2010
DOI: 10.1590/s1679-87592010000400008
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Chemometry use in the evaluation of the sanya bay water quality

Abstract: In this study, chemometric method is employed to identify anthropogenic effects on the water quality in Sanya Bay, South China Sea, and its marine and natural characteristics. Principal component analysis has extracted the four latent factors, thus explaining 85.52% of the total variance. Cluster analysis and principal component analysis have identified three different patterns of water quality based on anthropogenic effects and marine characteristics: Cluster I located in the outer and middle parts of the bay… Show more

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Cited by 21 publications
(11 citation statements)
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“…High organic matter content in mangrove sediment as observed in our study also leads to increased microbial anaerobic fermentation resulting in ammonia formation 65,57 . On the other hand, Marine Jetty without mangroves have lower ammonium levels as the sediments are low in organic substrate (mangrove leaves) resulting in low denitrifying microbial population.…”
Section: Discussion;supporting
confidence: 65%
“…High organic matter content in mangrove sediment as observed in our study also leads to increased microbial anaerobic fermentation resulting in ammonia formation 65,57 . On the other hand, Marine Jetty without mangroves have lower ammonium levels as the sediments are low in organic substrate (mangrove leaves) resulting in low denitrifying microbial population.…”
Section: Discussion;supporting
confidence: 65%
“…Investigations of nutrients, Chl a and phytoplankton in the bay have been conducted seasonally for several years (Dong et al, 2010;Wu et al, 2011;Wu et al, 2012a;2012b) and demonstrate that the inner bay is influenced by the discharge of the Sanya River with its relatively high nutrient levels, and the central and outer bay are dominated by oceanic exchange with the South China Sea (Wu et al, 2012c). The distribution of salinity in Sanya Bay indicates that the coastal reef station CT is outside the influence of the Sanya River plume in February (Fig.…”
Section: Site Descriptionmentioning
confidence: 99%
“…Principal component analysis (PCA) is a suitable tool for resolution and modeling of large environmental multivariate datasets generated in fractionation studies (Dong et al 2010). PCA is a data reduction procedure (Singh et al 2005) that provides an easy visualization of latent relationships among objects or variables in large and complex data sets.…”
Section: Experimental Designmentioning
confidence: 99%