Progress of photocatalytic oxidation-adsorption synergistic removal of organic arsenic in water.

Photocatalytic oxidation-adsorption synergistic treatment of organic arsenic pollutants is a promising wastewater treatment technology, which not only degrades organic arsenic pollutants by photocatalytic degradation but also removes the generated inorganic arsenic by adsorption. This paper compares the results of photocatalytic oxidation-adsorption co-treatment of organic arsenic pollutants such as monomethylarsonic acid, dimethylarsinic acid, phenylarsonic acid, p-arsanilic acid, and 3-nitro-4-hydroxyphenylarsonic acid on titanium dioxide, goethite, zinc oxide, and copper oxide. It examines the influence of the morphology of organic arsenic molecules, pH, coexisting ions, and the role of natural organic matter. The photocatalytic oxidation-adsorption co-treatment mechanism is investigated, comparing the hydroxyl radical oxidation mechanism, the hydroxyl radical and superoxide anion radical cooxidation mechanism, and the hydroxyl radical and hole cooxidation mechanism. Finally, the future prospects of metal oxide photocatalytic materials and the development of robust and efficient technologies for removing organic arsenic are envisioned.

Application of surface-enhanced Raman scattering to qualitative and quantitative analysis of arsenic species.

Given the toxicity of arsenic, there is an urgent need for the development of efficient and reliable detection systems. Raman spectroscopy, a powerful tool for material characterization and analysis, can be used to explore the properties of a wide range of different materials. Surface-enhanced Raman spectroscopy (SERS) can detect low concentrations of chemicals. This review focuses on the progress of qualitative and quantitative studies of the adsorption processes of inorganic arsenic and organic arsenic in aqueous media using Raman spectroscopy in recent years and discusses the application of Raman spectroscopy theory simulations to arsenic adsorption processes. Sliver nanoparticles are generally used as the SERS substrate to detect arsenic. Inorganic arsenic is chemisorbed onto the silver surface by forming As-O-Ag bonds, and the Raman shift difference in the As-O stretching (∼60 cm-1) between As(V) and As(III) allows SERS to detect and distinguish between As(V) and As(III) in groundwater samples. For organic arsenicals, specific compounds can be identified based on spectral differences in the vibration modes of the chemical bonds. Under the same laser excitation, the intensity of the Raman spectra for different arsenic concentrations is linearly related to the concentration, thus allowing quantitative analysis of arsenic. Molecular modeling of adsorbed analytes via density functional theory calculation (DFT) can predict the Raman shifts of analytes in different laser wavelengths.