Heat-related mortality risks in the urban Northeast under a changing climate

This project seeks to analyze current and projected future temperature-related mortality impacts across a range of climate change models and scenarios. A statistical model using Poisson regression is being developed to quantify the exposure-response relationships, linking daily temperature and death counts at the urban scale in New York, Boston, and Philadelphia; this model will be created through an analysis of historical mortality data, controlling for air quality, timetrends, seasons, and day-of-week effects. We will then apply this relationship to future projections of daily temperatures for the 2020s, 2050s and 2080s over New York, Boston, and Philadelphia to assess potential future risks under different scenarios of climate change. Percentage changes in mortality in both winter and summer are calculated relative to the minimum mortality temperature (MMT), defined as the minimum point on the curve relating mortality to daily mean temperatures. The heat- and cold-related deaths in 30 year periods centered on the 1980s, 2020s, 2050s and 2080s will estimated by integrating the results from the climate models and the empirical exposure-response relationship. We will also develop vulnerability indicators for the cities of interest, and test whether mortality impacts vary in association with these indicators.

Initial results: Preliminary results for Manhattan suggest that, over a range of models and scenarios of future greenhouse gas emissions, increases in heat-related mortality will likely outweigh reductions in cold-related mortality. Further, while the two emissions scenarios used produce similar mortality estimates through the mid-21st century, the lower-emission B1 scenario results in substantially smaller annual mortality impacts by the 2080s.

Investigators: Patrick Kinney, Mark Arend, Elisaveta Petkova, Julia Morrison, Mayu Sasaki, Radley Horton