Climate Change Risk, Stress, and Adaptation Sammy Zahran, PhD Assistant Professor Colorado State Uni

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Climate Change Risk, Stress, and
AdaptationSammy Zahran, PhDAssistant
ProfessorColorado State University
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Discussion Outline

• Introduction and Problem Statement
• The Cities for Climate Protection Campaign
• Collective Action and Selective Incentives
• Variable Operations and Data Sources
• Logistic Regression and Scatter Plot
• Conclusion

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Climate Change Risks

• Climate change risks are social, economic, and
  ecological.
• Risks are distributed unevenly by geography.
• Risks are selectively harmful to coastal,
  maritime and low-lying island societies.
• Risks are potentially beneficial.
• Government willingness to participate in policy
  solutions to mitigate and adapt to climate change
  risks may be explained by these geographic
  specific impacts.

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Climate Planning Risks

• Climate policies designed to stabilize CO2
  emissions.
• Climate policies distribute costs and benefits
  unevenly by geography.
• The willingness of a government to support a
  climate policy solution may be partially
  determined by the relative distribution of costs
  and benefits that accompany policy action.

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Local Climate Planning

• 100 U.S. localities joined the Cities for
  Climate Protection (CCP) campaign sponsored by
  the International Council for Local Environmental
  Initiatives (ICLEI).
• ICLEI coordinates mitigation efforts of 700
  municipalities globally.
• Localities recognize climate change as a
  significant local concern, and commit to
  reduction of local GHG emissions.

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The Rationality on Non-Participation

• Reducing local emissions will not fully insulate
  a locality from the adverse transboundary
  effects.
• The costs of climate change mitigation may be
  greater than the expected benefits.
• The collective benefits of climate protection are
  non-excludable.
• No federal assistance for the implementation of
  climate change protection programs.
• Why would a U.S. locality commit to the CCP
  campaign when there are strong incentives to do
  otherwise?

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Cities for Climate Protection Campaign

• Estimated 78 percent of CO2 emissions from
  cities.
• Spiky world.
• ICLEI Urban CO2 Reduction Project.
• Toronto Target.

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Collective Action and Selective Incentives

• ICLEI has no regulatory authority.
• Collective benefits are non-excludable.
• CCP campaign more likely to succeed if localities
  accrue selective (excludable) benefits from
  participation.
• A separate and selective incentive will stimulate
  a rational individual in a latent group to act in
  group-oriented ways.
• Mancur Olson 1965

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Place as a Source of Selective Incentives

• Uneven geographic distribution of expected costs
  and benefits is the analytic pivot to predict
  variation in CCP campaign involvement.
• Selective incentives to participate in the CCP
  campaign spring from two major sources
• The extent to which a locality is vulnerable to
  the risks of climate change and variability.
• The socioeconomic capacity of a locality to
  commit to emission reduction targets.

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Climate Change Risk Incentives

• Coastal proximity and water risk.
• Expected temperature change.
• Extreme weather events.
• Constitute a localitys selective vulnerability
  to climate change.
• All things held equal, localities with higher
  vulnerability to the risks of climate change are
  significantly more likely to commit to the CCP
  campaign.

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Socioeconomic Capacity Incentives

• Carbon intensive activities and industries.
• Political and civic composition.
• Environmental concern.
• All things held equal, localities with higher
  socioeconomic capacity are significantly more
  likely to commit to the CCP campaign.

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Dependent Variable

• CCP Campaign Status
• A locality receives a score of 1 if it has
  officially committed to the CCP campaign by
  council resolution and a score of 0 if not.
• Overall, 112 counties examined were party to the
  CCP campaign as of November 2005.

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Localities Party to the Cities for Climate
Protection Campaign
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Independent Variable Measurement
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Binary Logistic Regression Coefficients
Estimating Odds of CCP Commitment
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Spatial Distribution of Climate Change Risk at
the County Scale
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Spatial Distribution of Socioeconomic Capacity at
the County Scale
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Distribution of Climate Change Risk for
Metropolitan Areas in the United States
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Distribution of Climate Change Stress for
Metropolitan Areas in the United States
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Scatter Plot of Risk and Capacity by CCP Status
High-High
Low-Low
Socioeconomic Capacity Dimension
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Conclusion

• Proximity to the coast, expected temperature
  change, and previous casualties from natural
  hazards such as floods and hurricanes are
  significant triggers for CCP involvement.
• Higher risk selectively motivates participation
  in the CCP campaign.
• CCP localities are responding to the threats of
  climate change.
• Socioeconomic makeup is significant.
• Recruitment options High-High as low hanging
  fruit.