Olive mill wastewater treatment using natural adsorbents: phytotoxicity on durum wheat (Triticum turgidum L. var. durum) and white bean (Phaseolus vulgaris L.) seed germination.

This research was undertaken to optimize the phenolic compound removal from Olive Mill Wastewater (OMW) by sawdust and red clay as natural adsorbents. Fractional factorial experimental design at 25-1 was used in order to optimize the experimental conditions for high removal efficiency. Statistics ANOVA analysis, Fisher's test, and Student's test suggested that the adsorbent dose has the most significant influence on polyphenol removal for both adsorbents. The maximum removal of polyphenols by sawdust reached 49.6% at 60 °C by using 60 g/L of adsorbent dose, pH 2, reaction time of 24 h, and agitation speed of 80 rpm. Whereas, for red clay, 48.08% of polyphenols removal was observed under the same conditions for sawdust except the temperature of 25 °C instead of 60 °C. In addition, the thermodynamic parameters suggested spontaneous process for both adsorbents, endothermic for the sawdust and exothermic for red clay. Furthermore, the phytotoxicity effect of OMW on durum wheat (Triticum turgidum L. var. durum) and white bean (Phaseolus vulgaris L.) seed germination was investigated. The obtained results showed that the untreated OMW inhibited the seed germination of T. turgidum and P. vulgaris seeds. OMW treatment with red clay followed by dilution (95% water) resulted in 87 and 30% germination of P. vulgaris and T. turgidum, respectively. While, the treatment of OMW with sawdust and dilution at 95% resulted in 51 and 26% germination of P. vulgaris and T. turgidum, respectively.

The state of art on the prediction of efficiency and modeling of the processes of pollutants removal based on machine learning.

During the last few years, important advances have been made in big data exploration, complex pattern recognition and prediction of complex variables. Machine learning (ML) algorithms can efficiently analyze voluminous data, identify complex patterns and extract conclusions. In chemical engineering, the application of machine learning approaches has become highly attractive due to the growing complexity of this field. Machine learning allows computers to solve problems by learning from large data sets and provides researchers with an excellent opportunity to enhance the quality of predictions for the output variables of a chemical process. Its performance has been increasingly exploited to overcome a wide range of challenges in chemistry and chemical engineering, including improving computational chemistry, planning materials synthesis and modeling pollutant removal processes. In this review, we introduce this discipline in terms of its accessible to chemistry and highlight studies that illustrate in-depth the exploitation of machine learning. The main aim of the review paper is to answer these questions by analyzing physicochemical processes that exploit machine learning in organic and inorganic pollutants removal. In general, the purpose of this review is both to provide a summary of research related to the removal of various contaminants performed by ML models and to present future research needs in ML for contaminant removal.

Chemically modified carbon-based electrodes for the determination of paracetamol in drugs and biological samples.

Paracetamol is a non-steroidal, anti-inflammatory drug widely used in pharmaceutical applications for its sturdy, antipyretic and analgesic action. However, an overdose of paracetamol can cause fulminant hepatic necrosis and other toxic effects. Thus, the development of advantageous analytical tools to detect and determine paracetamol is required. Due to simplicity, higher sensitivity and selectivity as well as costefficiency, electrochemical sensors were fully investigated in last decades. This review describes the advancements made in the development of electrochemical sensors for the paracetamol detection and quantification in pharmaceutical and biological samples. The progress made in electrochemical sensors for the selective detection of paracetamol in the last 10 years was examined, with a special focus on highly innovative features introduced by nanotechnology. As the literature is rather extensive, we tried to simplify this work by summarizing and grouping electrochemical sensors according to the by which manner their substrates were chemically modified and the analytical performances obtained.

Comparative overview of advanced oxidation processes and biological approaches for the removal pharmaceuticals.

Nowadays, pharmaceuticals are the center of significant environmental research due to their complex and highly stable bioactivity, increasing concentration in the water streams and high persistence in aquatic environments. Conventional wastewater treatment techniques are generally inadequate to remove these pollutants. Aiming to tackle this issue effectively, various methods have been developed and investigated on the light of chemical, physical and biological procedures. Increasing attention has recently been paid to the advanced oxidation processes (AOPs) as efficient methods for the complete mineralization of pharmaceuticals. Their high operating costs compared to other processes, however, remain a challenge. Hence, this review summarizes the current and state of art related to AOPs, biological treatment and their effective exploitation for the degradation of various pharmaceuticals and other emerging molecules present in wastewater. The review covers the last decade with a particular focus on the previous five years. It is further envisioned that this review of advanced oxidation methods and biological treatments, discussed herein, will help readers to better understand the mechanisms and limitations of these methods for the removal of pharmaceuticals from the environment. In addition, we compared AOPs and biological treatments for the disposal of pharmaceuticals from the point of view of cost, effectiveness, and popularity of their use. The exploitation of coupling AOPs and biological procedures for the degradation of pharmaceuticals in wastewater was also presented. It is worthy of note that an integrated AOPs/biological system is essential to reach the complete degradation of pharmaceuticals; other advantages of this hybrid technique involve low energy cost, an efficient degradation process and generation of non-toxic by-products.

