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https://apo.ansto.gov.au/dspace/handle/10238/9417
Title: | Characterising diurnal & synoptic timescale changes in urban air quality using Radon-222 |
Authors: | Chambers, SD Kikaj, D Podstawczyńska, A Williams, AG Crawford, J Griffiths, AD |
Keywords: | Daily variations Radon 222 Urban areas Air quality Atmospheres Emission Pollution Temperature inversions |
Issue Date: | 1-May-2020 |
Publisher: | Europenan Geosciences Union |
Citation: | Chambers, S., Kikaj, D., Podstawczyńska, A., Willaiams, A., Crawford, J., & Griffiths, A. (2020) Characterising diurnal & synoptic timescale changes in urban air quality using Radon-222. Paper presented at the EGU General Assembly 2020 Online, 4-8 May 2020. |
Series/Report no.: | EGU2020-1506 |
Abstract: | Urban air quality is strongly influenced by the atmosphere’s ability to disperse primary emissions and opportunities for secondary pollution formation. In mid- to high-latitude regions that experience enduring winter snow cover or soil freezing, regional subsidence and stagnation associated with persistent anti-cyclonic conditions such as the “Siberian High” can lead to “cold pool” or “persistent inversion” events. These events can result in life-threatening pollution episodes that last for weeks. While often associated with complex topography [1,2], persistent inversion events can also influence the air quality of urban centres in flat, inland regions [3]. This presentation will describe a recently-developed radon-based technique for identifying and characterising synoptic-timescale persistent inversion events, which is proving to be a simple and economical alternative to contemporary meteorological approaches that require regular sonde profiles [1]. Furthermore, key assumptions of the radon-based technique to characterise diurnaltimescale changes in the atmospheric mixing state described by Chambers et al. [4] are violated during persistent inversion conditions. Here we demonstrate how atmospheric class-typing, through successive application of radon-based techniques for identifying synoptic- and diurnaltimescale changes in the atmospheric mixing state, improves understanding of atmospheric controls on urban air quality in non-summer months across the full diurnal cycle. This knowledge translates directly to statistically-robust techniques for assessing public exposure to pollution, and for evaluating the efficacy of pollution mitigation measures. Lastly, we show how atmospheric class-typing can be used to enhance the evaluation of chemical transport models. © Author(s) 2020 |
Gov't Doc #: | 9481 |
URI: | https://presentations.copernicus.org/EGU2020/EGU2020-1506_presentation.pdf http://apo.ansto.gov.au/dspace/handle/10238/9417 https://doi.org/10.5194/egusphere-egu2020-1506 |
Appears in Collections: | Conference Publications |
Files in This Item:
File | Description | Size | Format | |
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EGU2020-1506_presentation.pdf | 1.59 MB | Adobe PDF | ![]() View/Open | |
EGU2020-1506-print.pdf | 292.39 kB | Adobe PDF | ![]() View/Open |
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