Selection of the scenarios of ozone pollution at southern Taiwan area utilizing principal component analysis

The monitoring data analysis performed in this investigation focuses mainly on selecting statistically representative scenarios of ozone pollution in southern Taiwan. Measured data of ozone employed in this analysis were obtained from the monitoring stations of Taiwan Environmental Protection Administration (TEPA). The multivariate statistical technique, principal component analysis (PCA), was proposed to screen the ozone scenarios. Kaiser’s varimax rotation method was also employed to separate the study area into several homogenous influence regimes. The analysis of spatial average ozone profiles, backward trajectories and statistical analysis could reveal features of selected ozone scenarios. Analysis results indicated that the first four unrotated components and rotated components accounted for more than 70 and 70.8% of the total variance, respectively. The score of the first unrotated principal component above 7 is the screening threshold for ozone scenarios. Such ozone scenarios accounted for 14.2% of ozone stations number days with a low occurrence rate of 1.37%. Varimax rotation method successfully separated southern Taiwan into four homogenous ozone subregions, contributing 33.9, 17.3, 12.1 and 2.5% of total the variances, respectively. Evaluating the backward trajectories and spatial ozone profiles revealed that weak westerly sea breeze is the dominant factor affecting the production of the high ozone event for most stations. The backward trajectories also indicated similar meteorological patterns of the stations in the same subregion.