The purpose of this study was to validate the applicability of specialized microbial consortium for the degradation of lipids in wastewater. An experimental model of the process is proposed that enables prediction of the required batch length. This model can be used for supervision of the process and to control cycles of the batch reactor. The study involved 4 reactors with microbial consortium obtained by inoculation from a commercially available biopreparate. Each reactor was fed a different load of lipid containing substrate. The biodiversity, settling characteristics and COD reductions were measured. The biodiversity of the microbial consortium changed within a range of ±15% depending on lipids concentration, as shown by the Shannon index and increasing amount of β-proteobacteria. Higher concentrations of lipids increased the biodiversity suggesting higher growth of microorganisms capable of utilizing lipids as energy and carbon source by producing lipid hydrolyzing enzymes. High lipid concentrations degrade the settling capabilities of the biomass. Higher lipid concentrations (0.5–2.0 [g/l]) increase the final COD (1445–2160 [mg O2/l]). The time necessary for substrate degradation changes with the initial concentration and can be predicted using the proposed model. The study showed that specialized microbial consortium is capable of reducing the lipids containing substrate and maintains its biodiversity suggesting that utilization of such consortia in multiple cycles of a batch reactor is possible. Future research should concentrate on assessing the biodiversity and effectiveness of substrate reduction after an increased number of batch reactor cycles.
A new method for measurement of sludge blanket height (SBH) based on image analysis is presented. The proposed method uses a histogram back-projection algorithm to distinguish between the settling sludge and supernatant and can be used with sludge possessing different coloring characteristics both in the sludge color and the color of supernatant produced. Individual pixels in the acquired image are compared with a histogram of a representative sludge region. Therefore, the proposed method relies neither on the assumed shape of light intensity profile nor on the dominant sludge or supernatant color. Batch sedimentation tests are presented for different initial sludge concentrations and different background colors to simulate different sludge characteristics. Parameters of a settling velocity function are estimated based on the obtained results. Additionally, an algorithm is proposed that enables the zone settling velocity (ZSV) to be estimated before the batch sedimentation test is completed.