1 Brief description (key words)
1 Policy issue
urban air quality
2 Application type
air quality assessment
regulatory purposes and compliance
3 Model output
4 Air pollution source
stack / multiple
array of line source
area / general
5 Release type
6 Spatial scale
7 Simulation character
8 Pollutants modelled
particulates / generic
9 Processes considered
10 Computer platform
2 Long description
1. Basic information
UDM-FMI (Urban Dispersion Modelling System – Finnish Meteorological Institute)
Model versions and status
Last update: November 1997
Finnish Meteorological Institute (FMI)
Contact person (providing all necessary technical support)
Finnish Meteorological Institute
Air Quality Research
Sahaajankatu 20 E
+358 9 1929 11
+358 9 1929 5403
Provided by contact person
2. Intended field of application
The dispersion part of UDM-FMI is an integrated Gaussian urban scale model. The model is commonly applied for regulatory purposes. The model requires information on emissions and meteorological parameters on an hourly basis. It computes time series of concentrations and related statistics at user-specified receptor points.
3. Model type and dimension
Multiple source Gaussian plume model, combined with a meteorological pre-processing model based on atmospheric boundary layer scaling.
4. Model description summary
The atmospheric dispersion module is an integrated urban scale model, taking into account of all source categories (point, line, area and volume sources). It includes a treatment of chemical transformation (for NO2), wet and and dry deposition (for SO2), plume rise (extended Briggs formulation), downwash phenomena and dispersion of inert particles.
The Gaussian dispersion parameters are functions of boundary layer variables, and their dependence on source height is also taken into account. The model includes the influence of a finite mixing height on the plume dispersion. The system computes statistical concentration parameters from the hourly time series, which can directly be compared to air quality guidelines and limit values.
5. Model limitations
The concentration distributions are assumed to be Gaussian in both the horizontal and vertical directions. The model does not allow for the influence on dispersion of individual buildings and obstacles, or inhomogeneous terrain. The treatment for particle dispersion takes into account only inert particles settling due to gravity.
Domain dimension: up to 50 *50 km, adjustable calculation grid.
Domain dimension: mixing height, grid size not explicitly limited.
Atmospheric boundary layer scaling theory.
Resistance model for gases and particles.
Chemical transformation of nitrogen oxides is modelled by using two semi-empirical regression models for the NO2/NOx ratio, one applied for mobile sources and another for stationary sources.
8. Solution technique
9. Input requirements
Required parameters include: the pollutant species, the hourly emission time-series, the effective source height and geometry (the height and width of the source building) and the geographical coordinates of the sources.
Meteorological measurements are processed by a pre-processor (MPP-FMI); the input includes three-hourly data from synoptic stations and twice-daily vertical profiles (of temperature, wind and humidity) from a radiosonde station.
Specified as terrain heights at receptor locations.
Other input requirements
Information on the canopy resistance.
10. Output quantities
The model output consists of hourly concentrations and deposition at each 3D-grid point.
11. User interface availability
The model has a unix-based user interface.
12. User community
Users of UDM-FMI should be scientists or engineers, with a sufficient background in atmospheric sciences.
13. Previous applications
The modelling system has been applied widely nationally in air quality assessments. It has also been applied world-wide in commissioned work, using meteorological data from the global observational network of the World Meteorological Organisation.
Examples of model applications have been discussed in the references. Karppinen et al. (1997a,b and 1998b) numerically evaluated the spatial distribution of concentrations and the statistical concentration parameters of NO2- and CO in the Helsinki metropolitan area. Valkonen et al. (1995 and 1996) evaluated the corresponding concentrations and parameters of CO-, NO2- and SO2 in the city of Espoo in southern Finland.
14. Documentation status
Level 3. The model is documented in publicly available reports and publication series (for instance, Karppinen et al, 1998a).
15. Validation and evaluation
Level 4. The model predictions have been compared with the Kincaid, Copenhagen and Lillestrom data (Olesen, 1995). The modelling system has also been tested extensively against results from urban measurement networks (Karppinen et al., 1997a,b and 1998b).
16. Frequently Asked Questions
17. Portability and computer requirements
The model has been written in Fortran 77. A parallel processor version of the program has been written for the Cray C-97 supercomputer. The program can also be executed (without the parallel processor routines) in any mainframe or workstation computer.
The computation time depends on the number of sources, the number of receptor points and the extent of the emission and meteorological time series. The computational times vary from seconds to a couple of tens of hours (for very extensive applications) CPU – time on Cray C-97.
The model is not currently in public domain.
Karppinen, A., Kukkonen, J., Konttinen, M., Härkönen, J., Valkonen, E. , Rantakrans, E., Koskentalo, T., and Elolähde, T., 1997a. The emissions, dispersion and chemical transformation of traffic-originated nitrogen oxides at the Helsinki metropolitan area. In: Joumard, R., Proceedings of the 4th international scientific symposium "Transport and Air Pollution" in Avignon, France, 9-13 June 1997. Avignon, pp.121-127.
Karppinen, A., Kukkonen, J., Konttinen, M., Rantakrans, E., Valkonen, E., Härkönen, J., Koskentalo, T. and Elolähde, T., 1997b. Comparison of dispersion model predictions and the results from an urban air quality measurement network. In: Power, H., Tirabassi, T., and Brebbia, C. A. (eds.). Air Pollution V. CMP, Southampton, pp. 405-411.
Karppinen, A., Kukkonen, J., Nordlund, G., Rantakrans, E., and Valkama, I., 1998a. A dispersion modelling system for urban air pollution. Finnish Meteorological Institute, Publications on Air Quality. Helsinki, 50 p
Karppinen, A., Kukkonen, J., Konttinen, M., Härkönen, J., Valkonen, E., Koskentalo, T., Elolähde, T., 1998b. Development and verification of a modelling system for predicting urban NO2 concentrations. In: Gryning, S.-E. and Chaumerliac, N. (eds.), Air pollution modelling and its application XXII, NATO, Challenges of Modern Society, Volume 22. New York and London, pp. 567-574.
Kukkonen, J., Härkönen, J., Valkonen, E., Karppinen, A. and Rantakrans, E., 1997. Regulatory dispersion modelling in Finland. International Journal of Environment and Pollution, Vol. 8., Nos. 3-6, p. 782-788.
Olesen, H.R., (1995), Datasets and protocol for model validation. International Journal of Environment and Pollution, Vol. 5, Nos. 4-5, pp. 693-701.
Valkonen, E., Härkönen, J., Kukkonen, J., Rantakrans, E., Jalkanen, L. and Haarala, S., 1995. Application of dispersion models for evaluating the influence of urban air pollution on human health. International Journal of Environment and Pollution, Vol. 5, Nos. 4-6, 557 - 566.
Valkonen, E., Härkönen, J., Kukkonen, J., Rantakrans, E., Jalkanen, L. and Haarala, S., 1996. Modelling urban air pollution in Espoo, Finland. The Science of the Total Environment 189/190, 205-211.