<p>This paper presents a comprehensive experimental evaluation of CO<sub>2</sub> storage efficiency in three carbonate lithologies—limestone, chalk, and dolomite—under ambient laboratory conditions simulating shallow subsurface environments. Using a combination of batch and flow-through systems, we investigated the dissolution kinetics, ion release behavior, mineral trapping potential, and surface morphological changes following CO<sub>2</sub> exposure over a 28&#xa0;day experimental period. Mineralogical analyses (XRD) confirmed that the chalk consists of more than 90% calcite, while limestone contains approximately 85% calcite, and dolomite is composed of approximately 85% dolomite, directly influencing their geochemical reactivity. The quantitative results showed that the chalk exhibited the highest Ca<sup>2+</sup> release (310&#xa0;mg/L) and porosity increase (+3.5%) owing to its high surface area (4.2&#xa0;m<sup>2</sup>/g) and micro-porosity. However, it demonstrated limited secondary carbonate precipitation, indicating low mineral trapping efficiency (25%). In contrast, the dolomite showed a slower dissolution rate but retained 68% of injected CO<sub>2</sub> via stable carbonate precipitation, with lower ion release (Ca<sup>2+</sup> 90&#xa0;mg/L; Mg<sup>2+</sup> 95&#xa0;mg/L). Limestone displayed intermediate behavior, balancing dissolution and precipitation, with a retention efficiency of 42%. SEM and profilometry revealed extensive surface etching in chalk and moderate textural preservation in dolomite. These results highlight the significance of lithological and textural controls on CO<sub>2</sub>–rock interactions. Chalk favors rapid acid buffering but offers poor long-term retention, while dolomite supports stable mineral trapping with limited porosity enhancement. This study suggests that dolomite and balanced carbonate systems, such as limestone, are more suitable for permanent geological carbon storage, providing essential information for site selection and reactive transport modeling.</p>

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Experimental Comparison of CO2 Storage Efficiency in Limestone, Chalk, and Dolomite: Dissolution Rates and Mineral Trapping

  • Haval Kukha Hawez,
  • Marco Fazio

摘要

This paper presents a comprehensive experimental evaluation of CO2 storage efficiency in three carbonate lithologies—limestone, chalk, and dolomite—under ambient laboratory conditions simulating shallow subsurface environments. Using a combination of batch and flow-through systems, we investigated the dissolution kinetics, ion release behavior, mineral trapping potential, and surface morphological changes following CO2 exposure over a 28 day experimental period. Mineralogical analyses (XRD) confirmed that the chalk consists of more than 90% calcite, while limestone contains approximately 85% calcite, and dolomite is composed of approximately 85% dolomite, directly influencing their geochemical reactivity. The quantitative results showed that the chalk exhibited the highest Ca2+ release (310 mg/L) and porosity increase (+3.5%) owing to its high surface area (4.2 m2/g) and micro-porosity. However, it demonstrated limited secondary carbonate precipitation, indicating low mineral trapping efficiency (25%). In contrast, the dolomite showed a slower dissolution rate but retained 68% of injected CO2 via stable carbonate precipitation, with lower ion release (Ca2+ 90 mg/L; Mg2+ 95 mg/L). Limestone displayed intermediate behavior, balancing dissolution and precipitation, with a retention efficiency of 42%. SEM and profilometry revealed extensive surface etching in chalk and moderate textural preservation in dolomite. These results highlight the significance of lithological and textural controls on CO2–rock interactions. Chalk favors rapid acid buffering but offers poor long-term retention, while dolomite supports stable mineral trapping with limited porosity enhancement. This study suggests that dolomite and balanced carbonate systems, such as limestone, are more suitable for permanent geological carbon storage, providing essential information for site selection and reactive transport modeling.