Big data in climate change and air pollution studies

Over the next century, climate change is expected to lead to an increase in the intensity and frequency of extreme weather events such as heat waves. Climate change is also expected to impact air pollution, such as ozone and particulate matter. The public health impact of climate change is poorly understood, in part because of numerous factors exhibiting a wide range of uncertainty that underlies estimates of future health risk. To mitigate the public health consequences of climate change we need a comprehensive understanding of how changes in all of the environmental exposures will affect vulnerability in a changing climate. In this talk, I will review statistical modeling for estimating the public health impact of air pollution and extreme heat both using historical data and climate change future projections. We will link and analyze massive data sets on weather, air pollution, health, and socio-demographic characteristics that are collected at different spatial and temporal resolution.. We will also present ongoing statistical modeling approaches to address the following challenges; 1) ambient air pollution levels (e.g., ozone and particulate matter) will change in response to the altered meteorological conditions arising from climate change; and 2) the health effects of combined exposure to degraded air quality and heat could be more severe than expected based on the individual exposures (i.e., synergism).