Highway tunnel air quality assessment using multivariate statistical classification on factor, cluster, and discriminant analysis

Abstract

The air quality monitoring points set up at the existing 10 tunnels (a total of 20 tunnel entrances) on Formosa Freeway in Northern Taiwan were used in this study to investigate the correlation among various types of air pollutants measured at these 20 tunnel entrances via a multivariate statistical analysis. This study aimed to determine the main factors that affect the extent of air pollution along the Formosa Freeway and its vicinity, and explored the interrelationships among various air pollutants to reflect the differences among the air pollutants found along the Formosa Freeway in Northern Taiwan, as well as to establish an evaluation mode for types and characteristics of air pollutants after their quantification. Two main factors were obtained from the factor analysis: the “photochemical reaction pollution factor” and the “vehicle fuel factor.” Cluster analysis is used to classify air quality in Formosa Freeway in Northern Taiwan into five clusters to present different characteristics and pollution degrees of air quality in this study. The more that the air pollutants and samples are used when performing a factor analysis, the more effective the validity and reliability of the factor analysis! This research results can serve as a reference for those involved in the review of air quality management effectiveness and/or the enactment of management control strategies. In addition, it is also a good method to use in an air quality management program and it is expected that the results can serve as a reference for the management to prevent and control air pollution in the future.