In porous water filters, the transport and entrapment of contaminants can be modeled as a classic mass transport problem, which employs the conventional convection-dispersion equation to predict the transport of species existing in trace amounts. Using the volume-averaging method (VAM), the upscaling has revealed two possible macroscopic equations for predicting contaminant concentrations in the filters. The first equation is the classical convection-dispersion equation, which incorporates a total dispersion tensor. The second equation involves an additional transport coefficient, identified as the adsorption-induced vector. In this study, the aforementioned equations were solved in 1D for column tests using 3D unit cells. The simulated breakthrough curves (BTCs), using the proposed micro-macro-coupling-based VAM model, are compared with the direct numerical simulation (DNS) results based on BCC-type unit cells arranged one-after-another in a daisy chain manner, as well as with three previously reported experimental works, in which the functionalized zeolite and zero-valent iron fillings were used as an adsorbent to remove phosphorous and arsenic from water, respectively. The disagreement of VAM BTC predictions with DNS and experimental results reveals the need for an alternative closure formulation in VAM. Detailed investigations reveal time constraint violations in all the three cases, suggesting this as the main cause of VAM's failure.
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http://dx.doi.org/10.3390/molecules29174218 | DOI Listing |
Sci Total Environ
January 2025
University of São Paulo, Luiz de Queiroz College of Agriculture, Department of Soil Science, Brazil.
Phosphorus (P) movement in soils is influenced by flow velocities, diffusion rates, and several soil characteristics and properties. In acidic soils, P is tightly bound to soil particles, reducing its availability to plants. Organomineral fertilizers combine organic matter with mineral nutrients, enhancing P fertilization efficiency, and reducing environmental impacts.
View Article and Find Full Text PDFJ Hazard Mater
January 2025
Université Paris Cité, Institut de physique du globe de Paris, CNRS, F-75005 Paris, France.
Molecules
September 2024
Laboratory for Flow and Transport Studies in Porous Media, University of Wisconsin-Milwaukee, Milwaukee, WI 53211, USA.
In porous water filters, the transport and entrapment of contaminants can be modeled as a classic mass transport problem, which employs the conventional convection-dispersion equation to predict the transport of species existing in trace amounts. Using the volume-averaging method (VAM), the upscaling has revealed two possible macroscopic equations for predicting contaminant concentrations in the filters. The first equation is the classical convection-dispersion equation, which incorporates a total dispersion tensor.
View Article and Find Full Text PDFEnviron Sci Pollut Res Int
June 2024
School of Resources and Environment, Henan Polytechnic University, Jiaozuo, 454000, China.
The dynamic changes in dissolved organic matter (DOM) during the transport of landfill leachate (LL) in porous medium should be explored, considering the high levels of DOM in the LL of municipal solid waste. Column experiments were carried out at 25 °C at a Darcy's flux of 0.29 cm/h for 2722 h to compare the transport of Cl, ultraviolet absorbance at 254 nm (UV), chemical oxygen demand (COD), and dissolved organic carbon (DOC) in the simulated porous medium by using the CXTFIT2.
View Article and Find Full Text PDFJ Hazard Mater
July 2024
Sino-Spain Joint Laboratory for Agricultural Environment Emerging Contaminants of Zhejiang Province, College of Environmental and Resource Sciences, Zhejiang Agriculture and Forestry University, Hangzhou 311300, China. Electronic address:
This study presents a comprehensive approach to estimating annual atrazine residues in China's agricultural soils, integrating machine learning algorithms and mechanism-based models. First, machine learning was used to predict essential parameters influencing atrazine's adsorption, degradation, and dispersivity of solute transport. The results demonstrated that soil organic matter was the most important input variable for predicting adsorption and degradation; clay content was the primary variable for predicting dispersivity.
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