Sustainability and Urban Spaces Thomas L. Theis Institute for - - PowerPoint PPT Presentation

Sustainability and Urban Spaces

Thomas L. Theis Institute for Environmental Science and Policy Department of Civil and Materials Engineering University of Illinois at Chicago Moira Zellner College of Urban Planning and Public Affairs Institute for Environmental Science and Policy University of Illinois at Chicago Heriberto Cabezas Sustainable Technology Division National Risk Management Research Laboratory US Environmental Protection Agency Cincinnati OH

US Japan Workshop on Life-Cycle Assessment of Sustainable Infrastructure Materials 21-22 October 2009

Talking Points

• Urban systems
• Sustainability, resiliency, and metrics
• Example: carbon dioxide emissions from

urban areas

• Agent-based modeling
• Fisher information

Urban Population Growth

What are Urban Systems?

• Complex, usually self-organizing systems
• Grow, and renew, in proportion to the economic

surplus that they are able to capture

• Contain layers of financial, infrastructure,

material (stocks and flows), energy and information transfers that operate at spatial scales and evolve over time

• Cities, in aggregate, are large consumers (of

materials and energy), but also large producers

• f capital, employment, goods, and services
• Urban regions have unique and complex

problems (e.g. infrastructure renewal, care of their populations, congestion, social equality)

Talking Points

• Urban systems
• Sustainability, resiliency, and metrics
• Example: carbon dioxide emissions from

urban areas

• Agent-based modeling
• Fisher information

Resiliency

• Capacity to maintain essential organization and

function in response to disturbances of both long and short duration (Berkes 2007)

• The degree of damage a system can withstand

without exhibiting a “regime” shift, defined as a transition that changes the structure and functioning of the system from one state to another as a result of one or more independent factors (Hollings 1996)

Sustainability = Resiliency +…

• The equitable and responsible distribution
• f resources among humans, present and

future, in ways that do not harm, and ideally reinforce, the social and biological systems upon which human society is based.

• Three “parts”: ecological, economic, and

social order

Common Features of Resilient and Sustainable Designs

• Network organization
• Built-in design redundancy or decentralization
• The intelligent use of advanced materials
• The ease-of-renewal or reconstruction
• The extent to which the infrastructure is integrated with

ecological systems

• Self-diagnostic and healing capabilities
• The ability to acquire accurate information that is

communicated back into the functioning of the system

• And…the sustainability of these systems includes

measures of capital economy and longevity, but as importantly the material and energy demands of the system (natural capital) over the complete life cycle

Central Tenet

Sustainable and resilient infrastructures result from a combination of engineering analysis and design, the incorporation of technological and material advances, and the interplay of human adaptation and response to the physical and ecological environment

Some Sustainability Indicators

Metric Property Definition Criteria Ecological footprint

Ecological stress Land area required to meet level of consump- tion and wastage Does not increase

Exergy and Emergy

Use of energy resources Available energy; the sum of all forms of energy used to make an item

Exergetic eff→Max (Renew Emergy) (Total Emergy)

Green net regional product

Economic well-being GRP-Loss of human and natural capital

gNRP≥0

Fisher information

System function

ds ds s dp s p I

2

) ( ) ( 1

∫

⎥ ⎦ ⎤ ⎢ ⎣ ⎡ =

≈ ∂ dt I

→1

Urban Footprints

Examples:

• Berlin 82
• London 120
• Toronto 280
• Tokyo 600

Exergy vs. Emergy: Corn vs. Beef

Mayer, A.L., Thurston, H.W., Pawlowski, C.W. Front. Ecol. Environ, 2(8), 419-426 (2004)

Talking Points

• Urban systems
• Sustainability, resiliency, and metrics
• Example: carbon dioxide emissions from

urban areas

• Agent-based modeling
• Fisher information

Two Views of Cities and CO2 (Chicago)

CO2/area CO2/household

Two Views of Cities and CO2 (New York)

CO2 /area CO2 /household

Two Views of Cities and CO2 (San Francisco)

CO2/area CO2/household

Talking Points

• Urban systems
• Sustainability, resiliency, and metrics
• Example: carbon dioxide emissions from

urban areas

• Agent-based modeling
• Fisher information

Agent Based Modeling

• ABM is a modeling technique for simulating a

system’s evolution over time.

