Sorption is widely used for the removal of toxic heavy metals such as hexavalent chromium (Cr(VI)) from aqueous solutions. Green sorbents prepared from biomass are attractive, because they leverage the value of waste biomass and reduce the overall cost of water treatment. In this study, we fabricated biochar (BC) adsorbent from the biomass of water hyacinth (Eichhornia crassipes), an invasive species in many river channels. Pristine BC was further modified with nanoscale zero-valent iron (nZVI) and stabilized with chitosan (C) to form C–nZVI–BC. C–nZVI–BC adsorbent showed high hexavalent chromium sorption capacity (82.2 mg/g) at pH 2 and removed 97.34% of 50 mg/L Cr(VI) from aqueous solutions. The sorption capacity of chitosan–nZVI-modified biochar decreased while increasing the solution pH value and ionic strength. The results of a sorption test indicated that multiple mechanisms accounted for Cr(VI) removal by C–nZVI–BC, including complexation, precipitation, electrostatic interactions, and reduction. Our study suggests a way of adding value to biomass waste by considering environmental treatment purposes.

Many disinfection technologies have emerged recently in water treatment industry, which are designed to inactivate water pathogens with extraordinary efficiency and minimum side effects and costs. Current disinfection processes, including chlorination, ozonation, UV irradiation, and so on, have their inherent drawbacks, and have been proven ineffective under certain scenarios. Bacterial inactivation by noble metals has been traditionally used, and copper is an ideal candidate as a bactericidal agent owing to its high abundance and low cost. Building on previous findings, we explored the bactericidal efficiency of Cu(I) and attempted to develop it into a novel water disinfection platform. Nanosized copper ferrite was synthesized, and it was reduced by hydroxylamine to form surface bound Cu(I) species. Our results showed that the generated Cu(I) on copper ferrite surface could inactivate E. coli at a much higher efficiency than Cu(II) species. Elevated reactive oxygen species’ content inside the cell primarily accounted for the strong bactericidal role of Cu(I), which may eventually lead to enhanced oxidative stress towards cell membrane, DNA, and functional proteins. The developed platform in this study is promising to be integrated into current water treatment industry.

Gobeil’s model is one of the most widely used models to identify lead (Pb) pollution sources in the environment. It is based on a set of equations involving Pb isotope fractions. Although a well-established numerical method, Gobeil’s model is often unable to provide an accurate estimation of each pollution sources’ contribution. This paper comprehensively examines the drawbacks of Gobeil’s model based on a numerical analysis and proposes a revised numerical method that provides a more accurate estimation of Pb pollution sources. Briefly, the mathematical inaccuracy of Gobeil’s model mainly lies in the misinterpretation of “lead fingerprint ratio balance.” To address this problem, the new analytic model relies on the mass balance of total lead in the contaminated sites, and uses a set of linear equations to obtain the contribution of each pollution source based on the lead fingerprint. A subsequent case study from an industrial park in Guanzhong area of Shaanxi Province in China shows that we can calculate the lead contribution rates accurately with the new model.