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OML: Model description

Below follows a description of the OML model. The description uses essentially the same format as the web-based model catalogue of atmospheric dispersion models  which is operated by the European Topic Centre on Air Quality under the European Environment Agency.

Alternative sources of information:


Model name

OML Acronym for the Danish term "Operationelle Meteorologiske Luftkvalitetsmodeller"

Contact address

Aarhus University

Department of Environmental Science

P.O. Box 358

DK-4000 Roskilde


Att. Per Løfstrøm or Anne Sofie Lansø

E-mail: oml@envs.au.dk 

URL: http://www.au.dk/oml-international

Model versions and status

The following version is currently distributed:

OML-Multi 7.0, Windows (in Danish and English). Released August 2020.

Intended field of application

The OML model is a modern Gaussian plume model intended to be used for distances up to about 20 km from the source. The source is typically one or more stacks, and possibly also area sources. Typically, the OML model is applied for regulatory purposes. In particular, it is the recommended model to be used for environmental impact assessments when new industrial sources are planned in Denmark. The model can be used for both high and low sources; it is not suitable for complex terrain conditions. The model requires information on emission and meteorology on an hourly basis. It computes a time series of concentrations at user-specified receptor points, from which statistics are extracted and presented to the user.

Model type and dimension

OML is a modern Gaussian plume model, based on boundary layer scaling instead of relying on Pasquill stability classification. It belongs to the same class of models as UK-ADMS, AERMOD and HPDM.

Model description summary

The model describes dispersion of a passive, or possibly buoyant, gas from a number of sources. It is characteristic for the OML model that it does not use traditional discrete stability categories, but instead describes dispersion processes in terms of basic boundary-layer scaling parameters, such as friction velocity, Monin-Obukhov length, and the convective velocity scale. Thus, before being used by the model, meteorological measurements must be processed by a pre-processor. In the OML model, the Gaussian dispersion parameters sigma-y and sigma-z are not - as in conventional operational models - functions only of stability category and distance from the source. Instead, they are continuous functions of several boundary layer parameters. The dispersion parameters are regarded as the result of contributions from several mechanisms: convective turbulence, mechanical turbulence, plume buoyancy and building downwash. Their dependence on source height is taken explicitly into account. The plume rise is modelled by methods proposed by Briggs (1984) supplemented by a number of extensions. In contrast to most conventional models, penetration of the plume into the atmosphere above the mixing layer is not simulated as an on/off process. Instead, the extent of plume penetration is considered.


The model is Gaussian. It thus essentially assumes that the plume has a straight centre line, pointing along the assigned wind direction. The concentration distribution is Gaussian, both horizontally and vertically. Under low wind conditions, a Gaussian model does not perform well, because the basic assumptions underlying the model are violated. The model assumes stationary conditions.

In its current version, the model does not take account of deposition.

The model calculates hourly averaged concentration values. Conversion to shorter averaging times is not simple.

The model does not account for changes in turbulence regimes acting on a plume due to changes in surface characteristics, e. g. from land to water or vice versa.

The model is not a complex terrain model, although it does include some simple algorithms to describe dispersion over slightly hilly terrain.

The handling of building effects is based on simple methods, whereas in reality, aerodynamics in the wake of a building is an extremely complex matter. The primary intent of the building effect algorithm used in OML-Point is to improve concentration estimates applicable for distances beyond ca. five building heights downwind. Concentration estimates close to buildings should not be considered reliable.


Temporal resolution

The model is designed to work with input and output in the form of one-hour averages

Horizontal resolution

Concept not applicable (the model is a Gaussian plume model)

Vertical resolution

Concept not applicable (the model is a Gaussian plume model)



Gaussian plume


Boundary layer scaling


The version 6.0 does not account for deposition. Version 6.2 performs very simple and conservative estimates based on average concentrations (without deposition) and an average deposition velocity supplied by the user. Version 7.0 estimates ammonia deposition from animal housing located in Denmark with outlet heights less than 15 m, and is a simplified version of OML-DEP. This part of deposition interface in version 7.0 is in Danish only.



Solution technique

Not applicable (Gaussian plume model)

Input requirements


Specify emission strengths etc. for point sources and area sources. Further indicate data concerning buildings close to the source (in order to estimate building downwash).


Before being used by the model, meteorological measurements must be processed by a pre-processor, the OML meteorological preprocessor.For use in Denmark, processed meteorological data are available off-the-shelf for many locations. The OML meteorological preprocessor has typically as input hourly meteorological measurements from a synoptic or analogous surface station, and twice-daily vertical profiles of temperature from a nearby radiosonde station. Output is in this case hourly values of turbulence parameters: most essentially sensible heat flux, Monin-Obukhov length, friction velocity and mixing height. More specialised versions of the preprocessor have been designed for non-standard input such as mast measurements instead of synoptic surface data. The main elements of the meteorological preprocessor have been documented in a number of publications (e.g. Berkowicz, R. and Prahm, L.P. (1982): Sensible heat flux estimated from routine meteorological data by the resistance method. J.App.Met. 21, 1845-1864; and:Olesen, H.R. and Brown, N. (1992, 2. edition): The OML meteorological preprocessor - a software package for the preparation of meteorological data for dispersion models. MST LUFT-A 122. National Environmental Research Institute, DK-4000 Roskilde, Denmark.)


Specified in the form of terrain heights at receptor locations.

