Future Air Quality in Danish cities

Contents

Preface

English summary

Sammendrag

1. Introduction

2. Methodology

3. Vehicle Emission Factors
3.1 Background Data for Vehicle Emissions
3.2 Calculated Emission Factors for the Scenario Years

4. Regional Air Quality Levels
4.1 Scenario Emission data
4.2 Validation of DEM-Predictions for 1995
4.3 Future Regional Air Quality

5. Urban Background Levels
5.1 Urban Vehicle Emission Inventory
5.2 Validation of UBM Predictions for 1995
5.3 Future Urban Background Air Quality

6. Air Quality at Street Level
6.1 Validation of OSPM Predictions
6.2 Possible Underestimation of COPERT III emissions
6.3 Future Air Quality at Street Level
6.4 Comparison With Air Quality Guidelines
6.5 Future Air Quality in 103 Copenhagen Streets
6.6 Preliminary Assessment of Particulate Air Pollution at Street Level

7. Comparison with EU Predictions
7.1 Comparison with EU Emission Predictions
7.2 Comparison with EU Air Quality Predictions

List of References

Appendix 1: Emission Data for DEM Model
Appendix 2: Distribution of Vehicle Stock and Annual Mileage
Appendix 3: Hot and Cold Emission Factors, and Beta-factors

Preface

Background

The EU Commission has in co-operation with the European Auto- and Oil industry carried out the Auto-Oil Programme. The aim of the programme was to identify cost effective methods to comply to future EU air quality standards in cities in 2010. Based on the study, EU directives have been proposed and partly approved to regulate vehicle emissions and fuel qualities.

Objectives

The aim of the present project is to evaluate the impact on the future air quality in selected Danish cities of the new EU directives and proposals on vehicle emissions and fuel qualities. Furthermore, the objective is to compare the estimated future air quality with air quality limit values for protection of human health approved or proposed by EU as well as air quality guidelines by WHO and the Danish EPA.

Steering Committee

The project has been carried out by: Steen Solvang Jensen, Ruwim Berkowicz, Morten Winther, Finn Palmgren and Zahari Zlatev from the National Environmental Research Institute. The report has been writing by Steen Solvang Jensen with contributions from Morten Winther (vehicle emissions, Chapter 3) and Finn Palmgren (assessment of particulate air pollution, Section 6.6).

A Steering committee has conducted the project: Chairman: Erik Iversen, the Danish EPA and members: Poul Bo Larsen, the Danish EPA, Gitte Ploug Lorenzen, the EPA of Municipality of Copenhagen, Ole Hertel, National Environmental Research Institute, Jesper Schramm, the Technical University of Denmark.

Funding

The project is primarily financed by the Danish EPA with co-funding by the National Environmental Research Institute.

Project Period

The present project started in the late autumn of 1998 and terminated January 2000.

Electronic Version of Report

An electronic version of this report is posted on the web site of the Danish EPA at www.mst.dk.

Information About Air Pollution

Additional information about air pollution in Denmark can be obtained at the web site of the National Environmental Research Institute under the Department of Atmospheric Environment at http://www.dmu.dk/atmosphericenvironment

English Summary

Future Air Quality in Danish cities

Background and Objectives

Background

The EU Commission has in co-operation with the European Auto- and Oil industry carried out the Auto-Oil Programme. The aim of the programme was to identify cost effective measures to comply to future EU air quality standards in cities in 2010 according to the new EU directive "Council directive 1999/30/EC of 22 April 1999 relating to limit values for sulphur dioxide, nitrogen dioxide and oxides of nitrogen, particulate matter and lead in ambient air". Based on the study, EU directives have been proposed and partly approved to regulate vehicle emissions and fuel qualities.

Objectives

The aim of the present project is to evaluate the impact on the future air quality in selected Danish cities of the new EU directives and proposals on vehicle emissions and fuel qualities. Furthermore, the objective is to compare the estimated future air quality with air quality limit values for protection of human health approved or proposed by EU as well as air quality guidelines by WHO and the Danish EPA.

Overall Approach, Applied Models and Main Assumptions

Overall Methodology

The assessment is carried out for the reference year 1995 and the scenario years: 2000, 2005, 2010, 2015 and 2020. Modelled substances include health related substances: NO₂ (NO_x), O_3, CO and benzene. Predictions for particles are based on expert judgement. Future air quality levels are predicted in a selected street named Jagtvej in the central part of Copenhagen that represent a near worst case. Jagtvej has an average daily traffic of about 24.000 vehicles, the street width is 25 meters with 3-5 storeyed buildings. Traffic loads and vehicle composition are assumed to be constant 1995-2020 in the street of Jagtvej which is in accordance with assessments of traffic development by local authorities. Air quality levels in the street is modelled by nested modelling taking into account emissions in the street, urban background levels and regional background levels. Interactions between the street air, the urban background air and the regional background air together with chemical transformations are modelled.

