Title of article
Using chemometrics to evaluate anthropogenic effects in Daya Bay, China
Author/Authors
Mei-Lin Wu، نويسنده , , You-Shao Wang، نويسنده ,
Issue Information
روزنامه با شماره پیاپی سال 2007
Pages
11
From page
732
To page
742
Abstract
In this work, we have monitored 12 stations to study the effects caused by natural, marine and anthropogenic activities on water quality in
Daya Bay, China. Results show that the N:P ratios are 71.54, 41.29, 81.50 and 98.27 in winter, spring, summer and autumn, respectively. Compared
with the data of the past 20 years, the atomic N:P ratios have increased, indicating increased potential for P limitation; the atomic Si:N
ratios have decreased; the nutrient structure has substantially changed over a period of 20 years. These findings show that the nutrient structure
may be related to anthropogenic influence. The data matrix has been built according to the results, which were analyzed by principal component
analysis (PCA). This analysis extracted the first four principal components (PC), explaining 73.58% of the total variance of the raw data. PC1
(25.53% of the variance) is associated with temperature, salinity and nitrate. PC2 (21.64% of the variance) is characterized by dissolved oxygen
and silicate. PC3 (15.91% of the variance) participates mainly by nitrite (NO2-N) and ammonia (NH4-N). PC4 explaining 10.50% of the variance
is mainly contributed by parameters of organic pollution (dissolved oxygen, 5-day biochemical oxygen demand and chemical oxygen demand).
PCA has found the important factors that can describe the natural, marine and anthropogenic influences. Temperature and salinity are
important indicators of natural and marine characters in this bay. The northeast monsoons from October to April and southwest monsoons
from May to September have important effects on the waters in Daya Bay. It has been demonstrated that anthropogenic activities have significant
influence on nitrogen form character. In spatial pattern, a marine aquaculture area and a non-aquaculture area are widely identified by the scores
of stations. In seasonal pattern, dry and wet season characters have been demonstrated.
Keywords
Spatial and temporal patterns , water quality , Daya Bay , Principal component analysis
Journal title
Estuarine, Coastal and Shelf Science
Serial Year
2007
Journal title
Estuarine, Coastal and Shelf Science
Record number
953151
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