Skip to main content
SpringerLink
Log in

Nitrogen and Phosphorus Removal Associated with Changes in Organic Loads from Biological Reactors Monitored by Multivariate Criteria

  • Published:
Water, Air, & Soil Pollution Aims and scope Submit manuscript

Abstract

The study aimed to evaluate the techniques of main principal components analysis (PCA) and hierarchical cluster analysis (HCA) as a criterion to monitor the removal of nitrogen forms and phosphorus in sequential upflow anaerobic sludge blanket (UASB), submerged aerated biological filters (SABF), and horizontal subsurface flow constructed wetland (HSSF-CW) treating different organic loads of swine wastewater. System was conducted in four organic loads of swine effluent. The UASB reactor did not provide satisfactory removal of nitrogen and phosphorus. In SABF, dissolved oxygen increased by more than 50 mg L−1 in nitric forms between phases I and IV. The HSSF-CW removed 87.5 and 63.1% and 70 and 42 kg ha−1d−1 of nitrogen and phosphorus, respectively. The PCA showed the effect of salinity and nitrogen/organic load measured and nitrogen and phosphorus removal with high positive correlation (r > 0.80). Two components extracted from the 7 variables were responsible for 81.8, 66.7, and 61.6% of the original influent and effluent data from the UASB, SABF, and HSSF-CW reactors, associated by nutrient removals. There was a reduction in HCA similarity with application of the sequential biological treatment, with the formation of four clusters and the central highlight of the nitrite and nitrate in the SABF reactor. The multivariate techniques presented in this document reduce the number of analyses, maintaining the representativeness of the monitoring data for wastewater treatment.

Graphical abstract

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6

Similar content being viewed by others

References

  • Abou-Elela, S. I., Hellal, M. S., Aly, O. H., & Abo-Elenin, S. A. (2019). Decentralized wastewater treatment using passively aerated biological filter. Environmental Technology, 40(2), 250–260. https://doi.org/10.1080/09593330.2017.1385648.

    Article  CAS  Google Scholar 

  • Addinsoft (2016). Data analysis and statistical solution for Microsoft Excel, Paris.

  • Almeida, A., Carvalho, F., Imaginário, M. J., Castanheira, I., Prazeres, A. R., & Ribeiro, C. (2017). Nitrate removal in vertical flow constructed wetland planted with Vetiveria zizanioides: effect of hydraulic load. Ecological Engineering, 99, 535–542. https://doi.org/10.1016/j.ecoleng.2016.11.069.

    Article  Google Scholar 

  • Babu, S., Gajanan, S. N., & Sanyal, P. (2014). Food security, poverty and nutrition policy analysis: statistical methods and applications: Academic Press.

  • Bayo, J., & López-Castellanos, J. (2016). Principal factor and hierarchical cluster analyses for the performance assessment of an urban wastewater treatment plant in the southeast of Spain. Chemosphere, 155, 152–162. https://doi.org/10.1016/j.chemosphere.2016.04.038.

    Article  CAS  Google Scholar 

  • Cheng, D. L., Ngo, H. H., Guo, W. S., Chang, S. W., Nguyen, D. D., Kumar, S. M., et al. (2018). Problematic effects of antibiotics on anaerobic treatment of swine wastewater. Bioresource Technology, 263, 642–653. https://doi.org/10.1016/j.biortech.2018.05.010.

    Article  CAS  Google Scholar 

  • Cheng, D. L., Ngo, H. H., Guo, W. S., Chang, S. W., Nguyen, D. D., & Kumar, S. M. (2019). Microalgae biomass from swine wastewater and its conversion to bioenergy. Bioresource Technology, 275, 109–122. https://doi.org/10.1016/j.biortech.2018.12.019.

    Article  CAS  Google Scholar 

  • Chernicharo, C. A. L. (2007). Princípios do tratamento biológico de águas residuárias: Reatores anaeróbios. 5, 379.

  • Core Team, R (2015). R: A Language and Environment for Statistical Computing; 2015.

