Trajectory statistics-A new method to establish source-receptor relationships of air pollutants and its application to the transport of particulate sulfate in Europe

Abstract A new method of trajectory statistics was developed which allows the identification of source areas with higher spatial resolution than other methods. It uses ambient air pollutant concentration measurements at a receptor site and corresponding back trajectories arriving at that site. In a first step, each pollutant concentration is attributed to its trajectory. From this, a first guess “concentration field” is computed which shows potential source areas of the respective pollutant. In an iterative procedure, the concentrations are redistributed along their corresponding trajectories which continuously improves the “concentration field”. The new method was tested with a large set of back trajectories ending at 14 measurement sites of the EMEP network. It was used to identify potential source areas of particulate sulfate. The procedure successfully identified many source areas with a much higher resolution than what would have been achievable with existing methods. The locations of the source areas were compared with the locations of the emission maxima of an emission inventory and a good agreement was found, both qualitatively and quantitatively.

[1]  J. Harris,et al.  A 10-year trajectory flow climatology for Amsterdam Island, 1980–1989 , 1993 .

[2]  P. Samson,et al.  The influence of atmospheric transport on precipitation chemistry at two sites in the midwestern United States , 1989 .

[3]  A. Stohl,et al.  A method for computing single trajectories representing boundary layer transport , 1995 .

[4]  K. Weingartner,et al.  Trajectory analysis of MAP3S precipitation chemistry data at Ithaca, N.Y. , 1982 .

[5]  B. Strauss,et al.  Relationship between rain and snow acidity and air mass trajectory in eastern France , 1989 .

[6]  W. Klug,et al.  Evaluation of long range atmospheric transport models using environmental radioactivity data from the Chernobyl accident : the ATMES report , 1992 .

[7]  Andreas Stohl,et al.  Eine Wetterlagenklassifikation mittels Trajektorienclusterung , 1994 .

[8]  Trevor D. Davies,et al.  Cluster analysis: A technique for estimating the synoptic meteorological controls on air and precipitation chemistry—Method and applications , 1992 .

[9]  William H. Press,et al.  Numerical recipes in C. The art of scientific computing , 1987 .

[10]  A. Stohl,et al.  Atmospheric aerosol in the finnish arctic: Particle number concentrations, chemical characteristics, and source analysis , 1995 .

[11]  J. Kahl,et al.  A descriptive atmospheric transport climatology for the Mauna Loa Observatory, using clustered trajectories , 1990 .

[12]  A. Stohl,et al.  Origin of ozone in Vienna and surroundings, Austria , 1994 .

[13]  John M. Miller A five-year climatology of back trajectories from the Mauna Loa Observatory, Hawaii , 1981 .

[14]  Trevor D. Davies,et al.  Cluster analysis: A technique for estimating the synoptic meteorological controls on air and precipitation chemistry—Results from Eskdalemuir, South Scotland , 1992 .

[15]  Meng-Dawn Cheng,et al.  A receptor-oriented methodology for determining source regions of particulate sulfate observed at Dorset, Ontario , 1993 .

[16]  A. Stohl,et al.  Interpolation Errors in Wind Fields as a Function of Spatial and Temporal Resolution and Their Impact on Different Types of Kinematic Trajectories , 1995 .

[17]  Philip K. Hopke,et al.  A study of the sources of acid precipitation in Ontario, Canada , 1989 .

[18]  L. Ashbaugh A statistical trajectory technique for determining air pollution source regions , 1983 .

[19]  Willy Z. Sadeh,et al.  A residence time probability analysis of sulfur concentrations at grand Canyon national park , 1985 .

[20]  William H. Press,et al.  Book-Review - Numerical Recipes in Pascal - the Art of Scientific Computing , 1989 .