Comparison of multi-receptor and single-receptor trajectory source apportionment (TSA) methods using artificial sources

Abstract

Two trajectory source apportionment methods were tested using an artificially generated data set to determine their ability to detect the known sources. The residence time or conditional probability method developed by Ashbaugh et al. [1985. A residence time probability analysis of sulfur concentrations at Grand Canyon National Park. Atmospheric Environment 19(8), 1263–1270] uses a single receptor at a time, whereas the new multi-receptor (MURA) method developed here uses several receptors at once in an attempt to detect the sources with higher accuracy. The methods were first tested using a simulation with a single source and then with another simulation using four sources. The ability of the methods to detect the sources was quantified for each simulation. The MURA trajectory method proved to be superior at identifying sources for these simulations.