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MATHEMATICAL MODELLING OF THE REMOVAL OF ORGANIC MICROPOLLUTANTS IN THE ACTIVATED SLUDGE PROCESS: A LINEAR BIODEGRADATION MODEL

Part of: Mathematical biology in general

Published online by Cambridge University Press:  05 November 2018

MARK I. NELSON Open the ORCID record for MARK I. NELSON [Opens in a new window] ,
RUBAYYI T. ALQAHTANI  and
FAISAL I. HAI
MARK I. NELSON*
Affiliation:
School of Mathematics and Applied Statistics, University of Wollongong, NSW 2522, Australia email mnelson@uow.edu.au
RUBAYYI T. ALQAHTANI
Affiliation:
Department of Mathematics and Statistics, College of Science, Al-Imam University, Riyadh 11566, Saudi Arabia email rtaa648@uowmail.edu.au
FAISAL I. HAI
Affiliation:
Strategic Water Infrastructure Laboratory, School of Civil, Mining and Environmental Engineering, University of Wollongong, NSW 2522, Australia email faisal@uow.edu.au
*
✉mnelson@uow.edu.au
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Abstract

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Before wastewaters can be released into the environment, they must be treated to reduce the concentration of organic pollutants in the effluent stream. There is a growing concern as to whether wastewater treatment plants are able to effectively reduce the concentration of micropollutants that are also contained in their influent streams. We investigate the removal of micropollutants in treatment plants by analysing a model that includes biodegradation and sorption as the main mechanisms of micropollutant removal. For the latter a linear adsorption model is used in which adsorption only occurs onto particulates.

The steady-state solutions of the model are found and their stability is determined as a function of the residence time. In the limit of infinite residence time, we show that the removal of biodegradable micropollutants is independent of the processes of adsorption and desorption. The limiting concentration can be decreased by increasing the concentration of growth-related macropollutants. Although, in principle, it is possible that the concentration of micropollutants is minimized at a finite value of the residence time, this was found not to be the case for the particular biodegradable micropollutants considered.

For nonbiodegradable pollutants, we show that their removal is always optimized at a finite value of the residence time. For finite values of the residence time, we obtain a simple condition which identifies whether biodegradation is more or less efficient than adsorption as a removal mechanism. Surprisingly, we find that, for the micropollutants considered, adsorption is always more important than biodegradation, even when the micropollutant is classified as being highly biodegradable with low adsorption.

Keywords

activated sludgebiodegradationmathematical modellingmicropollutantswastewater treatment

MSC classification

Primary: 92B05: General biology and biomathematics
Type
Research Article
Information
The ANZIAM Journal , Volume 60 , Issue 2 , October 2018 , pp. 191 - 229
Copyright
© 2018 Australian Mathematical Society 

