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Detection of wastewater treatment process disturbances in bioreactors using the e-nose technology

Identyfikatory
Warianty tytułu
PL
Wykrywanie zakłóceń procesu oczyszczania ścieków w bioreaktorze z wykorzystaniem e-nosa
Języki publikacji
EN
Abstrakty
EN
Wastewater treatment processes are subject to numerous disturbances during biological treatment of wastewater. In order to achieve and sustain suitable conditions of the process, basic wastewater parameters should be frequently monitored. While great improvements have been made in the automatization of treatment process, little is known about automatic measuring systems that can detect unusual process conditions in a bioreactor. Tracking these parameters can be difficult and the time required for the determination might vary from several minutes to few days. The objective of this study is to evaluate the use of an electronic nose in-house device (based on a non-selective gas sensor array) for the detection of process disturbances in a lab-scale sequencing batch reactor (SBR) during biological treatment of wastewater with activated sludge. Measurements were performed during a 12-hours working cycle. Continuous analyses of the headspace were performed using a sensor array based on the resistive Metal Oxide Semiconductor type (MOS) gas sensor. Based on the data obtained and the PCA analysis, this study showed that the e-nose technology can be used to predict or retrieve information about potential disruptions during wastewater processes using the e-nose technology.
Rocznik
Strony
405--418
Opis fizyczny
Bibliogr. 54 poz., rys., wykr., tab.
Twórcy
autor
  • Faculty of Environmental Engineering, Lublin University of Technology, ul. Nadbystrzycka 40B, 20-618 Lublin, Poland, phone +48 81 538 43 22
autor
  • Faculty of Environmental Engineering, Lublin University of Technology, ul. Nadbystrzycka 40B, 20-618 Lublin, Poland, phone +48 81 538 43 22
autor
  • Department of Civil and Environmental Engineering, Northwestern University, Evanston, Illinois 60208, United States
autor
  • Faculty of Environmental Engineering, Lublin University of Technology, ul. Nadbystrzycka 40B, 20-618 Lublin, Poland, phone +48 81 538 43 22
Bibliografia
  • [1] Thomas O, Theraulaz F, Cerda V, Constant D, Quevauviller P. Wastewater quality monitoring. Trends Anal Chem. 1997;16(7):419-424. DOI: 10.1016/S0165-9936(97)82859-2.
  • [2] Lobos-Moysa E, Dudziak M, Bodzek M. Effect of fatty acids and sterols on the efficiency of wastewater treatment by the activated sludge process in a batch system. Ochr Srod. 2010;32(2):53-56.
  • [3] Pomiès M, Choubert JM, Wisniewski C, Coquery M. Modelling of micropollutant removal in biological wastewater treatments: a review. Sci Total Environ. 2013;443:733-748. DOI: 10.1016/j.scitotenv.2012.11.037.
  • [4] Waclawek S, Grubel K, Chlad Z, Dudziak M, Cernik M. The impact of oxone on disintegration and dewaterability of waste activated sludge. Water Environ Res. 2016;88(2):152-157. DOI: 10.2175/106143016X14504669767139.
  • [5] Guz Ł, Sobczuk H, Suchorab Z. Odor measurement using portable device with semiconductor gas sensors array. Przem Chem. 2010;89(4):378-381.
  • [6] Zhang W, Tian F, Song A, Hu Y. Research on electronic nose system based on continuous wide spectral gas sensing. Microchem J. 2018;140:1-7. DOI: 10.1016/j.microc.2018.03.030.
  • [7] Wilson AD, Baietto M. Applications and advances in electronic-nose technologies. Sensors. 2009;9(7):5099-5148. DOI: 10.3390/s90705099.
  • [8] Kalman EL, Löfvendahl A, Winquist F, Lundström I. Classification of complex gas mixtures from automotive leather using an electronic nose. Anal Chim Acta. 2000;403(1-2):31-38. DOI: 10.1016/S0003-2670(99)00604-2.
