Jensen, S.S., Ketzel, M., Khan, J., Valencia, V.H., Brandt, J., Christensen, J.H., Frohn, L.M., Nielsen, O.-K. Plejdrup, M.S., Ellermann, T. (2021): Luften på din vej 2.0. DCE-Nationalt Center for Miljø og Energi, 62 s. - Videnskabelig rapport fra DCE – Nationalt Center for Miljø og Energi nr. 445, http://dce2.au.dk/pub/SR445.pdf
Air Quality at Your Street is a digital air quality map, which is accessible to everyone and which shows the air quality for all addresses in Denmark. The purpose of the air quality map is to illustrate the geographical variation of air quality in Denmark for selected health-related air pollutants. DCE-Danish Centre for Environment and Energy at Aarhus University has updated air quality data on Air Quality at Your Street to cover 2019 and has included new air pollutants. The new updated version is called Air Quality at Your Street 2.0. The concentration of a number of harmful substances is calculated with air quality models, and the air quality map can be viewed on the website http://luftenpaadinvej.au.dk. The interface is in Danish and English. The purpose of this report is to describe Air Quality at Your Street 2.0.
The first version of Air Quality at Your Street (now called 1.0) was launched in 2016 and included calculated annual mean concentrations for 2012 of NO2 (nitrogen dioxide), PM2.5 (particles below 2.5 micrometers) and PM10 (particles below 10 micrometers). As something new for 2019, BC (Black Carbon) and particle number concentration are also included in Air Quality at Your Street 2.0. Particle numbers are approximately the same as ultrafine particles.
Air Quality at Your Street may give an indication of potential exceedances of air quality limit values, but due to the greater uncertainty on modelling, official announcements are primarily based on measurements from measurement stations under the National Air Quality Monitoring Programme. Air Quality at Your Street 2.0 has become part of the monitoring programme as a complementary tool for assessment of air quality in Denmark. We term modelled exceedances as indicative exceedances.
DCE has provided air quality data on a professionally sound basis with a description of associated uncertainties. DCE is not liable for misinformation due to data errors, nor can DCE be held liable for loss or damage, either directly or indirectly, as a result of the use of air quality data. Data are purely indicative in nature. Data can only be used to give the user an overall assessment. It is therefore recommended that any user obtain further information before the user, for example, initiates actions based on expectations about air pollution.
Possible applications of Air Quality at Your Street are:
Air quality is calculated with air quality models. These models describe mathematically different physical and chemical processes. These are emission of air pollution from various sources, their dispersion, chemical transformation and deposition, the influence of buildings, etc., and meteorological conditions.
The air quality is calculated with a model system called DEHM/UBM/AirGIS that has been developed by Aarhus University over a number of years. The model system includes a regional transport model (DEHM), a high-resolution background model (UBM) and a street air quality model (OSPM) with associated meteorology and emission data, etc.:
Output from the model system is in theory particles with a size of approx. 10-1000 nm, which we here denote particle number concentrations. The unit "nm" is nanometer, and is one billionth of a meter. The unit of concentration of particle numbers is number per cm3. When measuring particle numbers, the measured number is very sensitive to the cut-off points, especially at the low end of the spectrum. Modelled particle number concentrations are therefore also compared to measurements of the number of particles with a lower cut-off point of approx. 10 nm.
The model calculations are compared to measurements from the National Air Quality Monitoring Programme to assess uncertainties on the model results for 2019. Further, limitations on the use of the calculation results are briefly discussed for different situations and sources.
Air quality in 2019 for background concentrations and street concentrations for NO2, PM2.5, PM10, BC (Black Carbon) and particle numbers is illustrated in maps and described statistically.
A detailed analysis of calculated indicative exceedances of the limit value for NO2 in 2019 (LPDV 2.0) has been carried out and developments since 2012 (LPDV 1.0) in number of exceedances have also been described.
Model calculations in the National Air quality Monitoring Program (NOVANA) as well as model calculations in Air Quality at Your Street (LPDV) are compared to measurements in the monitoring program. The model calculations in the monitoring programme for the street stations are based on traffic information obtained from the municipalities for the streets concerned, which are considered to have less uncertainty than data from the National Transport Model (LTM). As part of the monitoring programme, model calculations are made every year for about 100 streets in Copenhagen and 30 streets in Aalborg. For model calculations in LPDV, the nearest address point has been taken to represent the location of the street measurement stations, and traffic levels are from the National Transport Model (LTM).