References

Abegglen, C., Joss, A., McArdell, C. S., Fink, G., Schlüsener, M. P., Ternes, T. A. and Siegrist, H., “The fate of selected micropollutants in a single-house MBR”, Water Res. 43 (2009) 2036–2046; doi:10.1016/j.watres.2009.02.005.Google Scholar
Alex, J., Benedetti, L., Copp, J., Gernaey, K. V., Jeppsson, U., Nopens, I., Pons, M.-N., Rieger, L., Rosen, C., Steyer, J. P., Vanrolleghem, P. and Winkler, S., “Benchmark simulation model no. 1 (BSM1)”, CODEN:LUTEDX/(TEIE-7229) 80-2186, Department of Industrial Electrical Engineering and Automation, Lund University, 1998.http://www.iea.lth.se/publications/Reports/LTH-IEA-7229.pdf.Google Scholar
Bürger, R., Careaga, J., Diehl, S., Mejías, C., Nopens, I., Torfs, E. and Vanrolleghem, P. A., “Simulations of reactive settling of activated sludge with a reduced biokinetic model”, Comput. Chem. Eng. 92 (2016) 216–229; doi:10.1016/j.compchemeng.2016.04.037.Google Scholar
Byrns, G., “The fate of xenobiotic organic compounds in wastewater treatment plants”, Water Res. 35 (2001) 2523–2533; doi:10.1016/S0043-1354(00)00529-7.Google Scholar
Cadet, C., Martins, V. D. S. and Dochain, D., “Dynamic modeling of clarifier–thickeners for the control of wastewater treatment plants: a critical analysis”, in: 19th Int. Conf. System Theory, Control and Computing (ICSTCC), 2015 571–576; doi:10.1109/ICSTCC.2015.7321354.Google Scholar
Cowan, C. E., Larson, R. J., Feijtel, T. C. J. and Rapaport, R. A., “An improved model for predicting the fate of consumer product chemicals in wastewater treatment plants”, Water Res. 27 (1993) 561–573; doi:10.1016/0043-1354(93)90165-E.Google Scholar
Criddle, C. S., “The kinetics of cometabolism”, Biotechnol. Bioeng. 41 (1993) 1048–1056; doi:10.1002/bit.260411107.Google Scholar
Delgadillo-Mirquez, L., Lardon, L., Steyer, J.-P. and Patureau, D., “A new dynamic model for bioavailability and cometabolism of micropollutants during anaerobic digestion”, Water Res. 45 (2011) 4511–4521; doi:10.1016/j.watres.2011.05.047.Google Scholar
Diehl, S., Zambrano, J. and Carlsson, B., “Steady-state analysis of activated sludge processes with a settler model including sludge compression”, Water Res. 88 (2016) 104–116; doi:10.1016/j.watres.2015.09.052.Google Scholar
Diehl, S., Zambrano, J. and Carlsson, B., “Steady-state analyses of activated sludge processes with plug-flow reactor”, J. Environ. Chem. Eng. 5 (2017) 795–809; doi:10.1016/j.jece.2016.06.038.Google Scholar
Ekama, G. A., Bernard, G. I., Gunthert, F. W., Krebs, P., McCorquodale, J. A., Parker, D. S. and Wahlberg, E. J., Secondary settling tanks: theory, modelling, design and operation (IWA, London, 1997).Google Scholar
Fernandez-Fontaina, E., Carballa, M., Omil, F. and Lema, J. M., “Modelling cometabolic biotransformation of organic micropollutants in nitrifying reactors”, Water Res. 65 (2014) 371–383; doi:10.1016/j.watres.2014.07.048.Google Scholar
Fernandez-Fontaina, E., Omil, F., Lema, J. M. and Carballa, M., “Influence of nitrifying conditions on the biodegradation and sorption of emerging micropollutants”, Water Res. 46 (2012) 5434–5444; doi:10.1016/j.watres.2012.07.037.Google Scholar
Fernandez-Fontaina, E., Pinho, I., Carballa, M., Omil, F. and Lema, J. M., “Biodegradation kinetic constants and sorption coefficients of micropollutants in membrane bioreactors”, Biodegradation 24 (2013) 165–177; doi:10.1007/s10532-012-9568-3.Google Scholar
