Demographic Trends and Implications for Greenhouse Gas Emissions Brian C. O’Neill Institute for the Study of Society and Environment, National Center for Atmospheric Research (NCAR) & International Institute for Applied Systems Analysis (IIASA) GTSP Technical Review Workshop, JGCRI, College Park, Maryland 28 May 2008

Demographic Trends and Emissions Implications Population size Aging Household Size Urbanization Implications for Emissions Uncertainty, learning, and optimal emissions Aging, urbanization, and national emissions Global emissions effects?

Projecting Population Size: World UN 2006 Range Source: Lutz et al., 2008.

Projecting Population Size: World SRES Range UN 2006 Range Source: Lutz et al., 2008.

Sub-Saharan Africa UN 2006 Range Source: Lutz et al., 2008.

Eastern Europe UN 2006 Range Source: Lutz et al., 2008.

China+ UN 2006 Range Source: Lutz et al., 2008.

Population Projections Source: Oppenheimer, O’Neill, & Webster, 2008.

People Living with HIV, by Region Distribution, 2007 In 2007, an estimated 33.2 million adults and children worldwide were living with HIV. Sixty-eight percent of the world’s HIV population lives in sub-Saharan Africa. Slide from Population Reference Bureau Note: Total exceeds 100 percent due to rounding. Source: UNAIDS, AIDS Epidemic Update, December 2007.

South Africa’s Population With and Without AIDS Millions Slide from Population Reference Bureau Source: United Nations, World Population Prospects: The 2006 Revision (CD-ROM Edition—Extended Dataset), 2007.

Age Distribution of the World’s Population Population Structures by Age and Sex, 2005 Millions Less Developed Regions More Developed Regions Age 80+ 75-79 70-74 65-69 60-64 55-59 50-54 45-49 40-44 35-39 30-34 25-29 20-24 15-19 10-14 5-9 0-4 Male Female Male Female Sex and age distributions show that less developed countries have significantly younger populations than more developed countries. Almost one-third of the population in less developed countries is under age 15. In contrast, less than one-fifth of the population in more developed countries is under 15. Today there are more than 2 billion young people below age 20 in less developed regions—the age cohort that will soon become the world’s newest group of parents. Young age structures in the less developed countries are due mainly to higher levels of childbearing in recent decades. Slide from Population Reference Bureau Source: United Nations, World Population Prospects: The 2004 Revision, 2005.

China’s Age Distribution Population Structures by Age and Sex Millions 1950 2000 2050 Age Age 80+ 75-79 70-74 65-69 60-64 55-59 50-54 45-49 40-44 35-39 30-34 25-29 20-24 15-19 10-14 5-9 0-4 80+ 75-79 70-74 65-69 60-64 55-59 50-54 45-49 40-44 35-39 30-34 25-29 20-24 15-19 10-14 5-9 0-4 Male Female Male Female Male Female This figure illustrates China’s shrinking young and working-age population and growing elderly population. Dramatic fertility decline (due to the success of the “one-child” policy) and improved longevity over the past two decades are causing China’s population to age at one of the fastest rates ever recorded. China now faces the prospect of having too few children to support its rapidly aging population. Meeting the health and long-term care needs of this growing elderly population will result in soaring health care costs and fewer working-age people to share the burden. Slide from Population Reference Bureau Source: World Population Prospects: The 2004 Revision (2005).

Aging in China Percent of Elderly (65+) in China’s Population, 1950-2050 Due to vast improvements in health over the past five decades, life expectancy at birth has increased by two-thirds from 40.8 to 71.5 years between 1955 and 2005. The percent of elderly in China is projected to triple from 8 percent to 24 percent between 2006 and 2050. Because chronic health problems become more common in old age, China’s population aging has led to increases in the country’s prevalence of chronic disease and disability. Source: World Population Prospects: The 2004 Revision (2005).

Ageing: Likelihood of 1/3 population 60+ Source: Lutz, Sanderson & Scherbov, 2008.

