Investigating the Influence of Environmental Features on Air Pollution and Environmental Noise in Three Cities of Ontario, Canada

This thesis examines the impacts of environmental features on air and noise pollution covariance in three different cities of Southern Ontario. More specifically, the objectives of the study were to (1) Evaluate the correlation and spatial relationship between nitrogen dioxide 2NO ), and environmental noise in Mississauga, Hamilton and London; (2) Analyze the influence of environmental features on the covariance of NO and NO2se levels in the study areas. A combination of descriptive and inferential bivariate, and multivariate statistical techniques were performed to develop local and global models of noise and air pollution covariance. This study found a substantial correlation between the NO 2nd environmental noise in Mississauga and Hamilton; however, the correlation in London was very low. According to the final Land Use Regression (LUR) model, variables like traffic volume, road length, and industrial land-use increase the NO a2d environmental noise in different cities, whereas Normalized Difference Vegetation Index (NDVI) helps to reduce the NO a2d environmental noise. This approach could be a good option for LUR modeling of environmental pollution in cities where extensive spatial monitoring is unfeasible, and more specifically, the predicted results of such a study may be applied to further health studies in the cities with the same land-use patterns.