Treatment of olive mill based wastewater by means of magnetic nanoparticles: Decolourization, dephenolization and COD removal

AbstractOlive mill wastewater (OMW) is an environmental concern that has been highlighted as a serious environmental problem in the Mediterranean basin countries because of its high organic load and phytotoxic and antibacterial phenolic compounds, which resist biological degradation. Consequently, this type of wastewater represents a huge challenge for the conventional wastewater treatment techniques as it can impact the lifetime of bacteria needed for the treatment. Iron-oxide nanoparticles are attractive for wastewater treatment for two important reasons. First, nanoparticles can remove pollutants from wastewater rapidly. Second, this magnetic type of nanoparticles could be separated easily using a magnet after finishing treatment process. In this study, we aimed at investigating the effectiveness of the magnetic iron oxide nanoparticles in the removal of large organic contaminants from OMW. Batch and continuous mode processes were applied on OMW treatment to determine the effect of contact time, solution pH, coexisting contaminants and the adsorption isotherm.The results showed that the adsorption was fast and the adsorption reached equilibrium within less than 30min. The adsorption equilibrium data fit very well to the Brunauer–Emmett–Teller (BET) Model, indicating multi-layers adsorption. The adsorption of major pollutants was associated to an efficient removal of coexisting contaminants such as heavy metals and free ions. The adsorption of OMW pollutants was dependent on pH of the solution. Finally, continuous-mode process was tested successfully using a packed bed column that combined sand filtration with magnetic nanoparticles to decolourize OMW effluent. This study will provide valuable insight on the effect of nanoparticles toward the treatment and recyclability of olive mill wastewater, which is crucial for the local olive mill industry. After seeing the successful achievement of integrating nanoparticles with fixed bed filtration, a preliminary process description and cost estimation of stand-alone plant (with a capacity of 4m3/h) for OMW treatment were considered in this study. Process capital and annual operating costs were estimated to be $12,306 and$476/year, respectively

SARS-CoV-2 vaccination modelling for safe surgery to save lives: data from an international prospective cohort study

Background: Preoperative SARS-CoV-2 vaccination could support safer elective surgery. Vaccine numbers are limited so this study aimed to inform their prioritization by modelling. Methods: The primary outcome was the number needed to vaccinate (NNV) to prevent one COVID-19-related death in 1 year. NNVs were based on postoperative SARS-CoV-2 rates and mortality in an international cohort study (surgical patients), and community SARS-CoV-2 incidence and case fatality data (general population). NNV estimates were stratified by age (18-49, 50-69, 70 or more years) and type of surgery. Best- and worst-case scenarios were used to describe uncertainty. Results: NNVs were more favourable in surgical patients than the general population. The most favourable NNVs were in patients aged 70 years or more needing cancer surgery (351; best case 196, worst case 816) or non-cancer surgery (733; best case 407, worst case 1664). Both exceeded the NNV in the general population (1840; best case 1196, worst case 3066). NNVs for surgical patients remained favourable at a range of SARS-CoV-2 incidence rates in sensitivity analysis modelling. Globally, prioritizing preoperative vaccination of patients needing elective surgery ahead of the general population could prevent an additional 58 687 (best case 115 007, worst case 20 177) COVID-19-related deaths in 1 year. Conclusion: As global roll out of SARS-CoV-2 vaccination proceeds, patients needing elective surgery should be prioritized ahead of the general population