Initial conditions

Not applicable

Boundary conditions

Not applicable

Other input requirements

Receptor data: position and height of receptors

Output quantities

The usual output from a model run is a number of summary tables. OML-Multi allows far more flexibility in output than OML-Point. Output tables include averages, 99-percentiles and many other statistics related to EU limit values. Tables can be produced on a monthly, yearly or overall basis, calculated at each receptor. OML-Multi can display the results in the form of simple maps. Further, the tables may be exported and subjected to further data processing such as graphical presentation etc. by third party software.

User interface availability

The OML-Multi model is designed for the Windows operating system (any version of Windows). OML-Multi allows the user to choose either English or Danish language for the menus and help text.

User community

The OML model is being widely used in Denmark by non-expert users in local environmental agencies, by consulting engineers and by large industries. If the meteorological input is available, basic use of the model can be mastered in an hour of work. Familiarity with the model requires somewhat more. Users outside Denmark will normally need processed meteorological data from local stations. The preprocessing of meteorological data is a rather specialised task, which involves running the preprocessor, and possibly adapting it to local conditions.

Previous applications

The model is being widely applied in Denmark, and has also found use in some other countries. In Sweden, the Swedish Meteorological and Hydrological Institute (SMHI) maintains a model based on the same core code as OML.

Documentation status

The various parts of the model and the associated meteorological preprocessor have been described in many publications, the most detailed of which are reports by the Danish National Environmental Research Institute. A brief user's guide accompanies the model, and the model includes a comprehensive help text system.  Detailed descriptions of the model are given by Olesen et al. (2007a)Berkowicz et al. (1986) and Olesen et al. (1992). General descriptions of the model and the contexts in which it is used is given by Olesen (1995).

Validation and evaluation

Model validation against reference dataset

The model has been tested against experimental data sets from

  • Copenhagen, Denmark (1978/79)
  • Lillestrom, Norway (1987/88)
  • Cabouw, the Netherlands (1980)
  • Prairie Grass, USA (1957)
  • Kincaid, USA (1980/81)
  • Indianapolis, USA (1985)
  • Asnaes, Denmark (1986)
  • Ensted, Denmark (1988)

Results of the evaluations performed with three of these data sets have been reported in a European model evaluation exercise in 1994 which allowed several models to be compared on a similar basis, using the so-called "Model Validation Kit":

Olesen, H.R., 1995, The model validation exercise at Mol. Overview of results. Workshop on Operational Short-range Atmospheric Dispersion Models for Environmental Impact Assessment in Europe, Mol, Belgium, Nov. 1994, Int. J. Environment and Pollution, Vol. 5, Nos. 4-6, pp. 761-784.

Computer requirements

CPU time

The model can run on any Windows PC. As a guide to the computational resources required, the computer time used by OML-Multi for calculations with one source in a net of 400 receptor points and with one year of meteorology is on the order of one second with a modern PC.


The following versions exist:

  • OML-Multi: used for point sources that cannot be considered collocated, and for area sources. It has much increased capabilities compared to OML-Point.
  • OML-Point: Not distributed any more, as it is superseeded by OML-Multi. OML-Point was used for point sources that can be considered collocated, and was specifically intended for regulatory applications in Denmark.

The price of OML-Multi is Dkr 18900 excl. VAT (approximately 2550 Euro).  A demo version of OML-Multi (with limited lifetime) is available upon request.


  • Berkowicz, R., Olesen, H.R. and Torp, U. (1986): The Danish Gaussian air pollution model (OML): Description, test and sensitivity analysis in view of regulatory applications. In: Air Pollution Modeling and its Application V. C. De Wispelaere, F. A. Schiermeier, and N.V. Gillani (eds.). Plenum Press, New York.
  • Olesen, H.R., Løfstrøm, P., Berkowicz, R. and Jensen, A.B. (1992): An improved dispersion model for regulatory use - the OML model. In: Air Pollution Modeling and its Application IX, H. van Dop and G. Kallos (eds.). Plenum Press, New York.
  • Olesen, H.R., 1995, Regulatory Dispersion Modelling in Denmark. Workshop on Operational Short-range Atmospheric Dispersion Models for Environmental Impact Assessment in Europe, Mol, Belgium, Nov. 1994, Int. J. Environment and Pollution, Vol. 5, Nos. 4-6, 412-417.
  • Olesen, H.R., Berkowicz, R.B, Løfstrøm, P. (2007a): OML: Review of model formulation. National Environmental Research Institute, Denmark. 130pp. NERI Technical Report No. 609, www.dmu.dk/Pub/FR609.pdf .
  • Olesen, H.R., Berkowicz, R., Løfstrøm, P. (2007b): Evaulation of OML and AERMOD. 11th International conference on Harmonisation within Atmospheric Dispersion Modelling for Regulatory Purposes, Cambridge, July 2-5, 2007. 5-page extended abstract at http://www2.dmu.dk/atmosphericenvironment/Docs/Evaluation_OML_AERMOD.pdf
  • Olesen, H.R., Berkowicz, R., Ketzel, M., Løfstrøm, P. (2007c): Validation of OML, AERMOD/PRIME and MISKAM using the Thompson wind tunnel data set for simple stack-building configurations. 6th International Conference on Urban Air Quality, Cyprus, March 27-29, 2007. 4-page extended abstract at www2.dmu.dk/atmosphericenvironment/Docs/Using_Thompsons_data.pdf

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