Aarhus University Seal

Danish SPREAD model

In Denmark, the SPREAD model has been developed for high resolution (1 km x 1 km) spatial distribution of all sources and all pollutants included in the national emission inventories for air pollution and greenhouse gases (Plejdrup et al., 2016 & 2018). Spatial distribution is carried out on highly disaggregated emission source level, and resulting spatial emissions corresponds to the emissions in the national inventories. SPREAD is based on detailed national spatial data, e.g. the Danish Building and Dwelling Register, the Civil Registration Register, the national GIS-based road and traffic data base, and the Central Husbandry Register. Spatial data are analysed in a Geographical Information System (GIS) and through geoprocessing converted to spatial distribution keys to be included in the integrated database system.

The SPREAD model follows the requirements in the UNECE guidelines (UNECE, 2009) concerning spatial distribution of emissions as well as the technical guidance provided by the EMEP/EEA Guidebook (EEA, 2013). A separate module handles the conversion from the Danish orthogonal 1 km x 1 km grid to the present 50 km x 50 km EMEP grid, and a conversion to the new EMEP grid with a latitude-longitude resolution of 0.1 ° × 0.1 ° will be included from 2017 due to the new reporting requirements (UNECE, 2014). SPREAD covers the area defined by the Danish exclusive economic zone (EEZ), and the resulting gridded emissions are consistent with emissions in the national emission inventory.

The gridding in SPREAD is carried out on the most disaggregated level possible, both concerning activities (source, sub-sector or sectoral level) and spatial resolution. Emissions from point sources are allocated to the exact position, but for the major part aggregated to 1 km x 1 km resolution in the output files due to data confidentiality issues. Emissions that occur along a line, e.g. emissions from railways, are allocated to the course of the tracks. For some line sources the spatial distribution is further refined by including detailed activity data, e.g. for road transport where information on vehicle type, road type and annual average mileage per road segment is included in model. Area sources are groups of numerous small sources with common characteristics, e.g. residential combustion and industrial processes. It is not possible to allocate emissions from area sources to the position of each single source, but only to areas with similar properties, e.g. residential buildings and industrial areas.

Gridded emissions can be retrieved from SPREAD for single sources (e.g. residential wood combustion), sectors (agriculture), or as national totals for each pollutant. Improvements of the model can be carried out at the same disaggregated source level, enabling incorporation of new knowledge, or new or updated spatial data. Comparison of modelled and measured emissions and concentrations in ambient air is a valuable tool to identify sources that would benefit from improvements of the spatial distribution.

Emissions on a high spatial resolution from the SPREAD model are used as input to air quality models, e.g. the Danish Eulerian Hemispheric Model, DEHM (Christensen 1997; Brandt et al., 2012) and the Urban Background Model, UBM (Berkowicz, 2000a; Brandt et al., 2001a; b; c), which can feed into analysis of human exposure, and assessment of derived health effects and related costs.


Berkowicz, R., (2000a): A simple model for urban background pollution. Environmental Monitoring and Assessment 65 (1/2), 259–267.

Brandt, J., Christensen, J.H. Frohn, L.M. Palmgren, F. Berkowicz R. & Zlatev, Z., (2001a): Operational air pollution forecasts from European to local scale. Atmospheric Environment, Vol. 35, Sup. No. 1, pp. S91-S98.

Brandt, J., J. D. Silver, L. M. Frohn, C. Geels, A. Gross, A. B. Hansen, K. M. Hansen, G. B. Hedegaard, C. A. Skjøth, H. Villadsen, A. Zare, and J. H. Christensen, 2012: An integrated model study for Europe and North America using the Danish Eulerian Hemispheric Model with focus on intercontinental transport. Atmospheric Environment, Volume 53, June 2012, pp. 156-176, doi:10.1016/j.atmosenv.2012.01.011

Brandt, J., J. H. Christensen, L. M. Frohn and R. Berkowicz, (2001b): Operational air pollution forecast from regional scale to urban street scale. Part 1: system description, Physics and Chemistry of the Earth (B), Vol. 26, No. 10, pp. 781-786, 2001.

Brandt, J., J. H. Christensen, L. M. Frohn and R. Berkowicz, (2001c): Operational air pollution forecast from regional scale to urban street scale. Part 2: performance evaluation, Physics and Chemistry of the Earth (B), Vol. 26, No. 10, pp. 825-830, 2001.

Christensen, J., 1997: The Danish Eulerian Hemispheric Model - a Three Dimensional Air Pollution Model Used for the Arctic. Atmospheric Environment 31: 4169-4191.

EEA, 2013: EMEP/EEA air pollutant emission inventory guidebook — 2013 prepared by the UNECE/EMEP Task Force on Emissions Inventories and Projections.


Plejdrup, MS, Nielsen, O-K & Brandt, J 2016, 'Spatial emission modelling for residential wood combustion in Denmark' Atmospheric Environment, bind 144, s. 389-396. doi.org/10.1016/j.atmosenv.2016.09.013

Plejdrup, M.S., Nielsen, O.-K., Gyldenkærne, S. & Bruun, H. 2018: Spatial highresolution distribution of emissions to air – SPREAD 2.0. Aarhus University, DCE - Danish Centre for Environment and Energy, 186 pp. – NERI, Technical Report no. Scientific Report from 

DCE - Danish Centre for Environment and Energy, No 131, dce2.au.dk/pub/TR131.pdf


UNECE, 2009: Guidelines for Reporting Emission Data under the Convention on Long-range Transboundary Air Pollution. ECE/EB.AIR/97.

UNECE, 2014: Guidelines for Reporting Emissions and Projections Data under the Convention on Long-range Transboundary Air Pollution. ECE/EB.AIR/125.