Comparison between model results from the monitoring programme and measurements for NO2 concentrations for 2019 shows an overestimation of 17%-18% for three out of four street stations in the monitoring programme. For the fourth station, Odense, the overestimation is 67% and in previous years there has also been significantly overestimations for this station. The modelled NO2 concentrations are also overestimated at the background stations.
In LPDV, the same NO2 concentrations are modelled as in the monitoring programme for H.C. Andersens Boulevard and Jagtvej in Copenhagen, but also in Aarhus and in Odense the overestimation is only 27%.
In the case of the street station in Aarhus, the model results in LPDV are at the same level as the measurements, but input data for the model is partially incorrect, but compensates each other. A little more traffic, slightly lower travel speed and higher background levels give all other things equal, higher modelled concentrations, while lower bus share results in lower concentrations. The combination of this means that the modelled level ends at 23 μg/m3, just like the measurements.
The reason why the overestimation in LPDV for the street station in Odense is less than in the monitoring program is also a combination of differences in input data.
Thus, the modelling system tends to overestimates somewhat for NO2 in relation to the measurements.
For PM2.5, the model results for LPDV range between -8% and 8% when compared to street stations, and model results range between -10% and 5% compared to background stations. For PM10, model results are slightly underestimated with -13% to 0% for street stations and for the background stations, model results range from -10% to 0% of measurements.
The model system estimates the level of measurements for both street concentrations and background concentrations quite satisfactorily for PM2.5 and PM10.
BC modelling is not performed in the monitoring program and BC is not measured directly in the monitoring programme, but EC (Elemental Carbon) is measured, which can be used as an indicator of BC. The model calculations in Air Quality at Your Street are only 7% above the EC measurements for H.C. Andersens Boulevard in Copenhagen, while the model results differ from measured concentrations from -6% to 38% for the background stations. A previous more detailed analysis of the correlation between BC of background concentration calculations and measured EC from 2010 to 2019 shows that DEHM/UBM is able to reproduce trends over time with decreasing concentrations as well as seasonal variation within a year.
Despite good correlation between calculations and measurements, there is still considerable uncertainty in the model results, as there is uncertainty in the emission inventory and uncertainty about the degree of how good EC measured represents BC.
The most recent available measurements of particle numbers above 10 nm, with which the model results are comparable, are from 2016. The modelling system underestimates by approx. 20% for H.C. Andersens Boulevard in Copenhagen, and overestimates a lot for the background stations, between 135% and 211%. This means that the modelled street contribution is much less than what the measurements suggest. The street contribution is the difference between the street concentration at H.C. Andersens Boulevard and the background concentration at the H.C. Ørsted Institute. The modelled background concentrations are thus overestimated, which affects all addresses in Denmark, and the difference between background and busy streets is too small. The uncertainty on the modelling particle numbers in LPDV is therefore large.
There are a number of sources in the modelling system that are not described in detail. These are air pollution from motorway traffic, rail traffic, wood-burning stoves and small industrial sources. The modelling system calculates too low concentrations at homes close to motorways within about 200 m. The same applies to dwellings along the rail network with diesel-powered trains, where emissions are, however, much lower than from motorways. The contribution from wood-burning stoves is also included in an average way, as the contribution is calculated on the basis of the emissions from wood-burning stoves within one square kilometre. This means that the contribution of wood-burning stoves is more smoothed out than can be expected in reality, since the contribution of each source is not modelled separately. The same applies to small industrial sources.
The report presents maps of the geographical variation of background concentrations and street concentrations for the five air pollutants for 2019. In addition, the statistical variation is described for the five air pollutions. This is done as histograms, where the number of addresses located in different concentration intervals is shown. The geographical variation is different for the different pollutants and depends on the importance of regional background pollution and the sources in Denmark and their significance and their geographical variation.
In addition to a regional contribution, local sources have a clear impact on the geographical distribution of background concentrations of NO2 over land and sea areas. The contribution of road traffic is clearly seen as increased concentrations in major cities and along major transport corridors. The shipping routes with international shipping traffic through the Great Belt and the Kattegat also show high concentrations. The latter also give rise to increased concentrations in neighbouring coastal areas. The effect of emissions from the ferry line between Aarhus and Odden is also evident (the ferry line of Molslinjen).
The contribution of road traffic to geographical variation is evident with increased street concentrations in major cities and along major transport corridors.
The geographical distribution of background concentrations of PM2.5 has a different pattern than NO2, as there is a clear gradient from south to north with higher PM2.5 concentrations in southern Denmark than in northern Denmark. This is because PM2.5 concentrations are dominated by regional background pollution from Western and Central Europe.
