Bettina Strauch , Martin Zimmer , Kai Wendel , Leon Keim , Holger Class
{"title":"Measuring carbonate dissolution rates under well-controlled conditions for reactive CO2-water flow in a large lab-scale karst fracture imitate","authors":"Bettina Strauch , Martin Zimmer , Kai Wendel , Leon Keim , Holger Class","doi":"10.1016/j.mex.2025.103271","DOIUrl":null,"url":null,"abstract":"<div><div>This study explores the carbonate dissolution dynamics in karstic systems by simulating reactive water flow under controlled large lab-scale laboratory conditions.</div><div>Using a 1 m² Jura limestone tile, the experiments focus on carbonate dissolution in fractures under variable parameters, including CO<sub>2</sub> concentration (0-100 %), fluid flow velocity 50-1000 ml/l) and fracture aperture (2-10 mm). This large lab-scale setup bridges the gap between field-scale phenomena and small-scale laboratory studies.</div><div>Preliminary tests confirmed the suitability of the limestone for dynamic experiments, in terms of measurable calcium release at different experimental modifications. A novel, adjustable polyoxymethylene (POM) frame ensures precise control of flow and reaction boundaries. Process water with no CO<sub>2</sub> addition, 50% CO<sub>2</sub>-saturation and full CO<sub>2</sub>-saturation were used, to gain insight into the dissolution efficiency at these CO<sub>2</sub>-saturation levels. The results showed, that the effects of different CO<sub>2</sub> additions were well reflected in the limestone dissolution rates.</div><div>This setup provides important experimental data for the validation of numerical models for reactive transport in karst systems, to improve the understanding of the interplay between chemical reactions, fluid dynamics and geological settings.</div><div>The findings have implications for karst hydrology, geochemical modeling related subsurface processes, supporting advancements in predictive capabilities for natural and engineered systems.</div></div>","PeriodicalId":18446,"journal":{"name":"MethodsX","volume":"14 ","pages":"Article 103271"},"PeriodicalIF":1.6000,"publicationDate":"2025-03-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"MethodsX","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2215016125001177","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"MULTIDISCIPLINARY SCIENCES","Score":null,"Total":0}
引用次数: 0
Abstract
This study explores the carbonate dissolution dynamics in karstic systems by simulating reactive water flow under controlled large lab-scale laboratory conditions.
Using a 1 m² Jura limestone tile, the experiments focus on carbonate dissolution in fractures under variable parameters, including CO2 concentration (0-100 %), fluid flow velocity 50-1000 ml/l) and fracture aperture (2-10 mm). This large lab-scale setup bridges the gap between field-scale phenomena and small-scale laboratory studies.
Preliminary tests confirmed the suitability of the limestone for dynamic experiments, in terms of measurable calcium release at different experimental modifications. A novel, adjustable polyoxymethylene (POM) frame ensures precise control of flow and reaction boundaries. Process water with no CO2 addition, 50% CO2-saturation and full CO2-saturation were used, to gain insight into the dissolution efficiency at these CO2-saturation levels. The results showed, that the effects of different CO2 additions were well reflected in the limestone dissolution rates.
This setup provides important experimental data for the validation of numerical models for reactive transport in karst systems, to improve the understanding of the interplay between chemical reactions, fluid dynamics and geological settings.
The findings have implications for karst hydrology, geochemical modeling related subsurface processes, supporting advancements in predictive capabilities for natural and engineered systems.