Identification of airborne particulate sources, of samples collected in Ticomán, Mexico, using PIXE and multivariate analysis

Abstract

A set of samples of airborne particulate matter collected during February and March 1997 in Ticomán, a place located in the northern part of Mexico City's Metropolitan Area, were analysed by PIXE and the concentrations of ten main elements were determined. The fundamental information provided by PIXE was used to build up the data base needed to apply statistical tools such as absolute principal factor analysis. The VARIMAX rotated component matrix of the data was obtained, and the first three principal factors were assigned to soil, industry, and sulfates pollution sources. The quantitative source apportionments of the atmospheric trace element concentrations for the day time and the night time were determined by means of absolute principal factor scores.

Introduction

Mexico City is near to being the most polluted city in the world. At present, the problem expands across the country since many of the major cities such as Guadalajara, Monterrey and others have registered high rates of pollution as a consequence of contaminated residual fumes from neighbour industrial areas.

It is of interest to concentrate attention on Mexico City's Metropolitan Area (ZMCM). Since 1940 this area has shown an accelerated and steady increase in its population. 20% (approximately 20 million inhabitants) of the total population of the country is concentrated in only 1% of the national territory; the population density is about 5494 inhabitants per square kilometre. Moreover, 50% of the industrial activity [1] is also concentrated into the same percentage of the territory.

Several government institutions as well as the research and academic community have made a great effort to contribute to decrease the pollution problem [2], [3], [4], [5], [6]. However, the actions have not been enough and have only mitigated the situation. At present, more studies are needed in order to create new strategies that permit to control and diminish the problem. In this respect, it is worth mentioning that identification of the air pollutant sources can help to reduce the problem. The determination of the composition and sources of urban air particulate matter is becoming increasingly important to establish air pollution control programs. Once the sources are identified, especially those of undesirable elements, steps can be taken to control their release to the environment. Multivariate analysis has been shown to be a powerful technique for connecting a large body of elemental concentrations of atmospheric particles to their possible sources. In this respect, the fundamental and unique role played by PIXE in providing the basic information to build up the data base needed to apply these statistical tools must be pointed out.

One of the areas within the ZMCM which has been detected to have a poor air quality is Ticomán [7] and it has been chosen to apply the multivariate analysis. Partial results of the PIXE analysis performed on a set of samples taken in this place has already been presented [7]. However, the number of analysed samples was significantly increased in order to carry out this study, with a total of 73 samples taken during night and day periods.

Ten elements were identified: S, K, Ca, Ti, V, Mn, Fe, Cu, Zn and Pb appeared recurringly while others appeared with less frequency, for instance Cl, Ni, As and Br. Cl, Ni and Br appeared mainly during the night. In order to provide new insights into the air pollution problem in this area, absolute principal factor analysis (APFA) and absolute principal factor scores (APFS) were applied to the new data base using SPSS${}^{\mathrm{\circledR }}$ software [8] version 10.0 by SPSS Inc. It was thus possible to identify soil, industry and sulfates as emission sources for the day and night sampling periods, and to determine the apportionment of each source for each element.