The gradient from south to north is also found in the street concentrations of PM2.5, but contributions from busy streets are also seen.
The geographical distribution of background concentrations of PM10 is clearly influenced by contributions of sea salt from sea spray. This is seen as high PM10 concentrations on the west coast of Jutland and to a lesser extent on the western coasts of the islands in the inland waters. This is due to the dominant westerly wind. There are also generally high concentrations in the sea areas but decreasing from the North Sea to the Baltic Sea. The same gradient from south to north as for PM2.5 is partly visible to PM10, as PM2.5 is part of PM10.
The geographical variation of street concentrations of PM10 is characterized by the variation in background concentrations, but contributions from road traffic also show up as elevated concentrations, especially in the larger cities.
In addition to a regional contribution, the geographical distribution of background concentrations of BC is dominated by combustion sources from road traffic, wood-burning stoves, and power plants, but also to some extent from shipping traffic. Elevated concentrations occur in and around major cities.
Detailed analysis shows that the highest BC concentrations occur locally around power plants or large industrial companies such as Aalborg Portland. It will require more detailed calculations, e.g. with the OML model, to evaluate whether UBM correctly calculates the contribution from these sources.
Background concentrations have a clear influence on the geographical variation of street concentrations, but in addition there are also increased BC concentrations on busy roads, and wood-burning stoves can play a significant role locally for elevated BC concentrations.
The geographical variation of the background concentration of particle numbers largely follows the geographical variation of NO2 and, to some extent, BC. Important sources are shipping traffic, wood-burning stoves, road traffic, and power plants.
The geographical variation of background concentrations means a lot to the variation in street concentrations, but it is also clear that there are elevated concentrations along busy roads.
There is considerable uncertainty at both the level and the geographical distribution, as the modelling system overestimates the background contribution and underestimates the street contribution in relation to the measurements. There is therefore less geographical variation in the modelled particle number concentrations than the measurements show.
Calculated concentrations are compared to limit values and WHO guidelines for air quality.
EU limit values are applicable legislation in Denmark through implementation in Danish regulations. The Ministry of the Environment/Danish Environmental Protection Agency is responsible for compliance with the limit values. The limit value for NO2 is 40 μg/m3, 25 μg/m3 for PM2.5, and 40 μg/m3 for PM10. Because the limit value is defined as an integer, there will be an exceedance if, for example, the value 40.5 μg/m3 is exceeded for NO2.
The World Health Organisation (WHO) has stated air quality guidelines. These guidelines are not legally binding. WHO guidelines are around 40% of the EU limit values for PM2.5 (10 μg/m3) and half for PM10 (20 μg/m3), while they are the same for NO2 (40 μg/m3). Since there may be large uncertainty on the calculated air concentrations and model calculations only are an additional tool for assessing air quality, we call the calculated exceedances indicative.
There are not limit values for BC and particle number.
Calculated levels are significantly below the limit value for annual mean of PM2.5 of 25 μg/m3. WHO's guidelines for PM2.5 are 10 μg/m3, and are exceeded at many addresses.
Calculated levels are significantly below the limit value of 40 μg/m3 as annual means of PM10. WHO's guidelines for PM10 are 20 μg/m3, and are exceeded at a number of addresses.
The limit value for NO2 as annual mean is 40 μg/m3. The WHO air quality guidelines are also 40 μg/m3. In 2019, there are a total of 27 addresses that exceed the value 40.5 μg/m3, thus they are indicative exceedances of the limit value. Of the 27 indicative exceedances of the limit value for NO2, there are 24 in Copenhagen and 3 in Aarhus. Detailed analysis shows that in the vast majority of cases, the traffic level in the National Transport Model and the calculated street geometry are considered representative of the actual conditions. However, as the modelling system overestimates NO2, it is likely that there are no real exceedances of the limit value on the street segments, but elevated concentrations.
1,123 indicative exceedances of the NO2 limit value were calculated for 2012 in Air Quality at Your Street 1.0. There were exceedances in Copenhagen and the surrounding area, Aarhus and Aalborg in 2012. In 2019, 24 indicative exceedances have been calculated in Copenhagen and 3 indicative exceedances in Aarhus. Thus, the number of indicative exceedances has decreased dramatically from 2012 to 2019. In addition, the calculated maximum concentration has also decreased from 64.6 μg/m3 to 47.6 μg/m3. The decrease in the modelled concentrations and thus also in the number of calculated indicative exceedances is consistent with the general decrease in measured NO2 concentrations at the monitoring stations of the air quality monitoring programme in Denmark.