Hai, F. I., Nghiem, L. D., Khan, S. J., Price, W. E. and Yamamoto, K., “Wastewater reuse: removal of emerging trace organic contaminants”, in: Membrane biological reactors: theory, modeling, design, management and applications to wastewater reuse (eds Hai, F. I., Yamamoto, K. and Lee, C.), (IWA, London, 2014) 165–205.Google Scholar
Henze, M., Grady, C. P. L. Jr, Gujer, W., Marais, G. V. R. and Matsuo, T., “A general model for single-sludge wastewater treatment systems”, Water Res. 21 (1987) 505–515; doi:10.1016/0043-1354(87)90058-3.Google Scholar
Jacobsen, B. N. and Arvin, E., “Biodegradation kinetics and fate modelling of pentachlorophenol in bioaugmented activated sludge reactors”, Water Res. 30 (1996) 1184–1194; doi:10.1016/0043-1354(95)00259-6.Google Scholar
Jeppsson, U. and Diehl, S., “An evaluation of a dynamic model of the secondary clarifier”, Water Sci. Technol. 34(5–6) (1996) 19–26; wst.iwaponline.com/content/34/5-6/19.Google Scholar
Jeppsson, U. and Diehl, S., “On the modelling of the dynamic propagation of biological components in the secondary clarifier”, Water Sci. Technol. 34(5–6) (1996) 85–92; doi:10.1016/0273-1223(96)00632-4.Google Scholar
Joss, A., Zabczynski, S., Göbel, A., Hoffmann, B., Löffler, D., McArdell, C. S., Ternes, T. A., Thomsen, A. and Siegrist, H., “Biological degradation of pharmaceuticals in municipal wastewater treatment: proposing a classification scheme”, Water Res. 40 (2006) 1686–1696; doi:10.1016/j.watres.2006.02.014.Google Scholar
Karpinska, A. M. and Bridgeman, J., “CFD-aided modelling of activated sludge systems—a critical review”, Water Res. 88 (2016) 861–879; doi:10.1016/j.watres.2015.11.008.Google Scholar
Li, B. and Stenstrom, M. K., “Research advances and challenges in one-dimensional modeling of secondary settling tanks—a critical review”, Water Res. 65 (2014) 40–63; doi:10.1016/j.watres.2014.07.007.Google Scholar
Li, B. and Stenstrom, M. K., “A sensitivity and model reduction analysis of one-dimensional secondary settling tank models under wet-weather flow and sludge bulking conditions”, Chem. Eng. J. 288 (2016) 813–823; doi:10.1016/j.cej.2015.12.055.Google Scholar
Li, B. and Stenstrom, M. K., “Practical identifiability and uncertainty analysis of the one-dimensional hindered-compression continuous settling model”, Water Res. 90 (2016) 235–246; doi:10.1016/j.watres.2015.12.034.Google Scholar
Luo, Y., Guo, W., Ngo, H. H., Nghiem, L. D., Hai, F. I., Zhang, J., Liang, S. and Wang, X. C., “A review on the occurrence of micropollutants in the aquatic environment and their fate and removal during wastewater treatment”, Sci. Total Environ. 473–474 (2014) 619–641; doi:10.1016/j.scitotenv.2013.12.065.Google Scholar
Melcer, H., Bell, J. P., Thompson, D. J., Yendt, C. M., Kemp, J. and Steel, P., “Modeling volatile organic contaminants fate in wastewater treatment plants”, J. Environ. Eng. 120 (1994) 588–609; doi:10.1061/(ASCE)0733-9372(1994)120:3(588).Google Scholar
Nelson, M. I., Quigley, J. L. and Chen, X. D., “A fundamental analysis of continuous flow bioreactor and membrane bioreactor models with non-competitive product inhibition”, Asia-Pac. J. Chem. Eng. 4 (2009) 107–117; doi:10.1002/apj.234.Google Scholar
Orhon, D., Babuna, F. G. and Karahan, O., Industrial wastewater treatment by activated sludge, 1st edn (IWA, London, 2009).Google Scholar
Parker, W. J., Monteith, H. D., Bell, J. P., Melcer, H. and Mac Berthouex, P., “Comprehensive fate model for metals in municipal wastewater treatment”, J. Environ. Eng. 120 (1994) 1266–1283; doi:10.1061/(ASCE)0733-9372(1994)120:5(1266).Google Scholar
