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Coupled Human / Biological Systems in Urban Areas : Towards an Analytical Framework Using Dynamic Simulation (Concepts drawn from the NSF-sponsored Urban Trace-Gas Emissions Project) Phillip C. Emmi Professor of Urban and Regional Planning University of Utah November 20, 2003.

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  1. Coupled Human / Biological Systems in Urban Areas:Towards an Analytical Framework Using Dynamic Simulation(Concepts drawn from the NSF-sponsored Urban Trace-Gas Emissions Project)Phillip C. EmmiProfessor of Urban and Regional PlanningUniversity of UtahNovember 20, 2003

  2. Presentation Outline • Conceptualize coupled human - biological systems in urban areas • Mankind as an ecological force • Energy use and urban density • Population growth, urban land consumption and road-building • A reinforcing feedback loop • Simulate urban sprawl and traffic congestion • Reference behavior • Causal loop diagram and system map • Policy simulations • Structure, results, findings and conclusions • Future directions

  3. Mankind as an Ecological Force • Mankind is now a force of geologic proportions on the surface of the earth. • Mankind is now a force for global atmospheric and climatologic change. • Within 4 years, we become a predominately urban species: within 30 years, we will be 72% urban. • With further density declines, we go from occupying 3% to 8 - 9% of the earth’s habitable surface. We will then be an interconnected tissue across earth’s land surface. • We need to think seriously about the use of land and the reconstitution of our atmosphere through urban processes.

  4. Urbanization & Bio-/Atmosphere Exchange

  5. Urban Energy Consumption & Density

  6. Urban Land Development Before & After 1993

  7. Range of Change in Population and Urbanized Land, 1982-97. Sprawl in a Growing Region∂(land)=3.3*∂(pop) Source: Fulton. 2001. Who Sprawls Most? Brookings. The Piedmont of the Southern Appalachian Mountains

  8. Range of Change in Population and Urbanized Land, 1982-97. Sprawl in a Declining Region Maximum 53% 2% Minimum 25% -15% Median 38% -5% Lake Erie Source: Fulton. 2001. Who Sprawls Most? Brookings. ∂(land) = -7.6*∂(pop) Ohio, Pennsylvania, West Virginia

  9. A Reinforcing Feedback Loop(a la Newman & Kenworthy, 1989) • Most cities that built freeways found that this spread out urban land use and generated more traffic, until the freeways were congested again. • The response was to suggest that still more roads were urgently needed. • The new roads were justified again on technical grounds in terms of time, fuel, and eliminating congestion. • This sets in motion a self-reinforcing cycle of congestion, road building, sprawl, more congestion and more road building.

  10. Roads Beget Roads: The Cover of Asphalt (April, 1966)

  11. Expectations

  12. Simplified System Map

  13. Validation Statistics for SprawlSim, Salt Lake City, UT

  14. Percent Change in Key Variables

  15. Cockpit with Policy Sliders

  16. (1) Baseline, (2) Shock-and-Awe and (3) Cake-and-Eat-It-Too Land Development Densities in People per Acre

  17. Three Scenarios:(1) Baseline, (2) Shock-and-Awe and (3) Cake-and-Eat-It-Too Traffic Congestion as Measured by the Percent Change in the Road Gap

  18. System Structure • The interaction between urban land development, trip generation, and roadway construction can be represented asagoal-seeking process nested within a self-reinforcing feedback loop.

  19. System Results • This structure gravitates toward a pattern of incessantly more fervent activity in pursuit of an ever-receding goal – increasingly more miles of roadway construction, induced developmental density declines, increased vehicular traffic and more traffic congestion. • It gravitates toward an ever-expanding gap between actual and desired results.

  20. Finding #1:Feedback as Force • This reinforcingfeedback structure is anautonomous force sufficient to cause urban expansion even without an economic or demographic impulse.

  21. Finding #2:Management Requirements • Regulating this force is essential for the successful management of cities. • It is key to urban metabolics, thus … • It is key to the dynamic of human-biological systems in cities.

  22. Finding #3:Feedback Dampening Works • Dampened feedback scenarios work. • They do so by aggressively shifting travel mode, increasing existing roadway capacities, increasing developmental densities and thus lowering auto trip generation. • Defeating sprawl and congestion requires multiple policies aggressively implemented. • With that, other beneficial results ensue.

  23. Conclusions • A three-fold policy design dampens sprawl. • Dynamic simulation facilitates experimenting with alternative policies. • This creates a new basis upon which to learn and act. • Highlight critical factors, complex links • Visualize policy explorations • Identify robust strategies • Stimulate discussion among reference groups • Facilitates “steering” of inter-organizational networks

  24. Future Directions • Refine the current sector • Add further sectors • traffic volume, speed and congestion sector • local fiscal sector • atmospheric emissions sector • urban forest regime sector • Continue to engage local policy leaders in group-based modeling

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