University of California, Irvine; Department of Civil and Environmental Engineering
Ziwei Han is a current Ph.D. student at the University of California, Irvine, majoring in environmental engineering. His research is mainly focused on water and soil remediation by using nanotechnology, especially using nanoscale zero-valent iron (nZVI) and its further modification nanoparticle. He is also particularly interested in applying machine learning to simulate contaminant removal efficiency. Recently his work is mainly about accessing the role of the sulfidation process in immobilizing arsenic in soil by nZVI and the biocompatibility of the remediation process. Also, he uses artificial neural network technology to predict the arsenic immobilization efficiency in soil.
Sustainability of arsenic immobilization in soil by iron nanoparticles and application of machine learning
Arsenic topped the ATSDR-EPA 2019 priority list of hazardous substances, due to its widespread occurrence and negative impacts. Engineered nanoparticles (ENPs) are promising for environmental remediation but there are concerns about their long-term effectiveness and ecological impact. In this study, we synthesize and applied nanoscale zero-valent iron (nZVI) and its sulfidated variant (S-nZVI) to arsenic contaminated soil while simultaneously monitoring the effects of the ENPs on earthworm (Eisenia fetida) for 168 d. Both nanoparticles successfully immobilized arsenic in soil, with 100% efficiency observed at 5 wt.% of ENPs. The immobilization of arsenic by the ENPs over 168 d was successfully modeled using artificial neural network (ANN). The survival of earthworm increased from 60% in untreated arsenic contaminated soil to 73% when the soil was treated with 0.3% SnZVI. However, survival decreased at higher SnZVI concentrations and all concentrations of nZVI, showing that SnZVI is a promising for safe soil remediation.