Assessment of temporal and spatial variation of coastal water quality and source identification along Macau peninsula

Abstract

Cluster analysis (CA), discriminant analysis (DA) and principal component analysis (PCA) were comprehensively coupled to explore and identify the spatial and temporal variation and potential pollution sources in coastal water quality along Macau peninsula. The results show that the 12 months could be grouped into two periods, June-September and the remaining months, and the entire area divided into two clusters, one located at the western sides, and the other on the southeast and southern sides of the Macau peninsula. Through backward stepwise DA, pH, Cl -, TSS, Color and TP, Chloride, Color, NH 4 ? , DO, COD were discriminant variables of spatial and temporal variation, with 84.82 and 76.54% correct assignments, respectively. Fecal pollution, organic pollution and soil weathering are among the major sources for coastal water quality deterioration along Macau peninsula. This study illustrates that application of multivariate statistical techniques was beneficial to gain knowledge for further optimizing the monitoring network and controlling coastal water quality along Macau peninsula.

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Impact of anthropogenic activities on urban stream water quality: a case study in Guangzhou, China

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