Air quality forecasts at kilometer scale grid over Spanish complex terrains

dc.contributor.authorPay Pérez, María Teresa
dc.contributor.authorMartínez, F.
dc.contributor.authorGuevara, M.
dc.contributor.authorBaldasano Recio, José M. (José María)
dc.date.accessioned2016-05-26T14:26:54Z
dc.date.available2016-05-26T14:26:54Z
dc.date.issued2014-09-08
dc.date.updated2016-05-26T14:26:59Z
dc.description.abstractThe Caliope Air Quality Forecast System (CALIOPE-AQFS) represents the current state of the art in air quality forecasting systems of high-resolution running on high-performance computing platforms. It provides a 48 h forecast of NO2, O3, SO2, PM10, PM2.5, CO, and C6H6 at a 4 km horizontal resolution over all of Spain, and at a 1 km horizontal resolution over the most populated areas in Spain with complex terrains (the Barcelona (BCN), Madrid (MAD) and Andalusia (AND) domains). Increased horizontal resolution from 4 to 1 km over the aforementioned domains leads to finer textures and more realistic concentration maps, which is justified by the increase in NO2/O3 spatial correlation coefficients from 0.79/0.69 (4 km) to 0.81/0.73 (1 km). High-resolution emissions using the bottom-up HERMESv2.0 model are essential for improving model performance when increasing resolution on an urban scale, but it is still insufficient. Decreasing grid spacing does not reveal the expected improvement in hourly statistics, i.e., decreasing NO2 bias by only ~ 2 μg m−3 and increasing O3 bias by ~ 1 μg m−3. The grid effect is less pronounced for PM10, because part of its mass consists of secondary aerosols, which are less affected than the locally emitted primary components by a decreasing grid size. The resolution increase has the highest impact over Barcelona, where air flow is controlled mainly by mesoscale phenomena and a lower planetary boundary layer (PBL). Despite the merits and potential uses of the 1-km simulation, the limitations of current model formulations do not allow confirmation of their expected superiority close to highly urbanized areas and large emissions sources. Future work should combine high grid resolutions with techniques that decrease subgrid variability (e.g., stochastic field methods), and also include models that consider urban morphology and thermal parameters.
dc.format.extent21 p.
dc.format.mimetypeapplication/pdf
dc.identifier.idgrec657249
dc.identifier.issn1991-959X
dc.identifier.urihttps://hdl.handle.net/2445/98904
dc.language.isoeng
dc.publisherEuropean Geosciences Union (EGU)
dc.relation.isformatofReproducció del document publicat a: http://dx.doi.org/10.5194/gmd-7-1979-2014
dc.relation.ispartofGeoscientific Model Development, 2014, vol. 7, p. 1979-1999
dc.relation.urihttp://dx.doi.org/10.5194/gmd-7-1979-2014
dc.rightscc-by (c) Pay Pérez, María Teresa et al., 2014
dc.rights.accessRightsinfo:eu-repo/semantics/openAccess
dc.rights.urihttp://creativecommons.org/licenses/by/3.0/es
dc.sourceArticles publicats en revistes (Genètica, Microbiologia i Estadística)
dc.subject.classificationQualitat de l'aire
dc.subject.classificationEspanya
dc.subject.otherAir quality
dc.subject.otherSpain
dc.titleAir quality forecasts at kilometer scale grid over Spanish complex terrains
dc.typeinfo:eu-repo/semantics/article
dc.typeinfo:eu-repo/semantics/publishedVersion

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