Overall
- Language
- English
- Conflict of Interest
- In relation to this article, we declare that there is no conflict of interest.
- Publication history
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Received January 7, 2024
Accepted February 2, 2024
- This is an Open-Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/bync/3.0) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.
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Kinetic/Equilibrium Adsorption and Biodegradation-Incorporated Numerical Modeling for Reactive Capping in Nutrient-Contaminated Lake Sediments
Abstract
A one-dimensional contaminant transport model coupled with adsorption and degradation processes was validated by capping
incubation experiments that simulated nitrogen and phosphorus release from lake sediments. The model integrated
advective–diff usive transport through sediment and capping materials by incorporating kinetic and equilibrium adsorption
and microbial degradation. The results aligned well with the experimental data for dissolved oxygen (DO) and chemical
oxygen demand (COD) under capping conditions. The model accurately predicted NH 4 –N concentration variations based on
the capping material’s adsorption capacity. The NH 4 –N concentrations were negligibly impacted (< 10 −7 mg/L) by zeolite
kinetic adsorption rate; whereas, the equilibrium adsorption parameters, including the maximum capacity and Langmuir constant,
signifi cantly infl uenced them; they were more sensitive to lower maximum adsorption capacities and higher Langmuir
constant ranges. The maximum specifi c growth rates of heterotrophic aerobes and nitrifi ers aff ected the relatively NH 4 –N
concentration minimally. However, COD concentrations were sensitive to the maximum specifi c growth rate of heterotrophic
aerobes, which aff ected the DO concentration in the overlying water. Variations in the ammonium half-saturation constant
aff ected neither of COD, NH 4 –N, NO 3 –N, or DO concentrations. The proposed model enhances the understanding and
prediction of nutrient fate and transport in capping systems compared with that from conventional models.