Files
Document type
ArticleVersion
Published versionPublication date
Publication license
Please use this identifier to cite or link to this item: https://hdl.handle.net/2445/176931
Aerial mapping of odorous gases in a wastewater treatment plant using a small drone
Journal Title
Director/Tutor
Journal ISSN
Volume Title
Related resource
Abstract
Wastewater treatment plants (WWTPs) are sources of greenhouse gases, hazardous air pollutants and offensive odors. These emissions can have negative repercussions in and around the plant, degrading the quality of life of surrounding neighborhoods, damaging the environment, and reducing employee's overall job satisfaction. Current monitoring methodologies based on fixed gas detectors and sporadic olfactometric measurements (human panels) do not allow for an accurate spatial representation of such emissions. In this paper we use a small drone equipped with an array of electrochemical and metal oxide (MOX) sensors for mapping odorous gases in a mid-sized WWTP. An innovative sampling system based on two (10 m long) flexible tubes hanging from the drone allowed near-source sampling from a safe distance with negligible influence from the down-wash of the drone's propellers. The proposed platform is very convenient for monitoring hard-to-reach emission sources, such as the plant's deodorization chimney, which turned out to be respon-sible for the strongest odor emissions. The geo-localized measurements visualized in the form of a two-dimensional (2D) gas concentration map revealed the main emission hotspots where abatement solutions were needed. A principal component analysis (PCA) of the multivariate sensor signals suggests that the proposed system can also be used to trace which emission source is responsible for a certain measurement.
Subject (English)
Citation
Citation
BURGUÉS, Javier, et al. Aerial mapping of odorous gases in a wastewater treatment plant using a small drone. Remote Sensing. 2021. Vol. 13, num. 1757-1769. ISSN 2072-4292. [consulted: 17 of August of 2026]. Available at: https://hdl.handle.net/2445/176931