Iterative thermodynamic modelling—Part 2: tracing equilibrium relationships between minerals in metamorphic rocks

Author(s):  
Pierre Lanari ◽  
Jörg Hermann
Author(s):  
Gejing Li ◽  
D. R. Peacor ◽  
D. S. Coombs ◽  
Y. Kawachi

Recent advances in transmission electron microscopy (TEM) and analytical electron microscopy (AEM) have led to many new insights into the structural and chemical characteristics of very finegrained, optically homogeneous mineral aggregates in sedimentary and very low-grade metamorphic rocks. Chemical compositions obtained by electron microprobe analysis (EMPA) on such materials have been shown by TEM/AEM to result from beam overlap on contaminant phases on a scale below resolution of EMPA, which in turn can lead to errors in interpretation and determination of formation conditions. Here we present an in-depth analysis of the relation between AEM and EMPA data, which leads also to the definition of new mineral phases, and demonstrate the resolution power of AEM relative to EMPA in investigations of very fine-grained mineral aggregates in sedimentary and very low-grade metamorphic rocks.Celadonite, having end-member composition KMgFe3+Si4O10(OH)2, and with minor substitution of Fe2+ for Mg and Al for Fe3+ on octahedral sites, is a fine-grained mica widespread in volcanic rocks and volcaniclastic sediments which have undergone low-temperature alteration in the oceanic crust and in burial metamorphic sequences.


2004 ◽  
Vol 43 (4II) ◽  
pp. 619-637 ◽  
Author(s):  
Muhammad Nishat ◽  
Rozina Shaheen

This paper analyzes long-term equilibrium relationships between a group of macroeconomic variables and the Karachi Stock Exchange Index. The macroeconomic variables are represented by the industrial production index, the consumer price index, M1, and the value of an investment earning the money market rate. We employ a vector error correction model to explore such relationships during 1973:1 to 2004:4. We found that these five variables are cointegrated and two long-term equilibrium relationships exist among these variables. Our results indicated a "causal" relationship between the stock market and the economy. Analysis of our results indicates that industrial production is the largest positive determinant of Pakistani stock prices, while inflation is the largest negative determinant of stock prices in Pakistan. We found that while macroeconomic variables Granger-caused stock price movements, the reverse causality was observed in case of industrial production and stock prices. Furthermore, we found that statistically significant lag lengths between fluctuations in the stock market and changes in the real economy are relatively short.


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