SARS-CoV-2 in hospital wastewater during outbreak of COVID-19: A review on detection, survival and disinfection technologies.

Currently, the apparition of new SARS-CoV, known as SARS-CoV-2, affected more than 34 million people and causing high death rates worldwide. Recently, several studies reported SARS-CoV-2 ribonucleic acid (RNA) in hospital wastewater. SARS-CoV-2 can be transmitted between humans via respiratory droplets, close contact and fomites. Fecal-oral transmission is considered also as a potential route of transmission since several scientists confirmed the presence of SARS-CoV-2 RNA in feces of infected patients, therefore its transmission via feces in aquatic environment, particularly hospital wastewater. Hospitals are one of the important classes of polluting sectors around the world. It was identified that hospital wastewater contains hazardous elements and a wide variety of microbial pathogens and viruses. Therefore, this may potentially pose a significant risk of public health and environment infection. This study reported an introduction about the Physical-chemical and microbiological characterization of hospital wastewater, which can be a route to identify potential technology to reduce the impact of hospital contaminants before evacuation. The presence of SARS-CoV-2 in aqueous environment was reviewed. The knowledge of the detection and survival of SARS-CoV-2 in wastewater and hospital wastewater were described to understand the different routes of SARS-CoV-2 transmission, which is also useful to avoid the outbreak of CoV-19. In addition, disinfection technologies used commonly for deactivation of SARS-CoV-2 were highlighted. It was revealed that, chlorine-containing disinfectants are the most commonly used disinfectants in this field of research. Meanwhile, other efficient technologies must be developed and improved to avoid another wave of the pandemic of COVID-19 infections.

A combined molecular dynamic simulation, DFT calculations, and experimental study of the eriochrome black T dye adsorption onto chitosan in aqueous solutions.

This study aims to evaluate and understand the adsorption of eriochrome black T (EB) by chitosan extracted from local shrimp shells under different experimental conditions. Chitosan samples were characterized by XRD, SEM, and FTIR. Experimental results indicate that the process was pH-dependent with a high adsorption capacity in acidic medium. The adsorption was rapid and kinetic data were suitably correlated to the pseudo-second-order kinetic model. EB molecules were adsorbed on monolayer according to the Langmuir model with an adsorption capacity of 162.3 mg/g. On the other hand, it should be noted that calculated quantum chemical parameters support the experimentally obtained results. The interaction energies calculated for (molecule/chitosan) complexes were in the order of H2EB- > HEB2- (O38) > HEB2- (O48) > EB > H3EB > EB3-, which means that the best and possible adsorption process can take place with H2EB- form. The molecular dynamics (MD) approach was performed to illuminate the nature of the relationship between the EB and the chitosan (110) surface. It was found that the chitosan (110) surface adsorbs EB molecule in a nearby parallel orientation. The higher negative adsorption energy determined for the H2EB- implies that the adsorption mechanism is the typical chemisorption.

Chemically modified carbon-based electrodes for the determination of paracetamol in drugs and biological samples / 药物分析学报

Paracetamol is a non-steroidal,anti-inflammatory drug widely used in pharmaceutical applications for its sturdy,antipyretic and analgesic action.However,an overdose of paracetamol can cause fulminant hepatic necrosis and other toxic effects.Thus,the development of advantageous analytical tools to detect and determine paracetamol is required.Due to simplicity,higher sensitivity and selectivity as well as costefficiency,electrochemical sensors were fully investigated in last decades.This review describes the advancements made in the development of electrochemical sensors for the paracetamol detection and quantification in pharmaceutical and biological samples.The progress made in electrochemical sensors for the selective detection of paracetamol in the last 10 years was examined,with a special focus on highly innovative features introduced by nanotechnology.As the literature is rather extensive,we tried to simplify this work by summarizing and grouping electrochemical sensors according to the by which manner their substrates were chemically modified and the analytical performances obtained.