Microbial metabolism mediates interactions between dissolved organic matter and clay minerals in streamwater

Sorption of organic molecules to mineral surfaces is an important control upon the aquatic carbon (C) cycle. Organo-mineral interactions are known to regulate the transport and burial of C within inland waters, yet the mechanisms that underlie these processes are poorly constrained. Streamwater contains a complex and dynamic mix of dissolved organic compounds that coexists with a range of organic and inorganic particles and microorganisms. To test how microbial metabolism and organo-mineral complexation alter amino acid and organic carbon fluxes we experimented with 13C-labelled amino acids and two common clay minerals (kaolinite and montmorillonite). The addition of 13C-labelled amino acids stimulated increased microbial activity. Amino acids were preferentially mineralized by the microbial community, concomitant with the leaching of other (non-labelled) dissolved organic molecules that were removed from solution by clay-mediated processes. We propose that microbial processes mediate the formation of organo-mineral particles in streamwater, with potential implications for the biochemical composition of organic matter transported through and buried within fluvial environments.

Activated lignin‒chitosan extruded blends for efficient adsorption of methylene blue

This work investigates the production of activated lignin-chitosan extruded (ALiCE) pellets with controlled particle size distribution (almost spherical: dp ~500‒1000µm) for efficient methylene blue adsorption. The novel preparation method employed in this study successfully produced activated lignin-chitosan pellets. Structural and morphological characterizations were performed using BET, FTIR and SEM-EDX analyses. The influence of contact time, solution pH, ionic strength, initial adsorbate concentration and desorption studies was investigated. The experimental data fitted well with the Langmuir isotherm (R2 = 0.997), yielding a maximum adsorption capacity of 36.25mg/g. The kinetic data indicated that methylene blue (MB) adsorption onto ALiCE can be represented by the pseudo second-order-model with intraparticle processes initially controlling the process of MB adsorption. Overall, these results indicate that the novel ALiCE offers great potential for removing cationic organic pollutants from rivers and streams.

Avoiding Overfitting in Inverse Modeling of Chloride Migration in Concrete

Inverse analysis for reactive transport of chlorides through concrete in the presence of electric field is presented. The model is solved using MATLAB’s built-in solvers “pdepe.m” and “ode15s.m”. The results from the model are compared with experimental measurements from accelerated migration test and a function representing the lack of fit is formed. This function is optimised with respect to varying amount of key parameters defining the model. Levenberg-Marquardt trust-region optimisation approach is employed. The paper presents a method by which the degree of inter-dependency between parameters and sensitivity (significance) of each parameter towards model predictions can be studied on models with or without clearly defined governing equations. Eigen value analysis of the Hessian matrix was employed to investigate and avoid over-parametrisation in inverse analysis. We investigated simultaneous fitting of parameters for diffusivity, chloride binding as defined by Freundlich isotherm (thermodynamic) and binding rate (kinetic parameter). Fitting of more than 2 parameters, simultaneously, demonstrates a high degree of parameter inter-dependency. This finding is significant as mathematical models for representing chloride transport rely on several parameters for each mode of transport (i.e., diffusivity, binding, etc.), which combined may lead to unreliable simultaneous estimation of parameters.