol kg$^{-1}$ to 54.2 mmol kg$^{-1}$), respectively. For a stock solution TA of 5000 $\mu$mol kg$^{-1}$, atmosphere equilibration to a $pH_T$ of 8.25 resulted in a final DIC of ~4000 $\mu$mol kg$^{-1}$ for both minerals (figure 3). In contrast, when preparing a stock solution with a target TA of 11000 $\mu$mol kg$^{-1}$, the final equilibrated DIC exceeded 8700 $\mu$mol kg$^{-1}$ (figure 3).

The effect of equilibrating to a $pCO_2$ of 420 $\mu$atm resulted in a lower DIC for both the 5000 and 11000 $\mu$mol kg$^{-1}$ TA scenarios compared to a pH-equilibrated solution. However, the $pH_T$ endpoint of the $pCO_2$-equilibrated stock solution resulted in a higher than ambient pH value of ~8.3 and 8.55 for the 5000 and 11000 $\mu$mol kg$^{-1}$ scenarios, respectively. Overall, DIC was lower by 1.5 and 11% for the $pCO_2$ equilibrated stock solutions at 5000 and 11000 $\mu$mol kg$^{-1}$, respectively, compared to the pH-equilibrated scenarios (figure 3). We note that the differences observed in $pCO_2$ in figure 3 when pH is at 5.5 have a high degree of uncertainty as CO2SYS is incapable of providing accurate values at such extreme conditions. However, once re-equilibration occurs, and pH reaches values of natural seawater, the differences become apparent and accurate. The extremely high DIC values when $pH_T < 7.0$ likely create stochastic DIC speciation and out-gassing, thus, interpretation under these conditions are best kept at examining the magnitude differences between creating enriched alkaline solutions of 5000 and 11000 $\mu$mol kg$^{-1}$.

The differences across the derived carbonate chemistry parameters using the modified CO2SYS functions displayed a consistent offset for $pH_T$, $pCO_2$, and $\Omega_{ca,ar}$ when compared to the standard (i.e., non-enriched seawater) CO2SYS function at a TA of 5000 $\mu$mol kg$^{-1}$ (figure 4). The sensitivity effect from enhanced $Mg^{2+}$ shifted the $pH_T$ by 0.02 units above non-enriched conditions (figure 4(a)). This sensitivity effect was even greater for enhanced $Ca^{2+}$, which increased $pH_T$ by 0.04 units above non-enriched conditions (figure 4(a)). The effect on $pCO_2$ from $Mg^{2+}$ enrichment was ~20 $\mu$atm below non-enriched conditions, whereas the effect of $Ca^{2+}$ compared to non-enriched conditions was negligible (figure 4(b)). Enriched $Ca^{2+}$ conditions drove extreme
<figure><img src="image_7.png" /><figcaption>**Figure 3.** Simulation of pH and pCO₂ equilibration to ambient seawater conditions following an experimental decrease in pH<sub>T</sub> via CO₂ bubbling to drive dissolution of olivine or CaCO₃ minerals generating enriched TA stock solutions of 5000 µmol kg⁻¹ and 11000 µmol kg⁻¹. Different markers indicate stock solutions enriched with either Mg²⁺ or Ca²⁺ from olivine or CaCO₃, respectively, along with a non-Mg²⁺ or Ca²⁺ enriched control. Note the different x-axis scales between the top and bottom row plots.</figcaption></figure>

<figure><img src="image_8.png" /><figcaption>**Figure 4.** Results using the CO2SYS function modified to accommodate increases in either Mg²⁺ or Ca²⁺. Results simulate an enriched TA of 5000 µmol kg⁻¹. Different markers indicate enrichment of Mg²⁺, Ca²⁺ or non-enriched conditions for (a) pH<sub>T</sub>, (b) pCO₂, (c) Ω<sub>ca</sub> and (d) Ω<sub>ar</sub>.</figcaption></figure>

differences from enriched Mg²⁺ and non-enriched conditions for both calcite and aragonite Ω<sub>ca,ar</sub> values, which were ~14 to 8 units higher (e.g., when DIC was 4000; figure 4(c), d), respectively.

