Bayer-Oglesby, Lucy

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Lucy
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Bayer-Oglesby, Lucy

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Publikation

Determinants of perceived air pollution annoyance and association between annoyance scores and air pollution (PM2.5, NO2) concentrations in the European EXPOLIS study

2002, Rotko, Tuulia, Bayer-Oglesby, Lucy, Künzli, Nino, Carrer, Paolo, Nieuwenhuijsen, Mark J, Jantunen, Matti

Apart from its traditionally considered objective impacts on health, air pollution can also have perceived effects, such as annoyance. The psychological effects of air pollution may often be more important to well-being than the biophysical effects. Health effects of perceived annoyance from air pollution are so far unknown. More knowledge of air pollution annoyance levels, determinants and also associations with different air pollution components is needed. In the European air pollution exposure study, EXPOLIS, the air pollution annoyance as perceived at home, workplace and in traffic were surveyed among other study objectives. Overall 1736 randomly drawn 25–55-yr-old subjects participated in six cities (Athens, Basel, Milan, Oxford, Prague and Helsinki). Levels and predictors of individual perceived annoyances from air pollution were assessed. Instead of the usual air pollution concentrations at fixed monitoring sites, this paper compares the measured microenvironment concentrations and personal exposures of PM2.5 and NO2 to the perceived annoyance levels. A considerable proportion of the adults surveyed was annoyed by air pollution. Female gender, self-reported respiratory symptoms, downtown living and self-reported sensitivity to air pollution were directly associated with high air pollution annoyance score while in traffic, but smoking status, age or education level were not significantly associated. Population level annoyance averages correlated with the city average exposure levels of PM2.5 and NO2. A high correlation was observed between the personal 48-h PM2.5 exposure and perceived annoyance at home as well as between the mean annoyance at work and both the average work indoor PM2.5 and the personal work time PM2.5 exposure. With the other significant determinants (gender, city code, home location) and home outdoor levels the model explained 14% (PM2.5) and 19% (NO2) of the variation in perceived air pollution annoyance in traffic. Compared to Helsinki, in Basel and Prague the adult participants were more annoyed by air pollution while in traffic even after taking the current home outdoor PM2.5 and NO2 levels into account.

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Publikation

Personal exposures to NO2 in the EXPOLIS-study: relation to residential indoor, outdoor and workplace concentrations in Basel, Helsinki and Prague

2001, Kousa, Anu, Monn, Christian, Rotko, Tuulia, Alm, Sari, Bayer-Oglesby, Lucy, Jantunen, Matti J

Personal exposures, residential indoor, outdoor and workplace levels of nitrogen dioxide (NO2) were measured for 262 urban adult (25–55 years) participants in three EXPOLIS centres (Basel; Switzerland, Helsinki; Finland, and Prague; Czech Republic) using passive samplers for 48-h sampling periods during 1996–1997. The average residential outdoor and indoor NO2 levels were lowest in Helsinki (24 12 and18 11 mgm 3, respectively), highest in Prague (61 20 and43 23 mgm 3), with Basel in between (36 13 and27 13 mgm 3). Average workplace NO2 levels, however, were highest in Basel (36 24 mgm 3), lowest in Helsinki (27 15 mgm 3), with Prague in between (30 18 mgm 3). A time-weightedmicroenvironmental exposure model explained74% of the personal NO2 exposure variation in all centres and in average 88% of the exposures. Log-linear regression models, using residential outdoor measurements (fixedsite monitoring) combinedwith residential andwork characteristics (i.e. work location, using gas appliances and keeping windows open), explained48% (37%) of the personal NO2 exposure variation. Regression models based on ambient fixed site concentrations alone explained only 11–19% of personal NO2 exposure variation. Thus, ambient fixedsite monitoring alone was a poor predictor for personal NO2 exposure variation, but adding personal questionnaire information can significantly improve the predicting power.