The Danish Gaussian Air Pollution Model (Oml): Description, Test and Sensitivity Analysis in View of Regulatory Applications

Berkowicz, Ruwim; Olesen, Henrik; Torp, U.

doi:10.1007/978-1-4757-9125-9_30

Cited by 53 publications

(24 citation statements)

References 19 publications

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“…We use wind dispersal of oilseed rape (OSR) pollen from area sources as an example system. Several good physically based models of wind dispersal exist for use where topography and weather data are known (Berkowicz et al 1986;Olesen et al 1992;Carruthers et al 1994;Giddings 2000;Aylor 2003). However, when deciding policy, it is often necessary to manage a threat arising at an unknown location and time, over spatio-temporal scales outside the practical capacity of such models.…”

Section: Introductionmentioning

confidence: 99%

Assembling spatially explicit landscape models of pollen and spore dispersal by wind for risk assessment

et al. 2006

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Models of windblown pollen or spore movement are required to predict gene flow from genetically modified (GM) crops and the spread of fungal diseases. We suggest a simple form for a function describing the distance moved by a pollen grain or fungal spore, for use in generic models of dispersal. The function has power-law behaviour over sub-continental distances. We show that air-borne dispersal of rapeseed pollen in two experiments was inconsistent with an exponential model, but was fitted by power-law models, implying a large contribution from distant fields to the catches observed. After allowance for this 'background' by applying Fourier transforms to deconvolve the mixture of distant and local sources, the data were best fit by power-laws with exponents between 1.5 and 2. We also demonstrate that for a simple model of area sources, the median dispersal distance is a function of field radius and that measurement from the source edge can be misleading. Using an inverse-square dispersal distribution deduced from the experimental data and the distribution of rapeseed fields deduced by remote sensing, we successfully predict observed rapeseed pollen density in the city centres of Derby and Leicester (UK).

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Section: Introductionmentioning

confidence: 99%

Assembling spatially explicit landscape models of pollen and spore dispersal by wind for risk assessment

et al. 2006

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“…The wind profile employed in Eqs. (1) and (2) was parameterizated following the MoninObukhov Similarity Theory and the OML model (Bercowicz et al, 1986):…”

Section: Methodsmentioning

confidence: 99%

Turbulent Eddy Diffusivities for a Planetary Boundary Layer Generated by Thermal and Mechanical Effects

Nunes¹,

Degrazia²,

Campos³

et al. 2013

Rev. Bras. Geof.

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ABSTRACT.To estimate the superficial concentration of contaminants an eulerian model of dispersion was used, where the main scheme is the diffusion-advection equation that employs turbulent eddy diffusivity. The aim of this work is a comparison between different eddy diffusivity derivations for a planetary boundary layer turbulence generated by thermal and mechanical effects. The accuracy of eddy diffusivity derivations was evaluated by comparing the data simulated in the eulerian dispersion model and the observed concentrations of the Copenhagen and Praire Grass experiments. Three convective eddy diffusivity derivations were compared among themselves: 1) proposed by Degrazia et al., 2) proposed Hostlag & Moeng and 3) the derivation gotten by the parameters of Hanna. Two neutral eddy diffusivity derivations were also compared: 1) proposed by Degrazia et al. and 2) gotten by the parameters of Hanna. In order to improve the comparisons some adjustments and increments were made in Hostlag & Moeng derivation and in that gotten by the parameters of Hanna. We can observe that despite the eddy diffusivities having been formulated by different ways, the results were similar and sufficiently satisfactory. In the convective case, the best simulations of each derivation showed a RESUMO. Na estimativa da concentração superficial de contaminantes foi usado um modelo de dispersão euleriano, tendo como esquema principal a equação de difusão-advecção que emprega coeficiente de difusão turbulento. O objetivo deste trabalhoé a comparação entre diferentes derivações de coeficientes de difusão para uma camada limite planetária cuja turbulênciaé gerada por fatores térmicos e mecânicos. A precisão das derivações foi calculada por meio da comparação entre os dados simulados pelo modelo euleriano de dispersão e os dados de concentração observados nos experimentos de Copenhagen e Praire Grass. Três derivações de coeficientes de difusão convectivos foram comparadas: 1) a proposta por Degrazia et al., 2) a proposta por Hostlag & Moeng, e 3) a derivação obtida através dos parâmetros de Hanna. Também foram comparadas duas derivações de coeficientes de difusão neutros: 1) uma proposta por Degrazia et al. e 2) a obtida por meio dos parâmetros de Hanna. Para uma melhor comparação, foram feitos alguns ajustes nas derivações de Hostlag e Moeng e na obtida através dos parâmetros de Hanna.Pode-se observar que apesar das derivações serem obtidas por diferentes metodologias, os resultados foram similares e suficientemente satisfatórios. Para o caso convectivo, as melhores simulações de cada derivação apresentaram Erro Quadrático Médio Normalizado entre 0,04 e 0,05 quando comparados com os dados do experimento de Copenhagen.Palavras-chave: modelo de dispersão, teoria de Taylor, escala de tempo lagrangeana.

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“…Draxler (1976)), and methods based on similarity theory (e.g. Berkowicz et al (1985)). With standard deviation formulas for the lateral spread (a y ) as proposed by Briggs (1974), Draxler (1976) or Berkowicz et al (1985), it appears that the measured lateral spread increases faster downwind in a complex terrain area than is predicted by ordinary o y (x)-algorithms, see Andren (1987).…”

Section: Dispersion Modelsmentioning

confidence: 99%

“…Berkowicz et al (1985)). With standard deviation formulas for the lateral spread (a y ) as proposed by Briggs (1974), Draxler (1976) or Berkowicz et al (1985), it appears that the measured lateral spread increases faster downwind in a complex terrain area than is predicted by ordinary o y (x)-algorithms, see Andren (1987). This might be due to winddirection shear in the vertical, a problem that was first treated by Högström (1964).…”

Section: Dispersion Modelsmentioning

confidence: 99%

Modeling the Dispersion of Vapor and Aerosol Particulates in the Atmospheric Boundary Layer

Chai¹,

Koračin²,

Enger³

1999

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The Danish Gaussian Air Pollution Model (Oml): Description, Test and Sensitivity Analysis in View of Regulatory Applications

Cited by 53 publications

References 19 publications

Assembling spatially explicit landscape models of pollen and spore dispersal by wind for risk assessment

Assembling spatially explicit landscape models of pollen and spore dispersal by wind for risk assessment

Turbulent Eddy Diffusivities for a Planetary Boundary Layer Generated by Thermal and Mechanical Effects

Modeling the Dispersion of Vapor and Aerosol Particulates in the Atmospheric Boundary Layer

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