Appraisal of Super-Fast Membrane Bioreactors by MASM—A New Activated Sludge Model for Membrane Filtration

The structure of existing activated models is inherently deficient in reflecting the major role of the membrane filtration. The study developed a novel model, MASM, for the membrane activated process. The effective filtration size imposed by the membrane module, entrapping larger particles, was adopted as the basis of the proposed model. The model defines a modified form of COD fractionation that accounts for the captured COD fractions as additional model components and utilizes related mass-balance relationships. It was implemented to test the fate of soluble hydrolyzable COD and the system performance of super-fast membrane activated sludge based on real data for the characterization and process kinetics of domestic sewage and denim processing effluents. Model evaluation was carried out for parallel systems with gravity settling and membrane filtration operated at a sludge age range of 0.5–2.0 d. Results reflected significantly better performance by the super-fast membrane activated sludge system for both wastewaters, underlining that it was crucially important to account for the captured COD fractions to provide an accurate evaluation of system behavior and effluent quality. This should also be identified as the major shortcoming of the ASM models for evaluating and predicting the system performance of activated sludge configurations with membrane separation

Short and long-term impact of pharmacovigilance training on the pharmacovigilance knowledge of medical students

OBJECTIVES: The aim of this study was to evaluate the short and long-term impact of pharmacovigilance (PV) training on the 5(th) year medical students’ knowledge about definitions and on the awareness of the regulatory aspects in PV. MATERIALS AND METHODS: In academic year 2010/11, the students completed structured, questionnaire before and just after training. They also completed the same questionnaire 1-year after the training. RESULTS: The students’ knowledge about PV significantly increased after training in the short term (P < 0.001). However, the improvement decreased significantly in the long-term (P < 0.001). Although long-term scores were higher than the baseline score, the difference was not statistically significant. Total scores were 17.5 ± 2.0, 20.8 ± 2.0 and 18.0 ± 2.5; before, at short and long-term after the training. CONCLUSION: PV training increased the students’ knowledge significantly. However, in the long-term, the impact of the training is limited. Repeated training of PV should be planned

Pollutant footprint analysis for wastewater management in textile dye houses processing different fabrics

BACKGROUND: This study investigated the water and pollution footprints of a dye house, which processed cotton knits, polyester (PES) knits and PES-viscose woven fabrics. Experimental evaluation was carried out for each processing sequence. Variations in wastewater flow and quality were established as a function of the production program in the plant. A model evaluation of wastewater dynamics was performed and defined specifications of an appropriate treatment scheme. RESULTS: The plant was operated with a capacity of 4300 t year−1 of fabric, which generated a wastewater flow of 403 500m3 year−1 and a COD load of 675 t year−1. The overall wastewater footprint of the plant was computed as 91m3 t−1 and the COD footprint as 160 kg t−1 of fabric. Depending on the fabric type, results indicated expected changes in wastewater flow between 600 and 1750m3 day−1 in COD load between 1470 and 2260 kg day−1 and in COD concentration between 1290 and 3400mgL−1. CONCLUSION: A model simulation structured upon COD fractionation and related process kinetics revealed partial removal of slowly biodegradable COD, coupled with high residual COD, which would by-pass treatment. Resulting biodegradation characteristics necessitated an extended aeration system, which could also enable partial breakdown of residual COD. Effluent COD could be reduced to 220–320mgL−1 with this wastewater management strategy. © 2018 Society of Chemical Industr