Influence of sludge retention time on filtration performance and biomass characteristics in a hollow fiber membrane bioreactor

In this study, the filtration process and the biomass characteristics in a laboratory-scale submerged membrane bioreactor (MBR) equipped with a hollow fiber (HF) microfiltration membrane were studied at different solid retention times (SRT). The MBR was fed by synthetic wastewater and the organic loading rate (OLR) was 0.5, 0.2, 0.1, and 0.08 kg COD kg VSS−1 d−1 for 10, 30, 60, and 90 days of SRT, respectively. The hydraulic retention time was 8.4 h and the permeate flux was 6 L m−2 h−1(LMH). Data analysis confirmed that at all the studied SRTs, the HF-MBR operated very good obtaining of high quality permeates. Chemical Oxygen Demand (COD) removal efficiencies were higher than 95%. The best filtration performance was reached at SRT of 30 d. On the other hand, the respirometric analysis showed that biomass was more active and there was more biomass production at low SRTs. The concentration of soluble extracellular polymeric substances (EPS) decreased with increasing SRT. A decrease of soluble EPS caused a decrease of membrane fouling rate, decreasing the frequency of chemical cleanings. The floc size decreased with SRT increasing. At high SRTs, there was more friction among particles due to the increase of the cellular density and the flocs broke decreasing their size.

Multi-objective optimization of environmentally conscious chemical supply chains under demand uncertainty

In this work, we analyze the effect of demand uncertainty on the multi-objective optimization of chemical supply chains (SC) considering simultaneously their economic and environmental performance. To this end, we present a stochastic multi-scenario mixed-integer linear program (MILP) with the unique feature of incorporating explicitly the demand uncertainty using scenarios with given probability of occurrence. The environmental performance is quantified following life cycle assessment (LCA) principles, which are represented in the model formulation through standard algebraic equations. The capabilities of our approach are illustrated through a case study. We show that the stochastic solution improves the economic performance of the SC in comparison with the deterministic one at any level of the environmental impact.