论文标题
人类流动性不成比例地扩展了低收入人群的PM2.5排放暴露
Human Mobility Disproportionately Extends PM2.5 Emission Exposure for Low Income Populations
论文作者
论文摘要
环境暴露于小于2.5μm（PM2.5）的直径颗粒物问题已被确定为呼吸道疾病的关键原因。已知已经存在的单个住所的收入群体中PM2.5的差异已知并且易于计算。但是，现有的暴露评估方法不会捕获城市居民的动态流动性所隐含的暴露，而城市居民的动态流动性则占房屋外部的大部分接触。为了克服衡量城市居民对PM2.5暴露的挑战，我们分析了德克萨斯州哈里斯县的手机用户生成的数十亿个匿名和隐私增强的基于位置的数据，以表征人口的移动性模式和相关的暴露。我们根据人们在空气污染物的地方度过的时间介绍了暴露范围的度量标准，并检查了收入群体中基于移动性的暴露差异。我们的结果表明，PM2.5的排放量不成比例地暴露了低收入人群，因为它们的活动性活动。收入高于平均水平的人暴露于PM2.5的较低水平。基于移动性的暴露的这些差异是低收入人群经常访问PM2.5排放量高的城市地区工业部门的结果，以及这些人对生活需求的较大行动量表。结果为环境正义和公共卫生策略提供了信息，不仅是为了减少总体PM2.5暴露，而且还减轻了对低收入人群的不利影响。研究结果还表明，大规模的人口流动性和污染排放数据的整合可以揭示出对城市规模上空气污染暴露不平等的新见解。
Ambient exposure to fine particulate matters of diameters smaller than 2.5μm (PM2.5) has been identified as one critical cause for respiratory disease. Disparities in exposure to PM2.5 among income groups at individual residences are known to exist and are easy to calculate. Existing approaches for exposure assessment, however, do not capture the exposure implied by the dynamic mobility of city dwellers that accounts for a large proportion of the exposure outside homes. To overcome the challenge of gauging the exposure to PM2.5 for city dwellers, we analyzed billions of anonymized and privacy-enhanced location-based data generated by mobile phone users in Harris County, Texas, to characterize the mobility patterns of the populations and associated exposure. We introduce the metric for exposure extent based on the time people spent at places with the air pollutant and examine the disparities in mobility-based exposure across income groups. Our results show that PM2.5 emissions disproportionately expose low-income populations due to their mobility activities. People with higher-than-average income are exposed to lower levels of PM2.5 emissions. These disparities in mobility-based exposure are the result of frequent visits of low-income people to the industrial sectors of urban areas with high PM2.5 emissions, and the larger mobility scale of these people for life needs. The results inform about environmental justice and public health strategies, not only to reduce the overall PM2.5 exposure but also to mitigate the disproportional impacts on low-income populations. The findings also suggest that an integration of extensive fine-scale population mobility and pollution emissions data can unveil new insights into inequality in air pollution exposures at the urban scale.
