Detection and removal of emerging contaminants from water bodies: A statistical approach

Abstract

The integration of mathematical modelling in different scientific domains has increased dramatically in recent years. In general, modelling involves using programming languages, manipulating matrices, designing algorithms, and tracking functions and data to gain new insights and more quantitative and qualitative information about systems. These strategies have motivated researchers to investigate numerous approaches to accurately solve a variety of problems. In this direction, modelling and simulation have been used to create sensitive and focused detection methods for a variety of applications, including environmental control. New pollutants, including pesticides, heavy metals, and medications, are endangering wildlife by poisoning water supplies. As a result, numerous biosensors that use modelling for effective environmental monitoring have been documented in the literature. The most current model-inspired biosensors used for environmental monitoring will be discussed in this review study. Additionally, each analytical biosensor’s capabilities and degree of success will be discussed. Finally, present difficulties in this area will be highlighted.