Arsenic precipitation and bioscorodite crystallization from acidic metallurgical wastewater under different bioreactor schemes: In-silico performance analysis

Abstract

Arsenic removal from water is still a challenge to overcome, and the biologically induced formation of scorodite offers an effective approach for treating arsenic-containing effluents from the metallurgical industry. This paper presents a model-based analysis of the dynamics of the overall bioscorodite process under different bioreactor schemes. For this purpose, a modified model was experimentally validated obtaining 0.87 < R² < 0.99 for all variables with p-values <0.001. The validated model was able to adequately predict the dynamics of each variable, which were verified by experimental observations. Subsequently, batch, fed-batch, combined batch/continuous, single-stage, and multi-stage continuous bioreactors were investigated through simulations, testing operational variables that influence the arsenic removal capacity, such as inoculum, ion concentration, dilution rate, and seeding. A comparative basis was then established to identify the bioreactor setups that enhance the arsenic immobilization as a bioscorodite. Single-stage and cascade bioreactors had high arsenic precipitation rates (up to 3.2 g L⁻¹ d⁻¹) and crystal sizes around ∼150 μm. Results showed that three reactors connected in series were able to precipitate 87 % arsenic with a high fed concentration (6.2 g L⁻¹), while a higher number of serial reactors may increase conversion but affect negatively the practicality and feasibility of the system. Combined batch/continuous scheme was useful to obtain large crystal sizes, up to 225 μm. These findings underscore the effectiveness of a model-based design for bioscorodite crystallization process, providing a promising and scalable solution for arsenic removal from industrial effluents.