Abstract
The study of the correlation matrix between ion concentration and the principal component analysis on the related variance matrix are widely used to explore the presence of contamination patterns in rainwater. The paper shows that the covariance between ion concentrations is a perturbed measure, and that the total conductivity can be interpreted as the perturbation factor. Then, the paper describes some strategies for measuring and removing the perturbation and how, by removing this effect, correct contamination patterns can be identified. A summary of the results of an application on data measured by the monitoring network of the Veneto region is proposed.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Aitchison, J. (1983) Principal component analysis of compositional data, Biometrika, 70, 57 – 65.
Aitchison, J. (1986) The Statistical Analysis of Compositional Data, Chapman and Hall, New York.
Crow E.L. (1988) Applications in Atmospheric Sciences, in: Lognormal distributions, theory and applications, E.L. Crow and K. Shimizu (Eds.), Dekker, New York, 331 – 356.
Jackson J.E. (1991)A User’s Guide To Principal Components, Wiley, New York.
Johnson N.L.,Kotz S. (1972) Distributions in Statistics: Continuous Multivariate Distributions, Wiley, New York.
Mantovan P, Pastore A. (1996a) Alcuni problemi di identificazione di soluzioni fattoriali perturbate, Società Italiana di Statistica, Atti della XXXVIII Riunione Scientifica, Maggioli editore, 61–68
Mantovan P., Pastore A. (1996b) A Perturbation Model for Factorial Solutions with Application Metron, LIV(3–4), 39 – 63.
Mantovan P., Pastore A., Szpyrkovicz L., Zilio-Grandi F. (1995) Characterization of rainwater quality from the Veneto region network data using Multiway Data Analysis, The Science of the Total Environment, 164, 27 – 43.
Pastore A. (1998) A Perturbation Removal Strategy for Factorial Solution based on the Log-Normal Distribution, VI Conference of IPCS, Book of Short Papers229 – 232.
Saylor R.D., Butt K.M., Leonard K.P. (1992) Chemical Characterization of Precipitation from a Monitoring Network in the Lower Ohio Valley, Atmospheric Environment, 1147 – 1156.
Zeng Y., Hopke P.H. (1989), A study of the sources of acid precipitation in Ontario, Canada, Atmospheric Environment, 1499 – 1509.
Zilio-Grandi F., Szpyrkovicz L. (1991), Air Pollution Monitoring Network for the Venice Region: Preliminary Results for the Rain Quality, Toxicological and Environmental Chemistry, 29, 281 – 296.
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2001 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Mantovan, P., Pastore, A. (2001). Perturbation Models for Principal Component Analysis of Rainwater Pollution Data. In: Borra, S., Rocci, R., Vichi, M., Schader, M. (eds) Advances in Classification and Data Analysis. Studies in Classification, Data Analysis, and Knowledge Organization. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-59471-7_19
Download citation
DOI: https://doi.org/10.1007/978-3-642-59471-7_19
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-41488-9
Online ISBN: 978-3-642-59471-7
eBook Packages: Springer Book Archive