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Model-Based Analysis of Arsenic Retention by Stimulated Iron Mineral Transformation under Coastal Aquifer Conditions.
Barron, Alyssa; Jamieson, James; Colombani, Nicolò; Bostick, Benjamin C; Ortega-Tong, Pablo; Sbarbati, Chiara; Barbieri, Maurizio; Petitta, Marco; Prommer, Henning.
Afiliação
  • Barron A; School of Earth Sciences, University of Western Australia, Crawley 6009 WA, Australia.
  • Jamieson J; Ekion Pty Ltd., Swanbourne 6010 WA, Australia.
  • Colombani N; SIMAU, Polytechnic University of Marche, Ancona 60121, Italy.
  • Bostick BC; Lamont-Doherty Earth Observatory of Columbia University, Palisades, New York 10964, United States.
  • Ortega-Tong P; School of Earth Sciences, University of Western Australia, Crawley 6009 WA, Australia; Intera Inc., Perth 6000 WA, Australia.
  • Sbarbati C; Dept. of Ecological and Biological Sciences, University of Tuscia, Viterbo 01100, Italy.
  • Barbieri M; Dept. of Earth Sciences, "Sapienza" University of Roma, Roma 00185, Italy.
  • Petitta M; Dept. of Earth Sciences, "Sapienza" University of Roma, Roma 00185, Italy.
  • Prommer H; School of Earth Sciences, University of Western Australia, Crawley 6009 WA, Australia; Ekion Pty Ltd., Swanbourne 6010 WA, Australia.
ACS ES T Water ; 4(7): 2944-2956, 2024 Jul 12.
Article em En | MEDLINE | ID: mdl-39005241
ABSTRACT
A multitude of geochemical processes control the aqueous concentration and transport properties of trace metal contaminants such as arsenic (As) in groundwater environments. Effective As remediation, especially under reducing conditions, has remained a significant challenge. Fe(II) nitrate treatments are a promising option for As immobilization but require optimization to be most effective. Here, we develop a process-based numerical modeling framework to provide an in-depth understanding of the geochemical mechanisms controlling the response of As-contaminated sediments to Fe(II) nitrate treatment. The analyzed data sets included time series from two batch experiments (control vs treatment) and effluent concentrations from a flow-through column experiment. The reaction network incorporates a mixture of homogeneous and heterogeneous reactions affecting Fe redox chemistry. Modeling revealed that the precipitation of the Fe treatment caused a rapid pH decline, which then triggered multiple heterogeneous buffering processes. The model quantifies key processes for effective remediation, including the transfer of aqueous As to adsorbed As and the transformation of Fe minerals, which act as sorption hosts, from amorphous to more stable phases. The developed model provides the basis for predictions of the remedial benefits of Fe(II) nitrate treatments under varying geochemical and hydrogeological conditions, particularly in high-As coastal environments.
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Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2024 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2024 Tipo de documento: Article