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This paper presents the results of principal factor analysis technique (PFA) developed for a 3-year study (2010–2012) on two urban wastewater treatment plants (WWTPs) situated in Murcia, Southeast of Spain. One of them receives wastewater for a medium-sized city (WWTP1), with an important industrial area, and the other one treats only domestic wastewater from a small-sized town (WWTP2), with slightly different treatment systems between them. Process performance and operation of WWTP are carried out to ensure their compliance with legislative requirements imposed by European Union. Because high amounts of variables are daily measured, a coherent and structured approach of such a system is required to understand its inherent behavior and performance efficiency. In this sense, PFA as a chemometric technique allowed us to investigate and propose a data reduction that allowed to group water-quality variables into selected factors with common features to describe the behavior of both plants, and their similarities and differences. Four main factors were extracted for WWTP1, associated with the presence of nutrients, the ionic component, the organic load to the plant, and the efficiency of the whole process, with an explaining variance of 62.12%. For WWTP2, also four main components were extracted, explaining 63.82% of the variance. These factors were pollution load to the plant, pollution output, marine intrusion, and, finally, the ionic component of water. The geochemical background composition of water in this zone and the important use of fertilizers in agriculture appeared to be two significant factors driving the results.
chemometrics, principal factor analysis, wastewater treatment
[1] Tchobanoglous, V.G., Burton, F.L. & David, H. (eds), Wastewater Engineering: Treatment and Reuse, 4th edn., McGraw-Hill: New York, 2003.
[2] Council Directive 91/271/EEC of 21 May 1991 concerning urban waste water treatment (amended by Directive 98/15/EC). Official Journal of European Union L135/40 (30 of May 1991).
[3] Zuthi, M.F.R., Guo, W.S., Ngo, H.H., Nghiem, L.D. & Hai, F.I., Review: Enhanced biological phosphorus removal and its modeling for the activated sludge and membrane bioreactor processes. Bioresource Technology, 139, 363–374, 2013. http://dx.doi.org/10.1016/j.biortech.2013.04.038
[4] Noori, R., Karbassi, A. & Sabahi, M.S., Evaluation of PCA and gamma test techniques on ANN operation for weekly solid waste prediction. Journal of Environmental Management, 91, 767–771, 2010. http://dx.doi.org/10.1016/j.jenvman.2009.10.007
[5] Singh, K.P., Malik, A., Mohan, D., Sinha, S. & Singh, V.K., Chemometric data analysis of pollutants in wastewater: a case study. Analitycal Chimica Acta, 532, 15–25, 2005. http://dx.doi.org/10.1016/j.aca.2004.10.043
[6] Hussain, M., Ahmed, S.M. & Abderrahman, W., Cluster analysis and quality assessment of logged water at an irrigation project, eastern Saudi Arabia. Journal of Environmental Management, 86, 297–307, 2008. http://dx.doi.org/10.1016/j.jenvman.2006.12.007
[7] Zhang, Z., Tao, F., Du, J., Shi, P., Yu, D., Meng, Y. & Sun, Y., Surface water quality and its control in a river with intensive human impacts–a case study of the Xiangjiang River, China. Journal of Environmental Management, 91, 2483–2490, 2010. http://dx.doi.org/10.1016/j.jenvman.2010.07.002
[8] Vialle, C., Sablayrolles, C., Lovera, M., Jacob, S., Huau, M.C. & Montrejaud-Vignoles, M., Monitoring of water quality from roof runoff: Interpretation using multivariate analysis. Water Research, 45, 3765–3775, 2011. http://dx.doi.org/10.1016/j.watres.2011.04.029
[9] Olsen, R.L., Chappell, R.W. & Loftis, J.C., Water quality sample collection, data treatment and results presentation for principal components analysis–literature review and Illinois River watershed case study. Water Research, 46, 3110–3122, 2012. http://dx.doi.org/10.1016/j.watres.2012.03.028
