How to enhance cities' role in transitioning to sustainability and

resilience?

Urban Futures NCARPaty Romero-Lankao,

Sara Hughes, Dan Runfola, Josh Sperling

Urban Futures

1. Dynamics of urbanization that shape urban emissions, vulnerability and risk

2. Cities’ institutional capacity to meet the challenges of reducing emissionswhile improving resilience

Background report and chapters 1, 2 and 7

Special Issue on Cities and Climate Change

CLA for AR4 and AR5

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Total carbon emissions by city

M of tonnes of CO2 e.

19.7 M. of people

Urban mitigation challenges: The largest cities don't necessarily have the largest carbon

footprints. Why?

Source: Romero Lankao (2008)

15.2 M. of people

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Carbon emissions per capita

tonnes of CO2 equivalent

Multiple factors differences in urban GHG emissions

Poly-centric

Mono-centric Economic base and GDP per

capita

Urban form and population density (1% increase in urban density results in a 1.25% decrease in emissions)

Energy use intensity (public utility key here)

Transportation mode share 1% increase in public transport results in a 0.15% decrease in emissions!

City’s latitude & energy endowments

Database by Kenworthy covering 84 cities

STIRPAT formula (instead of multiplicative IPAT)

Estimates elasticity of each driver

Sources: Romero Lankao, Tribbia and Nychka (2009);

Bertaud (2009)

Cities face greatest risks from climate change

De Sherbinin and Romero Lankao (2008): The hazard risk of each city represents a cumulative score based on risk of cyclones, flooding, landslides and drought

Contoured: hazard risk associated with climate change

1. Many case studies, different

a. Hazards (focus: temperature)

b. Urban areas

c. Dimensions

d. Research Paradigms

2. Validation of conceptual framework

3. Mixed methods

a. meta-analysis & meta-knowledge

4. 53 papers covering 224 citiesRomero-Lankao and Qin (2011, COSUST) Romero Lankao, Qin and Dickinson (2012, GEC)

Framework: Urban vulnerability and risk

Factors shaping urban populations’ vulnerability to temperature-hazards

- 13 factors account for 66% of tallies on determinants of urban populations’ vulnerability

- 2 determinants extensively studied: hazard magnitude and age

- Findings result from dominance of a paradigm “urban vulnerability as impact”

(1) Text color denotes categories of vulnerability dimensions. Green = Hazard; Yellow = Exposure; Red = Sensitivity; Blue = Adaptive capacity/adaptation

(2) Symbols in parentheses = direction of relationship between vulnerability and outcome (medium or high level of agreement only)

+ positive relationship (increases vulnerability); - negative relationship (decreases vulnerability); ~ no relationship

Determinants of urban vulnerability: evidence and agreement

Dynamics of urbanization shaping vulnerability (global level)

1. Not only levels but also rates of urbanization influence vulnerability

2. Not only exposure but also sensitivity and capacity Urbanization and economic

indicators to cluster countries

Cross-correlation of clusters with national-level normalized sub-indices of hazard exposure, sensitivity, and adaptive capacity (World Risk Index 2012 )

Country groups

Source: Garschagen and Romero-Lankao 2013 Climatic Change (in press)

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Exposure Sensitivity Adaptive capacity

Institutional Capacity for Climate Change Responses in Cities

Patricia Romero-Lankao, Sara Hughes (USA)Angélica Rosas-Huerta (México), Roxana

Borquez (Chile), Daniel Gnatz,(USA)

Santiago: Extreme temperatures (2045-2065)

McPhee, et al. 2011

Mexico City: Precipitation

Magana, 2011

Climateand

Environmental Change

Temperature increases

Changes in precipitation

Heat waves

Droughts, floods

Why Santiago Chile and Mexico City?

Why Santiago Chile & Mexico City?

• Both share similar urbanization processes, reforms, and urban and environmental policies

– E.g., due to population growth alone • Mexico City: 2007- 2030 available water

per capita will diminish by 11.2% and in Santiago by 20.3 % per capita between 2005 - 2025

• Presence of scientific groups and multinational networks is key

• Yet differences also exist– Mexico City is a frontrunner– Santiago is a laggard

• Capacity for change has received increasing attention

• Scholarship has mostly focused on – Motivations & barriers to adaptation– Attributes of institutional capacity

• Yet, Frameworks distinguish between adaptive and mitigative capacity

• Response capacity, an alternative, refers to

– the broad pool of resources governmental and nongovernmental actors can use to reduce greenhouse gases and respond to climate variability and change (Burch and Robinson 2007)

Why institutional response capacity?

Methods: Qualitative analysis

1. Interviews with Government (City, State, National), Academics, and NGOs/Community organizers

a) 18 in Mexico Cityb) 22 in Santiago

2. Common coding scheme in Nvivo, network analysis software (UCINet)

3. Supplemented with government reports and academic studies

Source: Romero-Lankao, Hughes, Rosas-Huerta, Borquez, Gnatz (2013) Environment and Planning (accepted)

Unpacking institutional response capacity, a framework

Outline

Climate-relevant planning actions

time

Both cities at different stages of climate change planning

Source: Romero-Lankao, Hughes, Rosas-Huerta, Borquez, Gnatz (2013)

Unpacking institutional response capacity, a framework

Administrative Structures and Networks

• Mexico City

• Local (16 delegations), State (35 municipalities), and Federal authority

• Term limits and political tension

• Climate plan only for FD

• Santiago

• Local (52 communes), and Federal authority

• Term limits and single-party rule

Environmental authorities

- Don’t interact as frequently with health & energy- Don’t interact at all with housing, urban development,

transportation)

Cities working networks; the size of nodes is proportionalto the number of respondentsreporting to work with that actor. Mexico City exhibits a relativelymore integrated network.

Supranational

GovernmentNGOAcademicPrivate 

Local

National

State

Mexico City

Santiago

Centralized yet fragmented administrative structure

Use of Information

Mexico City

• Virtual Climate Change Center

• Top-down due to perceived lack of local capacity

• Want information on climate scenarios

Santiago

• Early stages of generation

• Top-down due to perceived lack of local capacity

• Want information on local impacts and adaptation responses

Participation

Mexico City

• Authoritarian political culture (70 years PRI gov.)

Santiago

• Authoritarian political culture (Pinochet dictatorship, techno neoliberalism)

• Mechanisms in place tend to be technocratic and paternalistic

• Consultations, pamphlets and guidelines

• Perceptions on this are mixed

• Yet participation in civil protection and disaster management is more common

Opportunities

• Leadership (and political ambition)

• For Mexico City institutionalization of climate into planning

• Presence of – Influential scientific groups – Non-governmental and international organizations

– Participation of local authorities in transnational networks

• Longer-term tradition of disaster management (although reactive)

Constraints

• Centralized yet fragmented administrative structure inhibits effective coordination

• Technocratic and top-down approach to information sharing inhibits learning and informed policy making at the city level

• Limited existing mechanisms for participation in decision making transfer to climate change planning

• Economic policies and efficiency dominate

Thank you!