Upscaling of batch adsorption of Cr(VI) using biomass ash: A case for the use of Pyomo and SymPy

Abstract

Prosopis trees, an invasive species, are used as biomass in boilers. The resulting biomass ash introduces a new disposal problem. To meet the demands of the circular economy, it was proposed to investigate the use of biomass ash as an adsorbent for heavy metals in aqueous solutions. The ability to regenerate the metal-loaded biomass was also investigated. Biomass ash from Prosopis trees was used as an adsorbent for Cr(VI) ions in a synthetic effluent. Adsorption time, solid loading, temperature and initial metal ion concentration were varied using a central composite rotable design (CCRD). The adsorption of Cr(VI) onto biomass ash followed the Freundlich isotherm and pseudo-second order kinetics. The metal-loaded biomass ash could be regenerated for 4 cycles before desorption efficiency fell to 59%, with the corresponding adsorption plummeting to 77%. A dimensionless time pi group from dimensional analysis was used for scaling up. The Python Optimization Modeling Objects (Pyomo) predicted scaling-up result showed an accuracy of 98.6% compared to actual scaled-up experiments. The study showed that Prosopis tree ash can be used as an adsorbent for Cr(VI), and Pyomo can be used as a scaling-up tool via dimensional analysis to generate pi groups.