Analyses of the Effects of Global Change on 

Human Health and Welfare and Human Systems 

Final Report, Synthesis and Assessment Product 4.6 

U.S. Climate Change Science Program 

And the Subcommittee on Global Change Research 

Convening Lead Author 

Janet L. Gamble, Ph.D., U.S. Environmental Protection Agency 

Lead Authors 1

Kristie L. Ebi, Ph.D., ESS LLC. 

Anne E. Grambsch, U.S. Environmental Protection Agency 

Frances G. Sussman, Ph.D., Environmental Economics Consulting 

Thomas J. Wilbanks, Ph.D., Oak Ridge National Laboratory 

 

1

 Contributing authors are acknowledged in individual chapters. 
SAP 4.6 Analysis of the Effects of Global Change on Human Health and Welfare and Human Systems

FEDERAL EXECUTIVE TEAM 

Acting Director, Climate Change Science Program: William J. Brennan 

Director, Climate Change Science Program Office: Peter A. Schultz 

Lead Agency Principal Representative to CCSP, 

National Program Director for the Global Change 

Research Program, U.S. Environmental Protection Agency: Joel D. Scheraga 

Product Lead, Global Change Research 

Program, U.S. Environmental Protection Agency: Janet L. Gamble 

Chair, Synthesis and Assessment Product Advisory Group 

Associate Director, National Center for Environmental 

Assessment, U.S. Environmental Protection Agency: Michael W. Slimak 

Synthesis and Assessment Product Coordinator, 

Climate Change Science Program Office: Fabien J.G. Laurier 

Special Advisor, National Oceanic and Atmospheric 

Administration Chad A.McNutt 

EDITORIAL AND PRODUCTION TEAM 

Editor, U.S. Environmental Protection Agency: Janet Gamble 

Technical Editor, ICF International: Melinda Harris 

Technical Editor, ICF International: Toby Krasney 

Reference Coordinator, ICF International: Paul Stewart 

Reference Coordinator, ICF International: Dylan Harrison-Atlas 

Reference Coordinator, ICF International: Sarah Shapiro 

Logistical and Technical Support, ICF International: Lauren Smith

ii 
SAP 4.6 Analysis of the Effects of Global Change on Human Health and Welfare and Human Systems

Disclaimer: This document, part of the Synthesis and Assessment Products described in the U.S. Climate Change Science 

Program (CCSP) Strategic Plan, was prepared in accordance with Section 515 of the Treasury and General Government 

Appropriations Act for Fiscal Year 2001 (Public Law 106-554) and the information quality act guidelines issued by the 

U.S. Environmental Protection Agency pursuant to Section 515. The CCSP Interagency Committee relies on U.S. 

Environmental Protection Agency certifications regarding compliance with Section 515 and Agency guidelines as the basis 

for determining that this product conforms with Section 515. For purposes of compliance with Section 515, this CCSP 

Synthesis and Assessment Product is an “interpreted product” as that term is used in U.S. Environmental Protection 

Agency guidelines and is classified as “highly influential”. This document does not express any regulatory policies of the 

United States or any of its agencies, or provides recommendations for regulatory action. 

iii 
July 2008 

Members of Congress: 

On behalf of the National Science and Technology Council, the U.S. Climate Change Science Program 

(CCSP) is pleased to transmit to the President and the Congress this Synthesis and Assessment Product 

(SAP), Analyses of the Effects of Global Change on Human Health and Welfare and Human Systems. 

This is part of a series of 21 SAPs produced by the CCSP aimed at providing current assessments of 

climate change science to inform public debate, policy, and operational decisions. These SAPs are also 

intended to help the CCSP develop future program research priorities. This SAP is issued pursuant to 

Section 106 of the Global Change Research Act of 1990 (Public Law 101-606). 

The CCSP’s guiding vision is to provide the Nation and the global community with the science-based 

knowledge needed to manage the risks and capture the opportunities associated with climate and related 

environmental changes. The SAPs are important steps toward achieving that vision and help to translate 

the CCSP’s extensive observational and research database into informational tools that directly address 

key questions being asked of the research community. 

This SAP focuses on the effects of global change on human health and welfare and human systems. It 

was developed with broad scientific input and in accordance with the Guidelines for Producing CCSP 

SAPs, the Federal Advisory Committee Act, the Information Quality Act, Section 515 of the Treasury 

and General Government Appropriations Act for fiscal year 2001 (Public Law 106-554), and the 

guidelines issued by the Environmental Protection Agency pursuant to Section 515. 

We commend the report’s authors for both the thorough nature of their work and their adherence to an 

inclusive review process. 

 Sincerely, 

Carlos M. Gutierrez Samuel W. Bodman John H. Marburger III 

Secretary of Commerce Secretary of Energy Director, Office of Science 

and Technology Policy 

Chair, Committee on Vice Chair, Committee on Executive Director, Committee 

Climate Change Science Climate Change Science on Climate Change Science and 

and Technology Integration and Technology Integration Technology Integration 

iv 
SAP 4.6 Analysis of the Effects of Global Change on Human Health and Welfare and Human Systems

AUTHORS TEAM FOR THIS REPORT 

Executive Summary Convening Lead Author: Janet L. Gamble, U.S. EPA 

Lead Authors: Kristie L. Ebi, ESS LLC.; Frances G. Sussman, 

Environmental Economics Consulting; Thomas J. Wilbanks, Oak 

Ridge National Laboratory 

Contributing Authors: Colleen Reid, ASPH Fellow; John V. 

Thomas, U.S. EPA; Christopher P. Weaver, U.S. EPA; Melinda 

Harris, ICF International; Randy Freed, ICF International 

Chapter 1 Convening Lead Author: Janet L. Gamble, U.S. EPA 

Lead Authors: Kristie L. Ebi, ESS LLC.; Anne Grambsch, U.S. 

EPA; Frances G. Sussman, Environmental Economics Consulting; 

Thomas J. Wilbanks, Oak Ridge National Laboratory 

Contributing Authors: Colleen E. Reid, ASPH Fellow; Katharine 

Hayhoe, Texas Tech University; John V. Thomas, U.S. EPA; 

Christopher P. Weaver, U.S. EPA 

Chapter 2 Lead Author: Kristie L. Ebi, ESS LLC.

Contributing Authors: John Balbus, Environmental Defense; 

Patrick L. Kinney, Columbia University; Erin Lipp, University of 

Georgia; David Mills, Stratus Consulting; Marie S. O’Neill, 

University of Michigan; Mark Wilson, University of Michigan 

Chapter 3 Lead Author: Thomas J. Wilbanks, Oak Ridge National 

Laboratory 

Contributing Authors: Paul Kirshen, Tufts University; Dale 

Quattrochi, NASA/Marshall Space Flight Center; Patricia RomeroLankao, NCAR; Cynthia Rosenzweig, NASA/Goddard; Matthias 

Ruth, University of Maryland; William Solecki, Hunter College; 

Joel Tarr, Carnegie Mellon University 

Contributors: Peter Larsen, University of Alaska-Anchorage; 

Brian Stone, Georgia Tech 

Chapter 4 Lead Author: Frances G. Sussman, Environmental Economics 

Consulting 

Contributing Authors: Maureen L. Cropper, University of 

Maryland at College Park; Hector Galbraith, Galbraith 

Environmental Sciences LLC.; David Godschalk, University of 

North Carolina at Chapel Hill; John Loomis, Colorado State 

University; George Luber, Centers for Disease Control and 

Prevention; Michael McGeehin, Centers for Disease Control and 

Prevention; James E. Neumann, Industrial Economics, Inc.; W. 

Douglass Shaw, Texas A&M University; Arnold Vedlitz, Texas 

A&M University; Sammy Zahran, Colorado State University 

Chapter 5 Convening Lead Author: Janet L. Gamble, U.S. EPA 

Lead Authors: Kristie L. Ebi, ESS LLC.; Frances G. Sussman, 

Environmental Economics Consulting; Thomas J. Wilbanks, Oak 

Ridge National Laboratory 

Contributing Authors: Colleen E. Reid, ASPH Fellow; John V. 

Thomas, U.S. EPA; Christopher P. Weaver, U.S. EPA

v 
SAP 4.6 Analysis of the Effects of Global Change on Human Health and Welfare and Human Systems

ACKNOWLEDGMENTS 

This report has been peer reviewed in draft form by individuals identified for their diverse 

perspectives and technical expertise. The expert review and selection of reviewers followed the 

OMB’s Information Quality Bulletin for Peer Review. The purpose of this independent review 

is to provide candid and critical comments that will assist the Climate Change Science Program 

in making this published report as sound as possible and to ensure that the report meets 

institutional standards. The peer review comments, draft manuscript and response to the peer 

review comments are publicly available at: www.climatescience.gov/Library/sap/sap4-

6/default.php. 

Environmental Protection Agency Internal Reviewers 

We wish to thank the following individuals from the U.S. Environmental Protection Agency for 

their review of the first, and in some case later, draft(s) of the report. Reviewers from within 

EPA, included: 

 Lisa Conner Adam Daigneault Benjamin De Angelo 

 Barbara Glenn Doug Grano Matthew Heberling 

 Ju-Chin Huang Stephen Newbold Jason Samenow 

 Sara Terry 

National Center for Environmental Assessment, Global Change Research Program 

We extend our thanks to our colleagues in the Global Change Research Program who contributed 

thoughtful insights, reviewed numerous drafts, and helped with the production of the report. 

 John Thomas Christopher Weaver 

Federal Agency Reviewers 

Likewise, we thank the reviewers from within the federal “family.” Reviewers from across the 

federal agencies provided their comments during the public comment period. 

 Brigid DeCoursey Department of Transportation 

 Mary Gant National Institutes of Environmental Health Sciences / NIH 

Indur M. Goklany Department of Interior 

 Charlotte Skidmore Office of Management and Budget 

 Samuel P. Williamson Office of the Federal Coordinator for Meteorology 

Public Reviewers 

We also extend our thanks to the reviewers who provided their comments during the public 

comment period, included individuals from the public. 

 William Fang Edison Electric Institute 

vi 
SAP 4.6 Analysis of the Effects of Global Change on Human Health and Welfare and Human Systems

 Katherine Farrell AACDH 

 Hans Martin Fuessel PICIR 

 Eric Holdsworth Edison Electric Institute 

 John Kinsman Edison Electric Institute 

 Kim Knowlton Natural Resources Defense Council 

 Sabrina McCormick Michigan State University 

 J. Alan Roberson American Water Works Association 

 Gina Solomon Natural Resources Defense Council 

Human Impacts of Climate Change Advisory Committee (HICCAC) 

Finally, we are indebted to the thoughtful review provided by a Federal Advisory Committee 

convened by the U.S. Environmental Protection Agency to provide an independent expert review 

of the SAP 4.6. The panel (the Human Impacts of Climate Change Advisory Committee) met in 

October 2007 to discuss their findings and recommendations for the report. Following extensive 

revisions to the report, the HICCAC reconvened by teleconference in January 2008 to review the 

authors’ response to comments. The panel’s review of the report has contributed to a markedly 

improved document. 

Chair Tom Dietz Michigan State University 

Co-chair Barbara Entwisle University of North Carolina 

Members Howard Frumkin Centers for Disease Control and Prevention 

 Peter Gleick Pacific Institute 

 Jonathan Patz University of Wisconsin 

 Roger Pulwarty NOAA 

 Eugene Rosa Washington State University 

 Susan Stonich University of California at Santa Barbara 

Thanks are also in order to Joanna Foellmer, the Designated Federal Official from within the 

National Center for Environmental Assessment (NCEA) who organized and managed the 

HICCAC. 

ICF International 

We thank our colleagues at ICF International for their support—logistical and technical—in 

preparing the report. We wish to extend special thanks to Melinda Harris and Randy Freed. 

Summary 

It has been an honor and a pleasure to work with all of the people named above as well as the 

many colleagues we have encountered in the process of preparing this report. We hope that this 

document will be a positive step forward in our efforts to assess the impacts of climate change on 

human systems and to evaluate opportunities for adaptation. 

vii 
SAP 4.6 Analysis of the Effects of Global Change on Human Health and Welfare and Human Systems

RECOMMENDED CITATIONS

Note: The page numbers included below are 

specific to the pre-layout draft of the report. 

These page numbers will change in the final 

printed version. 

For the Report as a Whole:

CCSP, 2008: Analyses of the effects of global 

change on human health and welfare and 

human systems. A Report by the U.S. Climate 

Change Science Program and the 

Subcommittee on Global Change Research. 

[Gamble, J.L. (ed.), K.L. Ebi, F.G. Sussman, 

T.J. Wilbanks, (Authors)]. U.S. 

Environmental Protection Agency, 

Washington, DC, USA. 

For Executive Summary: 

Gamble, J.L., K.L. Ebi, F.G. Sussman, T.J. 

Wilbanks, C. Reid, J.V. Thomas, C.P. 

Weaver, M. Harris, and R. Freed, 2008: 

Executive Summary. In: Analyses of the 

effects of global change on human health and 

welfare and human systems. A Report by the 

U.S. Climate Change Science Program and the 

Subcommittee on Global Change Research. 

[Gamble, J.L. (ed.), K.L. Ebi, F.G. Sussman, 

T.J. Wilbanks, (Authors)]. U.S. 

Environmental Protection Agency, 

Washington, DC, USA, p. ES-1 to ES-14. 

For Chapter 1: 

Gamble, J.L., K.L. Ebi, A. Grambsch, F.G. 

Sussman, T.J. Wilbanks, C.E. Reid, K. 

Hayhoe, J.V. Thomas, and C.P. Weaver, 2008: 

Introduction. In: Analyses of the effects of 

global change on human health and welfare 

and human systems. A Report by the U.S. 

Climate Change Science Program and the 

Subcommittee on Global Change Research. 

[Gamble, J.L. (ed.), K.L. Ebi, F.G. Sussman, 

T.J. Wilbanks, (Authors)]. U.S. 

Environmental Protection Agency, 

Washington, DC, USA, p. 1-1 to 1-41. 

For Chapter 2: 

Ebi, K.L., J. Balbus, P.L. Kinney, E. Lipp, D. 

Mills, M.S. O’Neill, and M. Wilson, 2008: 

Effects of Global Change on Human Health. 

In: Analyses of the effects of global change on 

human health and welfare and human systems. 

A Report by the U.S. Climate Change Science 

Program and the Subcommittee on Global 

Change Research. [Gamble, J.L. (ed.), K.L. 

Ebi, F.G. Sussman, T.J. Wilbanks, (Authors)]. 

U.S. Environmental Protection Agency, 

Washington, DC, USA, p. 2-1 to 2-78. 

For Chapter 3: 

Wilbanks, T.J., P. Kirshen, D. Quattrochi, P. 

Romero-Lankao, C. Rosenzweig, M. Ruth, W. 

Solecki, and J. Tarr, 2008: Effects of Global 

Change on Human Settlements. In: Analyses 

of the effects of global change on human 

health and welfare and human systems. A 

Report by the U.S. Climate Change Science 

Program and the Subcommittee on Global 

Change Research. [Gamble, J.L. (ed.), K.L. 

Ebi, F.G. Sussman, T.J. Wilbanks, (Authors)]. 

U.S. Environmental Protection Agency, 

Washington, DC, USA, p. 3-1 to 3-31. 

For Chapter 4: 

Sussman, F.G., M.L. Cropper, H. Galbraith, 

D. Godschalk, J. Loomis, G. Luber, M. 

McGeehin, J.E. Neumann, W.D. Shaw, A. 

Vedlitz, and S. Zahran, 2008: Effects of 

Global Change on Human Welfare. In: 

Analyses of the effects of global change on 

human health and welfare and human systems. 

A Report by the U.S. Climate Change Science 

Program and the Subcommittee on Global 

Change Research. [Gamble, J.L. (ed.), K.L. 

Ebi, F.G. Sussman, T.J. Wilbanks, (Authors)]. 

U.S. Environmental Protection Agency, 

Washington, DC, USA, p. 4-1 to 4-74. 

viii 
SAP 4.6 Analysis of the Effects of Global Change on Human Health and Welfare and Human Systems

For Chapter 5: Gamble, J.L., K.L. Ebi, F.G. 

Sussman, T.J. Wilbanks, C. Reid, J.V. 

Thomas, and C.P. Weaver, 2008: Common 

Themes and Research Recommendations. In: 

Analyses of the effects of global change on 

human health and welfare and human systems. 

A Report by the U.S. Climate Change Science 

Program and the Subcommittee on Global 

Change Research. [Gamble, J.L. (ed.), K.L. 

Ebi, F.G. Sussman, T.J. Wilbanks, (Authors)]. 

U.S. Environmental Protection Agency, 

Washington, DC, USA, p. 5-1 to 5-11. 

ix 
SAP 4.6 Analysis of the Effects of Global Change on Human Health and Welfare and Human Systems

TABLE OF CONTENTS 

Executive Summary 

Abstract ES-3 

ES.1 Climate Change and Vulnerability ES-3 

ES.2 Climate Change and Human Health ES-5 

ES.3 Climate Change and Human Settlements ES-7 

ES.4 Climate Change and Human Welfare ES-9 

ES.5 Tables ES-11 

1. Introduction 

1.1 Scope and Approach of the SAP 4.6 1-3 

1.2 Climate Change in the United States: Context for an Assessment of Impacts on Human 

Systems 1-7 

1.2.1 Rising temperatures 1-8 

1.2.2 Trends in precipitation 1-9 

1.2.3 Rising sea levels and erosion of coastal zones 1-10 

1.2.4 Changes in Extreme Conditions 1-11 

1.3 Population Trends and Migration Patterns: A Context for Assessing Climate-related Impacts 

1-14 

1.3.1 Trends in total U.S. Population 1-14 

1.3.2 Migration patterns 1-15 

1.4 Complex Linkages: The Role of Non-climate Factors 1-17 

1.4.1 Economic status 1-18 

1.4.2 Technology 1-18 

1.4.3 Infrastructure 1-19 

1.4.4 Human and Social Capital and Behaviors 1-20 

1.4.5 Institutions 1-20 

1.4.6 Interacting effects 1-21 

1.5 Reporting Uncertainty in SAP 4.6 1-22 

1.6 References 1-24 

1.7 Tables 1-36 

1.8 Figures 1-37 

2. Human Health 

2.1 Introduction 2-3 

2.2 Observed Climate-Sensitive Health Outcomes in the United States 2-4 

2.2.1 Thermal Extremes: Heat Waves 2-4 

2.2.2 Thermal Extremes: Cold Waves 2-6 

2.2.3 Extreme Events: Hurricanes, Floods, and Wildfires 2-6 

2.2.4 Indirect Health Impacts of Climate Change 2-8 

2.3 Projected Health Impacts of Climate Change in the United States 2-15 

2.3.1 Heat-Related Mortality 2-15 

2.3.2 Hurricanes, Floods, Wildfires and Health Impacts 2-17 

2.3.3 Vectorborne and Zoonotic Diseases 2-18 

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SAP 4.6 Analysis of the Effects of Global Change on Human Health and Welfare and Human Systems

2.3.4 Water- and Foodborne Diseases 2-18 

2.3.5 Air Quality Morbidity and Mortality 2-19 

2.4 Vulnerable Regions and Subpopulations 2-22 

2.4.1 Vulnerable Regions 2-23 

2.4.2 Specific Subpopulations at Risk 2-23 

2.5 Adaptation 2-26 

2.5.1 Actors and Their Roles and Responsibilities for Adaptation 2-27 

2.5.2 Adaptation Measures to Manage Climate Change-Related Health Risks 2-29 

2.6 Conclusions 2-29 

2.7 Expanding the Knowledge Base 2-30 

2.8 References 2-32 

2.9 Boxes 2-57 

2.10 Tables 2-61 

2.11 Figures 2-72 

3. Human Settlements 

3.1 Introduction 3-3 

3.1.1 Purpose 3-3 

3.1.2 Background 3-3 

3.1.3 Current State of Knowledge 3-4 

3.2 Climate Change Impacts and the Vulnerabilities of Human Settlements 3-4 

3.2.1 Determinants of Vulnerability 3-4 

3.2.2 Impacts of Climate Change on Human Settlements 3-5 

3.2.3 The Interaction of Climate Impacts with Non-Climate Factors 3-7 

3.2.4 Realizing Opportunities from Climate Change in the United States 3-9 

3.2.5 Examples of Impacts on Metropolitan Areas in the United States 3-10 

3.3 Opportunities for Adaptation of Human Settlements to Climate Change 3-10 

3.3.1 Perspectives on Adaptation by Settlements 3-11 

3.3.2 Major Categories of Adaptation Strategies 3-12 

3.3.3 Examples of Current Adaptation Strategies 3-13 

3.3.4 Strategies to Enhance Adaptive Capacity 3-14 

3.4 Conclusions 3-14 

3.5 Expanding the Knowledge Base 3-15 

3.6 References 3-17 

3.7 Boxes 3-24 

3.8 Tables 3-29 

3.9 Figures 3-31 

4. Human Welfare 

4.1 Introduction 4-3 

4.2 Human Welfare, Well-being, and Quality of Life 4-4 

4.2.1 Individual Measures of Well-being 4-5 

4.2.2 The Social Indicators Approach 4-6 

4.2.3 A Closer Look at Communities 4-10 

4.2.4 Vulnerable Populations, Communities, and Adaptation 4-12 

4.3 An Economic Approach to Human Welfare 4-13 

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SAP 4.6 Analysis of the Effects of Global Change on Human Health and Welfare and Human Systems

4.3.1 Economic Valuation 4-15 

4.3.2 Impacts Assessment and Monetary Valuation 4-16 

4.3.3 Human Health 4-17 

4.3.4 Ecosystems 4-22 

4.3.5 Recreational Activities and Opportunities 4-28 

4.3.6 Amenity Value of Climate 4-35 

4.4 Conclusions 4-38 

4.5 Expanding the Knowledge Base 4-39 

4.6 References 4-41 

4.7 Appendix 1 4-57 

4.8 Boxes 4-64 

4.9 Tables 4-66 

4.10 Figures 4-72 

5. Research 

5.1 Synthesis and Assessment Product 4.6: Advances in the Science 5-3 

5.1.1 Complex Linkages and a Cascading Chain of Impacts Across Global Changes 5-3 

5.1.2 Changes in Climate Extremes and Climate Averages 5-4 

5.1.3 Vulnerable Populations and Vulnerable Locations 5-5 

5.1.4 The Cost of and Capacity for Adaptation 5-6 

5.1.5 An Integrative Framework 5-6 

5.2 Expanding the Knowledge Base 5-7 

5.2.1 Human Health Research Gaps 5-9 

5.2.2 Human Settlements Research Gaps 5-10 

5.2.3 Human Welfare Research Gaps 5-10 

6. Glossary and Acronyms 

xii 
Synthesis and Assessment Product 4.6 

Analyses of the Effects of Global Change on Human 

Health and Welfare and Human Systems 

Executive Summary 

Convening Lead Author: Janet L. Gamble, U.S. Environmental Protection Agency

Lead Authors: Kristie L. Ebi, ESS, LLC; Frances G. Sussman, Environmental Economics Consulting; 

Thomas J. Wilbanks, Oak Ridge National Laboratory 

Contributing Authors: Colleen Reid, ASPH Fellow; John V. Thomas, U.S. Environmental Protection 

Agency; Christopher P. Weaver, U.S. Environmental Protection Agency; Melinda Harris, ICF International; 

Randy Freed, ICF International 

ES-1 
SAP 4.6 Executive Summary 

Table of Contents 

Abstract .......................................................................................................................................................... 3

ES.1 Climate Change and Vulnerability ..................................................................................................... 3

ES.2 Climate Change and Human Health................................................................................................... 5

ES.3 Climate Change and Human Settlements........................................................................................... 7

ES.4 Climate Change and Human Welfare................................................................................................. 9

ES.5 Tables................................................................................................................................................... 11

ES-2 
Abstract 

Climate change, interacting with changes in land use and demographics, will affect 

important human dimensions in the United States, especially those related to human 

health, settlements and welfare. The challenges presented by population growth, an aging 

population, migration patterns, and urban and coastal development will be affected by 

changes in temperature, precipitation, and extreme climate-related events. In the future, 

with continued global warming, heat waves and heavy downpours are very likely to 

further increase in frequency and intensity. Cold days and cold nights are very likely to 

become much less frequent over North America. Substantial areas of North America are 

likely to have more frequent droughts of greater severity. Hurricane wind speeds, rainfall 

intensity, and storm surge levels are likely to increase. Other changes include measurable 

sea-level rise and increases in the occurrence of coastal and riverine flooding. The United 

States is certainly capable of adapting to the collective impacts of climate change. 

However, there will still be certain individuals and locations where the adaptive capacity 

is less and these individuals and their communities will be disproportionally impacted by 

climate change. 

This report – the Synthesis and Assessment Product 4.6 (SAP 4.6) – focuses on impacts 

of global climate change, especially impacts on three broad dimensions of the human 

condition: human health, human settlements, and human welfare. The SAP 4.6 has been 

prepared by a team of experts from academia, government, and the private sector in 

response to the mandate of the U.S. Climate Change Science Program’s Strategic Plan 

(2003). The assessment examines potential impacts of climate change on human society, 

opportunities for adaptation, and associated recommendations for addressing data gaps 

and near- and long-term research goals. 

ES.1 Climate Change and Vulnerability 

Climate variability and change challenge even the world’s most advanced societies. At a 

very basic level, climate affects the costs of providing comfort in our homes and work 

places. A favorable climate can provide inputs for a good life: adequate fresh water 

supplies; products from the ranch, the farm, the forests, the rivers and the coasts; pleasure 

derived from tourist destinations and from nature, biodiversity, and outdoor recreation. 

Climate not only supports the provision of many goods and services, but also affects the 

spread of some diseases and the prevalence of other health problems. It is also associated 

with threats from extreme events and natural disasters such as tropical storms, riverine 

and coastal flooding, wildfires, droughts, wind, hail, ice, heat, and cold. 

This report examines the impacts on human society of global change, especially those 

associated with climate change. The impact assessments in this report do not rely on 

specific emissions or climate change scenarios but, instead, rely on the existing scientific 

literature with respect to our understanding of climate change and its impacts on human 

health, settlements and human well-being in the United States. Because climate change 

forecasts are generally not specific enough for the scale of local decision-making, this 

report adopts a vulnerability perspective in assessing impacts on human society. 

ES-3 
SAP 4.6 Executive Summary 

A vulnerability approach focuses on estimating risks or opportunities associated with 

possible impacts of climate change, rather than on estimating (quantitatively) the impacts 

themselves which would require far more detailed information about future conditions. 

Vulnerabilities are shaped not only by existing exposures, sensitivities, and adaptive 

capacities but also by responses to risks. For example, Boston is generally more 

vulnerable to heat waves than Dallas because there are fewer air-conditioned homes in 

Boston than in Dallas. At the same time, human responses (e.g., the elderly not using airconditioning) also are an important determinant of impacts. This leads to our conclusion 

that climate change will result in regional differences in impacts in the United States not 

only due to a regional pattern of changes in climate but the regional nature of our 

communities in adapting to these changes. 

In the United States, we are observing the evidence of long-term changes in temperature 

and precipitation consistent with global warming. Changes in average conditions are 

being realized through rising temperatures, changes in annual and seasonal precipitation, 

and rising sea levels. Observations also indicate there are changes in extreme conditions, 

such as an increased frequency of heavy rainfall (with some increase in flooding), more 

heat waves, fewer very cold days, and an increase in areas affected by drought. There 

have been large fluctuations in the number of hurricanes from year to year which make it 

difficult to discern trends. Evidence suggests that the intensity of Atlantic hurricanes and 

tropical storms has increased over the past few decades. However, changes in frequency 

are currently too uncertain for confident projection. 

Changes in the size of the population, including especially sensitive sub-populations, and 

their geographic distribution across the landscape need to be accounted for when 

assessing climate variability and change impacts. According to the Census Bureau’s 

middle series projection, the US population will increase to some 570 million people. 

Moreover, the elderly population is increasing rapidly and many health assessments 

identify them as more vulnerable than younger age groups to a range of health impacts 

associated with climate change. Although numbers produced by population projections 

are important, nearly all trends point to more Americans living in areas that may be 

especially vulnerable to the effects of climate change. For example, many rapidly 

growing places in the Mountain West may also experience decreased snow pack during 

winter and earlier spring melting, leading to lower stream flows, particularly during the 

high-demand period of summer. Similarly, coastal areas are projected to continue to 

increase in population, with associated increases in population density, over the next 

several decades. 

Climate is only one of a number of global changes that affect human well-being. These 

non-climate processes and stresses interact with climate change, determining the overall 

severity of climate impacts. Socioeconomic factors that can influence exposures, 

vulnerability and impacts include population, economic status, technology, infrastructure, 

human capital and social context and behaviors, and institutions. Trends in these factors 

alter anticipated impacts from climate because they fundamentally shape the nature and 

scope of human vulnerability. Understanding the impacts of climate change and 

ES-4 
SAP 4.6 Executive Summary 

variability on the quality of life in the United States therefore implies knowledge of how 

these factors vary by location, time, and socioeconomic group. 

Climate change will seldom be the sole or primary factor determining a population’s or a 

location’s well-being. Ongoing adaptation also can significantly influence climate 

impacts. For example, emergency warning systems have generally reduced deaths and 

death rates from extreme events, while greater access to insurance and broader, 

government-funded safety nets for people struck by natural disasters have ameliorated the 

hardships they face. While this assessment focuses on how climate change could affect 

the future health, well-being, and settlements in the United States, the extent of any 

impacts will depend on an array of non-climate factors and adaptive measures. Finally, 

the effects of climate change very often spread from directly impacted areas and sectors 

to other areas and sectors through extensive and complex linkages. In summary, the 

importance of climate change depends on the directness of the climate impact coupled 

with demographic, social, economic, institutional, and political factors, including, the 

degree of preparedness. 

Consistent with all of the Synthesis and Assessment Products being prepared by the 

CCSP, this report includes statements regarding uncertainty. Each chapter author team 

assigned likelihood judgments that reflect their assessment of the current consensus of the 

science and the quality and amount of evidence. The likelihood terminology and the 

corresponding values that are used in this report are consistent with the latest IPCC 

Fourth Assessment and are further explained in Chapter 1 of this report. As the focus of 

this report is on impacts, it is important to note that these likelihood statements refer to 

the statement of the impact, not statements related to underlying climatic changes. 

Table ES.1 provides examples of climate change impacts that are identified in the 

chapters for human health, settlements, and human welfare and includes potential 

adaptation strategies. The list of impacts is not comprehensive, but rather includes those 

that the available evidence suggests may occur. It is important to note that not all effects 

have been equally well-studied. The effects identified for welfare, in particular, should 

be taken as examples of effects about which we have some knowledge, rather than a 

complete listing of all welfare effects. 

ES.2 Climate Change and Human Health 

The United States is a highly developed country with a wide range of climates. While 

there may be fewer cases of illness and death associated with climate change in the 

United States than in the developing world, we nevertheless anticipate increased costs to 

human health and well being. Greater wealth and a more developed public health system 

and infrastructure (e.g., water treatment plants, sewers, and drinking water systems; 

roads, rails and bridges; flood control structures) will continue to enhance our capacity to 

respond to climate change. Similarly, governments’ capacities for disaster planning and 

emergency response are key assets that should allow the United States to adapt to many 

of the health effects associated with climate change. 

ES-5 
SAP 4.6 Executive Summary 

It is very likely that heat-related morbidity and mortality will increase over the 

coming decades. According to the U.S. Census, the U.S. population is aging; the percent 

of the population over age 65 is projected to be 13% by 2010 and 20% by 2030 (over 50 

million people). Older adults, very young children, and persons with compromised 

immune systems are vulnerable to temperature extremes. This suggests that temperaturerelated morbidity and mortality are likely to increase. Similarly, heat-related mortality 

affects poor and minority populations disproportionately, in part due to lack of air 

conditioning. The concentration of poverty in inner city neighborhoods leads to 

disproportionate adverse effects associated with urban heat islands. 

There is considerable speculation concerning the balance of climate change-related 

decreases in winter mortality compared with increases in summer mortality. Net changes 

in mortality are difficult to estimate because, in part, much depends on complexities in 

the relationship between mortality and the changes associated with global change. Few 

studies have attempted to link the epidemiological findings to climate scenarios for the 

United States, and studies that have done so have focused on the effects of changes in 

average temperature, with results dependent on climate scenarios and assumptions of 

future adaptation. Moreover, many factors contribute to winter mortality, making highly 

uncertain how climate change could affect mortality. No projections have been published 

for the U.S. that incorporate critical factors, such as the influence of influenza outbreaks. 

The impacts of higher temperatures in urban areas and likely associated increases 

in tropospheric ozone concentrations can contribute to or exacerbate cardiovascular 

and pulmonary illness if current regulatory standards are not attained. In addition, 

stagnant air masses related to climate change are likely to degrade air quality in some 

densely populated areas. It is important to recognize that the United States has a welldeveloped and successful national regulatory program for ozone, PM2.5, and other criteria 

pollutants. That is, the influence of climate change on air quality will play out against a 

backdrop of ongoing regulatory control that will shift the baseline concentrations of air 

pollutants. Studies to date have typically held air pollutant emissions constant over future 

decades (i.e., have examined the sensitivity of ozone concentrations to climate change rather 

than projecting actual future ozone concentrations). Physical features of communities, 

including housing quality and green space, social programs that affect access to health 

care, aspects of population composition (level of education, racial/ethnic composition), 

and social and cultural factors are all likely to affect vulnerability to air quality. 

Hurricanes, extreme precipitation resulting in floods, and wildfires also have the 

potential to affect public health through direct and indirect health risks. SAP3.3 

indicates that there is evidence for a human contribution to increased sea surface 

temperatures in the tropical Atlantic and there is a strong correlation to Atlantic tropical 

storm frequency, duration, and intensity. However, a confident assessment will require 

further studies. The health risks associated with such extreme events are thus likely to 

increase with the size of the population and the degree to which it is physically, mentally, 

or financially constrained in its ability to prepare for and respond to extreme weather 

events. For example, coastal evacuations prompted by imminent hurricane landfall are 

only moderately successful. Many of those who are advised to flee to higher ground stay 

ES-6 
SAP 4.6 Executive Summary 

behind in inadequate shelter. Surveys find that the public is either not aware of the 

appropriate preventive actions or incorrectly assesses the extent of their personal risk. 

There will likely be an increase in the spread of several food and water-borne 

pathogens among susceptible populations depending on the pathogens’ survival, 

persistence, habitat range and transmission under changing climate and 

environmental conditions. While the United States has successful programs to protect 

water quality under the Safe Drinking Water Act and the Clean Water Act, some 

contamination pathways and routes of exposure do not fall under regulatory programs 

(e.g., dermal absorption from floodwaters, swimming in lakes and ponds with elevated 

pathogen levels, etc.).The primary climate-related factors that affect these pathogens 

include temperature, precipitation, extreme weather events, and shifts in their ecological 

regimes. Consistent with our understanding of climate change on human health, the 

impact of climate on food and water-borne pathogens will seldom be the only factor 

determining the burden of human injuries, illness, and death. 

Health burdens related to climate change will vary by region. For the continental 

United States, the northern latitudes are likely to experience the largest increases in 

average temperatures; they will also bear the brunt of increases in ground-level ozone and 

other airborne pollutants. Because Midwestern and Northeastern cities are generally not 

as well adapted to the heat as Southern cities, their populations are likely to be 

disproportionately affected by heat related illnesses as heat waves increase in frequency, 

severity, and duration. The range of many vectors is likely to extend northward and to 

higher elevations. For some vectors, such as rodents associated with Hantavirus, ranges 

are likely to expand, as the precipitation patterns under a warmer climate enhance the 

vegetation that controls the rodent population. Forest fires with their associated 

decrements to air quality and pulmonary effects are likely to increase in frequency, 

severity, distribution, and duration in the Southeast, the Intermountain West and the 

West. Table ES.2 summarizes regional vulnerabilities to a range of climate impacts.

Finally, climate change is very likely to accentuate the disparities already evident in 

the American health care system. Many of the expected health effects are likely to fall 

disproportionately on the poor, the elderly, the disabled, and the uninsured. The most 

important adaptation to ameliorate health effects from climate change is to support and 

maintain the United States’ public health infrastructure. 

ES.3 Climate Change and Human Settlements 

Effects of climate change on human settlements are likely to vary considerably 

according to location-specific vulnerabilities, with the most vulnerable areas likely 

to include Alaska with increased permafrost melt, flood-risk coastal zones and river 

basins, and arid areas with associated water scarcity. The main climate impacts have 

to do with changes in the intensity, frequency and location of extreme weather events 

and, in some cases, water availability rather than temperature change. 

ES-7 
SAP 4.6 Executive Summary 

Changes in precipitation patterns will affect water supplies nationwide, with 

precipitation varying across regions and over time. Likely reductions in snowmelt, 

river flows, and groundwater levels, along with increases in saline intrusion into 

coastal rivers and groundwater will reduce fresh water supplies. All things held 

constant, population growth will increase the demand for drinking water even as changes 

in precipitation will change the availability of water supplies. Moreover, storms, floods, 

and other severe weather events are likely to affect infrastructure such as sanitation, 

transportation, supply lines for food and energy, and communication. Some of the 

nation’s most expensive infrastructure, such as exposed structures like bridges and utility 

networks, are especially vulnerable. In many cases, water supply networks and stressed 

reservoir capacity interact with growing populations (especially in coastal cities and in 

the Mountain and Pacific West). The complex interactions of land use, population 

growth and dynamics of settlement patterns further challenge supplies of water for 

municipal, industrial, and agricultural uses. In the Pacific Northwest the electricity base 

dominated by hydropower is directly dependent upon the water flows from snowmelt. 

Reduced hydropower would mean the need for supplemental electricity sources, resulting 

in a wide variety of negative ripple effects to the economy and to human welfare. 

Similarly, along the West Coast, communities are likely to experience greater demands 

on water supplies even as regional precipitation declines and average snow packs 

decrease. 

Communities in risk-prone regions, such as coastal zones, have reason to be 

concerned about potential increases in severe weather events. The combined effects 

of severe storms and sea-level rise in coastal areas or increased risks of fire in more arid 

areas are examples of how climate change may increase the magnitude of challenges 

already facing risk-prone regions. Vulnerabilities may be especially pronounced for 

rapidly-growing and/or larger metropolitan areas, where the potential magnitude of both 

impacts and coping requirements are likely to be very large. On the other hand, such 

regions have greater opportunity to adapt infrastructure and to make decisions that limit 

vulnerability. 

Warming is virtually certain to increase energy demand in U.S. cities for cooling in 

buildings while it reduces demands for heating in buildings (see SAP 4.5 Effects of 

Climate Change on Energy Production and Use in the United States). Demands for 

cooling during warm periods could jeopardize the reliability of service in some regions 

by exceeding the supply capacity, especially during periods of unusually high 

temperatures. Higher temperatures also affect costs of living and business operation by 

increasing costs of climate control in buildings 

Climate change has the potential not only to affect communities directly but also 

indirectly through impacts on other areas linked to their economies. Regional 

economies that depend on sectors highly sensitive to climate such as agriculture, forestry, 

water resources, or recreation and tourism could be affected either positively or 

negatively by climate change. Climate change can add to stress on social and political 

structures by increasing management and budget requirements for public services such as 

public health care, disaster risk reduction, and even public safety. As sources of stress 

grow and combine, the resilience of social and political structures are expected to be 

ES-8 
SAP 4.6 Executive Summary 

challenged, especially in locales with relatively limited social and political capital. 

Finally, population growth and economic development is occurring in those areas 

that are likely to be vulnerable to the effects of climate change. Approximately half 

of the U.S. population, 160 million people, will live in one of 673 coastal counties by 

2008. Coastal areas – particularly those on gently-sloping coasts and zones with gradual 

land subsidence – will be at risk for sea level rise, especially related to severe storms and 

storm surges. 

ES.4 Climate Change and Human Welfare 

The terms human welfare, quality of life, and well-being are often used 

interchangeably, and by a number of disciplines as diverse as psychology, 

economics, health science, geography, urban planning, and sociology. There is a 

shared understanding that all three terms refer to aspects of individual and group life that 

improve living conditions and reduce chances of injury, stress, and loss. 

Human well-being is typically defined and measured as a multi-dimensional 

concept. Taxonomies of place-specific well-being or quality of life typically converge on 

six dimensions: 1) economic conditions, 2) natural resources and amenities, 3) human 

health, 4) public and private infrastructure, including transportation systems, 5) 

government and public safety and 6) social and cultural resources. Climate change will 

likely have impacts across all of these dimensions – both positive and negative. In 

addition, the positive and negative effects of climate change will affect broader 

communities, as networks of households, businesses, physical structures, and institutions 

are located together across space and time. 

Quantifying impacts of climate change on human well-being requires linking effects 

in quality of life to the projected1

 physical effects of climate change and the 

consequent effects on human and natural systems. Economic analyses provide a 

means of quantifying and, in some cases, placing dollar values on welfare effects. Even 

in cases where welfare effects have been quantified, it is difficult to compare and 

aggregate a range of effects across a number of sectors. 

This report examines four types of effects on economic welfare: those on 

ecosystems, human health, recreation, and amenities associated with climate. Many 

of the goods and services affected by climate are not traded in markets; as a result, they 

can be difficult to value.” For example, ecologists have already identified a number of 

ecological impacts of climate change, including the shifting, break up, and loss of certain 

ecological communities; plant and animal extinctions and a loss in biodiversity; shifting 

ranges of plant and animal populations; and changes in ecosystem processes, such as 

 

1 A climate projection is the calculated response of the climate system to emissions or concentration 

scenarios of greenhouse gases and aerosols, or radiative forcing scenarios, often based on simulations by 

climate models. Climate projections are distinguished from climate predictions, in that the former critically 

depend on the emissions/concentration/radiative forcing scenario used, and therefore on highly uncertain 

assumptions of future socio-economic and technological development.

ES-9 
SAP 4.6 Executive Summary 

nutrient cycling and decomposition. While ecosystems provide a variety of services to 

humans, including food and fiber, regulating air and water quality, support services such 

as photosynthesis, and cultural services such as recreation and aesthetic or spiritual 

values, these typically are not traded in markets. 

Little research has been done linking these ecological changes to changes in services, 

and still less has been done to quantify, or place dollar values on, these changes.

Ecosystem impacts also extend beyond the obvious direct effects within the natural 

environment to indirect effects on human systems. For instance, nearly 90% of 

Americans take part in outdoor recreation. The length of season of some of these 

activities, such as hiking, boating, or golfing, may be favorably affected by slightly 

increased temperatures. However, snow and ice sport seasons are likely to be shortened, 

resulting in lost recreation opportunities. The net effect is unclear as decrements 

associated with snow-based recreation may be more than outweighed by increases in 

other outdoor activities. 

An agenda for understanding the impacts of climate change on human welfare may 

require taking steps both to develop a framework for addressing welfare, and to 

address the data and methodological gaps inherent in the estimation and 

quantification of effects. To that end, the study of climate change on human welfare is 

still developing, and, to our knowledge, no study has made a systematic survey of the full 

range of welfare impacts associated with climate change, much less attempted to quantify 

them. 

ES-10 
SAP 4.6 Executive Summary 

ES.5 Tables 

Table ES.1 Examples of Possible Impacts (present to 2050) of Climate Variability and Change 

on Human Health, Settlements, and Welfare in the United States and Potential Adaptation 

Strategies) 

Focus Area Climate Event Examples of Possible 

Impacts 

Likelihood of 

Impact Given 

Climate Event 

Occurs1

Potential Adaptation 

Strategies 

HUMAN HEALTH 

 Extreme temperatures 

More heat waves and 

higher maximum 

temperatures 

Fewer cold waves and 

higher minimum 

temperatures 

Heat stress/stroke or 

hyperthermia 

Uncertain impacts on 

mortality2

Very likely in 

Midwest and 

northeast urban 

centers 

Early watch and 

warning systems and 

installation of cooling 

systems in residential 

and commercial 

buildings, 

Changes in precipitation, 

especially extreme 

precipitation 

Contaminated water and 

food supplies with 

associated 

gastrointestinal illnesses, 

including salmonella and 

giardia

Likely in areas 

with out-dated 

or oversubscribed water 

treatment plants 

Improve 

infrastructure to 

guard against 

combined sewer 

overflow; public 

health response to 

include “boil water” 

advisories 

Hurricane and storm 

surge 

Injuries from flying debris 

and drowning / exposure 

to contaminated flood 

waters and to mold and 

mildew / exposure to 

carbon monoxide 

poisoning from portable 

generators 

Likely in coastal 

zones of the 

southeast 

Atlantic and the 

Gulf Coast 

Increase knowledge 

and awareness of 

vulnerability to 

climate change (e.g.,

maps showing areas 

vulnerable to storm 

surges); public health 

advisories in 

immediate aftermath 

of storm; coordinate 

storm relief efforts 

to insure that people 

receive necessary 

information for 

safeguarding their 

health 

Temperature-related 

effects on ozone3

Ozone concentrations 

more likely to increase 

than decrease; possible 

contribution to 

cardiovascular and 

pulmonary illnesses, 

including exacerbation of 

asthma and chronic 

obstructive pulmonary 

disorder (COPD) if 

current regulatory 

standards are not 

attained 

Likely in urban 

centers in the 

mid-Atlantic and 

the northeast 

Public warning via air 

quality action days; 

encourage public 

transit, walking and 

bicycling to decrease 

emissions 

ES-11 
SAP 4.6 Executive Summary 

Focus Area Climate Event Examples of Possible 

Impacts 

Likelihood of Potential Adaptation 

Impact Given Strategies 

Climate Event 

Occurs1

Wildfires Degraded air quality, 

contributing to asthma 

and COPD aggravated 

Likely in 

California, the 

Intermountain 

West, the 

southwest and 

the southeast 

Public health air 

quality advisories 

HUMAN SETTLEMENTS 

Extreme temperatures 

More heat waves and 

higher maximum 

temperatures 

Fewer cold waves and 

higher minimum 

temperatures 

Increased net energy 

demand and expand 

capacity for peak cooling 

Reduced cold-related 

stresses and costs 

Very likely Expand capacity for 

cooling through 

public utilities; invest 

in alternative energy 

sources 

Drought Strain on municipal and 

agricultural water 

supplies 

Very likely in 

intermountain 

west, desert 

southwest, and 

southeast 

Reallocate water 

among current users; 

develop water 

markets to 

encourage more 

efficient allocation; 

identify new sources 

through expansion of 

reservoirs; 

encourage 

conservation of 

water for personal 

and public use; 

develop drought 

resistant crops, 

Hurricane and storm 

surge 

Disruption of 

infrastructure, including 

levee systems, river 

channels, bridges, and 

highway systems; 

disruption of residential 

neighborhoods 

Very likely in 

southeast 

Atlantic Coast 

and Gulf Coast 

Increase knowledge 

and awareness of 

climate impacts (e.g.,

maps showing areas 

vulnerable to storm 

surges); harden 

coastal zones or 

retreat or relocate; 

insure against 

catastrophic loss due 

to flooding and high 

winds 

Wildfires Disruption of

communities and 

property destruction 

Very likely in 

intermountain 

west, desert 

southwest, and 

southeast 

Clear vegetation

away from buildings; 

issue emergency 

evacuation orders, 

prescribed burns, 

thinning of 

combustible matter 

ES-12 
SAP 4.6 Executive Summary 

Focus Area Climate Event Examples of Possible 

Impacts 

Likelihood of Potential Adaptation 

Impact Given Strategies 

Climate Event 

Occurs1

Late snow fall and early 

snow melt 

Disruption of water 

supplies for municipal and 

agricultural use 

Very likely in 

intermountain 

west 

Build reservoirs; 

conserve water 

supplies; divert 

supply from 

agricultural to 

municipal use; modify 

operation of existing 

infrastructure to 

account for changes 

in hydrology; develop 

drought resistant 

crops, water prices 

at replacement cost, 

enable trading by 

working with states 

to develop property 

rights 

HUMAN WELFARE 

Extreme temperatures 

More heat waves and 

higher maximum 

temperatures 

Fewer cold waves and 

higher minimum 

temperatures 

Discomfort; limit some 

outdoor activities / 

recreation 

Limit some snow- and 

cold-related recreational 

opportunities; substantial 

economic disruption to 

recreation industry 

Very likely in 

more northern 

latitudes of the 

United States 

and in Alaska 

Very likely in 

intermountain 

west, Northern 

New England and 

the Upper Great 

Lakes 

Public health 

watch/warning 

advisories 

Engage in alternative 

recreation activities 

Late autumn snow fall and 

early spring snow melt 

Limit some snow-related 

recreational 

opportunities; substantial 

economic disruption to 

recreation industry 

Very likely in 

intermountain 

west, Northern 

New England and 

the Upper Great 

Lakes 

Engage in alternative 

recreation activities 

Extreme precipitation 

events 

Local flooding and 

contamination of water 

supplies 

Very likely 

nationwide 

Issue flood advisories 

/ warnings 

Hurricane and coastal 

storms 

At-risk properties 

experience flood and 

wind damage; individuals 

experience disruption to 

daily life 

Very likely in 

coastal zone of 

the Gulf Coast 

and the southern 

Atlantic 

Relocate dwellings 

and business, and 

reinforce structures 

and infrastructure to 

reduce disruptions 

1 Based on impacts identified in the published, peer-reviewed literature and expert opinion. Does not include an 

evaluation of likelihood of the climate event. May include some adaptation (e.g., in the baseline estimate) but generally 

does not account for additional changes or developments in adaptive capacity. 

2 Many factors contribute to winter mortality, making highly uncertain how climate change could affect mortality. No 

projections have been published for the United States that incorporates critical factors, such as the influence of 

influenza outbreaks. 

3 If areas remain in compliance with National Ambient Air Quality Standards, people will not be exposed to unhealthy 

air (i.e., cardiovascular and pulmonary illnesses will not occur). More stringent emissions controls may be required to 

remain in compliance although this is uncertain and additional study is needed.

ES-13 
SAP 4.6 Executive Summary 

Table ES.2 Summary of Regional Vulnerabilities to Climate-Related Impacts1

Climate-Related Impacts 

United States 

Census Regions Early 

Snowmelt 

Degraded 

Air Quality 

Urban Heat 

Island Wildfires Heat Waves Drought Tropical Storms 

Extreme 

Rainfall 

with 

Flooding 

Sea Level 

Rise 

New England 

ME VT NH MA RI CT ● ● ● ● ● ● ●

Middle Atlantic 

NY PA NJ ● ● ● ● ● ● ● ●

East North Central 

WI MI IL IN OH ● ● ● ● ● ●

West North Central 

ND MN SD IA NE KS MO ● ● ● ● ●

South Atlantic 

WV VA MD MC SC GA FL DC ● ● ● ● ● ● ● ●

East South Central 

KY TN MS AL ● ● ● ●

West South Central 

TX OK AR LA ● ● ● ● ● ● ● ●

Mountain 

MT ID WY NV UT CO AZ NM ● ● ● ● ● ●

Pacific 

AK CA WA OR HI ● ● ● ● ● ● ● ● ●

1 Based on impacts identified in the published, peer-reviewed literature and expert opinion. 

ES-14 
Synthesis and Assessment Product 4.6 

Chapter 1: Introduction 

Convening Lead Author: Janet L. Gamble, U.S. Environmental Protection Agency

Lead Authors: Kristie L. Ebi, ESS, LLC; Anne Grambsch, U.S. Environmental Protection Agency; Frances 

G. Sussman, Environmental Economics Consulting; Thomas J. Wilbanks, Oak Ridge National Laboratory 

Contributing Authors: Colleen E. Reid, ASPH Fellow; Katharine Hayhoe, Texas Tech University; John 

V. Thomas, U.S. Environmental Protection Agency; Christopher P. Weaver, U.S. Environmental Protection 

Agency 
SAP 4.6 Chapter 1: Introduction

Table of Contents 

Table of Contents.......................................................................................................................................... 2

1.1 Scope and Approach of the SAP 4.6...................................................................................................... 3

1.2 Climate Change in the United States: Context for an Assessment of Impacts on Human Systems 7

1.2.1 Rising Temperatures......................................................................................................................... 8

1.2.2 Trends in Precipitation ..................................................................................................................... 9

1.2.3 Rising Sea Levels and Erosion of Coastal Zones............................................................................ 10

1.2.4 Changes in Extreme Conditions...................................................................................................... 11

1.3 Population Trends and Migration Patterns: A Context for Assessing Climate-related Impacts 14

1.3.1 Trends in Total U.S. Population ..................................................................................................... 14

1.3.2 Migration Patterns.......................................................................................................................... 15

1.4. Complex Linkages: The Role of Non-climate Factors...................................................................... 17

1.4.1 Economic Status.............................................................................................................................. 18

1.4.2 Technology...................................................................................................................................... 18

1.4.3 Infrastructure.................................................................................................................................. 19

1.4.4 Human and Social Capital and Behaviors...................................................................................... 20

1.4.5 Institutions ...................................................................................................................................... 20

1.4.6 Interacting Effects........................................................................................................................... 21

1.5 Reporting Uncertainty in SAP 4.6....................................................................................................... 22

1.6 References ............................................................................................................................................ 24

1.7 Tables.................................................................................................................................................... 36

1.8 Figures .................................................................................................................................................. 37

1 - 2 
SAP 4.6 Chapter 1: Introduction

1.1 Scope and Approach of the SAP 4.6 

The Global Change Research Act of 1990 (Public Law 101-606) calls for the periodic 

assessment of the impacts of global environmental change for the United States. In 2001, 

a series of sector and regional assessments were conducted by the U.S. Global Change 

Research Program as part of the First National Assessment of the Potential Consequences 

of Climate Variability and Change on the United States. Subsequently, the U.S. Climate 

Change Science Program developed a Strategic Plan (CCSP, 2003) calling for the 

preparation of 21 synthesis and assessment products (SAPs) to inform policy making and 

adaptive management across a range of climate-sensitive issues. Synthesis and 

Assessment Product 4.6 examines the effects of global change on human systems. This 

product addresses Goal 4 of the five strategic goals set forth in the CCSP Strategic Plan 

to “understand the sensitivity and adaptability of different natural and managed 

ecosystems and human systems to climate and related global changes” (CCSP, 2003). 

The “global changes” assessed in this report include: climate variability and change, 

evolving patterns of land use within the United States, and changes in the nation’s 

population. 

While the mandate for the preparation of this report calls for evaluating the impacts of 

global change, the emphasis is on those impacts associated with climate change. 

Collectively, global changes are human problems, not simply problems for the natural or 

the physical world. Hence, this SAP examines the vulnerability of human health and 

socioeconomic systems to climate change across three foci, including: human health, 

human settlements and human welfare. The three topics are fundamentally linked but 

unique dimensions of global change. 

Human health is one of the most basic and direct measures of human welfare. Following 

past assessments of climate change impacts on human health, SAP 4.6 focuses on human 

morbidity and mortality associated with extreme weather, vector-, water- and food-borne 

diseases, and changes in air quality in the United States. However, it should be noted that 

climate change in other parts of the world could impact human health in the United 

States. (e.g., by affecting migration into the U.S., the safety of food imported into the 

U.S., etc.). Adaptation is a key component to evaluating human health vulnerabilities, 

including consideration of public health interventions (including prevention, response, 

and treatment strategies) that could be revised, supplemented, or implemented to protect 

human health and how much adaptation could be achieved. 

Settlements are where people live. Humans live in a wide variety of settlements in the 

United States, ranging from small villages and towns with a handful of people to 

metropolitan regions with millions of inhabitants. In particular, SAP 4.6 focuses on urban 

and highly-developed population centers in the United States. Because of their high 

population density, urban areas multiply human health risks, and this is compounded by 

their relatively high proportions of the very old, the very young, and the poor. In addition, 

the components of infrastructure that support settlements, such as energy, water supply, 

transportation, and waste disposal, have varying degrees of vulnerability to climate 

change. 

1 - 3 
SAP 4.6 Chapter 1: Introduction

Welfare is an economic term used to describe the state of well-being of humans on an 

individual or collective basis. Human welfare is an elusive concept, and there is no 

single, commonly accepted definition or approach to thinking about welfare. There is, 

however, a shared understanding that increases in human welfare are associated with 

improvements in individual and communal conditions in areas such as political power, 

individual freedoms, economic power, social contacts, health and opportunities for 

leisure and recreation, along with reductions in injury, stress, and loss. The physical 

environment, with climate as one aspect, is among many factors that can affect human 

welfare via economic, physical, psychological, and social pathways that influence 

individual perceptions of quality of life. Some core aspects of quality of life are 

expressed directly in markets (e.g., income, consumption, personal wealth, etc.). The 

focus in SAP 4.6 is on non-market effects, although, these aspects of human welfare are 

often difficult to measure and value (Mendelsohn et al., 1999; EPA, 2000). 

The other Synthesis and Assessment Products related to CCSP’s Goal 4 include reports 

on climate impacts on sea level rise (SAP 4.1), ecosystem changes (SAP 4.2), agricultural 

production (SAP 4.3), adaptive options for climate sensitive ecosystems (SAP 4.4), 

energy use (SAP 4.5) and transportation system impacts along the Gulf Coast (SAP 4.7). 

Collectively, these reports provide an overview of climate change impacts and 

adaptations related to a range of human conditions in the United States. 

The audience for this report includes research scientists, public health practitioners, 

resource managers, urban planners, transportation planners, elected officials and other 

policy makers, and concerned citizens. A recent National Research Council analysis of 

global change assessments argues that the best assessments have an audience asking for 

them, and a broad range of stakeholders (U.S. National Research Council, 2007). This 

report clearly identifies the pertinent audience and what decisions it will inform. 

Chapters 2-4 describe the impacts of climate change on human systems and outline 

opportunities for adaptation. SAP 4.6 addresses the questions of how and where climate 

change may impact U.S. socio-economic systems. The challenge for this project is to 

derive an assessment of risks associated with health, welfare, and settlements and to 

develop timely adaptive strategies to address a range of vulnerabilities. Risk assessments 

evaluate impacts of climate change across an array of characteristics, including: the 

magnitude of risk (both baseline and incremental risks), the distribution of risks across 

populations (including minimally-impacted individuals as compared to maximallyexposed individuals), and the availability, difficulty, irreversibility, and cost of adaptation 

strategies. While the state of science limits the ability to conduct formal, quantitative risk 

assessments, it is possible to develop information that is useful for formulating adaptation 

strategies. Primary goals for adaptation to climate variability and change include: 

1. To avoid maladaptive responses; 

2. To establish protocols to detect and measure risks and to manage risks proactively 

when possible; 

3. To leverage technical and institutional capacity; 

1 - 4 
SAP 4.6 Chapter 1: Introduction

4. To reduce current vulnerabilities to climate change; 

5. To develop adaptive capacity to address new climate risks that exceed 

conventional adaptive responses; and, 

6. To recognize and respond to impacts which play out across time. (Scheraga and 

Grambsch, 1998; WHO, 2003; IPCC, 2007b) 

The issue of co-benefits is central in the consideration of adaptation to climate change. 

Many potential adaptive strategies have co-benefits. Along with helping human 

populations cope with climate change, adaptive strategies produce additional benefits. 

For example: 

 Creating and implementing early warning systems and emergency response plans 

for heat waves can also improve those services for other emergency responses 

while improving all-hazards preparedness; (Glantz, 2004) 

 Improving the infrastructure and capacity of combined sewer systems to avoid 

overflows due to changes in precipitation patterns also has the added benefit of 

decreasing contaminant flows that cause beach closings and impact the local 

ecology; (Rose et al., 2001) 

 A key adaptation technique for settlements in coastal zones is to promote 

maintenance or reconstruction of coastal wetlands ecosystems, which has the 

added benefit of creation or protection of coastal habitats (Rose et al., 2001); and, 

 Promotion of green building practices has added health and welfare benefits as 

improving natural light in office space and schools has been shown to increase 

productivity and mental health (Edwards and Torcellini, 2002). 

Chapter 2 assesses the potential impacts of climate change on human health in the United 

States. Timely knowledge of human health impacts may support our public health 

infrastructure in devising and implementing strategies to prevent, compensate, or respond 

to these effects. For each of the health endpoints, the assessment addresses a number of 

topics, including: 

 Reviewing evidence of the current burden associated with the identified health 

outcome; 

 Characterizing the human health impacts of current climate variability and 

projected climate change (to the extent that the current literature allows); 

 Discussing adaptation opportunities and support for effective decision making; 

and, 

 Outlining key knowledge gaps. 

Each topic chapter includes research published from 2001 through early 2007 in the 

United States, or in Canada, Europe, and Australia, where results may provide insights 

for U.S. populations. As such, the health chapter serves as an update to the Health Sector 

Assessment conducted as part of the First National Assessment in 2001. 

Chapter 3 focuses on the climate change impacts and adaptations associated with human 

settlements in the United States. The IPCC Third and Fourth Assessment Reports (IPCC, 

1 - 5 
SAP 4.6 Chapter 1: Introduction

2001; IPCC, 2007c) conclude that settlements are among the human systems that are the 

most sensitive to climate change. For example, if there are changes in climate extremes 

there could be serious consequences for human settlements that are vulnerable to 

droughts and wildfires, coastal and river floods, sea level rise and storm surge, heat 

waves, land slides, and windstorms. However, specific changes in these conditions in 

specific places cannot yet be projected with great confidence. Chapter 3 focuses on the 

interactions between settlement characteristics, climate and other global stressors, with a 

particular focus on urban areas and other densely-developed population centers in the 

United States. 

The scale and complexity of these built environments, transportation networks, energy 

and resource demands, and the interdependence of these systems and their populaces, 

suggests that urban areas are especially vulnerable to multiplying impacts in response to 

externally imposed environmental stresses. The collective vulnerability of American 

urban centers may also be determined by the disproportionate share of urban growth in 

areas like the Inter-Mountain West or the Gulf Coast. The focus of Chapter 3 is on high 

density or rapidly-growing settlements and the potential for changes over time in the 

vulnerabilities associated with place-based characteristics (such as their climate regime, 

elevation, and proximity to coasts and rivers) and spatial characteristics (such as whether 

development patterns are sprawling or compact). 

Chapter 4 focuses on the impacts of climate change on human welfare. To examine the 

impacts of climate change on human welfare, this chapter reports on two relevant bodies 

of literature: approaches to welfare that rely on both qualitative assessment and 

quantitative measures, and economic approaches that monetize, or place money values, 

on quantitative impacts. 

Finally, Chapter 5 revisits the research recommendations and data gaps of previous 

assessment activities and describes the progress to date and the opportunities going 

forward. In addition, Chapter 5 reviews the overarching themes derived from Chapters 2-

4. 

The remainder of this chapter is designed to provide the reader with an overview of the 

current state of knowledge regarding: 

1. Changes in climate in the United States; 

2. Population trends, migration patterns, and the distribution of people across 

settlements; 

3. Non-climate stressors and their interactions with climate change to realize 

complex impacts; and, 

4. A discussion of the handling of uncertainty in reporting scientific results. 

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SAP 4.6 Chapter 1: Introduction

1.2 Climate Change in the United States: Context for an 

Assessment of Impacts on Human Systems 

In the following chapters, the authors examine the impacts on human society of global 

change, especially those associated with climate change. The impact assessments in 

Chapters 2-4 do not rely on specific emissions or climate change scenarios but, instead, 

rely on the existing scientific literature with respect to our understanding of climate 

change and its impacts on human health, settlements and human well-being in the United 

States. This report does not make quantitative projections of specific impacts in specific 

locations based on specific projections of climate drivers of these impacts. Instead the 

report adopts a vulnerability perspective. 

A vulnerability approach focuses on estimating risks or opportunities associated with 

possible impacts of climate change, rather than on estimating quantitatively the impacts

themselves which would require far more detailed information about future conditions. 

