## 3 Results and Discussion
### Technological Reliability of the Studied Systems  
The reliability of the analyzed WWTPs was determined using the Weibull method. In the first step, the distribution parameters were estimated, and the null hypothesis that empirical data can be described by a Weibull distribution was verified. The datasets were the values of the main pollutant indicators (BOD\({}_{5}\), COD, TSS, TN, and TP) in treated wastewater. The determined values of the distribution parameters (\(\theta\), \(b\), \(c\)) were consistent with the assumptions made. The null hypothesis was positively verified. The goodness of fit of the obtained distributions at the significance level of \(\alpha\) = 0.05 was high and was 68-98% for facility no. 1 and 51-99% for facility no. 2 (Table 4). The technological reliability of the studied WWTPs was determined on the basis of the distribution function (Figures 3-7), taking into account the limit values of the indicators, specified in the Regulation of the Minister of Maritime Economy and Inland Navigation [47] for WWTPs below 2000 PE. **Total suspended solids. ** The reliability of TSS removal in facility no. 1 was 86% (Figure 3A). On this basis, it can be concluded that, for a period of 51 days per year, the treatment plant malfunctioned. During this period, the concentration of TSS in treated wastewater exceeded the limit value (50 mg/dm\({}^{3}\)). According to [PERSON] and [PERSON] [58], for WWTPs below 2000 PE, the minimum reliability level should be 97.3%. This means that a treatment plant of this size can malfunction for 9 days per year without adversely affecting the rating of the facility. Taking these assumptions into account, it can be concluded that, in facility no. 1, the concentration of TSS in the outflow from the analyzed WWTPs \begin{table}
\begin{tabular}{c c c c c c} \hline \hline \multirow{2}{*}{**Parameter**} & \multicolumn{2}{c}{**Parameters of Weibull Distribution**} & \multicolumn{2}{c}{**Hollander–Proschan**} \\  & \(\theta\) & \(c\) & \(b\) & **Stat** & \(p\) \\ \hline \multicolumn{6}{c}{Facility no. 1—Obrocz} \\ \hline TSS & \(-0.2000\) & \(1.2122\) & \(28.9624\) & \(0.0217\) & \(0.9826\) \\ \hline BOD\({}_{5}\) & \(0.9636\) & \(0.7691\) & \(10.0911\) & \(0.4015\) & \(0.6880\) \\ \hline COD & \(14.6970\) & \(1.3850\) & \(80.1201\) & \(0.2532\) & \(0.8000\) \\ \hline TN & \(58.8890\) & \(8.6765\) & \(132.4568\) & \(0.1400\) & \(0.8886\) \\ \hline TP & \(9.4444\) & \(4.8527\) & \(12.5016\) & \(0.3000\) & \(0.7641\) \\ \hline \multicolumn{6}{c}{Facility no. 2—Rybakówka} \\ \hline TSS & \(2.2929\) & \(1.3035\) & \(21.5361\) & \(0.1127\) & \(0.9102\) \\ \hline BOD\({}_{5}\) & \(1.4000\) & \(1.0681\) & \(28.9343\) & \(-0.0998\) & \(0.9204\) \\ \hline COD & \(-2.0000\) & \(1.8159\) & \(102.2153\) & \(-0.1191\) & \(0.9051\) \\ \hline TN & \(-2.0000\) & \(3.1554\) & \(78.7167\) & \(-0.6526\) & \(0.5139\) \\ \hline TP & \(-0.5000\) & \(5.5212\) & \(12.6970\) & \(-0.0081\) & \(0.9934\) \\ \hline \hline \end{tabular} Symbols: stat—value of the test statistic, \(p\)—significance level of the test; when \(p\leq 0.05\), the distribution of data does not obey a Weibull distribution.  
\end{table} 
Table 4: Parameters of the Weibull distribution and the Hollander–Proschan goodness-of-fit test (\(n=20\)). Figure 4: Weibull cumulative distribution functions and the technological reliabilities determined for BOD\({}_{5}\) (**(A)**—facility no. 1; (**B**)—facility no. 2). Notation:dashed green line—reliability function, continuous green line—confidence intervals, red arrows—probability of achieving the indicators limit in the effluent. Figure 5: Weibull cumulative distribution functions and the technological reliabilities determined for COD (**(A)**—facility no. 1; (**B**)—facility no. 2). Notation:dashed green line—reliability function, continuous green line—confidence intervals, red arrows—probability of achieving the indicators limit in the effluent. Figure 3: Weibull cumulative distribution functions and the technological reliabilities determined for TSS ((**A**)—facility no.