## 3 Results and Discussion
### PCA and PCR Results of the Data Set  
In order to prove the hypothesis, factor analysis was performed using the PCA method. Kaiser-Meyer-Olkin measure of sampling adequacy criterion (KMO) was 0.649, a significance level of [PERSON]'s test of sphericity Sig. < 0.0001. All measures of sampling adequacy (MSA) were >0.520. Extraction communalities were high and varied from 0.415 to 0.957. This indicates that the extracted components are a good representation of the variables (four extracted PCs explained 80.2% of the total data variance [52]). Principal component PC1 (39.5%) named as \"Spectral data\" was explained by UV/VIS spectral data excluding absorbance at the wavelength A 210 nm. Principal component PC2 (22.3%) named as \"Dissolved solids\" is explained by the N\({}_{\rm Kj}\), P\({}_{\rm tot}\), TDS, and color. Principal component PC3 (11.0%) named as \"Organic substances\" is explained by COD\({}_{\rm Cr}\), BOD\({}_{5}\), and DOC. PC4 (7.5%), named as \"Electrochemical properties\" is explained by the pH, EC, and A210 nm, which is the measure of nitrates and is related to the electrochemical properties. Scores plot of the principal component analysis (PCA) for principal component PC1 that describe and map the UV/Vis absorbance data in the new axes defined by the principal components, and loadings plot PC1 vs PC2 that describe and map the relationships between water quality parameters and the principal components extracted are shown in Figure 6.  
UV/Vis scores plot of spectral data revealed the highest correlation at 270-320 nm showing the highest DOC and SS contribution to PC1 while the lowest correlation was at 240 nm and decreased  
Figure 5: UV/VIS fingerprints of the washing water and wastewater monitored at the sampling spots 1, 2, 3, 4 and 5 (Figures 1–3), C—deionized water. Figure 6: PCA scores plot of the UV/Vis absorbance for PC1 (**a**) and PC1 vs. PV2 (**b**) loadings plot of the water quality parameters monitored. evenly from 320 nm to 660 nm. These findings confirm some speculations that DOC correlates better with UV/Vis spectra in comparison to organic matter (OM) while SS interferes with them due to scattering [5; 21; 30]. The right-side variables in Figure 6b are positively correlated one with another and with chemical analytes of the wastewater. Two clusters of the chemical properties and spectral data were established, while pH seems to be an outlier. Significant Pearson correlations (\(p<0.05\)) were observed between PC1 (spectral data), PC3 (organic matter) (r = 0.86) and PC4 (electrochemical properties) (r = \(-0.79\)) while the correlation of PC2 (dissolved solids) was wake and statistically insignificant. The Chi-Square test (Asymp. Sig. 0.102 \(>\) 0.05) confirmed that our model consisting of four PCs represents a sufficient description of the chemical data. One-Sample Kolmogorov-Smirnov Test (Asymp. Sig \(<\) 0.05) confirmed the hypothesis about compatibility between normal empirical and theoretical distributions of PCs. Monte Carlo significance \(p>0.05\) let to reject H0 hypothesis and conclude that the PCs' distributions are compatible with normal distribution. Data of the [PERSON]'s test \(<\) 4 showed that there are not outliers in the model. Mahalanobis test identified outlier sample only of deionized water, which was used as background for spectral analysis. Results of the principal components regression (PCR) analysis were unreliable likely due to correlation between dependent variables, so called multi-collinearity (VIF \(<\) 2) [38].