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Environmental Factor

May 2011

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Economist models effects of global climate change

By Melissa Kerr
May 2011

Olivier Deschenes, Ph. D.

Deschenes teaches courses at UCSB on econometrics and climate change in terms of economics and policy. (Photo courtesy of Steve McCaw)

Caroline Dilworth, Ph.D.

Dilworth administers the NIEHS grant to Deschenes, "Using Medication Purchases to Measure the Health Consequences of Air Pollution." (Photo courtesy of Steve McCaw)

John Balbus, M.D.

NIEHS Senior Advisor John Balbus, M.D., was in the audience at Deschenes' talk. The presentation inspired several questions from Balbus about the models and the results. (Photo courtesy of Steve McCaw)

As the earth's temperature continues to rise, scientists are racing to understand how the change can affect human health. NIEHS grantee( Olivier Deschenes, Ph.D., spoke at NIEHS April 7 as part of the Keystone Science Lecture Seminar Series, to discuss his research on this topic. He presented "Health Impacts of Climate Change: Evidence from India and the United States," during a talk hosted by NIEHS Health Scientist Administrator Caroline Dilworth, Ph.D.

Deschenes( Exit NIEHS is an associate professor in the Department of Economics at the University of California, Santa Barbara (UCSB), as well as a research associate with the National Bureau of Economic Research. One of his primary areas of interest ( Exit NIEHS is environmental and resource economics.

Climate change modeling

Deschenes used the Community Climate System Model (CCSM) and the Hadley Centre for Climate Prediction and Research ocean-atmosphere general circulation model version 3 (HadCM3) to help predict how rising temperatures might affect the general population in coming decades. The CCSM is a four-component framework for building and testing various climate models and is maintained by the National Center for Atmospheric Research to analyze past, present, and future global climate data.

The HadleyCM3 model is the most recent climate model in use at the Hadley Center, which is part of the British Atmospheric Data Centre (BADC). The BADC provides atmospheric data for scientists and researchers. HadleyCM3 was one of the major models used in the Intergovernmental Panel on Climate Change Third Assessment Report in 2001.

As Deschenes explained, the human body's threshold in relation to air temperature is a per day mean of around 90 degrees Fahrenheit (F). When the body experiences the added stress of extreme temperature regulation, there are also additional demands on the cardiovascular and respiratory systems. 

Number of extreme weather events to rise

"Historically, the average person in the U.S. is exposed to one day a year where the mean temperature exceeds 90 degrees F," Deschenes explained. Using the climate change models, it is predicted that by the end of the century, the average person will be subject to about 60 such days.

Even at the present time, Deschenes stressed, "The wellbeing and the health of the vast majority of the world's population are significantly affected by extreme weather events." With the added effects of climate change, the conditions could become even more potentially harmful for vulnerable populations.

Impacts of climate change on U.S. and India

Changes to the earth's climate may have dramatic effects, but how to glean information empirically was challenging. Deschenes wanted to understand the extent to which extreme temperature stress affects human health, the defensive and adaptive behaviors of individuals, the mechanisms linking physiological effect, and the implications for potential health cost. Using the available data from the U.S. and India, he was able to answer many, but not all, of these questions for both countries.

For his studies in the U.S., Deschenes used mortality rates because there was significant geographical variation and a long time series of data available. His prediction of mortality rates, in conjunction with the climate change models, produced some grim possible scenarios (see text box).

Deschenes claimed this prediction is more of a troublesome issue in India than in the U.S., because India is growing faster. "There is cause for great concern," he concluded.

(Melissa Kerr studies chemistry at North Carolina Central University. She is currently an intern in the NIEHS Office of Communications and Public Liaison.)

A tale of two countries and climate change

Deschenes' findings reflect the geographic, demographic, and economic differences between the U.S. and India and underscore the notion that climate change will have more impact on people in developing countries.

"By the end of the century, climate change will lead to 64,000 more deaths per year in the U.S.  - about a 3 percent increase compared to the average annual mortality rate," Deschenes explained.

Deschenes' research took into account the concept of adaptation through energy use, as well as other changes in health-related welfare costs. He used climate change data to estimate indirect health costs in relation to climate change. Among those costs, the data projects a 15 to 30 percent - about $15 billion to $35 billion - increase in residential energy consumption in the US. 

In India, where the population is highly dependent on agriculture, the implications of climate change have greater potential impact. The data showed an interesting distinction between rural and urban populations that was not evident in the data from the US.

"The rural population, their well being, their health, is much more exposed to temperature extremes than the urban population," Deschenes said, and it is less likely to have the means to cope as effectively with the extremes.

Compared to the single day per year exposure of someone in the US to a 90-degree day, the average in India is currently 33 days. The data projecting the effects of climate change by the end of the century forecast an increase in the mortality rate in India of 10 to 50 percent. However, Deschenes found an insignificant change among urban populations of India. Almost all of the change in data projecting to the end of the century related to rural populations.

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