COMBINING CHEMICAL AND METEOROLOGICAL DATA TO INFER SOURCE AREAS OF AIRBORNE POLLUTANTS

Models have been developed to identify and quantitatively apportion the contributions of sources to the measured concentrations of airborne constituents. These models have generally been applied to local, urban scale problems in which the differences in the patterns of elemental concentrations in the emissions of different sources are used to partition aerosol mass to the identified sources. However, these models do not provide information on the locations of the sources. New approaches are thus needed to find specifically where airborne contaminant emission sources can be found. Using models of atmospheric transport, meteorological information in the form of air parcel back trajectories can be calculated. The trajectories are presented as a series of locations where the air parcels that deliver material to a given sample were at fixed intervals, backwards in time. If the area covered by these endpoints is divided into a gridded array, the amount of time spent in a cell is related to the number of endpoint segment locations that fall into that cell. The ratio of the number of endpoints related to high concentration samples to the total number of endpoint that fall into the cell can be considered to be the conditional probability that the particular grid cell was a source of the species found in high concentration. This probability is called the potential source contribution function (PSCF). This approach has been applied to three problems of identifying the sources of secondary sulfate in particles at different scale lengths; sub-regional, regional, and semiglobal. At a sub-regional scale in the Los Angeles area of southern California, PSCF analysis was applied to measured SO2 and SO42- measured at one site downwind of Los Angeles. Transport of particulate SO42- to Dorset, Ontario was observed on a regional scale, and non-marine sulfate contributions to samples collected in the high Arctic were examined on a semi-global scale. In all cases good agreement was found between the high PSCF cells and previously identified source areas. In each case the analysis helped to provide an improved understanding of the source-receptor relationships for the particular scale length.