Ground-level ozone has become a problem of major concern in urban airsheds in Canada, owing to its adverse effects on humans and crops. As a secondary pollutant, its formation is dependent on the presence of certain precursor gases in conjunction with appropriate meteorological conditions. Several studies have examined the relationship between maximum concentrations and key meteorological variables at the regional scale during episodic conditions. This study sought to understand this relationship at the local scale using surface and upper-air meteorological data for the Niagara Region. In the methodological approach, factor analysis and linear regression methods were used to determine the best combination of variables that would explain the highest percentage of variance in daily maximum ground-level ozone associated with different event categories. Each event category had a combination of unique meteorological characteristics. Factor analysis yielded seven factors that together constituted 20 of the original 59 variables in the data set. In the application of a series of regression analyses, the thermal factors of the lower atmosphere emerged as the most important variables, followed by variables related to persistence and advection characteristics. The daily maximum temperature was the single most important variable and accounted for the largest percentage of the variance explained, whereas the persistence factor was of secondary importance. The overall results suggest that a small number of surface variables based on the local meteorology of the Niagara Region can be used to estimate daily maximum ground-level ozone.
|Original language||English (US)|
|Number of pages||29|
|State||Published - 1996|