Vulnerabilities are shaped not only by existing exposures, sensitivities, and adaptive 

capacities but also by responses to risks. In addition, climate change is not the only 

change confronting human societies: from a vulnerability perspective projected changes 

in populations, the economy, technology, institutions, infrastructure, and human and 

social capital are among the factors that also affect vulnerability to climate change. The 

report reviews historical trends and variability to point to vulnerabilities and then, where 

possible, determines the likely direction and range of potential climate-related impacts. 

In the United States, we are observing the evidence of long-term changes in temperature 

and precipitation consistent with global warming. Changes in average conditions are 

being realized through rising temperatures, changes in annual and seasonal precipitation, 

and rising sea levels. Observations also indicate there are changes in extreme conditions, 

such as an increased frequency of heavy rainfall (with some increase in flooding), more 

heat waves, fewer very cold days, and an increase in areas affected by drought. 

Frequencies of tropical storms and hurricanes vary considerably from year to year and 

there are limitations in the quality of the data which make it difficult to discern trends, 

but evidence suggests some increases in their intensity and duration since the 1970s 

(Christensen et al., 2007). 

The following sections provide a brief introduction to climate change as a context for the 

following chapters on impacts and adaptation. SAP4.6 did not itself evaluate climate 

change projections as they were not used quantitatively in this assessment. The 

Intergovernmental Panel on Climate Change provides a comprehensive evaluation of 

climate change science. In their Summary for Policy Makers (IPCC, 2007a) reports the 

following observed changes in global climate: 

 “Warming of the climate system is unequivocal, as is now evident from 

observations of increases in global average air and ocean temperature, widespread 

melting of snow and ice, and rising global average sea level.” 

 “Eleven of the last twelve years rank among the 12 warmest years in the 

instrumental record of global surface temperatures (since 1850).” 

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SAP 4.6 Chapter 1: Introduction

 “Average temperature of the global ocean has increased to depths of at least 3000 

m and that the ocean has been absorbing more than 80% of the heat added to the 

climate system. Such warming causes sea water to expand, contributing to sea 

level rise.” 

 “Mountain glaciers and snow cover have declined on average in both 

hemispheres.” 

 “The frequency of heavy precipitation events has increased over most land areas, 

consistent with warming and observed increases of atmospheric water vapor.” 

 “Widespread changes in extreme temperatures have been observed over the last 

50 years... Hot days, hot nights, and heat waves have become more frequent.” 

 “There is observational evidence for an increase of intense tropical cyclone 

activity in the North Atlantic since about 1970.” (IPCC, 2007a) 

Note that these changes are for the entire globe: changes in the United States may be 

similar or differ from these global changes. The following sections examine U.S. climate 

trends and historical records related to temperature, precipitation, sea level rise, and 

changes in hurricanes and other catastrophic events. Information is also drawn from the 

North American Chapter of the IPCC Fourth Assessment Report and the Climate Change 

Science Programs Synthesis and Assessment Product 3.3: Weather and Climate Extremes 

in a Changing Climate. Taken together, this discussion provides a context from which to 

assess impacts of climate change on human health, human welfare, and human 

settlements. 

1.2.1 Rising Temperatures 

Climate change is already affecting the United States. According to long-term stationbased observational records such as the Historical Climatology Network (Karl et al., 

1990; Easterling et al., 1999; Williams et al., 2007), temperatures across the continental 

United States have been rising at a rate of 0.1°F per decade since the early 1900s. 

Increases in average annual temperatures over the last century now exceed 1°F (Figure 

1.1a). The degree of warming has varied by region across the United States, with the 

West and Alaska experiencing the greatest degree of warming (U.S. Environmental 

Protection Agency, 2007). These changes in temperature have led to an increase in the 

number of frost-free days, with the greatest increases occurring in the West and 

Southwest (Tebaldi et al., 2006). The Intergovernmental Panel on Climate Change, in its 

most recent assessment report concluded that “Warming of the climate system is 

unequivocal...” (IPCC, 2007a). 

Figure 1.1 Observed trends in annual average (a) temperature (oF) and (b) precipitation 

(inches) across the continental United States from 1896 to 2006 (Source: NCDC, 2007)

The current generation of global climate models, run with IPCC SRES scenarios of future 

greenhouse gas emissions, simulate future changes in the earth’s climate system that are 

greater in magnitude and scope than those already observed. According to the IPCC, by 

the end of the 21st century, annual surface temperature increases are projected to range 

from 2-3°C near the coasts in the conterminous United States to more than 5°C in 

northern Alaska. Nationally, annual warming in the United States is projected to exceed 

2o

C, with projected increases in summertime temperatures ranging between 3 and 5°C 

1 - 8 
SAP 4.6 Chapter 1: Introduction

(greatest in the Southwest). The largest warming is projected to reach 10oC for winter 

temperatures in the northernmost parts of Alaska. (IPCC, 2007c). For additional 

information about the modeling results, see the IPCC Fourth Assessment Working Group 

I Report, especially Chapter 11: Regional Climate Projections (Christensen et al., 2007) 

1.2.2 Trends in Precipitation 

Shifting precipitation patterns have also been observed. Over the last century, annual 

precipitation across the continental United States has been increasing by an average of 

0.18 inches per decade (Figure 1.1b). Broken down by season, winter precipitation 

around the coastal areas, including the West, Gulf, and Atlantic coasts, has been 

increasing by up to 30% while precipitation in the central part of the country (the 

Midwest and the Great Plains) has been decreasing by up to 20%. Large-scale spatial 

patterns in summer precipitation trends are more difficult to identify, as much of summer 

rainfall comes in the form of small-scale convective precipitation. However, it appears 

that there have been increases of 20-80% in summer rainfall over California and the 

Pacific Northwest, and decreases on the order of 20-40% across much of the south. The 

IPCC reports that rainfall is arriving in more intense events. (IPCC, 2007a). 

El Niño events (a periodic warming of the tropical Pacific Ocean between South America 

and the International Date Line) are associated with increased precipitation and severe 

storms in some regions, such as the southeast United States and the Great Basin region of 

the western United States. El Niño events have also been characterized by warmer 

temperatures and decreased precipitation in other areas, such as western Canada, the 

Pacific Northwest and parts of Alaska. Historically, El Niño events occur about every 3 

to 7 years and alternate with the opposite phases of below-average temperatures in the 

eastern tropical Pacific (La Niña). Since 1976-1977, there has been a tendency toward 

more prolonged and stronger El Niños (IPCC, 2007a). However, recent analyses of 

climate simulations indicate no consistent trends in future El Niño amplitude or 

frequency (Meehl et al., 2007) 

Global model simulations summarized in the North American Chapter of the IPCC AR4, 

show moderate increases in precipitation (10% or less) over much of the United States 

over the next 100 years, except for the southwest. However, projected increases in these 

simulations are partially offset by increases in evaporation, resulting in greater drying in 

the central part of the United States. Projections for the central, eastern and western 

regions of the United States show similar seasonal characteristics (i.e., winter increases, 

summer decreases), although there is greater consensus for winter increases in the north 

and summer decreases in the south. However, uncertainty around the projected changes is 

large (IPCC, 2007b). 

1.2.2.1 Changes in Snow Melt and Glacial Retreat 

Warmer temperatures are melting mountain glaciers and more winter precipitation in 

northern states is falling as rain instead of snow. (Huntington et al., 2004). Snow pack is 

also melting faster, affecting stream flow in rivers. Over the last fifty years, changes in 

the timing of snow melt has shifted the schedule of snow-fed stream flow in the western 

part of the country by 1-4 weeks earlier in the year (Stewart et al., 2005). The seasonal 

1 - 9 
SAP 4.6 Chapter 1: Introduction

“center of stream flow volume” (i.e., the date at which half of the expected winter-spring 

stream flow has occurred) also appears to be advancing by on average one day per decade 

for streams in the Northeast (Huntington et al., 2003). 

This trend is projected to continue, with more precipitation falling as rain rather than 

snow, and snow season length and snow depth are generally projected to decrease in most 

of the country. Such changes tend to favor increased risk of winter flooding and lower 

summer soil moisture and streamflows (IPCC, 2007a). 

1.2.3 Rising Sea Levels and Erosion of Coastal Zones 

Sea levels are rising and the IPCC concluded with high confidence that the rate of sea 

level rise increased from the 19th to the 20th centuries (IPCC, 2007a). The causes for 

observed sea-level rise over the past century include thermal expansion of seawater as it 

warms and changes in land ice (e.g., melting of glaciers and snow caps). Over the 20th

century, sea level was rising at a rate of about 0.7 inches per decade (1.7 mm/yr ± 0.5 

mm). For the period 1993 to 2003, the rate was nearly twice as fast, at 1.2 inches per 

decade (3.1 mm/yr ± 0.7 mm). However, there is considerably decadal variability in the 

tide gauge record so that it is unknown whether the higher rate in 1993 to 2003 is due to 

decadal variability or an increase in the longer-term trend. (Bindoff et al., 2007). In the 

past century, global sea level rose 5-8 inches. 

Spatially sea-level change varies considerably: in some regions, rates are up to several 

times the global mean rise, while in other regions sea level is falling. For example, for the 

mid-Atlantic coast (i.e., from New York to North Carolina), the “effective” or relative 

sea-level rise rates have exceeded the global rate due to a combination of land subsidence 

and global sea level rise. In this region, relative sea-level rise rates ranged between 3 to 4 

mm per year (~1ft per century) over the 20th century. In other cases, local sea-level rise 

is less than the global average because the land is still rising (rebounding) from when ice 

sheets covered the area, depressing the Earth’s crust. Local sea levels can actually be 

falling in some cases (for example, the Pacific Northwest coast) if the land is rising more 

than the sea is falling (for additional details about sea level rise and its effects on US 

coasts please see Synthesis and Assessment Product 4.1 Coastal elevations and sensitivity 

to sea level rise). 

Rising global temperatures are projected to accelerate the rate of sea-level rise by further 

expanding ocean water, melting mountain glaciers, and increasing the rate at which 

Greenland and Antarctic ice sheets melt or discharge ice into the oceans. Estimates of 

sea-level rise for a global temperature increase between 1.1 and 6.4°C (the IPCC estimate 

of likely temperature increases by 2100) are about 7 to 23 inches (0.18m to 0.59m), 

excluding the contribution from accelerated ice discharges from the Greenland and 

Antarctica ice sheets. Extrapolating the recent acceleration of ice discharges from the 

polar ice sheets would imply an additional contribution up to 8 inches (20cm). If melting 

of these ice caps increases, larger values of sea-level rise cannot be excluded (IPCC, 

2007a). 

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SAP 4.6 Chapter 1: Introduction

1.2.4 Changes in Extreme Conditions 

The climatic changes described above are often referred to as changes in “average” 

conditions. Most observations of temperature will tend to be close to the average: days 

with very hot temperatures happen infrequently. Similarly, only rarely will there be days 

with extremely heavy precipitation. Climate change could result in a shift of the entire 

distribution of a meteorological variable so that a relatively small shift in the mean could 

be accompanied by a relatively large change in the number of relatively rare (according 

to today’s perspective) events. For example, with an increase in average temperatures, it 

would be expected there would be an increase in the number of very hot days and a 

decrease in the number of very cold days. Other, relatively rare, extreme events of 

concern for human health, welfare and settlements include hurricanes, floods and 

droughts. 

In general, it is difficult to attribute any individual extreme event to a changing climate. 

Because extreme events occur infrequently, there is typically limited information to 

characterize these events and their trends. In addition, extreme events usually require 

several conditions to exist for the event to occur, so that linking a particular extreme 

event to a single, specific cause is problematic. For some extreme events, such as 

extremely hot/cold days or rainfall extremes, there is more of an observational basis for 

analyzing trends, increasing our understanding and ability to project future changes. 

Finally, there are many different aspects to extremes. Frequency is perhaps the most often 

discussed but changes in other aspects of extremes such as intensity (e.g., warmer hot 

days), time of occurrence (e.g., earlier snowmelt), duration (e.g., longer droughts), spatial 

extent and location are also important when determining impacts on human systems. 

Synthesis and Assessment Product 3.3 Weather and Climate Extremes in a Changing 

Climate (CCSP, 2008) has a much more detailed discussion of climate extremes that are 

only very briefly described here. The interested reader is referred to that report for 

additional details.

1.2.4.1 Heat and Cold Waves 

Extreme temperatures (e.g., temperatures in the upper 90th or 95th percentile of the 

distribution) often change in parallel with average temperatures. Since 1950, there are 

more 3-day warm spells (exceeding the 90th percentile) when averaged over all of North 

America (Peterson et al., 2008). While the number of heat waves has increased, the heat 

waves of the 1930s remain the most severe in the U.S. historical record. Mirroring this 

shift toward more hot days is a decrease in unusually cold days during the last few 

decades. There has been a corresponding decrease in frost days and a lengthening of the 

frost-free season over the past century. The number of frost days decreased by four days 

per year in the United States during the 1948-1999 period, with the largest decreases, as 

many as 13 days per year, occurring in the western United States (Easterling, 2002). For 

the United States, the average length of the frost-free season over the 20th century 

increased by almost two weeks (Kunkel et al., 2004). 

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SAP 4.6 Chapter 1: Introduction

Recent studies have found that there is an increased likelihood of more intense, longerlasting and more frequent heat waves (Meehl and Tebaldi, 2004, Schar et al., 2004, Clark 

et al., 2006). As the climate warms, the number of frost days is expected to decrease 

(Cubasch et al., 2001) particularly along the northwest coast of North America (Meehl et 

al., 2004). SAP 4.6, using a range of greenhouse gas emission scenarios and model 

simulations, found that hot days, hot nights and heat waves are very likely to become 

more frequent, that cold days and cold nights are very likely to become much less 

frequent, and that the number of days with frost is very likely to decrease (CCSP, 2008). 

Growing season length is related to frost days, which is projected to increase in a warmer 

climate in most areas (Tebaldi et al., 2006). 

1.2.4.2 Heavy Precipitation Events 

Over the 20th century, periods of heavy downpours became more frequent and more 

intense and accounted for a larger percentage of total precipitation (Karl and Knight, 

1997; Groisman et al., 1999, 2001, 2004, 2005; Kunkel et al., 1999; Easterling et al., 

2000; Kunkel, 2003). These heavy rainfall events have increased in frequency by as 

much as 100% across much of the Midwest and Northeast over the last century (Kunkel 

et al., 1999). These findings are consistent with observed warming and associated 

increases in atmospheric water vapor. 

The intensity of precipitation events is projected to increase, particularly in high latitude 

areas that experience increases in mean precipitation (Meehl et al., 2007). In areas where 

mean precipitation decreases (most subtropical and mid-latitude regions), precipitation 

intensity is projected to increase but there would be longer periods between rainfall 

events. Precipitation extremes increase more than does the mean in most tropical and 

mid- and high-latitude areas. Some studies project widespread increases in extreme 

precipitation (Christensen et al., 2007), with greater risks of not only flooding from 

intense precipitation, but also droughts from greater temporal variability in precipitation. 

SAP 3.3 concluded that, over most regions, future precipitation is likely to be less 

frequent but more intense, and precipitation extremes are very likely to increase (CCSP, 

2008). 

1.2.4.3 Changes in Flooding 

Heavy rainfall clearly can lead to flooding, but assessing whether observed changes in 

precipitation have lead to similar trends in flooding is difficult for a number of reasons. In 

particular, there are many human influences on streamflow (e.g., dams, land-use changes, 

etc.) that confound climatic influences. In some cases, researchers using the same data 

came to opposite assessments about trends in high streamflows (Lins and Slack, 1999, 

2005; Groisman et al., 2001, 2004). Short duration extreme precipitation events can lead 

to localized flash flooding, but for large river basins, significant flooding will not occur 

from these types of episodes alone; excessive precipitation must be sustained for weeks 

to months for flooding to occur. 

1.2.4.4 Changes in Droughts 

An extended period with little precipitation is the main cause of drought, but the intensity 

of a drought can be exacerbated by high temperatures and winds, a lack of cloudiness/low 

1 - 12 
SAP 4.6 Chapter 1: Introduction

humidity which result in high evaporation rates. Droughts occur on a range of geographic 

scales and can vary in their duration, in some cases lasting years. The 1930s and the 

1950s experienced the most widespread and severe drought conditions (Andreadis et al., 

2005), although the early 2000s also saw severe droughts in some areas, especially in the 

western United States (Piechota et al., 2004). 

Based on observations averaged over the United States, there is no clear overall national 

trend in droughts (CCSP, 2008). Over the past century, the area affected by severe and 

extreme drought in the United States each year averaged about 14%: by comparison, in 

1934 the area affected by drought was as high as 65% (CCSP, 2008). In recent years, the 

drought-affected area ranged between 35 and 40% (CCSP, 2008). These trends at the 

national level however mask important differences in drought conditions at regional 

scales: one area may be very dry while another is wet. For example, in the Southwest and 

parts of the interior of the West increased temperatures have led to rising drought trends 

(Groisman et al., 2004; Andreadis and Lettenmaier, 2006). In the Southwest, the 1950s 

were the driest period, though droughts in the past 10 years are approaching the 1950s 

drought (CCSP, 2008). There are also recent regional tendencies toward more severe 

droughts in parts of Alaska (CCSP, 2008). 

Several generations of global climate models, including the most recent find an increase 

in summer drying in the mid latitudes in a future, warmer climate (Meehl et al., 2007). 

This tendency for drying of the mid-continental areas during summer indicates a greater 

risk of droughts in those regions (CCSP, 2008). Analyses using several coupled global 

circulation models project an increased frequency of droughts lasting a month or longer 

in the Northeast (Hayhoe et al., 2007) and greatly reduced annual water availability over 

the Southwest (Milly et al., 2005). SAP 3.3 concluded that droughts are likely to become 

more frequent and severe in some regions of the country as higher air temperatures 

increase the potential for evaporation. 

1.2.4.5 Changes in Hurricanes 

Assessing changes in hurricanes is difficult: There have been large fluctuations in the 

number of hurricanes from year to year and from decade to decade. Furthermore, it is 

only since the 1960s that reliable data can be assembled for assessing trends. In general, 

there is increasing uncertainty in the data record the further back in time one goes but 

significant increases in tropical cyclone frequency are likely since 1900 (CCSP, 2008). 

However, the existing data and an adjusted record of tropical storms indicate no 

significant linear trends beginning from the mid- to late 1800s to 2005 (CCSP, 2008). 

Moreover, SAP 3.3 concluded that there is no evidence for a long-term increase in North 

American mainland land-falling hurricanes. 

Evidence suggests that the intensity of Atlantic hurricanes and tropical storms has 

increased over the past few decades. SAP3.3 indicates that there is evidence for a human 

contribution to increased sea surface temperatures in the tropical Atlantic and there is a 

strong correlation to Atlantic tropical storm frequency, duration, and intensity. However, 

a confident assessment will require further studies. An increase in extreme wave heights 

1 - 13 
SAP 4.6 Chapter 1: Introduction

in the Atlantic since the 1970s has been observed: consistent with more frequent and 

intense hurricanes (CCSP, 2008). 

For North Atlantic hurricanes, SAP3.3 concludes that it is likely that wind speeds and 

core rainfall rates will increase (Henderson-Sellers et al., 1998; Knutson and Tuleya, 

2004, 2008; Emanuel, 2005). However, SAP3.3 concluded that “frequency changes are 

currently too uncertain for confident projection” (CCSP, 2008). SAP3.3 also found that 

the spatial distribution of hurricanes will likely change. Storm surge is likely to increase 

due to projected sea level rise, though the degree to which these will increase has not 

been adequately studied (CCSP, 2008). 

1.3 Population Trends and Migration Patterns: A Context for 

Assessing Climate-related Impacts

Assessments of climate-related risk must account for the size of the population, including 

especially sensitive sub-populations, and their geographic distribution across the 

landscape. The following discussion provides a basis for assessing the interactions of 

global change within the larger context of demographic trends. In particular, the social 

characteristics of a populace may interact with its spatial distribution to produce a nonlinear risk. In such instances, risk assessments are shaped by questions such as: 

 Which counties, states, and regions will grow most rapidly? 

 How many people will live in at-risk areas, such as coastal zones, flood plains, 

and arid areas? 

 What share of retirees will migrate and where will they move? 

1.3.1 Trends in Total U.S. Population 

The US population numbered some 280 million individuals in 2000.1

 In 1900, the US 

population numbered about 76 million people; fifty years later the population had roughly 

doubled to 151 million people. 

Population projections are estimates of the population at future dates. They are based on 

assumptions about future births, deaths, international migration, and domestic migration 

and represent plausible scenarios of future population. 

In 2000 the IPCC published a set of emission scenarios for use in the Third Assessment 

Report (Nakicenovic et al., 2000). The SRES scenarios were constructed to explore 

future developments in the global environment with special reference to the production of 

greenhouse gases and aerosol precursor emissions. The SRES team defined four narrative 

storylines labeled A1, A2, B1 and B2, describing the relationships between the forces 

driving greenhouse gas and aerosol emissions and their evolution during the 21st century 

for large world regions and globally. Each storyline represents different demographic, 

social, economic, technological, and environmental developments that diverge in 

increasingly irreversible ways. (Nakicenovic et al., 2000) 

 

1

 Information on historical US population data and current population estimates and projections can be 

found at http://www.census.gov/. 

1 - 14 
SAP 4.6 Chapter 1: Introduction

The US Census Bureau periodically releases projections for the resident population of the 

United States based on Census data. The cohort-component methodology2

 is used in 

these projections. Alternative assumptions of fertility, life expectancy, and net 

immigration yield low, middle and high projections. 

Figure 1.2 displays the SRES and Census population projections3 for the US. The Census 

projections span a greater range than the SRES scenarios: by 2100 the low series 

projection of 282 million is below the current population while the high projection is 

about 1.2 billion, or about four times the current population. The Census middle series 

projection is relatively close to the SRES A2 scenario (570 million vs. 628 million in 

2100), while the SRES A1/B1 and B2 scenarios fall below the Census middle projection. 

Figure 1.2 US Population Projections 2000-2100 

1.3.1.1 Aging of the Population 

The US population has not simply increased by 300% over the past century, it has also 

shifted in its demographic structure. For example, in 1900 less than 4% of the US 

population was 65 years or older; currently about 12% of Americans are 65 or older (He 

et al., 2005). By 2050, the US population aged 65 and older is projected to be about 86 

million, or about 21% of the total population. Nearly 5% of the projected population in 

2050, over 20 million people, will be 85 years or older (He et al., 2005). Figure 1.3 

displays the projected age distribution for the total resident population of the United 

States by sex for the middle projection series. 

Figure 1.3 Population Pyramids of the US 2000 and 2050 (Interim Projections based on 

2000 Census)

The projected increase in the elderly population is an important variable in projections of 

the effects of climate change. The elderly are identified in many health assessments as 

more vulnerable than younger age groups to a range of health outcomes associated with 

climate change, including injury resulting from weather extremes such as heatwaves, 

storms and floods (WHO, 2003; IPCC, 2007b; NAST, 2001). Aging also can be expected 

to be accompanied by multiple, chronic illnesses that may result in increased 

vulnerability to infectious disease (NAST, 2001). Chapter two in this report also 

identifies the elderly as a vulnerable subpopulation. 

1.3.2 Migration Patterns 

Although numbers produced by population projections are important, the striking 

relationship between potential future settlement patterns and the areas that may 

experience significant impacts of climate change is the critical insight. In particular, 

nearly all trends point to more Americans living in areas that may be especially 

vulnerable to the effects of climate change (see Figure 1.4). For example, many rapidly 

 

2

 See Census web-site for additional details on the projection methodology. 

3

 The Census projections are based on the 1990 Census. Preliminary projections based on the 2000 Census 

for 2000-2050 are available. 

1 - 15 
SAP 4.6 Chapter 1: Introduction

growing places in the Mountain West may also experience decreased snow pack during 

winter and earlier spring melting, leading to lower stream flows, particularly during the 

high-demand period of summer. 

The continued growth of arid states in the West is therefore a critical crossroads for 

human settlements and climate change. These states are expected to account for one-third 

of all U.S. population growth over the next 25 years (US Census Bureau, 2005). The 

combined effects of growing demand for water due to a growing population and changes 

in water supplies associated with climatic change pose important challenges for these 

states. For example, a study commissioned by the California Energy Commission 

estimated that the Sierra Mountain snow pack could be reduced by 12% to 47% by 2050 

(Cayan et al., 2006). At the same time, state projections anticipate an additional 20 

million Californians by that date (California Department of Finance, 2007). 

Figure 1.4: U.S. Population and Growth Trends with evidence of more pronounced 

growth projected along the coasts, in urban centers, and in cities in the South and West 

(NAST, 2001)

Growth in coastal population has kept pace with population growth in other parts of the 

country, but given the small land area of the coasts, the density of coastal communities 

has been increasing (Crossett et al., 2004). Over 50% of the US population now lives in 

the coastal zone, and coastal areas are projected to continue to increase in population, 

with associated increases in population density, over the next several decades. The 

overlay of this migration pattern with climate change projections has several 

implications. Perhaps the most obvious is the increased exposure of people and property 

to the effects of sea level rise and hurricanes (Kunkel et al., 1999). With rapidly growing 

communities near coastlines, property damages would be expected to increase even 

without any changes in storm frequency or intensity (Changnon et al., 2003). 

1.3.2.1 How Climate Impacts Migration Patterns 

It is often said that Americans are a nation of movers and data collected for both the 1990 

and 2000 Census support this notion. While roughly half of the U.S. population had lived 

in the same house for the previous five years, nearly 10% had recently moved from out of 

state.4

 In other words, during the five year period preceding each Census, over 20 

million Americans had moved across state lines and half of those moved to different 

regions. 

Although many forces shape domestic migration, climate is a key element of perceived 

quality of life. In turn, quality of life can be an important factor driving the relocation 

decisions of households and businesses. The popularity of the Places Rated Almanac and 

other publications ranking cities’ livability illustrates the concept’s importance. 

Additionally, many of the indicators in these reports are based directly on climatic 

conditions (average winter and summer temperature, precipitation, days of sunshine, 

humidity, etc.). 

 

4

 http://www.census.gov/Press-Release/www/2002/sumfile3.html 

1 - 16 
SAP 4.6 Chapter 1: Introduction

A range of studies have attempted to quantify how natural amenities, including a 

favorable climate, affect migration. While the methods vary5

 the conclusions are similar. 

In general: 

 People move for a variety of reasons other than climate, such as: proximity to 

family and friends, employment opportunities, lower cost of living, and aesthetics, 

 Areas with natural amenities that are close to urban centers have attracted the 

largest numbers of in-migrants (Serow, 2001); 

 Climate’s impact on migration varies by income with lower income groups also 

moving to colder areas in which their wages are likely to compare more favorably 

to the cost of living (Rebhun and Raveh, 2006); 

 For retirees, weather is a far more important rationale cited for moving out of an 

area than moving to an area (AARP, 2006); and, 

 Population growth in rural counties is strongly related to a more favorable climate 

and other key natural amenities (McGranahan, 1999). In addition, new 

information technologies may make it possible for some urban dwellers to move 

to and work from rural regions. 

1.4. Complex Linkages: The Role of Non-climate Factors 

Climate is only one of a number of global changes that affect human well-being. These 

non-climate processes and stresses interact with climate change, determining the overall 

severity of climate impacts. Moreover, climate change impacts can spread from directly 

impacted areas and sectors to other areas and sectors through extensive and complex 

linkages (IPCC, 2007b). Evaluating future climate change impacts therefore require 

assumptions, explicit and implicit, about how future socioeconomic conditions will 

develop. The IPCC (1994) recommends the use of socioeconomic scenarios in impacts 

assessments to capture in a consistent way these factors. 

Socioeconomic scenarios have tended to focus on variables such as population and 

measures of economic activity (e.g., Gross Domestic Product) that can be quantified 

using well-established models or methods (for examples of economic models which have 

been used for long run projections, see Nakicenovic et al., 2000; NAST 2001; Yohe et 

al., 2007). While useful as a starting point, some key socioeconomic factors may not 

allow this type of quantification: they could however be incorporated through a 

qualitative, “storyline” approach and thus yield a more fully developed socioeconomic 

scenario. The UNEP country study program guidance (Tol, 1998) notes the role of formal 

modeling in filling in (but not defining) socioeconomic scenarios but also emphasizes the 

role of expert judgment in blending disparate elements into coherent and plausible 

scenarios. Generally socioeconomic scenarios have been developed in situations where it 

is not possible to assign levels of probability to any particular future state of the world 

and therefore it usually is not appropriate to make confidence statements with respect to a 

specific socioeconomic scenario (Moss and Schneider, 2000). 

 

5

 Study methodologies include: aggregate studies of population changes alongside regional characteristics, 

explanatory models developed from individual migration data and individual surveys. 

1 - 17 
SAP 4.6 Chapter 1: Introduction

Socioeconomic scenarios include non-environmental factors that influence exposures, 

vulnerability and impacts. Factors that may be incorporated into a scenario include: 

 Population (e.g., demographics, immigration, domestic migration patterns); 

 Economic status (income, prices); 

 Technology (e.g., pesticides, vaccines, transportation modes, wireless 

communications); 

 Infrastructure (e.g., water treatment plants, sewers, and drinking water systems; 

public health systems; roads, rails and bridges; flood control structures); 

 Human capital and social context and behaviors (e.g., skills and knowledge, social 

networks, lifestyles, diet); and, 

 Institutions (legislative, social, managerial). 

These factors are important both for characterizing potential effects of a changing climate 

on human health, settlements and welfare and for evaluating the ability of the US to adapt 

to climate change. 

1.4.1 Economic Status 

The US is a developed economy with GDP approaching $14 trillion and per capita 

income of $38,611 in 2007 (US BEA, 2008). The US economy has large private and 

public sectors, with strong emphasis on market mechanisms and private ownership 

(Christensen et al., 2007). A nation’s economic status clearly is important for 

determining vulnerability to climate change: wealthy nations have the economic 

resources to invest in adaptive measures and bear the costs of impacts and adaptation 

thereby reducing their vulnerability (WHO, 2003; IPCC, 2001). With the aging of the 

population (described in Section 1.3.1.1) however, the costs of health care are likely to 

rise over the coming decades (Christensen et al., 2007). Moreover, if the trend toward 

globalization continues through the 21st century, markets, primary factors of production, 

ownership of assets, and policies and governance will become more international in 

outlook (Stiglitz, 2002). Unfortunately, there has been little research to understand how 

these economic trends interact with climate change to affect vulnerability (i.e., whether 

they facilitate or hinder adaptation to climate change in the US). 

1.4.2 Technology 

The past half-century has seen stunning levels of technological advancement in the 

United States which has done much to improve American standards of living. The 

availability and access to technology at varying levels, in key sectors such as energy, 

agriculture, water, transportation and health is a key component to understanding 

vulnerability to climate change. Many technological changes, both large and small, have 

reduced American’s vulnerability to climate change (NAST, 2001). Improved roads and 

automobiles, better weather and climate forecasting systems, computers and wireless 

communication, new drugs and vaccines, better building materials, more efficient energy 

production – the list is very long indeed– have contributed to America’s material well 

being while reducing vulnerability to climate. Many of the adaptive strategies that are 

currently deployed that protect human beings from climate involve technology (e.g.,

warning systems, air conditioning and heating, pollution controls, building design, storm 

1 - 18 
SAP 4.6 Chapter 1: Introduction

shelters, vector control, water treatment and sanitation) (WHO, 2003). Continued 

advances in technology in the 21st century can increase substantially our ability to cope 

with climate change (IPCC, 2007a; USGCRP, 2001). 

However, it will be important to assess risks from proposed technological adaptations to 

avoid or mitigate adverse effects (i.e., maladaptation) (Patz, 1996; Klein and Tol, 1997). 

For example, if new pesticides are used to control disease vectors their effects on human 

populations, insect predators, and insect resistance to pesticides need to be considered 

(Scheraga and Grambsch, 1998; Gubler et al., 2001). 

In addition, technological change can interact in complex ways with other socioeconomic 

factors (e.g., migration patterns) and affect vulnerability to climate change. For example, 

advances in transportation technology – electric streetcars, freight trucks, personal 

automobiles, and the interstate highway system – have fueled the decentralization of 

urban regions (Hanson and Giuliano 2004; Garreau 1991; Lang 2003). More recently, the 

rapid development of new information technologies, such as the internet, have made 

previously remote locations more accessible for work, recreation, or retirement. Whether 

these developments increase or decrease vulnerability is unknown, but they do indicate 

the need for socioeconomic scenarios to better characterize the complex linkages between 

climate and non-climate factors in order evaluate vulnerability. 

1.4.3 Infrastructure 

Communities have reduced, and can further reduce, their vulnerability to adverse climate 

effects through investments in infrastructure. For example, water resources in the US 

have been modified and intensively managed over the years, partly in response to climate 

variability (Cohan and Miller, 2001). These investments range from small, privately 

constructed impoundments, water diversions and levees to major projects constructed by 

federal and state governments. Public health infrastructures, such as sanitation facilities, 

waste water treatment, and laboratory buildings reduce climate change health risks 

(Grambsch and Menne, 2003). Coastal communities have developed an array of systems 

to manage erosion and protect against flooding (see SAP 4.1 for an extensive discussion). 

More generally infrastructure such as roads, rails and bridges, water supply systems and 

drainage, mass transit and buildings can reduce vulnerability (Grambsch and Menne, 

2003). 

However, infrastructure can increase vulnerability if its presence encourages people to 

locate in more vulnerable areas. For example, increasing the density of people in coastal 

metropolitan areas, dependent on extensive fixed infrastructure, can increase 

vulnerability to extreme events such as floods, storm surges and heat waves (NAST, 

2001). In assessments of severe storms, measures of property damage are consistently 

higher and loss of life lower in the US when compared with less-developed countries 

(Cohan and Miller, 2001), reflecting both the high level of development in coastal zones 

and the effectiveness of warnings and emergency preparedness (Pielke and Pielke, 1997). 

Fixed infrastructure itself has the potential to be adversely impacted by climate change, 

which can increase vulnerability to climate change. For example, flooding can 

1 - 19 
SAP 4.6 Chapter 1: Introduction

overwhelm sanitation infrastructure and lead to water-related illnesses (Grambsch and 

Menne, 2003). Much of the transportation infrastructure in the Gulf Coast has been 

constructed on land at elevations below 16.4 ft: storm surge, therefore poses risks of 

immediate flooding of infrastructure and damage caused by the force of floodwaters (see 

SAP 4.7 for additional information on the vulnerability of Gulf Coast transportation 

infrastructure to climate change). Damage to transportation infrastructure can make it 

more difficult to assist affected populations (Grambsch and Menne, 2003). 

1.4.4 Human and Social Capital and Behaviors 

While these factors are extremely difficult to quantify, much less project into the future, 

they are widely perceived to be important in determining vulnerability in a number of 

different ways. In general, countries with higher levels of “human capital” or knowledge 

are considered to be less vulnerable to climate change. Effective adaptation will require 

individuals skilled at recognizing, reporting and responding to climate change effects. 

Moreover, a number of the adaptive measures described in the literature require 

knowledgeable, trained and skilled personnel to implement them. For example, skilled 

public health managers, who understand surveillance and diagnostic information, will be 

needed to mobilize appropriate responses. People trained in the operation, quality control 

and maintenance of laboratories, communications equipment, and sanitation, wastewater, 

and water supply systems are also key (Grambsch and Menne, 2003). Researchers and 

scientists spanning a broad range of disciplines will be needed to provide a sound basis 

for adaptive responses. 

In addition to a countries’ human capital (i.e., the knowledge, experience and expertise of 

its citizens) the relationships, exchange of resources and knowledge, and the levels of

trust and conflicts between individuals (i.e., “social capital”) are also important for 

understanding future vulnerability to climate change (Adger, 2003; Lehtonen, 2004; 

Pelling and High, 2005). Social networks can play an important role in coping and 

recovery from extreme weather events (Adger, 2003). For example, individuals who were 

socially isolated were found to be a greater risk of dying from extreme heat (Semenza et 

al., 1996), as well as people living in neighborhoods without public gathering places and 

active street life (Klinenberg, 2002). 

Individual behaviors and responses to changing conditions also determine vulnerability. 

For example, fitness, body composition, and level of activity are among the factors that 

determine the impact extremely hot weather will have on the human body (see Chapter 2 

for additional information). Whether this trend continues or not could have important 

implications for determining vulnerability to climate change. Individual responses and 

actions to reduce their exposures to extreme heat can also substantially ameliorate 

adverse health impacts (McGeehin and Mirabelli, 2001). Successfully motivating 

individuals to respond appropriately can therefore decrease vulnerability and reduce 

health impacts -- a key goal of public health efforts (McGeehin and Mirabelli, 2001). 

1.4.5 Institutions 

The ability to respond to climate change and reduce vulnerability is influenced by social 

institutions as well as the social factors noted above. Institutions are viewed broadly in 

1 - 20 
SAP 4.6 Chapter 1: Introduction

the climate change context and include a wide diversity of things such as regulations, 

rules and norms that guide behavior. Examples include past development and land use 

patterns, existing environmental and coastal laws; building codes, and legal rights. 

Institutions also can determine a decision-maker’s access to information and the ways in 

which the information can be used (Moser et al., 2007). 

Well-functioning institutions are essential to a modern society and provide a mechanism 

for stability in otherwise volatile environments (Moser et al., 2007). Future options for 

responding to future climate impacts are thus shaped by our past and present institutions 

and how they evolve over time. In addition, the complex interaction of issues expected 

with climate change may require new arrangements and collaborations between 

institutions to address risks effectively, thereby enhancing adaptive capacity (Grambsch 

and Menne, 2003). A number of institutional changes have been identified that improve 

adaptive capacity and reduce vulnerability (see Chapter 3 for additional details). While 

the importance of institutions is clear, there are few scenarios which incorporate an 

explicit representation of them. 

1.4.6 Interacting Effects 

The same social and economic systems that bear the stress of climate change also bear 

the stress of non-climate factors, including: air and water pollution, the influx of 

immigrants, and an aging and over-burdened infrastructure in rapidly-growing 

metropolitan centers and coastal zones. While non-climate stressors are currently more 

pronounced than climate impacts, one cannot assume that this trend will persist. 

Understanding the impacts of climate change and variability on health and quality of life 

assumes knowledge of how these dynamics might vary by location and across time and 

socioeconomic group. The effects of climate change often spread from directly affected 

areas and sectors to other areas and sectors through complex linkages. The relative 

importance of climate change depends on the directness of each climate impact and on 

demographic, social, economic, institutional, and political factors, including, the degree 

of emergency preparedness. 

Consider the damage left by Hurricanes Katrina and Rita in 2005. Damage was measured 

not only in terms of lives and property lost, but also in terms of the devastating impacts 

on infrastructure, neighborhoods, businesses, schools, and hospitals as well as in the 

disruption to families and friends in established communities, with lost lives and lost 

livelihoods, challenges to psychological well-being, and exacerbation of chronic 

illnesses. While the aftermath of a single hurricane is not the measure of climate change, 

such an event demonstrates the disruptive power of climate impacts and the resulting 

tangle of climate and non-climate stressors that complicate efforts to respond and to 

adapt. Certainly, the impacts following these hurricanes reveal that socioeconomic factors 

and failures in human systems may be as damaging as the storms themselves. 

Another trend of significance for climate change is the suburbanization of poverty. A 

recent study noted that by 2005 the number of low income households living in suburban 

communities had for the first time surpassed the number living in central cities (Berube 

and Kneebone, 2006). Although the poverty rate in cities was still double the suburban 

rate, there were 1 million more people living in poverty in America’s suburbs. Many of 

1 - 21 
SAP 4.6 Chapter 1: Introduction

these people live in older inner-ring suburbs developed in the 1950’s and 60’s. The 

climate adaptation challenge for these places is captured succinctly by a recent study: 

“Neither fully urban nor completely suburban, America's older, inner-ring, "first" suburbs 

have a unique set of challenges—such as concentrations of elderly and immigrant 

populations as well as outmoded housing and commercial buildings—very different from 

those of the center city and fast growing newer places. Yet first suburbs exist in a policy 

blind spot with little in the way of state or federal tools to help them adapt to their new 

realities” (Puentes and Warren, 2006). 

1.5 Reporting Uncertainty in SAP 4.6 

Uncertainty can be traced to a variety of sources: (1) a misspecification of the cause(s), 

such as the omission of a causal factor resulting in spurious correlations; (2) 

mischaracterization of the effect(s), such as a model that predicts cooling rather than 

warming; (3) absence of or imprecise measurement or calibration (such as devices that 

fail to detect minute causal agents); (4) fundamental stochastic (chance) processes; (5) 

ambiguity over the temporal ordering of cause and effect; (6) time delays in cause and 

effect; and, (7) complexity where cause and effect between certain factors are 

camouflaged by a context with multiple causes and effects, feedback loops, and 

considerable noise. 

A new perspective on the treatment of uncertainty has emerged from the IPCC Third and 

Fourth Assessment processes6. This new perspective suggests that uncertainties about 

projections of climate changes, impacts, and responses include two fundamentally 

different dimensions. One dimension recognizes that most processes and systems being 

observed are characterized by inherent variability in outcomes: the more variable the 

process or system, the greater the uncertainty associated with any attempt to project an 

outcome. A second dimension recognizes limitations in our knowledge about processes 

and systems. 

This report is a summary of the state of the science on the impacts of climate change on 

human health, human settlements and human welfare. With this focus, the assessment of 

uncertainty in this report is based on the literature and the author team’s expert judgment. 

The considerations in determining confidence include the degree of belief within the 

scientific community that available understanding, models, and analyses are accurate, 

expressed by the degree of consensus in the available evidence and its interpretation. This 

can be thought of using two different dimensions related to consensus. Figure 1.5 

represents the qualitatively defined levels of understanding. It considers both the amount 

of evidence available in support of findings and the degree of consensus among experts 

on its interpretation. 

 

6

 SAP4.6 follows the Guidance Notes for Lead Authors of the IPCC Fourth Assessment Report on 

Addressing Uncertainties, produced by the IPCC in July 2005. See http://www.ipcc.ch/pdf/supportingmaterial/uncertainty-guidance-note.pdf for more details. 

1 - 22 
SAP 4.6 Chapter 1: Introduction

Figure 1.5 Considerations in determining confidence 

In this report, each chapter author team assigned likelihood judgments that reflect their 

assessments of the current consensus of the science and the quality and amount of 

evidence. This represents their expert judgment that the given likelihood impact 

statement is likely to be true given a specified climatic change. The likelihood 

terminology and corresponding values used in this report are shown in Table 1.1. As the 

focus of this report is on impacts, it is important to note that these likelihood statements 

refer to the impact, not the underlying climatic changes, i.e., the report does not address 

whether the specific climatic change is likely to occur. Nor do the authors attempt an 

assessment that takes into account a probabilistic accounting of both the likelihood of the 

climatic change and the impact. The terms defined in Table 1.1 are intended to be used in 

a relative sense to summarize judgments of the scientific understanding relevant to an 

issue, or to express uncertainty in a finding where there is no basis for making more 

quantitative statements. 

The application of this approach to likelihood estimates demonstrates some variability 

across each of the three core chapters (Chapters 2-4). This variability in reporting 

uncertainty is based on the degree of richness of their respective knowledge bases. A 

relatively more extensive and specific application of likelihood and state of the 

knowledge estimates is possible for health impacts, only a more general approach is 

warranted for conclusions about human settlements, and uncertainty statements about 

human welfare conclusions are necessarily the least explicit. 

1 - 23 
SAP 4.6 Chapter 1: Introduction

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SAP 4.6 Chapter 1: Introduction

1.7 Tables 

Table 1.1 Description of likelihood: probabilistic assessment of outcome having occurred or 

occurring in the future based on quantitative analysis or elicitation of expert views. 

Likelihood Terminology Likelihood of the occurrence / outcome 

Virtually certain > 99% probability 

Very likely > 90% probability 

Likely > 66% probability 

About as likely as not 33 - 66% probability 

Unlikely < 33% probability 

Very unlikely < 10% probability 

Exceptionally unlikely < 1% probability 

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SAP 4.6 Chapter 1: Introduction

1.8 Figures 

Figure 1.1 Observed trends in annual average (a) temperature (oF) and (b) precipitation 

(inches) across the continental United States from 1896 to 2006 (Source: NCDC, 2007) 

50.5

51.0

51.5

52.0

52.5

53.0

53.5

54.0

54.5

55.0

55.5

1896 1916 1936 1956 1976 1996

Annual Avg Temperature (degF)

Source: NCDC, 2007

(a)

24

25

26

27

28

29

30

31

32

33

34

1896 1916 1936 1956 1976 1996

Annual Avg Precipitation (inches)

Source: NCDC, 2007

(b)

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SAP 4.6 Chapter 1: Introduction

Figure 1.2 US Population Projections 2000-2100 

0

100

200

300

400

500

600

700

800

900

1000

2000 2010 2020 2030 2040 2050 2060 2070 2080 2090 2100

In millions

Census 1990 low

Census 1990 mid

Census 1990 high

SRES A1, B1

SRES A2

SRES B2

Data sources: Census Population Projections http://www.census.gov/population/www/projections/natsumT1.html 

 SRES Population Projections: http://sres.ciesin.columbia.edu/tgcia/

1 - 38 
SAP 4.6 Chapter 1: Introduction

Figure 1.3 Population Pyramids of the US 2000 and 2050 (Interim Projections based on 2000 

Census) 

-5 -4 -3 -2 -1 0 1 2 3 4 5

 0 - 4

 5 - 9

 10-14

15 - 19

20 - 24

25 - 29

30 - 34

35 - 39

40 - 44

45 - 49

50 - 54

55 - 59

60 - 64

65 - 69

70 - 74

75 - 79

80 - 84

 85+

Male

Female

-5 -4 -3 -2 -1 0 1 2 3 4 5

Data source: Census Population Projections http://www.census.gov/ipc/www/usinterimproj/

1 - 39 
SAP 4.6 Chapter 1: Introduction

Figure 1.4: U.S. Population and Growth Trends with evidence of more pronounced growth 

projected along the coasts, in urban centers, and in cities in the South and West (NAST, 2001). 

1 - 40 
SAP 4.6 Chapter 1: Introduction

Figure 1.5 Considerations in determining confidence. 

High agreement, High agreement, High agreement, 

limited evidence medium evidence much evidence 

Level of 

agreement Medium agreement, Medium agreement, Medium agreement, (on a limited evidence medium evidence much evidence 

particular 

finding) 

Low agreement, Low agreement, Low agreement, 

limited evidence medium evidence much evidence 

Amount of evidence (number and quality of independent sources) 

Source: IPCC Guidance Notes on risk and uncertainty (2005) 

 

1 - 41 
Synthesis and Assessment Product 4.6 

Chapter 2: Effects of Global Change on Human Health 

Lead Author: Kristie L. Ebi, ESS, LLC 

Contributing Authors: John Balbus, Environmental Defense; Patrick L. Kinney, Columbia University; 

Erin Lipp, University of Georgia; David Mills, Stratus Consulting; Marie S. O’Neill, University of Michigan; 

Mark Wilson, University of Michigan 

2-1 
SAP 4.6 Chapter 2: Human Health 

Table of Contents 

2.1 Introduction ............................................................................................................................................ 3

2.2 Observed Climate-Sensitive Health Outcomes in the United States............................................... 4

2.2.1 Thermal Extremes: Heat Waves........................................................................................................ 4

2.2.2 Thermal Extremes: Cold Waves..................................................................................................... 6

2.2.3 Extreme Events: Hurricanes, Floods, and Wildfires ........................................................................ 6

2.2.4 Indirect Health Impacts of Climate Change ................................................................................... 8

2.3 Projected Health Impacts of Climate Change in the United States................................................. 15

2.3.1 Heat-Related Mortality................................................................................................................. 15

2.3.2 Hurricanes, Floods, Wildfires and Health Impacts ....................................................................... 17

2.3.3 Vectorborne and Zoonotic Diseases ............................................................................................ 18

2.3.4 Water- and Foodborne Diseases .................................................................................................. 18

2.3.5 Air Quality Morbidity and Mortality ............................................................................................ 19

2.4 Vulnerable Regions and Subpopulations........................................................................................... 22

2.4.1 Vulnerable Regions....................................................................................................................... 23

2.4.2 Specific Subpopulations at Risk.................................................................................................... 23

2.5 Adaptation ......................................................................................................................................... 26

2.5.1 Actors and Their Roles and Responsibilities for Adaptation ........................................................ 27

2.5.2 Adaptation Measures to Manage Climate Change-Related Health Risks ..................................... 29

2.6 Conclusions .......................................................................................................................................... 29

2.7 Expanding the Knowledge Base ......................................................................................................... 30

2.8 References ............................................................................................................................................ 32

2.9 Boxes..................................................................................................................................................... 57

2.10 Tables................................................................................................................................................... 61

2.11 Figures ................................................................................................................................................. 72

2-2 
SAP 4.6 Chapter 2: Human Health 

 

2.1 Introduction 

Climate change can affect health directly and indirectly. Directly, extreme weather events 

(floods, droughts, windstorms, fires, and heatwaves) can affect the health of Americans 

and cause significant economic impacts. Indirectly, climate change can alter or disrupt 

natural systems, making it possible for vector, water-, and foodborne diseases to spread 

or emerge in areas where they had been limited or not existed, or for such diseases to 

disappear by making areas less hospitable to the vector or pathogen (NRC, 2001). 

Climate also can affect the incidence of diseases associated with air pollutants and 

aeroallergens.1 (Bernard et al., 2001) The cause-and-effect chain from climate change to 

changing patterns of health outcomes is often complex and includes factors such as initial 

health status, financial resources, effectiveness of public health programs, and access to 

medical care. Therefore, the severity of future impacts will be determined by changes in 

climate as well as by concurrent changes in nonclimatic factors and by adaptations 

implemented to reduce negative impacts. 

A comprehensive assessment of the potential impacts of climate change on human health 

in the United States was published in 2000. This First National Assessment was 

undertaken by the U.S. Global Change Research Program. The Health Sector Assessment 

examined potential impacts and identified research and data gaps to be addressed in 

future research; results appeared in a special issue of Environmental Health Perspectives

(May 2001). The Health Sector Assessment’s conclusions on the potential health impacts 

of climate change in the United States included: 

 Populations in Northeastern and Midwestern U.S. cities are likely to experience 

the greatest number of illnesses and deaths in response to changes in summer 

temperatures (McGeehin and Mirabelli, 2001). 

 The health impacts of extreme weather events hinge on the vulnerabilities and 

recovery capabilities of the natural environment and the local population 

(Greenough et al., 2001). 

 If the climate becomes warmer and more variable, air quality is likely to be 

affected (Bernard et al., 2001). However, uncertainties in climate models make 

the direction and degree of change speculative (Bernard and Ebi, 2001). 

 Federal and state laws and regulatory programs protect much of the U.S. 

population from waterborne disease. However, if climate variability increases, 

current and future deficiencies in areas such as watershed protection, 

infrastructure, and storm drainage systems will probably increase the risk of 

contamination events (Rose et al., 2000). 

 It is unlikely that vector- and rodent-borne diseases will cause major epidemics in 

the United States if the public health infrastructure is maintained and improved 

(Gubler et al., 2001). 

 Multiple uncertainties preclude any definitive statement on the direction of 

potential future change for each of the health outcomes assessed (Patz et al., 

2000). 

1

 Any of various airborne substances, such as pollen or spores, that can cause an allergic response. 

2-3 
SAP 4.6 Chapter 2: Human Health 

The assessment further concluded that much of the U.S. population is protected against 

adverse health outcomes associated with weather and/or climate by existing public health 

and medical care systems, although certain populations are at increased risk. 

This chapter of Synthesis Assessment Product 4.6 updates the Health Sector Assessment. 

It also examines adaptation strategies that have been or are expected to be developed by 

the public health community in response to the challenges and opportunities posed by 

climate change. The first section of this chapter focuses on climate-related impacts on 

human morbidity and mortality from extreme weather, vector-, water- and foodborne 

diseases, and changes in air quality. For each health endpoint, the assessment addresses 

the potential impacts, populations that are particularly vulnerable, and research and data 

gaps that, if bridged, would allow significant advances in future assessments of the health 

impacts of global change. The assessment includes research published from 2001 through 

early 2007 in the United States or in Canada, Europe, and Australia, where results may 

provide insights for U.S. populations. 

This chapter summarizes the current burden of climate-sensitive health determinants and 

outcomes for the United States, before assessing the potential health impacts of climate 

change. Two types of studies are assessed. Studies that increase our understanding of the 

associations between weather variables and health outcomes raise possible concerns 

about the impacts of a changing climate. A few studies project the burden of health 

outcomes using scenarios of socioeconomic and climate change. 

It is important to note that the assessment focuses on how climate change could affect the 

future health of Americans. However, the net impact of any changes will depend on many 

other factors, including demographics; population and regional vulnerabilities; the future 

social, economic, and cultural context; availability of resources and technological 

options; built and natural environments; public health infrastructure; and the availability 

and quality of health and social services. 

The chapter then turns to adaptation to the potential health impacts of environmental 

change in the United States. It also considers public health interventions (including 

prevention, response, and treatment strategies) that could be revised, supplemented, or 

implemented to protect human health in response to the challenges and opportunities 

posed by global change; and how much adaptation could achieve. 

2.2 Observed Climate-Sensitive Health Outcomes in the United 

States 

2.2.1 Thermal Extremes: Heat Waves

Excess deaths occur during heatwaves, on days with higher-than-average temperatures, 

and in places where summer temperatures vary more or where extreme heat is rare (Braga 

et al., 2001). Figure 2.1 illustrates that the relation between temperature and mortality is 

nonlinear, typically J- or U-shaped, and that increases in mortality occur even below 

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temperatures considered to be extremely hot. This figure was created using log-linear 

regression to analyze 22 years of data on daily mortality and outdoor temperature in 

eleven U.S. cities (Curriero et al., 2002). Exposure to excessive natural heat caused a 

reported 4,780 deaths during the period 1979 to 2002, and an additional 1,203 deaths had 

hyperthermia reported as a contributing factor (CDC, 2005). These numbers are 

underestimates of the total mortality associated with heatwaves because the person filling 

out the death certificate may not always list heat as a cause. Furthermore, heat can 

exacerbate chronic health conditions, and several analyses have reported associations 

with cause-specific mortality, including cardiovascular, renal, and respiratory diseases; 

diabetes; nervous system disorders; and other causes not specifically described as heatrelated (Conti et al., 2007; Fouillet et al., 2006; Medina-Ramon et al., 2006). Among the 

most well-documented heatwaves in the United States are those that occurred in 1980 (St. 

Louis and Kansas City, Missouri), 1995 (Chicago, Illinois), and 1999 (Cincinnati, Ohio; 

Philadelphia, Pennsylvania; and Chicago, Illinois). The highest death rates in these 

heatwaves occurred in people over 65 years of age. 

Less information exists on temperature-related morbidity, and those studies that have 

examined hospital admissions and temperature have not seen consistent effects, either by 

cause or by demonstrated coherence with mortality effects where both deaths and 

hospitalizations were examined simultaneously (Kovats et al., 2004; Michelozzi et al.,

2006; Schwartz et al., 2004; Semenza et al., 1999). 

Age, fitness, body composition, and level of activity are important determinants of how 

the human body responds to exposure to thermal extremes (DeGroot et al., 2006; 

Havenith et al., 1995; Havenith et al., 1998; Havenith, 2001). Groups particularly 

vulnerable to heat-related mortality include the elderly, very young, city-dwellers, those 

with less education, people on medications such as diuretics, the socially isolated, the 

mentally ill, those lacking access to air conditioning, and outdoor laborers (Diaz et al.,

2002; Klinenberg, 2002; McGeehin and Mirabelli, 2001; Semenza et al., 1996; Whitman 

et al., 1997; Basu et al., 2005; Gouveia et al., 2003; Greenberg et al., 1983; O'Neill et al.,

2003; Schwartz, 2005; Jones et al., 1982; Kovats et al., 2004; Schwartz et al., 2004; 

Semenza et al., 1999; Watkins et al., 2001). A sociological analysis of the 1995 Chicago 

heatwave found that people living in neighborhoods without public gathering places and 

active street life were at higher risk, highlighting the important role that community and 

societal characteristics can play in determining vulnerability (Klinenberg, 2002). 

Figure 2.1 Temperature-mortality relative risk functions for 11 U.S. cities, 1973–1994. 

Northern cities: Boston, Massachusetts; Chicago, Illinois; New York, New York; 

Philadelphia, Pennsylvania; Baltimore, Maryland; and Washington, DC. Southern cities: 

Charlotte, North Carolina; Atlanta, Georgia; Jacksonville, Florida; Tampa, Florida; and 

Miami, Florida. Relative risk is defined as the risk of an event such as mortality relative 

to exposure, such that the relative risk is a ratio of the probability of the event 

occurring in the exposed group versus the probability of occurrence in the control 

(non-exposed) group. 

Urban heat islands may increase heat-related health impacts by raising air temperatures in 

cities 2-10oF over the surrounding suburban and rural areas due to absorption of heat by 

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SAP 4.6 Chapter 2: Human Health 

dark paved surfaces and buildings, lack of vegetation and trees, heat emitted from 

buildings, vehicles, and air conditioners, and reduced air flow around buildings (EPA, 

2005; Pinho and Orgaz, 2000; Vose et al., 2004; Xu and Chen, 2004). However, in some 

regions, urban areas may not experience greater heat-related mortality than in rural areas 

(Sheridan and Dolney, 2003); few comparisons of this nature have been published. 

The health impacts of high temperatures and high air pollution can interact, with the 

extent of interaction varying by location (Bates, 2005; Goodman et al., 2004; Goodman 

et al., 2004; Keatinge and Donaldson, 2001; O'Neill et al., 2005; Ren et al., 2006). 

2.2.2 Thermal Extremes: Cold Waves 

From 1979 to 2002, an average of 689 reported deaths per year (range 417-1,021), 

totaling 16,555 over the period, were attributed to exposure to excessive cold 

temperatures (Fallico et al., 2005). Cold also contributes to deaths caused by respiratory 

and cardiovascular diseases, so the overall mortality burden is likely underestimated. 

Factors associated with increased vulnerability to cold include black race (Fallico et al.,

2005); living in Alaska, New Mexico, North Dakota, and Montana, or living in milder 

states that experience rapid temperature changes (North and South Carolina) and western 

states with greater ranges in nighttime temperatures (e.g., Arizona) (Fallico et al., 2005); 

having less education (O'Neill et al., 2003); being female or having pre-existing 

respiratory illness (Wilkinson et al., 2004); lack of protective clothing (Donaldson et al.,

2001); income inequality, fuel poverty, and low residential thermal standards (Healy, 

2003); and living in nursing homes (Hajat et al., 2007). 

Because climate change is projected to reduce the severity and length of the winter 

season (IPCC, 2007a), there is considerable speculation concerning the balance of 

climate change-related decreases in winter mortality compared with increases in summer 

mortality. Net changes in mortality are difficult to estimate because, in part, much 

depends on complexities in the relationship between mortality and the changes associated 

with global change. Few studies have attempted to link the epidemiological findings to 

climate scenarios for the United States, and studies that have done so have focused on the 

effects of changes in average temperature, with results dependent on climate scenarios 

and assumptions of future adaptation. Moreover, many factors contribute to winter 

mortality, making highly uncertain how climate change could affect mortality. No 

projections have been published for the United States that incorporate critical factors, 

such as the influence of influenza outbreaks. 

2.2.3 Extreme Events: Hurricanes, Floods, and Wildfires 

The United States experiences a wide range of extreme weather events, including 

hurricanes, floods, tornadoes, blizzards, windstorms, and drought. Other extreme events, 

such as wildfires, are strongly influenced by meteorological conditions. Direct morbidity 

and mortality due to an event increase with the intensity and duration of the event, and 

can decrease with advance warning and preparation. Health also can be affected 

indirectly. Examples include carbon monoxide poisonings from portable electric 

generator use following hurricanes (CDC, 2006b) and an increase in gastroenteritis cases 

among hurricane evacuees (CDC, 2005a). The mental health impacts (e.g., post traumatic 

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stress disorder, depression) of these events are likely to be especially important, but are 

difficult to assess (Middleton et al., 2002; Russoniello et al., 2002; Verger et al., 2003; 

North et al., 2004; Fried et al., 2005; Weisler et al., 2006). However, failure to fully 

account for direct and indirect health impacts may result in inadequate preparation for 

and response to future extreme weather events. 

Figure 2.2 shows the annual number of deaths attributable to hurricanes in the United 

States from the 1900 Galveston storm, (NOAA, 2006), records for the years 1940-2004 

(NOAA, 2005a), and a summary of a subset of the 2005 hurricanes (NOAA, 2007). The 

data shown are dominated by the 1900 Galveston storm and a subset of 2005 hurricanes, 

particularly Katrina and Rita, which together accounted for 1,833 of the 2,002 lives lost 

to hurricanes in 2005 (NOAA, 2007b). While Katrina was a Category 3 hurricane and its 

path was forecast well in advance, there was a secondary failure of the levee system. This 

illustrates that multiple factors contribute to making a disaster and that adaptation 

measures may not fully avert adverse consequences. 

From 1940 through 2005 roughly 4,300 lives were lost in the United States to hurricanes. 

The impact of the 2005 hurricane season is especially notable as it doubled the estimate 

of the average number of lives lost to hurricanes in the United States over the previous 65 

years. 

Figure 2.2 Annual Deaths Attributed to Hurricanes in the United States, 1900 and 

1940-2005

Figure 2.3 shows the annual number of deaths attributed to flooding in the United States 

from 1940-2005 (NOAA, 2007a). Over this period roughly 7,000 lives were lost. 

Figure 2.3 Annual Deaths Attributed to Flooding in the United States, 1940-2005 

A wildfire’s health risk is largely a function of the population in the affected area and the 

speed and intensity with which the wildfire moves through those areas. Wildfires can 

increase eye and respiratory illnesses due to fire-related air pollution. Climate conditions 

affect wildfire incidence and severity in the West (Westerling et al., 2003; Gedalof et al., 

2005; Sibold and Veblen, 2006). Between 1987-2003 and 1970-1986, there was a nearly 

fourfold increase in the incidence of large Western wildfires (i.e., fires that burned at 

least 400 hectares) (Westerling et al., 2006). The key driver of this increase was an 

average increase in springtime temperature of 0.87°C that affected spring snowmelt, 

subsequent potential for evapotranspiration, loss of soil moisture, and drying of fuels 

(Running, 2006; Westerling et al., 2006). Data providing a time-series summary of deaths 

similar to the data in Figures 2.2 and 2.3 was not identified. 

There is a rich body of literature detailing the mental health impacts of extreme weather 

events. Anxiety and depression, the most common mental health disorders, can be 

directly attributable to the experience of the event (i.e., being flooded) or indirectly 

during the recovery process (e.g., Gerrity and Flynn, 1997). These psychological effects 

tend to be much longer lasting and can be worse than the physical effects experienced 

during an event and its immediate aftermath. 

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Extreme events are often multi-strike stressors, with stress associated with the event 

itself; the disruption and problems of the recovery period; and the worry or anxiety about 

the risk of recurrence of the event (Tapsell et al., 2002). During the recovery period, 

mental health problems can arise from the problems associated with geographic 

displacement, damage to the home or loss of familiar possessions, and stress involved 

with the process of repairing. The full impact often is not appreciated until after people’s 

homes have been put back in order. For instance, in the aftermath of Hurricane Katrina in 

2005, mental health services in New Orleans were challenged by an increased incidence 

of serious mental illness, including anxiety, major depression, and post-traumatic stress 

disorder (PTSD). Shortly after Katrina, a Centers for Disease Control and Prevention poll 

found that nearly half of all survey respondents indicated a need for mental health care, 

yet less than 2% were receiving professional attention (Weisler et al., 2006). 

