Tracking the formation potential of vivianite within the treatment train of full-scale wastewater treatment plants.

Phosphorus recovery is a vital element for the circular economy. Wastewater, especially sewage sludge, shows great potential for recovering phosphate in the form of vivianite. This work focuses on studying the iron, phosphorus, and sulfur interactions at full-scale wastewater treatment plants (Viikinmäki, Finland and Seine Aval, France) with the goal of identifying unit processes with a potential for vivianite formation. Concentrations of iron(III) and iron(II), phosphorus, and sulfur were used to evaluate the reduction of iron and the formation potential of vivianite. Mössbauer spectroscopy and X-ray diffraction (XRD) analysis were used to confirm the presence of vivianite in various locations on sludge lines. The results show that the vivianite formation potential increases as the molar Fe:P ratio increases, the anaerobic sludge retention time increases, and the sulfate concentration decreases. The digester is a prominent location for vivianite recovery, but not the only one. This work gives valuable insights into the dynamic interrelations of iron, phosphorus, and sulfur in full-scale conditions. These results will support the understanding of vivianite formation and pave the way for an alternative solution for vivianite recovery for example in plants that do not have an anaerobic digester.

Viral outbreaks detection and surveillance using wastewater-based epidemiology, viral air sampling, and machine learning techniques: A comprehensive review and outlook.

A viral outbreak is a global challenge that affects public health and safety. The coronavirus disease 2019 (COVID-19) has been spreading globally, affecting millions of people worldwide, and led to significant loss of lives and deterioration of the global economy. The current adverse effects caused by the COVID-19 pandemic demands finding new detection methods for future viral outbreaks. The environment's transmission pathways include and are not limited to air, surface water, and wastewater environments. The wastewater surveillance, known as wastewater-based epidemiology (WBE), can potentially monitor viral outbreaks and provide a complementary clinical testing method. Another investigated outbreak surveillance technique that has not been yet implemented in a sufficient number of studies is the surveillance of Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2) in the air. Artificial intelligence (AI) and its related machine learning (ML) and deep learning (DL) technologies are currently emerging techniques for detecting viral outbreaks using global data. To date, there are no reports that illustrate the potential of using WBE with AI to detect viral outbreaks. This study investigates the transmission pathways of SARS-CoV-2 in the environment and provides current updates on the surveillance of viral outbreaks using WBE, viral air sampling, and AI. It also proposes a novel framework based on an ensemble of ML and DL algorithms to provide a beneficial supportive tool for decision-makers. The framework exploits available data from reliable sources to discover meaningful insights and knowledge that allows researchers and practitioners to build efficient methods and protocols that accurately monitor and detect viral outbreaks. The proposed framework could provide early detection of viruses, forecast risk maps and vulnerable areas, and estimate the number of infected citizens.

New alginate-based interpenetrating polymer networks for water treatment: A response surface methodology based optimization study.

Different interpenetrating polymeric networks (IPN) based on sodium alginate, carrageenan and bentonite were developed to remove heavy metals and dyes from contaminated water. Four significant preparation factors; crosslinking time, calcium chloride concentration, alginate to carrageenan mass ratio,and bentonite to carrageenan mass ratio were studied and optimized via full factorial design and response surface methodology to determine the optimum composition with highest adsorption capacity. Different optimal conditions and combinations were found depending on the type of heavy metal or dye to be removed. Low calcium chloride concentration was a common factor in all cases of heavy metals and dyes removal which indicates the negative effect of excessive crosslinking on the removal percentage. The adsorption capacity of methylene blue, Fe3+, Ni2+, and Cr3+ ions is 1271, 1550, 1500 and 1540 mg/g adsorbent, respectively. Reusability tests confirmed that the optimized formulations can be reused five successive times without significant drop in their removal efficiency. Upon utilization of the optimized formulations on real contaminated waters from tannery plant and oasis groundwater, they demonstrated an excellent performance as they removed above 95% of the original heavy metals contaminants and 40% of the acidic dye content.