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Title: Incorporation of Radon-222 as a parameter in ME-2 to improve apportionment of PM2.5 sources in the Sydney region
Authors: Crawford, J
Cohen, DD
Chambers, SD
Williams, AG
Stelcer, E
Keywords: Ion beams
Radon 222
Fine particles
Issue Date: 1-Dec-2015
Publisher: Elsevier
Citation: Crawford, J., Cohen, D. D., Chambers, S., Williams, A., & Stelcer, E. (2013). Incorporation of Radon-222 as a parameter in ME-2 to improve apportionment of PM2.5 sources in the Sydney region. Atmospheric Environment, 80, 378-388. doi:10.1016/j.atmosenv.2013.08.015
Abstract: In recent years source apportionment of observed PM2.5 has been improved by incorporating meteorological information as additional factors in receptor modelling studies using ME-2. In this study we replace one of these meteorological factors, namely, parameterisation by wind speed, with a parameterisation based on hourly observations of the naturally occurring terrestrial gas Radon-222 (radon), and compare results of the two parameterisations over five years at an inland site in the Greater Sydney Region. The efficacy of the wind speed and radon parameterisation techniques is assessed by comparing regressions between the daily contributions from identified elemental fingerprints estimated from the wind speed and radon multi-linear models against those obtained from the corresponding bi-linear model (while the two models are solved simultaneously). The radon parameterisation yielded improved regressions for all source fingerprints, most notably Smoke and Autos (r2 ¼ 0.67 and 0.65, respectively, compared to 0.57 and 0.47 when the wind speed parameterisationwas used). Both parameterisation schemes were equally effective in attributing PM2.5 to wind sectors known to contain sources characterised by the observed fingerprints. Our findings demonstrate that incorporating radon as a parameter in ME-2 can lead to an improved PM2.5 source apportionment than that obtained using meteorological parameters alone, particularly for inland sites with distributed sources. © 2013, Elsevier Ltd.
Gov't Doc #: 6086
ISSN: 1352-2310
Appears in Collections:Journal Articles

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