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dc.contributor.authorBoermans GMF
dc.contributor.authorvan Pul WAJ
dc.date.accessioned2017-02-20T06:53:04
dc.date.issued1993-09-30
dc.identifier722105001
dc.description.abstractSLAM (Short-term Local scale Ammonia transport Model) has been developed to calculate the ammonia concentrations in a multiple source area on a short term (hour) and local scale (100 m up to 15 km). In SLAM the dispersion in the surface layer is modelled using a description given by Gryning et al. (1987). The model also takes into account dry deposition and chemical conversion of ammonia as well as a background concentration caused by remote sources outside the model area. The meteorological input parameters are hourly averaged values of wind speed, wind direction and its standard deviation, temperature and global radiation. The grid setting is limited to 75 x 75 grids within an area of 15 x 15 km. Also extra receptor points can be specified. Basically the number of sources is unlimited but will be restricted by computing time. A sensitivity analysis of several model parameters (except emission strength) showed that wind speed, standard deviation of the lateral wind global radiation, source height and height at which the concentration was calculated, were the most important factors influencing the calculated concentrations. Uncertainties in emissions are directly translated into to model results and are expected to be the largest uncertainty source. SLAM largely overestimated measured concentrations when the wind velocity was < 1.5 m s-1. For wind velocities > 1.5 m s-1 SLAM calculated a 10-15% higher yearly averaged concentration. Differences between measured and calculated diurnal concentration patterns were 10-30%. From the comparison with mobile measurements it was concluded that the spatial distribution of the ammonia concentration in time by SLAM was reasonable represented. Large deviations between the calculated and measured concentrations could be attributed to a strong variation in local emissions not represented in the inventory. SLAM can easily be adjusted or extended to describe the concentration of other gases and aerosols emitted from multiple source areas.<br>
dc.description.sponsorshipDGM/LE
dc.format.extent47 p
dc.language.isonl
dc.publisherRijksinstituut voor Volksgezondheid en Milieu RIVM
dc.relation.ispartofRIVM Rapport 722105001
dc.relation.urlhttp://www.rivm.nl/bibliotheek/rapporten/722105001.html
dc.subject15nl
dc.subjectwiskundig modelnl
dc.subjecttransportnl
dc.subjectammoniaknl
dc.subjectkorte termijnnl
dc.subjectkleinschalig; dispersienl
dc.subjectverzuringnl
dc.subjectverspreidingnl
dc.subjectmodellingen
dc.subjecttransport processesen
dc.subjectammoniaen
dc.subjectshort termen
dc.subjectdispersionen
dc.subjectacidificationen
dc.subjectsmall scaleen
dc.titleSLAM, een transportmodel voor de korte termijn en de korte afstand met als toepassing de beschrijving van de verspreiding van ammoniaknl
dc.title.alternative[SLAM, a Short-term and Local-scale Ammonia transport Model.]en
dc.typeReport
dc.date.updated2017-02-20T05:53:04Z
html.description.abstractSLAM (Short-term Local scale Ammonia transport Model) has been developed to calculate the ammonia concentrations in a multiple source area on a short term (hour) and local scale (100 m up to 15 km). In SLAM the dispersion in the surface layer is modelled using a description given by Gryning et al. (1987). The model also takes into account dry deposition and chemical conversion of ammonia as well as a background concentration caused by remote sources outside the model area. The meteorological input parameters are hourly averaged values of wind speed, wind direction and its standard deviation, temperature and global radiation. The grid setting is limited to 75 x 75 grids within an area of 15 x 15 km. Also extra receptor points can be specified. Basically the number of sources is unlimited but will be restricted by computing time. A sensitivity analysis of several model parameters (except emission strength) showed that wind speed, standard deviation of the lateral wind global radiation, source height and height at which the concentration was calculated, were the most important factors influencing the calculated concentrations. Uncertainties in emissions are directly translated into to model results and are expected to be the largest uncertainty source. SLAM largely overestimated measured concentrations when the wind velocity was &lt; 1.5 m s-1. For wind velocities &gt; 1.5 m s-1 SLAM calculated a 10-15% higher yearly averaged concentration. Differences between measured and calculated diurnal concentration patterns were 10-30%. From the comparison with mobile measurements it was concluded that the spatial distribution of the ammonia concentration in time by SLAM was reasonable represented. Large deviations between the calculated and measured concentrations could be attributed to a strong variation in local emissions not represented in the inventory. SLAM can easily be adjusted or extended to describe the concentration of other gases and aerosols emitted from multiple source areas.&lt;br&gt;


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