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|Title:||Assessing the impact of atmospheric stability on locally and remotely sourced aerosols at Richmond, Australia, using Radon-222|
|Citation:||Crawford, J., Chamber, S., Cohen, D., Williams, A., Griffiths, A., & Stelcer. E. (2016). Assessing the impact of atmospheric stability on locally and remotely sourced aerosols at Richmond, Australia, using Radon-222. Atmospheric Environment 127: 107-117. doi:10.1016/j.atmosenv.2015.12.034|
|Abstract:||A flexible radon-based scheme for the classification of nocturnal stability regimes was used for the interpretation of daily-integrated PM2.5 aerosol observations collected at Richmond, Australia, between 2007 and 2011. Source fingerprint concentrations for the dominant locally and remotely sourced aerosols were analysed by nocturnal radon stability category to characterise the influences of day-to-day changes in daily integrated atmospheric mixing. The fingerprints analysed included: smoke, vehicle exhaust, secondary sulfate and aged industrial sulfur. The largest and most consistent stability influences were observed on the locally sourced pollutants. Based on a 5-year composite, daily integrated concentrations of smoke were almost a factor of 7 higher when nocturnal conditions were classed as “stable” than when they were “near neutral”. For vehicle emissions a factor of 4 was seen. However, when the winter months were considered in isolation, it was found that these factors increased to 11.5 (smoke) and 5.5 (vehicle emissions) for daily average concentrations. The changes in concentration of the remotely sourced pollutants with atmospheric stability were comparatively small and less consistent, probably as a result of the nocturnal inversion frequently isolating near-surface observations from non-local sources at night. A similar classification was performed using the commonly-adopted Pasquill–Gifford (PG) stability typing technique based on meteorological parameters. While concentrations of fingerprints associated with locally-sourced pollutants were also shown to be positively correlated with atmospheric stability using the PG classification, this technique was found to underestimate peak pollutant concentrations under stable atmospheric conditions by almost a factor of 2. © 2015, Elsevier Ltd.|
|Gov't Doc #:||6403|
|Appears in Collections:||Journal Articles|
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