Simultaneous monitoring of biofilm growth, microbial activity, and inorganic deposits on surfaces with an in situ, online, real-time, non-destructive, optical sensor

Abstract

Deposits on surfaces in water-bearing systems, also known as ‘fouling’, can lead to substantial losses in the performance of industrial processes as well as a decreased product quality. Early detection and localization of such deposits can, to a considerable extent, save such losses. However, most of the surfaces that become fouled, for example, in process water pipes, membrane systems, power plants, and food and beverage industries, are difficult to access and analyses conducted on the water phase do not reveal the site or extent of deposits. Furthermore, it is of interest to distinguish biological from non-biological deposits. Although they usually occur together, different countermeasures are necessary. Therefore, sensors are required that indicate the development of surface fouling in real-time, non-destructively, and in situ, preferably allowing for discrimination between chemical and/or biological deposits. In this paper, an optical deposit sensor is presented which fulfills these requirements. Based on multiple fluorescence excitation emission matrix analysis, it detects autofluorescence of amino acids as indicators of biomass. Autofluorescence of nicotinamide adenine dinucleotide + hydrogen is interpreted as an indicator of biological activity, thus it acts as a viability marker, making the method suited for assessing the efficacy of disinfection treatments. Scattering signals from abiotic deposits such as calcium carbonate or corrosion products can clearly be distinguished from biotic substances and monitored separately. The sensor provides an early warning of fouling, allowing for timely countermeasures to be deployed. It also provides an assessment of the success of cleaning treatments and is a promising tool for integrated antifouling strategies.

Keywords:

• biofilm
• biofouling
• deposit
• disinfection
• online sensor
• surface monitoring

Acknowledgments

This work has been funded partly by the European Commission in the FP 7 project SecurEau (project no. 217,976) as well as partly by the German Federal Ministry of Economics and Technology (ZIM project KF2037302WM0) which is gratefully acknowledged.