2.2.4 Indirect Health Impacts of Climate Change 

The observation that most vector-, water- or foodborne and/or animal-associated diseases 

exhibit a distinct seasonal pattern suggests a priori that weather and/or climate influence 

their distribution and incidence. The following sections differentiate between zoonotic 

and water- and foodborne diseases, although many water- and foodborne diseases are 

zoonotic. 

2.2.4.1 Vectorborne and Zoonotic (VBZ) Diseases 

Transmission of infectious agents by blood-feeding arthropods (particular insect or tick 

species) and/or by non-human vertebrates (certain rodents, canids, and other mammals) 

has changed significantly in the United States during the past century. Diseases such as 

rabies and cholera have become less widespread and diseases such as typhus, malaria, 

yellow fever, and dengue fever have largely disappeared, primarily because of 

environmental modification and/or socioeconomic development (Philip and Bozeboom, 

1973; Beneson, 1995; Reiter, 1996). While increasing average temperatures may allow 

the permissive range for Aedes aegypti, the mosquito vector of dengue virus, to move 

further north in the US, it is unlikely that more cases of dengue fever will be observed 

because most people are protected while living indoors due to quality housing. Indeed, a 

recent epidemic of dengue in southern Texas and northern Mexico produced many cases 

among the relatively poor Mexicans, and very few cases among Texans (Reiter et al.,

1999). At the same time, other diseases reported their distribution either because of 

suitable environmental conditions (including climate) or enhanced detection (examples 

include Lyme disease, ehrlichioses, and Hantavirus pulmonary syndrome) or were 

introduced and are expanding their range due to appropriate climatic and ecosystem 

conditions (West Nile Virus; e.g., Reisen et al., 2006). Still others are associated with 

non-human vertebrates that have complex associations with climate variability and 

human disease (e.g., plague, influenza). The burden of VBZ diseases in the United States 

is not negligible and may grow in the future because the forces underlying VBZ disease 

risk simultaneously involve weather/climate, ecosystem change, social and behavioral 

factors, and larger political-economic forces that are part of globalization. In addition, 

introduction of pathogens from other regions of the world is a very real threat. 

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Few original research articles on climate and VBZ diseases have been published in the 

United States and in other developed temperate countries since the First National 

Assessment. Overall, these studies provide evidence that climate affects the abundance 

and distributions of vectors that may carry West Nile virus, Western Equine encephalitis, 

Eastern Equine encephalitis, Bluetongue virus, and Lyme disease. Climate also may 

affect disease risk, but sometimes in counter-intuitive ways that do not necessarily 

translate to increased disease incidence (Wegbreit and Reisen, 2000; Subak, 2003; 

McCabe and Bunnell, 2004; DeGaetano, 2005; Purse et al., 2005; Kunkel et al., 2006; 

Ostfeld et al., 2006; Shone et al., 2006). Changes in other factors such as hosts, habitats, 

and human behavior are also important. 

2.2.4.2 Waterborne and Foodborne Diseases 

Water and foodborne diseases continue to cause significant morbidity in the United 

States. In 2002, there were 1,330 food-related disease outbreaks (Lynch et al., 2006), 34 

outbreaks from recreational water (2004), and 30 outbreaks from drinking water (2004) 

(Dziuban et al., 2006; Liang et al., 2006). For outbreaks of foodborne disease with 

known etiology, bacteria (Salmonella) accounted for 55% and viruses accounted for 33% 

(Lynch et al., 2006). Viral associated outbreaks rose from 16% in 1998 to 42% in 2002, 

primarily due to increases in norovirus (Lynch et al., 2006). In recreational water, 

bacteria accounted for 32% of outbreaks, parasites (primarily Cryptosporidium) for 24%, 

and viruses 10% (Dziuban et al., 2006). Similarly in drinking water outbreaks of known 

etiology, bacteria were the most commonly identified agent (29%, primarily 

Campylobacter), followed by parasites and viruses (each identified 5% of the time) (2003 

– 2004; Liang et al., 2006). Gastroenteritis continues to be the primary disease associated 

with food and water exposure. In 2003 and 2004, gastroenteritis was noted in 48% and 

68% of reported recreational and drinking water outbreaks, respectively (Dziuban et al., 

2006; Liang et al., 2006). 

Water- and foodborne disease remain highly underreported (e.g., Mead et al., 1999). Few 

people seek medical attention and of those that do, few cases are diagnosed (many 

pathogens are difficult to detect and identify in stool samples) or reported. Using a 

combination of underreporting estimates, passive and active surveillance data, and 

hospital discharge data, Mead et al. (1999) estimated that over 210 million cases of 

gastroenteritis occur annually in the United States, including over 900,000 

hospitalizations and over 6,000 deaths. More recently, Herikstad et al. (2002) estimated 

as many as 375 million episodes of diarrhea occur annually in the United States, based on 

a self-reporting study. These numbers far exceed previous estimates. Of the total 

estimated annual cases, just over 39 million can be attributed to a specific pathogen and 

approximately 14 million are transmitted by food (Mead et al., 1999). While bacteria 

continue to cause the majority of documented foodborne and waterborne outbreaks 

(Lynch et al., 2006; Liang et al., 2006), the majority of sporadic (non outbreak) cases of 

disease are caused by viruses (67%; primarily noroviruses), followed by bacteria (30%, 

primarily Campylobacter and Salmonella) and parasites (3%, primarily Giardia and 

Cryptosporidium). While the outcome of many gastrointestinal diseases is mild and self 

limiting, they can be fatal or significantly decrease fitness in vulnerable populations, 

including young children, the immunocompromised, and the elderly. Children ages 1-4 

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and older adults (>80 years) each make up more than 25% of hospitalizations involving 

gastroenteritis, but older adults contributed to 85% of the associated deaths (Gangarosa et 

al., 1992). As the U.S. population ages, the economic and public health burden of 

diarrheal disease will increase proportionally without appropriate interventions. 

Most pathogens of concern for food- and waterborne exposure are enteric and transmitted 

by the fecal-oral route. Climate may affect the pathogen directly by influencing its 

growth, survival, persistence, transmission, or virulence. In addition, there may be 

important interactions between land-use practices and climate variability. For example, 

incidence of foodborne disease associated with fresh produce is growing (FDA, 2001; 

Powell and Chapman, 2007). Storm events and flooding may result in the contamination 

of food crops (especially produce such as leafy greens and tomatoes) with feces from 

nearby livestock or feral animals. Therefore, changing climate or environments may alter 

the transmission of pathogens or affect the ecology and/or habitat of zoonotic reservoirs 

(NAS, 2001) 

Studies in North America (United States and Canada) (Fleury et al., 2006; Naumova et 

al., 2006), Australia (D’Souza et al., 2004), and several countries across Europe (Kovats 

et al., 2004a) report striking similarities in correlations between peak ambient 

temperatures (controlled for season) and peak in clinical cases of salmonellosis. Over this 

broad geographic range, yearly peaks in salmonellosis cases occur within 1 to 6 weeks of 

the highest reported ambient temperatures. Mechanisms suggested include replication in 

food products at various stages of processing (D’Souza et al., 2004; Naumova et al., 

2006) and changes in eating habits during warm summer months (i.e., outdoor eating) 

(Fleury et al., 2006). Additionally, because Salmonella are well adapted to both host 

conditions and the environment, they can grow readily even under low nutrient 

conditions at warm temperatures (e.g., in water and associated with fruits and vegetables) 

(Zhuang et al., 1995; Mouslim et al., 2002). Evidence supports the notion that increasing 

global temperatures will likely increase rates of salmonellosis; however, additional 

research is needed to determine the critical drivers behind this trend (i.e., intrinsic 

properties of the pathogen or extrinsic factors related to human behavior). 

The possible effects of increasing temperatures on Campylobacter infection rates and 

patterns cannot be reliably projected. The apparent seasonality of campylobacteriosis 

incidence is more variable than salmonellosis and temperature models are less consistent 

in their ability to account for the observed infection patterns. In the northeastern United 

States, Canada, and the U.K., Camplyobacter infection peaks coincide with high annual 

daily or weekly temperatures (Louis et al., 2005; Fleury et al., 2006; Naumova et al., 

2006). However, in several other European countries, campylobacteriosis rates peak 

earlier, before high annual temperatures, and in those cases temperature accounts for only 

4% of the interannual variability (Kovats, et al., 2005). Pathogenic species of 

Campylobacter cannot replicate in the environment and will not persist long under nonmicroaerophilic conditions, suggesting that high ambient temperatures would not 

contribute to increased replication in water or in food products. 

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Leptospirosis is a re-emerging disease in the United States and, given its wide case 

distribution, high number of pathogenic strains and wide array of hosts, it is often cited as 

one of the most widespread zoonotic disease in the world (Meites et al., 2004; WHO, 

1999). While it has not been a reportable disease nationally since 1995, several states 

continue to collect passive surveillance data and cases continue to be reported (Katz et 

al., 2002; Meites et al., 2004). Because increased disease rates are linked to warm 

temperatures, epidemiological evidence suggest that climate change may increase the 

number of cases. 

Pathogenic species of Vibrio (primarily V. vulnificus) account for 20% of sporadic 

shellfish-related illnesses and over 95% of deaths (Lipp and Rose 1997; Morris, 2003). 

While the overall incidence of illness from Vibrio infections remains low, the rate of 

infection increased 41% since 1996 (Vugia et al., 2006). Vibrio species are more 

frequently associated with warm climates (e.g., Janda et al., 1988; Lipp et al., 2002). 

Coincident with proliferation in the environment, human cases also occur during warm 

temperatures. In the US, the highest case rates occur in the summer months (Dziuban et 

al., 2006). Given the close association between temperature, the pathogen, and disease, 

increasing temperatures may increase the geographic range and disease burdens of Vibrio

pathogens (e.g., Lipp et al., 2002). For example, increasing prevalence and diversity of 

Vibrio species has been noted in northern Atlantic waters of the United States coincident 

with warm water (Thompson et al., 2004). Additionally, although most cases of V. 

vulnificus infection are attributed to Gulf Coast states, this species recently has been 

isolated from northern waters in the United States (Pfeffer et al., 2003; Randa et al., 

2004). 

The most striking example of an increased range in pathogen distribution and incidence 

was documented in 2004, when an outbreak of shellfish-associated V. parahaemolyticus

was reported from Prince William Sound in Alaska (McLaughlin et al., 2005). V. 

parahaemolyticus had never been isolated from Alaskan shellfish before and it was 

thought that Alaskan waters were too cold to support the species (McLaughlin et al., 

2005). In the period preceding the July 2004 outbreak, water temperatures in the 

harvesting area consistently exceeded 15o C and the mean daily water temperatures were 

significantly higher than in the prior six years (McLaughlin et al., 2005). This outbreak 

extended the northern range of oysters known to contain V. parahaemolyticus and cause 

illness by 1,000 km. Given the well-documented association between increasing sea 

surface temperatures and proliferation of many Vibrio species, evidence suggests that 

increasing global temperatures will lead to an increased burden of disease associated with 

certain Vibrio species in the United States, especially V. vulnificus and V. 

parahaemolyticus. 

Protozoan parasites, particularly Cryptosporidium and Giardia, contribute significantly to 

waterborne and to a lesser extent foodborne disease burdens in the United States. Both 

parasites are zoonotic and form environmentally resistant infective stages, with only 10-

12 oocysts or cysts required to cause disease. In 1998, 1.2 cases of cryptosporidiosis per 

100,000 people were reported in the United States (Dietz and Roberts, 2000); the 

immunocompromised are at particularly high risk (Casman et al., 2001; King and Monis, 

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2006). Between 2003 and 2004, of the 30 reported outbreaks of gastroenteritis from 

recreational water, 78.6% were due to Cryptosporidium and 14.3% were due to Giardia

(Dzuiban et al., 2006). Giardia has historically been the most commonly diagnosed 

parasite in the United States; between 1992 and 1997 there were 9.5 cases per 100,000 

people (Furness et al., 2000). Both Cryptosporidium and Giardia case reports peak in late 

summer and early fall, particularly among younger age groups (Dietz and Roberts, 2000; 

Furness et al., 2000). For both parasites, peak rates of reported infection in Massachusetts 

occurred approximately one month after the annual temperature peak (Naumova et al., 

2006). The lagged association between peak annual temperatures and peaks in reported 

cases in late summer has been attributed to increased exposure during the summer 

bathing season, especially in the younger age groups, and to a slight lag in reporting 

(Dietz and Roberts, 2000; Furness et al., 2000; Casman et al., 2001). With increasing 

global temperatures, an increase in recreational use of water can be reasonably expected 

and could lead to increased exposure among certain groups, especially children. 

Naegleria fowleri is a free-living amboeboflagellate found in lakes and ponds at warm 

temperatures, either naturally or in thermally polluted bodies of water. While relatively 

rare, infections are almost always fatal (Lee et al., 2002). N. fowleri can be detected in 

environmental waters at rates up to 50% (Wellings et al., 1977) at water temperatures 

above 25oC (Cabanes et al., 2001). Cases are consistently reported in the United States; 

between 1999 and 2000, four cases (all fatal) were reported. While N. fowleri continues 

to be a rare disease, it remains more common in the United States than elsewhere in the 

world (Marciano-Cabral et al., 2003). Given its association with warm water, elevated 

temperatures could increase this pathogen’s range. 

Epidemiologically significant viruses for food and water exposure include enteroviruses, 

rotaviruses, hepatitis A virus, and norovirus. Viruses account for 67% of foodborne 

disease, and the vast majority of these are due to norovirus (Mead et al., 1999). Rotavirus 

accounts for a much smaller fraction of viral foodborne disease (Mead et al., 1999), but is 

a significant cause of diarrheal disease among infants and young children (Charles et al., 

2006). Enteroviruses are not reportable and therefore incidence rates are poorly reflected 

in surveillance summaries (Khetsuriani et al., 2006). With the exception of hepatitis A 

(Naumova et al., 2006), enteric viral infection patterns follow consistent year to year 

trends. Enteroviruses are characterized by peaks in cases in the early to late summer 

(Khetsuriani et al., 2006), while rotavirus and norovirus infections typically peak in the 

winter (Cook et al., 1990; Lynch et al., 2006). No studies have been able to identify a 

clear role for temperature in viral infection patterns. 

An analysis of waterborne outbreaks associated with drinking water in the United States 

between 1948 and 1994 found that 51% of outbreaks occurred following a daily 

precipitation event in the 90th percentile and 68% occurred when precipitation levels 

reached the 80th percentile (Curriero et al., 2001) (Figure 2.4). Similarly, Thomas et al.,

(2006) found that the risk of waterborne disease doubled when rainfall amounts surpassed 

the 93rd percentile. Rose et al., (2000) found that the relationship between rainfall and 

disease was stronger for surface water outbreaks, but the association was significant for 

both surface and groundwater sources. In 2000, groundwater used for drinking water in 

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SAP 4.6 Chapter 2: Human Health 

Walkerton, Ontario was contaminated with E. coli O157:H7 and Campylobacter during 

rains that surpassed the 60-year event mark for the region and the 100-year event mark in 

local areas (Auld et al., 2004). In combination with preceding record high temperatures, 

2,300 people in a community of 4,800 residents became ill (Hrudey et al., 2003; Auld et 

al., 2004). 

Figure 2.4 Drinking Waterborne Disease Outbreaks and 90%-ile Precipitation Events 

(a two month lag precedes outbreaks); 1948 – 1994.

Floodwaters may increase the likelihood of contaminated drinking water and lead to 

incidental exposure to standing floodwaters. In 1999, Hurricane Floyd hit North Carolina 

and resulted in severe flooding of much of the eastern portion of the state, including 

extensive hog farming operations. Residents in the affected areas experienced over twice 

the rate of gastrointestinal illness following the flood (Setzer and Domino, 2004). 

Following the severe floods of 2001 in the Midwest, contact with floodwater was shown 

to increase the rate and risk of gastrointestinal illness, especially among children (Wade 

et al., 2004); however, consumption of tap water was not a risk factor as drinking water 

continued to meet all regulatory standards (Wade et al., 2004). 

2.2.4.3 Influenza 

Influenza may be considered a zoonosis in that pigs, ducks, etc. serve as non-human hosts 

to the influenza viruses (e.g., H3N2, H1N1) that normally infect humans (not H5N1). A 

number of recent studies evaluated the influence of weather and climate variability on the 

timing and intensity of the annual influenza season in the United States and Europe. 

Results indicated that cold winters alone do not predict pneumonia and influenza (P&I)-

related winter deaths, even though cold spells may serve as a short-term trigger (Dushoff 

et al., 2005), and that regional differences in P&I mortality burden may be attributed to 

climate patterns and to the dominant circulating virus subtype (Greene et al., 2006). 

Studies in France and the United States demonstrated that the magnitude of seasonal 

transmission (whether measured as mortality or morbidity) during winter seasons is 

significantly higher during years with cold El Niño Southern Oscillation (ENSO) 

conditions than during warm ENSO years (Flahault et al., 2004; Viboud et al., 2004), 

whereas a study in California concluded that higher temperatures and El Niño years 

increased hospital admissions for viral pneumonia (Ebi et al., 2001). In an attempt to 

better understand the spatio-temporal patterns of ENSO and influenza, Choi et al., (2006) 

used stochastic models (mathematical models that take into account the presence of 

randomness) to analyze California county-specific influenza mortality, and produced 

maps that showed different risks during the warm and cool phases. In general, these 

studies of influenza further support the importance of climate drivers at a global and 

regional scale, but have not advanced our understanding of underlying mechanisms. 

2.2.4.4 Valley Fever 

Valley fever (Coccidioidomycosis) is an infectious disease caused by inhalation of the 

spores of a soil-inhabiting fungus that thrives during wet periods following droughts. The 

disease is of public health importance in the desert southwest. In the early 1990s, 

California experienced an epidemic of Valley Fever following five years of drought 

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(Kolivras and Comrie, 2003). Its incidence varies seasonally and annually, which may be 

partly due to climatic variations (Kolivras and Comrie, 2003; Zender and Talamantes, 

2006). If so, then climate change could affect its incidence and geographic range. 

2.2.4.5 Morbidity and Mortality Due to Changes in Air Quality 

Millions of Americans continue to live in areas that do not meet the health-based 

National Ambient Air Quality Standards (NAAQS) for ozone and fine particulate matter 

(PM2.5). Both ozone and PM2.5 have well-documented health effects, and levels of these 

two pollutants have the potential to be influenced by climate change in a variety of ways. 

Ground-level ozone is formed mainly by reactions that occur in polluted air in the 

presence of sunlight. Nitrogen oxides (emitted mainly by burning of fuels) and volatile 

organic compounds (emitted both by burning of fuels and by evaporation from vegetation 

and stored fuels, solvents, and other chemicals) are the key precursor pollutants for ozone 

formation. Ozone formation increases with greater sunlight and higher temperatures; it 

reaches peak concentrations during the warm half of the year, and then mostly in the late 

afternoon and early evening. Cloud cover and mixing height are two additional 

meteorological factors that influence ozone concentrations. It has been firmly established 

that breathing ozone results in short-term, reversible decreases in lung function 

(Folinsbee et al., 1988) as well as inflammation deep in the lungs (Devlin et al., 1991). In 

addition, epidemiology studies of people living in polluted areas have suggested that 

ozone may increase the risk of asthma-related hospital visits (Schwartz, 1995), premature 

mortality (Kinney and Ozkaynak, 1991; Bell et al., 2004), and possibly the development 

of asthma (McConnell et al., 2002). Vulnerability to ozone health effects is greater for 

persons who spend time outdoors during episode periods, especially with physical 

exertion, because this results in a higher cumulative dose to the lung. Thus, children, 

outdoor laborers, and athletes may be at greater risk than people who spend more time 

indoors and who are less active. At a given lung dose, little has been firmly established 

about vulnerability as a function of age, race, and/or existing health status. However, 

because their lungs are inflamed, asthmatics are potentially more vulnerable than nonasthmatics. 

PM2.5 is a far more complex pollutant than ozone, consisting of all airborne solid or 

liquid particles that share the property of being less than 2.5 micrometers in aerodynamic 

diameter.2 All such particles are included, regardless of their size, composition, and 

biological reactivity. PM2.5 has complex origins, including primary particles directly 

emitted from sources and secondary particles that form via atmospheric reactions of 

precursor gases. Most of the particles captured as PM2.5 arise from burning of fuels, 

including primary particles such as diesel soot and secondary particles such as sulfates 

and nitrates. Epidemiologic studies have demonstrated associations between both shortterm and long-term average ambient concentrations and a variety of adverse health 

outcomes including respiratory symptoms such as coughing and difficulty breathing, 

2

 Aerodynamic diameter is defined in a complex way to adjust for variations in shape and density of 

various particles, and is based on the physical diameter of a water droplet that would settle to the ground at 

the same rate as the particle in question. For a spherical water particle, the aerodynamic and physical 

diameters are identical. 

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SAP 4.6 Chapter 2: Human Health 

decreased lung function, aggravated asthma, development of chronic bronchitis, heart 

attack, and arrhythmias (Dockery et al., 1993; Samet et al., 2000; Pope et al., 1995, 2002, 

2004; Pope and Dockery, 2006; Dominici et al, 2006; Laden et al., 2006). Associations 

have also been reported for increased school absences, hospital admissions, emergency 

room visits, and premature mortality. Susceptible individuals include people with existing 

heart and lung disease, and diabetics, children, and older adults. Because the mortality 

risks of PM2.5 appear to be mediated through narrowing of arteries and resultant heart 

impacts (Künzli et al., 2005), persons or populations with high blood pressure and/or preexisting heart conditions may be at increased risk. In a study of mortality in relation to 

long-term PM2.5 concentrations in 50 U.S. cities, individuals without a high school 

education demonstrated higher concentration/response functions that those with more 

education (Pope et al., 2002). This result suggests that low education was a proxy for 

increased likelihood of engaging in outdoor labor with an associated increase in exposure 

to ambient air. 

Using a coupled climate-air pollution three-dimensional model, Jacobson (2008) 

compared the health effects of pre-industrial vs. present day atmospheric concentrations 

of CO2. The results suggest that increasing concentrations of CO2 increased tropospheric 

ozone and PM2.5, which increased mortality by about 1.1% per degree temperature 

increase over the baseline rate; Jacobson estimated that about 40% of the increase was 

due to ozone and the rest to particulate matter. The estimated mortality increase was 

higher in locations with poorer air quality. 

2.2.4.6 Aeroallergens and Allergenic Diseases 

Climate change has caused an earlier onset of the spring pollen season for several species 

in North America (Casassa et al., 2007). Although data are limited, it is reasonable to 

infer that allergenic diseases caused by pollen, such as allergic rhinitis, also have 

experienced concomitant changes in seasonality (Emberlin et al., 2002; Burr et al., 2003). 

Several laboratory studies suggest that increasing CO2 concentrations and temperatures 

could increase ragweed pollen production and prolong the ragweed pollen season (Wan et 

al., 2002; Wayne et al., 2002; Singer et al., 2005; Ziska et al., 2005; Rogers et al., 2006) 

and increase some plant metabolites that can affect human health (Ziska et al., 2005; 

Mohan et al., 2006). Although there are suggestions that the abundance of a few species 

of airborne pollens has increased due to climate change, it is unclear whether the 

allergenic content of these pollen types has changed (Huynen and Menne, 2003; Beggs 

and Bambrick, 2005). The introduction of new invasive species associated with climatic 

and other changes, such as ragweed and poison ivy, may increase current health risks. 

There are no projections of the possible impacts of climate change on allergenic diseases. 

2.3 Projected Health Impacts of Climate Change in the United 

States 

2.3.1 Heat-Related Mortality 

Determinants of how climate change could alter heat-related mortality include actual 

changes in the mean and variance of future temperatures; factors affecting temperature 

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SAP 4.6 Chapter 2: Human Health 

variability at the local scale; demographic and health characteristics of the population; 

and policies that affect the social and economic structure of communities, including 

urban design, energy policy, water use, and transportation planning. Barring an 

unexpected and catastrophic economic decline, residential and industrial development 

will increase over the coming decades, which could increase urban heat islands in the 

absence of urban design and new technologies to reduce heat loads. 

The U.S. population is aging; the percent of the population over age 65 is projected to be 

13% by 2010 and 20% by 2030 (over 50 million people) (Day, 1996). Older adults are 

physiologically and socially vulnerable (Khosla and Guntupalli, 1999; Klinenberg, 2002) 

to hot weather and heatwaves, suggesting that heat-related mortality could increase. 

Evidence that diabetics are at greater risk of heat-related mortality (Schwartz 2005), 

along with the increasing prevalence of obesity and diabetes (Seidell, 2000; Visscher and 

Seidell, 2001), suggests that reduced fitness and higher-fat body composition may 

contribute to increased mortality. 

Table 2.1 summarizes projections of temperature-related mortality either in the United 

States or in temperate countries whose experience is relevant to the United States (Dessai, 

2003) (Woodruff et al., 2005) (Knowlton et al., 2007) (CLIMB, 2004; Hayhoe et al.,

2004). Similar studies are underway in Europe (Kosatsky et al., 2006; Lachowsky and 

Kovats, 2006). All studies used downscaled projections of future temperature 

distributions in the geographic region of interest. The studies used different approaches to 

incorporate likely future adaptation, addressing such issues as increased availability of air 

conditioning, heatwave early warning systems, demographic changes, and enhanced 

services such as cooling shelters and physiological adaptation. 

Time-series studies also can shed light on potential future mortality during temperature 

extremes. Heat-related mortality has declined over the past decades (Davis et al., 2002; 

Davis et al., 2003a; Davis et al., 2003b). A similar trend, for cold and heat-related 

mortality, was observed in London over the last century (Carson et al., 2006). The 

authors speculate that these declines are due to increasing prevalence of air-conditioning 

(in the United States), improved health care, and other factors. These results do not 

necessarily mean that future increases in heat-related mortality may not occur in the 

United States, as some have claimed (Davis et al., 2004), because the percentage of the 

population with access to air conditioning is high in most regions (thus with limited 

possibilities for increasing access). Further, population level declines may obscure 

persistent mortality impacts in vulnerable groups. 

In summary, given the projections of increases in the frequency, intensity, and duration of 

heatwaves and projected demographic changes, the at-risk population will increase 

(highly likely). The extent to which mortality increases will depend on the effective 

implementation of a range of adaptation options, including heatwave early warning 

systems, urban design to reduce heat loads, and enhanced services during heatwaves. 

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SAP 4.6 Chapter 2: Human Health 

2.3.2 Hurricanes, Floods, Wildfires and Health Impacts 

No studies have projected the future health burdens of extreme weather events. There is 

concern that climate change could increase the frequency and/or severity of extreme 

events, including hurricanes, floods, and wildfires. 

Theoretically, climate change could increase the frequency and severity of hurricanes by 

warming tropical seas where hurricanes first emerge and gain most of their energy 

(Pielke et al., 2005; Trenberth, 2005; Halverson, 2006). Controversy over whether 

hurricane intensity increased over recent decades stem less from the conceptual 

arguments than from the limitations of available hurricane incidence data (Halverson, 

2006; Landsea, 2005; Pielke et al., 2005; Trenberth, 2005). Even if climate change 

increases the frequency and severity of hurricanes, it will be difficult to definitively 

identify this trend for some time because of the relatively short and highly variable 

historical data available as a baseline for comparison. Adding to the uncertainty, some 

research has projected that climate change could produce future conditions that might 

hinder the development of Atlantic hurricanes despite the warming of tropical seas 

(NOAA, 2007c). 

Evidence suggests that the intensity of Atlantic hurricanes and tropical storms has 

increased over the past few decades. SAP3.3 indicates that there is evidence for a human 

contribution to increased sea surface temperatures in the tropical Atlantic and there is a 

strong correlation to Atlantic tropical storm frequency, duration, and intensity. However, 

a confident assessment will require further studies. An increase in extreme wave heights 

in the Atlantic since the 1970s has been observed: consistent with more frequent and 

intense hurricanes (CCSP, 2008). 

For North Atlantic hurricanes, SAP3.3 concludes that it is likely that wind speeds and 

core rainfall rates will increase (Henderson-Sellers et al., 1998; Knutson and Tuleya, 

2004, 2008; Emanuel, 2005). However, SAP3.3 concluded that “frequency changes are 

currently too uncertain for confident projection” (CCSP, 2008). SAP3.3 also found that 

the spatial distribution of hurricanes will likely change. Storm surge is likely to increase 

due to projected sea level rise, though the degree to which these will increase has not 

been adequately studied (CCSP, 2008). 

Theoretical arguments for increases in extreme precipitation and flooding are based on 

the principles of the hydrological cycle where increasing average temperature will 

intensify evaporation and subsequently increase precipitation (Bronstert, 2003; Kunkel, 

2003, Senior et al., 2002). Looking at the available data for evidence of a climate change 

signal, evidence suggests that the number of extreme precipitation events in the United 

States has increased (Balling Jr. and Cerveny, 2003; Groisman et al., 2004; Kunkel, 

2003). However, these results are not as consistent when evaluated by season or region 

(Groisman et al., 2004). 

Projections of changes in the future incidence of extreme-precipitation and flooding rely 

on the results from general circulation models (GCMs). These models project increases in 

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SAP 4.6 Chapter 2: Human Health 

mean precipitation with a disproportionate increase in the frequency of extreme 

precipitation events (Senior et al., 2002). Kim (2003) used a regional climate model to 

project that a doubling in CO2 concentrations in roughly 70 years could increase the 

number of days with at least 0.5 mm of precipitation by roughly 33% across the study’s 

defined elevation gradients in the western United States. Furthermore, the IPCC 

concluded that it is very likely (>90% certainty) that trends in extreme precipitation will 

continue in the 21st century (IPCC, 2007a). 

Studies modeling future wildfire incidence in the western United States using GCM 

outputs project increasingly severe wildfires, measured both in terms of energy released 

and the number of fires that avoid initial containment in areas that GCMs project will be 

increasingly dry (Brown et al., 2004; Fried et al., 2004). In general, these results suggest 

much of the western United States could face an increasing wildfire risk from climate 

change. The apparent exception could be the Pacific Northwest, including northern 

California, where GCMs generally project a wetter future. 

Factors independent of the impacts of and responses to climate change will affect 

vulnerability to extreme events, including population growth, continued urban sprawl, 

population shifts to coastal areas, and differences in the degree of community preparation 

for extreme events (U.S. Census Bureau, 2004). 

All else equal, the anticipated demographic changes will increase the size of the U.S. 

population at risk for future extreme weather events (very likely). This raises the potential 

for increasing total numbers of adverse health impacts from these events, even if the rate 

these impacts are experienced decreases (where the rate reflects the number of impacts 

per some standard population size among those actually experiencing the events). 

2.3.3 Vectorborne and Zoonotic Diseases 

Modeling the possible impacts of climate change on VBZ diseases is complex, and few 

studies have made projections for diseases of concern in the United States. Studies 

suggest that temperature influences the distributions of Ixodes spp. ticks that transmit 

pathogens causing Lyme disease in the United States (Brownstein et al., 2003) and 

Canada (Ogden et al., 2006), and tick-borne encephalitis in Sweden (Lindgren et al., 

2000). Higher minimum temperatures were generally favorable to the potential of 

expanding tick distributions and greater local abundance of these vectors. However, 

changing patterns of tick-borne encephalitis (TBE) in Europe are not consistently related 

to changing climate (Randolph, 2004a). Climate change is projected to decrease the 

geographic range of TBE in areas of lower latitude and elevation as transmission expands 

northward (Randolph and Rogers, 2000). 

2.3.4 Water- and Foodborne Diseases 

Several important pathogens that are commonly transmitted by food or water may be 

susceptible to changes in replication, survival, persistence, habitat range, and 

transmission under changing climatic and environmental conditions (Table 2.2). Many of 

these agents show seasonal infection patterns (indicating potential underlying 

environmental or weather control), are capable of survival or growth in the environment, 

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SAP 4.6 Chapter 2: Human Health 

or are capable of waterborne transport. Factors that may affect these pathogens include 

changes in temperature, precipitation, extreme weather events (i.e., storms), and 

ecological shifts. While the US has successful programs to protect water quality under 

the Safe Drinking Water Act and the Clean Water Act, some contamination pathways and 

routes of exposure do not fall under regulatory programs (e.g., dermal absorption from 

floodwaters, swimming in lakes and ponds with elevated pathogen levels, etc.). 

2.3.5 Air Quality Morbidity and Mortality 

The sources and conditions that give rise to elevated ozone and PM2.5 in outdoor air in 

the United States have been and will continue to be affected by global environmental 

changes related to land use, economic development, and climate change. Conversions of 

farmland and forests into housing developments and the infrastructure of schools and 

businesses that support them change the spatial patterns and absolute amounts of 

emissions from fuel combustion related to transportation, space heating, energy 

production, and other activities. Resulting vegetation patterns affect biogenic volatile 

organic compound (VOC) emissions that influence ozone production. Conversion of land 

from natural to man-made also changes the degree to which surfaces absorb solar energy 

(mostly in the form of light) and later re-radiate that energy as heat, which contributes to 

urban heat islands. In addition to their potential for increasing heat-related health effects, 

heat islands also can influence local production and dispersion of air pollutants like ozone 

and PM2.5. 

It is important to recognize that U.S. Environmental Protection Agency administers a 

well-developed and successful national regulatory program for ozone, PM2.5, and other 

criteria pollutants. Although many areas of the US remain out of compliance with the 

ozone and PM2.5 standards, there is evidence for gradual improvements in recent years, 

and this progress can be expected to continue with more stringent emissions controls 

going forward in time. Thus, the influence of climate change on air quality will play out 

against a backdrop of ongoing regulatory control of both ozone and PM2.5 that will shift 

the baseline concentrations of these two important air pollutants. On the other hand, most 

of the studies that have examined potential future climate impacts on air quality reviewed 

below have tried to isolate the climate effect by holding precursor emissions constant 

over future decades. Thus, the focus has been on examining the sensitivity of ozone 

concentrations to alternative future climates rather than on attempting to predict actual 

future ozone concentrations. 

The influence of meteorology on air quality is substantial and well-established (EPRI, 

2005), raising the possibility that changes in climate could alter patterns of air pollution 

concentrations. Temperature and cloud cover affect the chemical reactions that lead to 

ozone and secondary particle formation. Winds, vertical mixing, and rainfall patterns 

influence the movement and dispersion of anthropogenic pollutant emissions in the 

atmosphere, with generally improved air quality at higher winds, mixing heights, and 

rainfall. The most severe U.S. air pollution episodes occur with atmospheric conditions 

that limit both vertical and horizontal dispersion over multi-day periods. Methods used to 

study the influence of climatic factors on air quality range from statistical analyses of 

empirical relationships to integrated modeling of future air quality resulting from climate 

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SAP 4.6 Chapter 2: Human Health 

change. To date, most studies have been limited to climatic effects on ozone. Additional 

research is needed on the impacts of climate change on anthropogenic particulate matter 

concentrations. 

Leung and Gustafson (2005) used regional climate simulations for temperature, solar 

radiation, precipitation, and stagnation/ventilation, and projected worse air quality in 

Texas and better air quality in the Midwest in 2045-2055 compared with 1995-2005. Aw 

and Kleeman (2003) simulated an episode of high air pollution in southern California in 

1996 with observed meteorology and then with higher temperatures. Ozone 

concentrations increased up to 16% with higher temperatures, while the PM2.5 response 

was more variable due to opposing forces of increased secondary particle formation and 

more evaporative losses from nitrate particles. Bell and Ellis (2004) showed greater 

sensitivity of ozone concentrations in the Mid-Atlantic to changes in biogenic than to 

changes in anthropogenic emissions. Ozone’s sensitivity to changing temperatures, 

absolute humidity, biogenic VOC emissions, and pollution boundary conditions on a 

fine-scale (4 km grid resolution) varied in different regions of California (Steiner et al., 

2006). 

Several studies explored the impacts of climate change alone on future ozone projections. 

In a coarse-scale analysis of pollution over the continental United States, Mickley et al.,

(2004) used the GISS (NASA Goddard Institute for Space Studies) 4x5o model to project 

that, due to climate change alone (A1b emission scenario), air pollution could increase in 

the upper Midwest due to decreases between 2000 and 2052 in the frequency of Canadian 

frontal passages that clear away stagnating air pollution episodes. The 2.8x2.8o Mozart 

global chemistry/climate model was used to explore global background and urban ozone 

changes over the 21st century in response to climate change, with ozone precursor 

emissions kept constant at 1990s levels (Murazaki and Hess, 2006). While global 

background decreased slightly, the urban concentrations due to U.S. emissions increased. 

As part of the New York Climate and Health Study, Hogrefe and colleagues conducted 

local-scale analyses of air pollution impacts of future climate changes using integrated 

modeling (Hogrefe et al., 2004a,b,c; 2005a,b) to examine the impacts of climate and land 

use changes on heat- and ozone-related health impacts in the NYC metropolitan area 

(Knowlton et al., 2004; Kinney et al., 2006; Bell et al., 2007; Civerolo et al., 2006). The 

GISS 4x5o was used to simulate hourly meteorological data from the 1990s through the 

2080s based on the A2 and B2 SRES scenarios. The A2 scenario assumes roughly double 

the CO2 emissions of B2. The global climate outputs were downscaled to a 36 km grid 

over the eastern United States using the MM5 regional climate model. The MM5 results 

were used in turn as inputs to the CMAQ regional-scale air quality model. Five summers 

(June, July, and August) in each of four decades (1990s, 2020s, 2050s, and 2080s) were 

simulated at the 36 km scale. Pollution precursor emissions over the eastern United States 

were based on U.S. EPA estimates at the county level for 1996. Compared with 

observations from ozone monitoring stations, initial projections were consistent with 

ozone spatial and temporal patterns over the eastern United States in the 1990s (Hogrefe 

et al., 2004a). Average daily maximum 8-hour concentrations were projected to increase 

by 2.7, 4.2, and 5.0 ppb in the 2020s, 2050s, and 2080s, respectively due to climate 

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SAP 4.6 Chapter 2: Human Health 

change (Figure 2.5) (Hogrefe et al., 2004b). The influence of climate on mean ozone 

values was similar in magnitude to the influence of rising global background by the 

2050s, but climate had a much greater impact on extreme values than did the global 

background. When biogenic VOC emissions were allowed to increase in response to 

warming, an additional increase in ozone concentrations was projected that was similar in 

magnitude to that of climate alone (Hogrefe et al., 2004b). Climate change shifted the 

distribution of ozone concentrations towards higher values, with larger relative increases 

in future decades (Figure 6). 

Figure 2.5 (a) Summertime Average Daily Maximum 8-hour Ozone Concentrations 

(ppb) for the 1990s and Changes for the (b) 2020s relative to the 1990s, (c) 2050s 

relative to the 1990s, and (d) 2080s relative to the 1990s. All are based on the A2 

Scenario relative to the 1990s. Five consecutive summer seasons were simulated in each 

decade. 

Figure 2.6 Frequency Distributions of Summertime Daily Maximum 8-hr Ozone 

Concentrations over the eastern United States in the 1990s, 2020s, and 2050s based on 

the A2 Scenario. 

Projections in Germany also found larger climate impacts on extreme ozone values 

(Forkel and Knoche, 2006). Using the IS92a business-as-usual scenario, the ECHAM4 

GCM projected changes for the 2030s compared with the 1990s; the output was 

downscaled to a 20 km grid using a modification of the MM5 regional model, which was 

in-turn linked to the RADM2 ozone chemistry model. Both biogenic VOC emissions and 

soil NO emissions were projected to increase as temperatures rose. Daily maximum 

ozone concentrations increased by between 2 and 6 ppb (6-10%) across the study region. 

The number of cases where daily maximum ozone exceeded 90 ppb increased by nearly 

four-fold, from 99 to 384. 

Using the NYCHP integrated model, PM2.5 concentrations are projected to increase with 

climate change, with the effects differing by component species, with sulfates and 

primary PM increasing markedly and with organic and nitrated components decreasing, 

mainly due to movement of these volatile species from the particulate to the gaseous 

phase (Hogrefe et al., 2005b; 2006). 

Hogrefe et al., (2005b) noted that “the simulated changes in pollutant concentrations 

stemming from climate change are the result of a complex interaction between changes in 

transport, mixing, and chemistry that cannot be parameterized by spatially uniform linear 

regression relationships.” Additional uncertainties include how population vulnerability, 

mix of pollutants, housing characteristics, and activity patterns may differ in the future. 

For example, in a warmer world, more people may stay indoors with air conditioners in 

the summer when ozone levels are highest, decreasing personal exposures (albeit with 

potential increases in pollution emissions from power plants). Baseline mortality rates 

may change due to medical advances, changes in other risk factors such as smoking and 

diet, and aging of the population. 

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SAP 4.6 Chapter 2: Human Health 

 

The New York Climate and Health Project examined the marginal sensitivity of health to 

changes in climate to project the potential health impacts of ozone in the eastern United 

States (Knowlton et al., 2004; Bell et al., 2007). Knowlton and colleagues computed 

absolute and percentage increases in ozone-related daily summer-season deaths in the 

NYC metropolitan region in the 2050s as compared with the 1990s using a downscaled 

GCM/RCM/air quality model (Knowlton et al., 2004; Kinney et al., 2006). The 

availability of county-scale ozone projections made it possible to compare impacts in the 

urban core with those in outlying areas. Increases in ozone-related mortality due to 

climate change ranged from 0.4 to 7.0% across 31 counties. Bell and colleagues 

expanded the analysis to 50 eastern cities and examined both mortality and hospital 

admissions (Bell et al., 2007). Average ozone concentrations were projected to increase 

by 4.4 ppb (7.4%) in the 2050s; the range was 0.8% to 13.7%. In addition, ozone red alert 

days could increase by 68%. Changes in health impacts were of corresponding 

magnitude. 

Based on the new research findings published since the previous assessment, the 

following summary statements can be made: 

 There is an established but incomplete level of knowledge suggesting that both 

ozone and fine particle concentrations may be affected by climate change. 

 A substantial body of new evidence on ozone supports the interpretation that 

ozone concentrations would be more likely to increase than decrease in the United 

States as a result of climate change, holding precursor emissions constant. 

 Too few data yet exist for PM to draw firm conclusions about the direction or 

magnitude of climate impacts 

2.4 Vulnerable Regions and Subpopulations 

In adapting the IPCC's definitions3 to public health, "vulnerability" can be defined as the 

summation of all risk and protective factors that ultimately determine whether an 

individual or subpopulation experiences adverse health outcomes, and "sensitivity" can 

be defined as an individual's or subpopulation's increased responsiveness, primarily for 

biological reasons, to a given exposure. Thus, specific subpopulations may experience 

heightened vulnerability for climate-related health effects for a wide variety of reasons. 

Biological sensitivity may be related to the developmental stage, presence of pre-existing 

chronic medical conditions (such as the sensitivity of people with chronic heart 

conditions to heat-related illness), acquired factors (such as immunity), and genetic 

factors (such as metabolic enzyme subtypes that play a role in sensitivity to air pollution 

effects). Socioeconomic factors also play a critical role in altering vulnerability and 

sensitivity to environmentally-mediated factors. They may alter the likelihood of 

exposure to harmful agents, interact with biological factors that mediate risk (such as 

nutritional status), and/or lead to differences in the ability to adapt or respond to 

exposures or early phases of illness and injury. For public health planning, it is critical to 

3

 IPCC Second Assessment. Climate Change 1995. Available at http://www.ipcc.ch/pub/sa(E).pdf. 

Accessed 11-12-07. 

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SAP 4.6 Chapter 2: Human Health 

recognize populations that may experience synergistic effects of multiple risk factors for 

health problems related to climate change and to other temporal trends. 

2.4.1 Vulnerable Regions 

Populations living in certain regions of the United States may experience altered risks for 

specific climate-sensitive health outcomes due to their regions' baseline climate, 

abundance of natural resources such as fertile soil and fresh water supplies, elevation, 

dependence on private wells for drinking water, or vulnerability to coastal surges or 

riverine flooding. Some regions' populations may in fact experience multiple climatesensitive health problems simultaneously. One approach to identifying such areas is to 

map regions currently experiencing increased rates of climate-sensitive health outcomes 

or other indicators of increased climate risk, as illustrated in Figure 2.7a-2.7d. 

Residents of low-lying coastal regions, which are common locations for hurricane 

landfalls and flooding, are particularly vulnerable to the health impacts of climate change. 

Those who live in the Gulf Coast region, for example, are likely to experience increased 

human health burdens due to the constellation of more intense storms, greater sea level 

rise, coastal erosion, and damage to freshwater resources and infrastructure. Other coastal 

areas may also experience the combination of sea level rise chronically threatening water 

supplies and periodic infrastructure damage from more intense storms. Populations in the 

Southwest and Great Lakes regions may experience increased strain on water resources 

and availability due to climate change. More intense heat waves and heat-related illnesses 

may take place in regions where extreme heat events already occur, such as interior 

continental zones of the United States. High-density urban populations will experience 

heightened health risks, in part due to the heat-island effect. In addition, increased 

demand for electricity during summers may lead to greater air pollution levels (IPCC, 

2007b). 

Figure 2.7 a-d U.S. maps indicating counties with existing vulnerability to climate 

sensitive health outcomes: (a) location of hurricane landfalls; (b) extreme heat events, 

defined by CDC as temperatures 10 or more degrees above the average high 

temperature for the region and lasting for several weeks; (c) percentage of population 

over age 65; (d) West Nile Virus cases reported in 2004. Historical disease activity, 

especially in the case of WNV, is not necessarily predictive of future vulnerability. 

2.4.2 Specific Subpopulations at Risk 

Vulnerable subpopulations may be categorized according to specific health endpoints. 

(Table 2.3). While this is typically the way the scientific literature reports risk factors for 

adverse health effects, this section discusses vulnerability for a variety of climatesensitive health endpoints one subpopulation at a time. 

2.4.2.1 Children 

Children’s small body mass to surface area ratio and other factors make them more 

vulnerable to heat-related morbidity and mortality (AAP, 2000), while their increased 

breathing rates relative to body size, time spent outdoors, and developing respiratory 

tracts heighten their sensitivity to harm from ozone air pollution (AAP, 2004). In 

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SAP 4.6 Chapter 2: Human Health 

addition, children's relatively naïve immune systems increase the risk of serious 

consequences from water and foodborne diseases; specific developmental factors make 

them more vulnerable to complications from specific severe infections like E Coli

O157:H7. 

Children's lack of immunity also plays a role in higher risk of mortality from malaria 

(CDC, 2004b). Conversely, maternal antibodies to dengue in infants convey increased 

risk of developing dengue hemorrhagic syndromes. A second peak of greater risk of 

complications from dengue appears in children between the ages of 3 and 5 (Guzman and 

Khouri, 2002). 

Children may also be more vulnerable to psychological complications of extreme weather 

events related to climate change. Following two floods in Europe in the 1990s, children 

demonstrated moderate to severe stress symptoms (Becht et al., 1998; cited in Hajat et 

al., 2003) and long-term PTSD, depression, and dissatisfaction with ongoing life 

(Bokszanin, 2000; cited in Hajat et al., 2003). 

2.4.2.2 Older Adults 

Health effects associated with climate change pose significant risks for the elderly, who 

often have frail health and limited mobility. Older adults are more sensitive to 

temperature extremes, particularly heat (Semenza et al., 1996; Medina-Ramon et al., 

2006); individuals 65 years of age and older comprised 72% of the heat-related deaths in 

the 1995 Chicago heatwave (Whitman et al., 1997). The elderly are also more likely to 

have preexisting medical conditions, including cardiovascular and respiratory illnesses, 

which may put them at greater risk of exacerbated illness by climate-related events or 

conditions. For example, a 2004 rapid needs assessment of older adults in Florida found 

that Hurricane Charley exacerbated preexisting, physician-diagnosed medical conditions 

in 24-32% of elderly households (CDC, 2004a). Also, effects of ambient particulate 

matter on daily mortality tend to be greatest in older age groups (Schwartz, 1995). 

2.4.2.3 Impoverished Populations 

Even in the United States, the greatest health burdens related to climate change are likely 

to fall on those with the lowest socioeconomic status (O'Neill et al., 2003a). Most 

affected are individuals with inadequate shelter or resources to find alternative shelter in 

the event their community is disrupted. While quantitative methods to assess the increase 

in risk related to these social and economic factors are not well-developed, qualitative 

insights can be gained by examining risk factors for mortality and morbidity from recent 

weather-related extreme events such as the 1995 heatwave in Chicago and Hurricane 

Katrina in 2005 (Box 2.1). 

Studies of heatwaves identify poor housing conditions, including lack of access to air 

conditioning and living spaces with fewer rooms, as significant risk factors for heatrelated mortality (Kalkstein, 1993; Semeza et al., 1996). Higher heat-related mortality 

has been associated with socioeconomic indicators, such as lacking a high school 

education and living in poverty (Curriero et al., 2002). Financial stress plays a role, as 

one study of the 1995 Chicago heatwave found that concern about the affordability of 

utility bills influenced individuals to limit air conditioning use (Klinenberg, 2002). The 

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SAP 4.6 Chapter 2: Human Health 

risk for exposure and sensitivity to air pollution is also elevated among groups in a lower 

socioeconomic position (O'Neill et al., 2003a). 

Air conditioning is an important short-term method for protecting health, but is not a 

sustainable long-term adaptation technology because the electricity use is often 

associated with greenhouse gas emissions and during heatwaves can overload the grid 

and contribute to outages (O’Neill, 2003c). Furthermore, the elderly with limited budgets 

and racial minorities are less likely to have access to air conditioning or to use it during 

hot weather (O’Neill et al., 2005b, Sheridan, 2006). Incentives for and availability of 

high-efficiency, low energy-demand residential cooling systems, especially among 

disadvantaged populations, can advance health equity and minimize some of the negative 

aspects of air conditioning. 

Another area of concern for impoverished populations is the impact that climate change 

may have on food systems and food supply. In the United States, food insecurity is a 

prevalent health risk among the poor, particularly poor children (Cook et al., 2007). On a 

global scale, studies suggest that climate change is likely to contribute to food insecurity 

by reducing crop yield, most significantly at lower latitudes, due to shortened growing 

periods and decreases in water availability (Parry et al., 2005). In the United States, 

changes in the price of food would likely contribute to food insecurity to a greater degree 

than overall scarcity. 

The tragic loss of life that occurred after Hurricane Katrina underscores the increased 

vulnerability of special populations and demonstrates that, in the wake of extreme 

weather events, particularly those that disrupt medical infrastructure and require largescale evacuation, treating individuals with chronic diseases is of critical concern (Ford et 

al., 2006). 

2.4.2.4 People with Chronic Conditions and Mobility and Cognitive Constraints 

People with chronic medical conditions have an especially heightened vulnerability for 

the health impacts of climate change. Extreme heat poses a great risk for individuals with 

diabetes (Schwartz, 2005), and extreme cold has an increased effect on individuals with 

chronic obstructive pulmonary disease (Schwartz, 2005). People with mobility and 

cognitive constraints may be at particular risk during heatwaves and other extreme 

weather events (EPA, 2006). As noted above, those with chronic medical conditions are 

also at risk of worsened status as the result of climate-related stressors and limited access 

to medical care during extreme events. 

2.4.2.5 Occupational Groups 

Certain occupational groups, primarily by virtue of spending their working hours 

outdoors, are at greater risk of climate-related health outcomes. Outdoor workers in rural 

or suburban areas, such as electricity and pipeline utility workers, are at increased risk of 

infection with Lyme Disease, although evidence is lacking for greater risk of clinical 

illness (Schwartz and Goldstein, 1990; Piacentino and Schwartz, 2002). They and other 

outdoor workers have increased exposures to ozone air pollution and heat stress, 

especially if work tasks involve heavy exertion. 

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2.4.2.6 Recent Migrants and Immigrants 

Residential mobility, migration, and immigration may increase vulnerability. For 

example, new residents in an area may not be acclimated to the weather patterns, have 

lower awareness of risks posed by local vectorborne diseases, and have fewer social 

networks to provide support during an extreme weather event. U.S. immigrants returning 

to their countries of origin to visit friends and relatives have also been shown to suffer 

increased risks of severe travel-associated diseases (Bacaner et al., 2004, Angell and 

Cetron, 2005). This vulnerability may become more significant if such diseases, which 

include malaria, viral hepatitis, and typhoid fever, become more prevalent in immigrants’ 

countries of origin because of climate change. 

2.5 Adaptation 

Realistically assessing the potential health effects of climate change must include 

consideration of the capacity to manage new and changing climatic conditions. 

Individuals, communities, governments, and other organizations currently engage in a 

wide range of actions to identify and prevent adverse health outcomes associated with 

weather and climate. Although these actions have been largely successful, recent extreme 

events and outbreaks of vectorborne diseases highlight areas for improvement 

(Confalonieri et al., 2007). Climate change is likely to further challenge the ability of 

current programs and activities to control climate-sensitive health determinants and 

outcomes. Preventing additional morbidity and mortality requires consideration of all 

upstream drivers of adverse health outcomes, including developing and deploying 

adaptation policies and measures that consider the full range of health risks that are likely 

to arise with climate change. 

In public health, prevention is the term analogous to adaptation, acknowledging that 

adaptation implies a set of continuous or evolving practices and not just upfront 

investments. Public health prevention is classified as primary, secondary, or tertiary. 

Primary prevention aims to prevent the onset of disease in an otherwise unaffected 

population (such as regulations to reduce harmful exposures to ozone). Secondary 

prevention entails preventive action in response to early evidence of health effects 

(including strengthening disease surveillance programs to provide early intelligence on 

the emergence or re-emergence of health risks at specific locations, and responding 

effectively to disease outbreaks, such as West Nile virus). Tertiary prevention consists of 

measures (often treatment) to reduce long-term impairment and disability and to 

minimize suffering caused by existing disease. In general, primary prevention is more 

effective and less expensive than secondary and tertiary prevention. For every health 

outcome, there are multiple possible primary, secondary, and tertiary preventions. 

The degree to which programs and measures will need to be modified to address the 

additional pressures due to climate change will depend on factors such as the current 

burden of climate-sensitive health outcomes, the effectiveness of current interventions, 

projections of where, when, and how quickly the health burdens could change with 

changes in climate and climate variability (which depends on the rate and magnitude of 

climate change), the feasibility of implementing additional cost-effective interventions, 

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SAP 4.6 Chapter 2: Human Health 

other stressors that could increase or decrease resilience to impacts, and the social, 

economic, and political context within which interventions are implemented (Ebi et al., 

2006a). Failure to invest in adaptation may leave communities poorly prepared and 

increase the probability of severe adverse consequences (Haines et al., 2006a,b). 

Adaptation to climate change is basically a risk management issue. Adaptation and 

mitigation are the primary responses to manage current and projected risks. Mitigation 

and adaptation are not mutually exclusive; co-benefits to human health can result 

concurrently with implementation of mitigation and adaptation actions. A dialogue is 

needed on prioritizing the costs of mitigation actions designed to limit future climate 

change and the potential costs of continually trying to adapt to its impacts. This dialogue 

should explicitly recognize that there is no guarantee that future changes in climate will 

not present a threshold that poses technological or physical limits to which adaptation is 

not possible. 

Adaptation policies and measures should address both projected risks and the regions and 

populations that currently are not well adapted to climate-related health risks. Because 

the degree and rate of climate change is projected to increase over time, adaptation will 

be a continual process of designing and implementing policies and programs to prevent 

adverse impacts from changing exposures and vulnerabilities (Ebi et al., 2006). Clearly, 

the extent to which effective proactive adaptations are developed and deployed will be a 

key determinant of future morbidity and mortality attributable to climate change. 

Regional vulnerabilities to the health impacts of climate change are influenced by 

physical, social, demographic, economic, and other factors. Adaptation activities take 

place within the context of slowly changing factors that are specific to a region or 

population, including specific population and regional vulnerabilities, social and cultural 

factors, the built and natural environment, the status of the public health infrastructure, 

and health and social services. Because these factors vary across geographic and temporal 

scales, adaptation policies and measures generally are more successful when focused on a 

specific population and location. Additional important factors include the degree of risk 

perceived, the human and financial resources available for adaptation, the available 

technological options, and the political will to undertake adaptation. 

2.5.1 Actors and Their Roles and Responsibilities for Adaptation 

Responsibility for the prevention of climate-sensitive health risks rests with individuals, 

community and state governments, national agencies, and others. The roles and 

responsibilities vary by health outcome. For example, individuals are responsible for 

taking appropriate action on days with declared poor air quality, with health care 

providers and others responsible for providing the relevant information, and government 

agencies providing the regulatory framework. Community governments play a central 

role in preparedness and response for extreme events because of their jurisdiction over 

police, fire, and emergency medical services. Early warning systems for extreme events 

such as heat waves (Box 2.2) and outbreaks of infectious diseases may be developed at 

the community or state level. The federal government funds research and development to 

increase the range of decision support planning and response tools. Medical and nursing 

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SAP 4.6 Chapter 2: Human Health 

schools are responsible for ensuring that health professionals are trained in the 

identification and treatment of climate-sensitive diseases. The Red Cross and other 

nongovernmental organizations (NGOs) often play critical roles in disaster response. 

Additional research and development are needed to ensure that surveillance systems 

account for and anticipate the potential effects of climate change. Ensuring that 

surveillance systems account for and anticipate the potential effects of climate change 

will be beneficial. For example, surveillance systems in locations where changes in 

weather and climate may foster the spread of climate-sensitive pathogens and vectors into 

new regions would help advance our understanding of the associations between disease 

patterns and environmental variables. This knowledge could be used to develop early 

warning systems that warn of outbreaks before most cases have occurred. Increased 

understanding is needed of how to design these systems where there is limited knowledge 

of the interactions of climate, ecosystems, and infectious diseases (NAS, 2001). 

There are no inventories in the United States of the various actors taking action to cope 

with climate change-related health impacts. However, the growing numbers of city and 

state actions on climate change show increasing awareness of the potential risks. As of 1 

November 2007, more than 700 cities have signed the U.S. Mayors Climate Protection 

Agreement (http://www.seattle.gov/mayor/climate/cpaText.htm); although this agreement 

focuses on mitigation through increased energy efficiency, one strategy, planting trees, 

can both sequester CO2 and reduce urban heat islands. The New England Governors and 

Eastern Canadian Premiers developed a Climate Change Action Plan because of concerns 

about public health associated with degradation in air quality, public health risks, the 

magnitude and frequency of extreme climatic phenomena and availability of water. 

(NEG/ECP, 2001). One action item focuses on the reduction and/or adaptation of 

negative social, economic, and environmental impacts. Activities being undertaken 

include a long-term phenology study, and studies on temperature increases and related 

potential impacts. 

Strategies, policies, and measures implemented by community and state governments, 

federal agencies, NGOs, and other actors can change the context for adaptation by 

conducting research to assess vulnerability and to identify technological options available 

for adaptation, implementing programs and activities to reduce vulnerability, and shifting 

human and financial resources to address the health impacts of climate change. State and 

federal governments also can provide guidance for vulnerability assessments that 

consider a range of plausible future scenarios. The results of these assessments can be 

used to identify priority health risks (over time), particularly vulnerable populations and 

regions, effectiveness of current adaptation activities, and modifications to current 

activities or new activities to implement to address current and future climate changerelated risks. 

Table 2.4 summarizes the other roles and responsibilities of various actors for adapting to 

climate change. Note that viewing adaptation from a public health perspective results in 

similar activities being classified as primary rather than secondary prevention under 

different health outcomes. It is not possible to prevent the occurrence of a heatwave, so 

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SAP 4.6 Chapter 2: Human Health 

primary prevention focuses on actions such as developing and enforcing appropriate 

infrastructure standards, while secondary prevention focuses on implementing early 

warning systems and other activities. For vectorborne diseases, primary prevention refers 

to preventing exposure to infected vectors; in this case, early warning systems can be 

considered primary prevention. For most vectorborne diseases, there are few options for 

preventing disease onset once an individual has been bitten. 

A key activity not included in this framework is research on the associations between 

weather / climate and various health outcomes, taking into consideration other drivers of 

those outcomes (e.g., taking a systems-based approach), and projecting how those risks 

may change with changing weather patterns. Increased understanding of the human 

health risks posed by climate change is needed for the design of effective, efficient, and 

timely adaptation options. 

2.5.2 Adaptation Measures to Manage Climate Change-Related Health Risks 

Determining where populations are not effectively coping with current climate variability 

and extremes facilitates identification of the additional interventions that are needed now. 

However, given uncertainties in climate change projections, identifying current 

adaptation deficits is not sufficient to protect against projected health risks. Adaptation 

measures can be categorized into legislative policies, decision support tools, technology 

development, surveillance and monitoring of health data, infrastructure development, and 

other. Table 2.5 lists some adaptation measures for health impacts from heatwaves, 

extreme weather events, vectorborne diseases, waterborne diseases, and air quality. These 

measures are generic because the local context, including vulnerabilities and adaptive 

capacity, need to be considered in the design of programs and activities to be 

implemented. 

An additional category of measures includes public education and outreach to provide 

information to the general public and specific vulnerable groups on climate risks to which 

they may be exposed and appropriate actions to take. Messages need to be specific to the 

region and group; for example, warnings to senior citizens of an impending heatwave 

should focus on keeping cool and drinking lots of water. Box 2.3 provides tips for dealing 

with extreme heatwaves developed by U.S. EPA with assistance from federal, state, local, 

and academic partners (U.S. EPA, 2006). 

2.6 Conclusions 

The conclusions from this assessment are consistent with those of the First National 

Assessment: climate change poses a risk for U.S. populations, with uncertainties limiting 

quantitative projections of the number of increased injuries, illnesses, and deaths 

attributable to climate change. However, the strength and consistency of projections for 

climatic changes for some exposures of concern to human health suggest that 

implementation of adaptation actions should commence now (Confalonieri et al., 2007). 

Further, trends in factors that affect vulnerability, such as a larger and older U.S. 

population, will increase overall vulnerability to health risks. At the same time, the 

capacity of the U.S to implement effective and timely adaptation measures is assumed to 

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SAP 4.6 Chapter 2: Human Health 

remain high throughout this century, thus reducing the likelihood of severe health 

impacts if appropriate programs and activities are implemented. However, the nature of 

the risks posed by climate change means that some adverse health outcomes may not be 

avoidable, even with attempts at adaptation. Severe health impacts will not be evenly 

distributed across populations and regions, but will be concentrated in the most 

vulnerable groups. 

Proactive policies and measures should be identified that improve the context for 

adaptation, reduce exposures related to climate variability and change, prevent the onset 

of climate-sensitive health outcomes, and increase treatment options. Future community, 

state, and national assessments of the health impacts of climate variability and change 

should identify gaps in adaptive capacity, including where barriers and constraints to 

implementation, such as governance mechanisms, need to be addressed. 

Because of regional variability in the types of health stressors attributable to climate 

change and their associated responses, it is difficult to summarize adaptation at the 

national level. Planning for adaptation is hindered by the fact that downscaled climate 

projections, as well as other climate information and tools, are generally not available to 

local governments. Such data and tools are essential for sectors potentially affected by 

climate change to assess their vulnerability and possible adaptation options, catalogue, 

evaluate, and disseminate adaptation measures. Explicit consideration of climate change 

is needed in the many programs and research activities within federal, state, and local 

agencies that are relevant to adaptation to ensure that they have maximum effectiveness 

and timeliness in reducing future vulnerability. In addition, collaboration and 

coordination are needed across agencies and sectors to ensure protection of the American 

population to the current and projected impacts of climate change. 

