Monitoring water quality remains a critical challenge in water engineering, especially for applications requiring quick, continuous, and autonomous measurements. My primary research focuses on overcoming this challenge with optical sensing methods, including spectral imaging and diffuse reflectance spectrophotometry (DRS). These methods, both based on the analysis of light reflection at the water surface, makes it possible to monitor contaminants without the fouling and maintenance issues typical of conventional submerged sensors. I work both on method development and on their implementation to study pollution dynamics and processes in wastewaters.
Decentralized water treatment systems offer more flexibility and modularity than conventional, centralized treatment plants. However, such small-scale water treatment units are often confronted with a lack of personnel and resources for process performance monitoring, making it difficult to ensure effluent quality. Sensors based on diffuse reflectance spectrophotometry could represent a low-maintenance and autonomous solution to this problem. My research objective is to investigate how to use DRS to monitor treatment processes in small scale facilities, and how to leverage DRS measurement for better process control to optimize treatment performance.
My long-term vision is the development of smart urban wastewater management systems that can adapt to the pressures of global warming, emerging contaminants, and demographic shifts. By integrating innovative sensors for data collection, and modern tools to transform data into knowledge, I want to optimize urban drainage and treatment. This holistic approach seeks to bridge the gap between innovative technology and environmental engineering to ensure long-term environmental protection and public health.