Monitoring volatile compounds in sewer systems is of high importance due to the toxic and corrosive nature of various nuisance chemicals generated such as hydrogen sulfide (H2S). Hotspot monitoring facilitates identification of the location of the generated H2S, and thereby targeted treatment can be applied which eventually minimizes the use of chemicals and lowers the environmental effect within the sewer system. Here, we developed a portable detector that automatically extracts and delivers sewer contents to a microfluidic-based detector, fabricated by a selective microchannel embedded with a metal oxide semiconductor (MOS) sensor. Using a wide concentration range of H2S and ammonia (NH3) dissolved in water (i.e., two components to which the MOS sensor has potential cross-selectivity), a database for a machine learning model was developed. The model could classify between NH3 and H2S with 96.4% and 96.9% overall recall in separate and mixture aqueous solutions, respectively. Overall regression precisions of 84.6% and 88.8% were obtained in separate and mixture aqueous solutions, respectively. The developed setup was used in a field test (at Annacis Island (Delta, BC)) wastewater treatment plant where the results showed that the device could identify H2S and NH3 in raw influent samples and measuring the concentrations via regression with 94.6% and 83.5% overall recall and precision for H2S and NH3, respectively. These results demonstrate the promise of the developed automated detector and machine-learning data processing methodology for applications in in-situ wastewater monitoring or treatment through the detection of H2S hotspots for targeted mitigation efforts.

Hydrogen sulfide (H2S) is a corrosive, flammable, and extremely toxic chemical compound which is typically formed under septic conditions in wastewater collection systems, and the root cause of odor from and corrosion of liquid waste service infrastructure. To control and mitigate H2S buildup in sewer pipelines, it is necessary to detect low concentrations of dissolved H2S. In this paper, a chemiresistive sensor, based on graphene and polymethyl methacrylate (PMMA) is developed, which is able to electrochemically measure various concentrations of H2S in aqueous media. Several tests using electrochemical impedance spectroscopy (EIS) have been conducted to characterize the sensor. The synergetic properties of graphene as the conductive component and PMMA as the linker depicted excellent performance of the thin film sensor to H2S in the range of 10 -2 %v/v. The results demonstrated the potential of the sensor for detection of H2S in aqueous media with high selectivity and sensitivity.