2.7 Expanding the Knowledge Base 

Few research and data gaps have been filled since the First National Assessment. An 

important shift in perspective that occurred since the First National Assessment is a 

greater appreciation of the complex pathways and relationships through which weather 

and climate affect health, and the understanding that many social and behavioral factors 

will influence disease risks and patterns (NRC, 2001). Several research gaps identified in 

the First National Assessment have been partially filled by studies that address the 

differential effects of temperature extremes by community, demographic, and biological 

characteristics; that improve our understanding of exposure-response relationships for 

extreme heat; and that project the public health burden posed by climate-related changes 

in heatwaves and air quality. Despite these advances, the body of literature remains small, 

limiting quantitative projections of future impacts. 

Improving our understanding of the linkages between climate change and health in the 

United States, may require a wide range of activities along the following lines: 

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SAP 4.6 Chapter 2: Human Health 

 Improve characterization of exposure-response relationships, particularly at 

regional and local levels, including identifying thresholds and particularly 

vulnerable groups. 

 Collect data on the early effects of changing weather patterns on climate-sensitive 

health outcomes. 

 Collect and enhance long-term surveillance data on health issues of potential 

concern, including vectorborne and zoonotic diseases, air quality, pollen and mold 

counts, reporting of food- and waterborne diseases, morbidity due to temperature 

extremes, and mental health impacts from extreme weather events. 

 Develop quantitative models of possible health impacts of climate change that can 

be used to explore the consequences of a range of socioeconomic and climate 

scenarios. 

 Increase understanding of the processes of adaptation, including social and 

behavioral dimensions, as well as the costs and benefits of interventions. 

 Evaluate the implementation of adaptation measures. For example, evaluation of 

heatwave warning systems, especially as they become implemented on a wider 

scale (NOAA, 2005), is needed to understand how to motivate appropriate 

behavior. 

 Understand local and regional scale vulnerability and adaptive capacity to 

characterize the potential risks and the time horizon over which climate risks 

might arise; these assessments should include stakeholders to ensure their needs 

are identified and addressed in subsequent research and adaptation activities. 

 Improve comprehensive estimates of the co-benefits of adaptation and mitigation 

policies in order to clarify trade-offs and synergies. 

 Improve collaboration across the multiple agencies and organizations with 

responsibility and research related to climate change-related health impacts, such 

as weather forecasting, air and water quality regulations, vector control programs, 

and disaster preparation and response. 

 Anticipate infrastructure requirements that will be needed to protect against 

extreme events such as heatwaves, and food- and waterborne diseases, or to alter 

urban design to decrease heat islands, and to maintain drinking and wastewater 

treatment standards and source water and watershed protection. 

 Develop downscaled climate projections at the local and regional scale in order to 

conduct the types of vulnerability and adaptation assessments that will enable 

adequate response to climate change and to determine the potential for 

interactions between climate and other risk factors, including societal, 

environmental, and economic. The growing concern over impacts from extreme 

events demonstrates the importance of climate models that allow for stochastic 

generation of possible future events, to assess not only how disease and pathogen 

population dynamics might respond, but also to assess whether levels of 

preparedness are likely to be adequate. 

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2.9 Boxes 

Box 2.1 Vulnerable Populations and Hurricane Katrina 

In 2005, Hurricane Katrina caused more than 1,500 deaths along the Gulf Coast, and 

many of these victims were members of vulnerable subpopulations, such as hospital and 

nursing-home patients, older adults who required care within their homes, and individuals 

with disabilities (U.S. CHSGA, 2006). The hurricane was complicated by a catastrophic 

failure of the levee system that was intended to shield those areas in New Orleans that lie 

at or below sea level. According to the Louisiana Department of Health and Hospitals, 

more than 45% of the state's identified victims were 75 years of age or older; 69% were 

above age 60 (LDHH, 2006). In Mississippi, 67% of the victims whose deaths were 

directly, indirectly, or possibly related to Katrina were 55 years of age or older (MSDH, 

2005). 

At hurricane evacuation centers in Louisiana, Mississippi, Arkansas, and Texas, chronic 

illness was the most commonly reported health problem, accounting for 33% or 4,786 of 

14,531 visits (CDC, 2006a). Six of the fifteen deaths indirectly related to the hurricane 

and its immediate aftermath in Alabama were associated with preexisting cardiovascular 

disease (CDC, 2006c), and the storm disrupted an estimated 100,000 diabetic evacuees 

across the region from obtaining appropriate care and medication (Cefalu et al., 2006). 

One study suggested that the hurricane had a negative effect on reproductive outcomes 

among pregnant women and infants, who experienced exposure to environmental toxins, 

limited access to safe food and water, psychological stress, and disrupted health care 

(Callaghan et al., 2007). Other vulnerable individuals included those without personal 

means of transportation and poor residents in Louisiana and Mississippi who were unable 

to evacuate in time (U.S. CHSGA, 2006). 

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Box 2.2 Heatwave Early Warning Systems 

Projections for increases in the frequency, intensity and duration of heatwaves suggests 

more cities need heatwave early warning systems, including forecasts coupled with 

effective response options, to warn the public about the risks during such events (Meehl 

and Tebaldi 2004). Prevention programs designed to reduce the toll of hot weather on the 

public have been instituted in several cities, and guidance has been developed to further 

aid communities seeking to plan such interventions, including buddy systems, cooling 

centers, and community preparedness (EPA 2006b). Although these systems appear to 

reduce the toll of hot weather (Ebi et al., 2004; Ebi and Schmier 2005; Weisskopf et al.,

2002), and enhanced preparedness following events such as the 1995 heatwaves in 

Chicago and elsewhere, a survey of individuals 65 or older in four North American cities 

(Dayton, OH; Philadelphia, PA; Phoenix, AZ; and Toronto, Ontario, Canada) found that 

the public was unaware of appropriate preventive actions to take during heatwaves 

(Sheridan 2006). Although respondents were aware of the heat warnings, the majority did 

not consider they were vulnerable to the heat, or did not consider hot weather to pose a 

significant danger to their health. Only 46% modified their behavior on the heat advisory 

days. Although many individuals surveyed had access to home air-conditioning, their use 

of it was influenced by concerns about energy costs. Precautionary steps recommended 

during hot weather, such as increasing intake of liquids, were taken by very few 

respondents (Sheridan 2006). Some respondents reported using a fan indoors with 

windows closed and no air-conditioning, a situation that can increase heat exposure and 

be potentially deadly. Further, simultaneous heat warnings and ozone alerts were a source 

of confusion, because recommendations not to drive conflicted with the suggestion to 

seek cooler locations if the residence was too warm. Critical evaluation is needed of 

heatwave early warning systems, including which components are effective and why 

(Kovats and Ebi 2006; NOAA 2005). 

2-58 
SAP 4.6 Chapter 2: Human Health 

Box 2.3: Quick Tips for Responding to Excessive Heat waves 

For the Public 

Do 

• Use air conditioners or spend time in air-conditioned locations such as malls and 

libraries 

• Use portable electric fans to exhaust hot air from rooms or draw in cooler air 

• Take a cool bath or shower 

• Minimize direct exposure to the sun 

• Stay hydrated – regularly drink water or other nonalcoholic fluids 

• Eat light, cool, easy-to-digest foods such as fruit or salads 

• Wear loose fitting, light-colored clothes 

• Check on older, sick, or frail people who may need help responding to the heat 

• Know the symptoms of excessive heat exposure and the appropriate responses. 

Don’t 

• Direct the flow of portable electric fans toward yourself when room temperature 

is hotter than 90°F 

• Leave children and pets alone in cars for any amount of time 

• Drink alcohol to try to stay cool 

• Eat heavy, hot, or hard-to-digest foods 

• Wear heavy, dark clothing. 

Useful Community Interventions 

For Public Officials 

Send a clear public message

• Communicate that EHEs [extreme heat event] are dangerous and conditions can 

be life-threatening. In the event of conflicting environmental safety 

recommendations, emphasize that health protection should be the first priority. 

Inform the public of anticipated EHE conditions 

• When will EHE conditions be dangerous? 

• How long will EHE conditions last? 

• How hot will it feel at specific times during the day (e.g., 8 a.m., 12 p.m., 4 p.m., 

8 p.m.)? 

Assist those at greatest risk

• Assess locations with vulnerable populations, such as nursing homes and public 

housing 

• Staff additional emergency medical personnel to address the anticipated increase 

in demand 

• Shift/expand homeless intervention services to cover daytime hours 

• Open cooling centers to offer relief for people without air conditioning and urge 

the public to use them. 

Provide access to additional sources of information 

• Provide toll-free numbers and Web site addresses for heat exposure symptoms 

and responses 

• Open hotlines to report concerns about individuals who may be at risk 

2-59 
SAP 4.6 Chapter 2: Human Health 

• Coordinate broadcasts of EHE response information in newspapers and on 

television and radio. 

Source: U.S. EPA, 2006 

2-60 
SAP 4.6 Chapter 2: Human Health 

2-61 

The impacts projected for Lisbon were more sensitive to the choice of regional climate model 

than the method used to calculate excess deaths, and the author described the challenge of 

extrapolating health effects at the high end of the temperature distribution, for which data are 

sparse or nonexistent (Dessai 2003).

Table 2.1 Projections of Impacts of Climate Change on Heat-Related Mortality 

2.10 Tables 
SAP 4.6 

Table 2.2. Possible Influence of Climate Change on Climate Susceptible Pathogens and/or Disease, Based Models or Empirical Evidence Pathogen Climate Related 

Driver 

Possible Influence of Climate Change Likelihood 

of Changea

Basis for Assessment 

Bacteria Salmonella Rising Temperature Increasing temperature associated with 

increasing clinical cases 

Likely Likelihood of climate event 

is high and published 

research supports disease trend 

Changes in Precipitation 

Precipitation and run-off associated with increased likelihood of contamination of 

surface waters used for recreation, drinking or irrigation. 

Likely Likelihood of climate event 

is probable but more research is needed to confirm disease trend 

Shifts in Reservoir Host Ranges 

Shifts in habitat and range of reservoir hosts may influence exposure routes and/or rate of 

contact with humans 

More likely than not

Likelihood of climate event is probable but there is insufficient research on this relationship 

Campylobacter Rising Temperature Increasing temperatures may expand typical 

peak season of clinical infection, or result in 

earlier peak (commonly spring and summer) 

More likely than not 

Likelihood of climate event is high and published 

research supports disease trend, but mechnisms are not understood 

Increasing temperatures may result in shorter developmental times for flies, contributing to 

increased transmission by this proposed vector 

About as likely as not 

Likelihood of climate event and fly development trend is 

high but additional research is needed to confirm disease association 

2-62 
SAP 4.6 

Changes in Precipitation 

Increasing precipitation and run-off associated with increased likelihood of 

contamination of surface waters used for recreation or drinking 

More likely than not 

Likelihood of climate event is probable but more 

research is needed to confirm disease trend 

Shifts in Reservoir Host Ranges or 

Behavoir 

Shifts in habitat and range of reservoir hosts (geographically or temporally) may influence 

exposure routes and/or rate of contact with humans 

More likely than not 

Likelihood of climate event is probable but there is 

insufficient research on this relationship 

Vibrio species Rising Temperature Increasing ambient temperatures associated 

with growth in pre-harvest and post-harvest shellfish (in absence of appropriate postharvest controls) and increasing disease 

Very likely Likelihood of climate event 

is high and evidence supports growth trend in ambient waters; adaptive (control) measures (refrigeration) would reduce this effect for post-harvest oysters 

Increasing temperature associated with higher environmental prevalence and disease 

Extremely likely 

Likelihood of climate event 

is high and evidence is 

supports environmental growth trend 

Increasing temperature associated with range expansion 

Very likely Likelihood of climate event 

is high and evidence 

collected to date supports trend; more data needed to confirm 

Changes in 

Precipitation 

Increasing precipitation and fresh water run off leads to depressed estuarine salinities and 

increase in some Vibrio species 

About as likely as not 

Likelihood of climate event is probable but additional 

research is needed to confirm pathogen distribution patterns 

Sea Level Changes Rising sea level and or storm surge increase 

range and human exposure 

Likely Likelihood of climate event 

is probable but confirmatory 

2-63 
SAP 4.6 

research is needed on disease patterns 

Leptospira Rising Temperature Increasing temperatures may increase range 

of pathogen (temporally and geographically) 

Likely Likelihood of climate event 

is high but additional 

research is needed to confirm pathogen distribution patterns 

Changes in 

Precipitation 

Increasing precipitation and run off precedes outbreaks 

Likely Likelihood of climate event 

in probable and research 

supports this pattern 

Viruses 

Enteroviruses Rising Temperature Increasing temperature associated with 

increased or expanded peak clinical season (summer) 

Unlikely Likelihood of climate event 

is high but no mechanistic studies are available to explain the underlying cause of this seasonality. 

Increasing temperature associated with increased decay and inactivation of viruses in 

the environment 

About as likely as not 

Likelihood of climate event is high and research 

demonstrates decreased persistence under increasing temperatures but little data are available to relate this with disease 

Changes in 

Precipitation 

Increasing precipitation associated with increased loading of viruses to water and 

increased exposure or disease 

Likely Likelihood of climate is 

probable and research 

supports this pattern 

Norovirus Rising Temperature Increasing temperature leads to decreased 

retention of virus in shellfish 

Unlikely Likelihood of climate event 

is high and research indicates seasonally high shellfish loading in winter but there is no evidence for direct control of temperature on seasonality of infection 

Increasing temperature associated with shorter peak clinical season (winter) 

Unlikely Likelihood of climate event 

is high and research indicates seasonal disease peak in winter but there is 

2-64 
SAP 4.6 

no evidence for direct control of temperature on seasonality of infection 

Increasing temperature associated with increased decay and inactivation of viruses in 

the environment 

About as likely as not 

Likelihood of climate event is high and research 

demonstrates decreased persistence under increasing temperatures but little data are available to relate this with disease 

Changes in 

Precipitation 

Increasing precipitation associated with increased loading of viruses to crops and 

fresh produce 

More likely than not

Likelihood of climate event is probable but there is insufficient research on this relationship 

Increasing precipitation associated with increased loading of viruses to water and 

increased exposure or disease 

Likely Likelihood of climate is 

probable and research 

supports this pattern 

Rotavirus Rising Temperature Increasing temperature associated with 

increased decay and inactivation of viruses in the environment 

About as likely as not 

Likelihood of climate event is high and research 

demonstrates decreased persistence under increasing temperatures but little data are available to relate this with disease 

Dampening of winter seasonal peak in temperate latitudes 

About as likely as not

Likelihood of climate event is high and research 

indicates seasonal disease peak in winter but there is no evidence for direct control of temperature on seasonality of infection; although tropical countries do not exhibit a seasonal peak 

Parasites 

Naegleria fowleri 

Rising Temperature Increasing temperature associated with 

expanded range and conversion to flagellated 

More likely than not

Likelihood of climate event is high but more research is 

2-65 
SAP 4.6 

2-66 

form (infective) needed to confirm disease 

trend 

Cryptosporidium Rising Temperature Expanding recreational (swimming) season 

may increase likelihood of exposure and 

disease 

About as likely as not

Likelihood of climate event is high but there is 

insufficient research on this relationship 

Changes in Precipitation 

Increasing precipitation associated with increased loading of parasite to water and 

increased exposure and disease 

Very likely Likelihood of climate event 

is probable and research supports this pattern but adaptive measures (water treatment and infrastructure) would reduce this effect 

Giardia Rising Temperature Expanding recreational (swimming) season 

may increase likelihood of exposure and 

disease 

About as likely as not

Likelihood of climate event is high but there is 

insufficient research on this relationship 

Changes in Precipitation 

Increasing precipitation associated with increased loading of parasite to water and 

increased disease 

Very likely Likelihood of climate event 

is probable and research supports this pattern but adaptive measures (water treatment and infrastructure) would reduce this effect 

Shifts in Reservoir Host Ranges or 

Behavoir 

Increasing temperature associated with shifting range in reservoir species (carriers) 

and expanded disease range 

About as likely as not

Likelihood of climate event is probable but there is insufficient research on this relationship 

a Likelihood was based on expert judgment of the strength of the research and the likelihood of the event. See Ch

discussion of likelihood (section 1.5). 
SAP 4.6 Chapter 2: Human Health 

2-67 

Table 2.3. Climate-Sensitive Health Outcomes and Particularly Vulnerable 

Groups 

Climate-Sensitive Health 

Outcome

Particularly Vulnerable Groups 

Heat-Related Illnesses and 

Deaths 

Elderly, chronic medical conditions, infants and 

children, pregnant women, urban and rural poor, 

outdoor workers 

Diseases and Deaths Related 

to Air Quality 

Children, pre-existing heart or lung disease, diabetes, 

athletes, outdoor workers 

Illnesses and Deaths Due to 

Extreme Weather Events

Poor, pregnant women, chronic medical conditions, 

mobility and cognitive constraints 

Water- and Foodborne Illness Immunocompromised, elderly, infants; specific risks for 

specific consequences (e.g., Campylobacter and 

Guillain-Barre syndrome, E. coli O157:H7) 

Vectorborne Illnesses 

A. Lyme Disease Children, outdoor workers 

B. Hantavirus Rural poor, occupational groups 

C. Dengue Infants, elderly 

D. Malaria Children, immunocompromised, pregnant women, 

genetic (e.g., G6PD status)
SAP 4.6 

Table 2.4: Actors and Their Roles and Responsibilities for Adaptation to Climate Change Health Risks Actor Reduce Exposures Prevent Onset of Adverse Health 

Outcomes 

Reduce Mo

Extreme Temperature and Weather Events Individuals Stay informed about impending weather 

events Follow guidance for emergency preparedness 

Follow guidance for conduct during and 

following an extreme weather event (such as 

seeking cooling centers during a heatwave or evacuation during a hurricane) 

Seek treatm

Community, State, and National Agencies 

Provide scientific and technical guidance for building and infrastructure 

standards Enforce building and infrastructure standards, including identification of restricted building zones where necessary 

Develop scientific and technical guidance and decisions support tools for development 

of early warning systems and emergency response plans, including appropriate individual behavior Implement early warning systems and emergency response plans Conduct tests of early warning systems and response plans before events Conduct education and outreach on emergency preparedness 

Ensure that preparedne

services Improve prair, water, aexposures Improve sucollect, anadata on the extreme eveMonitor aneffectivene

NGOs and Other Actors 

NGOs and other actors play critical roles in emergency preparedness and disaster relief 

Education aprofessionaextreme we

Vectorborne and Zoonotic Diseases Individuals Take appropriate actions to reduce 

exposure to infected vectors, including 

eliminating vector breeding sites around residence 

Vaccinate for diseases to which one would likely be exposed 

Seek treatm

2-68 
SAP 4.6 

Community, State, and National Agencies 

Provide scientific and technical guidance and decision support tools for 

development of early warning systems Conduct effective vector (and pathogen) surveillance and control programs (including consideration of land use policies that affect vector distribution and habitats) Develop early warning systems for disease outbreaks, such as West Nile virus Develop and disseminate information on appropriate individual behavior to avoid exposure to vectors 

Conduct research on vaccines and other preventive measures Conduct research and development on rapid 

diagnostic tools Provide vaccinations to those likely to be exposed 

Conduct resoptions Develop aninformation symptoms o

individuals treatment 

Waterborne and Foodborne Diseases Individuals Follow proper food-handling guidelines 

Follow guidelines on drinking water from outdoor sources 

Seek treatm

Community, State, and National Agencies 

Improve surveillance and control programs for early detection of disease 

outbreaks Develop methods to ensure watershed protection and safe water and food handling (e.g., Clean Water Act) 

Sponsor research and development on rapid diagnostic tools for food- and waterborne 

pathogens 

Sponsor reson treatmenDevelop aninformation symptoms o

individuals treatment 

Diseases Related to Air Quality Individuals Follow advice on appropriate behavior 

on high ozone days 

For individuals with certain respiratory diseases, follow medical advice during 

periods of high air pollution 

Seek treatm

2-69 
SAP 4.6 

Community, State, and National Agencies 

Develop and enforce regulations of air pollutants (e.g., Clean Air Act) 

Develop decision support tools for early 

warning systems 

Conduct education and outreach on the risks of exposure to air pollutants 

Conduct resoptions 

2-70 
SAP 4.6 

2-71 

Table 2.5: Adaptation Measures to Reduce Climate Change-Related Health Risks 

Heatwaves Extreme Weather 

Events 

Vectorborne Diseases Waterborne Diseases 

Decision Support Tools 

Enhance early warning systems 

Enhance early warning systems and emergency response 

plans 

Enhance early warning systems based on 

climate and environmental data for selected diseases 

Develop early warning systems based on climat

and environmental data fconditions that may increase selected disease

Technology Development 

Improve building 

design to reduce heat loads during summer 

months 

Develop vaccines for West Nile virus and 

other vectorborne diseases Develop more rapid diagnostic tests 

Develop more rapid diagnostic tests 

Surveillance and Monitoring 

Alter health data collection systems to 

monitor for increased morbidity and mortality during a heatwave 

Alter health data collection systems to 

monitor for disease outbreaks during and after an extreme event 

Enhance vector surveillance and control 

programs Monitor disease occurrence 

Enhance surveillance anmonitoring programs for 

waterborne diseases 

Infrastructure Development 

Improve urban design 

to reduce urban heat 

islands by planting trees, increasing green spaces, etc. 

Design infrastructure to withstand projected extreme events 

Consider possible impacts of infrastructure 

development, such as water storage tanks, on vectorborne diseases 

Consider possible impacof placement of sources 

water- and foodborne pathogens (e.g., cattle nedrinking water sources) 

Other Conduct research on 

effective approaches 

to encourage appropriate behavior 

during a heatwave 

Conduct research on effective approaches to encourage appropriate behavior during an 

extreme event 
SAP 4.6 Chapter 2: Human Health 

2.11 Figures 

Figure 2.1. Temperature-mortality relative risk functions for 11 U.S. cities, 1973–1994. 

Northern cities: Boston, Massachusetts; Chicago, Illinois; New York, New York; Philadelphia, 

Pennsylvania; Baltimore, Maryland; and Washington, DC. Southern cities: Charlotte, North 

Carolina; Atlanta, Georgia; Jacksonville, Florida; Tampa, Florida; and Miami, Florida. Relative risk 

is defined as the risk of an event such as mortality relative to exposure, such that the relative 

risk is a ratio of the probability of the event occurring in the exposed group versus the 

probability of occurrence in the control (non-exposed) group. 

 (Curriero et al., 2002) 

2-72 
SAP 4.6 Chapter 2: Human Health 

Figure 2.2. Annual Deaths Attributed to Hurricanes in the United States, 1900 and 1940-2005 

1

10

100

1000

10000

1895

1905

1915

1925

1935

1945

1955

1965

1975

1985

1995

2005

Galveston, 1900, 

~8,000 deaths

2005, Dennis, Katrina, 

Rita, and Wilma 2,002 

deaths

Source: NOAA, 2007 

2-73 
SAP 4.6 Chapter 2: Human Health 

Figure 2.3. Annual Deaths Attributed to Flooding in the United States, 1940-2005 

0

60

120

180

240

300

360

420

480

540

600

1940 1945 1950 1955 1960 1965 1970 1975 1980 1985 1990 1995 2000 2005 2010

Year

Annual Deaths from Flooding

Source: NOAA, 2007a 

2-74 
SAP 4.6 Chapter 2: Human Health 

Figure 2.4. Drinking Waterborne Disease Outbreaks and 90%-ile Precipitation Events (a two 

month lag precedes outbreaks); 1948 – 1994.

Source: Curriero et al., 2001 

2-75 
SAP 4.6 Chapter 2: Human Health 

Figure 2.5: (a) Summertime Average Daily Maximum 8-hour Ozone Concentrations (ppb) for 

the 1990s and Changes for the (b) 2020s relative to the 1990s, (c) 2050s relative to the 1990s, 

and (d) 2080s relative to the 1990s. All are based on the A2 Scenario relative to the 1990s. Five 

consecutive summer seasons were simulated in each decade. 

Source: Hogrefe et al., 2004a. 

2-76 
SAP 4.6 Chapter 2: Human Health 

Figure 2.6. Frequency Distributions of Summertime Daily Maximum 8-hr Ozone 

Concentrations over the eastern United States in the 1990s, 2020s, and 2050s based on the A2 

Scenario. 

Source: From Hogrefe et al., 2005a 

2-77 
SAP 4.6 Chapter 2: Human Health 

Figure 2.7.a-d. U.S. maps indicating counties with existing vulnerability to climate 

sensitive health outcomes: (a) location of hurricane landfalls; (b) extreme heat events, 

defined by CDC as temperatures 10 or more degrees above the average high temperature 

for the region and lasting for several weeks; (c) percentage of population over age 65; (d) 

West Nile Virus cases reported in 2004. Historical disease activity, especially in the case 

of WNV, is not necessarily predictive of future vulnerability. Maps were generated using 

NationalAtlas.govTM Map Maker (2008). 

2-78 
Synthesis and Assessment Product 4.6 

Chapter 3: Effects of Global Change on Human 

Settlements 

Lead Author: Thomas J. Wilbanks, Oak Ridge National Laboratory

Contributing Authors: Paul Kirshen, Tufts University; Dale Quattrochi, NASA/Marshall Space Flight 

Center; Patricia Romero-Lankao, NCAR; Cynthia Rosenzweig, NASA/Goddard; Matthias Ruth, University 

of Maryland; William Solecki, Hunter College; Joel Tarr, Carnegie Mellon University

Contributors: Peter Larsen, University of Alaska-Anchorage; Brian Stone, Georgia Tech 

 

 
SAP 4.6 Chapter 3: Human Settlements 

Table of Contents

3.1 Introduction ............................................................................................................................................ 3 

3.1.1 Purpose ............................................................................................................................................. 3 

3.1.2 Background ....................................................................................................................................... 3 

3.1.3 Current State of Knowledge .............................................................................................................. 4 

3.2 Climate Change Impacts and the Vulnerabilities of Human Settlements ......................................... 4 

3.2.1 Determinants of Vulnerability........................................................................................................... 4 

3.2.2 Impacts of Climate Change on Human Settlements .......................................................................... 5

3.2.3. The Interaction of Climate Impacts with Non-Climate Factors. ...................................................... 7 

3.2.4 Realizing Opportunities from Climate Change in the United States................................................. 9 

3.2.5 Examples of Impacts on Metropolitan Areas in the United States .................................................. 10 

3.3 Opportunities for Adaptation of Human Settlements to Climate Change ...................................... 10 

3.3.1. Perspectives on Adaptation by Settlements .................................................................................... 11 

3.3.2 Major Categories of Adaptation Strategies..................................................................................... 12 

3.3.3 Examples of Current Adaptation Strategies.................................................................................. 13 

3.3.4: Strategies to Enhance Adaptive Capacity ...................................................................................... 14 

3.4. Conclusions .......................................................................................................................................... 14 

3.5 Expanding the Knowledge Base .......................................................................................................... 15 

3.6 References ............................................................................................................................................. 17 

3.7 Boxes...................................................................................................................................................... 24 

3.8 Tables..................................................................................................................................................... 29 

3.9 Figures ................................................................................................................................................... 31 

3-2 
SAP 4.6 Chapter 3: Human Settlements 

3.1 Introduction 

3.1.1 Purpose 

Human settlements are where people live and work, including all population centers 

ranging from small rural communities to densely developed metropolitan areas. This 

chapter addresses climate change impacts, both positive and negative, on human 

settlements in the United States. First, the chapter summarizes current knowledge about 

the vulnerability of human settlements to climate change, in a context of concurrent 

changes in other non-climate factors. Next, the chapter summarizes opportunities within 

settlements for adaptation to climate change. Finally, the chapter provides an overview of 

recommendations for expanding the current knowledge base with respect to climate 

change and human settlements. 

3.1.2 Background 

Events such as Hurricane Katrina in 2005 and electric power outages during the hot 

summer of 2006 have demonstrated how climate-related events can dramatically impact 

U.S. settlements. Climate affects the costs of assuring comfort at home and work. 

Climate affects inputs for a good life: water, products and services from agriculture and 

forestry, pleasures and tourist potentials from nature, biodiversity, and outdoor recreation. 

Climate also affects the presence and spread of diseases and other health problems, and it 

is associated with threats from natural disasters, including floods, fires, droughts, wind, 

hail, ice, and heat and cold waves. 

Some U.S. settlements may find opportunities in climate change. Warmer winters are not 

necessarily undesirable. Periods of change tend to reward forward-looking, effectivelygoverned communities. Considering climate change effects may help to focus attention 

on other important issues for the long-term sustainable development of settlements and 

communities. Furthermore, planning for the future is an essential part of public policy 

decision-making in urban areas. 

Since infrastructure investments in urban areas are often both large and difficult to 

reverse, climate considerations are increasingly perceived as one of a number of relevant 

issues to consider when planning for the future (Ruth, 2006a). If U.S. settlements, 

especially larger cities, respond effectively to climate change concerns, their actions 

could have far-reaching implications for human well-being, because these areas are 

where most of the U.S. population lives, large financial decisions are made, political 

influence is often centered, and technological and social innovations take place. 

Meanwhile, the pattern of human settlements in the United States is changing. In addition 

to shifts of population from frost-belt to sun-belt settlements, patterns are changing in 

other ways as well. For instance, what once appeared to be an inexorable spread of 

households from urban centers to peripheries is showing renewal in many city centers as 

metropolitan areas continue to expand across multiple jurisdictions (Solecki and 

Leichenko, 2006). Modern information technologies are enabling people to perform what 

were historically urban functions from relatively remote locations (Riebsame, 1997). 

3-3 
SAP 4.6 Chapter 3: Human Settlements 

3.1.3 Current State of Knowledge 

The current knowledge base provides limited grounds for developing conclusions and 

recommendations related to climate impacts on human settlements. In many cases, the 

best that can be done is to sketch out the issue “landscape” that should be considered by 

both policy-makers and the research community as a basis for further discussion, offering 

illustrations from the relatively small research literature that is now available. 

The fact is that little research has been done to date specifically on the effects of climate 

change in U.S. cities and towns. Reasons appear to include (i) limitations in capacities to 

project climate change impacts at the geographic scale of a metropolitan area (or smaller) 

and (ii) the fact that none of the federal agencies currently active in climate science 

research has a clear responsibility for settlement impact issues. Improvements in our 

understanding of the impacts of and adaptation to climate change across different sectors 

and geographic regions, differential vulnerabilities, and in designing interventions to 

build resilience are all needed (NRC, 2007). 

To some degree, gaps can be filled by referring to several comprehensive analyses that do 

exist, to literature on effects of climate variation on settlements and their responses, to 

research on climate change impacts on cities in other parts of the world, and to historical 

analogs of responses of urban areas to significant environmental changes. A text box 

entitled Historical Perspective of the U.S. Urban Responses to Environmental Change is 

included as Box 3.1. This perspective examines how American cities have been affected 

by environmental change over the past two centuries. But this is little more than a place 

to start. 

At the current state of knowledge, vulnerabilities to possible impacts are easier to project 

than actual impacts because they estimate risks or opportunities associated with possible 

consequences rather than estimating the consequences themselves, which requires far 

more detailed information about future conditions. Vulnerabilities are shaped not only by 

existing exposures, sensitivities, and adaptive capacities but also by the ability of 

settlements to develop responses to risks. 

3.2 Climate Change Impacts and the Vulnerabilities of Human 

Settlements 

This section examines possible impacts of climate change on settlements in the United 

States including the determinants of vulnerability to such impacts and how those impacts 

could affect settlement patterns and various systems related to those patterns. 

3.2.1 Determinants of Vulnerability 

It has been difficult to project impacts of climate change on human settlements in the 

United States, in part because climate change forecasts are not specific enough for the 

scale of decision-making (as for other relatively local-scale impact questions) but 

moreover because climate change is not the only change being confronted by settlements. 

More often, attention is paid to vulnerabilities to climate change, if those changes should 

occur. 

3-4 
SAP 4.6 Chapter 3: Human Settlements 

Vulnerabilities to or opportunities from climate change are related to three factors, both 

in absolute terms and in comparison to other elements (Clark et al., 2000): 

1. Exposure to climate change. To what climate changes are settlements likely to be 

exposed: Changes in temperature or precipitation? Changes in storm exposures 

and/or intensities? Changes in sea level? 

2. Sensitivity to climate change. If primary climate changes occur, how sensitive are 

the activities and populations of a settlement to those changes? For instance, a 

city dependent substantially on a regional agricultural or forestry economy, or to 

the availability of abundant water resources, might be considered more sensitive 

than a city whose economy is based mainly on an industrial sector less sensitive to 

climate variation. 

3. Adaptive capacity. Finally, if effects are experienced due to a combination of 

exposure and sensitivity, how able is a settlement to handle those impacts without 

disabling damages, perhaps even while realizing new opportunities? 

3.2.2 Impacts of Climate Change on Human Settlements 

Impacts of climate change on human settlements vary regionally (see Table 3.2 and 

Vignettes below), and generally relate to some of the following issues: 

1. Effects on health. It is well-established that higher temperatures in urban areas are 

related to higher levels of ozone which cause respiratory and cardiovascular 

problems. There is also some evidence that combined effects of heat stress and air 

pollution may be greater than simple additive effects (Patz and Balbus, 2001). 

Moreover, historical data show relationships between mortality and temperature 

extremes (Rozenzweig and Solecki, 2001a). Other health concerns include 

changes in exposure to water and food-borne diseases, vector-borne diseases, 

concentrations of plant species associated with allergies, and exposures to 

extreme weather events such as storms, floods, and fires (see Chapter 2). 

2. Effects on water and other urban infrastructures. Changes in precipitation 

patterns may lead to reductions in meltwater, river flows, groundwater levels, and 

in coastal areas lead to saline intrusion in rivers and groundwater, affecting water 

supply; and warming may increase water demands (Gleick et al., 2000; Kirshen, 

2002; Ruth et al., 2007). Moreover, storms, floods, and other severe weather 

events may affect other infrastructure, including sanitation systems, 

transportation, supply lines for food and energy, and communication. Exposed 

structures such as bridges and electricity transmission networks are especially 

vulnerable. In many cases, infrastructures are interconnected; an impact on one 

can also affect others (Kirshen, et al., 2007). An example is an interruption in 

energy supply, which increases heat stress for vulnerable populations (Ruth et al., 

2006a). Many of the infrastructures in older cities are aging and are already under 

stress from increasing demands. 

3-5 
SAP 4.6 Chapter 3: Human Settlements 

3. Effects on energy requirements. Warming is virtually certain to increase energy 

demand in U.S. cities for cooling in buildings while it reduces demands for 

heating in buildings (see SAP 4.5). Demands for cooling during warm periods 

could jeopardize the reliability of service in some regions by exceeding the supply 

capacity, especially during periods of unusually high temperatures (see Vignettes 

in Boxes 3.2 and 3.3). Higher temperatures also affect costs of living and business 

operation by increasing costs of climate control in buildings (Amato et al., 2005; 

Ruth and Lin, 2006c; Kirshen et al., 2007). 

4. Effects on the urban metabolism. An urban area is a living complex megaorganism, associated with a host of inputs, transformations, and outputs: heat, 

energy, materials, and others (Decker et al., 2000). An example is the Urban Heat 

Index, which measures the degree to which built/paved areas are associated with 

higher temperatures than surrounding rural areas (see Box 3.4: Climate Change 

Impacts on the Urban Heat Island Effect (UHI)). Imbalances in the urban 

metabolism can aggravate climate change impacts, such as roles of UHI in the 

formation of smog in cities. The maps in this box demonstrate how the built 

environment creates and retains heat in metropolitan settings.

5. Effects on economic competitiveness, opportunities, and risks. Climate change has 

the potential not only to affect settlements directly but also to affect them through 

impacts on other areas linked to their economies at regional, national, and 

international scales (Rosenzweig and Solecki, 2006). In addition, it can affect a 

settlement’s economic base if it is sensitive to climate, as in areas where 

settlements are based on agriculture, forestry, water resources, or tourism (IPCC, 

2001b).

6. Effects on social and political structures. Climate change can add to stress on 

social and political structures by increasing management and budget requirements 

for public services such as public health care, disaster risk reduction, and even 

public security. As sources of stress grow and combine, the resilience of social 

and political structures that are already somewhat unstable is likely to suffer, 

especially in areas with relatively limited resources (Sherbinin et al., 2006). 

7. Effects on vulnerable populations (see Chapter 1). Where climate change stresses 

settlements, it is likely to be especially problematic for vulnerable parts of the 

population: the poor, the elderly, those already in poor health, the disabled, those 

living alone, those with limited rights and power (e.g., recent in-migrants with 

limited English skills), and/or indigenous populations dependent on one or a few 

resources. As one example, warmer temperatures in urban summers have a more 

direct impact on populations who live and work without air-conditioning. 

Implications for environmental justice are clear; see, for instance, Congressional 

Black Caucus Foundation, 2004. 

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8. Effects on vulnerable regions. Approximately half of the U.S. population, 160 

million people, will live in one of 673 coastal counties by 2008 (Crossett et al., 

2004). Obviously, settlements in coastal areas – particularly on gently-sloping 

coasts –should be concerned about sea level rise in the longer term, especially if 

they are subject to severe storms and storm surges and/or if their regions are 

showing gradual land subsidence (Neumann et al., 2000; Kirshen et al., 2004). 

Settlements in risk-prone regions have reason to be concerned about severe 

weather events, ranging from severe storms combined with sea-level rise in 

coastal areas to increased risks of fire in drier arid areas. Vulnerabilities may be 

especially great for rapidly-growing and/or larger metropolitan areas, where the 

potential magnitude of both impacts and coping requirements could be very large 

(IPCC, 2001b; Wilbanks et al., 2007b). 

Different combinations of circumstances are likely to cause particular concerns for cities 

and towns in the United States as they consider possible implications of climate change. 

3.2.3. The Interaction of Climate Impacts with Non-Climate Factors. 

In general, climate change effects on human settlements in the United States are 

imbedded in a variety of complexities that make projections of quantitative impacts over 

long periods of time very difficult. For instance, looking out over a period of many 

decades, it seems likely that other kinds of change—such as technological, economic, and 

institutional—will have more impact on the sustainability of most settlements rather than 

climate change per se (Wilbanks, et al., 2007b). Climate change will interact with other 

processes, driving forces, and stresses; and its significance, positive or negative, will 

largely be determined by these interactions. It is therefore difficult to assess effects of 

climate change without a reasonably clear picture of future scenarios for these other 

processes. 

In many cases, these interactions involve not only direct impacts such as warming or 

more or less precipitation but, sometimes more important, second, third, or higher-order 

impacts, as direct impacts cascade through urban systems and other settlementdetermined processes (e.g., warming which affects urban air pollution which affects 

health which affects public service requirements which affect social harmony: Kirshen et 

al., 2007). Some of these higher-order impacts, in turn, may feed back to create ripple 

effects of their own. For example, a heat wave may trigger increased energy demands for 

cooling, which may cause more air conditioners and power generators to be operated, 

which could lead to higher urban heat island effects, inducing even higher cooling needs. 

Besides this “multi-stress” perspective, it is highly likely that effects of climate change on 

settlements are shaped by certain “thresholds,” below which effects are incidental but 

beyond where effects quickly become major when a limiting or inflection point is 

reached. An example might be a city’s capacity to cope with sustained heat stress 

combined with a natural disaster. In general, these climate-related thresholds for human 

settlements in the United States are not well-understood. For multi-stress assessments of 

thresholds, changes in climate extremes are very often of more concern than changes in 

climate averages. Besides extreme weather events, such as hurricanes or tornadoes, ice 

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SAP 4.6 Chapter 3: Human Settlements 

storms, winds, heat waves, drought, or fire, settlements may be affected by changes in 

daily or seasonal high or low levels of temperature or precipitation, which have not 

always been projected by climate change models.

Finally, human settlements may be affected by climate change mitigation initiatives as 

well as by climate change itself. Examples include effects on policies related to energy 

sources and uses, environmental emissions, and land use. The most direct and short-term 

effects would likely be on settlements in regions whose economies are closely related to 

the production and consumption of large quantities of fossil fuels. Indirect and longer 

term effects are less predictable. 

As climate change affects settlements in the United States, impacts are realized at the 

intersection of climate change with underlying forces. Most of the possible effects are 

linked with changes in regional comparative advantage, with consequent migration of 

population and economic activities (Ruth and Coelho, in press). Examples of these 

complex interactions and issues include: 

1. Regional risks and availability of insurance. It is possible that regions exposed to 

risks from climate change will see movement of population and economic activity 

to other locations. One reason is public perceptions of risk, but a more powerful 

driving force may be the availability of insurance. The insurance sector is one of 

the most adaptable of all economic sectors, and its exposure to costs from severe 

storms and other extreme weather events is likely to lead it to withdraw (or to 

make much more expensive) private insurance coverage from areas vulnerable to 

climate change impacts (Wilbanks, et al., 2007b), which would encourage both 

businesses and individual citizens to consider other locations over a period of 

several decades. 

2. Areas whose economies are linked with climate-sensitive resources or assets. 

Settlements whose economic bases are related to such sectors as agriculture, 

forestry, tourism, water availability, or other climate-related activities could be 

affected either positively or negatively by climate change, depending partly on the 

adaptability of those sectors (i.e., their ability to adapt to changes without shifting 

to different locations). 

3. Shifts in comparative living costs, risks, and amenities. Related to a range of 

possible climate change effects – higher costs for space cooling in warmer areas, 

higher costs of water availability in drier areas, more or less exposure to storm 

impacts in some areas, and sea level rise – regions of the United States and their 

associated settlements are likely to see gradual changes over the long term in their 

relative attractiveness for a variety of human activities. One example, although its 

likelihood is highly uncertain, would be a gradual migration of the “Sun Belt” 

northward, as retirees and businesses attracted by environmental amenities find 

that regions less exposed to very high temperatures and seasonal major storms are 

more attractive as places to locate. 

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SAP 4.6 Chapter 3: Human Settlements 

4. Changes in regional comparative advantage related to shifts in energy resource 

use. If climate mitigation policies result in shifts from coal and other fossil 

resources toward non-fossil energy sources, or if climate changes affect the 

prospects of renewable energy sources (especially hydropower), regional 

economies related to the production and/or use of energy from these sources could 

be affected, along with regional economies more closely linked with alternatives. 

(citation: SAP 4.5) 

5. Urban “footprints” on other areas. Resource requirements for urban areas 

involve larger areas than their own bounded territories alone. Ecologists have 

sought to estimate the land area required to supply the consumption of resources 

and compensate for emissions and other wastes from urban areas (e.g., Folke et 

al., 1997). By possibly affecting settlements, along with their resource capacities 

for their inputs and destinations of their outputs, climate change could affect the 

nature, size, and geographic distribution of these footprints. 

Human settlements are foci for many economic, social, and governmental processes, and 

historical experience has shown that catastrophes in cities can have significant economic, 

financial, and political effects much more broadly. The case which has received the most 

attention to date is insurance and finance (Wilbanks, et al., 2007b). 

3.2.4 Realizing Opportunities from Climate Change in the United States 

Climate change can have positive as well as negative implications for settlements. 

Examples of potential positive effects include: 

1. Reduced winter weather costs and stresses. Warmer temperatures in periods of 

the year that are normally cold are not necessarily undesirable. They reduce coldrelated stresses and costs (e.g., costs of warming buildings and costs of clearing 

ice and snow from roads and streets), particularly for cold-vulnerable populations. 

They expand opportunities for warmer-weather recreational opportunities over 

larger parts of the year, and they expand growing seasons for crops, parks, and 

gardens. 

2. Increased attention to long-term sustainability. One of the most positive aspects 

of climate change can be that its capacity to stimulate a broader discussion of 

what sustainability means for settlements (Wilbanks, 2003; Ruth, 2006). Even if 

climate change itself may not be the most serious threat to sustainability, 

considering climate change impacts in a multi-change, multi-stage context can 

encourage and facilitate processes that lead to progress in dealing with other 

sources of stress as well. 

3. Improved competitiveness compared with settlements subject to more serious 

adverse impacts. While some settlements may turn out to be “losers” due to 

climate change impacts, others may be “winners,” as changes in temperature or 

precipitation result in added economic opportunities (see the following section), at 

least if climate change is not severe. In addition for many settlements climate 

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SAP 4.6 Chapter 3: Human Settlements 

change can be an opportunity not only to compare their net impacts with others, 

seeking advantages as a result, but to present a progressive image by taking 

climate change (and related sustainability issues) seriously. 

3.2.5 Examples of Impacts on Metropolitan Areas in the United States 

Possible impacts of climate change on settlements in the United States are usually 

assessed by projecting climate changes at a regional scale: temperature, precipitation, 

severe weather events, and sea level rise (see Table 3.2 and Boxes 3.2 and 3.3). Ideally, 

these regional projections are at a relatively detailed scale, and ideally they consider 

seasonal as well as annual changes and changes in extremes as well as in averages; but 

these conditions cannot always be met. 

The most comprehensive assessments of possible climate change impacts on settlements 

in the United States have been two studies of major metropolitan areas: 

1. New York: This assessment concluded that impacts of climate change on this 

metropolitan area are likely to be primarily negative over the long term, with 

potentially significant costs increasing as the magnitude of climate change 

increases, although there are substantial uncertainties. (Rosenzweig and Solecki, 

2001a; Rosenzweig and Solecki, 2001b; Solecki and Rosenzweig, 2006). 

2. Boston: This assessment concluded that long-term impacts of climate change are 

likely to depend at least as much on behavioral and policy changes over this 

period as on temperature and other climate changes (Kirshen et al., 2004; 

Kirshen et al., 2006; Kirshen et al., 2007) 

Other U.S. studies include Seattle (Hoo and Sumitani, 2005) and Los Angeles (Koteen et 

al., 2001) (Table 3.1). Internationally, studies have included several major metropolitan 

areas, such as London (London Climate Change Partnership, 2004) and Mexico City 

(Molina et al., 2005) as well as possible impacts on smaller settlements (e.g., AIACC: see 

www.aiaccproject.org). A relevant historical study of effects of an urban heat wave in the 

United States is reported by Klinenberg (2003). 

3.3 Opportunities for Adaptation of Human Settlements to 

Climate Change 

Settlements are important in considering prospects for adaptation to climate change, both 

because they represent concentrations of people and because buildings and other 

infrastructures offer ways to manage risk and monitor/control threats associated with 

climate extremes and other non-climate stressors. 

Where climate change presents risks of adverse impacts for U.S. settlements and their 

populations, there are two basic options to respond to such concerns (a third is combining 

the two). One response is to contribute to climate change mitigation strategies, i.e., by 

taking actions to reduce their greenhouse gas emissions and by showing leadership in 

encouraging others to support such actions (see Box 3.5: Roles of Settlements in Climate 

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SAP 4.6 Chapter 3: Human Settlements 

Change Mitigation). The second response is to consider strategies for adaptation, i.e.,

finding ways either to reduce sensitivity to projected changes or to increase the 

settlement’s coping capacities. Adaptation can rely mainly on anticipatory actions to 

avoid damages and costs, such as “hardening” coastal structures to sea-level rise; or 

adaptation can rely mainly on response potentials, such as emergency preparedness; or it 

can include a mix of the two approaches. Research to date suggests that anticipatory 

adaptation may be more cost-effective than reactive adaptation (Kirshen et al., 2004). 

Adaptation strategies will be important to the well-being of U.S. settlements as climate 

change evolves over the next century. As just one example, the New York climate impact 

assessment (Rosenzweig and Solecki, 2001a) projects significant increases in heat-related 

deaths based on historical relationships between heat stress and mortality, unchanged by 

adaptation. The Boston CLIMB assessment (Kirshen et al., 2004) projects that, despite 

similar projections of warming, heat-related deaths will decline over the coming century 

because of adaptation. Whether or not adaptation to climate change occurs in U.S. cities 

is therefore a potentially serious issue. The CLIMB assessment includes analyses 

showing that in many cases adaptation actions taken now are better than adaptation 

actions delayed until a later time (Kirshen et al., 2006). 

3.3.1. Perspectives on Adaptation by Settlements 

For decision-makers in U.S. settlements climate change is yet one more source of 

possible risks that need to be addressed. Climate change is different as an issue because it 

is relatively long-term in its implications, future impacts are uncertain, and public 

awareness is growing from a relatively low level to a higher level of concern. Because 

climate change is different in these ways, it is seldom attractive to consider allocating 

massive amounts of funding or management attention to current climate change actions. 

What generally makes more sense is to consider ways that actions which reduce 

vulnerabilities to climate change impacts (or increase prospects for realizing benefits 

from climate change impacts) are also desirable for other reasons as well: often referred 

to as “co-benefits.” Examples include actions that reduce vulnerabilities to current 

climate variability regardless of long-term climate change, actions that add resilience to 

water supply and other urban infrastructures that are already stressed, and actions that 

make metropolitan areas more attractive for their citizens in terms of their overall quality 

of life. 

Cities and towns have used both “hard” approaches such as developing infrastructure and 

“soft” approaches such as regulations to address impacts of climate variability. Examples 

include water supply and waste water systems, drainage networks, buildings, 

transportation systems, land use and zoning controls, water quality standards and 

emission caps, and tax incentives. All of these are designed in part with climate and 

environmental conditions in mind. The setting of regulations has always been a context of 

benefit-cost analysis and political realities; and infrastructure is also designed in a 

benefit-cost framework, subject to local design codes. The fact that both regulations and 

infrastructures vary considerably across the United States reflects cultural, economic, and 

environmental factors; and this suggests that mechanisms exist to respond to concerns 

about climate change. Urban designers and managers deal routinely with uncertainties, 

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SAP 4.6 Chapter 3: Human Settlements 

because they must consider uncertain demographic and other socioeconomic changes; 

thus, if climate change is properly institutionalized into the urban planning process, it can 

be handled as yet another uncertainty. 

3.3.2 Major Categories of Adaptation Strategies 

Adaptation strategies for human settlements, large and small, include a wide range of 

possibilities such as: 

1. Changing the location of people or activities (within or between settlements) – 

especially addressing the costs of sustaining built environments in vulnerable 

areas: e.g., siting and land use policies and practices to shift from more vulnerable 

areas to less, adding resilience to new construction in vulnerable areas, increased 

awareness of changing hazards and associated risks, and assistance for the lessadvantaged (including actions by the private insurance sector as a likely driving 

force). 

2. Changing the spatial form of a settlement – managing growth and change over 

decades without excluding critical functions (e.g., architectural innovations 

improving the sustainability of structures, reducing transportation emissions by 

reducing the length of journeys to work, seeking efficiencies in resource use 

through integration of functions, and moving from brown spaces to green spaces). 

Among the alternatives receiving the most attention are encouraging “green 

buildings” (e.g., green roofs: Parris, 2007; see Rosenzweig et al., 2006a; 

Rosenzweig et al., 2006b) and increasing “green spaces” within urban areas (e.g.,

Bonsignore, 2003). 

3. Technological change to reduce sensitivity of physical and linkage infrastructures

– e.g., more efficient and affordable interior climate control, surface materials that 

reduce heat island effects (Quattrochi et al., 2000), waste reduction and advanced 

waste treatment, and better warning systems and controls. Physical design 

changes for long-lived infrastructure may also be appropriate, such as building 

water-treatment or storm-water runoff outflow structures based on projected sea 

level rather than the historical level. 

4. Institutional change to improve adaptive capacity, including assuring effective 

governance, providing financial mechanisms for increasing resiliency, improving 

structures for coordinating among multiple jurisdictions, targeting assistance 

programs for especially impacted segments of the population, adopting 

sustainable community development practices, and monitoring changes in 

physical infrastructures at an early stage (Wilbanks et al., 2007a). Policy 

instruments include zoning, building and design codes, terms for financing, and 

early warning systems (Kirshen et al., 2005). 

5. “No regrets” or low net cost policy initiatives that add resilience to the settlement 

and its physical capital – e.g., in coastal areas changing building codes for new 

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SAP 4.6 Chapter 3: Human Settlements 

construction to require coping with projected amounts of sea-level rise over the 

expected lifetimes of the structures. 

The choice of strategies from among the options is likely to depend on co-benefits in 

terms of other social, economic, and ecological driving forces; the availability of fiscal 

and human resources; and political aspects of “who wins” and “who loses.” 

3.3.3 Examples of Current Adaptation Strategies 

In most cases in the United States, settlements have been more active in climate change 

mitigation than climate change adaptation (see Box 3.5), but there are some indications 

that adaptation is growing as a subject of interest (Solecki and Rosenzweig, 2005; Ruth, 

2006). Bottom-up grassroots activities currently under way in the United States are 

considerable, and that number appears to be growing. For example, Boston has built a 

new wastewater treatment plant at least one-half meter higher than currently necessary to 

cope with sea level rise, and in a coastal flood protection plan for a site north of Boston 

the U.S. Corps of Engineers incorporated sea-level rise into their analysis (Easterling et 

al., 2004). California is considering climate change adaptation strategies as a part of its 

more comprehensive attention to climate change policies (Franco, 2005). And, Alaska is 

already pursuing ways to adapt to permafrost melting and other climate change effects. 

Meanwhile, in some cases, settlements are taking actions for other reasons that add 

resilience to climate change effects. An example is the promotion of water conservation, 

which is reducing per capita water consumption in cities that could be subject to 

increased water scarcity (City of New York, 2005). 

It seems very likely that local governments will play an important role in climate change 

responses in the United States Many adaptation options must be evaluated at a relatively 

local scale in terms of their relative costs and benefits and their relationships with other 

urban sustainability issues, and local governments are important as guardians of public 

services, able to mobilize a wide range of stakeholders to contribute to broad communitybased initiatives (as in the case of the London Climate Change Partnership, 2004). 

Because climate change impact concerns and adaptation potentials tend to cross 

jurisdictional boundaries in highly fragmented metropolitan areas, local actions might 

encourage cross-boundary interactions that would have value for other reasons as well. 

While no U.S. communities have developed comprehensive programs to ameliorate the 

effects of heat islands, some localities are recognizing the need to address these effects. 

In Chicago, for example, several municipal buildings have been designed to 

accommodate “green” rooftops. Atlanta has had a Cool Communities “grass roots” effort 

to educate local and state officials and developers on strategies that can be used to 

mitigate the UHI. This Cool Communities effort was instrumental in getting the State of 

Georgia to adopt the first commercial building code in the country emphasizing the 

benefits of cool roofing technology (Young, 2002; Estes, Jr. et al., 2003). The “Excessive 

Heat Events Guidebook” developed by the Environmental Protection Agency in 

collaboration with NOAA, CDC, and DHS provides information for municipal officials 

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SAP 4.6 Chapter 3: Human Settlements 

in the event of an excessive heat event: 

http://www.epa.gov/hiri/about/heatguidebook.html. 

3.3.4: Strategies to Enhance Adaptive Capacity 

In most cases, the likelihood of effective adaptation is related to the capacity to adapt, 

which in turn is related to such variables as knowledge and awareness, access to fiscal 

and human resources, and good governance (IPCC, 2001b). Strategies for enhancing such 

capacities in U.S. settlements are likely to include the development and use of local 

expertise on climate change issues (AAG, 2003), attention to the emerging experience 

with climate change effects and response strategies globally and in other U.S. 

settlements, information sharing about adaptation potentials and constraints among 

settlements and their components (likely aided by modern information technology), and 

an emphasis on participatory decision-making, where local industries, institutions, and 

community groups are drawn into discussions of possible responses. 

3.4. Conclusions 

Even from a current knowledge base that is very limited, it is possible to conclude several 

things about effects of climate change on human settlements in the United States: 

1. Climate change takes place in the context of a variety of factors driving an area’s 

development: it is likely to be a secondary factor in most places, with its 

importance determined mainly by its interactions with other factors, except in the 

case of major abrupt climate change (very likely). 

2. Effects of climate change will vary considerably according to location-specific 

vulnerabilities, and the most vulnerable areas are likely to be Alaska, coastal and 

river basins susceptible to flooding, arid areas where water scarcity is a pressing 

issue, and areas whose economic bases are climate-sensitive (very likely). 

3. The main impact concerns, in areas other than Alaska, have to do with changes in 

the intensity, frequency, and/or location of extreme weather events and, in some 

cases, water availability rather than changes in temperature (very likely). 

4. Over the time period covered by current climate change projections, the potential 

for adaptation through technological and institutional development as well as 

behavioral changes are considerable, especially where such developments meet 

other sustainable development needs as well, especially considering the initiatives 

already being shown at the local level across the United States (extremely likely). 

5. While uncertainties are very large about specific impacts in specific time periods, 

it is possible to talk with a higher level of confidence about vulnerabilities to 

impacts for most settlements in most parts of the United States (virtually certain). 

3-14 
SAP 4.6 Chapter 3: Human Settlements 

3.5 Expanding the Knowledge Base 

A number of sources, including NACC, 1998; Parson et al., 2003; Ruth, 2006; and Ruth 

et al., 2004, have considered research pathways for improving the understanding of 

effects of climate change on human settlements in the United States. 

The following list suggests a number of research topics that would help expand the 

knowledge base about the linkages between climate change and human settlements. 

 Advance understanding of settlement vulnerabilities, impacts, and adaptive 

responses in a variety of different local contexts around the country through case 

studies. In addition to identifying vulnerable settlements, these studies should also 

identify vulnerable populations (such as the urban poor and native populations on 

rural and/or tribal lands) that have limited capacities for response to climate 

change, within those settlements. Better understanding of climate change at the 

community scale would provide a basis for adaptation research that addresses 

social justice and environmental equity concerns. 

 Develop better projections of climate change at the scale of U.S. metropolitan 

areas or smaller, including scenarios projecting extremes and scenarios involving 

abrupt changes. 

 Improve abilities to associate projections of climate change in U.S. settlements 

with changes in other driving forces related to impacts, such as changes in 

metropolitan/urban patterns and technological change. 

 Design practically implementable, socially acceptable strategies for shifting 

human populations and activities away from vulnerable locations. 

 Improve the understanding of vulnerabilities of urban inflows and outflows to 

climate change impacts, as well as second and third-order impacts of climate 

change in urban environments, including interaction effects among different 

aspects of the urban system. 

 Improve the understanding of the relationships between settlement patterns (both 

regional and intra-urban) and resilience/adaptive capacity. 

 Improve understanding of how urban decision-making is changing as populations 

become more heterogeneous and decisions become more decentralized, especially 

as this affects adaptive responses. 

 Review current policies and practices related to climate change responses to help 

inform community decision-makers and other stakeholders about potentials for 

relatively small changes to make a large difference. 

 Evaluate and document experiences with urban/settlement climate change 

responses while involving decision-making, research and stakeholder 

communities more actively in discussions of climate change impacts and response 

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SAP 4.6 Chapter 3: Human Settlements 

issues. Focus attention on the costs, benefits, and possible limits and potentials of 

adaptation to climate change vulnerabilities in U.S. cities and smaller settlements. 

 Improve tools and approaches for infrastructure planning and design to reduce 

exposure and sensitivity to climate change effects while increasing adaptive 

capacity. 

 Enhance coordination within federal government agencies to improve 

understanding about impacts, vulnerabilities and responses to climate change for 

the nation’s cities and smaller settlements. Connections with U.S. urban decisionmakers can enable integration of climate change considerations into what they do 

with building codes, zoning, lending practices, etc. as mainstreamed urban 

decision processes. 

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SAP 4.6 Chapter 3: Human Settlements 

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infrastructures and services: The case of metro Boston. In: Climate Change and 

Variability: Impacts and Responses [M. Ruth, P. Kirshen, and Donaghy, (eds.)]. 

Edward Elgar, Cheltenham, UK, pp. 190-252. 

Kirshen, P., M. Ruth, and W. Anderson, 2007: Interdependencies of urban climate 

change impacts and adaptation strategies: a case study of metropolitan Boston. 

Climatic Change, 66, 105-122. 

Klinenberg, E., 2003: Heat Wave: A Social Autopsy of Disaster in Chicago. University 

of Chicago, Chicago, Illinois. 

3-19 
SAP 4.6 Chapter 3: Human Settlements 

Koteen, L., J. Bloomfield, T. Eichler, C. Tonne, R. Young, H. Poulshock, and A. Sosler, 

2001: Hot Prospects: The Potential Impacts of Global Warming on Los Angeles 

and the Southland. Environmental Defense, Washington, DC. 

Kretch, S. III, 1999. Myth and History: The Ecological Indian. W.W. Norton, New 

York. 

Larsen, Peter, O.S. Goldsmith, O. Smith, and M. Wilson, 2007: A Probabilistic Model to 

Estimate the Value of Alaska Public Infrastructure at Risk to Climate Change. 

ISER Working Paper, Institute of Social and Economic Research, University of 

Alaska, Anchorage, Alaska.

Lo, C.P. and D.A. Quattrochi, 2003: Land-use and land-cover change, urban heat island 

phenomenon, and health implications: a remote sensing approach. 

Photogrammetric Engineering and Remote Sensing. 

London Climate Change Partnership, 2004: London’s Warming, A Climate Change 

Impacts in London Evaluation Study. London, 293 pp. 

McCarthy, K., D. Peterson, N. Sastry, and M. Pollard, 2006: The Repopulation of New 

Orleans after Hurricane Katrina. Rand, Santa Monica, California. 

Molina, M., et al., 2005: Air Quality in the Mexico Megacity: An Integrated Assessment. 

Kluwer, Dordrecht, Netherlands. 

Morehouse, B., G. Christopherson, M. Crimmins, B. Orr, J. Overpeck, T. Swetnam, and 

S. Yool, 2006: Modeling interactions among wildland fire, climate and society in 

the context of climatic variability and change in the southwest US. In: Regional 

Climate Change and Variability [M. Ruth, K. Donaghy, and P. Kirshen (eds.)]. 

Edward Elgar Publishing, pp. 58-78. 

NACC, 1998: Climate Change and a Global City: An Assessment of the Metropolitan 

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Studies. 

NACC, 2000: Climate Change Impacts on the United States: The Potential 

Consequences of Climate Variability and Change. U.S. Global Change Research 

Program, Washington, DC. 

NACC, 2001: Climate Change Impacts on the United States: The Potential 

Consequences of Climate Variability and Change, U.S. Global Change Research 

Program, Washington, DC. 

3-20 
SAP 4.6 Chapter 3: Human Settlements 

Neumann, J.E., G. Yohe, R. Nichols, and M. Manion, 2000: Sea Level Rise and Global 

Climate Change: A Review of Impacts to U.S. Coasts. Pew Center on Global 

Climate Change, Washington, DC. 

NRC, 2007: Evaluating Progress of the U.S. Climate Change Science Program: Methods 

and Preliminary Results. Committee on Strategic Advice on the U.S. Climate 

Change Science Program, National Academies Press, Washington, DC. 

Parris, T., 2007: Green buildings. Environment, 49(1), 3. 

Parson, E.A., R.W. Corell, E.J. Barron, V. Burkett, A. Janetos, L. Joyce, T.R. Karl, M.C. 

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Understanding climatic impacts, vulnerabilities, and adaptation in the United 

States: building a capacity for assessment, Climatic Change, 57(1-2), 9–42. 

Patz, J.A. and J.M. Balbus, 2001: Global climate change and air pollution. In: Ecosystem 

Change and Public Health. A Global Perspective [Aron J.L. and J.A. Patz (eds.)]. 

The Johns Hopkins University Press, Baltimore, pp. 379–408. 

Quattrochi, D.A., J.C. Luvall, D.L. Rickman, M.G. Estes, Jr., C.A. Laymon, and B.F. 

Howell, 2000: A decision support system for urban landscape management using 

thermal infrared data. Photogrammetric Engineering and Remote Sensing, 66,

1195-1207. 

Rabe, B., 2006: Second Generation Climate Policies in the States. Paper presented at the 

Conference Climate Change Politics in North America, Washington, DC, 18-19. 

Ridd, M.K., 2006: 10.3 Environmental dynamics of human settlements. In: Remote 

Sensing of Human Settlements, Manual of Remote Sensing, Third Edition, Volume 

5 [Ridd, M.K. and J.D. Ripple, (eds.)]. American Society for Photogrammetry and 

Remote Sensing, Bethesda, Maryland, pp. 564-642. 

