Establishment of a structural equation model for ground-level ozone: a case study at an urban roadside site.

Abstract

This study established a cause-effect relationship between ground-level ozone and latent variables employing partial least-squares analysis at an urban roadside site in four distinct seasons. Two multivariate analytic methods, factor analysis, and cluster analysis were adopted to cite and identify suitable latent variables from 14 observed variables (i.e., meteorological factors, wind and primary air pollutants) in 2008-2010. Analytical results showed that the first six components explained 80.3% of the variance, and eigenvalues of the first four components were greater than 1. The effectiveness of this model was empirically confirmed with three indicators. Except for surface pressure, factor loadings of observed variables were 0.303-0.910 and reached statistical significance at the 5% level. Composite reliabilities for latent variables were 0.672-0.812 and average variances were 0.404-0.547, except for latent variable "primary" in spring; thus, discriminant validity and convergent validity were marginally accepted. The developed model is suitable for the assessment of urban roadside surface ozone, considering interactions among meteorological factors, wind factors, and primary air pollutants in each season.