Principal component analysis of containership traffic in the Black Sea

A novel quantitative analysis employing the Principal Component Analysis (PCA) of containership traffic in Black Sea from 2018 to 2021 is performed. The study uses a matrix covering five ship size classes E for four years operation, 2021, accounting traffic, CO2, fuel consumption (FC), shipping intensity, and eco efficiency. Only first two principal factors are analysed because their total variation weight. Shipping FC CO2 intensity plays significant role factor, while Eco efficiency, Traffic efficiency considered second factor. Notably, set parameters pertains time strongly associated with DWT. Two components were identified, F1 F2, where integrates intensity. At same time, F2 separates conditional on year operations. In component activities ships C differ B, D E, separating more efficiently less used ships, class sizes contrast B distinguishing big-size small ones. It was concluded that most intensively D, efficient B. intensive use 2020, followed by 2018, 2019. Based using Within-class variance, grouped into clusters similar activities, one, lower variance homogeneous, includes only A. one relatively large consists rest ships. Linear relationships considering derived as function main variables, factor loading represents variable’s coefficient, given relative weight any