# Microplastic Pollution on the Beaches of the Black Sea in Romania and Bulgaria
## 4 Discussion
\begin{table}
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The interpretation of the table classifying beach zones in Romania and Bulgaria based on their sand microplastic contamination using the post hoc Tukey test revealed significant differences in the microplastic pollution levels. The Mamaia S beach (RO02S) stood out with an extremely high microplastic load (120.33), placing it clearly in a distinct category. In comparison, beaches such as Costinesti S (RO05S) (65.67) and Sunny Beach C (BG14C) (59.67) showed more moderate values, although there were still significantly higher than those of most other locations. Beaches with moderate contamination included locations such as Mamaia N (RO02N), Nessebar N (BG15N), Mamaia C (RO02C), and Bourgas C (BG18), where values ranged between 40 and 50 microplastic particles. These areas demonstrated a high level of pollution, though it was lower than that of some other beaches. On the other hand, beaches with low microplastic contamination included destinations such as 2 Mai (RO13), Saturn (RO11), Mangalia (RO12), and Albena (BG05), with values of below 30 particles. Regarding the cleanest sandy beaches, areas such as Altopol (BG24), Kiten (BG22), Sinemorets (BG25), and Pomorie (BG17) stood out, with very low microplastic levels. The overall analysis highlighted a clear trend: beaches on the northern Romanian coastline, such as Mamaia and Costinesti, were the most affected, while the southern coastline, both in Romania and Bulgaria, showed lower microplastic values. This distribution may have been influenced by factors such as the tourism intensity, expansion works, marine currents, and local pollution sources. The results of [PERSON]'s test for the one-way ANOVA are presented in Table 6. \begin{table}
\begin{tabular}{l c c c c} \hline \hline  & **DF** & **Sum of Squares** & **Mean Square** & **F Value** & **Prob > F** \\ \hline Model & 116 & 2935.23 & 25.30 & 3.35 & \textless{}0.0001 \\ Error & 234 & 1767.18 & 7.55 & \\ \hline \hline \end{tabular}
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Table 6: [PERSON]’s test table (absolute deviations). \begin{table}
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[PERSON]'s test examines whether the variance among groups is equal. Since the \(p\)-value was very low (<0.05), we rejected the assumption of equal variances. This suggests that the variability between groups was not homogeneous, which could impact the reliability of the ANOVA. [PERSON]'s test indicated a \(p\)-value of <0.0001, which means that the variances were significantly different between the groups. This result justified the use of the Tukey test for pairwise group comparisons. The PCA (Principal Component Analysis) method was used to highlight the potential grouping of the microfiber load values of beaches based on zones (north, center, south), which represented the three variables considered. The determination of the principal components was carried out using a correlation matrix. The obtained eigenvalues were 2.69, 0.89, 0.27, and 0.15 for PC1 through PC4, respectively. The first two principal components explained 89.31% of the total data variance, with PC1 accounting for 66.98% and PC2 for 22.33%. Figure 15 presents the PCA Biplot for all the analyzed beaches in Romania and Bulgaria. We can begin to interpret this Biplot by noting that the x-axis represents the first principal component, which consisted of a linear combination of the three variables and captured the highest proportion of the variability of the input data. Figure 15 presents the observations and principal components obtained from the analyzed data. In the 2D PCA Biplot (scores and loadings of PC1 vs. PC2), the formation of two distinct groups in the sample can be observed. Among the three zone variables, the southern zone showed the greatest variability, being positioned closest to the x-axis, followed by the northern zone and then the central zone. All variables had positive directions of variation, aligning with the positive direction of the x-axis, i.e., of PC1.