A comparative study on various statistical techniques predicting ozone concentrations: implications to environmental management

被引:21
作者
Paschalidou, A. K. [1 ]
Kassomenos, P. A. [1 ]
Bartzokas, A. [1 ]
机构
[1] Univ Ioannina, Dept Phys, Lab Meteorol, GR-45110 Ioannina, Greece
关键词
Multicollinearity; Principal component analysis; Stepwise regression analysis; Tropospheric ozone; NEURAL-NETWORK MODEL; AIR-QUALITY; PRINCIPAL COMPONENT; ATHENS; POLLUTION; REGRESSION; POLLUTANTS; GREECE; COVARIABILITY;
D O I
10.1007/s10661-008-0158-0
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
The objective of the present work is to compare various techniques for modeling the dependence of the tropospheric ozone concentrations on several meteorological and pollutant parameters. The study focuses on two different sites in the metropolitan area of Athens, Greece; one in the city centre and another one in the suburbs. It is found that although simple Linear Regression Analysis fails to construct accurate equations due to the existence of multicollinearity among the independent variables, still various combinations of a Multivariate Method (PCA) and Stepwise Regression Analysis manage to produce equations free of the multicollinearity issue. The derived formulas are validated and prove to have R-2 values in the order of 0.8 approximately. However, the equations are found to be unsuccessful in case of severe episodes. For this reason, a new procedure is followed for estimating the ozone values in case of episodes exclusively. The new R-2 value is estimated to be 0.9, approximately.
引用
收藏
页码:277 / 289
页数:13
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