Health Impacts of Climate Change Michael Greenstone 3M Professor of - - PowerPoint PPT Presentation

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Health Impacts of Climate Change Michael Greenstone 3M Professor of - - PowerPoint PPT Presentation

Health Impacts of Climate Change Michael Greenstone 3M Professor of Environmental Economics MIT February 2008 Variations in global surface temperature for the past 140 years Expected impact on global climate Change in global surface


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Health Impacts of Climate Change

Michael Greenstone 3M Professor of Environmental Economics MIT February 2008

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Variations in global surface temperature for the past 140 years

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Expected impact on global climate

  • Change in global surface

temperature

  • Change in global mean sea

level

Source: Hadley Centre (UK) Model 3 – A1F1

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SLIDE 4

Expected impact on U.S. climate

50 52 54 56 58 60 62 64 2000 2020 2040 2060 2080 2100 2120 Year Average Daily Mean Temperature (Annual)

  • Poly. (Average Daily Mean Temperature (Annual))

Source: Author’s Calculations From National Center for Atmospheric Research, Community Climate System Model (CCSM) 3 A2

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Distribution of Annual Daily Mean Temperatures (F), 1968-2002

10 20 30 40

<0 0-5 5-10 10-15 15-20 20-25 25-30 30-35 35-40 40-45 45-50 50-55 55-60 60-65 65-70 70-75 75-80 80-85 85-90 >90

Daily Mean Temperatures

Days Per Year Note: Population-weighted average over all counties

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Changes in Distribution of Daily Temperatures Under Hadley 3 A1FI and CCSM 3, A2

  • 20
  • 10

10 20 30 40 50 <0 0-5 5- 10 10- 15 15- 20 20- 25 25- 30 30- 35 35- 40 40- 45 45- 50 50- 55 55- 60 60- 65 65- 70 70- 75 75- 80 80- 85 85- 90 >90

Change in Distribution of Annual Daily Mean Temperatures (F)

CCSM 3, A2 Scenario Hadley 3, A1F1 Scenario

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Estimated Response Function Between Daily Temperature and Mortality: Females

  • 0.4
  • 0.2

0.0 0.2 0.4 0.6 0.8 1.0

<0 0-5 5-10 10-15 15-20 20-25 25-30 30-35 35-40 40-45 45-50 50-55 55-60 60-65 65-70 70-75 75-80 80-85 85-90 >90

Impact of a Day in 20 Daily Mean Temperature (F) Bins on Annual Female Mortality Rate, Relative to a Day in the 65° - 70° F Bin Annual Deaths Per 100,000

  • Poly. (Annual Deaths Per 100,000)

Note: Population-weighted sum of age-specific response functions

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Predicted change in annual female and male mortality

  • 4,000
  • 2,000

2,000 4,000 6,000 8,000

<0 0-5 5-10 10-15 15-20 20-25 25-30 30-35 35-40 40-45 45-50 50-55 55-60 60-65 65-70 70-75 75-80 80-85 85-90 >90

Daily Mean Temperature (F) Change in Annual Male Mortality Change in Annual Female Mortality

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Estimated Response Function Between Daily Temperature and Residential Energy Consumption

  • 0.05

0.00 0.05 0.10 0.15 0.20 0.25

<0 0-5 5-10 10-15 15-20 20-25 25-30 30-35 35-40 40-45 45-50 50-55 55-60 60-65 65-70 70-75 75-80 80-85 85-90 >90

Impact of a Day in 20 Daily Mean Temperature (F) Bins on Annual Residential Energy Consumption, Relative to a Day in the 65° - 70° F Bin Quadrillions of BTUs

  • Poly. (Quadrillions of BTUs)
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Predicted change in annual residential energy consumption

  • 1.0

0.0 1.0 2.0 3.0 4.0 5.0

<0 0-5 5-10 10-15 15-20 20-25 25-30 30-35 35-40 40-45 45-50 50-55 55-60 60-65 65-70 70-75 75-80 80-85 85-90 >90

Daily Mean Temperature (F) Quad BTU

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Conclusions

  • 1. Under “Business as Usual”, the World Will

Become Much Hotter

  • 2. Health Impacts in US Likely to be Small Due

to Adaptation/Self-Protection (Energy Consumption)

  • 3. Mortality Impacts Substantial in India (and

Probably Other Developing Countries)