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Application of pattern recognition to speciation data of heavy metals in suspended particulates of urban air
Author(s) -
Tomas X.,
Rius J.,
Obiols J.,
Sol A.
Publication year - 2005
Publication title -
journal of chemometrics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.47
H-Index - 92
eISSN - 1099-128X
pISSN - 0886-9383
DOI - 10.1002/cem.1180030506
Subject(s) - particulates , manganese , environmental chemistry , organic matter , metal , genetic algorithm , extraction (chemistry) , air pollution , chemistry , pollution , heavy metals , environmental science , ecology , organic chemistry , chromatography , evolutionary biology , biology
In order to get a better knowledge of the air pollution levels of the urban air of Barcelona, twelve samples from three stations of the air‐monitoring control network were analysed. Each control station is representative of a different environmental situation. Thus the station at Plaça Molina responds to a simple domestic and urban traffic situation; the station at Poble Nou to the influence of medium and small industries, mainly metallurgical; and the station at Montcada to a zone in which there exist important industries, a cement factory, two highways and railroads. The total content of unsedimentable particles, three inorganic anions (chlorides, sulphates and nitrates) and six heavy metals (Fe, Pb, Cu, Mn, Cr and Cd) were determined on all the samples obtained during the same period of time. The use of an analytical scheme of sequential extraction has also permitted the subdivision of the total content of each metal into the following four fractions: (1) soluble or exchangeable; (2) associated with carbonates and/or with iron and manganese oxides; (3) bound to organic matter; and (4) residual. The use of principal component analysis applied to the data as a whole showed the associations and correlations between the various parameters as well as between the different above mentioned fractions. The predominant presence of Cd in the ‘soluble or exchangeable’ fraction is confirmed, while the other metals are mainly associated with the ‘carbonates and/or Fe and Mn oxides’ and ‘bound to organic matter’ fractions. Hierarchical cluster analysis applied to the twelve samples showed clearly the presence of three different classes closely related to the origin (station) of the samples. Thus it becomes feasible to propose for each station a possible profile of the content in terms of the different parameters considered.