A climatology of air pollution in the Kansas City metropolitan area.

Abstract

My thesis characterizes the temporal and spatial behavior of ozone and fine particulate matter in the Kansas City metropolitan area. I also investigate the capability of a synoptic weather typing scheme, the Spatial Synoptic Classification, to characterize and explain the behavior of ozone and fine particulate matter in the Kansas City area. Daily maximum ozone concentrations from nine active ozone monitoring stations and daily average particulate concentrations six active PM2.5 monitoring stations were compared to daily SSC weather type records from 2004-2010. Analysis of Variance (ANOVA) tests were conducted on the ozone and PM2.5 data to analyze temporal and spatial behavior. A non-parametric recursive partitioning technique was used to create a conditional inference tree-based regression model to analyze the association between the different SSC weather types and the selected pollutants. The ANOVA results showed significant seasonal trends with both pollutants. In general, ozone concentrations are typically lower in the spring and autumn months and higher during the summer months. PM2.5 concentrations were not as dependent on the season, however, they did tend to be higher in the late summer months and lower in the autumn months. The results also showed significant differences for both pollutants in average concentration depending on location. The ozone concentrations generally tended to be higher in the areas that are located downwind of Kansas City and lowest at the station located in the middle of the urban area. Fine particulates also seemed to be highest in the downwind portion of the urban area and lowest in the region upwind of the city. The conditional inference tree showed that higher concentrations of both pollutants are associated with tropical air masses and lower concentrations are associated with polar air masses.