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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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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
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
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.
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
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
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.
(1) Baseline, (2) Shock-and-Awe and (3) Cake-and-Eat-It-Too Land Development Densities in People per Acre
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
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.
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.
Finding #1:Feedback as Force • This reinforcingfeedback structure is anautonomous force sufficient to cause urban expansion even without an economic or demographic impulse.
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.
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.
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
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