One decade of parallel fine (PM 2.5 ) and coarse (PM 10 –PM 2.5 ) particulate matter measurements in Europe: trends and variability

Abstract. The trends and variability of PM 10 , PM 2.5 and PM coarse concentrations at seven urban and rural background stations in five European countries for the period between 1998 and 2010 were investigated. Collocated or nearby PM measurements and meteorological observations were used in order to construct Generalized Additive Models, which model the effect of each meteorological variable on PM concentrations. In agreement with previous findings, the most important meteorological variables affecting PM concentrations were wind speed, wind direction, boundary layer depth, precipitation, temperature and number of consecutive days with synoptic weather patterns that favor high PM concentrations. Temperature has a negative relationship to PM 2.5 concentrations for low temperatures and a positive relationship for high temperatures. The stationary point of this relationship varies between 5 and 15 °C depending on the station. PM coarse concentrations increase for increasing temperatures almost throughout the temperature range. Wind speed has a monotonic relationship to PM 2.5 except for one station, which exhibits a stationary point. Considering PM coarse , concentrations tend to increase or stabilize for large wind speeds at most stations. It was also observed that at all stations except one, higher PM 2.5 concentrations occurred for east wind direction, compared to west wind direction. Meteorologically adjusted PM time series were produced by removing most of the PM variability due to meteorology. It was found that PM 10 and PM 2.5 concentrations decrease at most stations. The average trends of the raw and meteorologically adjusted data are −0.4 μg m −3 yr −1 for PM 10 and PM 2.5 size fractions. PM coarse have much smaller trends and after averaging over all stations, no significant trend was detected at the 95% level of confidence. It is suggested that decreasing PM coarse in addition to PM 2.5 can result in a faster decrease of PM 10 in the future. The trends of the 90th quantile of PM 10 and PM 2.5 concentrations were examined by quantile regression in order to detect long term changes in the occurrence of very large PM concentrations. The meteorologically adjusted trends of the 90th quantile were significantly larger (as an absolute value) on average over all stations (−0.6 μg m −3 yr −1 ).