  • Cristóvão, R. O., Pinto, V. M. S., Gonçalves, A., Martins, R. J. E., Loureiro, J. M., & Boaventura, R. A. R. (2016). Fish canning industry wastewater variability assessment using multivariate statistical methods. Process Safety and Environmental Protection, 102, 263–276. https://doi.org/10.1016/j.psep.2016.03.016.

    Article  CAS  Google Scholar 

  • Dacewicz, E., & Chmielowski, K. (2019). Application of multidimensional clustering for an assessment of pollutants removal from domestic wastewater using a filter with a plastic waste filling. Journal of Water Process Engineering, 29, 100794. https://doi.org/10.1016/j.jwpe.2019.100794.

    Article  Google Scholar 

  • Enitan, A. M., Kumari, S., Odiyo, J. O., Bux, F., & Swalaha, F. M. (2018). Principal component analysis and characterization of methane community in a full-scale bioenergy producing UASB reactor treating brewery wastewater. Physics and Chemistry of the Earth, Parts A/B/C, 108, 1–8. https://doi.org/10.1016/j.pce.2018.06.006.

    Article  Google Scholar 

  • Fávero, L. P., Belfiore, P., da Silva, F. & Chan, B. L. (2009). Análise de dados: modelagem multivariada para tomada de decisões.

  • Ferreira, D. F. (2011). Sisvar: a computer statistical analysis system. Ciência e Agrotecnologia, 35(6), 1039–1042.

    Article  Google Scholar 

  • Fia, F. R. L., Matos, A. T., Fia, R., Borges, A. C., & Cecon, P. R. (2017). Efeito da vegetação em sistemas alagados construídos para tratar águas residuárias da suinocultura. 22(2), 303-311.

  • Gamble, A., Babbar-Sebens, M. J. E. M., & Assessment. (2012). On the use of multivariate statistical methods for combining in-stream monitoring data and spatial analysis to characterize water quality conditions in the White River Basin, Indiana, USA. Environmental Monitoring and Assessment, 184(2), 845–875.

    Article  Google Scholar 

  • Gebski, M., & Wong, R. K. (2007) An efficient histogram method for outlier detection. In International Conference on Database Systems for Advanced Applications, (pp. 176–187): Springer.

  • Goddek, S., Delaide, B. P. L., Joyce, A., Wuertz, S., Jijakli, M. H., Gross, A., et al. (2018). Nutrient mineralization and organic matter reduction performance of RAS-based sludge in sequential UASB-EGSB reactors. Aquacultural Engineering, 83, 10–19. https://doi.org/10.1016/j.aquaeng.2018.07.003.

    Article  Google Scholar 

  • He, Y., Wang, Y., & Song, X. (2016). High-effective denitrification of low C/N wastewater by combined constructed wetland and biofilm-electrode reactor (CW–BER). Bioresource Technology, 203, 245–251. https://doi.org/10.1016/j.biortech.2015.12.060.

    Article  CAS  Google Scholar 

  • Hopkins, W. G. (2016). A new view of statistics. Middlesbrough: Internet Society for Sport Science. http://www.sportsci.org/resource/stats. Accessed 26 Aug 2019.

  • Hu, C., Yan, B., & Wang, K.-j., & Xiao, X.-m. (2018). Modeling the performance of anaerobic digestion reactor by the anaerobic digestion system model (ADSM). Journal of Environmental Chemical Engineering, 6(2), 2095–2104. https://doi.org/10.1016/j.jece.2018.03.018.

    Article  CAS  Google Scholar 

  • Huang, L., Wang, N., Deng, C., Liang, Y., Wang, Q., Liu, M., et al. (2019). Interactive effect of carbon source with influent COD/N on nitrogen removal and microbial community structure in subsurface flow constructed wetlands. Journal of Environmental Management, 250, 109491. https://doi.org/10.1016/j.jenvman.2019.109491.

    Article  CAS  Google Scholar 

  • Hutcheson, G. D., & Sofroniou, N. (1999). The multivariate social scientist: introductory statistics using generalized linear models: Sage.