**4. Discussion**

This study provides a dynamic model for quantifying the alkalinity generation potential associated with the dissolution of minerals such as olivine and biogenic CaCO₃, parameterized as a function of carbonate system variables, including pH and Ω. In addition, we provide modified functions for CO2SYS used to determine the carbonate system variables [26] when seawater is enriched with Mg²⁺ and Ca²⁺, a missing component when
conducting OAE based experiments [29]. By applying known dissolution rates of alkaline minerals into the model, the AGP estimated for olivine and CaCO₃ minerals demonstrated an alignment with the experimental data presented (table S1), signifying that both are suitable for creating highly enriched alkaline solutions. The effects of major cation release in the forms of Mg²⁺ and Ca²⁺ were shown to modify the sensitivity of the carbonate system to varying degrees, where enriched Mg²⁺ lowered pCO₂ relative to non-enriched and Ca²⁺-enriched seawater conditions. Alternatively, Ca²⁺ enrichment increased pH_T and saturation states comparatively. The sensitivities of the carbonate system to both Mg²⁺ and Ca²⁺ enrichment processes can now be accounted for using the modified functions presented here [26].

The provided models can be used as a framework when approaching experimental manipulation and generation of alkaline seawater. By determining an AGP for an identified mineral used for OAE, we demonstrate that a simple model provides an extensive overview of the carbonate chemistry conditions inherent when following the methods described above to achieve target TA and treatment levels. We found that CO2SYS (or SeaCarb) can act as valuable tools to demonstrate the differences in magnitude—specifically with respect to DIC —based on how a mineral dissolution generates alkalinity via accelerated weathering. We note that absolute values at extreme conditions (e.g., pH 5.5 and TA of 5000 µmol kg⁻¹) will derive unrealistic absolute values of pCO₂ and pH, however, the utility of using these programs becomes relevant upon re-equilibration of the manipulated seawater. That is, the assumption by carbonate chemistry programs are based on dissociation constants (k₁ and k₂) in natural seawater conditions (~pH 7.5–8.5), and outside those bounds can produce high uncertainties in actual values. However, focus should be given to the magnitude differences in DIC conditions between both models when interpreting pH and pCO₂ values outside of potential natural conditions in seawater.

We recommend using measured [Mg²⁺] and [Ca²⁺] when applying the Mg²⁺ and Ca²⁺ CO2SYS functions. We note that the modifications to CO2SYS assume a natural background seawater complexity, and a constant ionic strength. That is, given the scale of our conducted experiments where TA increased to 11000 µmol kg⁻¹, the additions only mildly affected the ionic strength of seawater (< 1%). Additionally, the modified CO2SYS functions account for the associated increase in Mg²⁺ and Ca²⁺ by adjusting the sensitivity of the dissociation constants. While background major ion concentrations in seawater are intrinsically estimated in CO2SYS (i.e., following the formulas in Riley and Tongudai [38]), it should be recognized that different source waters may vary in composition, and direct measurements will provide a more robust baseline from which alkaline enrichment occurs. In addition, actual measurements of reference and alkaline enriched seawater are crucial in order to properly quantify mineral release from the dissolution process. Applying stoichiometric calculations based on the mass of minerals added will likely result in incorrect calculations as complete dissolution of minerals is improbable. For example, the experimental work conducted which was used to parametrize this model found a TA increase of 11600 µmol kg⁻¹ following olivine dissolution, achieved by stirring 80 g of material in 600 ml of seawater saturated with CO₂ for ~3 h. During this process, [Mg²⁺] increased from 50.5 mmol kg⁻¹ to 54.2 mmol kg⁻¹. Given that olivine dissolution releases two moles of Mg²⁺ for every mole of dissolved olivine (equation (1)), complete dissolution of the added olivine should have released ~1.0 mole of Mg²⁺. However, the observed increase in Mg²⁺ in 600 ml of seawater corresponded to just 0.002 moles. This indicates that only 0.11% (0.002 mol; 1:2 olivine to Mg) of the olivine dissolved in the experiment. By adjusting the small proportion that did dissolve with the 4:1 (TA:olivine) ratio effect of olivine on TA increase, the alkalinity generated in 600 ml should equate to ~7500 µmol kg⁻¹. Adding this generated TA to the background level of ambient seawater (2300 µmol kg⁻¹) produces a value close to the measured TA of 11600 µmol kg⁻¹ (table S1). This value of AGP aligns well with the values predicted from the olivine model for thresholds between 6.5 and 5.5 pH (~9000 µmol kg⁻¹). In addition to incomplete dissolution, it is probable that missing TA could be accounted for due to secondary precipitation [12, 39].