Riebsame, W., 1997: Atlas of the New West: Portrait of a Changing Region. W.W. 

Morton, New York. 

Romero Lankao, P., 2007: Are we missing the point? Particularities of urbanization, 

sustainability and carbon emissions in Latin American cities. Urbanization and 

Environment, 19(1). 

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Kinney, D. Hill, and R. Zimmerman, 2000: Climate Change and a Global City: 

An Assessment of the Metropolitan East Coast Region. U.S. Global Change 

Research Program. 

3-21 
SAP 4.6 Chapter 3: Human Settlements 

Rosenzweig, C., and W. Solecki (eds.), 2001a: Climate Change and a Global City: The 

Potential Consequences of Climate Variability and Change – Metro East Coast. 

Columbia Earth Institute, New York. 

Rosenzweig, C. and W.D. Solecki, 2001b: Global environmental change and a global 

city: lessons for New York. Environment, 43(3), 8-18. 

Rosenzweig, C., S. Gaffin, and I. Parshall (eds.), 2006a: Green Roofs In The New York 

Metropolitan Region. Research Report, Columbia University Center for Climate 

Systems Research and NASA Goddard Institute for Space Studies, New York. 

Rosenzweig, C., W. Solecki, and R. Slosberg, 2006b: Mitigating New York City’s Heat 

Island with Urban Forestry, Living Roofs, and Light Surfaces. Final Report, New 

York City Regional Heat Island Initiative, Prepared for the New York State 

Energy Research and Development Authority, NYSERDA Contract #6681, New 

York. 

Rosenzweig, C., W. Solecki, L. Parshall, M. Chopping, G. Pope, and 

R. Goldberg, 2005: Characterizing the urban heat island in current and future 

climates in New Jersey, Global Environmental Change Part B: Environmental 

Hazards, (6), 51-62. 

Ruth, M. (ed.), 2006: Smart Growth and Climate Change. Edward Elgar Publishers, 

Cheltenham, England, 403 pp. 

Ruth, M., A. Amato, and P. Kirshen, 2006a: Impacts of changing temperatures on heatrelated mortality in urban areas: the issues and a case study from metropolitan 

Boston. In: Smart Growth and Climate Change [Ruth, M. (ed.)]. Edward Elgar 

Publishers, Cheltenham, England, pp. 364 – 392. 

Ruth, M., K. Donaghy, and P.H. Kirshen (eds.), 2006b: Regional Climate Change and 

Variability: Impacts and Responses. Edward Elgar Publishers, Cheltenham, 

England, 260 pp. 

Ruth, M. and A-C Lin, 2006c: Regional energy and adaptations to climate change: 

methodology and application to the state of Maryland, Energy Policy, 34, 2820-

2833. 

Ruth, M., C. Bernier, N. Jollands, and N. Golubiewski, 2007: Adaptation to urban water 

supply infrastructure to impacts from climate and socioeconomic changes: the 

case of Hamilton, New Zealand. Water Resources Management, 21, 1031-1045. 

Ruth, M. and D. Coelho. In press: Managing the interrelations among urban 

infrastructure, population, and institutions. Global Environmental Change.

3-22 
SAP 4.6 Chapter 3: Human Settlements 

Selin, H. and S.D. VanDeveer, 2006: Political science and prediction: 

What’s next for U.S. climate change policy? Review of Policy Research

(forthcoming). 

Sherbinin, A., A. Schiller, and A. Pulsipher, 2006: The vulnerability of global cities to 

climate hazards. Environment and Urbanization, 12(2), 93-102. 

Solecki, W.D. and C. Rosenzweig, 2006: Climate change and the city: observations from 

metropolitan New York. In: Cities and Environmental Change, [Bai, X. (ed.)]. 

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Environment, 48(4), 8-23. 

Steinberg, T., 2006. Acts of God: The Unnatural History of Natural Disaster in America. 

Oxford, New York. 

Stone, B., 2006: Physical planning and urban heat island formation, 2006. In: Smart 

Growth and Climate Change [Ruth, M. (ed.)]. Edward Elgar Publishers, 

Cheltenham, England, pp. 318-341. 

Vale, L.J., and T J. Campanella, 2005. The Resilient City: How Modern Cities Recover 

from Disaster, Oxford, New York. 

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place-based context. Climate Policy. Supplement on Climate Change and 

Sustainable Development, 3(1), 147-154. 

Wilbanks, T.J., P. Leiby, R. Perlack, J.T. Ensminger, and S.B. Wright, 2007a: Toward 

an integrated analysis of mitigation and adaptation: some preliminary findings. 

Mitigation and Adaptation Strategies for Global Change, 12(5), 713-725. 

Wilbanks, T.J., P. Romero Lankao, M. Bao, F. Berkhout, S. Cairncross, J.-P. Ceron, M. 

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society. Climate Change 2007: Impacts, Adaptation and Vulnerability. 

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Palutikof, P.J. van der Linden and C.E. Hanson (eds.)]. Cambridge University 

Press, Cambridge, UK, pp. 357-390. 

Young, B., 2002: Thinking clean and green. Georgia Trend, 18, 93-100. 

3-23 
SAP 4.6 Chapter 3: Human Settlements 

3.7 Boxes 

Box 3.1: U.S. Urban Responses to Environmental Change: 

A Historial Perspective 

Over time, American cities have been affected by environmental change. City founders often showed an 

important disregard with respect to siting of settlements, focusing on aspects of location such as 

commercial or recreational opportunities rather than on risks such as flood potential, limited water, food or 

fuel supplies, or the presence of health threats. Oftentimes settlers severely exploited their environments, 

polluting ground water and adjacent water bodies, building in unsafe and fragile locations, changing 

landforms, and filling in wetlands. Construction of the urban built environment involved vast alterations in 

the landscape, as forests and vegetation and wildlife species were eliminated and replaced by highways, 

suburbs, and commercial buildings. The building of wastewater and water supply systems had the effect of 

altering regional hydrology and creating large vulnerabilities. In other cases settlers concluded that the 

weather was changing for the good, that technology would solve problems or that new resources could be 

discovered. 

Technological fixes were pursued to seek ways to modify or control environmental change. Cities exposed 

to flooding built levees and seawalls and channelized rivers. When urbanites depleted and polluted local 

water supplies cities went outside their boundaries to seek new supplies: building reservoirs, aqueducts, and 

creating protected watersheds. When urban consumption exhausted local fuel sources, cities adapted to new 

fuels, embraced new technologies, or searched far beyond city boundaries for new supplies. Many of these 

actions resulted in the extension of the urban ecological footprint, so that urban growth and development 

affected not only the urban site but also increasingly the urban hinterland and beyond. 

There are few examples of environmental disasters or climate change actually resulting in the abandonment 

of an urban site. One case appears to be that of the Hohokam Indians of the Southwest, who built extensive 

irrigation systems, farmed land, and built large and dense settlements over a period of approximately 1,500 

years (Krech, 1999: 45-72). Yet, they abandoned their settlements and disappeared into history. The most 

prominent explanation for their disappearance is an ecological one -- that the Hohokam irrigation systems 

suffered from salinization and water logging, eventually making them unusable. Other factors besides 

ecological ones may have also entered into the demise of their civilization and abandonment of their cities, 

but the ecological explanation appears to have the most supporters. 

 

In the case of America in the 19th and 20th centuries, however, no city has been abandoned because of 

environmental or climatic factors. Galveston, Texas suffered from a catastrophic tidal wave but still exists 

as a human settlement, now protected by an extensive sea wall. Johnstown, Pennsylvania has undergone 

major and destructive flooding since the late 19th century, but continues to survive as a small city. Los 

Angeles and San Francisco are extremely vulnerable to earthquakes, but still continue to increase in 

population. And, in coming years New Orleans almost certainly will experience a hurricane as or more 

severe than Katrina, and yet rebuilding goes on, encouraged by the belief that technology will protect it in 

the future. Whether or not ecological disaster or extreme risk will eventually convince Americans to 

abandon some of their settlements, as the Hohokam did, has yet to be determined (Colten, 2005; Steinberg, 

2006; Vale and Campanella, 2005).

3-24 
SAP 4.6 Chapter 3: Human Settlements 

Box 3.2: Vignettes of Vulnerability - I 

Alaskan Settlements

 No other region in the United States is likely to be as profoundly changed by climate change as 

Alaska, our nation’s part of the polar region of Earth (ACIA, 2004). Because warming is more pronounced 

closer to the poles, and because settlement and economic activities in Alaska have been shaped and often 

constrained by Arctic conditions, in this region warming is especially likely to reshape patterns of human 

settlement. 

 Human settlements in Alaska are already being exposed to impacts from global warming (ACIA, 

2004), and these impacts are expected to increase. Many coastal communities see increasing exposure to 

storms, with significant coastal erosion, and in some cases facilities are being forced either to relocate or to 

face increasing risks and costs. Thawing ground is beginning to destabilize transportation, buildings, and 

other facilities, posing needs for rebuilding, with ongoing warming adding to construction and maintenance 

costs. And indigenous communities are facing major economic and cultural impacts. One recent estimate of 

the value of Alaska’s public infrastructure at risk from climate change set the value at tens of billions of 

today’s dollars by 2080, with the replacement of buildings, bridges, and other structures with long lifetimes 

having the largest public costs (Larsen et al., 2007). 

 Besides impacts on built infrastructures designed for permafrost foundations and effects on 

indigenous societies, many observers expect warming in Alaska to stimulate more active oil and gas 

development (and perhaps other natural resource exploitation), and if thawing of Arctic ice permits the 

opening of a year-round Northwest sea passage it is virtually certain that Alaska’s coast will see a boom in 

settlements and port facilities (ACIA, 2004). 

Coastal Southeast Settlements

 While there is currently no evidence for a long-term increase in North American mainland landfalling hurricanes, concerns remain that certain aspects of hurricanes, such as wind speed and rainfall rates 

may increase (CCSP, 2008). In addition, sea level rise is expected to increase storm surge levels (CCSP, 

2008). Recent hurricanes striking the coast of the U.S. Southeast cannot be attributed clearly to climate 

change, but they suggest a range of possible impacts. As an extreme case, consider the example of 

Hurricane Katrina. In 2005, the city of New Orleans had a population of about half a million, located on the 

delta of the Mississippi River along the U.S. Gulf Coast. Urban development throughout the 20th Century 

has significantly increased land use and settlement in areas vulnerable to flooding, and a number of studies 

had indicated growing vulnerabilities to storms and flooding. In late August 2005, Hurricane Katrina 

moved onto the Louisiana and Mississippi coast with a storm surge, supplemented by waves, reaching up to 

8.5 m above sea level. In New Orleans, the surge reached around 5m, overtopping and breaching sections 

of the city’s 4.5m defenses, flooding 70 to 80 % of New Orleans, with 55 % of the city’s properties 

inundated by more than 1.2 m and maximum flood depths up to 6 m. 1101 people died in Louisiana, nearly 

all related to flooding, concentrated among the poor and elderly. Across the whole region, there were 1.75 

million private insurance claims, costing in excess of $40 billion (Hartwig, 2006), while total economic 

costs are projected to be significantly in excess of $100 billion. Katrina also exhausted the federally backed 

National Flood Insurance Program (Hunter, 2006), which had to borrow $20.8 billion from the Government 

to fund the Katrina residential flood claims. In New Orleans alone, while flooding of residential structures 

caused $8-$10 billion in losses, $3-6 billion was uninsured. 34,000-35,000 of the flooded homes carried no 

flood insurance, including many that were not in a designated flood risk zone (Hartwig, 2006). Six months 

after Katrina, it was estimated that the population of New Orleans was 155,000, with the number projected 

to rise to 272,000 by September 2008 – 56% of its pre-Katrina level (McCarthy et al., 2006).

3-25 
SAP 4.6 Chapter 3: Human Settlements 

Box 3.3: Vignettes of Vulnerability – II 

Arid Western Settlements 

Human settlements in the arid West are affected by climate in a variety of ways, but perhaps most of all by 

water scarcity and risks of fire. Clearly, access to water for urban populations is sensitive to climate, 

although the region has developed a vast system of engineered water storage and transport facilities, 

associated with a very complex set of water rights laws (NACC, 2001). It is very likely that climate change 

will reduce winter snowfall in the West, reducing total runoff – increasing spring runoff while decreasing 

summer water flows. Meanwhile, water demands for urban populations, agriculture, and power supply are 

expected to increase, and conflicts over water rights are likely to increase. If total precipitation decreases or 

becomes more variable, extending the kinds of drought that have affected much of the interior West in 

recent years, water scarcity will be exacerbated, and increased water withdrawals from wells could affect 

aquifer levels and pumping costs. Moreover, drying increases risks of fire, which have threatened urban 

areas in California and other Western areas in recent years. The five-year average of acres burned in the 

West is more than 5 million, and urban expansion is increasing the length of the urban-wild lands interface 

(Morehouse et al., 2006). Drying would lengthen the fire season, and pest outbreaks such as the pine beetle 

could affect the scale of fires. 

Summer 2006 Heat Wave 

In July and August 2006, a severe heat wave spread across the United States, with most parts of the country 

recording temperatures well above the average for that time of the year. For example, temperatures in 

California were extraordinarily high, setting records as high as 130°. As many as 225 deaths were reported 

by press sources, many of them in major cities such as New York and Chicago. Electric power transformers 

failed in several areas, such as St. Louis and Queens, New York, causing interruptions of electric power 

supply, and some cities reported heat-related damages to water lines and roads. In many cities, citizens 

without home air-conditioning sought shelter in public and office buildings, and city/county health 

departments expressed particular concern for the elderly, the young, pregnant women, and individuals in 

poor health. Although this heat wave cannot be attributed directly to climate change, it suggests a number 

of issues for human settlements in the United States as they contemplate a prospect of temperature 

extremes in the future that are higher and/or longer-lasting than historical experience. 

3-26 
SAP 4.6 Chapter 3: Human Settlements 

3-27 

Box 3.4: Climate Change Impacts on The Urban Heat Island Effect (UHI) 

(Lo and Quattrochi, 2003; Brazel and Quattrochi, 2006; Ridd, 2006; Stone, 2006) 

Climate change impacts on the Urban Heat Island (UHI) effect will primarily depend upon the geographic 

location of a specific city, its urban morphology (i.e., landscape and built-up characteristics), and areal 

extent (i.e., overall spatial “footprint”). These factors will mitigate or exacerbate how the UHI phenomenon 

(Figure 3.1) is affected by climate change, but overall, climate change is likely to impact the UHI effect in 

the following ways: 

• Exacerbation of the intensity and areal extent of the UHI as a result of warmer surface and air 

temperatures along with the overall growth of urban areas around the world. Additionally, as urban 

areas grow and expand, there is a propensity for lower albedos which forces a more intense UHI effect. 

(There is also some indication that sustained or prolonged higher nighttime air temperatures over cities 

that may result from warmer global temperatures will have a more significant impact on humans than 

higher daytime temperatures.) 

• As the UHI intensifies and increases, there could be a subsequent impact on deterioration of air quality, 

particularly on ground level ozone caused by higher overall air temperatures and an increased 

background effect produced by the UHI as an additive air temperature factor that helps to elevate 

ground level ozone production. Additionally, particulate matter (PM2.5) could increase due to a number 

of human induced and natural factors (e.g., more energy production to support higher usage of air 

conditioning).

• The UHI has an impact on local meteorological conditions by forcing rainfall production either over, 

or downwind, of cities. As the UHI effect intensifies, there will be a higher probability for urbaninduced rainfall production (dependent upon geographic location) with a subsequent increase in urban 

runoff and flash flooding. 

• Exacerbation and intensification of the UHI would have impacts on human health: 

- increased incidence of heat stress 

- impact on respiratory illnesses such as asthma due to increases in particulate matter 

caused by deterioration in air quality as well as increased pollination production because 

of earlier pollen production from vegetation in response to warmer overall temperatures 

Figure 3.1. Example of urban surface temperatures and albedo for the Atlanta, Georgia Central Business 

District (CBD) area derived from high spatial resolution (10m) aircraft thermal remote sensing data. 

The image on the left illustrates daytime surface heating for urban surfaces across the CBD. White and red 

colors indicate very warm surfaces (~40-50°C). Green relates to surfaces of moderately warm temperatures 

(~25-30°C). Blue indicates cool surfaces (e.g., vegetation, shadows) (~15-20°C). Surface temperatures are 

reflected in the albedo image on the right where warm surfaces are dark (i.e., low reflectivity) and cooler 

surfaces are in red and green (i.e., higher reflectivity). The images exemplify how urban surface 

characteristics influence temperature and albedo as drivers of the urban heat island effect (Quattrochi et al.,

2000). 
SAP 4.6 Chapter 3: Human Settlements 

Box 3.5: Roles of Settlements in Climate Change Mitigation 

 Although U.S. government commitments to climate change mitigation policies at the 

national level have emerged only recently, an increasing number of state and local authorities are 

involved in strategies to mitigate greenhouse gas emissions (Selin and Vandeveer, 2005; Rabe, 

2006; Selin, 2006). U.S. states and cities are joining such initiatives as ICLEI (ICLEI, 2006), the 

U.S. Mayor Climate Protection Agreement, the Climate Change Action Plan, the Regional 

Greenhouse Gas Initiative (RGGI) (Selin, 2006), and the Large Cities Climate Leadership 

Group.1 These initiatives focus on emissions inventories; on such actions aimed at reducing GHG 

emissions as switching to more energy efficient vehicles, using more efficient furnaces and 

conditioning systems, and introducing renewable portfolio standards (RPS). These strategies, 

which mandate an increase in the amount of electricity generated from renewable resources also 

adapt to negative social, economic and environmental impacts; and on actions to promote public 

awareness (see references in footnote 1). 

 Different drivers lie behind these mitigation efforts. Public and private entities have 

begun to “perceive” such possible impacts of climate change as rising sea level, extreme shifts in 

weather, and losses of key resources. They have realized that a reduction of GHG emissions 

opens opportunities for longer economic development (e.g., investment in renewable energy: 

Rabe, 2006). In addition, climate change can become a political priority if it is reframed in terms 

of local issues (i.e., air quality, energy conservation) already on the policy agenda (Betsill, 2001; 

Bulkeley and Betsill, 2003; Romero Lankao, 2007) 

 The promoters of these initiatives face challenges related partly to inertia (e.g., the time it 

takes to replace energy facilities and equipment with a relatively long life of 5 to 50 years: Haites 

et al., 2007). They can also face opposition from organizations who do not favor actions to reduce 

GHG emissions, some of whom are prepared to bring legal challenges against state and local 

initiatives (Rabe, 2006:17). But the number of bottom-up grassroots activities currently under 

way in the United States is considerable, and that number appears to be growing. 

1 ICLEI is the International Council for Local Environmental Initiatives. Local governments participating in 

ICLEI’s Cities for Climate Protection (CCP) Campaign commit to a) conduct an energy- and emissionsinventory and forecast, b) establish an emissions target, c) develop and obtain approval for the Local 

Action Plan, d) Implement policies and measures, and e) monitor and verify results (ICLEI, 2006: April 20 

2006 www.iclei.org). The Large Cities Climate Leadership Group is a group of cities committed to the 

reduction of urban carbon emissions and adapting to climate change. It was founded following the World 

Cities Leadership Climate Change Summit organized by the Mayor of London in October 2005. For more 

information on the US Mayor Climate Protection Agreement see http://www.seattle.gov/mayor/climate/

3-28 
SAP 4.6 Chapter 3: Human Settlements 

3.8 Tables 

Table 3.1. Overview of Integrated Assessments of Climate Impacts and Adaptation in U.S. 

Cities. “x” indicates that the reference addresses a category of interest. 

Bloomfield 

et al., 1999

Kooten 

et al., 2001

Rosenzweig 

et al., 2000

Kirshen 

et al., 2004 

Hoo and 

Sumitani, 2005

Location: Greater Los 

Angeles

New York Metropolitan 

New York 

Metropolitan 

Boston

Metropolitan 

Seattle

Coverage:

Water supply 9 9 9 9

Water Quality 9

Water Demand 9

Sea-level Rise 9 9 9 9

Transportation 9 9

Communication

Energy 9 9

Public Health

Vector-borne Diseases

Food-borne Diseases 9

Temperature-related 

Mortality

9

Temperature-related 

Morbidity

9 9

Air-quality Related 

Mortality

Air-quality Related 

Morbidity

9

Other Health Issues 9 9 9

Ecosystems

Wetlands

Other Ecol.(Wildfires) 9 9

Urban Forests (Trees and 

Vegetation)

9

Air Quality 9 9

Extent of:

Quantitative Analysis Low Medium Medium High Low

Computer-based 

Modeling

None Low Low High None

Scenario Analysis None None Medium High Medium

Explicit Risk Analysis None None None Medium None

Involvement of:

Local Planning Agencies None None High High High

Local Government 

Agencies

None None High High High

Private Industry None None None Low None

Non-profits None None Low High None

Citizens None None None Medium None

Identification of:

Adaptation Options X X X X X

Adaptation Cost X X

Extent of Integration 

Across Systems

None None Low Medium Low

Attention to Differential 

Impacts (e.g., on 

individual types of 

businesses, populations)

None None Low Low Low

3-29 
SAP 4.6 Chapter 3: Human Settlements 

Table 3.2. Regional vulnerabilities of settlements to impacts of climate change in the United 

States

REGIONAL VULNERABILITIES OF SETTLEMENTS TO 

IMPACTS OF CLIMATE CHANGE 

Region Vulnerabilities Major Uncertainties

Metro NE Flooding, infrastructures, health, 

water supply, sea-level rise Storm behavior, precipitation

Larger NE Changes in local landscapes, 

tourism, water, energy needs

Ecosystem impacts

Mid-Atlantic

Multiple stresses; e.g.,

interactions between climate 

change and aging infrastructures

Ecosystem impacts

Coastal SE

More intense storms, 

sea-level rise, flooding, heat 

stress

Storm behavior, 

coastal land use, sea-level rise

Inland SE

Water shortages, 

heat stress, 

UH1, economic impacts

Precipitation change, 

development paths

Upper Midwest Lake and river levels, extreme 

weather events, health

Precipitation change, storm 

behavior

Inner Midwest Extreme weather events, health Storm behavior

Appalachians Ecological change, reduced 

demand for coal

Ecosystem impacts, energy 

policy impacts

Great Plains Water supply, extreme events, 

stresses on communities

Precipitation changes, weather 

extremes

Mountain West Reduced snow, water shortages, 

fire, tourism

Precipitation changes, effects 

on winter snowpack

Arid Southwest Water shortages, fire Development paths, 

precipitation changes

California Water shortages, heat stress; sea 

level rise

Temperature and precipitation 

changes, infrastructure impacts

Northwest Water shortages, ecosystem 

stresses, coastal effects

Precipitation changes, sea-level 

rise

Alaska Effects of warming, vulnerable 

populations

Warming, sea-level rise

Hawaii

Storms and other weather 

extremes, freshwater supplies, 

health, sea-level rise 

Storm behavior, precipitation 

change

3-30 
SAP 4.6 Chapter 3: Human Settlements 

3.9 Figures 

Figure 3.1. Example of urban surface temperatures and albedo for the Atlanta, Georgia Central 

Business District (CBD) area derived from high spatial resolution (10m) aircraft thermal remote 

sensing data. 

(Quattrochi et al., 2000)

3-31 
Synthesis and Assessment Product 4.6 

Chapter 4: Effects of Global Change on Human Welfare 

Lead Author: Frances G. Sussman, Environmental Economics Consulting 

Contributing Authors: Maureen L. Cropper, University of Maryland at College Park; Hector 

Galbraith, Galbraith Environmental Sciences LLC; David Godschalk, University of North Carolina at 

Chapel Hill; John Loomis, Colorado State University; George Luber, Centers for Disease Control and 

Prevention; Michael McGeehin, Centers for Disease Control and Prevention; James E. Neumann, 

Industrial Economics, Incorporated; W. Douglass Shaw, Texas A&M University; Arnold Vedlitz, Texas 

A&M University; Sammy Zahran, Colorado State University 
SAP 4.6 Chapter 4: Human Welfare 

TABLE OF CONTENTS 

4.1 Introduction .............................................................................................................................................3

4.2 Human Welfare, Well-being, and Quality of Life.................................................................................4

4.2.1 Individual Measures of Well-being...................................................................................................5

4.2.2 The Social Indicators Approach .......................................................................................................6

4.2.3 A Closer Look at Communities.......................................................................................................10

4.2.4 Vulnerable Populations, Communities, and Adaptation.................................................................12

4.3 An Economic Approach to Human Welfare .......................................................................................13

4.3.1 Economic Valuation .......................................................................................................................15

4.3.2 Impacts Assessment and Monetary Valuation ................................................................................16

4.3.3 Human Health ................................................................................................................................17

4.3.4 Ecosystems......................................................................................................................................22

4.3.5 Recreational Activities and Opportunities......................................................................................28

4.3.6 Amenity Value of Climate ...............................................................................................................35

4.4 Conclusions ............................................................................................................................................38

4.5 Expanding the Knowledge Base ...........................................................................................................39

4.6 References ..............................................................................................................................................41

4.7 Appendix 1 .............................................................................................................................................57

4.8 Boxes.......................................................................................................................................................64

4.9 Tables......................................................................................................................................................66

4.10 Figures ..................................................................................................................................................72

4 -2
SAP 4.6 Chapter 4: Human Welfare 

4.1 Introduction 

Human welfare is an elusive concept, and there is no single, commonly accepted definition or 

approach to thinking about welfare. Yet there is a shared understanding that human welfare, 

well-being, and quality of life (terms that are often used interchangeably) refer to aspects of 

individual and group life that improve living conditions and reduce chances of injury, stress, and 

loss. The physical environment is one factor, among many, that may improve or reduce human 

well-being. Climate is one aspect of the physical environment, and can affect human well-being 

via economic, physical, psychological, and social pathways that influence individual perceptions 

of quality of life. 

Climate change may result in lifestyle changes and adaptive behavior with both positive and 

negative implications for well-being. For example, warmer temperatures may change the amount 

of time that individuals are comfortable spending outdoors in work, recreation, or other 

activities, and temperature combined with other climatic changes may alter (or induce) changes 

in intra- and inter-country human migration patterns. More generally, studies of climate change 

and the United States identify an assortment of impacts on human health, the productivity of 

human and natural systems, and human settlements. Many of these impacts—ranging from 

changes in livelihoods to changes in water quality and supply—are linked to some aspect of 

human well-being. 

Communities are an integral determinant of human well-being. Climate change that affects 

public goods—such as damaged infrastructure or interruptions in public services—or disrupts the 

production of goods and services, will affect economic performance including overall health, 

poverty, employment, and other measures. These changes may have consequences, such as a lost 

job or a more difficult commute, that affect individual well-being directly. In other cases, 

individual well-being may be indirectly affected due to concern for the well-being of other 

individuals, or for a lack of cohesion within the community. The sustainability or resilience of a 

community (i.e., its ability to cope with climate change and other stressors over the long term) 

may be reduced by climate change weakening the physical and social environment. In the 

extreme, such changes may undermine the individual’s sense of security or faith in government’s 

capacity to accommodate change. 

Completely cataloging the effects of global change on human well-being or welfare would be an 

immense undertaking. Despite its importance, no well-accepted structure for doing so has been 

developed and applied. Moreover, little (if any) research focuses explicitly on the impact of 

global change on human well-being, per se. The chapter seeks to make a review of this topic 

manageable by focusing on several discrete issues: 

 Alternative approaches to defining and studying human well-being 

 Identifying human well-being and quality of life measures and indicators (qualitative and 

quantitative) 

 Describing economic welfare and monetary methods of assigning value to climate 

change’s potential impacts 

 Providing examples of climate change impacts on selected categories of well-being and 

reporting indicators of economic welfare for these categories 

4 -3 
SAP 4.6 Chapter 4: Human Welfare 

Section 4.2, focuses on valuation and non-monetary metrics and draws on the literature to 

provide insights into a possible foundation for future research into the effects of climate change 

on human well-being. This section first discusses the literature defining human well-being. Next, 

it presents an illustrative place-based-indicators approach (the typical approach of planners and 

policy makers to evaluating quality of life in communities, cities, and countries). Approaches of 

this type represent a commonly accepted way of thinking about well-being that is linked to 

objective (and sometimes subjective) measures. While a place-based indicators approach has not 

been applied to climate change, it has the potential to provide a framework for identifying 

categories of human well-being that might be affected by climate change, and for making the 

identification of measures or metrics of well-being a more concrete enterprise in the future. To 

illustrate that potential, the section draws links between community welfare and some of the 

negative impacts of climate change. 

Economics has been at the forefront of efforts to quantify the welfare impacts of climate change. 

Economists employ, however, a very specific definition of well-being—economic welfare—for 

valuing goods and services or, in this case, climate impacts. This approach is commonly used to 

support environmental policy decision making in many areas. Section 4.3 very briefly describes 

the basis of this approach, and the techniques that economists use (focusing on those that have 

been applied to estimate impacts of climate change). This section next summarizes the existing 

economic estimates of the non-market impacts of climate change.1

 An accompanying appendix 

provides more information on the economic approach to valuing changes in welfare, and 

highlights some of the challenges in applying valuation techniques to climate impacts. 

The fourth section of the chapter summarizes some of the key points of the chapter and the 

chapter concludes with a brief discussion of research gaps. 

4.2 Human Welfare, Well-being, and Quality of Life 

No single, widely accepted definition exists for the term human welfare, or for related terms such 

as well-being and quality of life, and they are all often used interchangeably (Veenhoven, 1988, 

1996, 2000; Ng, 2003; Rahman, 2007). Academic economists, epidemiologists, health scientists, 

psychologists, sociologists, geographers, political scientists, and urban planners have all rendered 

their own definitions and statistical indicators of life quality at both individual and community 

levels.2

 For purposes of clarity in this chapter, from this point forward we adopt the convention 

of the Millenium Assessment (MA, 2005) and the Intergovernmental Panel on Climate Change 

(IPCC, 2007b), which use “well-being” as an umbrella term—referring broadly to the extent to 

which human conditions satisfy the range of constituents of well-being, including health, social 

relations, material needs, security, and freedom of choice. “Quality of life” is here used 

 

1

 Because more concrete aspects of welfare, such as impacts on prices or income, may be covered by other synthesis 

and assessment products (see, for example, discussions of dollar values in SAP 4.3, The Effects of Climate Change 

on Agriculture, Land Resources, Water Resources, and Biodiversity, which is in draft form at the time this is being 

written), this report focuses exclusively on the types of intangible amenities that directly impact quality of life, but 

are not traded in markets, including health, recreation, ecosystems, and climate amenities. 

2

 For example, In sociological literature, the terms well-being and welfare are used interchangeably to refer to 

objectively measurable life chances and experiences, and the term quality of life is used to describe subjective 

assessments and experiences of individuals. 

4 -4 
SAP 4.6 Chapter 4: Human Welfare 

synonymously with well-being, to reflect usage in a wide range of disciplines, including medical, 

sociological, psychological, and urban planning literatures. The term “welfare” is generally used 

herein to refer narrowly to economic measures of individual well-being, although it is also used 

in the context of communities in a broader sense. 

Despite differences in definitions, human well-being—in its broadest sense—is typically a multidimensional concept, addressing the availability, distribution, and possession of economic assets, 

and non-economic goods such as life expectancy, morbidity and mortality, literacy and 

educational attainment, natural resources and ecosystem services, and participatory democracy. 

These conceptualizations often also include social and community resources (sometimes referred 

to as social capital in social scientific literature), such as the presence of voluntary associations, 

arts, entertainment, and shared recreational amenities (see Putnam, 1993, 2000). The quantity of 

community resources shared by a population is often called social capital.3 These components of 

life quality are interrelated and correlate with subjective valuations of life satisfaction, happiness, 

pleasure, and the operation of successful democratic political systems (Putnam, 2000). 

The concepts of well-being, economic welfare, and quality of life play important roles not only 

in academic research, but also in practical analysis and policy making. Quality of life measures 

may be used, for example, to gauge progress in meeting policy or normative goals in particular 

cities by planners; municipalities in New Zealand, England, Canada, and United States have 

constructed their own metrics of quality of life to estimate the overall well-being and life chances 

available to citizens. Similarly, health-related quality of life measures can indicate progress in 

meeting goals. For example, the U.S. Medicare program uses metrics to track quality of life for 

beneficiaries and to monitor and improve health care quality (HCFR, 2004). Moreover, 

international agencies from the United Nations Human Development Programme (UNDP) to the 

Milllenium Ecosystem Assessment on Ecosystems and Human Well-Being and highly regarded 

periodicals like The Economist, have built composite measures of human and societal well-being 

to compare and rank nations of the world.4

 

Life quality and human well-being are increasingly important objects of theoretical and empirical 

research in diverse disciplines. Two analytic approaches characterize the research literature: 

(1) studies that emphasize well-being as an individual attribute or possession; and (2) studies that 

treat well-being as a social or economic phenomenon associated with a geographic place. 

4.2.1 Individual Measures of Well-being 

Approaches focusing on individuals are generally found in medical, health, cognitive, and 

economic sciences, and it is to these we turn first, and then next to place-focused indicators. 

 

3

 The concept of social capital has been defined, in different ways, by Putnam (1993, 1995, 2000) and by Coleman 

(1988, 1990, 1993). For Coleman, social capital is a store of community value that is embodied in social structures 

and the relations between social actors, from which individuals can draw in the pursuit of private interest. Putnam’s 

definition is similar, but places a stronger emphasis on altruism and community resources. 

4

 See, for example, the discussion of the sources of Table 1 subsequently in this chapter, which include a number of 

country-level quality of life assessments. The UNDP Human Development Index, a country by country ranking of 

quality of life indicators, can be accessed at http://hdr.undp.org/en/statistics/. 

4 -5 
SAP 4.6 Chapter 4: Human Welfare 

4.2.1.1 Health Focused Approaches 

In medical science, quality of life is used as an outcome variable to evaluate the effectiveness of 

medical, therapeutic, and/or policy interventions to promote population health. Quality of life is 

an individual’s physiological state constituted by body structure, function, and capability that 

enable pursuit of stated and revealed preferences. In medical science, the concept of life quality 

is synonymous with good health – a life free of disease, illness, physical, and/or cognitive 

impairment (Raphael et al., 1996, 1999, 2001). 

In addition to objective measures of physical and occupational function, disease absence, or 

somatic sensation, life quality scientists measure an individual’s perception of life satisfaction. 

The scientific basis of such research is that pain and/or discomfort associated with a 

physiological impairment are registered and experienced variably. Based on patient reports or 

subjective valuations, psychologists and occupational therapists have developed valid and 

reliable instruments to assess how mental, developmental, and physical disabilities interfere with 

the performance and enjoyment of life activities (Bowling, 1997; Guyatt et al., 1993). 

4.2.1.2 Economic and Psychological Approaches 

Individual valuations of life quality also anchor economic and psychological investigations of 

happiness and utility. In the new science of happiness, scholars use the tools of neuroscience, 

experimental research, and modern statistics to discover and quantify the underlying 

psychological and physiological sources of happiness (for reviews see Kahneman et al., 1999; 

Frey and Stutzer, 2002; Kahneman and Krueger, 2006). Empirical studies show, for example, 

that life satisfaction and happiness correlate predictably with marital status (married persons are 

generally happier than single people), religiosity (persons that practice religion report lower 

levels of stress and higher levels of life satisfaction), and individual willingness to donate time, 

money and effort to charitable causes. Similarly, the scholarly literature notes interesting 

statistical associations between features of climate (such as variations in sunlight, temperature, 

and extreme weather events) and self-reported levels of happiness, utility, or life satisfaction. 

Individual valuations of health, psychological, and emotional well-being are sometimes summed 

across representative samples of a population or country to estimate correspondences between 

life satisfaction and “hard” indicators of living standards such as income, life expectancy, 

educational attainment, and environmental quality. Cross-national analyses generally find that 

population happiness or life satisfaction increases with income levels and material standards of 

living (Ng, 2003) and greater personal autonomy (Diener et al., 1995; Diener and Diener, 

1995).5

 In such studies, subjective valuations of life satisfaction are embedded in broader 

conceptions of quality of life associated with the conditions of a geographic place, community, 

region or country—the social indicators approach. 

4.2.2 The Social Indicators Approach 

In this second strand of research, what some refer to as the social indicators approach, scholars 

assemble location-specific measures of social, economic, and environmental conditions, such as 

 

5

Some studies suggest that individual utility or happiness is not positively determined by some absolute quantity of 

income, wealth, or items consumed, but rather how an individual perceives his or her lot in relation to others or to 

conditions in their past. See, for example, Frank 1985. 

4 -6 
SAP 4.6 Chapter 4: Human Welfare 

employment rates, consumption flows, the availability of affordable housing, rates of crime 

victimization and public safety, public monies invested in education and transportation 

infrastructure, and local access to environmental, cultural, and recreational amenities. These 

place-specific variables are seen as exogenous sources of individual life quality. Scholars reason 

that life quality is a bundle of conditions, amenities, and lifestyle options that shape stated and 

revealed preferences. In technical terms, the social indicators approach treats quality of life as a 

latent variable, jointly determined by several causal variables that can be measured with 

reasonable accuracy. 

The indicators approach has several advantages in the context of understanding the impacts of 

climate change on human well-being. First, social indicators have considerable intuitive appeal, 

and their widespread use has not only made it familiar to both researchers and the general public, 

but has subjected them to considerable debate and discussion. Second, they offer considerable 

breadth and flexibility in terms of categories of human well-being that can be included. Third, 

for many of the indicators or dimensions of well-being, objective metrics exist for measurement. 

In addition, while its strength is in providing indicators of progress on individual dimensions of 

quality of life, the indicators approach has also been used to support aggregate or composite 

measures, at least for purposes of ranking or measuring progress. Various techniques are also 

available, or being developed, that aggregate or combine measures of well-being. These range 

from pure data reduction procedures to stakeholder input models where variables are evaluated 

on their level of social and economic importance. For example, Richard Florida (2002a) has 

constructed a statistical index of technology, talent, and social tolerance variables to estimate the 

human capital of cities in the United States. Given the analytical strengths of the social indicators 

approach, it may be a good starting point for understanding the relationships between human 

well-being and climate change. 

4.2.2.1 A Taxonomy of Categories of Wellbeing 

Taxonomies of place-specific well-being or quality of life typically converge on six categories or

dimensions: (1) economic conditions; (2) natural resources, environment, and amenities; (3) 

human health; (4) public and private infrastructure; (5) government and public safety; and (6) 

social and cultural resources. These categories represent broad aspects of personal and family 

circumstances, social structures, government, environment, and the economy that influence wellbeing. Table 4.1 illustrates these categories, which are listed in Column 1. The third column, 

“components/indicators of welfare” provides examples of the way in which these categories are 

often interpreted. These components represent what, in an ideal world, researchers would wish to 

measure in order to determine how a specific society fares from the perspective of well-being. 

The fourth column provides illustrative metrics, i.e., objective or quantifiable measures that are 

often used by researchers as indicators of well-being for each category.6 Finally, the last column 

provides some examples of climate impacts that may be linked to that category. This column 

should not be viewed as an attempt to create a comprehensive list of impacts, or even to list 

 

6

 Sources that contributed to the development of Table 1 include: MA (2005); Sufian, 1993; Rahman, 2007, and

Lambiri, et al., 2007. Insights were also derived from quality of life studies of individual cities and countries, 

including: http://www.bigcities.govt.nz/indicators.htm Quality of Life in New Zealand’s Large Urban Areas; 

http://www.asu.edu/copp/morrison/public/qofl99.htm What Matters in Greater Phoenix 1999 Edition: Indicators of 

Our Quality of Life; and http://www.jcci.org/statistics/qualityoflife.aspx Tracking the Quality of Life in 

Jacksonville. 

4 -7 
SAP 4.6 Chapter 4: Human Welfare 

impacts with equal weights, in terms of importance or likelihood of occurrence. Further, while 

Table 4.1 focuses on negative impacts (as potentially more troubling for quality of life), there are 

also opportunities or potential positive impacts that will result in some categories. 

These categories of well-being or life quality are interrelated. For example, as economic or social 

conditions in a society improve (e.g., as measured by GDP per capita and rates of adult literacy), 

improvements occur in human health outcomes such as infant mortality, rates of morbidity, and 

female life expectancy at birth. Thus, while the categories and corresponding metrics of wellbeing presented in Table 4.1 are analytically separable, in reality they are highly interconnected.7

 

Economics as a source of quality of life refers to a mix of production, consumption, and 

exchange activities that constitute the material well-being of a geographic place, community, 

region or country. Standard components of economic well-being include income, wealth, 

poverty, employment opportunities, and costs of living. Localities characterized by efficient and 

equitable allocation of economic rewards and opportunities enable material security and 

subjective happiness of residents (Florida, 2002a). 

Natural resources, environment, and amenities as a source of well-being refers to natural 

features, such as ecosystem services, species diversity, air and water quality, natural hazards and 

risks, parks and recreational amenities, and resource supplies and reserves. Natural resources and 

amenities directly and indirectly affect economic productivity, aesthetic and spiritual values, and 

human health (Blomquist et al., 1988; Glaeser et al., 2001; Cheshire and Magrini, 2006). 

Human health as a source of well-being includes features of a community, locality, region or 

country that influence risks of mortality, morbidity, and the availability of health care services. 

Good health is desirable in itself as a driver of life expectancy (and the quality of life during 

those years), and is also critical to economic well-being by enabling labor force participation 

(Raphael et al., 1996, 1999, 2001). 

Public and private infrastructure sources of well-being include transportation, energy and 

communication technologies that enable commerce, mobility, and social connectivity. These 

technologies provide basic conditions for individual pursuits of well-being (Lambiri et al., 2007). 

Government and public safety as a source of well-being are activities by elected representatives 

and bureaucratic officials that secure and maximize the public services, rights, liberties, and 

safety of citizens. Individuals derive happiness and utility from the employment, educational, 

civil rights, public service, and security efforts of their governments (Suffian, 1993). 

Finally, social and cultural resources as a source of well-being are conditions of life that 

promote social harmony, family and friendship, and the availability of arts, entertainment, and 

leisure activities that facilitate human happiness. The terms social and creative capital have 

 

7

 More recently, scholars (Costanza et al. 2007) and government agencies (like NOAA’s Coastal Service Center) 

have moved toward the global concept of capital to integrate indicators and assess community quality of life. The 

term capital is divided into four types: economic; physical; ecological or natural; and socio-cultural. Various metrics 

constitute these types of capital, and are understood to foster community resilience and human needs of subsistence, 

reproduction, security, affection, understanding, participation, leisure, spirituality, creativity, identity, and freedom. 

See also Rothman, Amelung, and Poleme (2003). 

4 -8 
SAP 4.6 Chapter 4: Human Welfare 

become associated with these factors. Communities with greater levels of social and creative 

capital are expected to have greater individual and community quality of life (Putnam, 2000; 

Florida, 2002b). 

In thinking about these indicators, it is important to keep two important contextual realities about 

climate change and well-being at the forefront. First, while discussions of climate change usually 

have a global resonance to them, the fact is that the effects of any specific changes in 

temperature, rainfall, storm frequency/intensity and sea level rise will be felt at the local and 

regional level by citizens and communities living and working in those vulnerable areas. 

Therefore, not all populations will be placed under equal amounts of climate change-generated 

stress. Some will experience greater impacts, will suffer greater damage, and will need more 

remediation and better plans and resource allocations for adaptation and recovery efforts to 

protect and restore quality of life (see, for example, Zahran et al., 2008; Liu, Vedlitz and Alston, 

2008; Vedlitz et al., 2007). 

Second, not all citizens in areas more vulnerable to climate change effects are equally at risk. 

Some population groupings, within the same community, will be more vulnerable and at risk 

than others. Those who are poorer, minorities, aged or infirmed, and children are at greater risk 

than others to the stresses of climate change events (Lindell and Perry, 2004; Peacock, 2003). 

Recognizing that not all citizens of a particular vulnerable area share the same level of risk is 

something that planners and decision makers must take into account in projecting the likely 

impacts of climate change events on their populations, and in dealing with recovery of those 

populations (Murphy and Gardoni, 2008). 

Finally, the situation is further complicated as climate stressors negatively affect disease 

conditions in other nations with particularly vulnerable and mobile populations. Increased 

communicable disease incidence in developing nations have the potential, through legal and 

illegal tourism and immigration, to affect community welfare and individual well-being in the 

United States.

4.2.2.2 Climate Change and Quality of Life Indicators 

Social indicators are generally used to evaluate progress towards a goal: How is society doing? 

Who is being affected? Tracking performance for these indicators——using the types of metrics 

or measures indicated in Table 4.1—could provide information to the public on how 

communities and other entities are reacting to, and successfully adapting to (or failing to adapt 

to), climate change. The indicators and metrics included in Table 4.1 are intended to be 

illustrative of the types of indicators that might be used, rather than a comprehensive or 

recommended set. In any category, multiple indicators could be used; and any one of the 

indicators could have several measures. For example, exposure to natural hazards and risks could 

be measured by the percentage of a locality’s tax base located in a high hazard zone, the number 

of people exposed to a natural hazard, the funding devoted to hazard mitigation, or the costs of 

hazard insurance, among others. Similarly, some indicators are more amenable to objective 

measurement; others are more difficult to measure, such as measures of social cohesion. The 

point to be taken from Table 4.1 is that social indicators provide a diverse and potentially rich 

perspective on human well-being. 

4 -9 
SAP 4.6 Chapter 4: Human Welfare 

The taxonomy presented in Table 4.1—or a similar taxonomy—might also provide a basis for 

analyses of the impacts of climate change on human well-being, providing a list of important 

categories for research (the components or indicators of life quality), as well as appropriate 

metrics (e.g., employment, mortality or morbidity, etc.). The social indicators approach, and the 

specific taxonomy presented here, are only one of many that could be developed.8 At the least, 

different conditions and stakeholder mixes may demand different emphases. All taxonomies, 

however, face a common problem: how to interpret and use the diverse indicators, in order to 

compare and contrast alternative adaptive or mitigating responses to climate change. For some 

purposes, metrics have been developed that that aggregate across individuals or individual 

categories of well-being and present a composite measure of well-being; or otherwise 

operationalize related concepts, such as vulnerability (see, for example the discussion of Figure 

4.1). 

Figure 4.1 Geography of Climate Change Vulnerability at the County Scale

4.2.3 A Closer Look at Communities 

Looking beyond well-being of individuals to the welfare (broadly speaking) of communities—

networks of households, businesses, physical structures, and institutions—provides a broader 

perspective on the impacts of climate change. The categories and metrics in Table 4.1 are 

appealing from an analytical perspective in part because they represent dimensions of well-being 

that are clearly important to individuals, but that also have counterparts and can generally be 

measured objectively at the community level. Thus, for example, the counterparts of individual 

income or health status are, at the social level, per capita income or mortality/illness rates. The 

concept of community welfare is linked to human communities, but is not confined to 

communities in urban areas, or even in industrialized cultures. Human communities in remote 

areas, or subsistence economies, face the same range of quality of life issues—from health to 

spiritual values—although they may place different weights on different values; thus, the weights 

placed on different components of welfare are not determined a priori, but depend on 

community values and decision making. 

Viewing social indicators and metrics through the lens of the community can be instructive in 

several ways. First, communities are dynamic entities, with multiple pathways of interactions 

among people, places, institutions, policies, structures, and enterprises. Thus, while the social 

indicators described in Table 4.1 have metrics that can be measured independently of each other, 

they are not determined independently within the complex reality of interdependent human 

systems. Second, in part because of this interdependence, the aggregate welfare of a community 

is more than a composite of its quality of life metrics; sustainability provides one means of 

approaching a concept of aggregate welfare. Third, vulnerability and adaptation are typically 

analyzed at the sectoral level: “what should agriculture, or the public health system, do to plan 

for or adapt to climate change.” The issue can also, however, be addressed at the level of the 

community. Each of these issues is touched on below. 

 

8

 In addition to variants on the social indicators approach, other types of taxonomies are possible—for example a 

taxonomy based on broad systems (atmospheric, aquatic, geologic, biological, and built environment), or on forms 

of capital that make up the productive base of society (natural, manufactured, human, and social). Well-being can 

also be viewed in terms of its endpoints: necessary material for a good life, health and bodily well-being, good social 

relations, security, freedom and choice, and peace of mind and spiritual existence (Rothman, Amelung, and Poleme., 

2003). 

4 -10 
SAP 4.6 Chapter 4: Human Welfare 

4.2.3.1 Community Welfare and Individual Well-being 

Rapid onset extreme weather events, such as hurricanes or tornadoes, can do serious damage to 

community infrastructure, public facilities and services, tax base, and overall community 

reputation and quality of life, from which recovery may take years and never be complete (see 

additional discussion in Chapter 3). More gradual changes in temperature and precipitation will 

have both negative and positive effects. For example, as discussed elsewhere in this chapter, 

warmer average temperatures increase risks from heat-related mortality in the summer, but 

decrease risks from cold-related mortality in the winter, for susceptible populations. Effects such 

as these will not, however, be confined to a few individual sectors, nor are the effects across all 

sectors independent. 

To illustrate the interdependence of impacts and, by extension, the analogous social indicators 

and metrics, consider a natural resource that faces additional stresses from climate change: fish 

populations in estuaries, such as the Chesapeake Bay, that are already stressed by air and water 

pollution from industry, agriculture, and cities. In this case, while the direct effects of climate 

will occur to the resource itself, indirect effects can alter welfare as measured by economic, 

social, and human health indicators. Table 4.2 presents some of the possible pathways by which 

resource changes could affect diverse categories of quality of life; the purpose of Table 4.2 is not 

to assert that all these effects will occur or that they will be significant if they do occur as a result 

of climate change, but rather to illustrate the linkages. These linkages underscore the importance 

of understanding interdependencies within the community or, from another perspective, across 

welfare indicators. Table 4.2 illustrates the general principle of complex linkages in which a 

general equilibrium approach can be used to model climate change impacts. 

4.2.3.2 Sustainability of Communities 

Understanding how climate change and extreme events affect community welfare requires a 

different conceptual framework than that for understanding individual level impacts, such as 

quality of life.9 Communities are more than the sum of their parts; they have unique aggregate 

identities shaped by dynamic social, economic, and environmental components. They also have 

life cycles, waxing and waning in response to societal and environmental changes (Diamond, 

2005; Fagan, 2001; Ponting, 1991; Tainter, 1988). Sustainability is a paramount community 

goal, typically expressed in terms of sustainable development in order to express the ongoing 

process of adaptation into the long-term future. “Climate change involves complex interactions 

between climatic, environment, economic, political, institutional, social, and technological 

processes. It cannot be addressed or comprehended in isolation from broader societal goals (such 

as sustainable development)...” (Banuri and Weyant, 2001). Even for a country as developed as 

the US, continuing growth and development creates both pressures on the natural and built 

environments and opportunities for moving in sustainable directions. 

While the term sustainability does not have a single, widely-accepted definition, a central 

guideline is to balance economic, environmental, and social needs and values (Campbell, 1996; 

 

9

 Measures of quality of life provide a database of relevant individual characteristics at various points in time, 

including economic conditions, natural resources and amenities, human health, public and private infrastructure, 

government and public safety, and social and cultural resources. Sustainable development measures are similar, but 

reflect more emphasis on long-term and reciprocal effects, as well as a concern for community-wide and equitable 

outcomes. 

4 -11 
SAP 4.6 Chapter 4: Human Welfare 

Berke et al., 2006), sometimes portrayed as a three-legged stool. It is distinguished from quality 

of life by its dynamic linking of economic, environmental, and social components, and by its 

future orientation (Campbell, 1996; Porter, 2000). Sustainability is seen as living on nature’s 

“interest,” while protecting natural capital. Sustainability is a comprehensive social goal that 

transcends individual sector or impact measurements, although it can include narrower 

community welfare concepts such as the healthy city. Thinking about the impacts of climate 

change on communities through the lens of sustainable development allows us to envision crosssector economic, environmental, and social dynamics. 

4.2.4 Vulnerable Populations, Communities, and Adaptation 

Responding to climate change at the community level requires understanding both vulnerability 

and adaptive responses that the community can take. Vulnerability of a community depends on

its exposure to climate risk, how sensitive systems within that community are to climate 

variability and change, and the adaptive capacity of the community (i.e., how it is able to respond 

and protect its citizens from climate change). Different groups within the community will be 

differentially vulnerable to climate changes, such as extreme events, and infrastructure and 

community coping capacity will be more or less effective in invoking a resilient response to 

climate change.

4.2.4.1 Vulnerable Populations 

Categories of persons susceptible to environmental risks and hazards include racial and ethnic 

groups (Bolin, 1986; Fothergill et al., 1999; Lindell and Perry, 2004; Cutter, 2006), and groups 

defined by economic variables of wealth, income, and poverty (Peacock, 2003; Dash et al., 1997; 

Fothergill and Peek, 2004). Overall, research indicates that minorities and the poor are 

differentially harmed by disaster events. Economic disadvantage, lower human capital, limited 

access to social and political resources, and residential choices are social and economic reasons 

that contribute to observed differences in disaster vulnerability by race/ethnicity and economic 

status. While the literature on climate change and vulnerable populations is relatively 

underdeveloped, Chapter 2 on Human Health and Chapter 3 on Human Settlements each address 

population vulnerabilities. 

Economic, social and health effects are not neatly bounded by geographic or political regions, 

and so the damage and stresses that occur in a specific locality are not limited in their effects to 

only that community. As Hurricane Katrina made clear, impacts felt in one community ripple 

throughout the region and nation. Persons made homeless in New Orleans resettled in Baton 

Rouge, Lafayette and Houston, creating stresses on those communities. Vulnerable groups 

migrate from stricken areas to more hospitable ones, taking their health, economic and 

educational needs and problems with them across both national and state lines

4.2.4.2 Vulnerable Communities 

While most analyses of vulnerability tend to be conducted at the regional scale, Zahran et al.

(2008) have brought the analysis closer to the community level by mapping the geography of 

climate change vulnerability at the county scale. The study uses measures of both physical 

vulnerability (expected temperature change, extreme weather events, and coastal proximity) and 

adaptive capacity (as represented by economic, demographic, and civic participation variables 

that constitute a locality’s socioeconomic capacity to commit to costly climate change policy 

4 -12 
SAP 4.6 Chapter 4: Human Welfare 

initiatives). Their map identifies the concentrations of highly vulnerable counties as lying along 

the east and west coasts and Great Lakes, with medium vulnerability counties mostly inland in 

the southeast, southwest, and northeast. (See Figure 4.1, in which darker areas represent higher 

vulnerability). 

Many possible dimensions can be used to identify and measure vulnerabilities to climate change 

impacts and stressors. The one presented in Figure 4.1 illustrates that the concept of vulnerability 

is a viable one and can be measured and applied to communities in a GIS context. It is not the 

purpose of this chapter to focus in great detail on vulnerability measurement issues (for those 

interested in other formulations of the vulnerability concept, see Dietz et al., In Press). 

4.2.4.3 Adaptation

From the perspective of the community, the goal of successful adaptation to climate impacts—

particularly potentially adverse impacts—is to maintain the long-term sustainability and survival 

of the community. Thus, a resilient community is capable of absorbing climate changes and the 

shocks of extreme events without breakdowns in its economy, natural resource base, or social 

systems (Godschalk, 2003). Given their control over shared resources, communities have the 

capacity to adapt to climate change in larger and more coordinated ways than individuals, by 

creating plans and strategies to increase resilience in the face of future shocks, while at the same 

time ensuring that the negative impacts of climate change do not fall disproportionately on their 

most vulnerable populations and demographic groups (Smit and Pilifosova, 2001). 

Public policies and programs are in place in the United States to enhance the capacity of 

communities to mitigate10 damage and loss from natural hazards and extreme events (Burby, 

1998; Mileti, 1999; Godschalk, 2007). A considerable body of research looks at responses to 

natural hazards, and recent research has shown that the benefits of natural hazard mitigation at 

the national level outweigh its costs by a factor of four to one on average (Multihazard 

Mitigation Council, 2005; Rose et al., 2007). Research also has been done on the social 

vulnerability of communities to natural hazards (Cutter et al., 2003) and the economic resilience 

of businesses to natural hazards (Tierney, 1997; Rose, 2004). However, there is scant research on 

U.S. policies dealing with community adaptation to the broader impacts of climate change. 

4.3 An Economic Approach to Human Welfare 

Welfare, well-being, and quality of life are often viewed as multi-faceted concepts. In subjective 

assessments of happiness or quality of life (see the discussion in Section 4.2), the individual 

makes a net evaluation of his or her current state, taking into account (at least implicitly) and 

balancing all the relevant facets or dimensions of that state of being. Constructing an overall 

statement regarding welfare from a set of objective measures, however, requires a means of 

weighting or ranking, or otherwise aggregating, these measures. The economic approach supplies 

one—although not the only possible—approach to aggregation.11

 

10 In the natural hazards and disasters field, a single term—mitigation—refers both to adaptation to hazards and 

mitigation of their stresses. (See the Disaster Mitigation Act of 2000, Public Law 106-390.) 

11 In part because of the difficulty in compiling the information needed for aggregation of economic measures, 

Jacoby (2004) proposes a portfolio approach to benefits estimation, focusing on a limited set of indicators of global 

climate change, of regional impact, and one global monetary measure. The set of measures would not be the only 

4 -13 
SAP 4.6 Chapter 4: Human Welfare 

Quantitative measures of welfare that use a common metric have two potential advantages. First, 

the ability to compare welfare impacts across different welfare categories makes it possible to 

identify and rank categories with regard to the magnitude or importance of effects. Welfare 

impacts can then provide a signal about the relative importance of different impacts, and so help 

to set priorities with regard to adaptation or research. Second, if the concept of welfare is 

(ideally) a net measure, then it should be possible to aggregate the effects of climate across 

disparate indicators. Quantitative measures that use the same metric can, potentially, be summed 

to generate net measures of welfare, and gauge progress over time, or under different policy or 

adaptation scenarios. 

Given the value of welfare both as a multi-dimensional concept, and as one that facilitates 

comparisons, the economic approach to welfare analysis—which monetizes or puts dollar values 

on impacts—is one means of comparing disparate impacts. Further—and this is the second 

advantage of the economic approach—dollar values of impacts can be aggregated, and so 

provide net measures of changes in impacts that can be useful to policy makers. This section of 

the chapter discusses the foundation of economic valuation, the distinction between market and 

non-market effects (only the latter are covered in this paper), and describes some of the valuation 

tools that economists use for non-market effects. An appendix covers these issues in additional 

detail, and also describes the challenges that economic valuation faces when used as a tool for 

policy analysis in the long term context of climate change. 

Fundamental to the economic approach is a notion that a key element of support for decisionmaking is an understanding of the magnitude of costs and benefits, so that the tradeoffs implicit 

in any decision can be balanced and compared. However, the economic approach, when 

interpreted as requiring a strict cost-benefit test, is not appropriate in all circumstances, and is 

viewed by some as controversial in the context of climate change.12 Benefit cost analysis is one 

tool available to decision makers; in the context of climate change; other decision rules and tools, 

or other definitions of welfare, may be equally, or more relevant. For example, the recent 

Synthesis Report of the IPCC Fourth Assessment (IPCC, 2007a) presents an average social cost 

(i.e., damages) of carbon in 2005 of $12 per ton of CO2, but also notes that the range of the 

roughly 100 peer-reviewed estimates of this value is -$3 to $95/tCO2.

13 IPCC attributes this very 

broad range to differences in assumptions on climate sensitivity, response lags, the treatment of 

risk and equity, economic and non-economic impacts, the inclusion of potentially catastrophic 

losses, and discount rates. IPCC therefore suggests consideration of an "iterative risk 

management process" to support decision-making.14 Estimated benefits and costs therefore can 

provide information relevant to decision makers, but some of the methodologies and data 

 

information generated and made available, but it would represent a set of variables continuously maintained and 

used to describe policy choices. 

12 See Arrow et al., 1996 - at page 7, "There may be factors other than economic benefits and costs that agencies will 

want to weigh in decisions, such as equity within and across generations. In addition, a decision maker may want to 

place greater weight on particular characteristics of a decision, such as potential irreversible consequences." 13 See IPCC 2007a, page 23. 

14 IPCC further notes that existing analyses suggest costs and benefits of mitigation are roughly comparable in 

magnitude, "but do not as yet permit an unambiguous determination of an emissions pathway or stabilization level 

where benefits exceed costs." (IPCC 2007a page 23). 

4 -14 
SAP 4.6 Chapter 4: Human Welfare 

necessary to provide a relatively complete assessment may be unavailable, as discussed 

subsequently in this section.15

4.3.1 Economic Valuation 

The framework that economists employ reflects a specific view of human welfare and how to 

measure it. Economists define the value of something—be it a good, service, or state of the 

world—by focusing on the well-being, utility, or level of satisfaction that the individual derives. 

The basic economic paradigm assumes that individuals allocate their available income and time 

to achieve the greatest level of satisfaction. The value of a good—in terms of the utility or 

satisfaction it provides—is revealed by the tradeoffs that individuals make between that good 

and other goods, or between that good and income.16 The term “willingness to pay” (WTP) is 

used by economists to represent the value of something, i.e., the individual’s willingness to trade 

money for that particular good, service, or state of the world. 

Economists distinguish between market and non-market goods. Market goods are those that can 

be bought and sold in the market, and for which a price generally exists. Market behavior and, in 

particular, the prices that are paid for these goods, is a source of information on the economic 

value or benefit of these goods. The economic benefit—the amount that members of society 

would in aggregate be willing to pay for these goods—is related to, but frequently greater than, 

market prices. 

Non-market goods are those that are not bought and sold in markets. Consequently, climate 

change impacts that involve non-market effects—such as health effects, loss of endangered 

species, and other effects—are difficult to value in monetary terms. Economists have developed 

techniques for measuring non-market values, by inferring economic value from behavior 

(including other market behavior), or by asking individuals directly. 

A number of studies have attempted to value the range of effects of climate change. For the US, 

some of the most comprehensive studies are the Report to Congress completed by U.S. EPA in 

1989 (U.S. EPA, 1989), Cline (1992), Nordhaus (1994), Fankhauser (1995), Mendelsohn and 

Neumann (1999), Nordhaus and Boyer (2000), and a body of work by Richard Tol (e.g., Tol, 

2002 and Tol, 2005). In all of these studies, the focus is largely on market impacts, particularly 

the effects of climate change on agriculture, forestry, water resource availability, energy demand 

(mostly for air conditioning), coastal property, and in some cases, health. 

Non-market effects, however, are less well characterized in these studies (Smith et al., 2003); 

where comprehensive attempts are made, they usually involve either expert judgment or very 

rudimentary calculations, such as multiplying the numbers of coastal wetland acres at risk of 

inundation from sea-level rise by an estimate of the average non-market value of a wetland. One 

such comprehensive attempt generated a value for 17 ecosystem services from 16 ecosystem 

types (Costanza et al., 1997), but also generated controversy and criticism from many 

 

15 Other factors that might be considered, in addition to economic estimates, include emotions, perceptions, cultural 

values, and other subjective factors, all of which can play a role in creating preferences and reaching decisions. 

Those factors are beyond what we can evaluate in this chapter. 16 Although economists are careful to distinguish between the metrics of utility and money as distinct, valuation 

metric in dollar units (rather than units of utility) may be generally viewed as the outcomes of individual preference 

expressions among goods, income, and time. 

