Volatile organic compounds in the area of Madrid: A chemometrical approach

Multivariate techniques have been applied to the set of data obtained after one year sampling of volatile organic compounds (VOCs), including volatile aldehydes in the area of Madrid in order to evaluate the possible correspondence among groups of analysed compounds, as far as modelling of different...

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Bibliographic Details
Published inEnvironmental monitoring and assessment Vol. 75; no. 1; pp. 33 - 50
Main Authors PEREZ PASTOR, R. M, GARCIA ALONSO, S, QUEJIDO CABEZAS, A. J
Format Journal Article
LanguageEnglish
Published Dordrect Springer 01.04.2002
Springer Nature B.V
Subjects
Air Pollutants - analysis
Aldehydes
Analysis methods
Anthropogenic factors
Applied sciences
Atmospheric pollution
Cities
Cluster Analysis
Correlation analysis
Environmental monitoring
Environmental Monitoring - statistics & numerical data
Exact sciences and technology
Factor analysis
Gas Chromatography-Mass Spectrometry
Organic Chemicals - analysis
Organic compounds
Pollution
Rural areas
Seasonal variations
Seasons
Spain
Studies
Suburban areas
Vehicle Emissions - analysis
VOCs
Volatile organic compounds
Volatilization
Europe
Spain
Spain, Madrid
Spain, Castilla, Madrid
Cluster analysis
Factor analysis
Air content
Correlation analysis
Pollution source
Air pollution
Suburban zone
Volatile organic compound
Urban area
Multivariate analysis
Spatial variation
Time variation
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Summary:Multivariate techniques have been applied to the set of data obtained after one year sampling of volatile organic compounds (VOCs), including volatile aldehydes in the area of Madrid in order to evaluate the possible correspondence among groups of analysed compounds, as far as modelling of different emission sources in relation to location and season. The measurements were carried out at four sites in Madrid, characteristic for urban and suburban areas. Additionally, as reference, a rural area 100 km far from the city was considered. Results of correlation analysis, factor and cluster analysis are presented. Higher correlations were found between variables related with traffic emissions. Factor analysis results showed two main significant variables related to anthropogenic and biogenic emissions respectively. In relation to cluster analysis, samples were grouped according to sampling site and seasonal variations.
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ISSN:0167-6369
1573-2959
DOI:10.1023/A:1014207918378