Heliyon (May 2024)
Gasification chars and activated carbon: Systematic physico-chemical characterization and effect on biogas production
Abstract
Gasification residues/chars (GR) and activated carbon (AC) are added to wastewater treatment processes mainly as a fourth purification stage, e.g., to adsorb heavy metals or pharmaceutical residues. However, the effects of GR or AC, which are transferred to the anaerobic digestion (AD) via the sludge, are not yet fully understood. Although, the positive effect of char addition on AD has been demonstrated in several investigations, systematic studies with chemically well described chars are still missing. Therefore, in this study, different chars were characterized in detail, subjected to AD in different concentrations, and their effect on methane production investigated. GR of a gasification plant with a floating fixed bed technology, carbon made by chemical impregnation with ZnCl2 from waste-wood, carbon produced by thermochemical activation with CO2 from GR and commercial powdered AC were used for the experiments. Among others, thermogravimetric analysis, physisorption, pH, and conductivity analysis were used to characterize the chars. Mesophilic AD batch tests with different concentrations (0.025, 0.05, 0.5, 1.0, 7.0, 14.0 gL−1) of all chars (GR and ACs, respectively) were performed with digester sludge from a wastewater treatment plant for a period of 47 d. Volatile fatty acids (VFA) as well as biogas production and CH4 concentrations were monitored. It could be shown, that concentrations below 1.0 g char L−1 did not result in significant effects on CH4 and/or VFA production, whereas high concentrations of GR and AC influenced both, the CH4 yield and kinetics. Depending on the production process and the characteristics of the chars, the effect on AD varied, whereby both, positive and negative effects on biogas yield and methane production were observed. This study provides the first systematic evaluation of char application to AD processes, and therefore allows for better predictions of char applicability and effect.