Recent Trends in Biosensors for Environmental Quality Monitoring

The monitoring of environmental pollution requires fast, reliable, cost-effective and small devices. This need explains the recent trends in the development of biosensing devices for pollutant detection. The present review aims to summarize the newest trends regarding the use of biosensors to detect environmental contaminants. Enzyme, whole cell, antibody, aptamer, and DNA-based biosensors and biomimetic sensors are discussed. We summarize their applicability to the detection of various pollutants and mention their constructive characteristics. Several detection principles are used in biosensor design: amperometry, conductometry, luminescence, etc. They differ in terms of rapidity, sensitivity, profitability, and design. Each one is characterized by specific selectivity and detection limits depending on the sensitive element. Mimetic biosensors are slowly gaining attention from researchers and users due to their advantages compared with classical ones. Further studies are necessary for the development of robust biosensing devices that can successfully be used for the detection of pollutants from complex matrices without prior sample preparation.

Automated summary

The development of fast, reliable, cost-effective, and small biosensing devices is crucial for environmental pollution monitoring. This review discusses the latest trends in using biosensors to detect environmental contaminants. Different types of biosensors, including enzyme, whole cell, antibody, aptamer, DNA-based biosensors, and biomimetic sensors, are discussed, highlighting their applicability and construction characteristics. Various detection principles, such as amperometry, conductometry, and luminescence, are used in biosensor design, each with its specific selectivity and detection limits. Mimetic biosensors are gaining attention due to their advantages over classical ones. Further studies are needed for the development of robust biosensing devices capable of detecting pollutants from complex matrices without prior sample preparation.