Additionally, calculations are carried out with less detailed input data for 103 other streets in the Copenhagen area with a wide range of traffic loads and street configurations to be able to generalise and relate the results to general traffic conditions in urban areas.

Danish Eulerian Model (DEM)

Regional background levels are predicted by the Danish Eulerian Model (DEM), a large-scale transport model based on 50 x 50 km² emission grids for all Europe and meteorology on a 150 x 150 km² grid. Development in European emissions is based on proposals for the new ECE protocols on regulation of trans-boundary air pollution to be met in 2010. Development in European emissions is determined by development in emission factors for each activity and development in the activities (industry, energy, transport etc.). National emission ceilings include all these sources. Expected increases in e.g. transport are therefore included.

Danish Urban Background Model (UBM) and Urban Emission Model (UBE)

The urban background levels are modelled by the Danish Urban Background Model (UBM) based on a 2 x 2 km² emission grid for the Greater Copenhagen urban area covering 151 km². Grid emissions are determined by a Urban Emission Model (UEM) that takes into account the traffic levels on the road network. Other sources are not considered as traffic is the dominating source in larger urban areas. Validation studies of the UBM model show a good agreement between modelled and measured levels when just considering traffic as source indicating that other sources play a minor role. Traffic is expected to increase by 17% on main roads in the urban road network during 1995-2010 corresponding to a general traffic increase of 10% in the road network. Development in traffic emission factors is based on the EU COPERT III emission model, proposed emission reductions and prediction of the development of the age profile of the Danish car fleet.

Danish Operational Street Pollution Model (OSPM)

Air pollution levels in the street of Jagtvej in Copenhagen are modelled by the Danish Operational Street Pollution Model (OSPM) as a contribution from the direct traffic emission in the street and a contribution from the modelled urban background. Vehicle emission factors are also based on COPERT III.

Predicted Future Air Quality

Vehicle Emission Reduction

Vehicle emission reductions during 1995-2010 are determined to about 70%, 75% and 85% for NO_x, CO and benzene, respectively. The impact on future air quality levels has been modelled and compared with limit values.

Importance of Regional and Urban Background Concentrations

The relation between air quality levels in the street of Jagtvej in Copenhagen has been related to concentration levels in the urban background of Copenhagen and the regional background outside Copenhagen, see Table 1. In 1995, urban background and regional background NO₂ levels are about 50% and 25% of the levels in the street, respectively. For CO and benzene, it is about 25% and 10%, respectively. Urban and regional NO₂ levels are relatively high compared to the street levels because NO₂ is mainly a secondary pollutant formed in reactions between NO and ozone. For ozone, concentration levels in the regional background, the urban background and at street level will narrow down from 1995 to 2010. For non-reactive species like CO and benzene, urban and regional levels are relatively low compared to the street levels.

Direct Vehicle Emissions -Decrease in Importance in Determining Street Levels

Table 1
The Relation Between Air Quality at Street Level and in the Urban and Regional Background (Index)

It is also seen that the regional and urban background will play a relatively larger role in determining street levels in 2010 compared to 1995, most profound for CO and benzene, and less for NO₂. In other words, the direct vehicle emission in the street will decrease in importance in determining air quality levels, although still dominating.

Predicted Future Trends in Air Quality

In Table 2, the predicted regional background, urban background and street air quality levels are shown for the different scenario years.

Table 2
Development in Regional, Urban Background and Street Air Quality Levels (Index and Annual Means)

NO Becomes Limiting Factor in Forming NO₂

Catalyst cars were introduced in Denmark in 1990/91 and reduce NO_x emissions (NO and NO₂). NO₂ observed levels in Jagtvej were more or less constant during 1990-95 indicating that ozone was the limiting factor in forming NO₂ in reactions between NO and ozone. From 1995 to 1998, measurements show a downward trend in NO₂ levels, and this trend is also reproduced by the OSPM model.

During 1995-2010/2020, 98- and 99.8-percentiles of NO₂ are predicted to decrease about 50% and 35%, respectively. The predictions show that NO becomes the limiting factor in forming NO₂ in reactions with ozone in the future due to the steadily decreasing NO_x emissions (NO and NO₂). NO constitutes about 95% of NO_x vehicle emissions.