  • [9] Wolfrum EJ, Meglen RM, Peterson D, Sluiter J. Metal oxide sensor arrays for the detection, differentiation, and quantification of volatile organic compounds at sub-parts-per-million concentration levels. Sens Actuator B. 2006;115(1):322-329. DOI: 10.1016/j.snb.2005.09.026.
  • [10] Krivetskiy V, Malkov I, Garshev A. Chemically modified nanocrystalline SnO2-based materials for nitrogen-containing gases detection using gas sensor array. J Alloy Compd. 2017;691:514-523. DOI: 10.1016/j.jallcom.2016.08.275.
  • [11] Nicolas J, Cerisier C, Delva J. Potential of a network of electronic noses to assess in real time the odour annoyance in the environment of a compost facility. 3rd Biannual Int Conf Environ Odour Monitoring. 2012;30:133-138. DOI: 10.3303/CET1230023.
  • [12] Kateb B, Ryan MA, Homer ML, Lara LM, Yin Y, Higa K, et al. Sniffing out cancer using the JPL electronic nose: A pilot study of a novel approach to detection and differentiation of brain cancer. Neuroimage. 2009;47(S2),T5-T9. DOI: 10.1016/j.neuroimage.2009.04.015.
  • [13] Bruins M, Rahim Z, Bos A, van de Sande WWJ, Endtz HP, van Belkum A. Diagnosis of active tuberculosis by e-nose analysis of exhaled air. Tuberculosis. 2013;93(2):232-238. DOI: 10.1016/j.tube.2012.10.002.
  • [14] Baldwin EA, Bai J, Plotto A, Dea S. Electronic noses and tongues: Applications for the food and pharmaceutical industries. Sensors. 2011;11:4744-4766. DOI: 10.3390/s110504744.
  • [15] Bonnefille M. Electronic noses: Sniffing fast, safe and objective. Cosmetics. 2007;6,9-12.
  • [16] Śliwińska M, Wiśniewska P, Dymerski T, Namieśnik J, Wardencki W. Food analysis using artificial senses. J Agric Food Chem. 2014;62(7):1423-1448. DOI: 10.1021/jf403215y.
  • [17] Wilson AD. Diverse applications of electronic-nose technologies in agriculture and forestry. Sensors. 2013;13(2):2295-2348. DOI: 10.3390/s130202295.
  • [18] Gebicki J, Bylinski H, Namiesnik J. Measurement techniques for assessing the olfactory impact of municipal sewage treatment plants. Environ Monit Assess. 2016;188(1):32. DOI: 10.1007/s10661-015-5024-2.
  • [19] Zhang WL, Tian FC, Song A, Hu YW. Research on electronic nose system based on continuous wide spectral gas sensing. Microchem J. 2018;140:1-7. DOI: 10.1016/j.microc.2018.03.030.
  • [20] Gancarz M, Wawrzyniak J, Gawrysiak-Witulska M, Wiącek D, Nawrocka A, Tadla M, et al. Application of electronic nose with MOS sensors to prediction of rapeseed quality. Measurement. 2017;103:227-234. DOI: 10.1016/j.measurement.2017.02.042.
  • [21] Guthrie B. Machine Olfaction. In: Buettner A, editor. Springer Handbook of Odor. Springer Handbooks. Cham: Springer; 2017. DOI: 10.1007/978-3-319-26932-0_21
  • [22] Szulczyński B, Wasilewski T, Wojnowski W, Majchrzak T, Dymerski T, Namieśnik J, et al. Different ways to apply a measurement instrument of e-nose type to evaluate ambient air quality with respect to odour nuisance in a vicinity of municipal processing plants. Sensors. 2017;17(11):2671. DOI: 10.3390/s17112671.
  • [23] Sunil TT, Chaudhuri S, Sharma MU. Sensor Selection for E-Nose. In: Pal A, Pal SK, editors. Pattern Recognition and Big Data. Singapore: World Scientific Publishing Co Pte Ltd; 2018 DOI: 10.1142/9789813144552_0023.
