Assessing the impacts of air pollution and extreme weather on human health in the urban environment

The aim of this dissertation is to support efforts to mitigate the impacts of climate change on human health by advancing our understanding of the relationships between human health, air pollution, and current weather conditions and by providing forecasts of the trends and intensity of high-risk weather classes on a decadal-to-century timescale. The first chapter develops a method to assess the differential impacts of extreme weather and air pollution on respiratory and cardiovascular mortality in Santiago, Chile. The study finds that the attribution of mortality risk to these two environmental stressors is dependent on the type of information used to perform the classification (weather data or air pollution data). The second chapter determines how changes in the climate of the 21st century will affect the frequency, persistence, and character of high-risk winter weather classes in the airshed surrounding Santiago, Chile, finding that the mortality risk associated with increased occurrence of a high-pollution 'coastal low' weather pattern, is largely negated by the warming and moistening of the lower atmosphere across all weather classes. This is the first study to apply objective synoptic weather pattern classification to predict future changes in the weather patterns historically associated with elevated pollution and mortality levels. The final chapter establishes a baseline understanding of the potential biological effects of air pollution exposures in the New York City subway. While this pilot study indicates that subway workers are exposed to concentrations of particulate metals exceeding those aboveground by almost two orders of magnitude, the results provide no compelling evidence to suggest that exposure at such levels poses a risk to the health of the population studied. The results of the subway study complement the understanding developed in the first and second chapters of the health risks of air pollution and extreme weather in an urban environment. The findings described in this dissertation will contribute to the development of improved extreme weather and air pollution early warning systems, for example by enhancing our ability to tailor air pollution and severe weather warnings to segments of the population whose risk of death is elevated based on pre-existing disease status. Successful applications of such forecasts can play an important role in strengthening public health systems as a first line of defense to mitigate the risks posed by global climate change