Ozone

Annual regional ozone levels are only predicted to decrease about 2% in Denmark during 1995-2010 despite European reductions of ozone precursors like NO_x and VOCs of about 40%. However, high ozone levels during spring and summer decreases more. At Danish meteorological conditions, the regional background ozone is dominated by long-range transport as the net production of ozone is small in Denmark. Ozone levels are modelled to increase about 14% during 1995-2010 in the urban background since less NO is available for ozone depletion due to NO_x vehicle emission reductions.

CO and Benzene

CO levels are predicted to decrease by a factor of 4 and benzene levels by a factor of 10 from 1995 to 2010. The predicted downward trends of CO and benzene are also supported by observed levels during 1995-1998.

Comparison with Air Quality Guidelines

Air Quality Guidelines

Modelled street levels in Jagtvej, Copenhagen were compared with EU air quality limit values, WHO guidelines and Danish EPA criteria. The Danish EPA air quality criteria were set up to minimize adverse health effects. The air quality criteria are not administrative limit values but should be regarded as desired long-term objectives (Larsen et al. 1997).

New EU limit values have to be met in 2010. A margin of tolerance has been defined to secure that limit values will be met in 2010. The margin of tolerance given as a percentage in the table refers to the year the directive entries into force. The margin of tolerance is equally stepped down each year to reach 0% in 2010. Member states have to take local action if the margin of tolerance is exceeded.

Ozone

At street levels, the proposed EU limit value for short-term exposure was not exceeded in 1995 nor will it be exceeded in 2010 despite an increase in ozone levels in the street due to a decrease in NO vehicle emissions leaving less NO for depletion of ozone in forming NO₂. However, the sum of NO₂ and O₃ decreases. The urban background is a better indicator for ozone exposure of the population than levels in the streets since ozone levels are influenced by NO emissions. The proposed EU limit value for short-term exposure was not exceeded in the urban background.

NO₂

The EU limit value for NO₂ for long-term exposure was exceeded in 1995 and the limit value for short-term exposure is tangent. However, the margin of tolerance of 50% in 1999 is not exceeded.

The predicted NO₂ levels in 2010 at Jagtvej are about half of the EU limit value in 2010. The Danish EPA criteria for short-term and long-term exposure is exceeded for all scenario years until 2015-2020.

CO

The EU limit value for CO will be between the 98- and 99.8-percentile. The EU limit value for CO was not exceeded in 1995, and the margin of tolerance of 50% will not be exceeded in the expected year of entry into force of the directive (2000). In 2010 the predicted CO levels will be 10-20% of the EU limit value for 2010. The EU limit value and WHO guidelines are identically for CO. The Danish EPA has not suggested criteria for CO.

Benzene

The EU limit value for benzene was exceeded in 1995. The margin of tolerance of 100% will not be exceeded based on modelled levels in 2000, the expected year of entry into force of the proposed directive. The predicted levels in 2010 will be about half of the EU limit value. WHO guidelines and Danish EPA criteria are exceeded for all scenario years.

103 Streets in Copenhagen

Crude calculations of annual levels of NO₂ and benzene for 103 streets in Copenhagen showed that levels were below EU limit values for all streets.

The health impacts of NO₂, benzene and CO are likely to decrease in the future due to improved air quality for these pollutants.

Particulate Matter

Preliminary assessment

A separate assessment was carried out for particulate matter since Danish air quality models for particles are not yet available but under development.

A preliminary assessment of the particle levels of TSP (Total Suspended Particulate Matter) and PM₁₀ (particles less than 10 m m) in selected streets in Denmark was carried out and levels were related to the new EU limit values for PM₁₀. Measurements of ultrafine particles from vehicles in two Danish streets (particles less than 0.2 m m) were also presented.

TSP/PM₁₀

Measurements show that TSP is approx. 35% higher than PM₁₀, that is, PM₁₀ constitutes on average about 74% of TSP. This relation was used to give an indicative estimation of PM₁₀ levels at selected streets in Denmark where TSP is measured. Estimated PM₁₀ levels in 1998-99 were below the new limit value for 2005 but exceed the limit value for 2010.

Possible Future Development

Denmark has a national objective to reduce particle vehicle emission by 50% in urban areas 1988-2010, and further reductions after 2010. The increase in penetration of catalyst converters reduce particle emissions for petrol powered vehicles due to unleaded petrol. Catalysts become mandatory in 1990. New stringent particulate emission standards for especially diesel powered vehicles will reduce particle emissions. The conversion to diesel with a low content of sulphur will also reduce particulate emissions.