  • [24] Nakamoto T. Odor handling and delivery systems. In: Pearce TC, Schiffman SS, Nagle HT, Gardner JW, editors. Handbook of Machine Olfaction. Weinheim: Wiley-VCH Verlag GmbH & Co. KGaA; 2003. DOI: 10.1002/3527601597.ch3.
  • [25] Blanco-Rodríguez A, Camara VF, Campo F, Becherán L, Durán A, Vieira VD, et al. Development of an electronic nose to characterize odours emitted from different stages in a wastewater treatment plant. Water Res. 2018;134,92-100. DOI: 10.1016/j.watres.2018.01.067.
  • [26] Babko R, Kuzmina T, Jaromin-Glen K, Bieganowski A. Bioindication assessment of activated sludge adaptation in a lab-scale experiment. Ecol Chem Eng S. 2014;21(4): 605-616. DOI: 10.1515/eces-2014-0043.
  • [27] Sytek-Szmeichel K, Podedworna J, Zubrowska-Sudol M. Efficiency of wastewater treatment in SBR and IFAS-MBSBBR systems in specified technological conditions. Water Sci Technol. 2016;73(6):1349-1356. DOI: 10.2166/wst.2015.611.
  • [28] Świerczyńska A, Bohdziewicz J, Puszczało E. Treatment of industrial wastewater in the sequential membrane bioreactor. Ecol Chem Eng S. 2016;23(2):285-295. DOI: 10.1515/eces-2016-0020.
  • [29] Capelli L, Sironi S, Céntola P, Del Rosso R, Grande MI. Electronic noses for the continuous monitoring of odours from a wastewater treatment plant at specific receptors: Focus on training methods. Sens Actuator B. 2008;131:53-62. DOI: 10.1016/j.snb.2007.12.004.
  • [30] Nake A, Dubreuil B, Raynaud C, Talou T. Outdoor in situ monitoring of volatile emissions from wastewater treatment plants with two portable technologies of electronic noses. Sens Actuator B. 2005;106:36-39. DOI: 10.1016/j.snb.2004.05.034.
  • [31] Giuliani S, Zarra T, Nicolas J, Naddeo V. An alternative approach of the e-nose training phase in odour impact assessment. Chem Eng Transact. 2012;30:139-144. DOI: 10.3303/CET1230024.
  • [32] Littarru P. Environmental odours assessment from waste treatment plants: dynamic olfactometry in combination with sensorial analysers “electronic noses”. Waste Manage. 2007;27(2):302-309. DOI: 10.1016/j.wasman.2006.03.011.
  • [33] Zarra T, Reiser M, Naddeo V, Belgiorno V, Kranert M. Odour emissions characterization from wastewater treatment plants by different measurement methods. Chem Eng Transact. 2014;40:37-42. DOI: 10.3303/CET1440007.
  • [34] Barczak R, Kulig A, Szydłowski M. Olfactometric methods application for odour nuisance assessment of wastewater treatment facilities in Poland. Chem Eng Transact. 2012;30,187-192. DOI: 10.3303/CET1230032.
  • [35] Michałkiewicz M, Kruszelnicka I, Widomska M. The variability of the concentration of bioaerosols above the chambers of biological wastewater treatment. Ecol Chem Eng S. 2018;25(2):267-278. DOI: 10.1515/eces-2018-0018.
  • [36] Wang YJ, Lan HC, Li L, Yang KX, Qu JH, Liu JX. Chemicals and microbes in bioaerosols from reaction tanks of six wastewater treatment plants: survival factors, generation sources, and mechanisms. Sci Rep. 2018;8,9362. DOI: 10.1038/s41598-018-27652-2.
  • [37] Onkal-Engin G, Demir I, Engin SN. E-nose response classification of sewage odors by neural networks and fuzzy clustering. Advanc Natural Comput. 2005;3611:648-651. DOI: 10.1007/11539117_92.
  • [38] Stuetz RM, Fenner RA, Engin G. Assessment of odours from sewage treatment works by an electronic nose. H2S analysis and olfactometry. Water Res. 1999;33(2):453-461. DOI: 10.1016/S0043-1354(98)00246-2.
