Residential Proximity to Traffic

The HCI Residential Proximity to Traffic indicator measures how much of a residential neighborhood is impacted by streets that carry a large amount of traffic. It serves as a proxy for the impact on health from motor vehicle air pollution and traffic noise. Significant evidence indicates a link between the proximity to highways and increased incidence of adverse health effects from exposure to air pollution and excessive traffic noise. Listed under Environmental Hazards, this measure is also tied to the transportation, economic health, housing, health systems and public safety, and neighborhood characteristics domains. It is an “inverse” measure, meaning the higher the value, the higher the negative impact on neighborhood health. Computation of this indicator requires highway, traffic volume, and population data which is available from the U.S. Census and state departments of transportation (DOT) or metropolitan planning organizations (MPO).

Neighborhoodsort descending Indicator Value Rank
Blackstone 0.0% 1
Charles 10.4% 14
College Hill 0.0% 1
Downtown 16.2% 18
Elmhurst 0.0% 1
Elmwood 5.0% 9
Federal Hill 24.1% 23
Fox Point 14.4% 16
Hartford 23.9% 22
Hope 8.3% 13
Lower South Providence 15.4% 17
Manton 0.0% 1
Mount Hope 25.0% 24
Mount Pleasant 0.0% 1
Olneyville 30.6% 25
Reservoir 20.7% 21
Silver Lake 6.7% 11
Smith Hill 17.5% 19
South Elmwood 12.8% 15
Upper South Providence 18.3% 20
Valley 4.2% 8
Wanskuck 6.1% 10
Washington Park 3.0% 7
Wayland 0.0% 1
West End 8.2% 12

Key Citations:
1. CARB (2005). Air Quality and Land Use Handbook: A Community Health Perspective. California Air Resources Board. April 2005. Available at: http://www.arb.ca.gv/ch/handbook.Pdf
2. HEI (2010). Traffic-Related Air Pollution: A Critical Review of the Literature on Emissions, Exposure, and Health Effects. Health Effects Institute, January 2010. Available at: http://pubs.healtheffects.org/getfile.php?u=553
3. Zhu, Y et al. (2002). “Study of Ultra-Fine Particles Near A Major Highway With Heavy-Duty Diesel Traffic.” Atmospheric Environment. 2002 ; 36:4323-4335.
4. Zhou, Y. and Levy, J. (2007). Factors influencing the spatial extent of mobile source air pollution impacts: a meta-analysis. BMC Public Health. doi:10.1186/1471-2458-7-89. Available at http://www.ncbi.nlm.nih.gov/pmc/articles/PMC1890281/
5. Rioux (2010). “Characterizing Urban Traffic Exposures Using Transportation Planning Tools: An Illustrated Methodology for Health Researchers”. Journal of Urban Health: Bulletin of the New York Academy of Medicine, Vol. 87, No. 2.