Evaluation of spatial and temporal variations in marine sediments quality using multivariate statistical techniques

• Published in: Environmental monitoring and assessment Vol. 186; no. 10; pp. 6867 - 6878
• Main Authors: Alvarez, Odalys Quevedo, Tagle, Margarita Edelia Villanueva, Pascual, Jorge L. Gómez, Marín, Ma. Teresa Larrea, Clemente, Ana Catalina Nuñez, Medina, Miriam Odette Cora, Palau, Raiza Rey, Alfonso, Mario Simeón Pomares
• Format: Journal Article
• Language: English
• Published: Cham Springer-Verlag 01.10.2014; Springer International Publishing; Springer Nature B.V
• Subjects: aluminum; arsenic; Atmospheric Protection/Air Quality Control/Air Pollution; Bays - chemistry; Cluster analysis; Coasts; cobalt; Copper; Cuba; data collection; Discriminant analysis; Earth and Environmental Science; Ecology; Ecosystem; ecosystems; Ecotoxicology; Electric power plants; Environment; Environmental Management; Environmental monitoring; Environmental Monitoring - methods; Environmental quality; Geologic Sediments - analysis; Geologic Sediments - chemistry; Heavy metals; Hydrocarbons; iron; lead; manganese; Marine sediments; Metals; Metals, Heavy - analysis; Monitoring/Environmental Analysis; Multivariate Analysis; nickel; Pollutants; Principal components analysis; Reference materials; Sediments; Spatio-Temporal Analysis; Statistical methods; temporal variation; Trace elements; Water Pollutants, Chemical - analysis; zinc; Cuba; ASW, Caribbean Sea, Greater Antilles, Cuba, Matanzas; ASW, Caribbean Sea, Greater Antilles, Cuba; Hydrocarbons; Cuba; Multivariate statistical techniques; Sediments; Metals
• ISSN: 0167-6369; 1573-2959
• DOI: 10.1007/s10661-014-3895-2

Spatial and temporal variations of sediment quality in Matanzas Bay (Cuba) were studied by determining a total of 12 variables (Zn, Cu, Pb, As, Ni, Co, Al, Fe, Mn, V, CO₃ ²⁻, and total hydrocarbons (THC). Surface sediments were collected, annually, at eight stations during 2005–2008. Multivariate statistical techniques, such as principal component (PCA), cluster (CA), and lineal discriminant (LDA) analyses were applied for identification of the most significant variables influencing the environmental quality of sediments. Heavy metals (Zn, Cu, Pb, V, and As) and THC were the most significant species contributing to sediment quality variations during the sampling period. Concentrations of V and As were determined in sediments of this ecosystem for the first time. The variation of sediment environmental quality with the sampling period and the differentiation of samples in three groups along the bay were obtained. The usefulness of the multivariate statistical techniques employed for the environmental interpretation of a limited dataset was confirmed.