ABSTRACT
Anaerobic digestion (AD) is a physio-biochemical process widely used for treating industrial or municipal wastewater with concomitant methane production. Several technologies have been tested to improve AD's efficiency, like pretreatments and co-digestion, among others. Recently the imposition of a low-magnitude electric field (LMEF) has been applied at the AD to improve methane yield. Despite the positive results of imputing an electric field, many gaps are not understood yet. Therefore, this review focuses on the biochemical aspects of AD and electric field for a better understanding of the effect of the LMEF on the metabolisms of the AD during wastewater treatment and its application in methane production enhancement.
Subject(s)
Sewage , Water Purification , Waste Disposal, Fluid/methods , Anaerobiosis , MethaneABSTRACT
This work aimed to analyze the performance of a hybrid upflow anaerobic sludge blanket (HUASB) reactor packed with natural zeolite for slaughterhouse wastewater treatment through kinetics modeling. Wastewater samples from a municipal bovine slaughterhouse were sieved through a 1-mm mesh screen and thermally pretreated in an autoclave. Then, biological treatment was carried out in a HUASB reactor packed with a zeolite filter at the top. Slaughterhouse wastewater was diluted with municipal wastewater during the start-up period to achieve a low organic loading rate (OLR) (3.4 kg chemical oxygen demand (COD)/m3/day); afterward, it gradually increased until dilution was eliminated, reaching 14.4 kg COD/m3/day. At this OLR, the maximum percentage removals of total COD, soluble COD, total solid, and volatile solid (67.7%, 68.3%, 55.2%, and 72.1%, respectively) were found. Moreover, the zeolite filter enabled NH4+-N and PO43--P removal, with the highest values (32.8% and 35%, respectively) at 9.8 kg COD/m3/day. Thus, the natural zeolite filter improved the reactor's performance. Among all equations analyzed, the modified Stover-Kincannon equation correctly fitted the results and provided the best prediction of the HUASB reactor's performance.