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中文摘要：
目的探讨PM2.5个体暴露数据与环境监测站点数据的关系,为指导雾霾天气公众交通出行提供建议,为未来大规模空气污染健康研究提供数据支持。方法在北京市招募7名在职人员作为调查对象,对调查对象真实通勤过程中不同通勤方式的PM2.5个体暴露水平进行监测,收集同期相关站点的PM2.5环境监测数据,建立PM2.5个体暴露数据与环境监测数据之间的关联。结果通勤情况下人群PM2.5个体暴露水平较高;本研究调查的通勤方式中,除轻轨以外,PM2.5个体暴露数据与环境监测数据差异均有统计学意义（P〈0.05）;PM2.5个体暴露数据与环境监测数据均呈正相关（P〈0.01）。结论雾霾天气应尽可能地选择地铁和轻轨出行,利用环境监测站点PM2.5浓度数据可以较好地模拟通勤方式的PM2.5个体暴露水平。
英文摘要：
Objective To explore the relationship between personal exposure levels in different commuting patterns and corresponding air monitoring data of PM2.5, and to provide scientific evidence for making preventive policies of air pollution and human health effects. Methods Seven staff members were recruited to wear the personal aerosol exposure monitor to detect PM2.5 and the time-activities during commuting were recorded, and the corresponding air monitoring data of PM2.5were collected at the same time. The personal exposure data and the monitoring data were analyzed through the linear regression model. Results The personal exposure levels of PM2.5 in different commuting patterns were significantly higher compared with the corresponding air monitoring data except for light railway（P〈0.05）, and the personal exposure data of all commuting patterns were statistically and positively correlated with the air monitoring data. Conclusion The air monitoring data can be used to project the personal exposure levels of all commuting patterns. The subway and the light railway should be the first choice in haze weather.
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