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Abstract

The aim of the study was to model the operation of a wastewater treatment plant using the Monte Carlo method and selected probability distributions of random variables. Pollutant indices in treated wastewater were analysed, such as: biological oxygen demand ( BOD 5), chemical oxygen demand ( COD Cr), total suspended solids ( TSS), total nitrogen (N tot), total phosphorus (P tot). The preliminary analysis of pollution indicators series included the: calculation of descriptive statistics and assessment of biological degradability of wastewater. The consistency of the theoretical distributions with the empirical ones was assessed using Anderson–Darling statistics. The best-fitting statistical distributions were selected using the percent bias criterion. Based on the calculations performed, it was found that the analysed indicators of pollution in treated wastewater were characterised by an average variability of composition for BOD 5, COD Cr and TSS, and a high variability of composition for N tot and P tot. The best fitted distribution was log-normal for BOD 5, TSS, N tot and P tot and general extreme values for COD Cr. The simulation carried out using the Monte-Carlo method confirmed that there may be problems associated with the reduction of nutrients (N tot and P tot) the analysed wastewater treatment plant. Results of values obtained of the risk values of negative control of wastewater treatment plant operation for biogenic compounds, different from 1, indicate that the number of exceedances at the outflow may be higher than the acceptable one.
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Authors and Affiliations

Karolina Migdał
1
ORCID: ORCID
Agnieszka Operacz
1
ORCID: ORCID
Iryna Vaskina
2
ORCID: ORCID
Paulina Śliz
3
ORCID: ORCID
Jorge Tavares
4 5
ORCID: ORCID
Adelaide Almeida
4 5 6
ORCID: ORCID
Michał Migdał
7

  1. University of Agriculture in Krakow, Faculty of Environmental Engineering and Land Surveying, Department of Sanitary Engineering and Water Management, al. Mickiewicza 24/28, 30-059 Kraków, Poland
  2. Sumy State University, Faculty of Technical System and Energy Efficient Technologies, Department of Applied Ecology, Sumy, Ukraine
  3. Cracow University of Economics, Institute of Spatial Management and Urban Studies, Department of Spatial Management, Kraków, Poland
  4. Polytechnic Institute of Beja, Department of Technology and Applied Sciences, Beja, Portugal
  5. University of Beira Interior, Faculty of Engineering, Research Unit Fiber Materials and Environmental Technologies (FibEnTech-UBI), Covilhã, Portugal
  6. University Nova of Lisbon, Faculty of Science and Technology, Center for Environmental and Sustainability Research (CENSE), Lisbon, Portugal
  7. Stalprodukt S.A., Bochnia, Poland

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