Effect of sewage sampling frequency on determination of design parameters for municipal wastewater treatment plants

Abstract

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. HIGHLIGHTS Uncertainty of statistical measures for COD loads relating to sampling frequency.; Determination of yearly 85-percentile values from COD loads with one weekly sample results in an up to ±13% uncertainty.; Calculation of weekly averages of COD loads with four samples per week is associated with an uncertainty of up to ±11%.; Relative influent COD loading decreases with higher temperatures.;

Keywords

• chemical oxygen demand
• inflow load variation
• monte carlo simulation
• sampling frequency
• wastewater treatment plant design
• uncertainty analysis