Population-Level Exposure to Particulate Air Pollution during Active Travel: Planning for Low-Exposure, Health-Promoting Cities

By Hankey, Steve; Lindsey, Greg et al. | Environmental Health Perspectives, April 1, 2017 | Go to article overview

Population-Level Exposure to Particulate Air Pollution during Active Travel: Planning for Low-Exposure, Health-Promoting Cities


Hankey, Steve, Lindsey, Greg, Marshall, Julian D., Environmental Health Perspectives


Introduction

Designing cities to promote active travel is a potential strategy to improve public health (HUD 2012; Nieuwenhuijsen and Khreis 2016). Two health-relevant factors associated with the built environment are physical activity and air quality (Abrams et al. 2012; Frank et al. 2006). Most prior research has isolated the built environment's effects on these factors separately; a recent literature review emphasizes that assessing how the spatial patterns of these factors overlap and are distributed in urban areas is an important yet understudied question (Giles and Koehle 2014). Our research aims to help fill this gap.

Dense, walkable neighborhoods are associated with increased physical activity (Frank et al. 2005), partially owing to increased active travel [i.e., cycling and walking (Hankey et al. 2012; Oakes et al. 2007)]. Emerging research focuses on describing patterns of bicycle and pedestrian traffic on transportation networks--for example, designing traffic count programs (Hankey et al. 2014; Nordback et al. 2013) and building facility-demand models (Hankey and Lindsey 2016; Miranda-Moreno and Fernandes 2011; Schneider et al. 2012). Those findings highlight research and policy questions about how best to provide safe, health-promoting infrastructure for active travel (Loukaitou-Sideris et al. 2014; McDonald et al. 2014; Wilson et al. 2010).

Epidemiologic studies suggest that within-city spatial patterns of air pollution are important for health (Beelen et al. 2014; Crouse et al. 2015; Miller et al. 2007). Urban air quality is associated with the built environment (Bechle et al. 2011; Hankey et al. 2012; Stone et al. 2007), and transport micro-environments--especially while cycling or walking--are important exposure pathways (Dons et al. 2012; Int Panis et al. 2010). Exposure to traffic-related air pollution during active travel has been linked to a number of health indicators (Cole-Hunter et al. 2016; Kubesch et al. 2015; Strak et al. 2010; Weichenthal et al. 2011, 2014), and exploratory studies have assessed individual level exposure on cycling routes (Cole-Hunter et al. 2012; Jarjour et al. 2013).

A few studies have explored spatial interactions between neighborhood "walkability" (i.e., characteristics in a neighborhood that may influence a resident's likelihood of walking) and ambient air pollution concentrations (Frank and Engelke 2005; Hankey et al. 2012; Marshall et al. 2009); we are not aware of studies that compared spatial patterns of "bikeability" and ambient air pollution. The walkability-based studies found that few places in urban areas have both low levels of air pollution and high walkability ("sweet-spot" locations). Several health impact assessments have found that the individual-level health benefits (i.e., physical activity) outweigh risks (i.e., air pollution, accidents) for hypothetical shifts to active travel (de Hartog et al. 2010; Doorley et al. 2015; Macmillan et al. 2014; Mueller et al. 2015; Rojas-Rueda et al. 2011). However, an understudied topic is the relative exposure of population-level flows of cyclists and pedestrians to air pollution [i.e., exposure where people actually walk and bike (traffic flows) rather than the characteristics of neighborhoods that influence their likelihood to walk ("walkability") or bike ("bikeability")]. [Several prior studies explore walkability and bikeability (Cole-Hunter et al. 2015; Frank et al. 2006; Winters et al. 2013).]

In this paper we used model-derived spatial estimates of bicycle and pedestrian traffic volumes and particulate air pollution concentrations in Minneapolis, Minnesota, to assess population-level patterns of exposure during active travel. We identified areas that are overall health-promoting and explored aspects of how best to design low-exposure transportation networks and neighborhoods (e.g., moving bicycle facilities away from high-traffic roads). Our analysis is one of the first to assess urban-scale exposure based on spatial estimates of actual rates of active travel (rather than "walkability"/"bikeability"). …

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