Core Ideas Gellike and dense ferrihydrite had different structures and Pb/Cu distributions. Ferrihydrite morphology and solution chemistry affected sorption and desorption kinetics. The kinetics model successfully described the stirred‐flow kinetic data of Pb and Cu. Different binding sites controlled adsorption and desorption kinetics differently. Understanding the effect of ferrihydrite morphology on the kinetic reactions of metals with ferrihydrite is essential for predicting the dynamic behavior of metals in soil. In this study, kinetics of Pb(II) and Cu(II) adsorption and desorption on two types of ferrihydrite, the freshly precipitated gellike ferrihydrite and freeze‐dried dense ferrihydrite representing two typical morphologies under extreme soil conditions, were studied. The high‐resolution transmission electron microscopy (TEM) images revealed that the gellike ferrihydrite loosely aggregated with open structure, while the dense ferrihydrite compactly aggregated with more consolidated and thicker structure. The energy dispersive spectroscopy (EDS), at the nanometer scale, showed that Pb(II) and Cu(II) distributed evenly on gellike ferrihydrite but localized on dense ferrihydrite after adsorption. The stirred‐flow kinetic experiments showed that higher pH and higher influent metal concentrations increased metal adsorption for both types of ferrihydrite. The dense ferrihydrite adsorbed slower and much less metals than gellike ferrihydrite because of less reactive sites. The desorption of heavy metals from ferrihydrite was affected by combined factors of the ferrihydrite morphology, adsorbed metal concentrations, pH, and metal re‐adsorption rates. The mechanic kinetics model based on the CD‐MUSIC model successfully described the adsorption and desorption kinetics of Pb(II) and Cu(II) on both gellike and dense ferrihydrite under various chemistry conditions. Our model provided quantitative tools for considering the effects of ferrihydrite morphology and heterogeneous binding sites under varying solution chemistry conditions when predicting the dynamic behavior of Pb(II) and Cu(II) in soil environment.
The environmental behaviors of hexavalent chromium (Cr(VI)) are of great concern due to its high toxicity and mobility.Despite the common co-occurrence of natural organic matter (NOM), Fe(II)-bearing clay minerals, and Cr(VI) in contaminated environments, how their mutual interactions affect the fate of Cr has rarely been studied.In this manuscript, we investigated the kinetics and possible mechanisms of Cr(VI) reduction by reduced nontronite (rNAu-2), a typical Fe(II)bearing clay mineral, in the presence of Suwannee River NOM under circumneutral pH.The aqueous-phase and solid-phase at different time intervals were characterized with wet chemical methods, X-ray diffraction, transmission electron microscopy, and X-ray photoelectron spectroscopy analyses.Our results demonstrated that besides the predominant solid Cr(III) species, soluble NOM-Cr(III) complexes were formed during reduction.Overall, NOM inhibited the reduction rate of Cr(VI), possibly because the solid Cr(III) products formed during Cr(VI) reduction co-precipitated and/or sorbed NOM, which impeded the sorption of Cr(VI) onto rNAu-2 reactive sites.Interestingly, the reduction rate decreased with the increase of NOM from 0 to 20 mg C/L, but kept increasing when NOM increased from 30 to 100 mg C/L.The opposing trend was likely attributed to the increase of promotion effects with increasing NOM concentrations, which offset the inhibitory effect.The main promotion effects may include: (1) NOM offered electrons to Cr(VI) through NOM-Fe(II/III) complexes and/or NOM-Cr(V) complexes; (2) NOM caused NAu-2 dissolution and resulted in the release of Fe(II) and Fe(III), which enabled better contact between Fe(II) and Cr(VI) and/or offered additional electron transfer pathways from NOM-Fe(II/III) complexes to Cr(VI), respectively; (3) NOM weakened the passivation of rNAu-2 by forming stable and aqueous NOM-Cr(III) complexes, which stimulated the sorption of Cr(VI) on rNAu-2.This study points out that NOM is a factor that cannot be neglected in understanding the fate of Cr(VI) in the geochemical cycling of Fe in NOM-rich environments given the reduction rate of Cr(VI) and the mobility and potential re-oxidation of reduction products.
Kinetic release of trace metals from soil dissolved organic matter (DOM) to solution is the key process controlling the mobility and bioavailability of trace metals in soil environment. However, due to the complexity of soil DOM, predicting the reaction rates of trace metals with soil DOM from different sources remains challenging. In this study, we developed a novel hybrid model integrating machine learning with mechanistic kinetics model, which can quantitatively predict the release rates of Cu and Cd from diverse soil DOM based on their compositions and properties. Our model quantitatively demonstrated that the molecular compositions of DOM controlled metal release rates, which had more profound impact on Cu than Cd. Our modeling results also identified two key factors affecting metal release rates, in which high concentrations of Ca and Mg ions in DOM significantly decreased the release rates of Cu and Cd, and the reassociation reactions of metal ions with DOM became more significant with the release of metals from DOM. This work has provided a unified kinetic modeling framework combining both mechanistic and data-driven approaches, which offers a new perspective for developing predictive kinetics models and can be applied to different metals and DOM in dynamic environments.
'/%3e%3cuse xlink:href='%23a' transform='rotate(23.036 .093 25.536)'/%3e%3cuse xlink:href='%23a' transform='rotate(45.87 1.273 16.18)'/%3e%3cuse xlink:href='%23a' transform='rotate(69.945 .996 12.078)'/%3e%3cuse xlink:href='%23a' transform='rotate(20.66 -19.689 31.932)'/%3e%3c/svg%3e)
'%3e%3cg id='e'%3e%3cg id='c' fill='none' stroke='%23fff' stroke-width='2'%3e%3cpath id='b' d='M0 1h26M1 10V5h8v4h8V5h-5M4 9h2m20 0h-5V5h8m0-5v9h8V0m-4 0v9' transform='scale(1.4)'/%3e%3cpath id='a' d='M0 7h9m1 0h9' transform='scale(2.8)'/%3e%3cuse xlink:href='%23a' y='120'/%3e%3cuse xlink:href='%23b' y='145.2'/%3e%3c/g%3e%3cg id='d'%3e%3cuse xlink:href='%23c' x='56'/%3e%3cuse xlink:href='%23c' x='112'/%3e%3cuse xlink:href='%23c' x='168'/%3e%3c/g%3e%3c/g%3e%3cuse xlink:href='%23d' x='168'/%3e%3cuse xlink:href='%23e' x='392'/%3e%3c/g%3e%3cg fill='%23da0000' transform='matrix(45 0 0 45 315 180)'%3e%3cg id='f'%3e%3cpath d='M-.548.836A.912.912 0 0 0 .329-.722 1 1 0 0 1-.548.836'/%3e%3cpath d='M.618.661A.764.764 0 0 0 .422-.74 1 1 0 0 1 .618.661M0 1l-.05-1L0-.787a.31.31 0 0 0 .118.099V-.1l-.04.993zM-.02-.85 0-.831a.144.144 0 0 0 .252-.137A.136.136 0 0 1 0-.925'/%3e%3c/g%3e%3cuse xlink:href='%23f' transform='scale(-1 1)'/%3e%3c/g%3e%3c/svg%3e)