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A chemometrical study regarding a 10-years water quality monitoring plan at 15 sampling points along a section of the Reconquista River and its stream channels, which embraces 21 campaigns, is presented. The original data were pre-treated in order to eliminate missing data and outliers, obtaining a final data matrix of 270 samples by 26 physical-chemistry variables. Multivariate statistical methods like multi curve resolution, canonical correlation analysis and factor analysis methods, as well as current univariate statistics were applied. The interpretation was simplified when variables were separated in groups containing environmentally and chemically related variables instead of analyzing them all together. These methods have shown that the presence of metals likely come from at least 3 different type of sources. Although the stream channels arriving to the main river course are highly polluted, their flow rates are so low that do not significantly decrease its water quality. They mainly contribute to the high levels of biochemical-oxygen demand and chemical-oxygen demand as well as nitrogen-content species. Furthermore, regarding metals, the pollution of the river coming from the upstream is higher than those introduced by all channels. Fil: Garcia Reiriz, Alejandro Gabriel. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Rosario. Instituto de Química Rosario. Universidad Nacional de Rosario. Facultad de Ciencias Bioquímicas y Farmacéuticas. Instituto de Química Rosario; Argentina Fil: Magallanes, Jorge Federico. Comisión Nacional de Energía Atómica; Argentina Fil: Vracko, Marjan. National Institute of Chemistry; Eslovenia Fil: Zupan, Jure. National Institute of Chemistry; Eslovenia Fil: Reich, Silvia Leonor. Universidad Nacional de San Martín. Instituto de Investigación en Ingeniería Ambiental; Argentina Fil: Cicerone, Daniel. Comisión Nacional de Energía Atómica; Argentina. Universidad Nacional de San Martín. Instituto de Investigación en Ingeniería Ambiental; Argentina

In this article a method to increase the capability of an electronic nose to discriminate between a priori similar odours is presented. Olive oil is analyzed because it is well known that the characteristics of its aroma impair in many cases the discrimination between different kinds of olive oils especially when they are from similar geographic regions. In the present work the improvement of the electronic nose performance for the above-mentioned discrimination by a non-destructive method of IR laser vaporization of the sample is studied. Laser vaporization has also been performed at two different IR wavelengths to analyze the effect of laser radiation absorption of the sample on the electronic nose selectivity.

The Riachuelo–Matanza basin area (2.240 km 2 ) is located in Buenos Aires province, Argentina. This area is affected by intensive and extensive agricultural activities, and bears almost 3,000,000 inhabitants and more than 10,000 industries, that release their effluents to the main collector of the basin, the Riachuelo River. It is a highly polluted area and the quality of water, soil and air is severely impaired causing chronic health problems. As part of an interdisciplinary study undertaken by local institutions to reach an environmental quality diagnosis and analysis of the pollutants dynamics in the basin system we have measured, with an electronic nose, the air immediately above the water in several points at the Riachuelo River mouth where the painteresque La Boca district is located. Water quality parameters simultaneously collected at the same sites were analyzed and correlated with the electronic nose response. This study is only exploratory and focuses on the viability of using an electronic nose to locate conflictive emissions throughout a given zone.

Air pollutant concentrations from a monitoring campaign in Buenos Aires City, Argentina, are used to investigate the relationships between ambient levels of ozone (O3), nitric oxide (NO) and nitrogen dioxide (NO2) as a function of NO x (=NO + NO2). This campaign undertaken by the electricity sector was aimed at elucidating the apportionment of thermal power plants to air quality deterioration. Concentrations of carbon monoxide (CO) and sulphur dioxide (SO2) were also registered. Photo stationary state (PSS) of the NO, NO2, O3 and peroxy radicals species has been analysed. The ‘oxidant’ level concept has been introduced, OX (=O3 + NO2), which varies with the level of NO x . It is shown that this level is made up of NO x -independent and NO x -dependent contributions. The former is a regional contribution that equates the background O3 level, whereas the latter is a local contribution that correlates with the level of primary pollution. Furthermore, the anticorrelation between NO2 and O3 levels, which is a characteristic of the atmospheric photo stationary cycle has been verified. The analysis of the concentration of the primary pollutants CO and NO strongly suggests that the vehicle traffic is the principal source of them. Levels of continuous measurements of SO2 for Buenos Aires City are reported in this work as a complement of previously published results.

A prototype of an electronic nose (e-nose), based on an array of six undoped and doped SnO2 gas sensors made by the rheotaxial growth and thermal oxidation (RGTO) technique, is applied to the analysis of a basic ingredient of beer, the hop. We address two main requirements from the local brewing industry: to detect departures from the hop’s quality due to aging processes or lousy storage and to obtain a quick discrimination of the various similar types of pellets usually employed. Different methods for the extraction of the features of each sensor response have been studied. A comparison between discrimination obtained with a linear dimensional reduction via principal component analysis and a nonlinear reduction obtained with self-organized maps has also been made. © 2004 Elsevier B.V. All rights reserved.

The 15-variable environmental data (7 concentrations: CO, SO2, O3, NOx, NO, NO2, particulate matter smaller than 10 micron (PM10), and 8 weather data: cloudiness, rainfall, insolation factor (Isfi), temperature, pressure at two locations, and wind intensity with direction) in a period of 45 days with 1-h intervals were extracted from a larger database of concentrations recorded in minute intervals for the same time period. The monitoring site was located in the City of Buenos Aires in a relatively heavy traffic crossroad of two avenues. The data required special pretreatment where the hourly content of rain, wind intensity, wind velocity, and cloudiness were concerned. The new variable named insolation factor (relative UV radiation) calculated on the basis of the general meteorological data, the geographic position of the monitoring site, cloudiness, date, and the time of the recording was composed. The relative intensity of UV radiation was modeled by a Gaussian function, multiplied by a cloudiness factor. Based on the 14-variable input and the 1-variable output (ozone) data, first, the clustering of all 980 data records was made. The top map clustering showing the ozone concentration was related to the maps of all 14 variables. The link between O3 clusters, NO2, and Isfi weight levels is shown and discussed. As a preliminary result of this study some of the most interesting correlations between the maps and remaining variables are given.

This job refers to classification of multidimensional objects and Kohonen artificial neural networks. A new concept is introduced, called the mean angular distance among objects (MADO). Its value can be calculated as the cosine of the mean centered vectors between objects. It can be expressed in matrix form for any number of objects. The MADO allows us to interpret the final organization of the objects in a Kohonen map. Simulated examples demonstrate the relationship between MADO and Kohonen maps and show a way to take advantage of the information present in both of them. Finally, a real analytical chemistry case is analyzed as an application on a big data set of an air quality monitoring campaign. It is possible to discover in it a subgroup of objects with different characteristics than those of the general trend. This subgroup is linked to the existence of an unidentified SO(2) source that, a priori, has not been taken into account.

We report preliminary results of our first prototype of electronic nose (e-nose) for discrimination between different mate brands. This work shows advances along the three main lines of our e-nose system: i) development and characterization of each of the six sensors in the array, ii) electronic interface for control of the sensor array and for data acquisition and iii) design and optimization of the pattern recognition algorithm.

Se describe el Proyecto ARPAS, que se ha comenzado recientemente en la República Argentina, con el objeto de construir una computadora con arquitectura paralela tipo SIMD.