Prediction of ozone concentration in ambient air using multivariate methods

Multivariate statistical methods including pattern recognition (Principal Component Analysis—PCA) and modeling (Multiple Linear Regression—MLR, Partial Least Squares—PLS, as well as Principal Component Regression—PCR) methods were carried out to evaluate the state of ambient air in Miskolc (second l...

Full description

Saved in:
Bibliographic Details
Published in:Chemosphere (Oxford) 2004-11, Vol.57 (8), p.889-896
Main Authors: Lengyel, A., Héberger, K., Paksy, L., Bánhidi, O., Rajkó, R.
Format: Article
Language:English
Subjects:
Air - analysis
Ambient air
Applied sciences
Atmospheric pollution
Environmental data
Environmental Monitoring - methods
Exact sciences and technology
Hungary
Linear Models
Modeling of ozone concentration
Multivariate Analysis
Ozone - analysis
Partial least squares (PLS)
Pollutants physicochemistry study: properties, effects, reactions, transport and distribution
Pollution
Principal Component Analysis
Principal component analysis (PCA)
Principal component regression (PCR)
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:Multivariate statistical methods including pattern recognition (Principal Component Analysis—PCA) and modeling (Multiple Linear Regression—MLR, Partial Least Squares—PLS, as well as Principal Component Regression—PCR) methods were carried out to evaluate the state of ambient air in Miskolc (second largest city in Hungary). Samples were taken from near the ground at a place with an extremely heavy traffic. Although PCA is not able to determine the significance of variables, it can uncover their similarities and classify the cases. PCA revealed that it is worth to separate day and night data because different factors influence the ozone concentrations during all day. Ozone concentration was modeled by MLR and PCR with the same efficiency if the conditions of meteorological parameters were not changed (i.e. morning and afternoon). Without night data, PCR and PLS suggest that the main process is not a photochemical but a chemical one.
ISSN:0045-6535
1879-1298
DOI:10.1016/j.chemosphere.2004.07.043