4 -15 
SAP 4.6 Chapter 4: Human Welfare 

economists (Bockstael et al., 2000; Toman, 1998; see National Research Council 2004 for a 

summary). Other analysts have attempted to define measures to reflect non-market ecosystem 

services in terms similar to those used for Gross Domestic Product (Boyd, 2006), or indicators of 

ecosystem health that reflect ecological contributions to human welfare (Boyd and Banzhaf, 

2006).17 While there are several well-done valuation analyses for non-market effects of climate 

change (as described later in this chapter), it is fair to characterize this literature as opportunistic 

in its focus; where data and methods exist, there are high quality studies, but the overall coverage 

of non-market effects remains inadequate. 

4.3.2 Impacts Assessment and Monetary Valuation 

The process of estimating the welfare effects of climate change involves four steps: (1) estimate 

climate changes; (2) estimate physical effects of climate change, (3) estimate the impacts on 

human and natural systems that are amenable to valuation and (4) value or monetize effects. The 

first step requires estimating the change in relevant measures of climate, including temperature, 

precipitation, sea-level rise, and the frequency and severity of extreme events. The second step 

involves estimating the physical effects of those changes in climate. Such effects might include 

changes in ecosystem structure and function, human exposures to heat stress, changes in the 

geographic range of disease vectors, or flooding of coastal areas. In the third step, the physical 

effects of climate change are translated into measures that economists can value, for example the 

number and location of properties that are vulnerable to floods, or the number of individuals 

exposed to and sensitive to heat stress. Many analyses that reach this step in the process, but not 

all, also proceed on to the fourth step, valuing the changes in dollar terms. . 

The simplest approach to valuation would be to apply a unit valuation approach - for example, 

the cost of treating a nonfatal case of heat stress or malaria attributable to climate change is a 

first approximation of the value of avoiding that case altogether. In many contexts, however, unit 

values can misrepresent the true marginal economic impact of these changes. For example, if 

climate change reduces the length of the ski season, individuals could engage in another 

recreational activity, such as golf. Whether they might prefer skiing to golf at that time and 

location is something economists might try to measure. 

This step-by-step linear approach to effects estimation is sometimes called the "damage 

function" approach. A damage function approach might imply that we look at effects of climate 

on human health as separate and independent from effects on ecology and recreation, an 

assumption that ignores the complex economic interrelationships among goods and services and 

individual decisions regarding these. Recent research suggests that the damage function 

approach, under some conditions, may be both overly simplistic (Freeman, 2003) and sometimes 

subject to serious errors (Strzepek and Smith, 1995; Strezpek et al., 1999). 

Economists have a number of techniques available for moving from quantified effects to dollar 

values. In some cases, the values estimated in one situation—e.g., one ecosystem or species—

can be transferred and used to value another. For example, value or benefits transfer is 

commonly used by federal agencies such as the US EPA and US Forest Service to value 

recreation when there is insufficient time or budget to conduct original valuation studies 

 

17 Some political economists also emphasize the role of explicit recognition of non-market environmental values as 

an important step in improving the well-being of poor populations (Boyce and Shelley, 2003). 

4 -16 
SAP 4.6 Chapter 4: Human Welfare 

(Rosenberger and Loomis, 2003). Techniques commonly used by economists to value nonmarket goods and services include: 

 Revealed preference. Revealed preference, sometimes referred to as the indirect valuation 

approach, involves inferring the value of a non-market good using data from market 

transactions (U.S. EPA, 2000; Freeman, 2003). For example, the value of a lake for its 

ability to provide a good fishing experience can be estimated by the time and money 

expended by the angler to fish at that particular site, relative to all other possible fishing 

sites. Or, the amenity value of a coastal property that is protected from storm damage (by 

a dune, perhaps) can be estimated by comparing the price of that property to other 

properties similar in every way but the enhanced storm protection. 

 Stated preference. Stated preference methods, sometimes referred to as the direct 

valuation, are survey methods that estimate the value individuals place on particular nonmarket goods based on choices they make in hypothetical markets. The earliest stated 

preference studies involved simply asking individuals what they would be willing to pay 

for a particular non-market good. The best studies involve great care in constructing a 

credible, though still hypothetical, trade-off between money and the non-market good of 

interest (or bundle of goods) to discern individual preferences for that good and hence, 

WTP. 

 Replacement or avoided costs. Replacement cost studies approach non-market values by 

estimating the cost to replace the services provided to individuals by the non-market 

good. For example, healthy coastal wetlands may provide a wide range of services to 

individuals who live near them (such as filtering pollutants present in water). A 

replacement cost approach would estimate the value of these services by estimating 

market costs for replacing the services provided by the wetlands. Analogously, the cost of 

health effects can be estimated using the cost of treating illness and of the lost workdays, 

etc. associated with illness. 

 Value of inputs. This approach calculated value based on the contribution of an input into 

some productive process. This approach can be used to determine the value of both 

market and non-market inputs, for example, fertilizer, water, or soil, in farm output and 

profits 

In the remainder of this section, we briefly discuss the relationship between climate change and 

four non-market effects (human health, ecosystems, recreation and tourism, and amenities), and 

discuss economic estimates of these effects using these techniques. 

4.3.3 Human Health 

In the US, climate change is likely to measurably affect health outcomes known to be associated 

with weather and climate, including heat-related illnesses and deaths , health effects due to 

storms, floods, and other extreme weather events, health effects related to poor air quality, waterand food-borne diseases, and insect-,tick-,and rodent-borne diseases. In addition to changes in 

mortality and morbidity, climate change may affect health in more subtle ways. Good health is 

more than the absence of illness; it includes mental health, the ability to function physically (to 

climb stairs or walk a mile), socially (to move freely in the world), and in a work environment. 

Please see Chapter 2 of this report, which provides an overview of health effects that have been 

associated with climate change. 

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SAP 4.6 Chapter 4: Human Welfare 

 

Despite our understanding of the pathways linking climate and health effects, there is uncertainty 

as to the magnitude and geographic and temporal variation of possible impacts on morbidity and 

mortality in the US, primarily due to a poor understanding of many key risk factors and 

confounding issues, such as behavioral adaptation and variability in population vulnerability 

(Patz et al., 2001). Even where our understanding of underlying climate and health relationships 

is better, few studies have attempted to explicitly link these findings to climate change scenarios 

to quantitatively estimate health impacts. Economists have relatively well established (although 

sometimes controversial) techniques for valuing mortality and some forms of morbidity, which 

could, in theory be applied to quantified impacts assessments. 

4.3.3.1 Overview of Health Effects of Climate Change 

The US is a developed country with a temperate climate. It has a well-developed health 

infrastructure and government and non-governmental agencies involved in disaster planning and 

response, both of which can help to mitigate potential health effects from climate change. 

Nevertheless, certain regions of the US will face difficult challenges arising from some of the 

following health effects. 

 Illnesses and deaths due to heatwaves. A likely impact in the US is an increase in the 

severity, duration, and frequency of heatwaves (Kalkstein and Greene, 1997; IPCC, 

2007c). This, coupled with an aging (and therefore more vulnerable) population, will 

increase the likelihood of higher mortality from exposure to excessive heat (see, for 

example, Semenza et al., 1996, and Knowlton et al., 2007). 

 Injuries and death from extreme weather events. Climate change is projected to alter the 

frequency, timing, intensity, and duration of extreme weather events, such as hurricanes 

and floods (Fowler and Hennessey, 1995). The health effects of these extreme weather 

events range from the direct effects, such as loss of life and acute trauma, to indirect 

effects, such as loss of shelter, large-scale population displacement, damage to sanitation 

infrastructure (drinking water and sewage systems), interruption of food production, 

damage to the health care infrastructure, and psychological problems such as post 

traumatic stress disorder (Curriero et al., 2001). 

 Illnesses and deaths due to poor air quality. Climate change can affect air quality by 

modifying local weather patterns and pollutant concentrations (such as ground level 

ozone), by affecting natural sources of air pollution, and by changing the distribution of 

airborne allergens (Morris et al., 1989; Sillman and Samson, 1995). Many of these effects 

are localized and, for ozone, compounded by assumptions of trends in precursor 

emissions. Despite these uncertainties, all else being equal, climate change is projected to 

contribute to or exacerbate ozone-related illnesses. 

 Water- and Foodborne Diseases. Altered weather patterns, including changes in 

precipitation, temperature, humidity, and water salinity, are likely to affect the 

distribution and prevalence of food- and waterborne diseases resulting from bacteria, 

overloaded drinking water systems, and increases in the frequency and range of harmful 

algal blooms (Weniger et al., 1983; MacKenzie et al., 1994; Lipp and Rose, 1997; 

Curriero et al., 2001). 

 Insect-, Tick-, and Rodent-borne Diseases. Vector-borne diseases, such as plague, 

Lyme’s disease, malaria, hanta virus, and dengue fever have distinct seasonal pattern, 

4 -18 
SAP 4.6 Chapter 4: Human Welfare 

suggesting that they may be sensitive to climate-driven changes in rainfall and 

temperature (Githeko and Woodward, 2003). Moderating factors, such as housing 

quality, land-use patterns, vector control programs, and a robust public health 

infrastructure, are likely to prevent the large-scale spread of these diseases in the United 

States.

4.3.3.2 Quantifying the Health Impacts of Climate Change 

A large epidemiological literature exists on the health effects associated with climate change, 

particularly the mortality effects associated with increases in average monthly or seasonal 

temperature, and with changes in the intensity, frequency, and duration of heatwaves. As 

described in Chapter 2, there is considerable speculation concerning the balance of climate 

change-related decreases in winter mortality compared with increases in summer mortality, 

although researchers suspect that declines in winter mortality associated with climate change are 

unlikely to outweigh increases in summer mortality (McMichael et al., 2001; Kalkstein and 

Greene, 1997; Davis, 2004). 

Net changes in mortality are difficult to estimate because, in part, much depends on complexities 

in the relationship between mortality and the changes associated with global change. Using 

average temperatures to estimate cold-related mortality, for example, is complicated by the fact 

that many factors contribute to winter mortality (such as spread of the influenza virus). Similarly, 

increased summer mortality may be affected not only by average temperature, but also by other 

temperature factors, such as variability in temperature, or the duration of heat waves. Moreover, 

quantifying projected temperature-related mortality requires going beyond epidemiology and (for 

example) projecting adaptive behaviors, such as the use of air conditioning, expanded public 

programs (such as heat warning systems), or migratory patterns. 

Few studies have attempted to link the epidemiological findings to climate scenarios for the 

United States, and studies that have done so have focused on the effects of changes in average 

temperature, with results dependent on climate scenarios and assumptions of future 

adaptation.18 Moreover, many factors contribute to winter mortality, making highly uncertain 

how climate change could affect mortality. No projections have been published for the U.S. that 

incorporate critical factors, such as the influence of influenza outbreaks. Below, we report the 

results of these studies in order to give a sense of the magnitude of mortality that might be 

associated with temperature changes associated with climate change and, by intimation, the 

magnitude of potential changes in economic welfare. The conclusions should be considered 

preliminary, however, in part because of the complexities in estimating mortality under future 

climate scenarios. Moreover, none of the studies reported below traces through the quantitative 

implications of various climate scenarios for mortality in all regions of the United States using 

region-specific data, suggesting a clear need for future research. 

 

18 McMichael et al. (2004) estimate the impact of climate change on DALYs (Disability-Adjusted Life Years) 

associated with waterborne and vector-borne illness for WHO regions. (DALYs represent the sum of life-years lost 

due to premature death and productive life years lost due to chronic illness or injury.) For the US, it is not 

anticipated that climate change will lead to loss of life or years of life due to chronic illness or injury from 

waterborne or foodborne illnesses. However, there will likely be an increase in the spread of several food- and 

water-borne pathogens among susceptible populations depending on the pathogens' survival, persistence, habitat 

range and transmission under changing climate and environmental conditions. 

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SAP 4.6 Chapter 4: Human Welfare 

Quantifying the relationship between climate change and cases of injury, illness, or death 

requires an exposure-response function that quantifies the relationship between a health endpoint 

(e.g., premature mortality due to cardiovascular disease (CVD), cases of diarrheal disease) and 

climate variables (e.g., temperature and humidity). The exposure-response function can be used 

to compute the relative risk of illness or death due to a specified change in climate, e.g., a 

temperature increase of 2.5°C. Applying this relative risk to the baseline incidence of the illness 

or death in a population yields an estimated number of cases associated with the climate 

scenario. 

Two studies have attempted to link exposure-response functions to future climate scenarios and 

thereby develop temperature-related mortality estimates.19 McMichael et al. (2004) estimate the 

effects of average temperature changes associated with projected climates resulting from 

alternative emissions scenarios, by WHO region. For the AMR-A region, which includes the 

United States, Canada, and Cuba, they estimate the impact on cardio-vascular mortality relative 

to baseline conditions in 1990. Effects are estimated for average temperature projections 

associated with three alternative emissions scenarios: (1) no control of GHG emissions,20

(2) stabilization at 750 parts-per-million (ppm) of CO2 equivalent by 2210, and (3) stabilization 

at 550 ppm CO2 equivalent by 2170.21

McMichael et al. (2004) bases the estimates of the effects of average temperature changes on 

mortality from cardio-vascular disease (CVD) for AMR-A on Kunst et al. (1993). Kunst et al.

(1993) find CVD mortality rates to be lowest at 16°C, and to increase by 0.5% for every degree 

C below 16°C and increase by 1.1% for each degree above 16°C. In applying these results to 

future climate scenarios, McMichael et al. (2004) assume that people will adjust to higher 

average temperatures; thus, the temperature at which mortality rates reach a minimum is adjusted 

by scenario. No adjustment is made for attempts to mitigate the effects of higher temperatures 

through (for example) increased use of air-conditioning. The effect of the climate scenarios for 

the North American region (AMR-A), reported for 2020 and 2030, is, on net, zero—reductions 

in CVD mortality due to warmer winter temperatures cancel out increases in CVD mortality due 

to warmer summer temperatures. 

Hayhoe et al. (2004) examine the impacts on climate and health in California of projected 

climate change associated with two emissions scenarios. The emissions scenarios are similar to 

those used in McMichael et al. (2004): (1) stabilization at 970 ppm of CO2 and (2) stabilization 

at 550 ppm of CO2.

22 In Los Angeles, by the end of the century, the number of heatwave days 

(3 or more days with temperatures above 32 °C) increases fourfold under scenario B1 and six to 

eight times under scenario A1fi. From a baseline of 165 excess deaths in the 1990s, heat-related 

deaths in Los Angeles are projected to increase two to three times under scenario B1 and five to 

seven times under scenario A1fi by 2090. 

 

19 These studies use climate scenarios that are associated with different emissions scenarios from IPCC (2000), the 

so-called SRES scenarios. 

20 McMichael et al. (2004) represent unmitigated emissions using the IS92a emissions scenario presented in IPCC 

(2000). 

21 Climate scenarios are projected for 2025 and 2050 using the HadCM2 model at a resolution of 3.75◦

longitude by 

2.5◦

 latitude and interpolated to other years. 22 Hayhoe uses two SRES (IPCC 2000) emissions scenarios: A1fi (corresponding to 970 ppm of CO2) and B1 

(corresponding to 550 ppm of CO2). 

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SAP 4.6 Chapter 4: Human Welfare 

These results can be compared with those of an earlier study that employed a composite climate 

variable to examine the impact of extreme temperatures on daily mortality under future climate 

scenarios. Kalkstein and Greene (1997) analyzed the effect of temperature extremes (both hot 

and cold) on mortality for 44 US cities in the summer and winter. They then applied these results 

to climate projections from two GCMs for 2020 and 2050. In 2020, under a no-control scenario, 

excess summer deaths in the 44 cities were estimated to increase from 1,840 to 1,981-4,100, 

depending on the GCM used. The corresponding figures for 2050 were 3,190-4,748 excess 

deaths. 

4.3.3.3 Valuation of Health Effects 

In benefit-cost analyses of health and safety programs, mortality risks are commonly valued 

using the “value of a statistical life” (VSL)—the sum of what people would pay to reduce their 

risk of dying by small amounts that, together, add up to one statistical life. This approach allows 

valuation economists to focus on how people respond to and implicitly value mortality risk in 

their daily decisions, rather than attempting to value the lives lost, per se (U.S. EPA, 2000). This 

approach also responds to the type of data that is typically available; the excess deaths associated 

with a particular climate scenario are indeed the number of statistical lives that would be lost. 

Willingness to pay for a current reduction in risk of death (e.g., over the coming year) is usually 

estimated from compensating wage differentials in the labor market (a revealed preference 

method), or from contingent valuation surveys (a stated preference method) in which people are 

asked directly what they would pay for a reduction in their risk of dying. The basic idea behind 

compensating wage differentials is that jobs can be characterized by various attributes, including 

risk of accidental death. If workers are well-informed about risks of fatal and non-fatal injuries, 

and if labor markets are competitive, riskier jobs should pay more, holding worker and other job 

attributes constant (Viscusi, 1993). In theory, the impact of a small change in risk of death on the 

wage should equal the amount a worker would have to be compensated to accept this risk. For 

small risk changes, this is also what the worker should pay for a risk reduction. 

For the compensating wage approach to yield reliable estimates of the VSL, it is necessary that 

workers be informed about fatal job risks and that there be sufficient competition in labor 

markets for compensating wage differentials to emerge.23. To measure these differentials 

empirically requires accurate estimates of the risk of death on the job—ideally, broken down by 

industry and occupation. The researcher must also be able to include enough other determinants 

of wages that fatal job risk does not pick up the effects of other worker or job characteristics. 

Empirical estimates of the value of a statistical life based on compensating wage studies 

conducted in the U. S. lie in the range of $0.6 million to $13.5 million (1990 dollars) (Viscusi, 

1993; U.S. EPA, 1997), which is the rough equivalent of $0.7 million to $16.5 million in year 

2000 dollars.24 

 

23 Estimates of compensating wage differentials are often quite sensitive to the exact specification of the wage 

equation. Black et al. (2003), in a reanalysis of data from U.S. compensating wage studies requested by the USEPA, 

conclude that the results are too unstable to be used for policy.

24 Adjusted using the GDP implicit price deflator produced by the Bureau of Economic Analysis US Department of 

Commerce, available at http://www.bea.gov/national/nipaweb/TableView.asp#Mid 

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SAP 4.6 Chapter 4: Human Welfare 

This challenge is compounded by the long-term nature of climate risks, which suggests that 

much of the premature mortality associated with higher temperatures will occur in the future. 

Indeed, McMichael et al. (2004) and Kalkstein and Greene (1997) estimate mortality based on 

climate effects around the years 2020 and 2050; Hayhoe et al. (2004) analyze impacts in 2070-

2099. 

It is also the case that the majority of the health effects of climate change will be felt by persons 

65 and over. Recent attempts to examine how the VSL varies with worker age (Viscusi and 

Aldy, 2007) suggest that the VSL ranges from $9.0 million (2000 dollars) for workers aged 35-

44 to $3.7 million for workers aged 55-62. Contingent valuation studies (Alberini et al., 2004) 

also suggest that the VSL may decline with age. Further, economic theory suggests that, under 

some assumptions, persons are willing to pay less to reduce a risk they will face in the future 

(say, at age 65) than they are willing to pay to reduce a risk they face today (Cropper and 

Sussman, 1990). Both these factors may affect the economic value that would be attached to 

excess mortality estimates, such as those derived by Kalkstein and Greene (1997). 

 

The potential health effects associated with climate change are much broader than the changes in 

excess mortality discussed above. The effects of climate on illness have been examined in the 

literature, as indicated in the previous section; however, there have been few attempts to examine 

the implications of these studies for future climate scenarios. In addition to quantified estimates 

of mortality and morbidity, themselves indications of well-being and welfare, a range of 

economic techniques that have been developed for use in cost-benefit analyses of health and 

safety regulations could be applied to many of the endpoints that may be affected by climate 

change, as suggested by Table 4.3. Before these methods could be applied, however, the impacts 

of climate change must be translated into physical damages. 

It is also the case that good health is more than the absence of illness. All of the dimensions of 

functioning measured in standard questionnaires (including various health outcomes surveys 

(HCFR, 2004) may be affected by changes in climate. From a valuation perspective, we would 

expect changes in functional limitations (stiffness of joints, difficulty walking) not to be linked 

directly to climate or to weather, but rather to be instrumental in people’s location decisions and, 

thus, reflected in wages and property values. The relationship between climate and wages and 

property values are discussed in the subsequent section on Amenity values. 

4.3.4 Ecosystems 

Human welfare depends on the Earth’s ecosystems and the services that they provide, where 

ecosystem services may be defined as “the conditions and processes through which natural 

ecosystems, and the species that make them up, sustain and fulfill human life” (Daily, 1997). 

These services contribute to human well-being and welfare by contributing to basic material 

needs, physical and psychological health, security, and economic activity, and in other ways (see 

Table 4.4). For example, a variety of ecosystem changes may be linked to changes in human 

health, from changes that encourage the expansion of the range of vector-borne diseases 

(discussed in Chapter 2) to the frequency and impact of floods and fires on human populations, 

due to changes in protection afforded by ecosystems. 

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SAP 4.6 Chapter 4: Human Welfare 

The ability of the biosphere to continue providing these vital goods and services is being strained 

by human activities, such as habitat destruction, releases of pollutants, over-harvesting of plants, 

fish and wildlife, and the introduction of invasive species into fragile systems. The recent 

Millennium Ecosystem Assessment reported that of 24 vital ecosystem services, 15 were being 

degraded by human activity (MA, 2005). Climate change is an additional human stressor that 

threatens to intensify and extend these adverse impacts to biodiversity, ecosystems, and the 

services they provide. 

Changes in temperature, precipitation, and other effects of climate change will have direct

effects on ecosystems. Climate change will also indirectly affect ecosystems, via, for example, 

effects of sea level rise on coastal ecosystems, decision-makers’ responses to climate change (in 

terms of coastline protection or land use), or increased demands on water supplies in some 

locations for drinking water, electricity generation, and agricultural use. Understanding how 

these changes alter economic welfare requires identifying and potentially valuing changes in 

ecosystems resulting from climate change. Getting to the point of valuation, however, requires 

establishing a number of linkages—from projected changes in climate to ecosystem change, to 

changes in services, to changes in the value of those services—as illustrated in Figure 4.2. The 

scientific community has not, thus far, focused explicitly on establishing these linkages in the 

context of climate change. Consequently, the published literature is somewhat fragmented, 

consisting of discussions of climate effects on ecosystems and of valuation of ecosystems and 

their services (in only a few cases do the latter focus on climate change). 

Figure 4.2 Steps from Climate Change to Economic Valuation of Ecosystem Services 

Already observed effects (see reviews in Parmesan and Yohe, 2003; Root et al., 2003; Parmesan 

and Galbraith, 2004) and modeling results indicate that climate change is very likely to have 

major adverse impacts on ecosystems (Peters and Lovejoy, 1992; Bachelet et al., 2001; Lenihan 

et al., 2006; Galbraith et al., 2006). It is also likely that these changes will adversely affect the 

services that humans and human systems derive from ecosystems (MA, 2005). Climate change 

may affect ecosystems in the US within this century in the following ways. 

Shifting, breakup and loss of ecological communities. As climate changes, species that are 

components of communities will be forced to shift their ranges to follow cooler temperatures 

either poleward or upward in elevation. In at least some cases, this is likely to result in the 

breakup of communities as organisms respond to temperature change and migrate at different 

rates. In general, study projections include: northern extensions of the ranges of southern 

broadleaf forest types, with northward contractions of the ranges of northern and boreal conifer 

forests; elimination of alpine tundra from much of its current range in the United States; and the 

replacement of forests by grasslands, shrub-dominated communities, and savannas, particularly 

in the south (e.g., VEMAP, 1995; Melillo et al., 2001; Lenihan et al., 2006). Because of different 

intrinsic rates of migration, communities may not move intact into new areas (Box 4.1). 

Another potential community effect of climate change is the facilitation of community 

penetration and degradation by invasive weeds that will replace more sensitive native species 

(Malcolm and Pitelka, 2000) 

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SAP 4.6 Chapter 4: Human Welfare 

Extinctions of plants and animals and reduced biodiversity. While some species may be able 

to adapt to changing climate conditions, others will be adversely affected. It is very likely that 

one result of this will be to accelerate current extinction rates, resulting in loss in biodiversity. 

The most vulnerable species within the United States may be those that are currently confined to 

small, fragmented habitats that may be sensitive to climate change. This is the case with Edith’s 

checkerspot, a western butterfly species that is already undergoing local subpopulation 

extinctions due to climate change (Parmesan, 1996). Other potentially vulnerable organisms 

include those that are restricted to alpine tundra habitats (Wang et al., 2002), or to coastal 

habitats which may be inundated by sea level rise (Galbraith et al., 2002). 

Range shifts. Faced with increasing temperatures, populations of plants and animals will attempt 

to track their preferred climatic conditions by shifting their ranges. Range shifts will be limited 

by factors such as geology (in the case of plants that are confined to certain soil types), or the 

presence of cities, agricultural land, or other human activities that block northward migration. 

Some individual species in North America and the US are already undergoing range shifts (Root 

et al., 2003; Parmesan and Galbraith, 2004). The red fox in the Canadian arctic shifted its range 

northward by up to 600 miles during the 20th century, with the greatest expansion occurring 

where temperature increases have been the largest (Hersteinsson and Macdonald, 1992). More 

generally, a number of bird species have shifted their ranges northward in the United States over 

the past few decades. While some of these changes may be attributable to non-climatic factors, it 

is very likely that some are due to climate change (Root et al., 2003; Parmesan and Galbraith, 

2004). 

Timing changes. The timing of major ecological events is often triggered or modulated by 

seasonal temperature change. Changes in timing may already be occurring in the breeding 

seasons of birds, hibernation seasons of amphibians, and emergences of butterflies in North 

America and Europe (Bebee, 1995; Crick et al., 1997; Brown et al., 1999; Dunn and Winkler, 

1999; Root et al., 2003; Roy and Sparks, 2000). Disconnects in timing of interdependent 

ecological events may be accompanied by adverse effects on sensitive organisms in the United 

States. Such effects have already been observed in Europe where forest-breeding birds have been 

unable to advance their breeding seasons sufficiently to keep up with the earlier emergence of 

the arboreal caterpillars with which they feed their young. This has resulted in declining 

productivity and population reductions in at least one species (Both et al., 2006). 

Changes in ecosystem processes. Ecosystem processes, such as nutrient cycling, 

decomposition, carbon flow, etc., are fundamentally influenced by climate. Climate change is 

likely to disrupt at least some of these processes. While these effects are difficult to quantify, 

some types of changes can—and have been observed. Increasing temperatures over the past few 

decades on the North Slope of Alaska have resulted in a summer breakdown of the permanently 

frozen soil of the Alaskan Tundra and increased activity by soil bacteria that decompose plant 

material. This has accelerated the rate at which CO2 (a breakdown product of the decomposition 

of the vegetation and also a greenhouse gas) is released to the atmosphere—changing the Tundra 

from a net sink (absorber) to a net emitter of CO2 (Oechel et al., 1993; Oechel et al., 2000). 

Indirect effects of climate change. Climate change may also result in “indirect” ecological 

effects as it triggers events (the frequency and intensity of fires, for example) that, in turn, 

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SAP 4.6 Chapter 4: Human Welfare 

adversely affect ecosystems. In U.S. forest habitats, increased temperatures are very likely to 

result in increased frequency and intensity of wildfires, especially in the arid west, leading to the 

breakup of contiguous forests into smaller patches, separated by shrub and grass dominated 

communities that are more resistant to the effects of fire (Lenihan et al., 2006). Other major 

indirect effects are likely to include the loss of coastal habitat through sea level rise (Warren and 

Niering, 1993; Ross et al., 1994; Galbraith et al., 2002), and the loss of coldwater fish 

communities (and the recreational fishing that they support) as water temperatures increase 

(Meyer et al., 1999). 

The linkages between these types of changes and the provision of ecosystem services are 

difficult to define. While ecologists have developed a number of metrics of ecosystem condition 

and functioning (e.g., species diversity, presence/absence of indicator species, primary 

productivity, nutrient cycling rates), these do not generally bear an obvious relation to metrics of 

services. In some cases, such as species diversity and bird population sizes, direct links might be 

drawn to services (in this case, opportunities for bird watching). However, in many, if not most 

cases, the linkages between stressor effects, change in ecosystem metrics, and service flows, are 

more obscure. For example, it is known that freshwater wetlands can remove contaminants from 

surface water (Daily, 1997) and this is an important service. However, the specific ways in which 

wetlands do this—in terms of the ecological processes and linkages within the system—are not 

well understood, probably vary between different types of wetland (e.g., beaver swamps vs. 

cattail stands), and may vary spatially and temporally. 

4.3.4.1 Economic Valuation of Effects on Ecosystems 

Ecosystems are generally considered non-market goods: although land itself can be bought and 

sold, there is no market for ecosystem services per se, and so land value is only a partial measure 

of the value of the full range of ecosystem services provided. From the perspective of human 

welfare and climate change, however, we are concerned less with the ecosystems or the land on 

which they are located, than with the diverse services they provide, as illustrated in Table 4.4. 

Economic valuation of changes in ecosystem services will be easier in cases where there are 

relationships between market goods and the ecosystem services being valued. For example, 

ecosystem changes may result in changes in the availability of goods and services that are traded 

on markets, as in the case of provisioning services, such as food, fisheries, pharmaceuticals etc. 

In other cases, market counterparts to the services may exist, as in the case of regulating services; 

for example, insights into the value of water purification services can come from looking at the 

(avoided) cost of a water purification plant to substitute for the ecosystem service. Services, such 

as water purification, may also have relationships with market goods and services (e.g., as an 

input into the production process) that make it possible to estimate economic values at least in 

part or approximately. 

Many ecosystem services are, however, truly non-market, in that there are no market 

counterparts by which to estimate their value. Recreational uses of ecosystems fall into this 

category, and so economists have developed means of inferring values from behavior (e.g., travel 

cost), as discussed in the next section), and in other ways. Most of the support services and 

cultural values of ecosystems are also in the “true” non-market category. Value can arise even if 

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SAP 4.6 Chapter 4: Human Welfare 

a good or service is not explicitly consumed, or an ecosystem even experienced.25 Thus, it can 

be difficult to define, much less to measure the value of changes in these non-market services. To 

value these services, economists typically use stated preference (direct valuation) methods, a 

method that can be used not only for non-market services, but also to value services in other 

categories, such as the value that individuals place on clean drinking water or swimming 

facilities. 

Below we report on the relevant literature in two categories. First, we report on studies that have 

looked at the non-market value of specific ecosystems or species. Since only a few of these 

studies attempt to value the impacts of climate change on ecosystems, we also highlight some 

non-market studies from the more general literature on ecosystem valuation, which can provide 

insights into the magnitude of potential values of services that might be vulnerable to climate 

change. Next we look at a different approach to valuation of ecosystems—a more “top-down” 

approach—which has been adopted both to look at the effects of climate change and more 

broadly at the total value of ecosystems. As the discussions indicate, the treatment of climate 

change, per se has been very sparse. Moreover, the lack of studies reflects, in part, a need to 

develop analytical linkages between the physical effects of climate on ecosystems, the services 

valued by humans, and appropriate techniques to value changes of the types, and with the 

breadth, indicated by studies of the effects of global change on ecosystems. 

4.3.5.2 Valuation of the Effects of Climate Change on Selected Ecosystem and Species 

Although climate change appears in a number of studies, it is often as a context for the scenario 

presented in the study for valuation, and so the study cannot be interpreted as valuation of 

climate change or climate effects per se. Only a few studies can be said to value the economic 

impacts of climate change on a particular ecosystem. 

Two studies, Layton and Brown (2000) and Layton and Levine (2003) estimate total values for 

preventing Colorado (Rocky Mountain) forest loss due to climate change, based on data from the 

same stated choice or preference survey. The survey was conducted with Denver-area residents, 

who were expected to be familiar with forested regions in their nearby mountains. Respondents 

were given detailed information about climate change impacts on these forests, including 

changes in tree line elevation over both 60-year and 150- year time horizons, and asked to make 

choices between alternatives, allowing recovery of implied willingness to pay (WTP). Layton 

and Brown (2000) found WTP in the range of $10 to $100 per month, per respondent, to prevent 

forest loss, with the range depending, in part, on the amount of forest lost. Layton and Levine 

(2003) reanalyzed the same data set, using a different approach that focuses on understanding 

respondents’ least preferred, as well as most preferred, choices. They found that respondents’ 

value of forest protection depends also on the time horizon—preventing effects that occur further 

into the future are valued less than nearer term effects. 

Kinnell et al. (2002) designed and implemented several versions of stated preference studies that 

explored the impacts of wild bird (duck) loss due to either adverse agricultural practices, climate 

 

25 Economists have devoted much effort to defining the source of non-market values of ecosystems, coining such 

terms as “use” and “non-use” value, consumption value, existence value, and invoking, as reasons why people care 

about ecosystesm, the moral philosophies inherent in terms such as stewardship, spiritual values, etc. (see for 

example, Freeman (2003). 

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SAP 4.6 Chapter 4: Human Welfare 

change, or both. The respondents consisted of Pennsylvania duck hunters, although the 

hypothetical ecosystem impacts occurred in the Prairie Pothole region, which is in the northern 

Midwestern states and parts of Canada. The authors considered a hypothetical loss in duck 

populations, with a scenario that presented some respondents with a 30% loss, and other with a 

74% loss, some with a 40 year time horizon, and others with a 100 year time horizon. The study 

cannot be viewed as an estimate of willingness to pay to avoid climate change; however, it is 

interesting because it suggests that recreational enthusiasts are willing to pay for ecosystem 

impacts that they do not necessarily expect to use. In addition, the study provides evidence that 

the context of climate change or other cause of ecosystem harm (in this case agricultural 

practices)—irrespective of the level of harm—may affect respondents’ valuation of the harm. 

Although very few studies have valued climate change impacts on ecosystems, economists have 

conducted numerous studies (primarily using direct valuation methods) of ecosystem values in 

particular geographic locations, often focusing on charismatic species, or specific types of 

ecosystems, such as wetlands, in a particular location. In some cases, the estimated values are 

linked to specific services that the species or ecosystem provide, but in many the services 

provided are somewhat ambiguous, and it is not always clear what aspect of the species, habitat, 

or ecosystem is driving the individual respondent’s economic valuation. 

A number of studies indicate that people value the protection of species or ecosystems. Some of 

these studies find potentially significant species values, ranging from a few dollars to hundreds 

of dollars per year, per person. For example, MacMillan et al. (2001) estimate the value of 

restoring woodlands habitat, and separately evaluate the reintroduction of the wolf and the 

beaver to Scottish highlands. In the United States, species such as salmon and spotted owls, as 

well as their habitat, have been examined in connection to their respective controversies. 

Studies have also looked at the value of ecosystems or changes in ecosystems. In the former 

case, economists use either the value of productive output (harvest) as an indicator of value, or 

respondents value protecting the ecosystem. For example, numerous coastal wetland and beach 

protection studies have used a variety of non-market valuation approaches. A survey of a number 

of these studies reports values ranging from $198 to approximately $1500 per acre (Woodward 

and Wui, 2001). 

Some studies have looked explicitly at the services provided by ecosystems. For example, 

Loomis et al. (2000) consider restoration of several ecosystem services (dilution of wastewater, 

purification, erosion control, as fish and wildlife habitat, and recreation) for a 45-mile section of 

the Platte River, which runs east from the State of Colorado into western Nebraska. Average 

values are about $21 per month for these additional ecosystem services for the in-person 

interviewees. While these studies and their values are generally informative, transferring values 

from studies like the ones above to other ecosystems, and using the results to estimate values 

associated with climate change impacts, can be problematic. 

4.3.4.3 Top-down Approaches to Valuing the Effects of Climate Change and Ecosystem 

Services 

From the perspective of deriving values for ecosystem changes (or changes in ecosystem 

services) associated with climatic changes, one difficulty with the above studies is that the focus 

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SAP 4.6 Chapter 4: Human Welfare 

is on discrete changes to particular species or geographic areas. It is therefore difficult to know 

how these studies relate to, or shed light on, the types of widespread and far-reaching changes to 

ecosystems (and the services they provide) that will result from climate change. Consequently, 

some studies have attempted to value ecosystems in a more aggregate or holistic manner. While 

these studies do not focus specifically on the US, they are indicative of an alternative approach 

that recognizes the interdependence of ecosystems and their components, and therefore deserve 

some discussion. 

Several models include values for non-market damages, worldwide, resulting from projected 

climate change. These impact studies have been conducted at a highly aggregated level; most of 

the models are calibrated using studies of the United States which are then scaled for application 

to other regions (Warren et al., 2006). 

A study of total ecosystem values, but not undertaken in the context of climate change, is the 

highly publicized study by Costanza et al. (1997), which offers a controversial look at valuing 

the “entire biosphere.” Because their reported estimated average value of $33 trillion per year 

exceeds the global gross national product, economists have a difficult time reconciling this 

estimate with the concept of economic value (WTP); since WTP cannot equal twice income. 

Ehrlich and Ehrlich (1996) and Pimental et al. (1997) are studies by natural scientists that have 

attempted to value ecosystems or in the case of the latter, biodiversity. These are important 

attempts to indicate the value of ecosystems, but the accuracy and reliability of the values are 

questionable. To paraphrase a study by several prominent environmental economists that is 

slightly critical of all of these studies, economists do not have any fundamental difference of 

opinion with these natural scientists about the importance of ecosystems and biodiversity, rather 

it is with the correct use of economic value concepts in these applications (see Bockstael et al.,

2000). 

4.3.5 Recreational Activities and Opportunities 

Ecosystems provide humans with a range of services, including outdoor recreational 

opportunities. In turn, outdoor recreation contributes to individual wellbeing by providing 

physical and psychological health benefits. In addition, tourism is one of the largest economic 

sectors in the world, and it is also one of the fastest growing (Hamilton and Tol, 2004); the jobs 

created by recreational tourism provide economic benefits not only to individuals but also to 

communities.26 A number of studies have looked at the qualitative effects of climate change on 

recreational opportunities (i.e., resources available) and activities in the US, but only a few have 

taken this literature the additional step of estimating the implications of climate change for 

visitation days or economic welfare. This section describes the results of this research into the 

impacts on several forms of recreation and reports the economic benefits and losses associated 

with these changes at the national level. 

Slightly more than 90% of the U.S. population participates in some form of outdoor recreation, 

representing nearly 270 million participants (Cordell et al., 1999), and several billion days spent 

each year in a wide variety of outdoor recreation activities. According to Cordell et al. (1999), 

the number of people participating in outdoor recreation is highest for walking (67%), visiting a 

beach or lakeshore or river (62%), sightseeing (56%), swimming (54%) and picnicking (49%). 

 

26 Effects on jobs, income, and similar metrics are considered market impacts, and are not discussed here. 

4 -28 
SAP 4.6 Chapter 4: Human Welfare 

Most days are spent in activities such as walking, biking, sightseeing, bird-watching, and wildlife 

viewing (Cordell et al., 1999), because of the high number of days per bicycle rider and bird 

watcher, but the range of outdoor recreation activities in the United States is as diverse as its 

people and environment. While camping, hunting, backpacking and horseback riding attract a 

fraction of the people who go biking or bird-watching, these other specialized activities provide a 

very high value to their devotees. Many of these devotees of specialized outdoor recreation 

activities are people who “work to live,” i.e., specialized weekend recreation is one of their 

rewards for the 40+ hour workweek. 

Climate change resulting from increasing average temperatures as well as changes in 

precipitation, weather variability (including more extreme weather events), and sea level rise, has 

the potential to affect recreation and tourism along two pathways. Figure 4.3 illustrates these 

direct and indirect effects of climate change on recreation. Since much recreation and tourism 

occurs out of doors, increased temperature and precipitation have a direct effect on the 

enjoyment of these activities, and on the desired number of visitor days and associated level of 

visitor spending (as well as tourism employment). Weather conditions are considered one of the 

four greatest factors influencing tourism visitation (Pileus Project, 2007). In addition, much 

outdoor recreation and tourism depends on the availability and quality of natural resources (Wall, 

1998), Consequently, climate change can also indirectly affect the outdoor recreational 

experience by affecting the quality and availability of natural resources (and, thus, the 

availability and quality of recreational experience) used for recreation such as beaches, forests, 

wetlands, snow, and wildlife. 

Figure 4.3. Direct and Indirect Effects of Climate Change on Recreation

Effects of climate change can be both positive and negative. The length of season for and 

desirability of several of the most popular activities—walking, visiting a beach, lakeshore, or 

river, sightseeing, swimming, and picnicking (Cordell et al., 1999)—will likely be enhanced by 

small near- term increases in temperature. However, long-term higher increases in temperature 

may eventually have adverse effects on activities like walking, and result in sufficient sea level 

rise to reduce publicly accessible beach areas, just at the time when demand for beach recreation 

to escape the heat is increasing. In contrast, some activities are likely to be unambiguously 

harmed by even small increase in global warming, such as snow and ice-dependent activities. 

In some ways, one can interpret the direct effects of climate change as influencing the demand 

for recreation and the indirect effects as influencing the supply of recreation opportunities. For 

example, warmer temperatures make whitewater boating more desirable. However, the warmer 

temperatures may reduce river flows since there is less snowpack, higher evapotranspiration, and 

greater water diversions for irrigated agriculture. Some studies cited below look only at the direct 

effects, while others represent the combined effect of the direct and indirect pathways. 

Direct effects. To date, most studies of the direct effects of climate change on recreation and 

tourism have been qualitative, although a few have been quantitative. Qualitatively, we would 

expect both positive and negative effects of climate change on different recreational activities. 

Many of the qualitative studies rely simply on intuition to suggest that increases in air and water 

temperatures will have a positive effect on outdoor recreation visitation in two ways: (a) more 

enjoyment from the activity; (b) a longer season in which to enjoy the activity (DeFreitas, 2005; 

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SAP 4.6 Chapter 4: Human Welfare 

Scott and Jones, 2005; Scott, Jones and Konopek (2007). Hall and Highman (2005) note that 

climate change may provide more days of “ideal” temperatures for water- based recreation 

activities and some land based recreation activities such as camping, picnicking and golf. 

The recreational activities most obviously harmed by warmer climate are sports that require 

snow or cold temperatures, such as downhill and cross country skiing, snowmobiling, ice fishing, 

and snowshoeing. Reductions in visitor use (see, for example, the studies reported in Table 4.5) 

occur primarily from shorter season, particularly early in the year at such traditional times as 

Thanksgiving and Spring break. But with warmer temperatures, there is also less precipitation as 

snow and more as rain on snow, which contributes to a much shallower snowpack and harder 

snow. Further, recreating in freezing rain or slushy temperatures is not a pleasant experience, 

reducing benefits from skiing, snowshoeing, and snowmobiling, further reducing use.

Some recreation areas that are already hot during the summer recreation season will see 

decreases in use. For example, the Death Valley National Park, Joshua Tree National Park, and 

Mesa Verde National Park are all projected to be “intolerably hot” reducing visitation (Saunders 

and Easley, 2006). 

Most quantitative studies of the effects of climate change on recreation evaluate specific 

projected changes in temperature and/or precipitation, such as a 2.5°C increase in temperature 

over the next fifty years. Two quantitative studies look at effects of temperature change in 

Canadian recreation.27 Scott and Jones (2005) project that the golf season in Banff, Canada could 

be extended by at least one week and up to eight weeks. The combined effect of warmer 

temperatures lengthening the golfing season, and the increasing the desirability of golfing during 

the existing season, together result in an increase in the rounds of golf played by between 50% 

and 86%. (Similar increases might be expected for golf in northern states of the U.S. such as 

Minnesota, Wisconsin, New York, etc. with longer golf seasons.) Scott et al. (2006) and Scott 

and Jones (2005) suggest that some of the previously projected large (30% to 50%) reductions in 

length of ski seasons at northern ski areas (e.g., in Canada, Michigan, and Vermont) can be 

reduced (to 5% to 25%) through the use of advanced snowmaking. While use of advanced 

snowmaking to minimize reductions in ski season seems plausible for the studied northern ski 

areas, it is doubtful that snowmaking would benefit ski areas in California, New Mexico, Oregon 

and West Virginia where the Thanksgiving and “Spring Break” periods are already too warm for 

successful snowmaking or retention of snow made in some years. 

Some studies have used natural variations in temperature to evaluate the effects of climate on 

recreation (including measures on monthly, seasonal and inter-annual variation). Two of these 

have found that while visitation increases with initial increases in temperature, visitation actually 

decreases as temperature increases even further (Hamilton and Tol, 2004; Loomis and 

Richardson, 2006). Two of the quantitative studies, which look not only at visitor days but also 

at monetary measures of economic welfare, are discussed in more detail below, following the 

discussion of indirect effects. 

 

27 Scott and Jones (2005) used +1C to +5C in their scenarios and Scott et al. (2006) used +1.5C to +3C in their low 

impact scenario and +2C to +8C in their high impact scenario. 

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SAP 4.6 Chapter 4: Human Welfare 

Indirect effects. While increased temperature may increase the demand for some outdoor 

recreation activities, in some cases climate change may reduce the supply of natural resources on 

which those recreational activities depend. As noted above, reduced snowpack for winter 

activities has been projected in the Great Lakes (Scott et al., 2005), in northern Arizona (BarkHodgins and Colby, 2006) and at a representative set of ski areas in the United States (Loomis 

and Crespi, 1999).28 

For example, lower in-stream flows and lower reservoir levels have consistently been shown to 

reduce recreation use and benefits (Shaw, 2005). Thus, changes associated with climate can 

reduce opportunities for summer boating and other water sports. When less precipitation falls as 

snow in the winter, and more falls as rain in the spring, early spring season run-off will increase. 

Summer river flows will be correspondingly lower, at times when demand for whitewater 

boating is higher. Human responses to the physical changes associated with climate change may 

exacerbate natural effects reducing recreational opportunities. For example, many current 

reservoirs are not designed to handle huge spring inflows, and thus this water may be “spilled,” 

which lowers reservoir levels during the summer season. These lower reservoir levels are then 

drawn down more rapidly as higher temperatures increase evapotranspiration and increase 

irrigation releases. In turn, the resulting lower reservoir may leave boat docks, marinas, and boat 

ramps inaccessible. 

Ecosystems that provide recreational benefits may also be at risk from climate change. Wetlands 

are another recreational environment that is at risk from climate change. Wetland based 

recreation include wildlife viewing and waterfowl hunting. With sea level rise, many existing 

coastal wetlands will be lost, and given existing development inland, these lost wetlands may not 

be naturally replaced (Wall, 1998). The higher temperatures and reduced water availability is 

also expected to adversely affect freshwater wetlands in the interior of the country. As such 

waterfowl hunting and wildlife viewing may be adversely affected. 

Higher water temperatures and lower stream flows are projected to reduce coldwater trout 

fisheries (U.S. EPA, 1995; Ahn et al., 2000) as well as native and hatchery stocks of Chinook 

salmon in the Pacific Northwest (Anderson et al., 1993). Given trout and Chinook salmon 

sensitivity to warm water temperatures, these affects are not surprising. However, Anderson et 

al.’s estimated magnitude of 50% to 100% reduction in Chinook spawning returns is quite large. 

Reductions of such magnitude will have a substantial adverse effect on recreational salmon catch 

rates, and possibly whether recreational fishing would even be allowed to continue in some areas 

of the Pacific Northwest. However, from a national viewpoint, fishing participation for trout, 

cool water species and warm water species dominates geographically specialized fishing like 

Chinook salmon. Warmer water temperatures are projected to eliminate stream trout fishing in 8-

10 states and result in a 50% reduction in coldwater stream habitat in another 11-16 states 

depending on the GCM model used (U.S. EPA, 1995). This could adversely affect up to 25% of 

U.S. fishing days (Vaughan and Russell, 1982). This 25% loss may be an upper limit as some 

 

28 Higher temperatures (while they increase snowmelt reducing the snow skiing season) may have two subtle effects: 

(a) stimulating demand for snow skiing due to warmer temperatures, for those skiers who prefer “spring skiing” due 

to the warmer temperatures even if the snow conditions are less than ideal; and (b) reduced snowmelt opens up the 

high mountains for hiking, backpacking and mountain biking activities somewhat earlier than is the case now, which 

may lead to increases in those visitor use days. 

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SAP 4.6 Chapter 4: Human Welfare 

coldwater stream anglers may substitute to less affected coldwater lakes/reservoirs or switch to 

cool/warm-water species such as bass (U.S. EPA, 1995). Studies that better account for 

substitution effects, such as Ahn et al. (2000), indicate a 2-20% drop in benefits of trout fishing 

depending on the projected degrees of temperature increase which ranged from 1°C to 5°C. 

Sea level rise reducing beach area and beach erosion are concerns with climate change that may 

make it difficult to accommodate the increased demand for beach recreation (Yohe et al., 1999). 

In the near term, recreational forests may also be adversely affected by climate change. Although 

forests may slowly migrate northward and into higher elevations, in the short run there may be 

dieback of forests at the current forest edges (as these areas become too hot), resulting in a loss 

of forests for recreation. In the long term, however, several analyses suggest forest species 

composition and migration due as well as net increases in forest area due to carbon dioxide 

fertilization (Joyce et al., 2001; Iverson and Matthews, 2007). Thus, eventually there may be 

resurgence in forest recreation. 

Saunders and Easley (2006) find that natural resources of many western National Parks, National 

Recreation Areas, and National Monuments resources will be adversely affected by climate 

change. The most common adverse effects are reductions in some wildlife species, loss of 

coldwater fishing opportunities and increasing park closures due to wildfire associated with 

stressed and dying forest stands. The text box discusses in more detail potential effects of climate 

change on one park: Rocky Mountain National Park, which has been the subject of both 

ecological and economic analysis. 

4.3.5.1 Economic Studies of Effects of Climate on Recreation 

Changes in economic welfare due to the effects of climate change on non-market resources, such 

as recreation, can be evaluated in several ways. First, since decisions regarding recreational 

activities depend on both direct and indirect effects of climate, changes in human well-being (as 

a result of these changes) will be reflected in changes in visitor use. Social scientists believe 

changes in visitor use are motivated by people “voting with their feet” to maintain or improve 

their well-being. In the face of higher temperatures, people may seek relief, for example, by 

visiting the beach or water skiing at reservoirs more frequently to cool down. Similarly, reduced 

opportunities for recreation due to indirect effects of climate change will also be reflected in 

reduced visitation days. Thus, one metric of effects on human well-being is the change in 

visitation days. 

Second, recreational trips—for example, to reservoirs and beaches—have economic implications 

to the visitor and the economy. Visitors allocate more of their scarce time and household budgets 

to the recreational activities that are now more preferred in a warmer climate. This reflects their 

“willingness to pay” for these recreational activities, which is a monetary measure of the benefits 

they receive from the activity. Numerous economic studies provide estimates of the value of 

changes in diverse recreational activities, using various economic techniques (such as travel 

cost29 analysis and stated preference methods) (see Section 3 of this chapter and the chapter 

Appendix for more information). While these studies typically do not focus directly on climate 

 

29 The travel cost method traces out a demand curve for recreation using travel cost as proxies for the price of 

recreation, along with the corresponding number of trips individual visitors take at these travel costs. From the 

demand curve, the net willingness to pay or consumer surplus is calculated. 

4 -32 
SAP 4.6 Chapter 4: Human Welfare 

change, they can be used to extract values for the types of changes that are projected to be 

associated with climate change. 

 

Third, some people who do not currently visit unique natural environments may value climate 

stabilization policies that preserve these natural environments for future visitation. These people 

have what economists call a value for preserving their option—their ability— to visit the 

environments in the future (Bishop, 1982). This option value is much like purchasing trip 

insurance to guarantee that if one wanted to go in the future, that conditions would be as they are 

today. 

As discussed below, economists have available a number of well-studied and techniques to 

evaluate the impacts of climate change on at least some of the recreational service provided by 

ecosystems. However, only a few studies have looked explicitly at the effects of climate change 

on recreation in the US. More research is needed to understand the linkages between weather and 

recreation, and to extrapolate results to the range of recreational activities throughout the US. 

Change in visitation days. Two studies (Loomis and Crespi, 1999; Mendelsohn and 

Markowski, 1999) have examined the effects of climate on recreational opportunities 

comprehensively for the entire US. These studies both examined the effects of 2.5°C and 5°C 

increases in temperature, along with a 7% increase in precipitation. The studies used similar 

methodologies to estimate visitor days for a range of recreational opportunities. Each study 

looked at slightly different effects, but between them examined a mix of direct and indirect 

climate effects, including direct effects of higher temperatures on golf and beach recreation 

visitor days, and indirect effects of snow cover on skiing. Both studies estimate changes in 

visitation days due to climate change, and then use the results of a number of economic valuation 

studies to place monetary values on the visitation days. The studies find that, as expected, nearterm climate change will increase participation in activities such as water-based recreation, and 

reduce participation in snow sports. 

Table 4.5 presents the results of the two studies. The results suggest that relatively high 

participation recreation activities such as beach and stream recreation gain, and low participation 

activities like snow skiing lose. Although the percentage drop in visitor days of snow sports is 

much larger than the percentage increase in visitor days in water-based recreation, the larger 

number of water-based sports participants more than offsets the loss in the low participation 

snow sports. Thus, on net, there is an overall net gain in visitation associated with the assumed 

increases of 2.5°C in temperature and 7% in precipitation.30

The methods used to forecast visitation were slightly different between the two studies. To 

estimate visitor days for all recreation activities, Mendelsohn and Markowski regressed state 

level data on visitation by recreation activity as a function of land area, water area, population, 

monthly temperature and monthly precipitation. The Loomis and Crespi study used a similar 

 

30 Geographic regions within the U.S. will experience different gains and losses. Currently hot areas with less access 

to water resources (e.g., New Mexico) may suffer net overall reductions in recreation use to due higher heat that 

makes walking, sightseeing, and picnicking less desirable. States with substantial water resources (lakes, seashores) 

may gain visitor days and tourism. Currently cold areas such as the Dakotas and New York may see increases in 

some recreation due to longer summer seasons. 

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SAP 4.6 Chapter 4: Human Welfare 

approach to Mendelsohhn and Markowski for some activities, such as golf. Other forecasting 

techniques were used for other activities; for example, for beach recreation, they used detailed 

data on to individual beaches in the Northeastern, Southern and Western United States to 

estimate three regional regression equations to project beach use, and the response of reservoir 

recreation to climate change was analyzed using visitation at U.S. Army Corps of Engineers 

reservoirs. 

For some of the recreational activities, the Loomis and Crespi study included indirect, as well as 

direct, effects. For example, the reservoir models incorporated climate-induced reductions in 

reservoir surface area besides temperature and precipitation. Similarly, the estimate of visitor 

days for snow skiing used projected changes in the number of days of minimum snow cover to 

adjust skier days proportionally. In some cases, only indirect (supply) effects were included, as 

in the case of stream recreation, water fowl hunting, bird viewing and forest recreation. Since 

these estimates do not include changes in visitation associated with direct effects of climate we 

have less confidence in the accuracy of these results, than we do for reservoir recreation which 

takes into account both demand and supply effects on recreation use. 

Valuation of gains and losses in visitor days. Since different activities may have different 

levels of enjoyment provided to the visitor (and, therefore, different economic values), adding up 

changes in visitation days to produce a “net change” is not an accurate representation of the 

overall change in well-being. The two studies discussed above used net willingness to pay as a 

measure of value of each day of recreation (Section 3 of this chapter provides a discussion of the 

concept of willingness to pay as a common economic measure of changes in welfare). 

To date there have been few original or primary valuation studies of climate change per se on 

recreation; the case study on Rocky Mountain National Park presented below provides one of the 

few examples. Other studies include Scott and Jones (2005), which focused on Banff National 

Park, Scott et al. (2006), which looked at snow skiing, Scott et al. (2007), which focused on 

Waterton National Parks, and Pendleton and Mendelsohn (1998), which estimated values for 

fishing in the northeastern US.31 There have, however, been hundreds of recreation valuation 

studies; the values from these studies (generally travel cost or stated preference) can be applied 

to other applications using a “benefit transfer” approach, and applying average values of 

recreation from previous studies to value their respective visitor days. 

Loomis and Crespi (1999) and Mendelsohn and Markowski (1999) estimate the overall net gain 

in visitor benefits, using the change in visitor days reported in Table 4.5 and estimated values of 

a visitation day reported in the literature. Loomis and Crespi (1999) adopt a disaggregated 

activity approach, and Mendelsohn and Markowski (1999) apply a state level approach.32 Both 

 

31 The three papers by Scott are discussed elsewhere in this paper. Pendleton and Mendelsohn use a random utility 

model of recreational fishing in the northeastern U.S. They find that, while catch rates of rainbow trout would 

decrease, catch rates of other trout and pan fish would increase. On net, recreational fishing benefits (under a climate 

scenario associated with a doubling of atmospheric CO2 concentrations) are reduced in the state of New York, but 

there are offsetting gains in more northern states like Maine. 32 As noted above, Mendelsohn and Markowski (1999) used state level regression modeling to estimate effects on all 

activities. In contrast, Loomis and Crespi (1999), used different regression models and different geographic scales 

for different recreation activities to take advantage of the more micro-level datasets available for beach and reservoir 

recreation. 

4 -34 
SAP 4.6 Chapter 4: Human Welfare 

of these studies find that temperature increases of 5°C and up result in increased benefits. 

However, as noted below, the case study of Rocky Mountain National Park suggests that extreme 

heat is likely (based on the model results) to cause these visitor benefits to decrease at some 

point. 

Visitors are somewhat adaptable to climate change in the recreation activities they choose and 

when they choose them. Thus, recreation represents one situation with opportunities to reduce 

the adverse impacts of climate change, or increase its benefits, via adaptation. As noted by 

Hamilton and Tol (2004), warmer temperatures may shift visitors northward, and up into the 

mountains. Thus currently cool areas (e.g., Maine, Minnesota, Washington) may gain, and warm 

areas (e.g., Florida, Arizona) may lose, tourism. 

Some adaptive responses can be expensive, and may be of limited effectiveness; such as 

snowmaking at night, which is often mentioned as an adaptation for downhill skiing (Irland et 

al., 2001). Other adaptive behavior may include moving some outdoor recreation activities 

indoors. For example, bouldering is now taking place in climbing gyms on artificial climbing 

walls. Running on a treadmill in an air conditioned gym may be a substitute for running out of 

doors for some people, but casual observation suggests that many people prefer to run out doors 

when weather permits. Unless preferences adjust to increased temperatures, there may be a loss 

in human well-being from substituting the treadmill in the air conditioned gym for the out of 

doors. Box 4.2 summarizes a case study of the impacts of climate change on Rocky Mountain 

National Park. 

4.3.6 Amenity Value of Climate 

It is well established that preferences for climate affect where people choose to live and work. 

The desire to live in a mild, sunny climate may reflect health considerations. For example, 

people with chronic obstructive lung disease or angina may wish to avoid cold winters. Warmer 

climates may be more pleasant for persons with arthritis. Climate preferences may also reflect 

the desire to reduce heating and/or cooling costs. Certain climates may be complementary to 

leisure activities. For example, skiers may wish to live in colder climates, sunbathers in warmer 

ones. Or a particular climate may simply make life more enjoyable in the course of everyday life. 

We would also expect based on the evidence that, in addition to preferring certain temperatures 

and more sunshine, people would prefer to reduce the risk of experiencing abrupt climate events 

such as hurricanes and floods. 

While climate itself is not bought and sold in markets, the goods that are integral to location 

decisions—such as housing and jobs—are market goods. Consequently, economists look at 

behavior with regard to location choice (the prices that are paid for houses and the wages that are 

accepted for jobs) in order to determine how large a role climate plays in these decisions and, 

therefore, how valuable different climates are to the general public. The remainder of this section 

discusses methods that have been used to estimate the amenity values people attach to various 

climate attributes, as well as the value they attach to avoiding extreme weather events. 

Unfortunately, few studies have rigorously estimated climate amenity values (e.g., the value of a 

2°C change in mean January temperature) for the United States and then used these values to 

estimate the dollar value of various climate scenarios. 

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SAP 4.6 Chapter 4: Human Welfare 

4.3.6.1 Valuing Climate Amenities 

People’s preferences for climate attributes should be reflected in their location decisions. Other 

things equal, homeowners should be willing to pay more for housing (and so bid up housing 

prices) in more desirable climates, and so property values should be higher in those climates. 

Similarly, workers should be willing to accept lower wages to live in more pleasant climates; if 

climate also affects firms’ costs, however, actual wages may rise or fall due to the interaction 

between firms and workers (Roback, 1982). 

Early attempts to estimate how much consumers will pay for more desirable climates start from 

the view that a good—such as housing or a job—is a bundle of attributes that are valued by the 

homeowner or worker. The price the consumer pays for the good (such as a house) is actually a 

composite of the prices that are implicitly paid for all the attributes of the good. Using a 

statistical technique (known as a hedonic value function), economists can estimate the price of a 

particular attribute, such as climate. The hedonic property value function, thus, describes how 

housing prices vary across cities as a function of housing characteristics and locational amenities, 

such as climate, crime, air quality, or proximity to the ocean. Similarly, the hedonic wage 

function relates the observed wages to job characteristics (such as occupation and industry), 

worker characteristics (such as education and years of experience), and locational amenities. 

The value of locational amenities—i.e., how much individuals are willing to pay for amenities—

can be inferred from these estimated hedonic wage and property value functions. Extracting this 

value, however, assumes that workers and homeowners are mobile, i.e., that they can choose 

where to live fairly freely within the United States. Similarly, it assumes that, in general, 

individuals have moved to where they would like to live (at the moment), so that housing and job 

markets are in what is said to be “equilibrium.” It also assumes that workers and homeowners 

have good information about the location to which they are moving, and that sufficient options 

(in terms of jobs and houses and amenities) are available to them. The estimates of the value of a 

particular amenity—such as climate—will be more accurate the more nearly these assumptions 

are met. 

A number of hedonic wage and property value studies have included climate, among other 

variables, in their analyses: by Hoch and Drake (1974); Cropper and Arriaga-Salinas (1980); 

Cropper (1981); Roback (1982); Smith (1983); Blomquist et al. (1988); Gyourko and Tracy 

(1991). The first four studies estimate only hedonic wage functions, while the last three estimate 

both wage and property value equations. As Moore (1998) and Gyourko and Tracy (1991) note, 

this literature suggests that climate amenities are reflected to a greater extent in wages than in 

property values.33 Roback (1982), Smith (1983), and Blomquist et al. (1988) all find sunshine to 

be capitalized in wages as an amenity, while heating degree days are capitalized as a disamenity 

(Roback, 1982, 1988; Gyourko and Tracy, 1991). 

 

33 The effect of weather variables on property values is mixed, with Blomquist et al. (1988) finding property values 

to be negatively correlated with precipitation, humidity and heating and cooling degree days, but Roback (1982) 

finding property values positively correlated with heating degree days. Gyourko and Tracy (1991) find heating and 

cooling degree days negatively correlated with housing expenditures, but humidity positively correlated. 

4 -36 
SAP 4.6 Chapter 4: Human Welfare 

More recent studies using the hedonic approach include Moore (1998) and Mendelsohn (2001), 

who use their results to estimate the value of mean temperature changes in the United States 

associated with future climate scenarios. Moore uses aggregate wage data for Metropolitan 

Statistical Areas (MSAs) to estimate the responsiveness of wages with respect to climate 

variables for various occupations. Climate is captured by annual temperature, precipitation and 

by the difference between average July and average January temperature. Moore estimates that a 

4.5◦

C increase in mean annual temperature would be worth between $30 and $100 billion 

(1987$) assuming that precipitation and seasonal variation in temperature remain unchanged. 

