Long-term exposure and health risk assessment from air pollution: impact of regional scale mobility

International Journal of Health Geographics

Research

Lorenza Gilardi¹  Thilo Erbertseder¹  Annekatrin Metz-Marconcini²  Mattia Marconcini²  Thomas Esch² 

[1] German Remote Sensing Data Center, Department Atmosphere (DFD-ATM), German Aerospace Center (DLR), Münchener Str. 20, 82234, Weßling, Germany;German Remote Sensing Data Center, Department Land Surface Dynamics (DFD-LAX), German Aerospace Center (DLR), Münchener Str. 20, 82234, Weßling, Germany;

关键词: Exposure assessment;    Air pollutants;    Satellite-based data;    Dynamic population;    Diurnal variability;    Settlement mask;   

DOI  :  10.1186/s12942-023-00333-8

 received in 2023-04-04, accepted in 2023-05-08,  发布年份 2023

来源: Springer

【 摘 要 】

BackgroundThe negative effect of air pollution on human health is widely reported in recent literature. It typically involves urbanized areas where the population is concentrated and where mostprimary air pollutants are produced. A comprehensive health risk assessment is therefore of strategic importance for health authorities.MethodsIn this study we propose a methodology to perform an indirect and retrospective health risk assessment of all-cause mortality associated with long-term exposure to particulate matter less than 2.5 microns (PM2.5), nitrogen dioxide (NO2) and ozone (O3) in a typical Monday to Friday working week. A combination of satellite-based settlement data, model-based air pollution data, land use, demographics and regional scale mobility, allowed to examine the effect of population mobility and pollutants daily variations on the health risk. A Health Risk Increase (HRI) metric was derived on the basis of three components: hazard, exposure and vulnerability, utilizing the relative risk values from the World Health Organization. An additional metric, the Health Burden (HB) was formulated, which accounts for the total number of people exposed to a certain risk level.ResultsThe effect of regional mobility patterns on the HRI metric was assessed, resulting in an increased HRI associated with all three stressors when considering a dynamic population compared to a static one. The effect of diurnal variation of pollutants was only observed for NO2 and O3. For both, the HRI metric resulted in significantly higher values during night. Concerning the HB parameter, we identified the commuting flows of the population as the main driver in the resulting metric.ConclusionsThis indirect exposure assessment methodology provides tools to support policy makers and health authorities in planning intervention and mitigation measures. The study was carried out in Lombardy, Italy, one of the most polluted regions in Europe, but the incorporation of satellite data makes our approach valuable for studying global health.

【 授权许可】

CC BY   
© The Author(s) 2023

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