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

机译:积极出行期间人口水平的特定空气污染暴露量:规划低暴露量,促进健康的城市

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Background: Providing infrastructure and land uses to encourage active travel (i.e., bicycling and walking) are promising strategies for designing health-promoting cities. Population-level exposure to air pollution during active travel is understudied. Objectives: Our goals were a ) to investigate population-level patterns in exposure during active travel, based on spatial estimates of bicycle traffic, pedestrian traffic, and particulate concentrations; and b ) to assess how those exposure patterns are associated with the built environment. Methods: We employed facility–demand models (active travel) and land use regression models (particulate concentrations) to estimate block-level ( n = 13,604) exposure during rush-hour (1600–1800 hours) in Minneapolis, Minnesota. We used the model-derived estimates to identify land use patterns and characteristics of the street network that are health promoting. We also assessed how exposure is correlated with indicators of health disparities (e.g., household income, proportion of nonwhite residents). Our work uses population-level rates of active travel (i.e., traffic flows) rather than the probability of walking or biking (i.e., “walkability” or “bikeability”) to assess exposure. Results: Active travel often occurs on high-traffic streets or near activity centers where particulate concentrations are highest (i.e., 20–42% of active travel occurs on blocks with high population-level exposure). Only 2–3% of blocks (3–8% of total active travel) are “sweet spots” (i.e., high active travel, low particulate concentrations); sweet spots are located a ) near but slightly removed from the city-center or b ) on off-street trails. We identified 1,721 blocks (~ 20% of local roads) where shifting active travel from high-traffic roads to adjacent low-traffic roads would reduce exposure by ~ 15%. Active travel is correlated with population density, land use mix, open space, and retail area; particulate concentrations were mostly unchanged with land use. Conclusions: Public health officials and urban planners may use our findings to promote healthy transportation choices. When designing health-promoting cities, benefits (physical activity) as well as hazards (air pollution) should be evaluated. Citation: Hankey S, Lindsey G, Marshall JD. 2017. Population-level exposure to particulate air pollution during active travel: planning for low-exposure, health-promoting cities. Environ Health Perspect 125:–534; http://dx.doi.org/10.1289/EHP442.
机译:背景:提供基础设施和土地用途以鼓励积极旅行(即骑自行车和步行)是设计健康城市的有前途的策略。人们对主动出行期间暴露于空气污染的人口水平的影响进行了研究。目标:我们的目标是:a)根据对自行车交通,行人交通和颗粒物浓度的空间估计,调查主动出行期间接触人群的水平模式; b)评估那些暴露方式与建筑环境之间的关系。方法:我们使用设施需求模型(主动出行)和土地利用回归模型(颗粒物浓度)来估计明尼苏达州明尼阿波利斯的高峰时间(1600-1800小时)内的地块水平(n = 13,604)暴露。我们使用模型得出的估算值来确定有利于健康的土地利用模式和街道网络特征。我们还评估了接触如何与健康差异指标(例如家庭收入,非白人居民比例)相关联。我们的工作使用人口水平的主动出行率(即交通流量)而不是步行或骑自行车的概率(即“步行性”或“可骑自行车性”)来评估接触程度。结果:主动出行经常发生在交通繁忙的街道上或附近的微粒浓度最高的活动中心(即,主动出行的20–42%发生在人口水平较高的街区)。只有2–3%的区块(占总活跃旅行的3–8%)是“最佳点”(即,活跃旅行数量高,微粒浓度低);最佳地点a)在市中心附近,但稍微远离市中心; b)在路外小径上。我们确定了1,721个街区(约占当地道路的20%),在此情况下,将主动出行从高流量的道路转移到相邻的低流量的道路会减少约15%的暴露。主动出行与人口密度,土地使用结构,开放空间和零售区域相关;颗粒物浓度随土地利用而基本不变。结论:公共卫生官员和城市规划人员可以利用我们的发现来促进健康的交通选择。在设计促进健康的城市时,应评估收益(体育活动)和危害(空气污染)。引用:Hankey S,Lindsey G,Marshall JD。 2017。主动出行期间人口一级暴露于颗粒状空气污染:规划低辐射,促进健康的城市。环境健康透视125:–534; http://dx.doi.org/10.1289/EHP442。

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