Mendelsohn (2001) uses county-level data on wages and rents to estimate hedonic wage and 

property value models. Separate equations are estimated for wages in retail, wholesale, service 

and manufacturing jobs. Climate variables, which include average January, April, June and 

October temperature and precipitation, enter each equation in quadratic form. Warmer 

temperatures are generally associated with lower wages and lower rents, although the former 

effect is larger in magnitude. Mendelsohn uses the results of these models to estimate the impact 

of a uniform increase in temperature of 1°C, 2°C and 3.5°C, paired, alternately with an 8% and a 

15% increase in precipitation. The results suggest that warming produces positive benefits in 

every scenario except the 3.5°C temperature change. Averaging across estimates produced by the 

3 models for each of the 6 scenarios suggests annual net benefits (in 1987$) of $25 billion. 

Unfortunately, hedonic wage and property value studies have limitations that have caused them

to be replaced by alternate approaches to analyzing data on location choices. One drawback of 

the hedonic approach is that, as mentioned above, it assumes that national labor and housing 

markets exist and are in equilibrium. As Graves and Mueser (1993) and Greenwood et al. (1991) 

point out, if national markets are not in equilibrium, inferring the value of climate amenities from 

hedonic wage and property value studies can lead to badly biased results. A second problem is 

that variables that are correlated with climate (e.g., the availability of recreational facilities) may 

be difficult to measure; hence, climate variables may pick up their effects. In hedonic property 

value studies, for example, the use of heating and cooling degree days to measure climate 

amenities is problematic because their coefficients may capture differences in construction and 

energy costs as well as climate amenities per se. A related problem in hedonic wage equations is 

that more able workers may locate in areas with more desirable climates. If ability is not 

adequately captured in the hedonic wage equation, the coefficients of climate amenities will 

reflect worker ability as well as the value of climate. 

Cragg and Kahn (1997) were the first to relax the national land and labor market equilibrium 

assumption by estimating a discrete location choice model. Using Census data, they model the 

location decisions of people in the United States who moved between 1975 and 1980. Movers 

compare the utility they would receive from living in different states—which depends on the 

wage they would earn and on the cost of housing, as well as on climate amenities—and are 

assumed to choose the state that yields the highest utility. This allows Cragg and Kahn to 

estimate the parameters of individuals’ utility functions and thus infer the rate at which they will 

trade income for climate amenities. 

The drawback of this study is that it estimates the preferences of movers, who may differ from 

the general population. An alternate approach (Bayer et al., 2006; Bayer and Timmins, 2005) is 

4 -37 
SAP 4.6 Chapter 4: Human Welfare 

to acknowledge that moving is costly and to explain the location decisions of all households, 

assuming that all households are in equilibrium, given moving costs. Unfortunately, the discrete 

choice literature has yet to provide reliable estimates of the value of climate amenities in the 

United States. 

4.3.6.2 Valuing Hurricanes, Floods, and Extreme Weather Events 

It is sometimes suggested that the value people place on avoiding extreme weather events can be 

measured by the damages that such events cause, or by the premiums that people pay for flood or 

disaster insurance. Ex post losses associated with extreme weather events represent a lower 

bound to the value people place on avoiding these events, as long as people are risk averse. It is 

also the case that people can purchase insurance only against the monetary losses associated with 

floods and hurricanes; hence, insurance premiums will not capture the entire value placed on 

avoiding these events. 

The value of avoiding extreme weather events should be reflected in property values, assuming 

that people are informed about risks: houses in an area with high probability of hurricane damage 

should sell for less than comparable houses in an area with a lower chance of hurricane damage, 

holding other amenities constant. To estimate the value of avoiding these events correctly is, 

however, tricky; it can be difficult, for example, to disentangle hurricane risk (a negative effect) 

from proximity to the coast (an amenity). 

Recent studies use natural experiments to determine the value of avoiding hurricanes and floods. 

Hallstrom and Smith (2005) use property value data before and after hurricane Andrew in Lee 

County, Florida, a county that did not suffer damage from the hurricane, to determine the impact 

of people’s perceptions of hurricane risk on property values. They find that property values in 

special flood hazard areas of Lee County declined by 19% after hurricane Andrew. The 

magnitude of this decline is significant, and agrees with Bin and Polasky (2004). Bin and 

Polasky find that housing values in a flood plain in North Carolina declined significantly after 

hurricane Floyd, compared to houses not at risk. For the average house, the decline in price 

exceeded the present value of premiums for flood insurance, suggesting that the latter are, 

indeed, a lower bound to the value of avoiding floods. 

4.4 Conclusions 

The study of the impacts of climate change on human welfare, well-being, and quality of life, is 

still developing. Many studies of impacts on particular sectors—such as health or agriculture—

discuss, and in some cases quantify, effects that have clear implications for welfare. Studies also 

hint at changes that are perhaps less obvious, but also have welfare implications (such as changes 

in outdoor activity levels and how much time is spent indoors) and point also to effects with far 

more dramatic consequences (such as breakdown in public services and infrastructure associated 

with possible extreme events of the magnitude of Katrina). Adaptation, too, has welfare 

implications that studies do not always point out, such as the costs (financial and psychological) 

to the individual of changing behavior. 

To our knowledge, no study has made a systematic survey of the myriad welfare implications of 

climate change, much less attempted to quantify—nor yet to aggregate—them. An almost 

4 -38 
SAP 4.6 Chapter 4: Human Welfare 

bewildering choice of typologies is available for categorizing effects on quality of life, wellbeing, or human welfare. The social science and planning literatures provide not only a range of 

typologies, but also an array of metrics that could be used to measure life quality. 

This chapter explores one commonly used method: the social indicators approach. This approach 

generally divides life quality effects into broad categories, such as economic conditions or 

human health, and then identifies subcategories of important effects. 

Most of the measures of well-being—including the social indicators approach—focus on 

individual measures of well-being, although measured at the society level. There is, however, 

another dimension to well-being—community welfare. Communities represent networks of 

households, businesses, physical structures, and institutions and so reflect the interdependencies 

and complex reality of human systems. Understanding how climate impacts communities, and 

how communities are vulnerable—or can be made more resilient—in the face of climate change, 

is an important component of understanding well-being and quality of life. 

Economics offers one alternative to address the diversity of impacts: valuing welfare impacts in 

monetary terms, which can then be summed. Estimating value, however, requires completing a 

series of links—from projected climate change to quantitative measures of effects on 

commodities, services, or conditions that are linked to well-being, and then valuing those effects 

using economic techniques. 

Regardless of the framework, estimating impacts on human well-being involves numerous and 

diverse effects. This poses several critical difficulties: 

 The large number of effects makes the task of linking impacts to climate change—

whether qualitatively or quantitatively—difficult. 

 The interdependence of physical and human systems further complicates the process of 

quantification—both for community effects, and also for ecosystems, raising doubts 

about a piecemeal approach to estimation. 

 The diversity of effects raises questions of how to aggregate effects in order to develop a 

composite measure of well-being or other metrics that can be used for policy purposes. 

4.5 Expanding the Knowledge Base 

Despite the potential for impacts on human well-being, little research focuses directly on 

understanding the relationship between well-being and climate change. Completely cataloging 

the effects of global change on human well-being or welfare would be an immense undertaking, 

and no well-accepted structure for doing so has been developed and applied. Moreover, 

identifying the potentially lengthy list of climate-related changes in lifestyle, as well as in other, 

more tangible, features of well-being (such as income), is itself a daunting task—and may 

includes changes that are not easily captured by objective measures of well-being or quality of 

life. 

This chapter has looked at the climate impacts and economics literature in four areas of welfare 

effects—human health, ecosystems, recreation, and climate amenities. For each of the non4 -39 
SAP 4.6 Chapter 4: Human Welfare 

market effects analyzed here, significant data gaps exist at each of the steps necessary to provide 

monetized values of climate impacts. Although the economics literature for only a few areas of 

effects is examined, it is probable that similar information gaps exist for the valuation of other 

impacts of climate change, particularly those that involve non-market effects (see Table 4.1). In 

addition, economic welfare—as with any other aggregative approach—does not adequately 

address the question of how to deal with effects which may not be amenable to valuation or with 

interdependencies among effects and systems. 

Developing an understanding of the impacts of climate change on human welfare may require 

taking the following steps: 

 Develop a framework for addressing individual and community welfare and well-being, 

including defining welfare/well-being for climate analysis and systematically 

categorizing and identifying impacts on welfare/well-being 

 Identify priority categories for data collection and research, in order to establish and 

quantify the linkage from climate to welfare effects 

 Decide which metrics should be used for these categories; more generally, which 

components of welfare/well-being should be measured in natural or physical units, and 

which should be monetized 

 Investigate methods by which diverse metrics can be aggregated into a synthetic indicator 

(e.g., vulnerability to climate change impacts, including drought, sea level rise, etc.), or at 

least weighted and compared in policy decisions where aggregation is impossible 

 Develop an approach for addressing those welfare effects that are difficult to look at in a 

piecemeal way, such as welfare changes on communities or ecosystems. 

 Identify appropriate top-down and bottom-up approaches for estimating impacts and 

value (whether economic or otherwise) of the most critical welfare categories. 

 Identify situations in which evaluation following the above steps is likely to be 

prohibitively difficult, and determining alternative methods for approaching the topic of 

the impact of global change on well-being. 

Together, these steps should enable researchers to make progress towards promoting the 

consistency and coordination in analyses of welfare/well-being that will facilitate developing the 

body of research necessary to analyze impacts on human welfare, well-being, and quality of life. 

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SAP 4.6 Chapter 4: Human Welfare 

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4.7 Appendix 1: 

Chapter 4: Human Welfare 

Economic Valuation: An Introduction to Techniques and Challenges 

Assessments of the benefits and costs, whether explicit or tacit, underlie all discussion and 

debates over alternative actions regarding climate change. These assessments are frequently used 

to inform such questions as: What actions are justified to ease adaptation to changing climate? 

Or how much are we willing to pay to reduce emissions? (Jacoby, 2004). Ideally, such analyses 

would be undertaken with complete and reliable information on benefits, converted into a 

common unit, commensurable with costs and with each other (Jacoby, 2004). In reality, 

however, while many impacts can be valued, some linkages from climate change to welfare 

effects are difficult to quantify, much less value. This appendix describes the steps in developing 

a benefits estimate, and the tools that economists have available for monetizing benefits. It also 

briefly discusses some of the challenges in monetizing benefits, and weaknesses in the approach. 

Estimating the Effects of Climate Change 

The process of estimating the effects of climate change, including effects on human welfare, 

involves up to four steps, illustrated in Figure 4A.1. Moving down from the top of Figure 4A.1, 

the gray area occupies a larger portion of each box, indicating (in rough terms) that at each stage 

it is more and more difficult to develop quantified, rather than qualitative, results. The first step 

is to estimate the change in relevant measures of climate, including temperature, precipitation, 

sea-level rise, and the frequency and severity of extreme events. This step is usually 

accomplished by atmospheric scientists - some form of global circulation model (GCM) is 

typically deployed. Some analyses stop after this step. 

The second step involves estimating the physical effects of those changes in climate in terms of 

qualitative changes in human and natural systems. These might include changes in ecosystem 

structure and function, human exposures to heat stress, changes in the geographic range of 

disease vectors, melting of snow on ski slopes, or flooding of coastal areas. A wide range of 

disciplines might be involved in carrying out those analyses, deploying an equally wide range of 

tools. Many analyses are complete once this step is completed - for example, we may be unable 

to say anything more than that increases in precipitation will change an ecosystem's function. 

The third step involves translating the physical effects of changes in climate into metrics 

indicating quantitative impacts. If the ultimate goal is monetization, ideally these measures 

should be amenable to valuation. Examples include quantifying the number and location of 

properties that are vulnerable to floods, estimating the number of individuals exposed to and 

sensitive to heat stress, or estimating the effect of diminished migratory bird populations on birdwatching participation rates. Many analyses that reach this step in the process, but not all, also 

proceed on to the fourth step. 

The fourth step involves valuing or monetizing the changes. The simplest approach would be to 

apply a unit valuation approach; for example, the cost of treating a nonfatal case of heat stress or 

malaria attributable to climate change is a first approximation of the value of avoiding that case 

altogether. In many contexts, however, unit values can misrepresent the true marginal economic 

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SAP 4.6 Chapter 4: Human Welfare 

impact of these changes. For example, if climate change reduces the length of the ski season, 

individuals could engage in another recreational activity, such as golf. Whether they might prefer 

skiing to golf at that time and location is something economists might try to measure. 

Figure 4A.1 Estimating the Effects of Climate Change 

Step 1: Estimate Climate Change 

(magnitude & timing) 

• Temperature 

• Precipitation 

• Sea-level rise 

• Extreme weather events 

Non-quantified 

physical effects 

Impacts that can 

not be quantified 

Impacts that can not be 

monetized 

Step 2: Estimate Physical Effects 

(spatial & temporal distribution) 

• Human exposure to heat stress 

• Change in ecosystem structure and 

function 

• Arial extent of flooding 

• Timing of snow melt 

• Many more... 

Step 3: Estimate Quantitative Impacts 

• Number of sick individuals 

• Changes in recreational participation rates 

• Property losses 

• Change in species populations 

• Many more... 

Step 4: Value or “Monetize” Effects 

• Lost property value 

• Cost of illness 

• Loss in recreational “use value” 

• Loss of human welfare for other effects 

This step-by-step linear approach to effects estimation is sometimes called the "damage 

function" approach. One practical advantage of the damage function approach is the separation 

of disciplines—scientists can complete their work in steps 1 and 2, and sometimes in step 3, and 

then economists do their work in step 4. The linear process can work well in cases where 

individuals respond and change their behavior in response to changes in their environment, 

without any "feedback" loop. 

The linear approach is not always appropriate, however. A damage function approach might 

imply that we look at effects of climate on human health as separate and independent from 

effects on ecology and recreation, but at some level they are inter-related, as health care and 

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SAP 4.6 Chapter 4: Human Welfare 

recreation both require resources in the form of income. In addition, responding to heat stress by 

installing air conditioning leads to higher energy demand, which in turn may increase greenhouse 

gas emissions and therefore contribute to further climate change. Recent research suggests that 

the damage function approach, under some conditions, may be both overly simplistic (Freeman, 

2003) and subject to serious errors (Strzepek et al., 1999; Strzepek and Smith, 1995). 

Monetizing and Valuing Non-Market Goods 

Economists have developed a suite of methods to estimate willingness to pay for non-market 

goods (see text for a discussion of the market vs. non-market distinction). These methods can be 

grouped into two broad categories, based largely on the source of the data: revealed preference 

and stated preference approaches (Freeman, 2003; U.S. EPA, 2000). Revealed preference, 

sometimes referred to as the indirect valuation approach, involves inferring the value of a nonmarket good using data from market transactions. For example, a lake may be valued for its 

ability to provide a good fishing experience. This value can be estimated by the time and money 

expended by the angler to fish at that particular site, relative to all other possible fishing sites. Or, 

the amenity value of a coastal property that is protected from storm damage (by a dune, perhaps) 

can be estimated by comparing the price of that property to other properties similar in every way 

but the enhanced storm protection. 

Stated And Revealed Preference Approaches 

Accurate measurement of the non-market amenity of interest, in a manner that is not inconsistent 

with the way market participants perceive the amenity, is critical to a robust estimate of value. 

Revealed preference approaches include recreational demand models, which estimate the value 

of recreational amenities through time and money expenditures to enjoy recreation; hedonic 

wage and hedonic property value models, which attempt to isolate the value of particular 

amenities of property and jobs not themselves directly traded in the marketplace based on their 

price or wage outcomes; and averting behavior models, which estimate the value of time or 

money expended to avert a particular bad outcome as a measure of its negative effect on welfare. 

Stated preference approaches, sometimes referred to as direct valuation approaches, are survey 

methods that estimate the value individuals place on particular non-market goods based on 

choices they make in hypothetical markets.34 The earliest stated preference studies involved 

simply asking individuals what they would be willing to pay for a particular non-market good. 

The best studies involve great care in constructing a credible, though still hypothetical, trade-off 

between money and the non-market good of interest to discern individual preferences for that 

good and hence, willingness to pay (WTP). For example, economists might construct a 

hypothetical choice between multiple housing locations, each of which differs along the 

dimensions of price and health risk. Repeated choice experiments of this type ultimately map out 

the individual’s tradeoff between money and the non-market good. The major challenges in 

stated preference methods involve study design, particularly the construction of a reasonable and 

credible market for the good, and estimation of a valuation function from the response data. 

 

34 The contingent valuation method (CVM), or a modern variants, a stated choice model (SCM), are forms of the 

stated preference methods. 

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SAP 4.6 Chapter 4: Human Welfare 

In theory, if individuals understand the full implications of their market choices, in real or 

constructed markets, then both revealed and stated preference approaches are capable of 

providing robust estimates of the total value of non-market goods. When considering the 

complex and multidimensional implications of climate change in the application of revealed and 

stated preference approaches, it can be extraordinarily challenging to ensure that individuals are 

sufficiently informed that their observed or stated choices truly reflect their preferences for a 

particular outcome. As a result, these methods are most often applied to a narrowly defined nonmarket good, rather than to a complex bundle of non-market goods that might involve multiple 

tradeoffs and synergistic or antagonistic effects that would be difficult to disentangle. 

In addition to market or non-market goods that reflect some use of the environment, value can 

arise even if a good or service is not explicitly consumed, or even experienced. For example, 

very few individuals would value a polar bear for its ability to provide sustenance - those who do 

might not express that value through a direct market for polar bear meat, but by hunting for the 

bear. Whether through a market or in a non-market activity, those individuals have value for a 

consumptive use—once enjoyed, that good is no longer available to others to enjoy. In addition 

to the consumptive users, a small but somewhat larger number of individuals might travel to the 

Arctic to see a polar bear in its natural environment. These individuals might express a value for 

polar bears, and their "use" of the bear is non-consumptive, but in some sense it does nonetheless 

affect others’ ability to view the bear—if too many individuals attempt to view the bears, the 

congestion might cause the bears to become frightened or, worse, domesticated, diminishing the 

experience of viewing them. 

A third, perhaps much larger group of individuals will never travel to see a polar bear in the 

flesh. But many individuals in this group would experience some diminishment in their overall 

quality of life if they knew that polar bears had become extinct. This concept is called "non-use 

value". Although there are several categories of non-use value - some individuals may wish to 

preserve the future option to visit the Arctic and see a bear, others to bequeath a world with polar 

bears to future generations, and others might value the mere existence of the bears out of a sense 

of environmental stewardship. While not all economists agree that non-use values ought to be 

relevant to policy decisions (Diamond and Hausman, 1993), there is broad agreement that they 

are difficult to measure, because the expression of non-use values does not result in measurable 

economic behavior (that is, there is no "use" expressed). Those that recognize non-use values 

acknowledge that they are likely to be of greatest consequence where a resource has a 

uniqueness or “specialness” and loss or injury is irreversible, for example in the global or local 

extinction of a species, or the distribution of a unique ecological resource (Freeman, 2003). 

Other Methods of Monetizing 

Analysts can employ other non-market valuation methods: avoided cost or replacement cost, and 

input value estimates. These methods do not measure willingness to pay as defined in welfare 

economic terms, but because the methods are relatively straightforward to apply and the results 

often have a known relationship to willingness to pay, they provide insights into non-market 

values. This chapter focuses on willingness to pay measures, but recognizes that alternative 

methods may provide insights and sometimes be more manageable (or appropriate) to estimate a 

particular non-market value, given data constraints and the limitations imposed by available 

methods. 

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Cost of illness studies estimate the change in health expenditures resulting from the change in 

incidence of a given illness. Direct costs of illness include costs for hospitalization, doctors’ fees, 

and medicine, among others. Indirect costs of illness include effects such as lost work and leisure 

time. Complete cost of illness estimates reflect both direct and indirect costs. Even the most 

complete cost of illness estimates, however, typically underestimate willingness to pay to avoid 

incidence of illness, because they ignore the loss of welfare associated with pain and suffering 

and may not reflect costs of averting behaviors the individuals have taken to avoid the illness. 

Some studies suggest that the difference between cost of illness and willingness to pay can be 

large, but the difference varies greatly across health effects and individuals (U.S. EPA, 2000). 

Replacement cost studies approach non-market values by estimating the cost to replace the 

services provided to individuals by the non-market good. For example, healthy coastal wetlands 

may provide a wide range of services to individuals who live near them; they may filter 

pollutants present in water; absorb water in times of flood; act as a buffer to protect properties 

from storm surges; provide nursery habitat for recreational and commercial fish; and provide 

amenities in the form of opportunities to view wildlife. A replacement cost approach would 

estimate the value of these services by estimating market costs for treating contaminants, 

containing floods, providing fish from hatcheries, or perhaps restoring an impaired wetland to 

health. 

The replacement cost approach is limited in three important ways: 1) the cost of replacing a 

resource does not necessarily bear any relation to the welfare enhancing effect of the resource; 2) 

as resources grow scarce, we would expect their value would be underestimated by an average 

replacement cost; 3) Complete replacement of ecological systems and services may be highly 

problematic. Replacement cost studies are most informative in those conditions where loss of the 

resource would certainly and without exception trigger the incidence of replacement costs - in 

reality, those conditions are not as common as they might seem, because in most cases there are 

readily available substitutes for those services, even if accessing them involves incurring some 

transition costs. 

Finally, value can also be calculated using the contribution of the resource as an input into a 

productive process. This approach can be used for both market and non-market inputs. For 

example, it can be used to estimate the value of fertilizer, as well as water or soil, in farm output 

and profits. An ecosystem’s service input into a productive process could, in theory, be used in 

this same way. 

Issues in Valuation and Aggregation 

The topic of issues in valuation is far larger than can be covered here. We focus only on 

identifying in a superficial way a few of the most important issues, in the context of climate 

change. 

By virtue of the simple process of aggregation, the economic approach creates some difficulties. 

These difficulties are not specific to the economic approach, however; any method of 

aggregation would face the same limitations. 

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SAP 4.6 Chapter 4: Human Welfare 

 Aggregation, by balancing out effects to produce a “net” effect, masks the positive and 

negative effects that comprise net effects, hides inequities in the distribution of impacts, 

or large negative impacts that fall on particular regions or vulnerable populations. 

 Any method of aggregation must make an explicit assumption about how to aggregate 

over time, i.e., whether to weight future benefits the same as current benefits (economic 

analyses generally discount the future, i.e., weight it less heavily in decision making than 

the present, for a number of reasons) 

 The method of putting diverse impacts on the same yardstick ignores differences in how 

we may wish to treat these impacts from a policy perspective, and assumes that all 

impacts are equally certain or uncertain, despite differences in estimation and valuation 

methods. These differences may be particularly apparent, for example, for non-market 

and market goods. 

Several potential criticisms of the economic approach in the context of climate change relate 

more directly to how economists approach the task of valuation. One issue is the assumption of 

stability of preferences over time. Economic studies conducted today, whether revealed or stated 

preference, reflect the actions and preferences of individuals today, expressed in today’s 

economic, social, and technological context. For an issue such as climate change, however, 

impacts may occur decades or centuries hence. The valuation of impacts that occur in the future 

should depend on preferences in the future. For the most part, however, while there are some 

rudimentary ways in which economists model changes in technology or income, there is no 

satisfactory means of modeling changes in preferences over time. 

A second issue is the treatment of uncertainty. Economic analysis under conditions of imperfect 

information and uncertainty is possible, but is one of the most difficult undertakings in 

economics. While some climate change impacts may be relatively straight-forward, valuation of 

many climate change impacts requires analysis and use of welfare measures that incorporate 

uncertainty. When imperfect information prevails, the valuation measure must factor in errors 

that arise because of it, and when risk or uncertainty prevail, the most commonly used valuation 

measure is the option price. Two related concepts are option value, and expected consumer’s 

surplus. All three concepts are more complicated than the discussion here can do justice to, but 

briefly: 

 Expected consumer’s surplus, E[CS] is just consumer’s surplus (CS), or value in welfare 

terms, weighted by the probabilities of outcomes that yield CS. For example, if a hiker 

gets $5 of CS per year in a “dry” forest and $10 in a wet forest (one that is greener) and 

the probability of the forest being dry is 0.40 and of it being wet is 0.60, then the E[CS] = 

0.40 X $5 + 0.60 X $10. Expected consumer’s surplus is really an ex-post concept, 

because we must know CS in each state after it occurs. 

 Option price (OP) is the WTP that balances expected utility (utility weighted by the 

probabilities of outcomes) with and without some change. It is a measure of WTP the 

individual must express before outcomes can be known with certainty, i.e., a true ex ante 

welfare measure. For example, the hiker might be willing to pay $8 per year to balance 

her expected utility with conditions being wet, versus conditions being dry. The $8 might 

be a payment to support a reduction in dryness otherwise due to climate change. 

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SAP 4.6 Chapter 4: Human Welfare 

 Option value (OV) is the difference between OP and E[CS]. A related concept is called 

quasi-option value and pertains to the value of waiting to get more information. 

A third issue concerns behavioral paradoxes. Most economic analyses, particularly if they 

involve uncertain or risky outcomes, require rationality in the expression of preferences. Such 

basic axioms as treating gains and losses equally, reacting to a series of small incremental gains 

with equal strength to a single large gain of the same aggregate magnitude, and viewing gains 

and losses from an absolute rather than relative or positional scale are particularly important to 

studies that rely on expected utility theory - that individuals gain and lose welfare in proportion 

to the product of the likelihood of the gain or loss and its magnitude. Several social and 

psychological science studies, however, suggest that under many conditions individuals do not 

behave in a manner consistent with this definition of rationality. For example, prospect theory, 

often credited as resulting from the work of Daniel Kahneman and Amos Tversky, suggests that 

behavior under risk or uncertainty is better explained both by reference to a status quo reference 

point and acknowledgement of unequal treatment of risk aversion when considering losses and 

gains, even when it can be shown that a different behavior would certainly make the individual 

better off. 

Finally, the issue of perspective—“whose lens are we looking through"—is critical to welfare 

analysis, particularly economic welfare. In health policy, for example, thinking about whether it 

is worthwhile to invest in mosquito netting to control malaria depends on whether you are at 

CDC, are a provider of health insurance, or are an individual in a place where malaria risk is 

high. In general, the perspective of valuation focuses on the valuation of individuals who are 

directly affected, and who are living today. The perspectives of public decision makers may be 

somewhat different from those of individuals, since they will take into account social and 

community consequences, as well as individual consequences. 

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4.8 Boxes 

Box 4.1 Effects of Climate Change on Selected US Ecosystems 

At their most extreme, community changes could result in the loss of entire habitats valued by the general 

public. For example, sea level rise puts much of the freshwater wetland that comprises Florida Everglades 

National Park at risk (Glick and Clough, 2006). Even relatively modest sea level rise projections could result in 

the conversion of much of this low-lying area to brackish or intertidal marine and mangrove habitats. Another 

such extreme example is alpine tundra habitat in mountain ranges in the contiguous states. Since tundra lies at 

the highest elevations, there is little or no opportunity for the plants and animals that comprise this ecosystem 

to respond to increasing temperatures by moving upward. Thus, one of the probable effects of climate change 

will be the further fragmentation and loss of this unique habitat (VEMAP, 1995; Root et al., 2003; Lenihan et 

al., 2006). 

California already reports an example of how climate change might modify major marine ecological 

communities. Over the final four decades of the 20th century the average annual ocean surface temperature off 

the California coast warmed by approximately 1.5o

C (Holbrook et al., 1997). Sagarin et al. (1999) found that 

the intertidal invertebrate community at Monterey has changed since first it was characterized in the 1930s. 

Many of the coolwater species have retracted their ranges northward, to be replaced by southern warm water 

species. The community that exists there now is markedly different in its make-up from that which existed 

prior to warming of the coastal California Current.

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SAP 4.6 Chapter 4: Human Welfare 

4 -65 

Box 4.2 Case Study of the Effects of Climate Change on Rocky Mountain National Park 

One of the National Parks most closely studied to determine the net effect of direct and indirect 

effect of climate change on visitation, visitor benefits and tourism employment is Rocky 

Mountain National Park (RMNP) in Colorado. This alpine national park is located at elevations 

ranging from 7,000 to 14,000 feet above sea level. It is known for elk viewing, hiking, tundra 

flowers, snowcapped peaks, and one of Colorado’s most visible and recognizable 14,000 foot 

peaks, Longs Peak. 

Loomis and Richardson (2006) compared two approaches to estimating the effect of climate 

change on visitation and employment in RMNP. The first approach examined variations in 

monthly visitation in response to historic variations in temperature. The results of this first 

approach showed a statistically significant positive effect of temperature on visitation (see 

Loomis and Richardson (2006) for more details). However, increased visitation slowed as 

temperatures got hotter and hotter, and visitation even declined during one summer of very high 

temperatures (60 days over 80°F) by 7.5%. 

The second approach used a survey that portrayed the direct effects (e.g., temperature) and 

indirect effects (e.g., changes in elk and ptarmigan (an alpine bird), or percent of the park in 

tundra). Visitors were then asked to indicate if they would change their visits to RMNP or length 

of stay in the park. The surveys used three climate change scenarios, one produced by the 

Canadian Climate Center (CCC) indicating a 4°F increase in temperature by 2020, a Hadley 

climate scenario that forecasted a 2°F temperature increase by 2020, and an extreme heat 

scenario designed to capture very hot future conditions (50 days with temperatures above 80°F, 

as compared to 3 days currently). All climate change scenarios were used with wildlife models to 

estimate the increase in elk populations and decrease in ptarmigan populations. The extreme heat 

survey found similar results to that of the monthly visitation model. 

Table 4.6 shows the results of the CCC, Hadley, and Extreme Heat temperature scenarios on 

visitation, visitor benefits and tourism employment as compared to current conditions. As 

indicated in the table, applying visitor survey estimates of visitation change yields a 13.6% 

increase with CCC and 9.9% increase with Hadley. Loomis and Richardson also report that 

applying the historic visitation patterns to the same scenarios yields an 11.6% increase in 

visitation with CCC and 6.8% with Hadley. Not only is there fairly good agreement between the 

two methods, but the warmer CCC climate change scenario produces larger increases in 

visitation. In the extreme heat scenario, however, visitations declines from current conditions. 
SAP 4.6 Chapter 

4 -66 

4.9 Tables Table 4.1 Categorization of Well-Being

Category of Wellbeing Description and Rationale Components / Indicators of Well-being Illustrative Metrics / Measures of Well- being 

Economic 

conditions 

The economy supports a mix of activities: opportunities for employment, a strong consumer market, funding for needed public services, and a high standard of living shared by citizens.

 Income and production  Economic standard of living, e.g., wealth and 

income, cost of living, poverty 

 Economic development, e.g., business and 

enterprise, employment 

 Availability of affordable housing 

 Equity in the distribution of income 

 Gross Domestic Product (GDP) 

 Wage rates (e.g., persons at minimum wage) 

 Employment rates 

 Business startups and job creation  Housing prices  Dependence on public assistance 

 Families/children living in poverty  Utility costs, gasoline prices, and other prices 

Natural resources, 

environment, and 

amenities 

Resources enhance the quality of life of citizens; pollution and other negative environmental effects are kept below levels harmful to ecosystems, human health, and other quality of life considerations; and natural beauty and aesthetics are enhanced. 

 Air, water, and land pollution  Recreational opportunities  Water supply and quality  Natural hazards and risks  Ecosystem condition and services  Biodiversity  Direct climate amenity effects 

 Air and water quality indices 

 Waste recycling rates 

 Acreage, visitation, funding of recreational an

protected/preserved areas 

 Water consumption and levels  Deaths, injuries, and property loss due to 

natural hazards 

 Endangered and threatened species 

Human health 

Health care institutions provide medical and preventive health-care services with excellence, citizens have access to services regardless of financial means, and physical and mental health is generally high. 

 Mortality risks  Morbidity and risk of illness 

 Quality and accessibility of health care 

 Health status of vulnerable populations  Prenatal and childhood health  Psychological and emotional health 

 Deaths from various causes (suicide, cancer, 

accidents, heart disease) 

 Life expectancy at birth  Health insurance coverage  Hospital services and costs  Infant mortality and care of elderly  Subjective measure of health status 

Public and private 

infrastructure 

Transportation and communication infrastructure enable citizens to move around efficiently and communicate reliably. 

 Affordable, and accessible public transit  Adequate road, air, and rail infrastructure  Reliable communication systems 

 Waste management and sewerage  Maintained and available public and private 

facilities 

 Power generation 

 Mass transit use and commute times 

 Rail lines, and airport use and capacity 

 Telephones, newspapers, and internet 

 Waste tonnage and sewerage safety  Congestion and commute to work  Transportation accident rates 

 Noise pollution 

Government and 

public safety 

Governments are led by competent and responsive officials, who provide public services effectively and equitably, such as order and public safety; citizens are well-informed and participate in civic activities. 

 Electoral participation  Civic engagement

 Equity and opportunity  Municipal budgets and finance 

 Public safety 

 Emergency services

 Voter registration, turnout, approval  Civic organizations membership rates 

 Availability of public assistance programs 

 Debt, deficits, taxation, and spending 

 Crime rates and victimization  Emergency first-responders per capita 

Social and cultural 

resources 

Social institutions provide services to those in need, support philanthropy, volunteerism, patronage of arts and leisure activities, and social interactions characterized by equality of opportunity and social harmony.

 Volunteerism  Culture, arts, entertainment, and leisure 

activities 

 Education and human capital services  Social harmony  Family and friendship networks 

 Donations of time, money, and effort  Sports participation, library circulation, and 

support for the arts 

 Graduation rates and school quality  Hate, prejudice, and homelessness  Divorce rates, social supports 

* The focus is on negative impacts as potentially more troubling for quality of life; there are also positive impacts and opportuncategories 
SAP 4.6 Chapter 4: Human Welfare 

Table 4.2 An illustration of Possible Effects of Climate Change on Fishery Resources

Linkages/Pathways Category of Welfare Effect Possible Metrics 

Fishery resource declines as climate 

changes 

Natural resources, environment, and 

amenities Fish populations 

Recreational opportunities decline Natural resources, environment, and 

amenities Fish catch, visitation days 

Related species and habitats are 

affected 

Natural resources, environment, and 

amenities Species number and diversity 

Employment and wages in resourcebased jobs (including recreation) fall 

as resources decline 

Economic conditions Number of jobs, unemployment 

rate, wages 

Incomes fall as jobs are lost Economic conditions Per capita income 

More children live in poverty as jobs 

are lost and incomes fall Economic conditions Families, children below poverty level 

Access to health care that is tied to 

jobs and income falls Human Health Households without health insurance increase 

Increased mortality and morbidity as 

a result of reduced health care Human Health Disease and death rates increase 

Working age population 

decreases Lack of jobs results in out-migration Economic conditions 

Fewer new residents attracted, 

because of reduced jobs and 

amenities (recreation) 

Social and cultural resources Population growth rate slows 

Drop in volunteerism civic 

participation, completion of high 

school 

Less incentive/drive to participate in 

community activities Social and cultural resources 

4 -67 
SAP 4.6 Chapter 4: Human Welfare 

Table 4.3 Techniques to Value Health Effects Associated with Climate Change

Health Effect Economic Valuation Tools 

Premature mortality (associated with 

temperature changes, extreme 

weather events and air pollution 

effects) 

Use of revealed preference techniques to value changes in risk of death (e.g., compensating wage 

studies). 

Use of stated preference studies to value changes in risk of death. 

Use of foregone earnings as a lower bound estimate to the value of premature mortality. 

Exacerbation of cardiovascular and 

respiratory morbidity; morbidity 

associated with water-borne or 

vector-borne disease 

Use of stated preference methods to elicit WTP to avoid illness (e.g., asthma attacks) or risk of 

illness (heart attack risk) or injury. 

Estimation of medical costs and productivity losses (known as the cost-of-illness (COI)) as a lower 

bound estimate of the value of avoiding illness. 

Injuries associated with extreme 

weather events 

Use of stated preference methods to elicit WTP. 

Use of compensating wage studies that value risk of injury. 

Use of COI as a lower bound estimate. 

Impacts of climate change on 

physical functioning; sub-clinical 

effects 

Use of stated preference methods to estimate WTP to avoid functional limitation. 

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SAP 4.6 Chapter 4: Human Welfare 

Table 4.4 Examples of Ecosystem Services Important to Human Welfare*

Service Category Components of Service Illustration of Service 

Provisioning services 

Food 

Fiber 

Fresh water 

Genetic Resources 

Pharmaceuticals 

Harvestable fish, wildlife and plants 

Timber, hemp, cotton 

Water for drinking, hydroelectricity generation, and 

irrigation 

Regulating services 

Air quality regulation 

Erosion regulation 

Water purification 

Pest control 

Crop pollination 

Climate and water supply regulation 

Protection from natural hazards 

Local and global amelioration of extremes 

Removal of contaminants by wetlands 

Removal of timber pests by birds 

Pollination of orchards by flying insects 

Support services 

Primary production 

Soil formation 

Photosynthesis 

Nutrient and water cycling 

Conversion of solar energy to plant material 

Conversion of geological materials to soil by 

addition of organic material and bacterial activity 

Cultural services 

Recreation/tourism 

Aesthetic values 

Spiritual/religious values 

Cultural heritage 

Natural sites for “green” tourism/recreation/nature 

viewing 

Existence value of rainforests and charismatic 

species, “holy” or “spiritual” natural sites 

*Based on a classification system developed for the Millennium Ecosystem Assessment (MA, 2005) 

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SAP 4.6 Chapter 4: Human Welfare 

Table 4.5 Comparison of Changes in US Visitor Days

Activity Loomis and Crespi (1999) Mendelsohn and Markowski (1999) 

Boating 9.2% 36.1% 

Camping -2.0% -12.7% 

Fishing 3.5% 39.0% 

Golf 13.6% 4.0% 

Hunting -1.2% no change 

Snow Skiing -52.0% -39.0% 

Wildlife Viewing -0.1% -38.4% 

Beach Recreation 14.1% not estimated 

Stream Recreation 3.4% included in boating 

Gain in Visitor Benefits 

(in Billions) $2.74 $2.80 

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SAP 4.6 Chapter 4: Human Welfare 

Table 4.6 Change in Visits, Jobs and Visitor Benefits with Three Climate Change Scenarios

Annual Tourism Visitor

Climate Scenario Visits % change Jobs Benefits

(Millions) 

Current 3,186,323 6,370 $1,004

CCC 3,618,856 13.6% 7,351 $1,216

Hadley 3,502,426 9.9% 7,095 $1,157

Extreme Heat 2,907,520 -8.7% 5,770 $959

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SAP 4.6 Chapter 4: Human Welfare 

4.10 Figures 

Figure 4.1 Geography of Climate Change Vulnerability at the County Scale

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SAP 4.6 Chapter 4: Human Welfare 

Figure 4.2 Steps from Climate Change to Economic Valuation of Ecosystem Services 

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SAP 4.6 Chapter 4: Human Welfare 

Figure 4.3 Direct and Indirect Effects of Climate Change on Recreation

Climate Change: Effects on Outdoor Recreation 

+Temperature 

+/- Precipitation 

+Climate Variability 

Use & Benefits: 

Enjoyment & Comfort while in 

outdoors 

Visitor Days of outdoor recreation 

demanded 

Benefits of outdoor recreation 

Direct 

Effects of Climate Change: 

Changes in. . .

. . .Vegetation (forests) 

. . .Stream flows 

. . .Reservoir levels 

. . .Recreational Fisheries 

. . .Wildlife populations 

. . .Miles of Beaches 

. . .Snow, Ice 

. . .Length of season 

Indirect 

4 -74 
 

Synthesis and Assessment Product 4.6 

Chapter 5: Common Themes and Research 

Recommendations 

Convening Lead Author: Janet L. Gamble, U.S. Environmental Protection Agency

Lead Authors: Kristie L. Ebi, ESS, LLC; Frances G. Sussman, Environmental Economics Consulting; 

Thomas J. Wilbanks, Oak Ridge National Laboratory 

Contributing Authors: Colleen E. Reid, ASPH Fellow; John V. Thomas, U.S. Environmental Protection 

Agency; Christopher P. Weaver, U.S. Environmental Protection Agency 

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SAP 4.6 Chapter 5: Research

Table of Contents 

5.1 Synthesis and Assessment Product 4.6: Advances in the Science....................................................... 3

5.1.1 Complex Linkages and a Cascading Chain of Impacts Across Global Changes.............................. 3 

5.1.2 Changes in Climate Extremes and Climate Averages....................................................................... 4 

5.1.3 Vulnerable Populations and Vulnerable Locations .......................................................................... 5 

5.1.4. The Cost of and Capacity for Adaptation ........................................................................................ 6 

5.1.5 An Integrative Framework................................................................................................................ 6 

5.2 Expanding the Knowledge Base ............................................................................................................ 7

5.2.1 Human Health Research Gaps.......................................................................................................... 9 

5.2.2 Human Settlements Research Gaps ................................................................................................ 10 

5.2.3 Human Welfare Research Gaps...................................................................................................... 10

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SAP 4.6 Chapter 5: Research

5.1 Synthesis and Assessment Product 4.6: Advances in the 

Science 

The Synthesis and Assessment Product 4.6 assesses the impacts of climate variability and 

change on human systems in the United States. Each of the assessment chapters have 

drawn on different literatures, with generally more available scientific knowledge on 

impacts and adaptations related to human health, somewhat less related to human 

settlements, and still somewhat less related to human welfare. 

Several themes recur across these chapters and point to advances in the science of climate 

impacts assessment and the development and deployment of adaptation responses. 

1. Climate change is connected to other environmental and social changes in a 

complex and dynamic fashion. In some cases climate change compounds other 

global changes, while in other cases the impacts of climate change are determined 

or moderated by other socioeconomic factors (5.1.1). 

2. Extreme weather events will play a defining role, particularly in the near term, 

shaping climate-related impacts and adaptive capacity. While impacts associated 

with changes in climate averages may be less important now, these averages are 

expected to have more pronounced long-run effects on sea level rise, permafrost 

melt, glacial retreat, drought patterns and water supplies, etc. (5.1.2). 

3. Climate change will have a disproportionate impact on disadvantaged groups in 

communities across the United States. Some regions and some resources are more 

vulnerable to climate impacts, such as coastal zones, drought-prone regions, and 

flood-prone river basins (5.1.3). 

4. Adaptation of infrastructure and services to climate change may be costly, but 

many communities will have adequate resources. However, for places already 

struggling to provide or maintain basic public amenities and services, the 

additional costs of adaptation will impose a potentially-insupportable burden 

(5.1.4.). 

5. With such a complex scientific and policy landscape, an integrated multidisciplinary framework is needed to enable climate change impacts to be 

measured in meaningful ways and for optimal mitigation and adaptation strategies 

to be identified, developed, and deployed (5.1.5). 

5.1.1 Complex Linkages and a Cascading Chain of Impacts Across Global 

Changes 

Climate is only one of a number of global changes that impact human well-being. The 

major effects of climate will be shaped by interactions with non-climate stressors. As 

such, climate change will seldom be the sole or primary factor determining a population’s 

or a location’s well-being. The impacts of climate variability and change interact with 

impacts tied to population growth and change and other socioeconomic endpoints (for 

example, impacts on infrastructure capacity, water supplies, habitat preservation, 

community growth and development, and access to health care). While this assessment 

focuses on how climate change could affect the future health, well-being, and settlements 

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SAP 4.6 Chapter 5: Research

in the United States, the extent of any impacts will depend on an array of non-climate 

factors, including: 

 Demographic changes related to the location, size, age and characteristics of 

populations; population and regional vulnerabilities; 

 Future social, economic, and cultural contexts; 

 Availability of natural resources; 

 Human, cultural and social capital; 

 Advances in science and technology; 

 Characteristics of the built environment; 

 Land use change; 

 Public health and public utility infrastructures; and, 

 The capacity and availability of health and social services. 

The effects of climate change very often spread from directly impacted areas and sectors 

to other areas and sectors through extensive and complex linkages. The importance of 

climate change depends on the directness of the climate impact coupled with 

demographic, social, economic, institutional, and political factors, including, the degree 

of preparedness. Consider the damage left by Hurricanes Katrina and Rita in 2005. 

Damage was measured not only in terms of lives lost, but also on the devastating impacts 

on infrastructure, neighborhoods, businesses, schools, and hospitals as well as in the 

personal disruption of family and friends in established communities, with lost lives and 

lost livelihoods, challenged psychological well-being, and exacerbation of chronic 

illnesses. While the aftermath of a single hurricane is not the measure of climate change, 

such an event demonstrates the disruptive capacity of extreme weather events. 

5.1.2 Changes in Climate Extremes and Climate Averages. 

Past and present climates have been, and are, variable. This variability in all likelihood 

will continue into the future. Changes in climate occur as changes in particular weather 

conditions, including extremes, in specific places (unfortunately, projections of climate 

changes at small geographic scales remain highly uncertain). The meteorological 

variables of interest from an impacts perspective include both changes in average 

conditions and in extreme conditions. More gradual changes in average temperature and 

precipitation have the potential to strongly affect, both positively and negatively, human 

systems. For example, changes in the average length of the growing season can affect 

agricultural practices and changes in the timing and amount of spring runoff can affect 

water resource management. Effects such as these will not, however, be confined to a few 

individual sectors, nor are the effects across all sectors independent (e.g., changes in 

water supplies can impact agricultural practices such as irrigation).

Changes in the climate extremes, both those that accompany changes in mean conditions 

(e.g., a shift in the entire temperature distribution) as well as changes in variability are 

very often of more concern than changes in climate averages. Unfortunately these types 

of changes (e.g., heat waves, drought, storms, seasonal high or low levels of temperature 

or precipitation) have not always been projected by climate change models. Many human 

systems have evolved to accommodate the “average climate” and some variation around 

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SAP 4.6 Chapter 5: Research

this average. This evolution takes place in a dynamic social, economic, technological, 

biophysical and political context, which determine the ability of human systems to cope. 

Rapid onset extreme weather events in particular can do serious damage to a settlement’s 

infrastructure, public health, and overall community reputation and quality of life, from 

which recovery may take years. 

Finally key vulnerabilities are often defined by certain “thresholds,” below which effects 

are incidental but beyond where effects quickly become major. The severity of impacts is 

therefore not only related to the rate and magnitude of climate change, but also to the 

presence or absence of thresholds. In general, these climate-related thresholds for human 

systems in the United States are not well-understood. Focused research on thresholds 

would substantially improve understanding of climate impacts. 

5.1.3 Vulnerable Populations and Vulnerable Locations 

Impacts of climate variability and change on human systems are location- and 

population-specific. For instance, in densely-developed coastlines, populations are 

especially vulnerable to tropical storms, storm surge and flooding, just as the very old and 

the very young residing in urban areas experience increases in cardiovascular and 

pulmonary morbidity and mortality caused by extreme heat coupled with degraded air 

quality. Native American peoples in Alaska and other low socio-economic communities 

because of their decreased economic capacity to prepare for and respond to the impacts of 

climate change. Just as there are differences across populations, there are important 

differences in vulnerability across geographic regions, such as the exposure to extreme 

events along the Gulf Coast and water supply issues in the southeast, the southwest and 

the Inter-Mountain West. 

With respect to health impacts from climate variability and change, specific 

subpopulations may experience heightened vulnerability for climate-related health effects 

associated with: 

1. Biological sensitivity related to age (especially the very young and the very old), 

the presence of pre-existing chronic medical conditions (such as the sensitivity of 

people with chronic heart and pulmonary conditions to heat-related illness), 

developmental characteristics, acquired factors (such as immunity), those taking 

certain medications (e.g., some antihypertensive and psychotropic medications) 

and genetic factors (such as metabolic enzyme subtypes that play a role in 

vulnerability to air pollution effects). 

2. Socioeconomic factors also play a critical role in determining vulnerability to 

environmentally-mediated factors. The distribution of climate-related effects will 

vary among those who live alone; those with limited rights (for instance, some in 

the immigrant communities); by economic strata; by housing type and according 

to other elements that either accentuate or limit vulnerability. Socioeconomic 

factors may increase the likelihood of exposure to harmful agents, interact with 

biological factors that mediate risk (such as nutritional status), and/or lead to 

differences in the ability to adapt or respond to exposures or to early phases of 

illness and injury. 

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SAP 4.6 Chapter 5: Research

3. Given their location, the underlying vulnerability of some communities is 

inherently high just as their adaptive capacity is similarly limited. Populations in 

gently-sloping coastal areas are particularly vulnerable to sea level rise and 

settlements along floodplains of large rivers are particularly vulnerable due to 

projections of increased variability in precipitation. Projections of increased 

frequencies of drought combined put the increasing populations of desert 

southwest cities at risk. 

It is essential that public health interventions and preventions recognize populations that 

may experience interactive or synergistic effects of multiple risk factors for health 

problems, both related to climate change and to other global changes. Poor communities 

and households are already under stress from climate variability and climate-related 

extreme events such as heat waves, hurricanes, and tropical and riverine flooding. Since 

they tend to be concentrated in relatively high-risk areas, have limited access to services 

and other resources for coping, they can be especially vulnerable to climate change. 

These differential effects propagate concerns regarding social inequity and environmental 

justice and increased pressure for adaptive responses from local, state, and federal 

governments. 

5.1.4. The Cost of and Capacity for Adaptation

U.S. society is capable of considerable adaptation, depending heavily on the competence 

and capacity of individuals, communities, federal, state, and local governments, and 

available financial and other social resources. While adaptation to climate change will 

come at a cost that may reduce available resources to cope with other societal burdens, 

potentials for adaptation through technological and institutional development and 

behavioral changes are considerable, especially where such developments meet other 

sustainable development needs. 

With scarce resources, communities should also choose adaptation options with cobenefits that help ameliorate other issues or where they can easily add climate concerns to 

existing response plans. The focus on all-hazards response within public health agencies 

can simply add climate impacts to its list of hazards for which to prepare. This will likely 

improve their response plans to events in the near term such as storms that happen in a 

variable climate, whether or not they increase in frequency or intensity with a changing 

climate. Planting trees and green roofs to reduce urban heat islands has the added benefit 

of creating a more aesthetically pleasing location that increasing well-being and by 

decreasing energy use in these buildings. Thus, some adaptation measures can also 

considered mitigation measures. 

5.1.5 An Integrative Framework 

The impacts of climate variability and change on human health and human settlements 

are fairly well characterized in broad terms, although additional research is needed to 

refine impact assessments and provide better decision support (particularly with respect 

to deploying adaptation measures). Human well-being is an emerging concept, and in 

theory could encompass human health and settlements. As an organizing principle, 

human well-being could provide a paradigm for identifying and categorizing climate 

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SAP 4.6 Chapter 5: Research

impacts, and may ultimately provide a framework for integrating multiple impacts into an 

internally-consistent, coherent framework for assessing costs, benefits, and tradeoffs. The 

potential for utilizing concepts of human well-being to develop an integrating framework 

is not yet mature. Additional conceptual work and research will be needed, such as 

valuation methodologies (in the case of economic welfare), or developing metrics of 

well-being or quality of life (in the case of a place-based indicators, or similar, approach). 

As an integrating concept, human well-being can provide insight into the determinants of 

human happiness. Just as health can be considered a component of well-being (i.e.,

physical health is closely tied to individual measures of happiness, contentment, and 

quality of life) aspects of human settlements also determine well-being and could be 

incorporated into a broader framework of well-being or welfare. 

An alternative integrating framework could revolve around settlements or the more 

expansive concept of communities (See Section 4.2.3 for a fuller discussion). There is a 

growing awareness that the built environment can have a profound impact on our health 

and quality of life1. A major goal of community design is to create more vibrant and 

livable communities, making sure that they address the needs of residents and improve 

their quality of life. More specifically, “Green communities”, “Smart communities”, 

“Smart growth” and “Sustainable development” are intended to offer alternatives to 

traditional settlement patterns, aiming to meet the goals of creating livable, desirable 

communities while minimizing the collective footprint of communities on natural 

resources, ecosystems and pollution. As an integrating framework, communities could be 

evaluated based on how well they protect human health and welfare. Put slightly 

differently, adaptation could be realized as increasing resilience within communities. 

Resilience is measured by a community’s capacity for absorbing climate changes and the 

shocks of extreme events without breakdowns in its economy, natural resources, and 

social systems. Resiliency, as a central concept in measuring the vulnerability and 

adaptability of communities and individuals, depends not only on physical infrastructure, 

but also on social infrastructure and the natural environment. As with welfare, these 

concepts involving settlements or communities as an integrating framework are not yet 

mature. 

5.2 Expanding the Knowledge Base 

The present state of the science suggests that opportunities remain for addressing critical 

research areas. The SAP 4.6 concludes that climate observations and modeling are 

becoming increasingly important for a wide segment of public and private sector entities, 

such as water resource managers, public health officials, agribusinesses, energy 

providers, forest managers, insurance companies, and urban and transportation planners. 

In order to more accurately portray the consequences of climate change and support 

better-informed adaptation strategies, research efforts should focus on: 

 Deriving socioeconomic scenarios that describe how the world may evolve in the 

future, including assumptions about changes in societal characteristics, 

 

1

 See for example, the CDC web-site on healthy places: www.cdc.gov/healthyplaces/ 

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SAP 4.6 Chapter 5: Research

governments and public policy, as well as economic and technological 

development; 

 Connecting those socioeconomic scenarios with downscaled climate models to 

create projections of future changes in climate, including the intensity and 

severity of extreme weather events, at the regional and local scales; 

 Characterizing the costs of climate change, both those that relate to impacts and 

those that relate to response strategies (including adaptation and mitigation); 

 Estimating the damages avoided by stabilizing or reducing emissions; 

 Determining the factors that contribute to synergies between adaptive capacity 

and sustainable development as well as synergies between adaptation and 

mitigation; 

 Pursuing cross-disciplinary efforts that focus on the human dimensions of climate 

change in an integrated fashion; 

 Improving capacity to incorporate scientific knowledge about climate, including 

uncertainty, in existing adaptation strategies; 

 Conducting research at regional and sectoral levels that promote analyses of the 

response of human and natural systems to multiple stresses. Impacts of climate 

change are most damaging when they occur in a context of multiple climate and 

non-climate stressors; 

 Evaluating the adaptation strategies that effectively address challenges presented 

by current non-climate stressors (e.g., land use and population dynamics) as well 

as anticipated climate change impacts and develop comprehensive estimates of 

these co-benefits; 

 Implementing adaptation measures to address the near- and long-term responses 

to climate change, using regional and local stakeholders as key stakeholders in the 

development of effective, responsive, and timely adaptation policies; 

 Advancing the concept of human welfare as an integrating framework by 

developing methods to achieve comparable and comprehensive valuations across 

diverse impacts and sectors; 

 Determining which climate impacts exhibit thresholds. Threshold-based damage 

functions can be fundamentally different in their nature and extent than 

continuous damage functions; 

 Supporting research on impacts and the development, implementation and 

evaluation of adaptive responses by collecting high quality time-series 

measurements and other observations of both climate and human systems; and, 

 Identifying early effects of changing weather patterns on climate-sensitive 

outcomes. 

This report concludes that periodic assessments of the impacts of global change on 

human health, human settlements, and human welfare are necessary to support a rapidly 

developing knowledge base, especially related to impacts and adaptation. Gaps should be 

addressed that characterize exposure and sensitivity at the local or regional level. 

Research should evaluate the adaptive capacity of places and institutions to climateinduced risks. Key research and development areas should address short-term risk 

assessment and evaluation of the costs and effectiveness of near-term adaptive strategies 

as well as longer-term impacts and responses. 

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SAP 4.6 Chapter 5: Research

The following sections provide a more detailed discussion of research needs and 

recommendations by topic: human health, human settlements, and human welfare. There 

is significant overlap across topics with opportunities for investigating cross-disciplinary 

pursuits of research opportunities and adaptation responses. 

5.2.1 Human Health Research Gaps 

An important shift in perspective has occurred since the Health Sector Assessment of the 

First National Assessment in 2001. There is a greater appreciation of the complex 

pathways by which weather and climate affect individual and societal health and wellbeing. In the research community, there is a more finely-honed understanding of the 

interaction of multiple non-climate, social, and behavioral factors and impacts on risks 

from injury and disease. While significant gaps remain, several gaps identified in the 

First National Assessment have been addressed, including: 

 A more finely honed understanding of the differential effects of temperature 

extremes by community, demographic, and biological characteristics; 

 Improved characterization of the exposure-response relationships to extreme heat; 

and, 

 Improved understanding of the public health burden posed by climate-related 

changes from heat waves and air pollution. 

Despite these advances, the body of literature has only limited quantitative 

projections of future impacts. Research related to the human health impacts of climate 

change will lead to a better understanding in this area. 

 The following specific suggestions for research on climate change and human health: 

 Increase the skill with which we characterize exposure-response relationships, 

including identifying thresholds and particularly vulnerable groups, considering 

relevant factors that affect the geographic range and incidence of climate-sensitive 

health outcomes, and including disease ecology and transmission dynamics; 

 Develop quantitative models of possible health impacts of climate change that can 

be used to explore a range of socioeconomic and climate scenarios; 

 Evaluate effectiveness of current adaptation projects, including the costs and 

benefits of interventions. For example, heat wave and health early warning 

systems have not been effective; further research is needed to understand how 

public health messages can be made more helpful; 

 Characterize with local stakeholders the local and regional scale vulnerability and 

adaptive capacity related to the potential risks and the time horizon over which 

climate risks might arise; and, 

 Anticipate requirements for infrastructure such as may be needed to provide 

protection against extreme events, to alter urban design to decrease heat islands, 

and to maintain drinking and wastewater treatment standards and source water 

and watershed protection. 

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SAP 4.6 Chapter 5: Research

5.2.2 Human Settlements Research Gaps 

Chapter 3 examines the vulnerabilities and impacts of climate change and variability on 

human settlements. The following list enumerates topics where a better understanding of 

the linkages between climate change and human settlements is appropriate. 

 Advance the understanding of settlement vulnerabilities, impacts, and adaptive 

responses in a variety of different local contexts around the country. 

 Develop plans for out-migration from vulnerable locations via realistic, socially 

acceptable strategies for shifting human populations away from vulnerable zones. 

 Improve the understanding of vulnerable populations (such as the urban poor and 

native populations on rural, tribal lands) that have limited capacities for response 

to climate change in order to provide a basis for adaptation research that addresses 

social justice and environmental equity concerns. 

 Improve the understanding of how urban decision-making is changing as 

populations become more heterogeneous and decisions become more 

decentralized especially as this affects adaptive responses. 

 Improve abilities to associate projections of climate change in U.S. settlements 

with changes in other driving forces related to impacts, such as changes in 

metropolitan/urban patterns, changes in transportation infrastructure and 

technological change. With continued growth in vulnerable regions, research is 

needed to consider alternative growth futures and to minimize the vulnerability of 

new development, to insure that communities adopt measures to manage 

significant changes in sea level, temperature, rainfall and extreme weather events. 

 Improve the understanding of relationships between settlement patterns (both 

regional and intra-urban) and resilience/adaptation. 

 Improve the understanding of vulnerabilities of urban population inflows and 

outflows to climate change impacts. 

 Improve the understanding of second and third-order impacts of climate change in 

urban environments, including interactive effects among different aspects of the 

urban system. 

 Review current policies and practices related to climate change responses to help 

inform community decision-makers and other stakeholders about potentials for 

relatively small changes to make a large difference. 

Meeting these needs is likely to require well-developed partnerships across local, state, 

and federal governments, industry, non-governmental organizations, foundations, 

stakeholders, resource managers, urban planners, public utility and public health 

authorities, and the academic research community. 

5.2.3 Human Welfare Research Gaps 

Despite the potential for impacts on human well-being, little research focuses directly on 

understanding the relationship between well-being and climate change. Completely 

cataloging the effects of global change on human well-being or welfare would be an 

immense undertaking, and no well-accepted structure for doing so has been developed 

and applied. Moreover, identifying the potentially lengthy list of climate-related changes 

in lifestyle, as well as in other, more tangible, features of well-being (such as income), is 

5-10 
SAP 4.6 Chapter 5: Research

itself a daunting task—and may include changes that are not easily captured by objective 

measures of well-being or quality of life. 

Developing an understanding of the impacts of climate change on human welfare will 

require steps designed to develop a framework for addressing individual and community 

welfare and well-being, as well as to fill the data gaps associated with the estimation and 

quantification of effects. 

Regarding climate change and human welfare, there is a range of topics associated with 

human welfare impacts and adaptations where improved understanding would be useful. 

 Design an appropriate method for systematically categorizing and identifying 

impacts on welfare/well-being. 

 Identify priority categories for data collection and research in order to establish 

and quantify the linkage from climate to effects on welfare/well-being. 

 Decide which metrics should be used for these categories; more generally, which 

components of welfare/well-being should be measured in natural or physical 

units, and which should be monetized. 

 Investigate methods by which diverse metrics can be aggregated, or at least 

weighted and compared in policy decisions where aggregation is impossible. 

 Develop an approach for addressing those human welfare effects that are difficult 

to look at in a piecemeal way, such as welfare changes on communities or 

ecosystem services. 

 Identify appropriate top-down and bottom-up approaches for estimating impacts 

and value (whether economic or otherwise) of the most critical categories of 

welfare/well-being. 

Together, these steps should enable researchers to make progress towards promoting the 

consistency and coordination in analyses of welfare/well-being that will facilitate 

developing the body of research necessary to analyze impacts on human welfare, wellbeing, and quality of life. 

5-11 
SAP 4.6 Glossary and Acronyms

6 Glossary and Acronyms 

6.1 Glossary 

Sources: Derived from the Intergovernmental Panel on Climate Change 

Third and Fourth Assessment Reports, Working Group II and other sources as 

indicated. 

Words in italics indicate that the following term is also contained in this glossary. 

A 

Acclimatization 

The physiological adaptation to climatic 

variations. 

Adaptability 

See Adaptive capacity. 

Adaptation 

Adjustment in natural or human systems to a 

new or changing environment. Adaptation to 

climate change refers to adjustment in 

natural or human systems in response to 

actual or expected climatic stimuli or their 

effects, which moderates harm or exploits 

beneficial opportunities. Various types of 

adaptation can be distinguished, including 

anticipatory and reactive adaptation, private 

and public adaptation, and autonomous and 

planned adaptation. 

Adaptation assessment 

The practice of identifying options to adapt 

to climate change and evaluating them in 

terms of criteria such as availability, 

benefits, costs, effectiveness, efficiency, and 

feasibility. 

Adaptation benefits 

The avoided damage costs or the accrued 

benefits following the adoption and 

implementation of adaptation measures. 

Adaptation costs 

Costs of planning, preparing for, facilitating, 

and implementing adaptation measures, 

including transition costs. 

Adaptive capacity 

The ability of a system to adjust to climate 

change (including climate variability and 

extremes) to moderate potential damages, to 

take advantage of opportunities, or to cope 

with the consequences. 

Aeroallergens1

Any of various airborne substances, such as 

pollen or spores, that can cause an allergic 

response.

Aggregate impacts 

Total impacts summed up across sectors 

and/or regions. The aggregation of impacts

requires knowledge of (or assumptions 

about) the relative importance of impacts in 

different sectors and regions. Measures of 

aggregate impacts include, for example, the 

total number of people affected, change in 

net primary productivity, number of systems 

undergoing change, or total economic costs. 

Albedo 

The fraction of solar radiation reflected by a 

surface or object, often expressed as a 

percentage. Snow-covered surfaces have a 

high albedo; the albedo of soils ranges from 

high to low; vegetation-covered surfaces and 

oceans have a low albedo. The Earth’s 

albedo varies mainly through varying 

cloudiness, snow, ice, leaf area, and landcover changes. 

 

1 The American Heritage® Dictionary of the 

English Language, Fourth Edition. Retrieved 

November 21, 2007, from Dictionary.com 

website: 

http://dictionary.reference.com/browse/aeroaller

gen 

6-1 
SAP 4.6 Glossary and Acronyms

Algal bloom 

A reproductive explosion of algae in a lake, 

river or ocean. 

