Analysis of long-range transport influences on urban PM 10 using two-stage atmospheric trajectory clusters

Abstract

There is evidence that long-range transport of natural and/or anthropogenic particles can have a negative impact on urban air quality. Certain European cities may fail to comply with the currently implemented 24-h PM 10 limit value due to the additional impact of remote sources of particles, which are not controllable at local level. For that reason, reliable methodologies identifying long-range transport patterns and quantifying their contribution to urban PM 10 levels are required. In this study, a two-stage clustering methodology was developed and applied to back trajectories arriving in three European cities: Athens, Madrid and Birmingham, which experience large, moderate and small numbers of daily PM 10 episodes, respectively. The atmospheric trajectories used in this analysis were computed with HYSPLIT model (NOAA) for a 3-year period. The two-stage cluster analysis has the advantage of providing highly disaggregated trajectory clusters, which proved to correspond to significantly different PM 10 levels. In the case of Madrid and Birmingham, clusters of trajectories originating from North Africa and continental Europe, respectively, were strongly associated with the highest PM 10 levels recorded in selected monitoring stations. In Athens, long-range transport patterns and trans-boundary influences were less evident, which highlighted the more substantial impact of local emission sources. Finally, two simple statistical indexes were proposed for assessing PM 10 episodes associated with different clusters of trajectories. This study has established a practical methodology for examining the impact of long-range atmospheric transport on local air quality, without resorting to high resource-demanding source apportionment techniques.