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. 2020 May 20;20(10):2888.
doi: 10.3390/s20102888.

Fecal Malodor Detection Using Low-Cost Electrochemical Sensors

Siddharth Kawadiya  1 , Claire Welling  2 , Sonia Grego  2 , Marc A Deshusses  1   3
Affiliations

Fecal Malodor Detection Using Low-Cost Electrochemical Sensors

Siddharth Kawadiya et al. Sensors (Basel). .

Abstract

Technology innovation in sanitation is needed for the 4.2 billion people worldwide, lacking safely managed sanitation services. A major requirement for the adoption of these technologies is the management of malodor around toilet and treatment systems. There is an unmet need for a low-cost instrumented technology for detecting the onset of sanitation malodor and triggering corrective actions. This study combines sensory data with low-cost gas sensor data on malodor emanating from feces. The response of 10 commercial electrochemical gas sensors was collected alongside olfactometric measurements. Odor from fecal specimens at different relevant dilution as well as specimens with pleasant odors as a control were evaluated for a total of 64 responses. Several of the sensors responded positively to the fecal odor, with the formaldehyde, hydrogen sulfide, and ammonia sensors featuring the highest signal to noise ratio. A positive trend was observed between the sensors' responses and the concentration of the odorant and with odor intensity, but no clear correspondence with dilution to threshold (D/T) values was found. Selected sensors were responsive both above and below the intensity values used as the cutoff for offensive odor, suggesting the possibility of using those sensors to differentiate odor offensiveness based just on the magnitude of their response. The specificity of the sensors suggested that discrimination between the selected non-fecal and fecal odors was possible. This study demonstrates that some of the evaluated sensors could be used to assemble a low-cost malodor warning system.

Keywords: electronic nose; low-cost sensors; malodor; odor.

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Conflict of interest statement

The authors declare no conflict of interest. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript, or in the decision to publish the results.

Figures

Figure 1
Figure 1
Schematic of the experimental setup for odor generation and collection (top left), and odor analysis (top right), and pictures of the sensor box (bottom left) and of the overall test system (bottom right).
Figure 2
Figure 2
Typical dose response vs. time for Membrapor formaldehyde sensor when exposed to air containing fecal odor. The green bands indicate exposure to malodor. The values above the graph indicate the concentration with respect to the original odor sample (i.e., 100% is undiluted, 71% means 71% odor sample, and 29% odorless air).
Figure 3
Figure 3
Dilution to threshold (D/T) (A and B panels) and odor intensity (C and D panels) of fecal odor samples tested with the low-cost sensors as a function of their concentration with respect to the original odor sample (i.e., 100% is undiluted). See the Methods section for details.
Figure 4
Figure 4
Heatmap showing the signal to noise (S/N) ratios to 64 odorant exposures for the 10 sensors tested. The horizontal dashed lines separate the different odor intensity levels.
Figure 5
Figure 5
Dose response to three fecal malodor specimens by four sensors, two Membrapor (CH2O and NH3, A,B), and two SGX sensors (C,D). The dose (%) represents the concentration with respect to the original odor sample. The olfactometry data of each sample (reported as dilution to threshold, or D/T) is indicated by the marker type. Error bars represent the standard deviation.
Figure 6
Figure 6
S/N ratios for three malodors specimen by four sensors (same as Figure 5) as a function of the odor intensity. Error bars represent the standard deviation.
See this image and copyright information in PMC

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