Ancillary benefits 

The ancillary, or side effects, of policies 

aimed exclusively at climate change 

mitigation. Such policies have an impact not 

only on greenhouse gas emissions, but also 

on resource use efficiency, like reduction in 

emissions of local and regional air pollutants 

associated with fossil-fuel use, and on issues 

such as transportation, agriculture, land-use 

practices, employment, and fuel security. 

Sometimes these benefits are referred to as 

“ancillary impacts” to reflect that in some 

cases the benefits may be negative. From the 

perspective of policies directed at abating 

local air pollution, greenhouse gas 

mitigation may also be considered an 

ancillary benefit, but these relationships are 

not considered in this assessment. 

Anthropogenic 

Resulting from or produced by human 

beings. 

Anthropogenic emissions 

Emissions of greenhouse gases, greenhouse 

gas precursors, and aerosols associated with 

human activities. These include burning of 

fossil fuels for energy, deforestation, and 

land-use changes that result in net increase 

in emissions. 

Aquifer 

A stratum of permeable rock that bears 

water. An unconfined aquifer is recharged 

directly by local rainfall, rivers and lakes, 

and the rate of recharge will be influenced 

by the permeability of the overlying rocks 

and soils. 

Arid regions 

Ecosystems with less than 250 mm

precipitation per year. 

Atmosphere 

The gaseous envelop surrounding the Earth. 

The dry atmosphere consists almost entirely 

of nitrogen (78.1% volume mixing ratio) and 

oxygen (20.9% volume mixing ratio), 

together with a number of trace gases, such 

as argon (0.93% volume mixing ratio), 

helium, and radiatively active greenhouse 

gases such as carbon dioxide (0.035% 

volume mixing ratio) and ozone. In addition, 

the atmosphere contains water vapor, whose 

amount is highly variable but typically 1% 

volume mixing ratio. The atmosphere also 

contains clouds and aerosols. 

B

Baseline 

The baseline (or reference) is any datum 

against which change is measured. It might 

be a “current baseline,” in which case it 

represents observable, present-day 

conditions. It might also be a “future 

baseline,” which is a projected future set of 

conditions excluding the driving factor of 

interest. Alternative interpretations of the 

reference conditions can give rise to 

multiple baselines. 

Biofuel 

A fuel produced from organic matter or 

bombustible oils produced by plants. 

Examples of biofuel include alcohol, black 

liquor from the paper-manufacturing 

process, wood, and soybean oil. 

Biogenic2

Produced by living organisms or biological 

processes. 

C 

Carbon dioxide (CO2) 

A naturally occurring gas, and also a byproduct of burning fossil fuels and biomass, 

as well as land-use changes and other 

industrial processes. It is the principal 

anthropogenic greenhouse gas that affects 

the Earth’s radiative balance. It is the 

reference gas against which other 

greenhouse gases are measured and has a 

Global Warming Potential of 1. 

Cholera 

An intestinal infection that results in 

frequent watery stools, cramping abdominal 

 

2 The American Heritage® Dictionary of the 

English Language, Fourth Edition. Retrieved 

November 21, 2007, from Dictionary.com 

website: 

http://dictionary.reference.com/browse/biogenic 

6-2 
SAP 4.6 Glossary and Acronyms

pain, and eventual collapse from 

dehydration. 

Chronic obstructed pulmonary disease 

(COPD)3

Chronic obstructive pulmonary disease, or 

COPD, refers to a group of diseases that 

cause airflow blockage and breathing-related 

problems. It includes emphysema, chronic 

bronchitis, and in some cases asthma. 

Climate 

Climate in a narrow sense is usually defined 

as the “average weather” or more rigorously 

as the statistical description in terms of the 

mean and variability of relevant quantities 

over a period of time ranging from months 

to thousands or millions of years. The 

classical period is 30 years, as defined by 

the World Meteorological Organization 

(WMO). These relevant quantities are most 

often surface variables such as temperature, 

precipitation, and wind. Climate in a wider 

sense is the state, including a statistical 

description, of the climate system. 

Climate change 

Climate change refers to any change in 

climate over time, whether due to natural 

variability or as a result of human activity. 

This usage differs from that in the United 

Nations Framework Convention on Climate 

Change (UNFCCC), which defines ‘climate 

change’ as: ‘a change of climate which is 

attributed directly or indirectly to human 

activity that alters the composition of the 

global atmosphere and which is in addition 

to natural climate variability observed over 

comparable time periods’. See also climate 

variability. 

Climate change commitment 

Due to the thermal inertia of the ocean and 

slow processes in the biosphere, the 

cryosphere and land surfaces, the climate 

would continue to change even if the 

atmospherica composition was held fixed at 

today’s values. Past changes in atmospheric 

position leads to a ‘committed’ climatic 

change which continues for as long as a 

radiative imbalance persists and until all 

 

3

 Definition taken from 

http://www.cdc.gov/nceh/airpollution/copd/copd

faq.htm visited on November 21, 2007. 

components of the climate system have 

adjusted to a new state. The further change 

in temperature after the composition of the 

atmosphere is head constant is referred to as 

the committed warming or warming 

commitment. Climate change commitment 

includes other future changes, for example 

in the hydrological cycle, in extreme 

weather events, and in sea-level rise.

Climate model (hierarchy) 

A numerical representation of the climate 

system based on the physical, chemical, and 

biological properties of its components, their 

interactions and feedback processes, and 

accounting for all or some of its known 

properties. The climate system can be 

represented by models of varying 

complexity—that is, for any one component 

or combination of components a “hierarchy” 

of models can be identified, differing in such 

aspects as the number of spatial dimensions, 

the extent to which physical, chemical or 

biological processes are explicitly 

represented, or the level at which empirical 

parametrizations are involved. Coupled 

atmosphere/ocean/sea-ice general 

circulation models (AOGCMs) provide a 

comprehensive representation of the climate 

system. There is an evolution towards more 

complex models with active chemistry and 

biology. Climate models are applied, as a 

research tool, to study and simulate the 

climate, but also for operational purposes, 

including monthly, seasonal, and interannual 

climate predictions. 

Climate prediction 

A climate prediction or climate forecast is 

the result of an attempt to produce a most 

likely description or estimate of the actual 

evolution of the climate in the future (e.g., at 

seasonal, interannual, or long-term timescales). See also climate projection and 

climate (change) scenario. 

Climate projection 

A projection of the response of the climate 

system to emission or concentration 

scenarios of greenhouse gases and aerosols, 

or radiative forcing scenarios, often based 

upon simulations by climate models. 

Climate projections are distinguished from 

climate predictions in order to emphasize 

6-3 
SAP 4.6 Glossary and Acronyms

that climate projections depend upon the 

emission/concentration/radiative forcing 

scenario used, which are based on 

assumptions, concerning, for example, 

future socio-economic and technological 

developments that may or may not be 

realized, and are therefore subject to 

substantial uncertainty. 

Climate scenario 

A plausible and often simplified 

representation of the future climate, based 

on an internally consistent set of 

climatological relationships, that has been 

constructed for explicit use in investigating 

the potential consequences of anthropogenic 

climate change, often serving as input to 

impact models. Climate projections often 

serve as the raw material for constructing 

climate scenarios, but climate scenarios 

usually require additional information such 

as about the observed current climate. A 

“climate change scenario” is the difference 

between a climate scenario and the current 

climate.

Climate system 

The climate system is the highly complex 

system consisting of five major components: 

the atmosphere, the hydrosphere, the 

cryosphere, the land surface and the 

biosphere, and the interactions between 

them. The climate system evolves in time 

under the influence of its own internal 

dynamics and because of external forcings 

such as volcanic eruptions, solar variations, 

and human-induced forcings such as the 

changing composition of the atmosphere and 

land-use change. 

Climate variability 

Climate variability refers to variations in the 

mean state and other statistics (such as 

standard deviations, the occurrence of 

extremes, etc.) of the climate on all temporal 

and spatial scales beyond that of individual 

weather events. Variability may be due to 

natural internal processes within the climate 

system (internal variability), or to variations 

in natural or anthropogenic external forcing 

(external variability). See also climate 

change. 

Co-benefits 

The benefits of policies that are 

implemented for various reasons at the same 

time—including climate change 

mitigation— acknowledging that most 

policies designed to address greenhouse gas 

mitigation also have other, often at least 

equally important, rationales (e.g., related to 

objectives of development, sustainability, 

and equity). The term co-impact is also used 

in a more generic sense to cover both the 

positive and negative sides of the benefits. 

See also ancillary benefits. 

Communicable Disease 

An infectious disease caused by 

transmission of an infective biological agent 

(virus, bacterium, protozoan, or 

multicellular macroparasite). 

Confidence 

In this Report, the level of confidence in a 

statement is expressed using a standard 

terminology defined in the Introduction. See 

also uncertainty.

Coping range 

The variation in climatic stimuli that a 

system can absorb without producing 

significant impacts. 

Cost-effective 

A criterion that specifies that a technology 

or measure delivers a good or service at 

equal or lower cost than current practice, or 

the least-cost alternative for the achievement 

of a given target. 

D 

DALY (Disability-adjusted life years)4

The sum of years of life lost due to 

premature death and illness, taking into 

account the age of death compared with 

natural life expectancy and the number of 

years of life lived with a disability. The 

measure of number of years lived with the 

disability considers the duration of the 

disease, weighted by a measure of the 

severity of the disease.

Dengue Fever 

 

4

 Definition from the glossary of the Millenium 

Ecosystem Assessment, 2005. 

6-4 
SAP 4.6 Glossary and Acronyms

An infectious viral disease spread by 

mosquitoes often called breakbone fever 

because it is characterized by severe pain in 

joints and back. Subsequent infections of the 

virus may lead to dengue hemorrhagic fever 

(DHF) and dengue shock syndrome (DSS), 

which may be fatal. 

Desert 

An ecosystem with less than 100 mm

precipitation per year. 

Desertification 

Land degradation in arid, semi-arid, and dry 

sub-humid areas resulting from various 

factors, including climatic variations and 

human activities. Further, the United 

Nations Convention to Combat 

Desertification defines land degradation as a 

reduction or loss in arid, semi-arid, and dry 

sub-humid areas of the biological or 

economic productivity and complexity of 

rain-fed cropland, irrigated cropland, or 

range, pasture, forest, and woodlands 

resulting from land uses or from a process or 

combination of processes, including 

processes arising from human activities and 

habitation patterns, such as: (i) soil erosion 

caused by wind and/or water; (ii) 

deterioration of the physical, chemical, and 

biological or economic properties of soil; 

and (iii) long-term loss of natural vegetation. 

Detection and attribution 

Climate varies continually on all time scales. 

Detection of climate change is the process 

of demonstrating that climate has changed in 

some defined statistical sense, without 

providing a reason for that change. 

Attribution of causes of climate change is 

the process of establishing the most likely 

causes for the detected change with some 

defined level of confidence. 

Disturbance regime 

Frequency, intensity, and types of 

disturbances, such as fires, inspect or pest 

outbreaks, floods, and droughts. 

Diurnal temperature range 

The difference between the maximum and 

minimum temperature during a day. 

Dose-response function5

 

A mathematical relationship is established 

which relates how much a certain amount of 

exposure impacts on production, capital, 

ecosystems, human health etc. 

Downscaling 

A method that derives local- to regionalscale (10 to 100 km) information from

larger-scale models or data analyses.

Drought 

The phenomenon that exists when 

precipitation has been significantly below 

normal recorded levels, causing serious 

hydrological imbalances that adversely 

affect land resource production systems. 

E 

Ecosystem 

A system of interacting living organisms 

together with their physical environment. 

The boundaries of what could be called an 

ecosystem are somewhat arbitrary, 

depending on the focus of interest or study. 

Thus, the extent of an ecosystem may range 

from very small spatial scales to, ultimately, 

the entire Earth. 

Ecosystem processes 

The processes that underpin the integrity and 

functioning of ecosystems, such as 

decomposition, carbon cycling, or soil 

renewal, etc. 

Ecosystem services 

Ecological processes or functions that have 

monetary or non-monetary value to 

individuals or society. There are (i) 

supporting services such as productivity or 

biodiversity maintenance, (ii) provisioning 

services such as food, fibre, or fish, (iii) 

regulating services such as climate 

regulation or carbon sequestration, and (iv) 

cultural services such as tourism or spiritual 

and aesthetic appreciation. 

El Niño Southern Oscillation (ENSO) 

 

5

 Definition modified from 

http://stats.oecd.org/glossary/detail.asp?ID=6404 

visited on November 21, 2007. 

6-5 
SAP 4.6 Glossary and Acronyms

El Niño, in its original sense, is a warm 

water current that periodically flows along 

the coast of Ecuador and Peru, disrupting the 

local fishery. This oceanic event is 

associated with a fluctuation of the 

intertropical surface pressure pattern and 

circulation in the Indian and Pacific Oceans, 

called the Southern Oscillation. This 

coupled atmosphere-ocean phenomenon is 

collectively known as El Niño Southern 

Oscillation, or ENSO. During an El Niño 

event, the prevailing trade winds weaken 

and the equatorial countercurrent 

strengthens, causing warm surface waters in 

the Indonesian area to flow eastward to 

overlie the cold waters of the Peru current. 

This event has great impact on the wind, sea 

surface temperature, and precipitation 

patterns in the tropical Pacific. It has 

climatic effects throughout the Pacific 

region and in many other parts of the world. 

The opposite of an El Niño event is called 

La Niña. 

Emissions 

In the climate change context, emissions 

refer to the release of greenhouse gases 

and/or their precursors and aerosols into the 

atmosphere over a specified area and period 

of time. 

Endemic 

Restricted or peculiar to a locality or region. 

With regard to human health, endemic can 

refer to a disease or agent present or usually 

prevalent in a population or geographical 

area at all times. 

Epidemic 

Occurring suddenly in numbers clearly in 

excess of normal expectancy, said especially 

of infectious diseases but applied also 

to any disease, injury, or other health-related 

event occurring in such outbreaks. 

Eutrophication 

The process by which a body of water (often 

shallow) becomes (either naturally or by 

pollution) rich in dissolved nutrients with 

a seasonal deficiency in dissolved oxygen. 

Evaporation 

The process by which a liquid becomes a 

gas. 

Evapotranspiration 

The combined process of evaporation from 

the Earth’s surface and transpiration from 

vegetation. 

Exotic species 

See introduced species. 

Exposure 

The nature and degree to which a system is 

exposed to significant climatic variations. 

Externality 

See external cost. 

External cost 

Used to define the costs arising from any 

human activity, when the agent responsible 

for the activity does not take full account 

of the impacts on others of his or her 

actions. Equally, when the impacts are 

positive and not accounted for in the actions 

of the agent responsible they are referred to 

as external benefits. Emissions of particulate 

pollution from a power station affect the 

health of people in the vicinity, but this is 

not often considered, or is given inadequate 

weight, in private decision making and there 

is no market for such impacts. Such a 

phenomenon is referred to as an 

“externality,” and the costs it imposes are 

referred to as the external costs. 

Extinction 

The complete disappearance of an entire 

species. 

Extirpation 

The disappearance of a species from part of 

its range; local extinction. 

Extreme weather event 

An extreme weather event is an event that is 

rare within its statistical reference 

distribution at a particular place. Definitions 

of “rare” vary, but an extreme weather event 

would normally be as rare as or rarer than 

the 10th or 90th percentile. 

By definition, the characteristics of what is 

called extreme weather may vary from place 

to place. An extreme climate event is an 

average of a number of weather events over 

a certain period of time, an average which is 

itself extreme (e.g., rainfall over a season). 

F 

Food security 

6-6 
SAP 4.6 Glossary and Acronyms

A situation that exists when people have 

secure access to sufficient amounts of safe 

and nutritious food for normal growth, 

development and an active and healthy life. 

Food insecurity may be caused by the 

unavailability of food, insufficient 

purchasing power, inappropriate 

distribution, or inadequate use of food at the 

household level. 

Foodborne illness6

An illness caused by consuming foods or 

beverages contaminated with any of many 

different disease-causing microbes, or 

pathogens, or poisonous chemicals, or other 

harmful substances. 

Footprint (ecological)7

An index of the area of productive land and 

aquatic ecosystems required to produce the 

resources used and to assimilate the wastes 

produced by a defined population at a 

specified material standard of living, 

wherever on Earth that land may be located. 

Forecast 

See climate prediction and climate 

projection.

G 

General circulation 

The large scale motions of the atmosphere 

and the ocean as a consequence of 

differential heating on a rotating Earth, 

aiming to restore the energy balance of the 

system through transport of heat and 

momentum. 

General Circulation Model (GCM) 

See climate model. 

GIS (Geographic Information Systems)8

A computerized system organizing data sets 

through a geographical referencing of all 

data included in its collections. 

 

6

 Definition modified from the Centers for 

Disease Control and Prevention website: 

http://www.cdc.gov/ncidod/dbmd/diseaseinfo/fo

odborneinfections_g.htm, viewed on November 

21, 2007. 

7

 From the glossary of the Millenium Ecosystem 

Assessment, 2005. 

8

 From the glossary of the Millenium Ecosystem 

Assessment, 2005. 

Global surface temperature 

The global surface temperature is the areaweighted global average of (i) the sea 

surface temperature over the oceans (i.e., the 

sub-surface bulk temperature in the first few 

meters of the ocean), and (ii) the surface air 

temperature over land at 1.5 m above the 

ground. 

Globalization 

The growing integration and 

interdependence of countries worldwide 

through the increasing volume and variety of 

crossborder transactions in goods and 

services, free international capital flows, and 

the more rapid and widespread diffusion of 

technology, information and culture.

Greenhouse effect 

Greenhouse gases effectively absorb 

infrared radiation, emitted by the Earth’s 

surface, by the atmosphere itself due to the 

same gases, and by clouds. Atmospheric 

radiation is emitted to all sides, including 

downward to the Earth’s surface. Thus 

greenhouse gases trap heat within the 

surface-troposphere system. This is called 

the “natural greenhouse effect.” 

Atmospheric radiation is strongly coupled to 

the temperature of the level at which it is 

emitted. In the troposphere, the temperature 

generally decreases with height. Effectively, 

infrared radiation emitted to space originates 

from an altitude with a temperature of, on 

average, -19°C, in balance with the net 

incoming solar radiation, whereas the 

Earth’s surface is kept at a much higher 

temperature of, on average, +14°C. An 

increase in the concentration of greenhouse 

gases leads to an increased infrared opacity 

of the atmosphere, and therefore to an 

effective radiation into space from a higher 

altitude at a lower temperature. This causes 

a radiative forcing, an imbalance that can 

only be compensated for by an increase of 

the temperature of the surface-troposphere 

system. This is the “enhanced greenhouse 

effect.” 

Greenhouse gas 

Greenhouse gases are those gaseous 

constituents of the atmosphere, both natural 

and anthropogenic, that absorb and emit 

radiation at specific wavelengths within the 

6-7 
SAP 4.6 Glossary and Acronyms

spectrum of infrared radiation emitted by 

the Earth’s surface, the atmosphere, and 

clouds. This property causes the greenhouse 

effect. Water vapor (H2O), carbon dioxide 

(CO2), nitrous oxide (N2O), methane 

(CH4), and ozone (O3) are the primary 

greenhouse gases in the Earth’s atmosphere. 

Moreover there are a number of entirely 

human-made greenhouse gases in the 

atmosphere, such as the halocarbons and 

other chlorine- and bromine-containing 

substances, dealt with under the Montreal 

Protocol. Besides CO2, N2O, and CH4, the 

Kyoto Protocol deals with the greenhouse 

gases sulfur hexafluoride (SF6), 

hydrofluorocarbons (HFCs), and 

perfluorocarbons (PFCs). 

Gross Domestic Product 

Gross Domestic Product (GDP) is the 

monetary value of all goods and services 

produced within a nation.

Gross National Product 

Gross National Product (GNP) is the 

monetary value of all goods and services 

produced in a nation’s economy, including 

income generated abroad by domestic 

residents, but without income generated by 

foreigners.

Groundwater Recharge 

The process by which external water is 

added to the zone of saturation of an aquifer, 

either directly into a formation or indirectly 

by way of another formation.

H

Habitat 

The particular environment or place where 

an organism or species tend to live; a more 

locally circumscribed portion of the total 

environment. 

Hantavirus 

A virus in the family Bunyaviridae that 

causes a type of haemorrhagic fever. It is 

thought that humans catch the disease 

mainly from infected rodents, either through 

direct contact with the animals or by 

inhaling or ingesting dust that contains 

aerosolized viral particles from their dried 

urine and other secretions.

Healthy Cities Program9

The WHO Healthy Cities programme 

engages local governments in health 

development through a process of political 

commitment, institutional change, capacity 

building, partnership-based planning and 

innovative projects. It promotes 

comprehensive and systematic policy and 

planning with a special emphasis on health 

inequalities and urban poverty, the needs of 

vulnerable groups, participatory governance 

and the social, economic and environmental 

determinants of health. It also strives to 

include health considerations in economic, 

regeneration and urban development efforts.

Heat exhaustion10

Heat exhaustion is a phenomenon caused by 

fluid loss, which in turn causes decreased 

blood flow to vital organs. Reduced blood 

flow from heat exhaustion can result in a 

form of shock. Victims of heat exhaustion 

often complain of flu-like symptoms hours 

after exposure. 

Heat index11

The heat index (HI), given in degrees F, is a 

measure of how hot it feels when relative 

humidity (RH) is combined with the actual 

air temperature. 

Heat island 

An area within an urban area characterized 

by ambient temperatures higher than those 

of the surrounding area because of the 

absorption of solar energy by materials like 

asphalt. 

Heat stroke12

 

9

 Definition taken directly from 

http://www.euro.who.int/healthy-cities on 

November 21, 2007. 

10 Definition from the U.S. Environmental 

Protection Agency’s Heat Island Glossary, 

http://www.epa.gov/hiri/resources/glossary.html

#h, visited on November 21, 2007. 

11 Defintion modified from NOAA’s Heat Index 

website, 

http://www.crh.noaa.gov/jkl/?n=heat_index_calc

ulator, visited on November 21, 2007. 

12 Definition from the U.S. Environmental 

Protection Agency’s Heat Island Glossary, 

http://www.epa.gov/hiri/resources/glossary.html

#h, visited on November 21, 2007. 

6-8 
SAP 4.6 Glossary and Acronyms

Heat stroke occurs when the body's heat 

regulating mechanisms – including 

convection, sweating, and respiration – fail. 

The likelihood of heat stroke increases when 

air temperatures are higher than skin 

temperature, and when individuals are low 

on fluids. Body temperatures can be raised 

to the point at which brain damage and death 

can result unless cooling measures are 

quickly taken. 

Human settlement 

A place or area occupied by settlers. 

Human system 

Any system in which human organizations 

play a major role. Often, but not always, the 

term is synonymous with “society” 

or “social system” (e.g., agricultural system, 

political system, technological system, 

economic system). 

Hydrological systems 

The systems involved in movement, 

distribution, and quality of water throughout 

the Earth, including both the hydrologic 

cycle and water resources. 

Hyperthermia13

Unusually high body temperature. 

I

Ice sheet 

A mass of land ice that is sufficiently deep 

to cover most of the underlying bedrock 

topography, so that its shape is mainly 

determined by its internal dynamics (the 

flow of the ice as it deforms internally and 

slides at its base). An ice sheet flows 

outward from a high central plateau with a 

small average surface slope. The margins 

slope steeply, and the ice is discharged 

through fast-flowing ice streams or outlet 

glaciers, in some cases into the sea or into 

ice shelves floating on the sea. There are 

only two large ice sheets in the modern 

world, on Greenland and Antarctica, the 

 

 

13 The American Heritage® Dictionary of the 

English Language, Fourth Edition. Retrieved 

November 21, 2007, from Dictionary.com 

website: 

http://dictionary.reference.com/browse/hyperther

mia

Antarctic ice sheet being divided into East 

and West by the Transantarctic Mountains; 

during glacial periods there were others. 

Ice shelf 

A floating ice sheet of considerable 

thickness attached to a coast (usually of 

great horizontal extent with a level or gently 

undulating surface); often a seaward 

extension of ice sheets. 

(Climate) Impact assessment 

The practice of identifying and evaluating 

the detrimental and beneficial consequences 

of climate change on natural and human 

systems. 

(Climate) Impacts 

Consequences of climate change on natural 

and human systems. Depending on the 

consideration of adaptation, one can 

distinguish between potential impacts and 

residual impacts. Potential impacts: All 

impacts that may occur given a projected 

change in climate, without considering 

adaptation. Residual impacts: The impacts 

of climate change that would occur after 

adaptation. See also aggregate impacts, 

market impacts, and non-market impacts. 

Indicator14

Information based on measured data used to 

represent a particular attribute, 

characteristic, or property of a system. 

Indigenous peoples 

People whose ancestors inhabited a place or 

a country when persons from another culture 

or ethnic background arrived on the scene 

and dominated them through conquest, 

settlement, or other means and who today 

live more in conformity with their own 

social, economic, and cultural customs and 

traditions than those of the country of which 

they now form a part (also referred to as 

“native,” “aboriginal,” or “tribal” peoples). 

Industrial Revolution 

A period of rapid industrial growth with farreaching social and economic consequences, 

beginning in England during the second half 

of the 18th century and spreading to Europe 

and later to other countries including the 

14 Definition taken from the Millenium 

Ecosystem Assessment, Current State and 

Trends Assessment Glossary, 2005 

6-9 
SAP 4.6 Glossary and Acronyms

United States. The invention of the steam 

engine was an important trigger of this 

development. The Industrial Revolution 

marks the beginning of a strong increase in 

the use of fossil fuels and emission of, in 

particular, fossil carbon dioxide. In this 

report, the terms “pre-industrial” and 

“industrial” refer, somewhat arbitrarily, to 

the periods before and after the year 1750, 

respectively. 

Inertia 

Delay, slowness, or resistance in the 

response of the climate, biological, or 

human systems to factors that alter their rate 

of change, including continuation of change 

in the system after the cause of that change 

has been removed. 

Infectious diseases 

Any disease that can be transmitted from 

one person to another. This may occur by 

direct physical contact, by common handling 

of an object that has picked up infective 

organisms, through a disease carrier, or by 

spread of infected droplets coughed or 

exhaled into the air. 

Infrastructure 

The basic equipment, utilities, productive 

enterprises, installations, institutions, and 

services essential for the development, 

operation, and growth of an organization, 

city, or nation. For example, roads; schools; 

electric, gas, and water utilities; 

transportation; communication; and legal 

systems would be all considered as 

infrastructure. 

Integrated assessment 

A method of analysis that combines results 

and models from the physical, biological, 

economic, and social sciences, and the 

interactions between these components, in a 

consistent framework, to evaluate the status 

and the consequences of environmental 

change and the policy responses to it. 

Introduced species 

A species occurring in an area outside its 

historically known natural range as a result 

of accidental dispersal by humans (also 

referred to as “exotic species” or “alien 

species”). 

Invasive species 

An introduced species that invades natural 

habitats. 

IPCC15

A panel set up by the United Nations in 

1988 to review scientific information on 

climate change. This panel involves over 

2,000 of the world’s climate experts. Many 

of the climate change facts and future 

predictions we read about come from 

information reviewed by the IPCC. 

K

Kyoto Protocol 

The Kyoto Protocol was adopted at the 

Third Session of the Conference of the 

Parties (COP) to the UN Framework 

Convention on Climate Change (UNFCCC) 

in 1997 in Kyoto, Japan. It contains legally 

binding commitments, in addition to those 

included in the UNFCCC. Countries 

included in Annex B of the Protocol (most 

member countries of the Organisation for 

Economic Cooperation and Development 

(OECD) and those with economies in 

transition) agreed to reduce their 

anthropogenic greenhouse gas emissions 

(CO2, CH4, N2O, HFCs, PFCs, and SF6) by 

at least 5% below 1990 levels in the 

commitment period 2008 to 2012. The 

Kyoto Protocol entered into force on 16 

February 2005.

L 

La Niña 

See El Niño Southern Oscillation. 

Land use 

The total of arrangements, activities, and 

inputs undertaken in a certain land cover 

type (a set of human actions). The social and 

economic purposes for which land is 

managed (e.g., grazing, timber extraction, 

and conservation). 

Land-use change 

 

15 Definition taken from the Climate Change 

North Glossary at 

http://www.climatechangenorth.ca/H1_Glossary.

html on November 21, 2007. 

6-10 
SAP 4.6 Glossary and Acronyms

A change in the use or management of land 

by humans, which may lead to a change in 

land cover. Land cover and land-use change 

may have an impact on the albedo, 

evapotranspiration, sources, and sinks of 

greenhouse gases, or other properties of the 

climate system, and may thus have an impact 

on climate, locally or globally. 

Landslide 

A mass of material that has slipped downhill 

by gravity, often assisted by water when the 

material is saturated; rapid movement of a 

mass of soil, rock, or debris down a slope. 

Likelihood 

The likelihood of an occurrence, an outcome 

or a result, where this can be estimated 

probabilistically, is expressed in this Report 

using a standard terminology, defined in the 

Introduction. See also uncertainty and 

confidence.

Lyme disease 

A vector-borne disease caused by the 

spirochete Borrelia burgdorferi and 

transmitted by Ixodes ticks, commonly 

known as deer ticks. Symptoms include 

skin lesions, fatigue, fever, and chills, and if 

left untreated may later manifest itself in 

cardiac and neurological disorders, joint 

pain, and arthritis. 

M 

Maladaptation 

Any changes in natural or human systems 

that inadvertently increase vulnerability to 

climatic stimuli; an adaptation that does not 

succeed in reducing vulnerability but 

increases it instead. 

Malaria 

Endemic or epidemic parasitic disease 

caused by species of the genus Plasmodium 

(protozoa) and transmitted by mosquitoes 

of the genus Anopheles; produces high fever 

attacks and systemic disorders, and kills 

approximately 2 million people every year. 

Market barriers 

In the context of mitigation of climate 

change, conditions that prevent or impede 

the diffusion of cost-effective technologies 

or practices that would mitigate greenhouse 

gas emissions. 

Market-based incentives 

Measures intended to use price mechanisms 

(e.g., taxes and tradable permits) to reduce 

greenhouse gas emissions. 

Market impacts 

Impacts that are linked to market 

transactions and directly affect Gross 

Domestic Product (a country’s national 

accounts)—for example, changes in the 

supply and price of agricultural goods. See 

also non-market impacts. 

Mitigation 

An anthropogenic intervention to reduce the 

sources or enhance the sinks of greenhouse 

gases. 

Mitigative capacity 

The social, political, and economic 

structures and conditions that are required 

for effective mitigation. 

Morbidity 

Rate of occurrence of disease or other health 

disorder within a population, taking account 

of the age-specific morbidity rates. Health 

outcomes include chronic disease 

incidence/prevalence, rates of 

hospitalization, primary care consultations, 

disability-days (i.e., days when absent from 

work), and prevalence of symptoms. 

Mortality 

Rate of occurrence of death within a 

population within a specified time period; 

calculation of mortality takes account of 

age-specific death rates, and can thus yield 

measures of life expectancy and the extent 

of premature death. 

N 

Nitrogen oxides16

Compounds of nitrogen and oxygen 

produced by the burning of fossil fuels. 

No-regrets opportunities 

See no-regrets policy. 

No-regret options 

 

16 Definition from 

www.eia.doe.gov/oiaf/1605/95report/glossary.ht

ml visited on November 21, 2007. 

6-11 
SAP 4.6 Glossary and Acronyms

See no-regrets policy. 

No-regrets policy 

One that would generate net social benefits 

whether or not there is climate change. Noregrets opportunities for greenhouse gas 

emissions reduction are defined as those 

options whose benefits such as reduced 

energy costs and reduced emissions of 

local/regional pollutants equal or exceed 

their costs to society, excluding the benefits 

of avoided climate change. No-regrets 

potential is defined as the gap between the 

market potential and the socio-economic 

potential. 

Non-linearity 

A process is called “non-linear” when there 

is no simple proportional relation between 

cause and effect. The climate system 

contains many such non-linear processes, 

resulting in a system with a potentially very 

complex behavior. Such complexity may 

lead to rapid climate change. 

Non-market impacts 

Impacts that affect ecosystems or human 

welfare, but that are not directly linked to 

market transactions—for example, an 

increased risk of premature death. See also 

market impacts. 

North Atlantic Oscillation (NAO) 

The North Atlantic Oscillation consists of 

opposing variations of barometric pressure 

near Iceland and near the Azores. On 

average, a westerly current, between the 

Icelandic low pressure area and the Azores 

high pressure area, carries cyclones with 

their associated frontal systems towards 

Europe. However, the pressure difference 

between Iceland and the Azores fluctuates 

on time scales of days to decades, and can 

be reversed at times. It is the dominant 

mode of winter climate variability in the 

North Atlantic region, ranging from central 

North America to Europe. 

O 

Ocean conveyor belt 

The theoretical route by which water 

circulates around the entire global ocean, 

driven by wind and the thermohaline 

circulation. 

Opportunity 

An opportunity is a situation or 

circumstance to decrease the gap between 

the market potential of any technology or 

practice and the economic potential, socioeconomic potential, or technological 

potential. 

Opportunity costs 

The cost of an economic activity forgone by 

the choice of another activity. 

Ozone (O3) 

Ozone, the triatomic form of oxygen (O3), is 

a gaseous atmospheric constituent. In the 

troposphere it is created both naturally and 

by photochemical reactions involving gases 

resulting from human activities 

(photochemical “smog”). In high 

concentrations, tropospheric ozone can be 

harmful to a wide-range of living organisms. 

Tropospheric ozone acts as a greenhouse 

gas. In the stratosphere, ozone is created by 

the interaction between solar ultraviolet 

radiation and molecular oxygen (O2). 

Stratospheric ozone plays a decisive role in 

the stratospheric radiative balance. Its 

concentration is highest in the ozone layer. 

Depletion of stratospheric ozone, due to 

chemical reactions that may be enhanced by 

climate change, results in an increased 

ground-level flux of ultraviolet-B radiation. 

See also Montreal Protocol and ozone layer. 

P 

Parameterization 

In climate models, this term refers to the 

technique of representing processes, that 

cannot be explicitly resolved at the spatial or 

temporal resolution of the model (sub-grid 

scale processes), by relationships between 

the area- or time-averaged effect of such 

sub-grid-scale processes and the larger scale 

flow. 

Pareto criterion/Pareto optimum 

A requirement or status that an individual’s 

welfare could not be further improved 

without making others in the society worse 

off. 

6-12 
SAP 4.6 Glossary and Acronyms

Particulates 

Very small solid exhaust particles emitted 

during the combustion of fossil and biomass 

fuels. Particulates may consist of a wide 

variety of substances. Of greatest concern 

for health are particulates of less than or 

equal to 10nm and 2.5 nm in diameter, 

usually designated as PM10 and PM2.5, 

respectively.

Pathogen17

An agent that causes disease, especially a 

living microorganism such as a bacterium or 

fungus. 

Permafrost 

Perennially frozen ground that occurs 

wherever the temperature remains below 

0°C for several years. 

Photochemical smog 

A mix of photochemical oxidant air 

pollutants produced by the reaction of 

sunlight with primary air pollutants, 

especially hydrocarbons.

Point-source pollution 

Pollution resulting from any confined, 

discrete source, such as a pipe, ditch, tunnel, 

well, container, concentrated animal feeding 

operation, or floating craft. See also nonpoint-source pollution. 

Present value cost 

The sum of all costs over all time periods, 

with future costs discounted. 

Projection (generic) 

A projection is a potential future evolution 

of a quantity or set of quantities, often 

computed with the aid of a model. 

Projections are distinguished from 

“predictions” in order to emphasize that 

projections involve assumptions concerning, 

for example, future socio-economic and 

technological developments that may or may 

not be realized, and are therefore subject to 

substantial uncertainty. See also climate 

projection and climate prediction. 

Proxy 

 17 The American Heritage® Dictionary of the 

English Language, Fourth Edition. Retrieved 

November 21, 2007, from Dictionary.com 

website: 

http://dictionary.reference.com/browse/pathogen 

A proxy climate indicator is a local record 

that is interpreted, using physical and 

biophysical principles, to represent some 

combination of climate-related variations 

back in time. Climate-related data derived in 

this way are referred to as proxy data. 

Examples of proxies are tree ring records, 

characteristics of corals, and various data 

derived from ice cores. 

Q 

QALY (Quality Adjusted Life Year)18

A measure of the outcome of actions (either 

individual or treatment interventions) in 

terms of their health impact. If an action 

gives a person an extra year of healthy life 

expectancy, that counts as one QALY. If an 

action gives a person an extra year of 

unhealthy life expectancy (partly disabled or 

in some distress), it has a value of less than 

one. Death is rated at zero. 

Quality of Life19

A scientific measure of personal well-being. 

Categories used to define place-specific 

quality of life include the inter-related 

categories of economic conditions; natural 

resources, environment, and amenities; 

human health; public and private 

infrastructure; government and public 

safety; and social and cultural resources. 

R 

Radiative forcing 

Radiative forcing is the change in the net 

vertical irradiance (expressed in Wm-2) at 

the tropopause due to an internal change or 

a change in the external forcing of the 

climate system, such as, for example, a 

change in the concentration of carbon 

dioxide or the output of the Sun. Usually 

radiative forcing is computed after allowing 

18 Definition taken from 

http://www.aihw.gov.au/publications/health/ah9

6/ah96-x04.html visited on November 21, 2007. 

19 Definition modified from text within Chapter 5 

of this document. 

6-13 
SAP 4.6 Glossary and Acronyms

for stratospheric temperatures to readjust to 

radiative equilibrium, but with all 

tropospheric properties held fixed at their 

unperturbed values. 

Range shifts 

Climate change-induced changes in the 

geographical distributions of plants, animals 

and ecosystems 

Rapid climate change 

The non-linearity of the climate system may 

lead to rapid climate change, sometimes 

called abrupt events or even surprises. Some 

such abrupt events may be imaginable, such 

as a dramatic reorganization of the 

thermohaline circulation, rapid deglaciation, 

or massive melting of permafrost leading to 

fast changes in the carbon cycle. Others may 

be truly unexpected, as a consequence of a 

strong, rapidly changing, forcing of a nonlinear system. 

Reference scenario 

See baseline/reference. 

Reinsurance 

The transfer of a portion of primary 

insurance risks to a secondary tier of 

insurers (reinsurers); essentially “insurance 

for insurers.” 

Relative sea level 

Sea level measured by a tide gauge with 

respect to the land upon which it is situated. 

See also Mean Sea Level. 

Revealed preference20

The use of the value of expenditure to 

"reveal" the preference of a consumer or 

group of consumers for the bundle of goods 

they purchase compared to other bundles of 

equal or smaller value. 

Reservoir 

A component of the climate system, other 

than the atmosphere, that has the capacity to 

store, accumulate or release a substance of 

concern (e.g., carbon or a greenhouse gas). 

Oceans, soils, and forests are examples of 

carbon reservoirs. The term also means an 

artificial or natural storage place for water, 

such as a lake, pond or aquifer, from which 

 

 

20 Definition http://wwwpersonal.umich.edu/~alandear/glossary/r.html 

visited on November 21, 2007. 

the water may be withdrawn for such 

purposes as irrigation or water supply.

Resilience 

Amount of change a system can undergo 

without changing state. 

Response time 

The response time or adjustment time is the 

time needed for the climate system or its 

components to re-equilibrate to a new state, 

following a forcing resulting from external 

and internal processes or feedbacks. It is 

very different for various components of the 

climate system. The response time of the 

troposphere is relatively short, from days to 

weeks, whereas the stratosphere comes into 

equilibrium on a time scale of typically a 

few months. Due to their large heat capacity, 

the oceans have a much longer response 

time, typically decades, but up to centuries 

or millennia. The response time of the 

strongly coupled surface-troposphere system 

is, therefore, slow compared to that of the 

stratosphere, and mainly determined by the 

oceans. The biosphere may respond fast 

(e.g., to droughts), but also very slowly to 

imposed changes. See lifetime for a 

different definition of response time 

pertinent to the rate of processes affecting 

the concentration of trace gases. 

Rodent-borne disease21

Disease that is transmitted between hosts by 

a rodent (e.g. bubonic plague, hantavirus). 

Runoff 

That part of precipitation that does not 

evaporate and is not transpired. 

S 

Salinization 

The accumulation of salts in soils.

Salmonella22

21 Definition modified from definition of vectorborne disease. 

22 Definition modified from information on the 

CDC’s website: 

http://www.cdc.gov/ncidod/dbmd/diseaseinfo/sal

monellosis_g.htm#What%20sort%20of%20germ

%20is%20Salmonella visited on November 21, 

2007. 

6-14 
SAP 4.6 Glossary and Acronyms

There are many different kinds of 

Salmonella bacteria. They pass from the 

feces of people or animals to other people or 

other animals and can cause diarrheal illness 

in humans. Salmonella has been known to 

cause illness for over 100 years. They were 

discovered by a American scientist named 

Salmon, for whom they are named.

Saltwater intrusion/encroachment 

Displacement of fresh surface water or 

ground water by the advance of saltwater 

due to its greater density, usually in coastal 

and estuarine areas. 

Scenario (generic) 

A plausible and often simplified description 

of how the future may develop, based on a 

coherent and internally consistent set 

of assumptions about key driving forces 

(e.g., rate of technology change, prices) and 

relationships. Scenarios are neither 

predictions nor forecasts and sometimes 

may be based on a “narrative storyline.” 

Scenarios may be derived from projections, 

but are often based on additional 

information from other sources. See also 

SRES scenarios, climate scenario, and 

emission scenarios. 

Sea-level rise 

An increase in the mean level of the ocean. 

Eustatic sea-level rise is a change in global 

average sea level brought about by an 

alteration to the volume of the world ocean. 

Relative sealevel rise occurs where there is a 

net increase in the level of the ocean relative 

to local land movements. Climate modelers 

largely concentrate on estimating eustatic 

sea-level change. Impact researchers focus 

on relative sea-level change. 

Seawall 

A human-made wall or embankment along a 

shore to prevent wave erosion. 

Semi-arid regions 

Ecosystems that have more than 250 mm 

precipitation per year but are not highly 

productive; usually classified as rangelands. 

Sensitivity 

Sensitivity is the degree to which a system is 

affected, either adversely or beneficially, by 

climate-related stimuli. The effect may be 

direct (e.g., a change in crop yield in 

response to a change in the mean, range, or 

variability of temperature) or indirect 

(e.g., damages caused by an increase in the 

frequency of coastal flooding due to sealevel rise). See also climate sensitivity. 

Sequential decision making 

Stepwise decision making aiming to identify 

short-term strategies in the face of long-term 

uncertainties, by incorporating additional 

information over time and making midcourse corrections. 

Sequestration 

The process of increasing the carbon content 

of a carbon reservoir other than the 

atmosphere. Biological approaches to 

sequestration include direct removal of 

carbon dioxide from the atmosphere through 

land-use change, afforestation, 

reforestation, and practices that enhance soil 

carbon in agriculture. Physical approaches 

include separation and disposal of carbon 

dioxide from flue gases or from processing 

fossil fuels to produce hydrogen- and carbon 

dioxide-rich fractions and longterm storage 

in underground in depleted oil and gas 

reservoirs, coal seams, and saline aquifers. 

See also uptake. 

Sink 

Any process, activity or mechanism that 

removes a greenhouse gas, an aerosol, or a 

precursor of a greenhouse gas or aerosol 

from the atmosphere. 

Smog23

Air pollution typically associated with 

oxidants. 

Snowpacks 

A seasonal accumulation of slow-melting 

snow. 

Social cost 

The social cost of an activity includes the 

value of all the resources used in its 

provision. Some of these are priced and 

others are not. Non-priced resources are 

referred to as externalities. It is the sum of 

the costs of these externalities and the priced 

 

23 Definition from The U.S. EPA’s Terms of 

Environment Glossary at 

http://www.epa.gov/OCEPAterms/sterms.html 

visited on November 21, 2007. 

6-15 
SAP 4.6 Glossary and Acronyms

resources that makes up the social cost. See 

also private cost and total cost. 

Social indicators24

Broad, standardized measures of the quality 

of life or other socio-economic conditions of 

geographic areas such as nations, 

metropolitan areas, or other areas; used to 

assess health conditions, educational levels, 

food availability, violence, and other 

conditions.

Socio-economic scenarios 

Scenarios concerning future conditions in 

terms of population, Gross Domestic 

Product and other socio-economic factors 

relevant to understanding the implications of 

climate change. See SRES scenarios.

Source 

Any process, activity, or mechanism that 

releases a greenhouse gas, an aerosol, or a 

precursor of a greenhouse gas or aerosol 

into the atmosphere. 

Southern Oscillation 

See El Niño Southern Oscillation. 

Spatial and temporal scales 

Climate may vary on a large range of spatial 

and temporal scales. Spatial scales may 

range from local (less than 100,000 km2), 

through regional (100,000 to 10 million 

km2) to continental (10 to 100 million km2). 

Temporal scales may range from seasonal to 

geological (up to hundreds of millions of 

years). 

SRES scenarios 

SRES scenarios are emissions scenarios 

developed by Nakicenovic et al. (2000) and 

used, among others, as a basis for the 

climate projections in the IPCC WGI 

contribution to the Third Assessment Report 

(IPCC, 2001a). The following terms are 

relevant for a better understanding of the 

structure and use of the set of SRES 

scenarios: 

(Scenario) Family: Scenarios that have a 

similar demographic, societal, economic, 

and technical-change storyline. Four 

scenario families comprise the SRES 

scenario set: A1, A2, B1, and B2. 

 

24 Definition from 

http://srmdc.net/glossary.htm#s visited on 

November 21, 2007. 

(Scenario) Group: Scenarios within a 

family that reflect a consistent variation of 

the storyline. The A1 scenario family 

includes four groups designated as A1T, 

A1C, A1G, and A1B that explore alternative 

structures of future energy systems. 

In the Summary for Policymakers of 

Nakicenovic et al (2000), the A1C and A1G 

groups have been combined into one 

“Fossil-Intensive” A1FI scenario group. The 

other three scenario families consist of one 

group each. The SRES scenario set reflected 

in the Summary for Policymakers of 

Nakicenovic et al. (2000) thus consist of six 

distinct scenario groups, all of which are 

equally sound and together capture the range 

of uncertainties associated with driving 

forces and emissions. 

Illustrative Scenario: A scenario that is 

illustrative for each of the six scenario 

groups reflected in the Summary for 

Policymakers of Nakicenovic et al. (2000). 

They include four revised scenario markers 

for the scenario groups A1B, A2, B1, B2, 

and two additional scenarios for the A1FI 

and A1T groups. All scenario groups are 

equally sound. 

(Scenario) Marker: A scenario that was 

originally posted in draft form on the SRES 

website to represent a given scenario family. 

The choice of markers was based on which 

of the initial quantifications best reflected 

the storyline, and the features of specific 

models. Markers are no more likely than 

other scenarios, but are considered by the 

SRES writing team as illustrative of a 

particular storyline. They are included in 

revised form in Nakicenovic et al. (2000). 

These scenarios have received the closest 

scrutiny of the entire writing team and via 

the SRES open process. Scenarios have also 

been selected to illustrate the other two 

scenario groups. 

(Scenario) Storyline: A narrative 

description of a scenario (or family of 

scenarios) highlighting the main scenario 

characteristics, relationships between key 

driving forces, and the dynamics of their 

evolution. 

Stabilization 

6-16 
SAP 4.6 Glossary and Acronyms

The achievement of stabilization of 

atmospheric concentrations of one or more 

greenhouse gases (e.g., carbon dioxide or a 

CO2-equivalent basket of greenhouse 

gases). 

Stakeholder 

A person or an organization that has a 

legitimate interest in a project or entity, or 

would be affected by a particular action or 

policy. 

Stated preference25

Stated preference approaches, sometimes 

referred to as direct valuation approaches, 

are survey methods that estimate the value 

individuals place on particular non-market 

goods based on choices they make in 

hypothetical markets 

Stimuli (climate-related) 

All the elements of climate change, 

including mean climate characteristics, 

climate variability, and the frequency and 

magnitude of extremes. 

Storm surge 

The temporary increase, at a particular 

locality, in the height of the sea due to 

extreme meteorological conditions (low 

atmospheric pressure and/or strong winds). 

The storm surge is defined as being the 

excess above the level expected from the 

tidal variation alone at that time and place. 

Storyline 

See SRES scenarios. 

Streamflow 

Water within a river channel, usually 

expressed in m3 sec-1. 

Stratosphere 

The highly stratified region of the 

atmosphere above the troposphere 

extending from about 10 km (ranging from 9 

km in high latitudes to 16 km in the tropics 

on average) to about 50 km. 

Submergence 

A rise in the water level in relation to the 

land, so that areas of formerly dry land 

become inundated; it results either from a 

sinking of the land or from a rise of the 

water level. 

Subsidence 

 

25 Definition taken from SAP 4.6. 

The sudden sinking or gradual downward 

settling of the Earth’s surface with little or 

no horizontal motion. 

Subsidy 

Direct payment from the government to an 

entity, or a tax reduction to that entity, for 

implementing a practice the government 

wishes to encourage. Greenhouse gas 

emissions can be reduced by lowering 

existing subsidies that have the effect of 

raising emissions, such as subsidies to fossilfuel use, or by providing subsidies for 

practices that reduce emissions or enhance 

sinks (e.g., for insulation of buildings or 

planting trees). 

Sustainable development 

Development that meets the needs of the 

present without compromising the ability of 

future generations to meet their own needs. 

T 

Technology 

A piece of equipment or a technique for 

performing a particular activity. 

Thermal erosion 

The erosion of ice-rich permafrost by the 

combined thermal and mechanical action of 

moving water. 

Thermal expansion 

In connection with sea level, this refers to 

the increase in volume (and decrease in 

density) that results from warming water. A 

warming of the ocean leads to an expansion 

of the ocean volume and hence an increase 

in sea level. 

Thermohaline circulation 

Large-scale density-driven circulation in the 

ocean, caused by differences in temperature 

and salinity. In the North Atlantic, the 

thermohaline circulation consists of warm 

surface water flowing northward and cold 

deepwater flowing southward, resulting in a 

net poleward transport of heat. The surface 

water sinks in highly restricted sinking 

regions located in high latitudes. 

Threshold 

The level of magnitude of a system process 

at which sudden or rapid change occurs. A 

point or level at which new properties 

6-17 
SAP 4.6 Glossary and Acronyms

emerge in an ecological, economic or other 

system, invalidating predictions based on 

mathematical relationships that apply at 

lower levels.

Time-series studies26

Studies done using a set of data that 

expresses a particular variable measured 

over time. 

Top-down models 

The terms “top” and “bottom” are shorthand 

for aggregate and disaggregated models. The 

top-down label derives from how modelers 

applied macro-economic theory and 

econometric techniques to historical data on 

consumption, prices, incomes, and factor 

costs to model final demand for goods and 

services, and supply from main sectors, like 

the energy sector, transportation, agriculture, 

and industry. Therefore, top-down models 

evaluate the system from aggregate 

economic variables, as compared to bottomup models that consider technological 

options or project specific climate change 

mitigation policies. Some technology data 

were, however, integrated into top-down 

analysis and so the distinction is not that 

clear-cut. 

Total cost 

All items of cost added together. The total 

cost to society is made up of both the 

external cost and the private cost, which 

together are defined as social cost.

Trade effects 

Economic impacts of changes in the 

purchasing power of a bundle of exported 

goods of a country for bundles of goods 

imported from its trade partners. Climate 

policies change the relative production costs 

and may change terms of trade substantially 

enough to change the ultimate economic 

balance. 

Transient climate response 

The globally averaged surface air 

temperature increase, averaged over a 20-

year period, centered at the time of CO2 

doubling (i.e., at year 70 in a 1% per year 

 

26 Definition modified from the definition of 

time-series data from the Millennium Ecosystem 

Assessment, 2005. 

compound CO2 increase experiment with a 

global coupled climate model). 

Troposphere 

The lowest part of the atmosphere from the 

surface to about 10 km in altitude in midlatitudes (ranging from 9 km in high 

latitudes to 16 km in the tropics on average) 

where clouds and “weather” phenomena 

occur. In the troposphere, temperatures 

generally decrease with height. 

Tundra 

A treeless, level, or gently undulating plain 

characteristic of arctic and subarctic regions. 

U 

Uncertainty 

An expression of the degree to which a 

value (e.g., the future state of the climate 

system) is unknown. Uncertainty can result 

from lack of information or from 

disagreement about what is known or even 

knowable. It may have many types of 

sources, from quantifiable errors in the data 

to ambiguously defined concepts or 

terminology, or uncertain projections of 

human behavior. Uncertainty can therefore 

be represented by quantitative measures 

(e.g., a range of values calculated by various 

models) or by qualitative statements (e.g., 

reflecting the judgment of a team of 

experts). See Moss and Schneider (2000). 

See also confidence and likelihood. 

Unique and threatened systems 

Entities that are confined to a relatively 

narrow geographical range but can affect 

other, often larger entities beyond their 

range; narrow geographical range points to 

sensitivity to environmental variables, 

including climate, and therefore attests to 

potential vulnerability to climate change. 

United Nations Framework Convention 

on Climate Change (UNFCCC) 

The Convention was adopted on 9 May 

1992, in New York, and signed at the 1992 

Earth Summit in Rio de Janeiro by more 

than 150 countries and the European 

Community. Its ultimate objective is the 

‘stabilization of greenhouse gas 

concentrations in the atmosphere at a level 

6-18 
SAP 4.6 Glossary and Acronyms

that would prevent dangerous anthropogenic 

interference with the climate system’. It 

contains commitments for all Parties. Under 

the Convention, Parties included in Annex I 

aim to return greenhouse gas emissions not 

controlled by the Montreal Protocol to 1990 

levels by the year 2000. The Convention 

entered in force in March 1994. See also 

Kyoto Protocol.

Urban Heat Island Effect27

The urban heat island effect is a measurable 

increase in ambient urban air temperatures 

resulting primarily from the replacement of 

vegetation with buildings, roads, and other 

heat-absorbing infrastructure. The heat 

island effect can result in significant 

temperature differences between rural and 

urban areas. 

Urbanization 

The conversion of land from a natural state 

or managed natural state (such as 

agriculture) to cities; a process driven by net 

rural-to-urban migration through which an 

increasing percentage of the population in 

any nation or region come to live in 

settlements that are defined as “urban 

centers”. 

V 

Valley Fever (Coccidiomycosis)28

An infectious respiratory disease of humans 

and other animals caused by inhaling the 

fungus Coccidioides immitis. It is 

characterized by fever and various 

respiratory symptoms. Also called 

coccidiomycosis. 

Valuation29

 

 

27 Definition from the U.S. Environmental 

Protection Agency’s Heat Island Glossary, 

http://www.epa.gov/hiri/resources/glossary.html

#h, visited on November 21, 2007. 

28 The American Heritage® Dictionary of the 

English Language, Fourth Edition. Retrieved 

November 21, 2007, from Dictionary.com 

website: 

http://dictionary.reference.com/browse/valley 

fever. 29 Definition taken from the glossary of the 

Millenium Ecosystem Assessment, 2005. 

The process of expressing a value for a 

particular good or service in a certain 

context (e.g., of decision-making) usually in 

terms of something that can be counted, 

often money, but also through methods and 

measures from other disciplines (sociology, 

ecology, and so on). See also Values. 

Value added 

The net output of a sector after adding up all 

outputs and subtracting intermediate inputs. 

Value of a statistical life (VSL)30

The sum of what people would pay to 

reduce their risk of dying by small amounts 

that, together, add up to one statistical life.

Values 

Worth, desirability, or utility based on 

individual preferences. The total value of 

any resource is the sum of the values of the 

different individuals involved in the use of 

the resource. The values, which are the 

foundation of the estimation of costs, 

are measured in terms of the willingness to 

pay (WTP) by individuals to receive the 

resource or by the willingness of individuals 

to accept payment (WTA) to part with the 

resource. 

Vector 

An organism, such as an insect, that 

transmits a pathogen from one host to 

another. See also vector-borne diseases. 

Vector-borne diseases 

Disease that is transmitted between hosts by 

a vector organism such as a mosquito or tick 

(e.g., malaria, dengue fever, and 

leishmaniasis). 

Volatile Organic Compounds (VOCs)31

Organic compounds that evaporate readily 

into the air. VOCs include substances such 

as benzene, toluene, methylene chloride, and 

methyl chloroform.

Vulnerability 

The degree to which a system is susceptible 

to, or unable to cope with, adverse effects of 

climate change, including climate variability 

and extremes. Vulnerability is a function of 

the character, magnitude, and rate of climate 

30 Definition taken from SAP4.6. 

31 Definition from ATSDR’s Glossary of Terms 

at http://www.atsdr.cdc.gov/glossary.html#G-Tvisited on November 21, 2007. 

6-19 
SAP 4.6 Glossary and Acronyms

variation to which a system is exposed, its 

sensitivity, and its adaptive capacity. 

collective basis. The constituents of wellbeing are commonly considered to include 

materials to satisfy basic needs, freedom and 

choice, health, good social relations, and W 

security.

Well-being 34

Water consumption A context- and situation-dependent state, 

comprising basic material for a good life, 

freedom and choice, health and bodily wellbeing, good social relations, security, peace 

of mind, and spiritual experience. 

Amount of extracted water irretrievably lost 

during its use (by evaporation and goods 

production).Water consumption is equal to 

water withdrawal minus return flow.

Water stress West Nile virus35

A country is water-stressed if the available 

freshwater supply relative to water 

withdrawals acts as an important constraint 

on development. Withdrawals exceeding 

20% of renewable water supply has been 

used as an indicator of water stress. 

West Nile virus (WNV) is a single-stranded 

RNA virus of the family Flaviviridae, genus 

Flavivirus. The main lifecycle of WNV is 

between birds and insects. Humans are most 

often infected by a bite from an infected 

mosquito. Most people infected with WNV 

don’t show any symptoms, whereas those 

that do are often diagnosed with West Nile 

Fever which can last up to two weeks. 

Water-use efficiency 

Carbon gain in photosynthesis per unit water 

lost in evapotranspiration. It can be 

expressed on a short-term basis as the ratio 

of photosynthetic carbon gain per unit 

transpirational water loss, or on a seasonal 

basis as the ratio of net primary production 

or agricultural yield to the amount of 

available water. 

Z 

Zoonoses 

Diseases and infections which are naturally 

transmitted between vertebrate animals and 

people. See also zoonotic disease.

Water withdrawal 

Amount of water extracted from water 

bodies. Zoonotic disease 

Waterborne diseases32 A disease that normally exists in other 

vertebrates but also infects humans, such as 

dengue fever, avian flu, west Nile virus and 

bubonic plague. 

Diseases contracted through contact with 

water that is infected with any of numerous 

pathogens including Vibrio cholerae, 

Campylobacter, Salmonella, Shigella, and 

the diarrheogenic Escherichia coli.

Watershed33

The land area that drains into a particular 

watercourse or body of water. Sometimes 

used to describe the dividing line of high 

ground between two catchment basins. 

Welfare 

An economic term used to describe the state 

of well-being of humans on an individual or 

 32 Definition modified from information on 

CDC’s website 

http://www.cdc.gov/ncidod/dbmd/diseaseinfo/wa

terbornediseases_t.htm visited on November 21, 

2007. 

34 Definition modified from the Millenium 

Ecosystem Assessment, Current State and 

Trends Assessment Glossary, 2005 

35 Definition modified from information on 

http://www.cdc.gov/ncidod/dvbid/westnile/index

.htm 

33 Definition taken from the glossary of the 

Millenium Ecosystem Assessment, 2005. 

6-20 
SAP 4.6 Glossary and Acronyms

6.2 Acronyms 

AAG Association of American Geographers 

AAP American Academy of Pediatrics 

AIACC Assessment of Impacts and Adaptations to Climate Change 

AMR-A North American Region 

CCP ICLEI’s Cities for Climate Protection 

CCSP Climate Change Science Program 

CDC Center for Disease Control 

CLIMB Climate’s Long-Term Impacts on Metro Boston 

CO2 Carbon Dioxide 

CVD Cardiovascular Disease 

DHS Department of Homeland Security 

ECHAM4 

A model named after the European Centre for Medium Range Weather Forecasts 

(ECMRWF), (giving it the first part of the name – EC), which was developed in 

Hamburg (HAM) 

ENSO El Niño/Southern Oscillation 

EPA Environmental Protection Agency 

FDA Food and Drug Administration 

FEMA Federal Emergency Management Agency 

GCM General Circulation Model 

GDP Gross Domestic Product 

GIS Geographic Information Systems 

GISS NASA Goddard Institute for Space Studies 

ICLEI International Council for Local Environmental Initiatives 

IPCC Intergovernmental Panel on Climate Change 

MA Millennium Assessment 

MM5 Mesoscale Model 

MSA Metropolitan Statistical Areas 

NAAQS National Ambient Air Quality Standards 

NACC U.S. National Assessment of Climate Change 

NAS National Academy of Sciences 

NAST National Assessment Synthesis Team 

NEG/ECP New England Governors and Eastern Canadian Premiers 

NGO Non-Governmental Organization 

NO Nitric oxide 

NOAA National Oceanic and Atmospheric Administration 

NRC National Research Council 

NYCHP New York Climate and Health Project 

PM Particulate Matter 

PM2.5 Particulate Matter (smaller than 2.5 micrometers) 

PTSD Post-Traumatic Stress Disorder 

RADM2 Regional Acid Deposition Model, Version 2 

RCM Regional Climate Model 

RMNP Rocky Mountain National Park 

SAP Synthesis and Assessment Products 

SRES Special Report on Emissions Scenarios 

TBE Tick-borne Encephalitis 

6-21 
SAP 4.6 Glossary and Acronyms

UHI Urban Heat Island Effect 

UNDP United Nations Development Programme 

UNEP United Nations Environmental Programme 

U.S. BEA United States Bureau of Economic Analysis 

USDA U.S. Department of Agriculture 

USGCRP United States Global Change Research Program 

VBZ Vector Born and Zoonotic 

VEMAP Virtual Earth Map 

VOC Volatile Organic Matter 

VSL Value of Statistical Life 

WHO World Health Organization 

WTP Willingness to Pay 

6-22 
Contact Information 

Global Change Research Information Office 

c/o Climate Change Science Program Office 

1717 Pennsylvania Avenue, NW 

Suite 250 

Washington, DC 20006 

202-223-6262 (voice) 

202-223-3065 (fax) 

The Climate Change Science Program 

incorporates the U.S. Global Change 

Research Program and the Climate Change 

Research Initiative. 

To obtain a copy of this document, place an 

order at the Global Change Research 

Information Office (GCRIO) web site: 

http://www.gcrio.org/orders

Climate Change Science Program and 

The Subcommittee on Global Change Research 

William J. Brennan, Chair 

Department of Commerce 

National Oceanic and Atmospheric Administration 

Acting Director, Climate Change Science Program 

Jack Kaye, Vice Chair 

National Aeronautics and Space Administration 

Allen Dearry 

Department of Health and Human Services 

Anna Palmisano

Department of Energy 

Mary Glackin 

National Oceanic and Atmospheric Administration 

Patricia Gruber 

Department of Defense 

William Hohenstein 

Department of Agriculture 

Linda Lawson 

Department of Transportation 

Mark Myers 

U.S. Geological Survey 

Jarvis Moyers 

National Science Foundation 

Patrick Neale 

Smithsonian Institution 

Jacqueline Schafer 

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Environmental Protection Agency 

Harlan Watson 

Department of State 

Executive Office and other Liaisons 

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Office of Management and Budget 

Stephen Eule 

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Director, Climate Change Technology Program 

Katharine Gebbie 

National Institute of Standards & Technology 

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Bob Rainey 

Council on Environmental Quality 

Gene Whitney 

Office of Science and Technology Policy