GIS-based approach and multivariate statistical analysis for identifying sources of heavy metals in marine sediments from the coast of Hong Kong

Abstract

AbstractMultiple methods consisting of geographic information system (GIS) technique, enrichment factor (EF), potential ecological risk index (PEI) and multivariate statistical methods was developed to identify anthropogenic heavy metal sources in marine sediments of Hong Kong. The distributions of heavy metals in sediments have been analyzed, and their pollution degrees, corresponding potential ecological risks and source identifications have been studied using geo-accumulation index, potential ecological risk index and integrated multivariate statistical methods, respectively. Three different types of anthropogenic inputs could be identified via multivariate analysis. Acoording to the findings, the first principal component might originate from the industrial discharges and shipping activities. The second principal component were identified from the natural sources. The third component mainly from the municipal discharges and industrial wastewater. These results provide baseline information for both the coastal environment management and the worldwide heavy metal distribution and assessment.