Monitoring procedures in environmental geochemistry and compositional data analysis theory

First discussion on compositional data analysis is attributable to Karl Pearson, in 1897. However, notwithstanding the recent developments on algebraic structure of the simplex, more than twenty years after Aitchison’s idea of log-transformations of closed data, scientific literature is again full of statistical treatments of this type of data by using traditional methodologies. This is particularly true in environmental geochemistry where besides the problem of the closure, the spatial structure (dependence) of the data have to be considered. In this work we propose the use of log-contrast values, obtained by asimplicial principal component analysis, as LQGLFDWRUV of given environmental conditions. The investigation of the log-constrast frequency distributions allows pointing out the statistical laws able togenerate the values and to govern their variability. The changes, if compared, for example, with the mean values of the random variables assumed as models, or other reference parameters, allow definingmonitors to be used to assess the extent of possible environmental contamination. Case study on running and ground waters from Chiavenna Valley (Northern Italy) by using Na+, K+, Ca2+, Mg2+, HCO3-, SO4 2- and Cl- concentrations will be illustrated

Chemical composition of the small coastal lagoons of the Mediterranean Spanish littoral

About sixty small water bodies (coastal lagoons, marshes, salt pans, channels, springs, etc.) of the Spanish Mediterranean coast were sampled seasonally for one year (1979-1980), in order to study different aspects of their chemical composition. The concentrations of major ions (alkalinity, Cl-, Ca2+, Mg2+, Na+, and K+), nutrients (N.NO-3, N.NO2-, TRP and Si), oxygen and pH were determined for this purpose. The salt concentrations measured range between 0.4 and 361.3 g l-1. The samples have been divided into four classes of salinity (in g l-1): Cl, S < 5; C2, 5 40. Within these classes, the pattern of ionic dominance recorded is remarkably constant and similar to that found in most coastal lagoons (Cl- > So42- > Alk., for the anions, and Na+ > Mg2+ > Ca2+ > K+, for the cations), although other models occur especially in the first class. The dominance of Na+ and Cl-, as well as the molar ratios Mg2+/Ca2+ and Cl- / SO42- ,clearly increase from class Cl to class C4. The hyperhaline waters include different subtypes of the major brine type"c",, of EUGSTER & HARDIE (1978), the Na+ - (Mg2+) - Cl- - (SO42-) being the most frequent. Nutrient concentrations fall within a wide range (N.NO3 from 0.1 to 1100 mg-at 1-1; PRT from 0.01 to 23.56 mg-at l-1 and Si from 1.0 to 502.0 mg-at l-1). The oxygen values are very variable too, ranging between 0 and 14.4 ml l-1. Four different patterns of nutrient distribution have been distinguished based on the mean concentrations of N.NO3-, and TRP (mean values in mg-at l-1): A, N.NO3- < 10, TRP > l ; B, N.NO3- > 100, TRP < 1; C, 10 < N.NO3- < 100, TRP < 1; C, D, N.NO3- < 10, TRP < 1. As a rule, lagoons of low salinity (C1 and C2 classes) display the nutrient pattern C, and lagoons of high salinity (C3 and C4) show the nutrient pattern D. Model A only appears in waters of very low salinity, whereas model B does not seem to be related to salinity.

Reliability of the density functional approximation to describe the charge transfer and electrostatic complexes involved in the modeling of organic conducting polymers

Both the intermolecular interaction energies and the geometries for M ̄ thiophene, M ̄ pyrrole, M n+ ̄ thiophene, and M n+ ̄ pyrrole ͑with M = Li, Na, K, Ca, and Mg; and M n+ = Li+ , Na+ , K+ , Ca2+, and Mg2+͒ have been estimated using four commonly used density functional theory ͑DFT͒ methods: B3LYP, B3PW91, PBE, and MPW1PW91. Results have been compared to those provided by HF, MP2, and MP4 conventional ab initio methods. The PBE and MPW1PW91 are the only DFT methods able to provide a reasonable description of the M ̄ complexes. Regarding M n+ ̄ ␲ complexes, the four DFT methods have been proven to be adequate in the prediction of these electrostatically stabilized systems, even though they tend to overestimate the interaction energies.