Comparison of the MURA and an improved single-receptor (SIRA) trajectory source apportionment (TSA) method using artificial sources |
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| Affiliation: | 1. The Centre for Atmospheric Science, The School of Earth, Atmospheric and Environmental Sciences, The University of Manchester, Simon Building, Brunswick Street, Manchester, M13 9PL, UK;2. School of Chemistry, The University of Bristol, Cantock''s Close BS8 1TS, UK;3. Facility for Airborne Atmospheric Measurements (FAAM), Building 125, Cranfield University, Cranfield, Bedford, MK43 0AL, UK;1. Morgan State University, GESTAR, USA;2. NASA Goddard Space Flight Center, USA;3. NASA Langley Research Center, USA;4. Earth System Science Interdisciplinary Center, University of Maryland, USA;5. University of Colorado, USA;6. National Center for Atmospheric Research, USA;1. Centre for Atmospheric Science, School of Earth, Atmospheric and Environmental Science, University of Manchester, Oxford Road, Manchester M13 9PL, UK;2. Biogeochemistry Research Centre, School of Chemistry, University of Bristol, Cantock''s Close, Bristol BS8 1TS, UK;1. Department of Geosciences, University of Rhode Island, Kingston, RI 02881, USA;2. Department of Civil and Environmental Engineering, University of Rhode Island, Kingston, RI 02881, USA;1. Department of Clinical Psychology, University of Amsterdam, The Netherlands;2. Department of Psychology, Ghent University, Ghent, Belgium;3. Department of Clinical Psychological Science, Maastricht University, Maastricht, The Netherlands;4. Amsterdam University College, The Netherlands |
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| Abstract: | Two trajectory source apportionment methods were tested using an artificially generated data set to determine their ability to detect the known sources. The forward-looking step from the multi-receptor trajectory analysis (MURA) method was added to the conditional probability (CP)method of Ashbaugh et al. [1985. A residence time probability analysis of sulfur concentrations at Grand Canyon National Park. Atmospheric Environment 19(8), 1263–1270] to develop the single-receptor forward CP (SIRA) method. The multi-receptor (MURA) and the SIRA methods were tested with three simulations using artificially generated sources. The ability of the methods to detect the sources was quantified for each simulation. The first simulation showed that the SIRA method is an improvement over the original CP method. The MURA trajectory method proved to be superior at identifying sources for the simulation located in the west and comparable to the SIRA method for the two simulations located in the east. |
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