Please use this identifier to cite or link to this item: http://hdl.handle.net/10773/26577
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dc.contributor.authorCoelho, Sílviapt_PT
dc.contributor.authorFerreira, Joanapt_PT
dc.contributor.authorRodrigues, Verapt_PT
dc.contributor.authorRafael, Sandrapt_PT
dc.contributor.authorBorrego, Carlospt_PT
dc.contributor.authorLopes, Myriampt_PT
dc.date.accessioned2019-09-18T09:58:41Z-
dc.date.available2019-09-18T09:58:41Z-
dc.date.issued2017-
dc.identifier.issn1746-448Xpt_PT
dc.identifier.urihttp://hdl.handle.net/10773/26577-
dc.description.abstractAir pollution has become a growing concern in the past few years, with an increasing number of acute air pollution episodes in many cities worldwide. Ozone (O3) is a powerful oxidising agent and one of the air pollutants of most concern in Europe. Source apportionment modelling provides valuable information on the contributions of different source sectors and source regions to ozone concentrations. This information can be useful in designing air quality management strategies and in understanding the potential benefits of reducing emissions from a particular source category. In the present work, the Comprehensive Air Quality Model with Extensions (CAMx), with its Ozone Source Apportionment Technology (OSAT), was applied over Amsterdam Region, Netherlands, for the period of 8th to 12th July 2010, when high concentration of ozone were measured in several air quality monitoring stations in the region of Amsterdam. The contributions of different source categories and the NOx/VOC limitation to the ozone formation were quantified. Results indicated a great influence of transboundary transport on the O3 simulated concentrations. The OSAT tool revealed that this is the main factor affecting O3 levels in the area of study, followed by VOC emissions from solvent use and NOx emissions from industry and other sources not individually analysed. O3 formation is slightly more NOx limited than VOC limited.pt_PT
dc.language.isoengpt_PT
dc.publisherWIT presspt_PT
dc.relationThis work was partially supported by the ClairCity project. ClairCity has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement 689289. The authors would like to thank Hugo A. C. Denier van der Gon and Jeroen J. P. Kuenen for the access and use of the TNO MACC_II European Emission Inventory. The authors would also like to acknowledge the financial support through national funds from FCT – Science and Technology Portuguese Foundation for the Post Doc grant of J. Ferreira (SFRH/BPD/100346/2014) and the PhD grant of S. Rafael (SFRH/BD/103184/2014).pt_PT
dc.relationinfo:eu-repo/grantAgreement/EC/H2020/689289/EUpt_PT
dc.relationSFRH/BPD/100346/2014pt_PT
dc.relationSFRH/BD/103184/2014pt_PT
dc.rightsopenAccesspt_PT
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/pt_PT
dc.subjectOzonept_PT
dc.subjectNumerical modellingpt_PT
dc.subjectSource apportionmentpt_PT
dc.titleIdentification and analysis of source contributions to the air quality in the Amsterdam Regionpt_PT
dc.typearticlept_PT
dc.description.versionpublishedpt_PT
dc.peerreviewedyespt_PT
degois.publication.firstPage31pt_PT
degois.publication.lastPage40pt_PT
degois.publication.titleWIT Transactions on Ecology and the Environmentpt_PT
degois.publication.volume211pt_PT
dc.identifier.doi10.2495/AIR170031pt_PT
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DAO - Artigos

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