Multivariate statistical analysis of coastal sediment data

Multivariate statistical analysis of sediment data (information matrix 123 x 16) from the Gulf of Mexico, USA shows that the data structure is defined by four latent factors conditionally called "inorganic natural", "inorganic anthropogenic", "bioorganic" and "organic anthropogenic" explaining 39.24%, 23.17%, 10.77% and 10.67% of the total variance of the data system, respectively. The receptor model obtained by the application of the PCR approach makes it possible to apportion the contribution of each chemical component for the latent factor formation. A separation of the contribution of each chemical parameter is achieved within the frames of "natural" and "anthropogenic" origin of the respective heavy metal or organic matter to the sediment formation process. This is a new approach as compared to the traditional "one dimensional" search with a limited number of preliminary selected tracer components. The model suggested divides natural from anthropogenic influences and allows in this way each participant in the sediment formation process to be used as marker of either natural or anthropogenic effects.