Treatment of Poultry Slaughterhouse Wastewater (PSW) Using a Pretreatment Stage, an Expanded Granular Sludge Bed Reactor (EGSB), and a Membrane Bioreactor (MBR).

This study presents the biological treatment of poultry slaughterhouse wastewater (PSW) using a combination of a biological pretreatment stage, an expanded granular sludge bed reactor (EGSB), and a membrane bioreactor (MBR) to treat PSW. This PSW treatment was geared toward reducing the concentration of contaminants present in the PSW to meet the City of Cape Town (CoCT) discharge standards and evaluate an alternative means of treating medium- to high-strength wastewater at low cost. The EGSB used in this study was operated under mesophilic conditions and at an organic loading rate (OLR) of 69 to 456 mg COD/L·h. The pretreatment stage of this laboratory-scale (lab-scale) plant played an important role in the pretreatment of the PSW, with removal percentages varying between 20% and 50% for total suspended solids (TSS), 20% and 70% for chemical oxygen demand (COD), and 50% and 83% for fats, oil, and grease (FOG). The EGSB further reduced the concentration of these contaminants to between 25% and 90% for TSS, 20% and 80% for COD, and 20% and >95% for FOG. The last stage of this process, i.e., the membrane bioreactor (MBR), contributed to a further decrease in the concentration of these contaminants with a peak removal performance of >95% for TSS and COD and 80% for the FOG. Overall, the system (pretreatment-EGSB-MBR) exceeded 97% for TSS and COD removal and 97.5% for FOG removal. These results culminated in a product (treated wastewater) meeting the discharge standards.

Acetoclastic methanogenesis led by Methanosarcina in anaerobic co-digestion of fats, oil and grease for enhanced production of methane.

Fats, oil and grease (FOG) are energy-dense wastes that substantially increase biomethane recovery. Shifts in the microbial community during anaerobic co-digestion of FOG was assessed to understand relationships between substrate digestion and microbial adaptations. Excessive addition of FOG inhibited the methanogenic activity during initial phase; however, it enhanced the ultimate methane production by 217% compared to the control. The dominance of Proteobacteria was decreased with a simultaneous increase in Firmicutes, Bacteriodetes, Synergistetes and Euryarchaeota during the co-digestion. A significant increase in Syntrophomonas (0.18-11%), Sporanaerobacter (0.14-6%) and Propionispira (0.02-19%) was observed during co-digestion, which substantiated their importance in acetogenesis. Among methanogenic Archaea, the dominance of Methanosaeta (94%) at the beginning of co-digestion was gradually replaced by Methanosarcina (0.52-95%). The absence/relatively low abundance of syntrophic acetate oxidizers and hydrogenotrophic methanogens, and dominance of acetoclastic methanogens suggested that methane generation during co-digestion of FOG was predominantly conducted through acetoclastic pathway led by Methanosarcina.

Evaluating analytical methods for the characterization of lipids, proteins and carbohydrates in organic substrates for anaerobic co-digestion.

This study provides insights into the characterization of lipids, proteins and carbohydrate content in substrates for codigestion, and evaluates their effects on biogas yield. Among the analytical methods evaluated, the Bligh and Dyer, Hach Total Nitrogen and the Anthrone method were found to be most suitable for lipids, proteins and carbohydrates analysis, respectively. The co-digestibility of ten co-substrate mixes prepared using various volume-to-volume ratios of foodwaste (FW), fats, oils and grease (FOG), and waste activated sludge (WAS) were tested using biomethane potential assays. The three main substrates were mono-digested as well. WAS mono-digestion yielded the lowest methane yield of 118mL CH4/g VS, while a 50:50 mix of WAS and FOG, containing 85% lipid and 15% protein produced the highest methane yield of 1040mL CH4/g VS. In general, lipid-rich samples yielded more biogas than samples rich in proteins and carbohydrates. However, samples rich in proteins and carbohydrates had faster biogas production rates.