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A METHOD TO ASSESS COMPETING RISKS ASSOCIATED WITH PEDESTRIAN-ORIENTED ENVIRONMENTS A METHOD TO ASSESS COMPETING RISKS ASSOCIATED WITH PEDESTRIAN-ORIENTED ENVIRONMENTS Audrey de Nazelle and Douglas Crawford-Brown Department of Environmental Sciences and Engineering, School of Public Health, and Carolina Environmental Program, The University of North Carolina at Chapel Hill Contact: Campus Box 7431, UNC Chapel Hill, Chapel Hill NC 27599, [email protected], 919 966 7238 Increased in-street physical activity may increase risks due to air pollution exposure: people walking or biking may be spending more time in more polluted environments and with a higher inhalation rate than if they were driving. METHODS Features of pedestrian- oriented built environments are shown to increase physical activity for transportation or leisure, including: compact and mixed land uses, sidewalks, bicycle facilities, access to parks and trails, and well connected streets Example of a modeled individual profile of daily energy expenditure (left) and pollutant cumulative exposure (inhalation dose) (right). Red diamonds indicate times of travel. CONCLUSIONS • Decision-makers should assess and address potential unintended consequences of creating more pedestrian-friendly built environments in certain communities. • The risk assessment approach proposed is an appropriate methodology to assess the competing risks, particularly because of its ability to track uncertainty rigorously. • Future work needs to consider the many other benefits for a fair appraisal of the value of pedestrian-oriented environments. Increasing walking, cycling, or jogging in streets may increase the risk of traffic death or injury. In the US traffic mortality per mile traveled is 23 times higher for pedestrians than car drivers, for cyclists 12 times. Miami Beach, FL, photo by Dan Burden BACKGROUND Creating more pedestrian- friendly environments is seen as a “common cause” solution for a multitude of health and environmental problems that have challenged US policy makers, such as air pollution, physical activity, and social interaction. However, some unintended consequences may emerge from such community designs. OBJECTIVE: This research aims at estimating tradeoffs between competing health risks and benefits: physical activity, and exposures to air pollution and traffic hazards. Principles of pedestrian- friendly environments include creating accessible destinations and human scale designs, through: • Density (compact land uses) • Diversity (Land use mix) • Design (connected streets, grid-like pattern, small block sizes, continuous PEDESTRIAN-ORIENTED ENVIRONMENTS DEFINED Nîmes, France, photo by David McNelis Built Built Environment Environment Natural Natural Environment Environment Society Society Health Health Quality of Life Quality of Life Behavior Behavior •Use an activity database for daily activity patterns •Simulate individuals’ choice of destinations and travel mode choice in a built environment scenario •Simulate air pollution concentration field in time and space •Combine activity and air pollution data •Repeat for a different built environment scenario •Estimate change in traffic injury, air pollution, and physical activity health effects •Combine disparate health effects using a quality-adjusted life years method •Run a Monte Carlo simulation for uncertainty and variability analysis # * % % % % % % % TravelTim e Exposure F Transportation N etw ork # * O rigin % D estinations R outes O zone field 4PM 1-houraverage (ppm ) 0.000000 0.000001 -0.089700 0.089701 -0.091900 0.091901 -0.093300 0.093301 -0.094200 0.094201 -0.094900 0.094901 -0.095600 0.095601 -0.096400 0.096401 -0.097200 0.097201 -0.098700 0 0.6 1.2 0.3 M iles Probabilistic model of individual behavior and exposure to air pollution and traffic hazards: Example of exposure to ozone during a trip from home to go shopping at 4PM. The model first estimates location choice, then mode choice, and combines activity rate data with the air pollution field at the time of day the activity takes place PRELIMINARY RESULTS Results of the two-step Monte Carlo process: variability distribution of the mean difference in individuals’ energy expenditure (left) and mean percent increase in ozone inhalation dose (right) due to the built environment transformations towards more pedestrian- friendly design. The mean of the mean difference in energy expenditure is 12.3 kcal/day; the mean of the mean ozone inhalation increase is 1.9%. Madison, WI, Photo Michael King