  • Jizheng, P., Houhu, Z., Xuejun, L., Yong, L., Min, Z., & Hongling, X. (2019). Enhanced nitrogen removal by the integrated constructed wetlands with artificial aeration. Environmental Technology and Innovation, 14, 100362. https://doi.org/10.1016/j.eti.2019.100362.

    Article  Google Scholar 

  • Kaiser, H. F. (1974). An index of factorial simplicity. Psychometrika, 39(1), 31–36. https://doi.org/10.1007/BF02291575.

    Article  Google Scholar 

  • Kasak, K., Kill, K., Pärn, J., & Mander, Ü. (2018). Efficiency of a newly established in-stream constructed wetland treating diffuse agricultural pollution. Ecological Engineering, 119, 1–7. https://doi.org/10.1016/j.ecoleng.2018.05.015.

    Article  Google Scholar 

  • Kaufman, L., & Rousseeuw, P. (1990). Finding groups in data; an introduction to cluster analysis. J. Wiley.

  • Lan, W., Zhang, J., Hu, Z., Ji, M., Zhang, X., Zhang, J., et al. (2018). Phosphorus removal enhancement of magnesium modified constructed wetland microcosm and its mechanism study. Chemical Engineering Journal, 335, 209–214. https://doi.org/10.1016/j.cej.2017.10.150.

    Article  CAS  Google Scholar 

  • Leiva, A. M., Núñez, R., Gómez, G., López, D., & Vidal, G. (2018). Performance of ornamental plants in monoculture and polyculture horizontal subsurface flow constructed wetlands for treating wastewater. Ecological Engineering, 120, 116–125. https://doi.org/10.1016/j.ecoleng.2018.05.023.

    Article  Google Scholar 

  • Lettinga, G., van Velsen, A. F. M., Hobma, S. W., de Zeeuw, W., & Klapwijk, A. (1980). Use of the upflow sludge blanket (USB) reactor concept for biological wastewater treatment, especially for anaerobic treatment. Biotechnology and Bioengineering, 22(4), 699–734. https://doi.org/10.1002/bit.260220402.

    Article  CAS  Google Scholar 

  • Lim, S. J., & Kim, T.-H. (2014). Applicability and trends of anaerobic granular sludge treatment processes. Biomass and Bioenergy, 60, 189–202. https://doi.org/10.1016/j.biombioe.2013.11.011.

    Article  CAS  Google Scholar 

  • Lin, J., Zhang, P., Li, G., Yin, J., Li, J., & Zhao, X. (2016). Effect of COD/N ratio on nitrogen removal in a membrane-aerated biofilm reactor. International Biodeterioration & Biodegradation, 113, 74–79. https://doi.org/10.1016/j.ibiod.2016.01.009.

    Article  CAS  Google Scholar 

  • Lutterbeck, C. A., Zerwes, F. V., Radtke, J. F., Köhler, A., Kist, L. T., & Machado, Ê. L. (2018). Integrated system with constructed wetlands for the treatment of domestic wastewaters generated at a rural property – evaluation of general parameters ecotoxicity and cytogenetics. Ecological Engineering, 115, 1–8. https://doi.org/10.1016/j.ecoleng.2018.01.004.

    Article  Google Scholar 

  • Matos, M. P., von Sperling, M., Matos, A. T., Dias, D. F. C., & Santos, C. R. S. (2018). Colmatação e desempenho de sistemas alagados construídos de escoamento horizontal subsuperficial ao longo de oito anos de operação. Engenharia Sanitaria e Ambiental, 23(6), 1227–1237.

    Article  Google Scholar 

  • Metcalf, E. I. (2003). Wastewater engineering: treatment, disposal, and reuse. 4th Edition. McGraw-Hill, New York.

  • Oliveira, J. F., Fia, R., Fia, F. R. L., Rodrigues, F. N., Matos, M. P., & Siniscalchi, L. A. B. (2020). Principal component analysis as a criterion for monitoring variable organic load of swine wastewater in integrated biological reactors UASB, SABF and HSSF-CW. Journal of Environmental Management, 262, 110386. https://doi.org/10.1016/j.jenvman.2020.110386.

