Abstract
Three sets of simulated aerosol compositional data were prepared to (1) assess the current state of the art of source apportionment procedures and (2) provide initial sets of test data to aid method development. The data sets were generated from reported source profiles, real meteorological data (St. Louis, 1976) and two constructed city plans. Following plume dispersion by means of the RAM model, 40 ‘samples’ having known source contributions and error structure were generated for each set. Seven laboratories participating in the Mathematical and Empirical Receptor Models Workshop (Quail Roost II) undertook deconvolution of one or two of the sets by various numerical techniques (chemical mass balance or multivariate). Comparison of the participants' results with the known source contributions showed that the source contribution estimates were consistent with the truth within a factor of ~ 2 and that the uncertainty estimates ranged from much too conservative (broad) to much too small. No unique method of choice emerged from this exercise; the participants' various techniques appeared complementary and capable of resolving ~ 6–9 different sources. The intercomparison did allow us to formulate suggestions for improving the simulation process per se and for improving the various treatments (especially with respect to estimating uncertainties).
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