Aarhus Universitets segl

No. 154: Mapping of air quality along motorways and highways in Denmark

Jensen, S.S., Im, U., Ketzel, M. Løfstrøm, P. & Brandt, J. 2015. Kortlægning af luftkvalitet langs motor- og landeveje i Danmark. Aarhus Universitet, DCE – Nationalt Center for Miljø og Energi, 41 s. - Videnskabelig rapport fra DCE - Nationalt Center for Miljø og Energi nr. 154. http://dce2.au.dk/pub/SR154.pdf

 

 Summary

Background and aim

The Danish Road Directorate mapped air quality along the motorways and other main roads throughout Denmark with the OML-Highway model during 2014-2015. It is the first time that a national data set of modelled air quality data has been established along the entire state road network. This report describes the results of the assessment, and the methodology and input data used.

The Danish Road Directorate has funded the development and application of OML-Highway, which is a GIS-based tool for calculating air quality along roads in open terrain.

Road authorities may use the nationwide air quality mapping results as a screening tool in connection with EIA studies of road projects and citizens may use the results as an information source on air quality. The Danish Road Directorate will publish the air quality maps at their home page during 2015.

The air quality maps show selected air pollutants related to health effects: Annual mean concentrations in 2012 of NO2 (nitrogen dioxide), and the mass of particulate matter of PM10 and PM2.5, respectively, the total mass of particles with a diameter less than 10 and 2.5 microns. The calculations are carried out for calculation points in different distances from the road out to a distance of 1000 m where the contribution from the road is less important.

The investigation

The OML-Highway model requires information about the road network with traffic data, background concentrations, meteorological data and calculation points.

The OML-Highway model has an existing tool for generating calculation points along the road network. This tool enables the user to define distances between calculation points perpendicular to the road, and to define the distance between calculation points along the road. In order to improve visualization of the results a supplemental tool has been developed. This tool can visualize the results as coherent buffer zones which the German company Lohmeyer has developed.

The road network is based on vejman.dk which includes all state roads in Denmark. The Danish Road directorate has developed vejman.dk. A new feature the GPS-based travel speed data from SpeedMap from the Danish Road Directorate (http://speedmap.dk/portal) has been used. SpeedMap data is associated to a ‘Navteq’ road network like the Landstrafikmodellen from DTU Transport (a national traffic model).This dataset has a different data model and segmentation than vejman.dk. Therefore, it has been necessary to develop a procedure to associate the travel speeds from SpeedMap to vejman.dk which the company Hermes Traffic Intelligence has developed.

In the calculations, the influence of noise barriers, dams and bridges are not taken into account, as it is difficult to link this data to the road network in such a way that it can be calculated with the OML-Highway, and also because the impact on air quality is limited.

Background concentrations are calculated with the regional air quality model Danish Eulerian Hemispheric Model (DEHM) and a local-scale model Urban Background Model (UBM) with associated emission and meteorological data. Emissions for Denmark are based on the emission model SPREAD which has emissions for Denmark for all sources broken down on 1 x 1 km2 grid cells. Models and data are developed by AU/DCE.

The calculations are carried out in the following way. The starting point is calculated background concentrations for the centre point of a 1 x 1 km2 grid from DEHM/UBM. This constitutes the background concentration for a given road segment of the road network. Emissions from the state roads have not been included in these background calculations to avoid double-counting of emissions from roads. Next, the OML-Highway model is used to calculate the contribution from the road to the calculation points along the road. The nearest located background concentrations are added to concentrations of the calculation points.

For non-reactive substances such as NOx, PM2.5 and PM10, the above calculation procedure can be carried out without adjustments. NOx includes NO and NO2. Since NO2 is part of photochemistry, there is not a linear relationship between NOx and NO2, and the NO2 contribution from the state roads are therefore calculated using a simplified chemistry model, which is based on annual mean of NOx, NO2 and ozone concentrations as well as information about the directly emitted NO2 emissions from traffic.

Main Conclusions

The geographical variation of NO2 in 2012 is as expected with the highest concentrations on the busiest motorways but the influence of background concentrations from the larger cities is also seen e.g. in the Copenhagen Area and in Aalborg.

The purpose of the mapping of air quality along the state road network is to describe the geographic variation, and can be considered a screening of air quality. The uncertainty can be considerable on single results due to uncertainty in input data and also due to the general uncertainly of the air quality models.

The aim is not to try to calculate the number of exceedances of the limit value along with state road network in Denmark for NO2. Model calculations should be seen as a complementary tool for preliminary assessment of ambient air quality and assessment of potential exceedances in locations where there are no measurements.

It is the Danish EPA which has the overall responsibility for compliance with the limit values for air quality in Denmark. The official announcement of exceedances of the limit values is done in the annual reporting from the Sub-program on air quality under the NOVANA program (Ellermann et al. 2015). The assessment of exceedances is based on measurements from the Danish monitoring stations, and partly on the basis of model calculations for selected urban streets in Copenhagen and Aalborg, which calculations are made, and where it is possible to get quality assured input data from the municipalities about traffic. The only limit value that is exceeded is the annual mean of NO2 which is exceeded on H.C. Andersens Boulevard in Copenhagen.

The limit value does not apply for the carriageway of roads, but where people are staying e.g. where people live and work.

There are no air quality monitor stations along motorways since traffic stations in the larger cities are prioritized. Furthermore, former air quality campaigns at the Køge Bugt Motorway and the Holbæk Motorway have only indicated possible exceedances of the NO2 limit value very close to the motorway.

The limit value is 40 µg/m3 for annual NO2 in 2010. An exceedance is considered if the value of 40.5 is exceeded. The location of indicative exceedances of the NO2 annual mean in 2012 has been identified. Exceedances of this value occur along parts of Køge Bugt Motorway, Holbæk Motorway and Motorway Ring 3. Almost all exceedances occur in the calculation points of 15 m from the centre line of the road and only a few cases at the Køge Bugt Motorway also at distances of 37.5 m from the centre line of the road. This is in areas where it is likely that no or very few people live and the limit value is therefore likely not exceeded. The highest calculated value is 54.7 µg/m3 and occurs at the Køge Bugt Motorway.

The geographical variation of PM2.5 in 2012 is very different from NO2 since background concentrations dominate, and the contribution from the state roads contribute less. There is a clear gradient from south to north in Denmark with higher concentrations in south and lower in north due to the contribution from emission sources in Central Europe.

The highest calculated value is 13.3 µg/m3. The limit value for PM2.5 is 25 µg/m3 in 2015, and it is not likely that this limit value is to be exceeded even if the calculated background concentration of PM2.5 is underestimated, as comparisons between measurements and calculations show.

The geographical variation of PM10 in 2012 is similar to the variation of PM2.5 except that PM10 is also significantly influenced by sea salt, which causes higher concentrations along west and south-oriented coast areas due to the dominant southwest wind direction.

The highest calculated value is 19.5 µg/m3. The limit value for PM10 is 40 µg/m3 in 2010, and it is not likely that this value will be exceeded even if the calculated background concentrations of PM10 are underestimated, as comparisons between measurements and calculations show.