Projected Aging, Western Europe Source: Lutz, Sanderson & Scherbov, 2008.

Speed of Population Aging in Selected Countries Number of Years for Percent of Population Age 65 or Older to Rise from 7% to 14% More developed countries Less developed countries Aging has proceeded more gradually in more developed countries than in less developed countries, affording these nations time to adjust to this structural change. Japan is the major exception, doubling its percent of population age 65 or older in just 26 years. Other countries in East and Southeast Asia (especially China, South Korea, Taiwan, and Thailand) are on a similarly rapid trajectory, fueled by dramatic and relatively recent drops in fertility. * Dates show the span of years when percent of population age 65 or older rose (or is projected to rise) from 7 percent to 14 percent. Source: K. Kinsella and Y.J. Gist, Older Workers, Retirement, and Pensions: A Comparative International Chartbook (1995) and K. Kinsella and D. Phillips, “The Challenge of Global Aging,” Population Bulletin 60, no. 1 (2005).

Alternative measures of aging, U.S. Source: Sanderson & Scherbov, 2005.

Alternative measures of aging, World Source: Lutz, Sanderson & Scherbov, 2008.

Urbanization, Global Urban Rural Source: UN, 2007.

Urbanization, Industrialized & Developing Rural LDCs MDCs Source: UN, 2007.

Inverting UN Urbanization Projections Source: O’Neill and Scherbov, 2007.

Inverting UN Urbanization Projections Source: O’Neill and Scherbov, 2007.

Trends Summary Divergent trends in population size Globally, less growth than previously expected Aging everywhere, older in industrialized countries, faster in developing countries Declines in household size in developing countries, trends unclear in industrialized countries Urbanization in developing countries, projections not well developed

Implications for Emissions Uncertainty and learning Aging, urbanization, and national emissions Toward global emissions implications

Population Learning: An Example Source: O’Neill & Sanderson, 2008.

Managing Uncertainty: Preparing to Respond to New Information Optimal emissions for stabilization at 600 ppm Learning about outlook for future population growth occurs in 2020 Potential for outlook to shift to faster or slower population growth modeled using probabilistic projections After 2020, substantial adjustments made to optimal emissions strategy depending on what is learned Red lines: Learn in 2020 Emissions (GtC/yr) Blue line: Total uncertainty (no learning) Source: O’Neill & Sanderson, 2008.

Population and Emissions: The PET Model Households Consumption & Savings Capital & Labor Final Goods Producers Consumption Investment Government Exports & Imports Intermediate goods producers Oil&Gas Coal Electricity Refined Petroleum Materials Labor Capital Final Goods Energy CO2 Emissions Source: Dalton et al., 2008; Dalton & Goulder, 1998.

Labor Income Heterogeneity, China, 2000 Source: Dalton et al., 2008.

Expenditure Heterogeneity, China, 2000 Source: Dalton et al., 2008.

Effects of Aging and Urbanization on Chinese CO2 Emissions, B2 Scenario No demography Urb. + Aging + Size Aging Aging + size Urbanization effect on emissions Source: Dalton et al., 2008.

Effects of Aging and Urbanization on Indian CO2 Emissions, B2 Scenario No demography Urb. + Aging Aging Urbanization effect on emissions Source: Dalton et al., 2008.

Effects of Aging on U.S. CO2 Emissions in 2100

Effects of Aging and HH Size Changes on U.S. CO2 Emissions in 2100

iPETS: Global, regionally disaggregated IA Model (Integrated Population-Economy-Technology-Science Model) PET Population Households Producers Labor, Land, Capital Food and other goods Terrestrial Ecosystems Ocean, Sea ice, Atmosphere LU Emissions CO2 and Climate Energy Emissions Fertilizer use Demand for Land Supply of Land ISAM Collaborators: O’Neill (NCAR); Dalton (NOAA); Jain (U. Illinois); Jiang (Brown U.); Pachauri/Fuchs/Zigova (IIASA)