Climate change has resulted in frequent extreme disasters and scarce resources, leading to a massive population into cities for favorable survival conditions, and also increasing urban air pollution burdens. It is urgent to assess population health risks related with urban air pollution, which usually relies on census method and meteorological measurement data. However, health impacts may be underestimated, because of challenges to represent the dynamic population mobility and perform unified analysis of different pollution hazards. The contribution of this work is to combine census data with Location Based Service to identify the spatiotemporal mobility pattern of urban population, and then population-weighted exposure (PWE) and health impacts of various air pollution (PM2.5, O3, and NO2) are synergistically evaluated. Taking Nanjing as the study area, it was found that the pollution peak areas correlated with population mobility in the study region, shifting from urban suburbs to the center during the daytime, with the maximum concentration exceeding 165 μg/m3. O3 caused a relatively high PWE level and had a greater health impact than PM2.5 and NO2, adding the mortality by up to 5 % especially on weekdays. The annual health impact of O3 was approximately twice that of PM2.5 and NO2. Human-centered regulation strategies of urban air pollution were proposed in terms of personnel behaviors, government control, and urban design towards mitigation of air pollution risk and sustainable urban development.

中文翻译：

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城市空气污染相关暴露和健康影响的时空分析：推动以人为本的监管和控制


气候变化导致极端灾害频发，资源稀缺，导致大量人口涌入城市寻求良好的生存条件，也增加了城市空气污染的负担。评估与城市空气污染相关的人口健康风险刻不容缓，这通常依赖于普查方法和气象测量数据。然而，由于难以表示动态的人口流动性和对不同的污染危害进行统一分析，健康影响可能被低估。这项工作的贡献是将人口普查数据与基于位置的服务相结合，以确定城市人口的时空流动性模式，然后协同评估各种空气污染（PM2.5、O3 和 NO2）的人口加权暴露 （PWE） 和健康影响。以南京市为研究区，发现污染峰值区域与研究区人口流动性相关，白天由市郊向中心转移，最高浓度超过165 μg/m3。O3 导致相对较高的 PWE 水平，并且比 PM2.5 和 NO2 对健康的影响更大，使死亡率增加高达 5%，尤其是在工作日。O3 的年度健康影响大约是 PM2.5 和 NO2 的两倍。从人员行为、政府控制和城市设计等方面提出了以人为本的城市空气污染监管策略，以减轻空气污染风险和城市可持续发展。