Pomiès, M., Choubert, J.-M., Wisniewski, C. and Coquery, M., “Modelling of micropollutant removal in biological wastewater treatments: a review”, Sci. Total Environ. 443 (2013) 733–748; doi:10.1016/j.scitotenv.2012.11.037.Google Scholar
Ramin, E., Flores-Alsina, X., Sin, G., Gernaey, K. V., Jeppsson, U., Mikkelsen, P. S. and Plósz, B. G., “Influence of selecting secondary settling tank sub-models on the calibration of WWTP models—a global sensitivity analysis using BSM2”, Chem. Eng. J. 241 (2014) 28–34; doi:10.1016/j.cej.2013.12.015.Google Scholar
Siegrist, H., Alder, A., Gujer, W. and Giger, W., “Behavior and modeling of NTA degradation in activated-sludge systems”, Water Sci. Technol. 21 (1989) 315–324; http://wst.iwaponline.com/content/21/4-5/315.Google Scholar
Struijs, J., Stoltenkamp, J. and van de Meent, D., “A spreadsheet-based box model to predict the fate of xenobiotics in a municipal wastewater treatment plant”, Water Res. 25 (1991) 891–900; doi:10.1016/0043-1354(91)90170-U.Google Scholar
Suarez, S., Lema, J. M. and Omil, F., “Removal of pharmaceutical and personal care products (PPCPs) under nitrifying and denitrifying conditions”, Water Res. 44 (2010) 3214–3224; doi:10.1016/j.watres.2010.02.040.Google Scholar
Takács, I. and Ekama, G. A., “Final settling”, in: Biological wastewater treatment (eds Henze, M., van Loosdrecht, M. C. M., Ekama, G. A. and Brdjanovic, D.), (International Water Association Publishing, London, 2008) 309–334; Chapter 12.Google Scholar
Takács, I., Patry, G. G. and Nolasco, D., “A dynamic model of the clarification–thickening process”, Water Res. 25(10) (1991) 1263–1271; doi:10.1016/0043-1354(91)90066-Y.Google Scholar
Torfs, E., Maere, T., Bürger, R., Diehl, S. and Nopens, I., “Impact on sludge inventory and control strategies using the benchmark simulation model no. 1 with the Bürger–Diehl settler model”, Water Sci. Technol. 71(10) (2015) 1524–1535; doi:10.2166/wst.2015.122.Google Scholar
Torfs, E., Martí, M. C., Locatelli, F., Balemans, S., Bürger, R., Diehl, S., Laurent, J., Vanrolleghem, P. A., François, P. and Nopens, I., “Concentration-driven models revisited: towards a unified framework to model settling tanks in water resource recovery facilities”, Water Sci. Technol. 75(3) (2017) 539–551; doi:10.2166/wst.2016.485.Google Scholar
Urase, T. and Kikuta, T., “Separate estimation of adsorption and degradation of pharmaceutical substances and estrogens in the activated sludge process”, Water Res. 39 (2005) 1289–1300; doi:10.1016/j.watres.2005.01.015.Google Scholar
Wang, J., Huang, C. P., Allen, H. E., Poesponegoro, I., Poesponegoro, H. and Takiyama, L. R., “Effects of dissolved organic matter and pH on heavy metal uptake by sludge particulates exemplified by copper (II) and nickel (II): three-variable model”, Water Environ. Res. 71(2) (1999) 139–147; www.jstor.org/stable/25045190.Google Scholar
Watts, R. W., Svoronos, S. A. and Koopman, B., “One-dimensional modeling of secondary clarifiers using a concentration and feed velocity-dependent dispersion coefficient”, Water Res. 30(9) (1996) 2112–2124; doi:10.1016/0043-1354(96)00024-3.Google Scholar
Xu, G., Yin, F., Xu, Y. and Yu, H.-Q., “A force-based mechanistic model for describing activated sludge settling process”, Water Res. 127 (2017) 118–126; doi:10.1016/j.watres.2017.10.013.Google Scholar
Yoon, S.-H. and Lee, S., “Critical operational parameters for zero sludge production in biological wastewater treatment processes combined with sludge disintegration”, Water Res. 39(15) (2005) 3738–3754; doi:10.1016/j.watres.2005.06.015.Google Scholar