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dc.contributor.authorDacre, HF
dc.contributor.authorBedwell, P
dc.contributor.authorHertwig, D
dc.contributor.authorLeadbetter, SJ
dc.contributor.authorLoizou, P
dc.contributor.authorWebster, HN
dc.date.accessioned2020-09-10T10:00:04Z
dc.date.issued2020-02-20
dc.description.abstractRadionuclides released into the atmosphere following the Fukushima Dai-ichi Nuclear Power Plant (FDNPP) accident were detected by ground-based monitoring stations worldwide. The inter-continental dispersion of radionuclides provides a unique opportunity to evaluate the ability of atmospheric dispersion models to represent the processes controlling their transport and deposition in the atmosphere. Co-located measurements of radioxenon (133Xe) and caesium (137Cs) concentrations enable individual physical processes (dispersion, dry and wet deposition) to be isolated. In this paper we focus on errors in the prediction of 137Cs attributed to the representation of particle size and solubility, in the process of modelling wet deposition. Simulations of 133Xe and 137Cs concentrations using the UK Met Office NAME (Numerical Atmospheric-dispersion Modelling Environment) model are compared with CTBTO (Comprehensive Nuclear-Test-Ban Treaty Organisation) surface station measurements. NAME predictions of 137Cs using a bulk wet deposition parameterisation (which does not account for particle size dependent scavenging or solubility) significantly underestimate observed 137Cs. When a binned wet deposition parameterisation is implemented (which accounts for particle size dependent scavenging) the correlations between modelled and observed air concentrations improve at all 9 of the Northern Hemisphere sites studied and the respective RMSLE (root-mean-square-log-error) decreases by a factor of 7 due to a decrease in the wet-deposition of Aitken and Accumulation mode particles. Finally, NAME simulations were performed in which insoluble submicron particles are represented. Representing insoluble particles in the NAME simulations improves the RMSLE at all sites further by a factor of 7. Thus NAME is able to predict 137Cs with good accuracy (within a factor of 10 of observed 137Cs values) at distances greater than 10,000 km from FDNPP only if insoluble submicron particles are considered in the description of the source. This result provides further evidence of the presence of insoluble Cs-rich microparticles in the release following the accident at FDNPP and suggests that these small particles travelled across the Pacific Ocean to the US and further across the North Atlantic Ocean towards Europe.en_GB
dc.identifier.citationVol. 217, article 106193en_GB
dc.identifier.doi10.1016/j.jenvrad.2020.106193
dc.identifier.urihttp://hdl.handle.net/10871/122810
dc.language.isoenen_GB
dc.publisherElsevier / International Union of Radioecologyen_GB
dc.rights.embargoreasonUnder embargo until 20 February 2021 in compliance with publisher policyen_GB
dc.rights© 2020. This version is made available under the CC-BY-NC-ND 4.0 license: https://creativecommons.org/licenses/by-nc-nd/4.0/  en_GB
dc.subjectFukushimaen_GB
dc.subjectWet depositionen_GB
dc.subjectCaesiumen_GB
dc.subjectXenonen_GB
dc.subjectParticle sizeen_GB
dc.subjectSolubilityen_GB
dc.titleImproved representation of particle size and solubility in model simulations of atmospheric dispersion and wet-deposition from Fukushimaen_GB
dc.typeArticleen_GB
dc.date.available2020-09-10T10:00:04Z
dc.identifier.issn0265-931X
dc.descriptionThis is the author accepted manuscript. the final version is available from Elsevier via the DOI in this recorden_GB
dc.identifier.journalJournal of Environmental Radioactivityen_GB
dc.rights.uri https://creativecommons.org/licenses/by-nc-nd/4.0/  en_GB
dcterms.dateAccepted2020-02-05
rioxxterms.versionAMen_GB
rioxxterms.licenseref.startdate2020-02-05
rioxxterms.typeJournal Article/Reviewen_GB
refterms.dateFCD2020-09-10T09:57:51Z
refterms.versionFCDAM
refterms.panelBen_GB


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© 2020. This version is made available under the CC-BY-NC-ND 4.0 license: https://creativecommons.org/licenses/by-nc-nd/4.0/  
Except where otherwise noted, this item's licence is described as © 2020. This version is made available under the CC-BY-NC-ND 4.0 license: https://creativecommons.org/licenses/by-nc-nd/4.0/