    Article  CAS  Google Scholar 

  • Parakh, S. K., Praveen, P., Loh, K.-C., & Tong, Y. W. (2019). Wastewater treatment and microbial community dynamics in a sequencing batch reactor operating under photosynthetic aeration. Chemosphere, 215, 893–903. https://doi.org/10.1016/j.chemosphere.2018.10.085.

    Article  CAS  Google Scholar 

  • Pelaz, L., Gómez, A., Letona, A., Garralón, G., & Fdz-Polanco, M. (2018). Nitrogen removal in domestic wastewater. Effect of nitrate recycling and COD/N ratio. Chemosphere, 212, 8–14. https://doi.org/10.1016/j.chemosphere.2018.08.052.

    Article  CAS  Google Scholar 

  • Peterson, B. G., Carl, P., Boudt, K., Bennett, R., Ulrich, J., Zivot, E., et al. (2018). Package ‘PerformanceAnalytics’.

  • Platikanov, S., Rodriguez-Mozaz, S., Huerta, B., Barceló, D., Cros, J., Batle, M., et al. (2014). Chemometrics quality assessment of wastewater treatment plant effluents using physicochemical parameters and UV absorption measurements. Journal of Environmental Management, 140, 33–44. https://doi.org/10.1016/j.jenvman.2014.03.006.

    Article  CAS  Google Scholar 

  • Porwal, H. J., Mane, A. V., & Velhal, S. G. (2015). Biodegradation of dairy effluent by using microbial isolates obtained from activated sludge. Water Resources and Industry, 9, 1–15. https://doi.org/10.1016/j.wri.2014.11.002.

    Article  Google Scholar 

  • Rastogi, G. K., & Sinha, D. K. (2011). A novel approach to water quality management through correlation study. Journal of Environmental Research and Development, 5(4), 1029–1035.

    CAS  Google Scholar 

  • Reportlinker (2017). Global pork meat market 2017–2021. https://www.prnewswire.com/news-releases/global-pork-meat-market-2017-2021-300537453.html. Accessed 10 March 2019.

  • Rice, E., Baird, R., Eaton, A., Odor, T., By, D., & Carbon, T. O. (2017). Standard methods for the examination of water and wastewater.

  • Sá Junior, A., Carvalho, L. G., Silva, F. F., & Alves, M. C. (2012). Application of the Köppen classification for climatic zoning in the state of Minas Gerais, Brazil. Theoretical and Applied Climatology, 108, 1–7. https://doi.org/10.1007/s00704-011-0507-8.

    Article  Google Scholar 

  • Saha, N., & Rahman, M. S. (2018). Multivariate statistical analysis of metal contamination in surface water around Dhaka export processing industrial zone, Bangladesh. Environmental Nanotechnology, Monitoring & Management, 10, 206–211. https://doi.org/10.1016/j.enmm.2018.07.007.

    Article  Google Scholar 

  • Soares, J. O., Marquês, M. M. L., & Monteiro, C. M. F. (2003). A multivariate methodology to uncover regional disparities: a contribution to improve European Union and governmental decisions. European Journal of Operational Research, 145(1), 121–135. https://doi.org/10.1016/S0377-2217(02)00146-7.

    Article  Google Scholar 

  • Tobias, S., & Carlson, J. E. (1969). Brief report: Bartlett’s test of sphericity and chance findings in factor analysis. Multivariate Behavioral Research, 4(3), 375–377. https://doi.org/10.1207/s15327906mbr0403_8.

    Article  CAS  Google Scholar 

  • Tripathi, M., & Singal, S. K. (2019). Use of principal component analysis for parameter selection for development of a novel water quality index: a case study of river Ganga India. Ecological Indicators, 96, 430–436. https://doi.org/10.1016/j.ecolind.2018.09.025.

