Application of the Homogeneous Surface Diffusion Model for the prediction of the breakthrough in full-scale GAC filters fed on groundwater

[Display omitted] •Full-scale PCE and chloroform breakthrough effectively simulated by HSDM.•Chloroform breakthrough and release over time was accurately predicted.•HSDM parameters were determined for two GACs in real groundwater samples.•HSDM sensitivity depends on contaminant adsorbability and adsorber scale. Homogeneous Surface Diffusion Model (HSDM) has been widely used to simulate the breakthrough of organic micropollutants in fixed-bed adsorbers, but its practical applicability in real-scale conditions is not fully established. In this study we proposed a validated methodology to support the assessment of full-scale GAC adsorbers, providing a sound framework for a sustainable management. Specifically, we predicted the breakthrough of volatile organic compounds by the HSDM applied to full-scale granular activated carbon (GAC) adsorbers treating a complex groundwater matrix. Isotherm and short bed adsorber (SBA) tests were conducted to obtain equilibrium and mass-transfer coefficients for two contaminants (chloroform and perchloroethylene, PCE) and two GACs. Isotherm data were well described by Freundlich and Langmuir models, showing that single-component isotherms can be also used in complex water matrices, indirectly taking into account competition phenomena into the estimated parameters. The fitting of SBA data by HSDM was effective for chloroform, while PCE results were not well described, indicating that the combination of isotherm and SBA experiments to estimate HSDM parameters is not always effective, but it can depend on the characteristics of the adsorbate. Breakthrough data from the monitoring of two full-scale adsorbers were finally used to validate HSDM parameters for chloroform: its breakthrough was effectively simulated, without introducing any competition effect in HSDM equations. The model well reproduced also the release of the contaminant (resulting in chromatographic effect) by considering the variation of its influent concentration over time.