Drone-Based System for Odour Monitoring in Wastewater Treatment Plants
Researchers at the Institute for Bioengineering of Catalonia (IBEC) and The Barcelona Institute of Science and Technology, led by Santiago Marco, have introduced an innovative drone-based system for characterizing odour emissions in wastewater treatment plants (WWTPs).
Conventional methods rely on dynamic olfactometry, where human assessors sniff and analyze air samples collected from the plant. However, this process is slow, costly, and infrequent, hindering rapid response to issues. In response, the team devised a novel solution: a small rotary-wing drone equipped with a lightweight electronic nose.
This “sniffing drone” utilizes a ten-meter tube to intake air, delivering it to a sensor chamber equipped with 21 gas sensors. These sensors, coupled with machine learning algorithms, predict odour concentrations akin to human assessments following EN13725 methodology. Crucially, the drone also collects air samples for post-flight dynamic olfactometry, ensuring calibration and validation of predictive models.
To evaluate the system’s efficacy, the team conducted extensive measurement campaigns in a Spanish WWTP, encompassing various plant operations and weather conditions. Impressively, ML algorithms trained on transient flight conditions outperformed traditional steady-state lab signals, showcasing the system’s adaptability.
Comparison with dynamic olfactometry revealed negligible bias and 95% limits of agreement within a factor of four. While this difference is partially attributed to olfactometric uncertainties, the immediacy of drone-based predictions offsets this discrepancy, offering practical advantages.
In summary, this drone-based system marks a significant advancement in WWTP odour monitoring, providing real-time insights that empower operators to swiftly address challenges and enhance environmental management.
Photo Credits: Graphical Abstract – Burgués et. al, Science of The Total Environment (2022).
