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Land use to characterize spatial representativeness of air quality monitoring stations and its relevance for model validation
Abstract The spatial representativeness of air quality monitoring stations is a crucial parameter when the observed concentration levels are used in an air quality assessment. Spatial representativeness defines to what extent the monitoring data is meaningful and useful in a spatial context. Within this paper a generic and robust methodology is presented for the assessment of the spatial representativeness of air pollution monitoring sites. The methodology relies on a statistical approach that links annual averaged concentration levels with land use characteristics. The methodology is demonstrated for the monitoring sites in the Belgian telemetric air quality network and then applied to define a set of zones with a given confidence level. Within such a zone the concentrations deviate to a maximum percentage from the measured values at the monitoring sites. Furthermore, the relevance of spatial representativeness for model validation is addressed and the technique is illustrated for the validation of the results of the regional air quality model BelEUROS. In general, the overall improvement of the model validation by taking into account spatial representativeness can be quantified as in the order of 20%.
Highlights ► A generic and robust methodology for spatial representativeness is presented. ► Methodology can be used to define a zone of a given confidence level. ► The relevance of spatial representativeness for model validation is addressed. ► Overall improvement of model validation can be quantified as in the order of 20%.
Land use to characterize spatial representativeness of air quality monitoring stations and its relevance for model validation
Abstract The spatial representativeness of air quality monitoring stations is a crucial parameter when the observed concentration levels are used in an air quality assessment. Spatial representativeness defines to what extent the monitoring data is meaningful and useful in a spatial context. Within this paper a generic and robust methodology is presented for the assessment of the spatial representativeness of air pollution monitoring sites. The methodology relies on a statistical approach that links annual averaged concentration levels with land use characteristics. The methodology is demonstrated for the monitoring sites in the Belgian telemetric air quality network and then applied to define a set of zones with a given confidence level. Within such a zone the concentrations deviate to a maximum percentage from the measured values at the monitoring sites. Furthermore, the relevance of spatial representativeness for model validation is addressed and the technique is illustrated for the validation of the results of the regional air quality model BelEUROS. In general, the overall improvement of the model validation by taking into account spatial representativeness can be quantified as in the order of 20%.
Highlights ► A generic and robust methodology for spatial representativeness is presented. ► Methodology can be used to define a zone of a given confidence level. ► The relevance of spatial representativeness for model validation is addressed. ► Overall improvement of model validation can be quantified as in the order of 20%.
Land use to characterize spatial representativeness of air quality monitoring stations and its relevance for model validation
Janssen, Stijn (Autor:in) / Dumont, Gerwin (Autor:in) / Fierens, Frans (Autor:in) / Deutsch, Felix (Autor:in) / Maiheu, Bino (Autor:in) / Celis, David (Autor:in) / Trimpeneers, Elke (Autor:in) / Mensink, Clemens (Autor:in)
Atmospheric Environment ; 59 ; 492-500
11.05.2012
9 pages
Aufsatz (Zeitschrift)
Elektronische Ressource
Englisch
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