Preprints
https://doi.org/10.5194/egusphere-2022-1179
https://doi.org/10.5194/egusphere-2022-1179
23 Nov 2022
 | 23 Nov 2022
Status: this preprint has been withdrawn by the authors.

Quantification of In-situ Remediation of Deep Unsaturated Zone and Groundwater

Ilil Levakov, Zeev Ronen, Tuvia Turkeltaub, and Ofer Dahan

Abstract. In-situ bioremediation techniques are cost-effective, environmentally friendly, and sustainable. This study examined a large-scale in-situ treatment of an unsaturated zone and a local groundwater system that were heavily contaminated with perchlorate and other co-contaminants, including nitrate, chlorate, and RDX. Principally, the upper section of the unsaturated zone was used as a bioreactor for treating the deep unsaturated zone and groundwater. The treatment was based on a cyclic process that included pumping contaminated groundwater, adding an essential electron donor, and injecting the amended water back into the top-soil, which was used as a bioreactor in the treatment process. In the shallow soil, the local bacteria reduced the perchlorate to chloride and water, and the treated water continued to displace the major pollutants from the deep part of the vadose zone, where the biological potential for contaminant degradation is low, towards the water table. The contaminated leachates were pumped back to the surface with polluted groundwater as part of the cyclic treatment process. Results show that the other co-contaminants, including nitrate, chlorate, and RDX, were removed. Water flow and reactive transport models were calibrated and validated against a time series of the water contents and bromide and perchlorate concentrations that were obtained across the unsaturated zone using the VMS. The calibrated models enabled quantifying the clean-up process and estimating the required time for full perchlorate removal. According to the model's predictions, after 700 days of continuous operation, all the perchlorate, in a total amount of 7754 kg, would be removed from the unsaturated zone. To obtain full removal, the modelling simulations suggest that the in-situ bioremediation should be implemented for an additional 200 days. Ultimately, we present a low-cost, efficient method for treating perchlorate contamination and potentially that of other pollutants in the subsurface.

This preprint has been withdrawn.

Publisher's note: Copernicus Publications remains neutral with regard to jurisdictional claims made in the text, published maps, institutional affiliations, or any other geographical representation in this preprint. The responsibility to include appropriate place names lies with the authors.
Ilil Levakov, Zeev Ronen, Tuvia Turkeltaub, and Ofer Dahan

Interactive discussion

Status: closed

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on egusphere-2022-1179', Anonymous Referee #1, 19 Dec 2022
    • AC1: 'Reply on RC1', Ilil Levakov, 09 May 2023
  • RC2: 'Comment on egusphere-2022-1179', Anonymous Referee #2, 07 Apr 2023
    • AC2: 'Reply on RC2', Ilil Levakov, 09 May 2023
  • AC3: 'reply to the editor', Ilil Levakov, 07 Jun 2023

Interactive discussion

Status: closed

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on egusphere-2022-1179', Anonymous Referee #1, 19 Dec 2022
    • AC1: 'Reply on RC1', Ilil Levakov, 09 May 2023
  • RC2: 'Comment on egusphere-2022-1179', Anonymous Referee #2, 07 Apr 2023
    • AC2: 'Reply on RC2', Ilil Levakov, 09 May 2023
  • AC3: 'reply to the editor', Ilil Levakov, 07 Jun 2023
Ilil Levakov, Zeev Ronen, Tuvia Turkeltaub, and Ofer Dahan
Ilil Levakov, Zeev Ronen, Tuvia Turkeltaub, and Ofer Dahan

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This preprint has been withdrawn.

Short summary
This study presents a novel approach for in-situ large-scale remediation of contaminated unsaturated zone and groundwater. Flow and transport models were calibrated against continuously monitored data, enabling evaluation of the required conditions for optimal contaminate removal. The results enabled realistic data-based predictions of the time frame that is required to attain full contaminant removal through efficient and low-cost in-situ treatment technique.