Previous assessments indicate that the total particulate emissions (as mass) from vehicle within the EU will decrease by about 70% 1995-2010 including expected increases in traffic. Based on a few number of European studies, WHO has estimated that the particulate emission from vehicles in urban areas contributes about 40-60% of PM₁₀.

Due to the above mentioned regulation of vehicle particulate emissions it is likely that the PM₁₀ will decrease in the future but it is difficult to estimate how much based on existing knowledge and to estimate if the limit value for 2010 will be met. The above figures indicate that it might be a problem.

Uncertainties and Future Research Needs

COPERT III underestimates emissions

Validation of the Urban Background Model and the OSPM model by comparing modelled and measured concentration levels showed that the models underestimate observed concentrations when using the EU COPERT III emission factors indicating that COPERT III underestimates real world emissions on the road assuming that the air quality models are correct.

A test was carried out that compared the ratio between modelled and measured CO and NO_x in the street of Jagtvej using COPERT III emission factors for CO and NO_x. If the ratio between CO and NO_x emissions is correct then the same ratio will be found in the observed concentrations of CO and NO_x. It was seen that the slope of modelled air quality levels using COPERT III emission factors was very different from the measured ratio between CO and NO_x in the street air. This indicates that the ratio between COPERT III emission factors for CO and NO_x is questionable since it does not comply with the ratio found in the measured street air.

Nevertheless, COPERT III emission factors were applied throughout the study although predicted air quality levels to begin with become underestimated. To compensate, the following approach was applied. For prediction of future concentrations in the urban background or in the street, observed levels have been applied from 1995 as a baseline for calibration, and the modelled trend as an index has been used to estimate future levels to give realistic predicted air quality levels that can be compared to air quality limit values. For reactive species like NO₂ this approach may underestimate future NO₂ levels in the street because of the non-linear relation between NO_x emissions and NO₂ due to interaction with ozone.

A study should be carried out that examines how well COPERT III emission factors correspond to on the road emissions by linking emissions to air quality levels in streets using models and measurements.

Particulate Matter

Particle emissions by mass and probably also by numbers are expected to decrease in the future promising less health impacts due to particulate matter. However, the knowledge about the air pollution with particulate matter is still rather limited. By the new PM₁₀/PM_2.5 methods and measurements of ultrafine particles from traffic, possibilities have opened to obtain valuable data. Systematic measurements, including long time-series, by these methods at representative sites will improve the possibilities for health studies substantially. However, more knowledge is needed about the chemical/physical properties of the particle, e.g. chemical composition, surface properties and morphology. The characterisation of the particles is also important for quantification of the contribution from different sources and parameterisation of the properties of the particles to be included in air quality models. This is necessary for decisions on abatement measures to be taken to reduce the health impacts of particulate air pollution and to evaluate the effects of the measures taken.

Traffic loads

Traffic loads at Jagtvej in Copenhagen was assumed to be constant during the scenario years and traffic loads on the road network in the Copenhagen area was assumed to increase by 17% on main roads during 1995-2010 corresponding to a general traffic increase of 10% in the road network. If these assumptions are too optimistic, air quality levels will be higher than predicted. However, somewhat higher traffic loads will not compromise the downward trend in concentrations due to the profound emission reductions.

Scenarios 2015-2020

Predictions for 2015 and 2020 are indicative. They reflect the penetration of cars that comply to EURO IV for passenger cars and vans (2006-7) and EURO V for lorries and buses (2010). Obviously, these scenarios do not take into account possible future new EU national emission ceilings or vehicle emission regulation.

Other Sources than Traffic

The regional and urban background concentrations gain in importance in relation to the direct vehicle emissions in urban streets in the future. However, traffic will still be the domination source in urban areas but more attention will have to be put on other sources in urban areas to predict concentration levels. In the present study, prediction of the regional background include all source but the Urban Background Model only includes traffic as source. However, it is likely that inclusion of other sources would not have changed predicted urban background levels significantly.

DEM Model

Prediction of CO in the DEM model could be improved by applying better emission data what is available. A feature for predicting benzene levels could be develop.

CO Monitoring

CO is a good indicator for petrol powered vehicles and can be used to estimate other pollutants like benzene. More CO monitoring in regional background is required to get a more complete picture of regional background concentrations, and to get reliable data for validation of the UBM model.