[10] Saba, T. & Su, S., Tracking polychlorinated biphenyls (PCBs) congener patterns in Newbark Bay surface sediments using principal component analysis (PCA) and positive matrix factorization (PMF). Journal of Hazardous Materials, 260, 634–643, 2013. http://dx.doi.org/10.1016/j.jhazmat.2013.05.046
[11] Zhang, W., Zhang, Y., Taniyasu, S., Yeung, L.W.Y., Lam, P.K.S., Wang, J., Li, X., Yamashita, N. & Dai, J., Distribution and fate of perfluoroalkyl substances in municipal wastewater treatment plants in economically developed areas of China. Environmental Pollution, 176, 10–17, 2013. http://dx.doi.org/10.1016/j.envpol.2012.12.019
[12] Bingöl, D., Ay, Ü., Bozbas, S.K. & Uzgören, N., Chemometric evaluation of the heavy metals distribution in waters from the Dilovasi region in Kocaeli, Turkey. Marine Pollution Bulletin, 68, 134-139, 2013. http://dx.doi.org/10.1016/j.marpolbul.2012.12.006
[13] Naughton, O. & Hynds, P.D., Public awareness, behaviours and attitudes towards domestic wastewater treatment systems in the Republic of Ireland. Journal of Hydrology, 518, 108–119, 2014. http://dx.doi.org/10.1016/j.jhydrol.2013.08.049
[14] Astel, A., Michalski, R., Lyko, A., Jablonska-Czapla, M., Bigus, K., Szopa, S. & Kwiecinska, A., Characterization of bottled mineral waters marketed in Poland using hierarchical cluster analysis. Journal of Geochemical Exploration, 143, 136–145, 2014. http://dx.doi.org/10.1016/j.gexplo.2014.04.002
[15] Aguado, D. & Rosen, C., Multivariate statistical monitoring of continuous wastewater treatment plants. Engineering Applications of Artificial Intelligence, 21, 1080–1091, 2008. http://dx.doi.org/10.1016/j.engappai.2007.08.004
[16] Ouali, A., Azri, C., Medhioub, K. & Ghrabi, A., Descriptive and multivariate analysis of the physico-chemical and biological parameters of Sfax wastewater treatment plant. Desalination, 246, 496–505, 2009. http://dx.doi.org/10.1016/j.desal.2008.04.058
[17] Platikanov, S., Rodriguez-Mozaz, S., Huerta, B., Barceló, D., Cros, J., Batle, M., Poch, G. & Tauler, R., Chemometrics quality assessment of wastewater treatment plant effluents using physicochemical parameters and UV absorption measurements. Journal of Environmental Management, 140, 33–44, 2014. http://dx.doi.org/10.1016/j.jenvman.2014.03.006
[18] Johnson, R.A. & Wichern, D.W., Applied Multivariate Statistical Analysis, 6th edn., Pearson: Mexico, 2008.
[19] Rice, E.W., Baird, R.D., Eaton, A.D. & Clesceri, L.S. (eds.), APHA, Standard Methods for the Examination of Water and Wastewater, 22nd edn., American Public Health Association, American Water Works Association & Water Environment Federation: Washington D.C., 2012.
[20] Gazzaz, N.M., Yusoff, M.K., Ramli, M.F., Aris, A.Z. & Juahir, H., Characterization of spatial patterns in river water quality using chemometric pattern recognition techniques. Marine Pollution Bulletin, 64, 688–698, 2012. http://dx.doi.org/10.1016/j.marpolbul.2012.01.032
[21] Reimann, C., Filzmoser, P. & Garrett, R.G., Factor analysis applied to regional geochemical data: problems and possibilities. Applied Geochemistry, 17, 185–206, 2002. http://dx.doi.org/10.1016/S0883-2927(01)00066-X
[22] Kaiser, H.F., An index of factorial simplicity. Psychometrika, 39, 31–36, 1974. http://dx.doi.org/10.1007/BF02291575
[23] Kaiser, H.F., The application of electronic computers to factor analysis. Education and Psychological Measurement, 20, 141–151, 1960. http://dx.doi.org/10.1177/001316446002000116
[24] Acosta, J.A., Faz, A., Jansen, B., Kalbitz, K. & Martínez-Martínez, S., Assessment of salinity status in intensively cultivated soils under semiarid climate, Murcia, SE Spain. Journal of Arid Environments, 75, 1056–1066, 2011. http://dx.doi.org/10.1016/j.jaridenv.2011.05.006
[25] Bayo, J., López-Castellanos, J., Martínez-García, R., Alcolea, A. & Lardín, C., Hydrocyclone as a cleaning device for anaerobic sludge digesters in a wastewater treatment plant. Journal of Cleaner Production, 87, 550–557, 2015. http://dx.doi.org/10.1016/j.jclepro.2014.10.064
[26] Osborne, J.W. & Costello, A.B., Best practices in exploratory factor analysis: Four recommendations for getting the most from your analysis. Pan-Pacific Management Review, 12(2), 131–146, 2009.