Application of gas sensor arrays in assessment of wastewater purification effects
Artykuł w czasopiśmie
MNiSW
30
Lista A
| Status: | |
| Autorzy: | Guz Łukasz, Łagód Grzegorz, Jaromin-Gleń Katarzyna, Suchorab Zbigniew, Sobczuk Henryk, Bieganowski Andrzej |
| Rok wydania: | 2015 |
| Wersja dokumentu: | Drukowana | Elektroniczna |
| Język: | angielski |
| Numer czasopisma: | 1 |
| Wolumen/Tom: | 15 |
| Strony: | 1 - 21 |
| Data nominalna: | 2014 |
| Impact Factor: | 2,033 |
| Web of Science® Times Cited: | 49 |
| Scopus® Cytowania: | 51 |
| Bazy: | Web of Science | Scopus | Web of Science | Scopus | PubMed | MEDLINE | CAS - Chemical Abstracts | CAB Abstracts i inne |
| Efekt badań statutowych | NIE |
| Materiał konferencyjny: | NIE |
| Publikacja OA: | TAK |
| Licencja: | |
| Sposób udostępnienia: | Witryna wydawcy |
| Wersja tekstu: | Ostateczna wersja opublikowana |
| Czas opublikowania: | W momencie opublikowania |
| Abstrakty: | angielski |
| 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. |
