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Effect of sewage sampling frequency on determination of design parameters for municipal wastewater treatment plants
Author(s) -
Tito Gehring,
Elija Deineko,
Inka Hobus,
G. Kolisch,
Manfred Lübken,
Marc Wichern
Publication year - 2020
Publication title -
water science and technology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.406
H-Index - 137
eISSN - 1996-9732
pISSN - 0273-1223
DOI - 10.2166/wst.2020.588
Subject(s) - percentile , sampling (signal processing) , sewage treatment , environmental science , chemical oxygen demand , inflow , wastewater , sewage , monte carlo method , sampling design , biochemical oxygen demand , statistics , environmental engineering , mathematics , engineering , meteorology , filter (signal processing) , population , physics , electrical engineering , demography , sociology
The uncertainty associated with the determination of load parameters, which is a key step in the design of wastewater treatment plants (WWTPs), was investigated on the basis of data sets from 58 WWTPs. A further analysed aspect was the organic load variations associated with variable sewage temperatures. Data from 26 WWTPs with a high inflow sampling frequency was used to simulate scenarios to investigate the effect of lower sampling frequencies through a Monte Carlo approach. The calculation of 85-percentile values for chemical oxygen demand (COD) loadings based on only 26 samples per year is associated with a variability of up to ±18%. Approximately 90 samples per year will be necessary to reduce this uncertainty for estimation of COD loadings below 10%. Hence, a low sampling frequency can potentially lead to under- or overestimation of design parameters. Through an analogous approach, it was possible to identify uncertainties of ±11% in COD loading when weekly average data was used with four samples per week. Finally, a tendency to lower COD input loads with increasing temperatures was identified, with a reduction of about 1% of the average loading per degree Celsius.

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