Water pollution is a severe health concern. Several studies have recently demonstrated the efficacy of various approaches for treating wastewater from anthropogenic activities. Wastewater treatment is an artificial procedure that removes contaminants and impurities from wastewater or sewage before discharging the effluent back into the environment. It can also be recycled by being further treated or polished to provide safe quality water for use, such as potable water. Municipal and industrial wastewater treatment systems are designed to create effluent discharged to the surrounding environments and must comply with various authorities’ environmental discharge quality rules. An effective, low-cost, environmentally friendly, and long-term wastewater treatment system is critical to protecting our unique and finite water supplies. Moreover, this paper discusses water pollution classification and the three traditional treatment methods of precipitation/encapsulation, adsorption, and membrane technologies, such as electrodialysis, nanofiltration, reverse osmosis, and other artificial intelligence technology. The treatment performances in terms of application and variables have been fully addressed. The ultimate purpose of wastewater treatment is to protect the environment that is compatible with public health and socioeconomic considerations. Realization of the nature of wastewater is the guiding concept for designing a practical and advanced treatment technology to assure the treated wastewater’s productivity, safety, and quality.

Arsenic is a common contaminant in gold mine soil and tailings. Microbes present an opportunity for bio-treatment of arsenic, since it is a sustainable and cost-effective approach to remove arsenic from water. However, the development of existing bio-treatment approaches depends on isolation of arsenic-resistant microbes from arsenic contaminated samples. Microbial cultures are commonly used in bio-treatment; however, it is not established whether the structure of the cultured isolates resembles the native microbial community from arsenic-contaminated soil. In this milieu, a culture-independent approach using Illumina sequencing technology was used to profile the microbial community in situ. This was coupled with a culture-dependent technique, that is, isolation using two different growth media, to analyse the microbial population in arsenic laden tailing dam sludge based on the culture-independent sequencing approach, 4 phyla and 8 genera were identified in a sample from the arsenic-rich gold mine. Firmicutes (92.23%) was the dominant phylum, followed by Proteobacteria (3.21%), Actinobacteria (2.41%), and Bacteroidetes (1.49%). The identified genera included Staphylococcus (89.8%), Pseudomonas (1.25), Corynebacterium (0.82), Prevotella (0.54%), Megamonas (0.38%) and Sphingomonas (0.36%). The Shannon index value (3.05) and Simpson index value (0.1661) indicated low diversity in arsenic laden tailing. The culture dependent method exposed significant similarities with culture independent methods at the phylum level with Firmicutes, Proteobacteria and Actinobacteria, being common, and Firmicutes was the dominant phylum whereas, at the genus level, only Pseudomonas was presented by both methods. It showed high similarities between culture independent and dependent methods at the phylum level and large differences at the genus level, highlighting the complementarity between the two methods for identification of the native population bacteria in arsenic-rich mine. As a result, the present study can be a resource on microbes for bio-treatment of arsenic in mining waste.

Sustainable wastewater treatment is one of the biggest issues of the 21st century. Metals such as Zn²⁺ have been released into the environment due to rapid industrial development. In this study, dried watermelon rind (D-WMR) is used as a low-cost adsorption material to assess natural adsorbents’ ability to remove Zn²⁺ from synthetic wastewater. D-WMR was characterized using scanning electron microscope (SEM) and X-ray fluorescence (XRF). According to the results of the analysis, the D-WMR has two colours, white and black, and a significant concentration of mesoporous silica (83.70%). Moreover, after three hours of contact time in a synthetic solution with 400 mg/L Zn²⁺ concentration at pH 8 and 30 to 40 °C, the highest adsorption capacity of Zn²⁺ onto 1.5 g D-WMR adsorbent dose with 150 μm particle size was 25 mg/g. The experimental equilibrium data of Zn²⁺ onto D-WMR was utilized to compare nonlinear and linear isotherm and kinetics models for parameter determination. The best models for fitting equilibrium data were nonlinear Langmuir and pseudo-second models with lower error functions. Consequently, the potential use of D-WMR as a natural adsorbent for Zn²⁺ removal was highlighted, and error analysis indicated that nonlinear models best explain the adsorption data.