The lognormal distribution of the elements (2)

Ahrens, L.H.

doi:10.1016/0016-7037(54)90021-6

Cited by 133 publications

(33 citation statements)

References 9 publications

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“…Each major element has an approximately normal dis tribution, but trace elements have a log-normal distribution (Ahrens, 1954). We confirmed that the volatiles are distributed almost log-normally (Yoshida et al, 1971).…”

Section: Samples and Chemical Analysissupporting

confidence: 71%

Multivariate analysis of Japanese volcanic rocks: Volatile and major elements.

Anazawa

Yoshida

1996

Geochem. J.

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Tokyo152, JapanFour types of multivariate procedures (principal components analysis (PCA), factor analysis (FA), cluster analysis and multiple regression analysis (MR)) were applied to find the relationship between volatile contents and genesis of Japanese volcanic rocks. Twelve major elements and seven volatile minor elements were considered on 44 rock samples obtained from various areas of Japan. The variation in the data was demonstrated by 5 components and 5 common factors in PCA and FA, respectively. The first factor implies similar behavior among the major elements; the second factor represents the contribution of seawater to magma genesis; the third factor corresponds to the contribution of the mantle component; the fourth factor suggests separation of sulfide phase from silicate phase; and the fifth factor shows the contribution of sedimentary materials to magma genesis. INTRODUCTION A knowledge of the volatile behavior in vol canic rocks is of great value for understanding magma genesis in subduction zones. However, little work on volatile contents in volcanic rocks has been done because of the difficulty in the analytical technique and the difficulty in estimat ing the original concentration in magmas. Yoshida and his co-workers gave analytical data on F, Cl, Br, I (Yoshida et al., 1971; Yoshida, unpub lished), S (Arikawa, 1987;Hong, 1988) and B (Isozaki et al., 1973). These works were investi gated on respective element individually or were applied elementary statistics on only two or three elements simultaneously. Further work on the synthetic correlation structure among these ele ments was awaited. In the previous work, we studied the multivariate analysis on these six ele ments to understand their behaviors and found the usefulness of the method (Anazawa and Yoshida, 1994).Multivariate analysis allows us to consider changes in several properties simultaneously and is not affected by the number of objects being studied. This group of statistical methods is very powerful, but only limited examples on geo chemical data have been reported, because of its complicated theoretical strategy and operational methodology.In the previous report, we examined six volatiles and found that these elements form three groups by their correlation: (1) Cl, Br and B; (2) F and S; (3) I (iodine). The obtained factor struc ture, however, contained the possibility of chang ing the characteristics with additional variables for lacking of data such as major element concentra tions. (personal communication, 1991) in our research group determined arsenic for 50 Japanese volcanic rocks. He, however, could not find the correlation between As and S. Instead, he suggested a high correlation between As and B. Because of this considerable interest in As properties, we took As analytical data for the application of statistical analysis.In the present report, we describe new findings from multivariate analysis on 44 samples for 12 major and 7 volatile minor elements. The purpose of the present work is, (1) to find the factor str...

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Section: Samples and Chemical Analysissupporting

confidence: 71%

Multivariate analysis of Japanese volcanic rocks: Volatile and major elements.

Anazawa

Yoshida

1996

Geochem. J.

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“…In factor analysis, the varieties whose distribution is distorted can not be put into practical use. As Ahrens' study on rare components reported (Ahrens, 1954), the six components in the present study were assured to have log-normal distribution. Therefore the com mon logarithms of all variates were applied to the statistical analysis.…”

Section: Sample Collection and Analysismentioning

confidence: 98%

Volatile contents in Japanese volcanic rocks: Application of multivariate analysis.

Anazawa

Yoshida

1994

Geochem. J.

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Multivariate analysis was applied to the volatile content data obtained by Yoshida and his co-workers (e.g., Yoshida et al., 1971) to understand magma genesis in subduction zones. A statistical analysis was conducted by the methods of principal component analysis (PCA), factor analysis and hierarchical aggregative cluster analysis. The data can be interpreted on the basis of three principal components and three common factors. The first factor implies the contribution of seawater to magma genesis, which may take place through volatile release from the downgoing plate to the overlying upper mantle wedge. The second factor corresponds to the contribution of the mantle component with higher scores in volcanic rocks on the far side of the volcanic front. The third factor suggests the separation of FeS phase from silicate phase.

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“…All data were treated as being lognormally distributed following Ahrens (1954Ahrens ( , 1957 and Lepeltier (1969), and were plotted on cumulative frequency graphs (Fig. 8-11).…”

Section: Resultsmentioning

confidence: 99%