• Combines time, space, and behavior
• Consists of
• agents (e.g. residents, developers, institutions) that

independently interact on

• infrastructural spaces (grids or networks) over time
• according to established patterns of behavior
• Agents are intelligent and/or purposeful, but not

always wise

Urban Sustainability Assessment Framework for Energy: Sprawl Simulation

Transition from farm to undeveloped cell Lattice with cells Municipal water/ sewer Roads Zoning Distance to destinations

• Ag. soil quality

Interactions

Farmer Transition from undeveloped to residential cell Residents

Land-use decision-making mechanisms

School scores Crime rate

0.5

Residential cells Farm cell

Lattice with cells

Distance to employment

Energy consumption mechanisms: electricity and fuel

Zoning (density)

Fuel use Electricity use

The default scenario

Parameters Spatial input

World size (cells) Households per time step Undeveloped cells per time step Mean preference value (all preferences) Surface of each cell (m2) Maximum energy per household (kWh/month) Minimum energy per household (kWh/month) Share of natural gas power plants Share of coal power plants Share of oil power plants Share of municipal waste power plants CO2 emission from natural gas (g/kWh) CO2 emission from coal (g/kWh) CO2 emission from oil (g/kWh) CO2 emission from municipal waste (g/kWh) Transportation fuel efficiency (miles/gal) Transportation CO2 coefficient (g/gal) 200 x 166 1000 100 0.5 63000.78 (~16 ac.) 1332.0 555.0 0.25 0.25 0.25 0.25 514.82 1020.12 758.40 1355.33 30.0 8744.611 Initial land use (farms) Roads Water/sewer/septic (1) Zoning (uniform_max) Agricultural soils (0) Distance to city School quality (0)

Aggregate values for electricity use, fuel use, CO2 emissions, and Fisher Information

Residents Electricity Fuel CO2 CO2/res Scenario (kWh) (gal) (mT) (mT/res) FI Default scenario (5 roundtrips/week) 199000 1.33E+09 1.23E+10 1.09E+08 5.45E+02 5 Minimum density zoning 19900 3.18E+08 6.08E+09 5.34E+07 2.68E+03 16 Concentric zoning 199000 2.58E+09 4.76E+10 4.19E+08 2.10E+03 2 Good central schools 199000 1.33E+09 1.22E+10 1.08E+08 5.41E+02 5 Good peripheral schools 199000 1.33E+09 5.92E+10 5.19E+08 2.61E+03 2

• Three roundtrips/week

199000 1.33E+09 7.29E+09 6.49E+07 3.26E+02 16

• Four roundtrips/week

199000 1.33E+09 9.74E+09 8.64E+07 4.34E+02 variable

Minimum density zoning

Default Minimum density zoning Residents/ cell CO2 (mT) CO2 (mT)/residident

Talking Points

• Urban systems
• Sustainability, resiliency, and metrics
• Example: carbon dioxide emissions from

urban areas

• Agent-based modeling
• Fisher information

Sustainable Regime Hypothesis

• Fisher Information is a measure of dynamic
• rder
• Well functioning systems (including human-

designed systems) exist in well ordered regimes where dynamic order does not change with time

• Sustainability Criteria I: if the system

dynamic regime is sustainable, then the time averaged Fisher Information must be constant

≈ ∂ ∂ t I

Sustainable Regime Hypothesis: Corollaries

• Sustainability Criteria II: steadily decreasing

Fisher information signifies progressive loss

• f dynamic order and a system that is

becoming disorganized and ceasing to function

• Steadily increasing Fisher information

signifies a system that is changing but is still

• rganized and functioning
• Sustainability Criteria III: the interval or shift

between two dynamic regimes is characterized by a steep drop in dynamic

• rder and Fisher information

Urban Scenario Results. Fisher Information for Three, Four, and Five (default) Roundtrips/week

Zellner et al. Computers, Environment and Urban Systems 32:474-488 (2008)

Continuing Work

• Spatial applications of Fisher Information
• Extensions to the ABM model
• Test technological scenarios (fuel efficiency, different

transportation networks and systems)

• Introduce different kinds of agents (e.g. developers,

municipal authority)

• Test economic instruments
• Fuel taxes
• Carbon taxes
• Credits for forest cover
• Stormwater debits

Concluding thoughts Policy implications: research and practice

• Understanding how lifestyle preferences and

reactions bring about tradeoffs

• Within the context of this analysis, zoning, public

school ranking, and private commuting are influential in determining urban form and consequent patterns of energy use and pollution emissions

• Land use and educational policies contribute to

environmental policies

• Technology not the only fix (but still important)

Thank You!