scholarly journals Analysis of the composition of heavy metal pollution in Japanese river sediments by principal component analysis.

1985 ◽  
Vol 46 (3) ◽  
pp. 169-173 ◽  
Author(s):  
Masaya MIYAI ◽  
Fumi TADA ◽  
Hideo NISHIDA
2019 ◽  
Vol 29 (3SI) ◽  
pp. 411
Author(s):  
N. H. Quyet ◽  
Le Hong Khiem ◽  
V. D. Quan ◽  
T. T. T. My ◽  
M. V. Frontasieva ◽  
...  

The aim of this paper was the application of statistical analysis including principal component analysis to evaluate heavy metal pollution obtained by moss technique in the air of Ha Noi and its surrounding areas and to evaluate potential pollution sources. The concentrations of 33 heavy metal elements in 27 samples of Barbula Indica moss in the investigated region collected in December of 2016 in the investigated area have been examined using multivariate statistical analysis. Five factors explaining 80% of the total variance were identified and their potential sources have been discussed.


2003 ◽  
Vol 37 (4) ◽  
pp. 813-822 ◽  
Author(s):  
H. Akcay ◽  
A. Oguz ◽  
C. Karapire

2021 ◽  
Author(s):  
Wende Chen ◽  
Kun Zhu ◽  
Yankun Cai ◽  
Peihao Peng

Abstract In megacities, due to frequent human activities, large amounts of metals enter the soil indirectly or directly and eventually flow to people through the food chain. Therefore, the analysis and identification of soil heavy metal sources is an important part of revealing soil heavy metal pollution. The spatial content and potential sources of 11 heavy metals were analyzed from 342 surface soil samples collected from the central city of Chongqing in southwest China. The results showed that the main heavy metal elements under the first principal component loading were copper (Cu), nickel(Ni), zinc (Zn), manganese (Mn), cadmium (Cr), plumbum (Pb) and cadmium (Cd). The second principal component (F2) was mainly loaded with molybdenum (Mo), arsenic (As), mercury (Hg) and antimony (Sb), and the PCA-APCs receptor model of 11 heavy metals was constructed. The PCA-APCs receptor models of 11 heavy metals were constructed. The results of classification regression analysis confirmed the main sources of heavy metals. Population density mainly affected Cu (0.539), soil mainly affected Ni (0.411), Sb (0.493), Zn (0.472) and Mn (0.206), and water quality mainly affected As (0.453) and Mo (0.374). Air quality mainly affects Cd (0.332) and Cr (0.371), traffic activity mainly affects Hg (0.312), and slope mainly affects Pb (0.313). Hot spot analysis showed that heavy metals had a high degree of coincidence with environmental factors such as soil parent material, slope, soil type and traffic activities. The results of this study can be effectively used to make scientific decisions and strategies, and an effective strategy for prevention and control of soil heavy metal pollution should be formulated to protect the urban soil environmental quality.


2009 ◽  
Vol 9 (6) ◽  
pp. 1190-1193 ◽  
Author(s):  
M. Goorzadi ◽  
Gh. Vahabzadeh ◽  
M.R. Ghanbarpou ◽  
A.R. Karbassi

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