AN EVALUATION OF CLIMATE/MORTALITY RELATIONSHIPS IN LARGE U.S. CITIES
AND THE POSSIBLE IMPACTS OF A CLIMATE CHANGE
Environmental Health Perspectives (1997), 105(1):84-93.

Dr. Laurence S. Kalkstein
Center for Climatic Research
Department of Geography
University of Delaware

J. Scott Greene
Oklahoma Climatological Survey
University of Oklahoma
Norman, OK 73109





ACKNOWLEDGMENTS:
This research was primarily funded by the Climate and Policy Assessment Division, U.S. Environmental Protection Agency, on Cooperative Agreement numbers CR-817693 and CR-824404. The authors would like to thank the Agency for its continued support.

ABSTRACT
A new air mass-based synoptic procedure is used to evaluate climate/mortality relationships as they presently exist, and to estimate how a predicted global warming might alter these values. Forty-four large U.S. cities with metropolitan areas exceed ing 1,000,000 population are analyzed. Sharp increases in mortality are noted in summer for most cities in the East and Midwest when two particular air masses are present. A very warm air mass of maritime origin is most important in the eastern U.S., an d when present can increase daily mortality by as many as 30 deaths in large cities. A hot, dry air mass is important in many cities, and, although rare in the East, can increase daily mortality by up to 50 deaths. Cities in the South and Southwest show lesser weather/mortality relationships in summer. During winter, air mass-induced increases in mortality are considerably less than in summer. Although daily winter mortality is usually higher than summer, the causes of death which are responsible for most winter mortality do not vary much with temperature. Using models which estimate climate change for the years 2020 and 2050, it is estimated that summer mortality will increase dramatically and winter mortality will decrease slightly, even if people acclimatize to the increased warmth. Thus, a sizable net increase in weather-related mortality is estimated if the climate warms as the models predict.



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Synoptic Climatology Lab
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