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Effects of road dust PM on acute morbidity : TRAPART 1 Forsberg, Bertil ; Meister, Kadri ; Johansson, Christer ; Segerstedt, Bo

By: Contributor(s): Publication details: Umeå Umeå universitet, 2011Description: 10 sSubject(s): Online resources: Abstract: Health effects from PM have been reported to depend much on the fine fraction, PM2.5, while the coarse fraction, including road dust, has been seen as less harmful. In Swedish cities the proportion of cars with studded tyres is often 70-90 percent in winter, producing large emissions of road wear particles and in some cases violations of the Swedish air quality limits for PM10. Thus there has been a discussion whether these particles should be in focus or not. We have studied the effect of daily concentrations of PM10 from road dust on morbidity in terms of hospital admissions i Greater Stockholm. The concentration of road dust PM10 has been calculated from urban background PM10 from a TEOM instrument by subtracting the rural PM10 concentration and exhaust particles as PM10 estimated from the urban NOx contribution. The association between the mean of lag 0-1 (same day and yesterday) pollution concentration and daily number of cases was evaluated using Poisson regression (software R) with adjustments for meteorology, calendar variables, influenza and time trends.
Item type: Reports, conferences, monographs
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Health effects from PM have been reported to depend much on the fine fraction, PM2.5, while the coarse fraction, including road dust, has been seen as less harmful. In Swedish cities the proportion of cars with studded tyres is often 70-90 percent in winter, producing large emissions of road wear particles and in some cases violations of the Swedish air quality limits for PM10. Thus there has been a discussion whether these particles should be in focus or not. We have studied the effect of daily concentrations of PM10 from road dust on morbidity in terms of hospital admissions i Greater Stockholm. The concentration of road dust PM10 has been calculated from urban background PM10 from a TEOM instrument by subtracting the rural PM10 concentration and exhaust particles as PM10 estimated from the urban NOx contribution. The association between the mean of lag 0-1 (same day and yesterday) pollution concentration and daily number of cases was evaluated using Poisson regression (software R) with adjustments for meteorology, calendar variables, influenza and time trends.