A model for estimating the lifelong exposure to PM2.5 and NO2 and the application to population studies

被引:12
作者
Li, Naixin [1 ]
Maesano, Cara N. [2 ,3 ]
Friedrich, Rainer [1 ]
Medda, Emanuela [4 ]
Brandstetter, Susanne [5 ]
Kabesch, Michael [5 ]
Apfelbacher, Christian [6 ,7 ]
Melter, Michael [5 ]
Seelbach-Goebel, Birgit [8 ]
Annesi-Maesano, Isabella [2 ,3 ]
Sarigiannis, Dimosthenis [9 ]
机构
[1] Univ Stuttgart, Inst Energy Econ & Rat Use Energy, Hessbruhlstr 49a, D-70565 Stuttgart, Germany
[2] Sorbonne Univ, Dept Epidemiol Allerg & Resp Dis, Pierre Louis Inst Epidemiol & Publ Hlth, Paris, France
[3] INSERM, Paris, France
[4] Ist Super Sanita, Rome, Italy
[5] Univ Childrens Hosp Regensburg KUNO Clin, Regensburg, Germany
[6] Univ Regensburg, Inst Epidemiol & Prevent Med, Med Sociol, Regensburg, Germany
[7] Otto von Guericke Univ, Inst Social Med & Hlth Econ, Magdeburg, Germany
[8] Univ Regensburg, Clin Obstet & Gynecol St Hedwig, Regensburg, Germany
[9] Aristotle Univ Thessaloniki, Dept Chem Engn, Environm Engn Lab, Technol Div, Thessaloniki, Greece
关键词
Fine particles; Nitrogen dioxide; Exposure modelling; Sequence analysis; Socio-demographic characteristics; INDOOR NITROGEN-DIOXIDE; AIR-POLLUTION; PARTICULATE MATTER; PERSONAL EXPOSURE; OUTDOOR; ASSOCIATION; MORTALITY; EMISSIONS; IMPACT; CITIES;
D O I
10.1016/j.envres.2019.108629
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Numerous epidemiological studies have confirmed the negative influences of air pollutants on human health, where fine particles (PM2.5) and nitrogen dioxide (NO2) cause the highest health risks. However, the traditional studies have only involved the ambient concentration for a short to medium time period, which ignores the influence of indoor sources, the individual time-activity pattern, and the fact that the health status is impacted by the long-term accumulated exposure. The aim of this paper is to develop a methodology to simulate the lifelong exposure (rather than outdoor concentration) to PM2.5 and NO2 for individuals in Europe. This method is realized by developing a probabilistic model that integrates an outdoor air quality model, a model estimating indoor air pollution, an exposure model, and a life course trajectory model for predicting retrospectively the employment status. This approach has been applied to samples of two population studies in the frame of the European Commission FP7-ENVIRONMENT research project HEALS (Health and Environment-wide Associations based on Large Population Surveys), where socioeconomic data of the participants have been collected. Results show that the simulated exposures to both pollutants for the samples are influenced by socio-demographic characteristics, including age, gender, residential location, employment status and smoking habits. Both outdoor concentrations and indoor sources play an important role in the total exposure. Moreover, large variances have been observed among countries and cities. The application of this methodology provides valuable insights for the exposure modelling, as well as important input data for exploring the correlation between exposure and health impacts.
引用
收藏
页数:12
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