Climate Change and Health Impacts of Transportation Network Design
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Dr. Lawrence Frank presents on the direct relationship between connectivity of transportation networks, street design and their health implications.
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Climate Change and Health Impacts of Transportation Network Design
- 1. Climate Change and Health Impacts of Transportation Network Design Dr. Lawrence Frank Bombardier Chair in Sustainable Transportation University of British Columbia
- 2. Transportation and Land use Decisions, Land Use Patterns, Travel Choices and Outcomes
- 4. The built environment affects our health
- 6. . Proximity Connect- ivity 2 KM 1 KM
- 8. Adult Findings - Transit Use Devlin and Frank, 2009
- 9. Adult Findings - Walking Devlin and Frank, 2009
- 10. Adult Findings - Vehicle Use Devlin and Frank, 2009
- 12. LFC, Inc. May 19, 2009 * Controlled for gender, income, age, total number of vehicles in the house * VOC differences across quartiles significant (p<0.001 Volatile Organic Compounds & Intersection Density (n=2467) Air Pollution & Neighborhood Design Source: Frank, L.D. Sallis, J.F., Conway, T., Chapman, J., Saelens, B. Bachman, W. (2006). Multiple Pathways from Land Use to Health: Walkability Associations With Active Transportation, Body Mass Index, and Air Quality. Journal of the American Planning Association .
- 13. CO2 & Neighbourhood Design LFC, Inc. May. 19, 2009 Source: LUTAQH final report, King County ORTP, 2005
- 17. *p<.05, **p<.01, ***p<.001 *p<.05, **p<.01, ***p<.001 controlling for socio-demographics and stratified by age group (Averaged over a two day period) LOGISTIC REGRESSION ANALYSES PREDICTING THE ODDS OF WALKING AT LEAST ONCE OVER 2-DAYS YOUTH Age Range 5-8 years OR (95% CI) 9-11 years OR (95% CI) 12-15 years OR (95% CI) 16-20 years OR (95% CI) N=847 N=632 N=867 N=815 Intersection highest tertile (vs lowest) 1.7 (1.0-2.9) 1.3 (0.8-2.3) 1.7 (1.1-2.8)* 2.0 (1.1-3.6)* Density highest tertile (vs lowest) 1.8 (1.0-3.1) 2.3 (1.2-4.3)** 3.7 (2.2-6.4)*** 2.0 (1.0-4.1) Mixed land use (vs no mix) 1.5 (0.9-2.4) 1.5 (0.9-2.5) 2.5 (1.6-3.8)*** 1.9 (1.0-3.2)* At least 1 commercial land use (vs 0) 1.5 (0.9-2.4) 1.6 (1.0-2.5) 2.6 (1.7-4.0)*** 1.7 (1.0-3.1) At least 1 recreation/open space land use (vs 0) 2.1 (1.3-3.4)*** 1.8 (1.1-2.9)* 2.5 (1.7-3.6)*** 1.8 (1.1-2.9)**
- 18. Analyzing the Fused Grid Fused Grid Residential Quadrant Resulting Pedestrian Network Resulting Vehicular Network
- 20. Typology of Connectivity Patterns
- 22. Residential Street Patterns in Study Area Seattle (Queen Anne) Bellevue (East) Redmond (South) King County, WA – Gridirons to Loop & Culs-de-sac
- 23. Findings - Descriptive Walking Mode Share and Street Connectivity Disparate Street Connectivity and associated Walk Shares (by person to commercial) Pedestrian Connectivity Low High Vehicular connectivity Low SE and Central Bellevue; SW Seattle – Loop and Culs-de-Sac Mean Mode Share: 10% walking n = 985 Queen Anne, Capital Hill (Seattle) – Modified grid with connectors Mean Mode Share: 18% walking n = 66 High N and , – Grid and major streets w/o sidewalks Mean Mode Share: 10% walking n = 59 Downtown and Older Neighbourhoods – Gridiron Mean Mode Share: 14% walking n = 966
- 25. Modeling Physical Activity Outcomes For Contrasting Land Use Scenarios
- 27. The White Center / SW 98 th St. Case Study White Center Neighborhood SW 98 th St. Corridor
- 30. Buildout Scenario Full buildout of Greenbridge public housing Pedestrian connection links Greenbridge & 98th St. Corridor Full buildout at maximum density High density mixed use development (pink) Mid-rise residential development (dark orange) Approx. 2500 households, 1800 employees x
- 33. Scenario Results CO2 (kg) / DU NOX (grams) / DU HC (grams) / DU CO (grams) / DU Car Vehicle Miles / DU Transit Person Miles / DU Walk / Bike Miles / DU BMI / Adult Minutes of Physical Activity / Adult BASE CASE 14.17 47.62 51.69 580.00 48.82 12.67 3.13 24.74 37.06 Buildout with ped connection 13.94 46.70 50.61 569.82 47.85 12.99 2.73 24.10 41.94 Base Case + Transit 13.13 44.62 48.62 542.38 45.64 13.34 3.13 24.60 37.06 Buildout + Ped Connection + Transit 12.90 43.70 47.54 532.20 44.67 13.65 2.73 23.96 41.94
- 35. LFC, Inc. May. 19, 2009 Final Map of CO2 emissions from transportation Includes: Local urban form (land use mix, intersection density, retail FAR) Regional location (auto travel time Transit accessibility & travel time Demographics
- 36. The Essential Role of Demand LFC, Inc. May. 9, 2009
- 38. High Walkability Low Walkability Prefers a Walkable Community Design Prefers Auto - Based Community Design 1 2 4 3 Neighborhood Preferences Built Environment Maximum Minimum
- 39. Stated Preference (Q8a, Q8b, Q8c) Street Design and Travel Options
- 40. There is a latent demand for more connected streets – Even in Atlanta.
- 42. PREFERENCE VS NEIGHBORHOOD DESIGN
- 43. Built Environment Transportation Investments and Land Use Human Behavior Travel Patterns and Physical Activity Environmental Quality Air Quality and Greenspace Quality of Life
- 44. Working Across Sectors
- 45. The End
Notas do Editor
- This is the Walkability Surface. It shows us how walkable each postal code is in the region based on measured densities, land use mix and street patterns. Note the inter and intra municipal variation in measured walkability in the image; generally neighbourhood walkability in the region decreases the further out one gets from the regional core. Vancouver, New Westminster and parts of North Vancouver and West Vancouver are all characterized as being highly walkable. Many neighbourhoods in these municipalities have high densities, a variety of shops and services nearby and a well-connected street network.
- Just based on KC data now, but has a lot of potential to expand – pull in data from other regions for broader geographic applicability.
- Final model explains about 41% of HH behavior.
- Reducing demand is essential to meeting the target in 2050. Either of these scenarios will meet the target – where technology can do more, there is less need to reduce demand, but all scenarios will need to address demand in some way.