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dc.contributor.authorAguilera, Inmaculada
dc.contributor.authorBasagaña, Xavier
dc.contributor.authorPay Pérez, M. Teresa
dc.contributor.authorAgis, David
dc.contributor.authorBouso, Laura
dc.contributor.authorForaster, María
dc.contributor.authorRivera, Marcel
dc.contributor.authorBaldasano Recio, José María
dc.contributor.authorKünzli, Nino
dc.contributor.otherUniversitat Politècnica de Catalunya. Departament de Projectes d'Enginyeria
dc.date.accessioned2013-04-02T16:50:49Z
dc.date.created2013-06-01
dc.date.issued2013-06-01
dc.identifier.citationAguilera, I. [et al.]. Evaluation of the CALIOPE air quality forecasting system for epidemiological research: the example of NO2 in the province of Girona (Spain). "Atmospheric environment", 01 Juny 2013, vol. 72, núm. June, p. 134-141.
dc.identifier.issn1352-2310
dc.identifier.urihttp://hdl.handle.net/2117/18548
dc.description.abstractBackground Air quality models are being increasingly used to estimate long-term individual exposures to air pollution in epidemiological studies. Most of them have been evaluated against measurements from a limited number of monitoring stations, which may not properly reflect the exposure characteristics of the study population. Methods We evaluated the performance of the high-resolution CALIOPE air quality forecasting system over a large sample of passive measurements of NO2 conducted at 635 home outdoor locations of the Girona province (Spain) during several 4-week sampling campaigns over one year (July 2007–June 2008). Sampling sites were superposed over the 4 km × 4 km CALIOPE grid, and average NO2 modeled concentrations were derived for all measurements conducted during the same sampling campaign at all the sampling sites located within the same grid cell. In addition, the ratio between measured and modeled concentrations for the whole study period at one fixed monitoring station was used to post-process the modeled values at the home outdoor locations. Results The correlation between measured and modeled concentrations for the entire study area (which includes urban settings, middle-size towns, and rural areas) was 0.78. Modeled concentrations were underestimated in the whole study area. After correcting the modeled concentrations by the measured to modeled ratio at the fixed station (r = 0.25), they were very similar to the measured concentrations (27.7 μg m−3 and 29.3 μg m−3, respectively). However, the performance of the modeling system depends on the type of subarea and is affected by the sub-grid emission sources. Conclusions The evaluation over the heterogenous Girona province showed that CALIOPE is able to reproduce the spatial variability of 4-week NO2 concentrations at the small regional level. CALIOPE output data is a valuable tool to complement study-specific air pollution measurements by incorporating regional spatial variability as well as short- and long-term temporal variability of background pollution in epidemiological research.
dc.format.extent8 p.
dc.language.isoeng
dc.rightsAttribution-NonCommercial-NoDerivs 3.0 Spain
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/3.0/es/
dc.subjectÀrees temàtiques de la UPC::Desenvolupament humà i sostenible::Degradació ambiental::Contaminació atmosfèrica
dc.subject.lcshAir quality -- Measurement -- Mathematical models
dc.titleEvaluation of the CALIOPE air quality forecasting system for epidemiological research: the example of NO2 in the province of Girona (Spain)
dc.typeArticle
dc.subject.lemacAire -- Qualitat -- Mesurament -- Models matemàtics
dc.contributor.groupUniversitat Politècnica de Catalunya. MTA - Modelització i Tecnologia Ambiental
dc.identifier.doi10.1016/j.atmosenv.2013.02.035
dc.relation.publisherversionhttp://www.sciencedirect.com/science/article/pii/S1352231013001362
dc.rights.accessRestricted access - publisher's policy
local.identifier.drac11803669
dc.description.versionPostprint (published version)
dc.date.lift10000-01-01
local.citation.authorAguilera, I.; Basagaña, X.; Pay, M.T.; Agis, D.; Bouso, L.; Foraster, M.; Rivera, M.; Baldasano, J.; Künzli, N.
local.citation.publicationNameAtmospheric environment
local.citation.volume72
local.citation.numberJune
local.citation.startingPage134
local.citation.endingPage141


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