Process-based modeling of arsenic(III) oxidation by manganese oxides under circumneutral pH conditions

Unraveling biogeochemical complexity through better integration of experiments and modeling

“…16 As example for the application to geochemical transport, a few recent studies have successfully adopted the approach of iteratively advancing the conceptual model and calibrating it to observation data to gain new insights into the biogeochemical processes controlling arsenic partitioning and transport. [17][18][19][20][21][22][23][24][25] Rawson et al 19 performed a model-based analysis in which several conceptual models were tested for their ability to represent the release, transport and attenuation of arsenite in cm-scale column experiments. Each of the conceptual models was calibrated through an automatic parameter estimation process, before the most plausible model was selected.…”

“…However, in recent years heuristic algorithms, such as particle swarm optimization (PSO), 35 have shown great promise in being a good compromise between being able to obtain the global solution to highly nonlinear inverse problems but at a computational expense much less than MCMC methods. 18,19,[21][22][23]32,[36][37][38][39][40] However, it is important to note that, like the Levenberg-Marquardt-type methods, such heuristic methods do not necessarily provide an immediate nonlinear estimation of parameter uncertainty.…”

“…If the observed data can be adequately reproduced by the model, its parameter estimates agree with prior knowledge, and the parameters central to the salient processes comprising the hypothesis under investigation are overall deemed identiable, then the conceptual model can be considered plausible for the given observation data, and the hypothesis cannot be rejected. Despite the existence of a number of biogeochemical studies involving numerical modeling, very few of them 19,20,23,25,32 employ such an iterative conceptual model identication procedure.…”

“…They concluded that in addition to arsenic sorption processes, the incorporation of arsenic within newly formed magnetite likely played a major role in explaining the observed attenuation of aqueous arsenic. At a similarly small scale, Rathi et al , 23 compiled and analyzed a range of literature data sets from batch- and stir-flow experiments that investigated the kinetic controls on the oxidation of arsenite by Mn-oxides to develop a process-based numerical model. They tested a range of increasingly complex models, where their most plausible conceptual model consisted of a three-phase oxidation mechanism driven by the accessibility of Mn( iv ) and Mn( iii ) edge sites, and regulated by solution pH and surface passivation by Mn( ii ).…”

Kinetic Study of the Influence of Humic Acids on the Oxidation of As(III) by Acid Birnessite

“…1 For surface electron transfer to occur, adsorption on the mineral surface must take place; As(III) oxidation rate is controlled by its adsorption on Mn III/IV O 2 edge sites, with an overall second-order rate. 41,45 Adsorption of As(III) involves inner-sphere surface complexation, which results in the formation of adsorbed surface precursor complexes (As� MnO 2 ). 40,45 Nonetheless, previous studies barely considered simultaneous oxidation and reversible adsorption of As-(III).…”