  • [39] Dewettinck T, Van Hege K, Verstraete W. The electronic nose as a rapid sensor for volatile compounds in treated domestic wastewater. Water Res. 2001;35(10):75-83. DOI: 10.1016/S0043-1354(00)00530-3.
  • [40] Bourgeois W, Gardey G, Servieres M, Stuetz RM. A chemical sensor array based system for protecting wastewater treatment plants. Sens Actuator B. 2003;91:109-116. DOI: 10.1016/S0925-4005(03)00074-1.
  • [41] Bourgeois W, Stuetz RM. Use of a chemical sensor array for detecting pollutants in domestic wastewater. Water Res. 2002;36,4505-4512. DOI: 10.1016/S0043-1354(02)00183-5.
  • [42] Bourgeois W, Hogben P, Pike A, Stuetz RM. Development of a sensor array based measurement system for continuous monitoring of water and wastewater. Sens Actuator B. 2003;88(3):312-319. DOI: 10.1016/S0925-4005(02)00377-5.
  • [43] Guz Ł, Łagód G, Jaromin-Gleń K, Suchorab Z, Sobczuk H, Bieganowski A. Application of gas sensor arrays in assessment of wastewater purification effects. Sensors. 2015;15:1-21. DOI: 10.3390/s150100001.
  • [44] Jaromin-Gleń K, Babko R, Łagód G, Sobczuk H. Community composition and abundance of protozoa under different concentration of nitrogen compounds at “Hajdow” wastewater treatment plant. Ecol Chem Eng S. 2013;20(1):127-139. DOI: 10.2478/eces-2013-0010.
  • [45] Guz Ł, Sobczuk H, Wasag H. Device for determination of odour chemical substances in air. Przem Chem. 2009;88(5):446-449.
  • [46] TGS 2600 - for the detection of Air Contaminants. Figaro series datasheet. http://www.figarosensor.com. 2018.
  • [47] Krzanowski WJ. Principles of Multivariate Analysis: A User’s Perspective. New York: Oxford University Press Inc.; 2008. ISBN 9780198507086.
  • [48] Fu J, Li G, Qin Y, Freeman WJ. A pattern recognition method for electronic noses based on an olfactory neural network. Sens Actuator B. 2007;125(2):489-497. DOI: 10.1016/j.snb.2007.02.058.
  • [49] Smolarz A, Kotyra A, Wojcik W, Ballester J. Advanced diagnostics of industrial pulverized coal burner using optical methods and artificial intelligence. Exp Therm Fluid Sci. 2012;43:82-89. DOI: 10.1016/j.snb.2007.02.058.
  • [50] Brereton RG, Lloyd GR. Partial least squares discriminant analysis: taking the magic away. J Chemometr. 2014;28(4):213-225. DOI: 10.1002/cem.2609.
  • [51] Kamiński K, Kamiński W, Mizerski T. Application of artificial neural networks to the technical condition assessment of water supply systems. Ecol Chem Eng S. 2017;24(1),31-40. DOI: 10.1515/eces-2017-0003.
  • [52] Macek-Kamińska K, Stemplewski S. Application of neural networks in diagnostics of chemical compounds based on their infrared spectra. Ecol Chem Eng S. 2017;24(1):107-118. DOI: 10.1515/eces-2017-0008.
  • [53] Onkal-Engina G, Demir I, Engin SN. Determination of the relationship between sewage odour and BOD by neural networks. Environ Model Softw. 2005;20:843-850. DOI: 10.1016/j.envsoft.2004.04.012.
  • [54] Stuetz RM, Fenner RA, Engin G. Characterisation of wastewater using an electronic nose. Water Res. 1999;33(2):442-452. DOI: 10.1016/S0043-1354(98)00245-0.
Uwagi
PL
Opracowanie rekordu w ramach umowy 509/P-DUN/2018 ze środków MNiSW przeznaczonych na działalność upowszechniającą naukę (2018).
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-163ef96e-c275-48ef-bde3-2e8687a3ea57
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