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 of 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 of 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 Ecological Land area required to Does not stress meet level of consump- increase footprint tion and wastage Exergetic eff → Max Use of Available energy; Exergy and energy the sum of all forms of Emergy resources (Renew Emergy) → 1 energy used to make (Total Emergy) an item gNRP ≥ 0 Economic GRP-Loss of human Green net and natural capital regional well-being product ∂ 2 System ⎡ ⎤ Fisher I 1 dp ( s ) ∫ ≈ = I ds 0 ⎢ ⎥ ⎣ ⎦ function p ( s ) ds information dt
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 CO 2 (Chicago) CO2/household CO2/area
Two Views of Cities and CO 2 (New York) /household CO 2 /area CO 2
CO2/household Two Views of Cities and CO 2 (San Francisco) CO2/area
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 Land-use decision-making mechanisms Transition from undeveloped Transition from farm to residential cell to undeveloped cell Lattice with cells Residents Farmer 0.5 Ag. soil quality Crime rate School scores Distance to destinations Municipal water/ sewer Roads Zoning Interactions
Energy consumption mechanisms: electricity and fuel Residential cells Farm cell Lattice with cells Distance to employment Fuel use Zoning (density) Electricity use
The default scenario Parameters Spatial input World size (cells) 200 x 166 Initial land use (farms) Households per time step 1000 Undeveloped cells per time step 100 Roads Mean preference value (all preferences) 0.5 Surface of each cell (m 2 ) 63000.78 (~16 ac.) Maximum energy per household (kWh/month) 1332.0 Water/sewer/septic (1) Minimum energy per household (kWh/month) 555.0 Share of natural gas power plants 0.25 Share of coal power plants 0.25 Zoning (uniform_max) Share of oil power plants 0.25 Share of municipal waste power plants 0.25 Agricultural soils (0) CO 2 emission from natural gas (g/kWh) 514.82 CO 2 emission from coal (g/kWh) 1020.12 CO 2 emission from oil (g/kWh) 758.40 Distance to city CO 2 emission from municipal waste (g/kWh) 1355.33 Transportation fuel efficiency (miles/gal) 30.0 Transportation CO 2 coefficient (g/gal) 8744.611 School quality (0)
Aggregate values for electricity use, fuel use, CO2 emissions, and Fisher Information Residents Electricity Fuel CO 2 CO 2 /res Scenario (kWh) (gal) (mT) (mT/res) FI Default scenario (5 roundtrips/week) 5 199000 1.33E+09 1.23E+10 1.09E+08 5.45E+02 Minimum density zoning 16 19900 3.18E+08 6.08E+09 5.34E+07 2.68E+03 Concentric zoning 2 2.58E+09 4.76E+10 2.10E+03 199000 4.19E+08 Good central schools 5 199000 1.33E+09 1.22E+10 1.08E+08 5.41E+02 Good peripheral schools 2 5.92E+10 5.19E+08 2.61E+03 199000 1.33E+09 -Three roundtrips/week 16 199000 1.33E+09 7.29E+09 6.49E+07 3.26E+02 -Four roundtrips/week variable 199000 1.33E+09 9.74E+09 8.64E+07 4.34E+02
Minimum density zoning Default Minimum density zoning Residents/ cell CO2 (mT) CO 2 (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 order • 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 ∂ I ≈ 0 ∂ t
Sustainable Regime Hypothesis: Corollaries • Sustainability Criteria II: steadily decreasing Fisher information signifies progressive loss of 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 organized and functioning • Sustainability Criteria III: the interval or shift between two dynamic regimes is characterized by a steep drop in dynamic order 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)
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