    Article  CAS  Google Scholar 

  • Verma, R., & Suthar, S. (2018). Performance assessment of horizontal and vertical surface flow constructed wetland system in wastewater treatment using multivariate principal component analysis. Ecological Engineering, 116, 121–126. https://doi.org/10.1016/j.ecoleng.2018.02.022.

    Article  Google Scholar 

  • Vymazal, J. (2010). Constructed wetlands for wastewater treatment. Water, 2(3), 530–549.

    Article  CAS  Google Scholar 

  • Vymazal, J. (2017). The use of constructed wetlands for nitrogen removal from agricultural drainage: A review. Scientia Agriculturae Bohemica, 48(2), 82–91.

    Article  Google Scholar 

  • Vymazal, J., & Kröpfelová, L. (2008). Wastewater treatment in constructed wetlands with horizontal sub-surface flow (Vol. 14): Springer science & business media.

  • Yang, J., Kim, J., Skogley, E., & Schaff, B. E. (1998). A simple spectrophotometric determination of nitrate in water, resin, and soil extracts. Soil Science Society of America, 62(4), 1108–1115.

    Article  CAS  Google Scholar 

  • Yang, H., Deng, L., Wang, L., Zheng, D., Liu, Y., Wang, S., et al. (2019). Comparison of three biomass-retaining reactors of the ASBR, the UBF and the USR treating swine wastewater for biogas production. Renewable Energy, 138, 521–530. https://doi.org/10.1016/j.renene.2019.01.124.

    Article  CAS  Google Scholar 

  • Yue, X., Yu, G., Lu, Y., Liu, Z., Li, Q., Tang, J., et al. (2018). Effect of dissolved oxygen on nitrogen removal and the microbial community of the completely autotrophic nitrogen removal over nitrite process in a submerged aerated biological filter. Bioresource Technology, 254, 67–74. https://doi.org/10.1016/j.biortech.2018.01.044.

    Article  CAS  Google Scholar 

  • Zhang, S., Zhu, C., Xia, S., & Li, M. (2019). Impact of different running conditions on performance of biofilters treating secondary effluent during start-up. Bioresource Technology, 281, 168–178. https://doi.org/10.1016/j.biortech.2019.02.094.

    Article  CAS  Google Scholar 

Download references

Acknowledgments

The research work was developed with the help of financial resources from the Coordination for the Improvement of Higher Education Personnel (CAPES) and the Minas Gerais State Research Support Foundation (FAPEMIG).

Author information

Authors and Affiliations

  1. Department of Water Resources and Sanitation, Environmental and Sanitary Engineering Centre, Federal University of Lavras, UFLA, Minas Gerais, 37200-000, Brazil

    Jacineumo Falcão de Oliveira, Ronaldo Fia, Bianca Selvati Brandino Nunes, Luciene Alves Batista Siniscalchi, Mateus Pimentel de Matos & Fátima Resende Luiz Fia

Authors
  1. Jacineumo Falcão de Oliveira
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Ronaldo Fia
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Bianca Selvati Brandino Nunes
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Luciene Alves Batista Siniscalchi
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Mateus Pimentel de Matos
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Fátima Resende Luiz Fia
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Jacineumo Falcão de Oliveira.

Additional information

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Highlights

• Evaluation of nitrogen and phosphorus removal in biological reactors by PCA and HCA.

• The system extracted 2 principal components with 81.87% of original data variability.

• There was strong clustering of the nitric variables in the swine wastewater.

• The COD/TKN ratio showed an antagonistic effect of PCA and HCA in the effluent.

• Use of HSSF-CW reactor as post-treatment associated with multivariate criteria.

Electronic Supplementary Material

ESM 1

(DOCX 30 kb)

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

de Oliveira, J.F., Fia, R., Nunes, B.S.B. et al. Nitrogen and Phosphorus Removal Associated with Changes in Organic Loads from Biological Reactors Monitored by Multivariate Criteria. Water Air Soil Pollut 231, 511 (2020). https://doi.org/10.1007/s11270-020-04858-7

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1007/s11270-020-04858-7

Keywords

Search

Navigation