Application of Gas Sensor Arrays in Assessment of Wastewater Purification Effects
A gas sensor array consisting of eight metal oxide semiconductor (MOS) type gas sensors was evaluated for its ability for assessment of the selected wastewater parameters. Municipal wastewater was collected in a wastewater treatment plant (WWTP) in a primary sedimentation tank and was treated in a l...
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MDPI AG
2014-12-01
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| Series: | Sensors |
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| Online Access: | http://www.mdpi.com/1424-8220/15/1/1 |
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| author | Łukasz Guz Grzegorz Łagód Katarzyna Jaromin-Gleń Zbigniew Suchorab Henryk Sobczuk Andrzej Bieganowski |
| author_facet | Łukasz Guz Grzegorz Łagód Katarzyna Jaromin-Gleń Zbigniew Suchorab Henryk Sobczuk Andrzej Bieganowski |
| author_sort | Łukasz Guz |
| collection | DOAJ |
| description | A gas sensor array consisting of eight metal oxide semiconductor (MOS) type gas sensors was evaluated for its ability for assessment of the selected wastewater parameters. Municipal wastewater was collected in a wastewater treatment plant (WWTP) in a primary sedimentation tank and was treated in a laboratory-scale sequential batch reactor (SBR). A comparison of the gas sensor array (electronic nose) response to the standard physical-chemical parameters of treated wastewater was performed. To analyze the measurement results, artificial neural networks were used. E-nose—gas sensors array and artificial neural networks proved to be a suitable method for the monitoring of treated wastewater quality. Neural networks used for data validation showed high correlation between the electronic nose readouts and: (I) chemical oxygen demand (COD) (r = 0.988); (II) total suspended solids (TSS) (r = 0.938); (III) turbidity (r = 0.940); (IV) pH (r = 0.554); (V) nitrogen compounds: N-NO3 (r = 0.958), N-NO2 (r = 0.869) and N-NH3 (r = 0.978); (VI) and volatile organic compounds (VOC) (r = 0.987). Good correlation of the abovementioned parameters are observed under stable treatment conditions in a laboratory batch reactor. |
| first_indexed | 2024-04-13T06:19:40Z |
| format | Article |
| id | doaj.art-250fee6a3b8f4b748d738ae06c29819b |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-04-13T06:19:40Z |
| publishDate | 2014-12-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-250fee6a3b8f4b748d738ae06c29819b2022-12-22T02:58:40ZengMDPI AGSensors1424-82202014-12-0115112110.3390/s150100001s150100001Application of Gas Sensor Arrays in Assessment of Wastewater Purification EffectsŁukasz Guz0Grzegorz Łagód1Katarzyna Jaromin-Gleń2Zbigniew Suchorab3Henryk Sobczuk4Andrzej Bieganowski5Faculty of Environmental Engineering, Lublin University of Technology, Nadbystrzycka 40B Str., Lublin 20-618, PolandFaculty of Environmental Engineering, Lublin University of Technology, Nadbystrzycka 40B Str., Lublin 20-618, PolandInstitute of Agrophysics, Polish Academy of Sciences, Doswiadczalna 4 Str., Lublin 20-290, PolandFaculty of Environmental Engineering, Lublin University of Technology, Nadbystrzycka 40B Str., Lublin 20-618, PolandFaculty of Environmental Engineering, Lublin University of Technology, Nadbystrzycka 40B Str., Lublin 20-618, PolandInstitute of Agrophysics, Polish Academy of Sciences, Doswiadczalna 4 Str., Lublin 20-290, PolandA gas sensor array consisting of eight metal oxide semiconductor (MOS) type gas sensors was evaluated for its ability for assessment of the selected wastewater parameters. Municipal wastewater was collected in a wastewater treatment plant (WWTP) in a primary sedimentation tank and was treated in a laboratory-scale sequential batch reactor (SBR). A comparison of the gas sensor array (electronic nose) response to the standard physical-chemical parameters of treated wastewater was performed. To analyze the measurement results, artificial neural networks were used. E-nose—gas sensors array and artificial neural networks proved to be a suitable method for the monitoring of treated wastewater quality. Neural networks used for data validation showed high correlation between the electronic nose readouts and: (I) chemical oxygen demand (COD) (r = 0.988); (II) total suspended solids (TSS) (r = 0.938); (III) turbidity (r = 0.940); (IV) pH (r = 0.554); (V) nitrogen compounds: N-NO3 (r = 0.958), N-NO2 (r = 0.869) and N-NH3 (r = 0.978); (VI) and volatile organic compounds (VOC) (r = 0.987). Good correlation of the abovementioned parameters are observed under stable treatment conditions in a laboratory batch reactor.http://www.mdpi.com/1424-8220/15/1/1gas sensor arrayelectronic nose (e-nose)sewage physical-chemical parameterswastewater treatmentsequencing batch reactors (SBR) |
| spellingShingle | Łukasz Guz Grzegorz Łagód Katarzyna Jaromin-Gleń Zbigniew Suchorab Henryk Sobczuk Andrzej Bieganowski Application of Gas Sensor Arrays in Assessment of Wastewater Purification Effects Sensors gas sensor array electronic nose (e-nose) sewage physical-chemical parameters wastewater treatment sequencing batch reactors (SBR) |
| title | Application of Gas Sensor Arrays in Assessment of Wastewater Purification Effects |
| title_full | Application of Gas Sensor Arrays in Assessment of Wastewater Purification Effects |
| title_fullStr | Application of Gas Sensor Arrays in Assessment of Wastewater Purification Effects |
| title_full_unstemmed | Application of Gas Sensor Arrays in Assessment of Wastewater Purification Effects |
| title_short | Application of Gas Sensor Arrays in Assessment of Wastewater Purification Effects |
| title_sort | application of gas sensor arrays in assessment of wastewater purification effects |
| topic | gas sensor array electronic nose (e-nose) sewage physical-chemical parameters wastewater treatment sequencing batch reactors (SBR) |
| url | http://www.mdpi.com/1424-8220/15/1/1 |
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