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Measured and modeled personal and environmental NO2 exposure

Publiceringsår: 2012
Språk: Engelska
Publikation/Tidskrift/Serie: Population Health Metrics
Volym: 10
Nummer: 10
Dokumenttyp: Artikel i tidskrift
Förlag: BioMed Central

Sammanfattning

Abstract in Undetermined

Background: Measured or modeled levels of outdoor air pollution are being used as proxies for individual exposure in a growing number of epidemiological studies. We studied the accuracy of such approaches, in comparison with measured individual levels, and also combined modeled levels for each subject's workplace with the levels at their residence to investigate the influence of living and working in different places on individual exposure levels.



Methods: A GIS-based dispersion model and an emissions database were used to model concentrations of NO2 at the subject's residence. Modeled levels were then compared with measured levels of NO2. Personal exposure was also modeled based on levels of NO2 at the subject's residence in combination with levels of NO2 at their workplace during working hours.



Results: There was a good agreement between measured facade levels and modeled residential NO2 levels (r(s) = 0.8, p > 0.001); however, the agreement between measured and modeled outdoor levels and measured personal exposure was poor with overestimations at low levels and underestimation at high levels (r(s) = 0.5, p > 0.001 and r(s) = 0.4, p > 0.001) even when compensating for workplace location (r(s) = 0.4, p > 0.001).



Conclusion: Modeling residential levels of NO2 proved to be a useful method of estimating facade concentrations. However, the agreement between outdoor levels (both modeled and measured) and personal exposure was, although significant, rather poor even when compensating for workplace location. These results indicate that personal exposure cannot be fully approximated by outdoor levels and that differences in personal activity patterns or household characteristics should be carefully considered when conducting exposure studies. This is an important finding that may help to correct substantial bias in epidemiological studies.

Nyckelord

  • Public Health, Global Health, Social Medicine and Epidemiology

Övriga

Published
  • BECC
  • ISSN: 1478-7954

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