When creating alkaline rich solutions, it is at the discretion of the experimentalist to apply the pH or pCO₂ equilibrated method. For example, if performing experiments on phytoplankton, a higher pCO₂ level (thus, higher DIC) may interfere with direct effects of alkalinity enhancement as higher DIC levels can promote elevated photosynthetic rates and physiological performance [40, 41]. In this scenario, it may be more beneficial to equilibrate to atmospheric pCO₂ [18]. However, this creates an elevated pH that is higher than ambient conditions. Given that specific organisms may be more sensitive to pH rather than hypercapnia (situational to elevated pCO₂), equilibrating to pH may be more representative for these scenarios.

While this study highlights the effects of major cation release on alkalinity and carbonate chemistry sensitivity, it would be remiss to not mention the potential release of trace metal impurities from each alkaline mineral. Several studies have noted increases in Ni and Co from olivine dissolution which can have negative effects on organisms [35, 39, 42–44]. Similarly, oyster shells are known to accumulation trace metals which could also result in leachates of Pb and Cd [45]. These potential contaminants should be quantified as their toxicological effects are relevant to biological assays.

In addition, the potential for secondary precipitation due to oversaturation of dissolved minerals has been well documented [11, 15, 46]. However, these effects were not relevant to this study as all secondary precipitated
minerals were removed during filtration. In fact, we did not observe secondary precipitation in the majority of experimental runs when creating enriched alkaline seawater from either olivine or CaCO₃ dissolution. There were two events during olivine dissolution when we enriched 10 l of seawater rather than 600 ml (majority of the experiments) where secondary precipitation was observed. Due to the filtration processes, however, we successfully removed all particulates and found alkalinity to be steady in the stock solution (TA = ~8000 µmol kg⁻¹) up to 7 days after the solution was prepared. The stock solution was not checked past the initial 7 days as it was discarded, so it is unclear if this stability lasted longer. Thus, the relevance for this study only applies to a final TA generation which may be inhibited by secondary precipitation. That is, the production of alkalinity will eventually asymptote as it is balanced by excessive secondary precipitation (figure S2). However, this leveling-off point may vary depending on the initial conditions and potential for nucleation in the media. This was observed first-hand as experimentally enriched TA waters for small volumes generated in spring 2024 generated higher TA compared to experiments later in the summer, which were performed on larger volumes of seawater, as described above (table S1, figure S2). This occurred despite applying a similar grain-mass to seawater volume ratio. These trails represent the range of application inhibition due to secondary precipitation but also highlight the coherence of TA generation experimentally with the model presented in this study.

## 5. Conclusion

This study presents a methodological workflow accompanied by a dynamic model to produce and estimate the alkalinity generation potential from olivine and biogenic CaCO₃ mineral dissolution for laboratory experiments. In addition, we provide modifications that can be applied to CO2SYS which account for enrichment of Mg²⁺ and Ca²⁺ when conducting OAE experiments and generating alkaline enriched water, thus accomodating for the sensitivities of carbonate system parameters to these mineral additions. Our experimental results aligned well with the model predictions, confirming that partial dissolution under elevated CO₂ can assist in generating high alkalinity water via acid hydrolysis. While CO2SYS has limitations at low pH and high TA, it remains a useful tool to assess relative changes in DIC and carbonate chemistry. This approach offers a practical framework for designing, interpreting, and optimizing OAE experiments.

## Acknowledgments

This work was supported by funding from the Prince Albert II of Monaco Foundation (Project: REPAIRS: finance agreement N°4000.2-1). The authors would like to thank the research technicians at Sité Experimental d'Argenton (Ifremer) and Prof. Mariette Wolthers for providing feedback on an early draft of the manuscript.

## Data availability statement

All data that support the findings of this study are included within the article (and any supplementary files).

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