Summary in Danish

Den fremtidige luftkvalitet i byerne bliver bedre

EU har vedtaget et rammedirektiv for vurdering og styring af luftkvaliteten som med datterdirektiver fastsætter skærpede grænseværdier for 12 stoffer. Vi har tidligere haft grænseværdier for 5 af stofferne. I forbindelse med udarbejdelse af luftkvalitetsdirektiverne er der sideløbende iværksat det såkaldte Auto-Oil program, som undersøgte, hvordan luftkvalitetsmålene kunne opfyldes gennem regulering af bilernes emission og af brænstofskvaliteten. Dette arbejde er mundet ud i en række nye direktiver, som skærper kravene til nye køretøjers emission af skadelige stoffer og til brændstofskvaliteten fx svovlindholdet.

Formålet med projektet har derfor været at undersøge den fremtidige luftkvalitet i danske byer som følge af de strengere emissions- og brændstofskrav, og vurdere om de nye skærpede EU grænseværdier for luftkvalitet i 2010 kan forventes at blive overholdt.

Undersøgelsen

Den fremtidige luftkvalitet er beregnet i Jagtvej i København, som repræsenterer en gade med forholdsvis høje koncentrationer. Den er ret trafikeret med omkring 24.000 biler i døgnet, og gaden er ca. 25 meter bred og er omgivet af 2-5 etagers bygninger. Time for time beregninger for NO_x (NO+NO₂), NO₂, ozon, CO og benzen er gennemført for referenceåret 1995 og scenarieårene: 2000, 2005, 2010, 2015 og 2020. Udviklingen i partikler er baseret på ekspertvurderinger. Ozon udsendes ikke direkte men dannes i atmosfæren ud fra NO_x og kulbrinter under indvirkning af sollys. Ozon i Danmark skyldes overvejende langtransport, idet det primært dannes i syd- og centraleuropa.

Den fremtidige luftkvalitet i gaden er beregnet ved at kombinere en række luftkvalitetsmodeller. En model beregner den regionale luftkvalitet uden for København, som er bestemt af emissionsudviklingen i hele Europa. Emissionudviklingen reguleres gennem en række internationale konventioner, hvor Danmark har forpligtiget sig til at opfylde en række mål for reduktion af de nationale emissioner. En anden model beregner bybaggrundsforureningen over København ud fra den regionale forurening og trafikkens emission i Københavnområdet. Trafikken emission er bestemt med en byemissionsmodel. Det er forudsat at trafikken stiger med 10% fra 1995 til 2010 i København med 17% på de store veje, hvilket er i overensstemmelse med Københavns Kommunes egne vurderinger. Luftkvaliteten på Jagtvej er bestemt med en gadeluftkvalitetsmodel, som tager hensyn til trafikken i gaden, gadens udformning, bybaggrundsforureningen og meteologien. Det er forudsat at trafikken på Jagtvej er den samme i alle scenarieårene.

Hovedkonklusioner

Undersøgelsen viser, at den beregnede luftkvalitet på Jagtvej i København forbedres for NO₂, CO og benzen fra 1995 til 2010 og videre frem trods stigende trafik, således at EU’s nye grænseværdier ikke overskrides i 2010. Ozonniveauerne i gaden vil stige, idet der er mindre NO emission i gaden til at omdanne ozon til NO₂. Summen af NO₂ og ozon vil dog falde. EU’s forventede nye grænseværdi for ozon i 2010 vil dog ikke overskrides. Det samme gælder for 103 andre gader med forskellige trafikmængder i København, hvor beregningerne er gennemført med mindre detaljeret input data.

De beregnede niveauer er også sammenlignet med WHO’s guidelines, og luftkvalitetskriterier foreslået af Miljøstyrelsen. Luftkvalitetskriterierne repræsenterer en minimering af mulige sundhedsskader med et meget højt sikkerhedsniveau. Kriterierne gælder ikke administrativ, men kan opfattes som ønskede langsigtede mål. (Larsen et al. 1997).

EU’s forslåede grænseværdi for ozon vil ikke blive overskredet hverken i gadeniveau eller i bybaggrunden. For ozon er bybaggrunden en bedre indikator for befolkningens eksponering, idet ozonniveauerne i gadeniveau er stærkt påvirket af NO emissionen i gaden. WHO’s strengere vejledende værdi og Miljøstyrelsens meget lave luftkvalitetskriterie vil være overskredet for ozon.

EU’s og WHO’s grænseværdier for NO₂ er ens, og er ikke overskredet i 2010, men Miljøstyrelsens luftkvalitetskriterie er overskredet frem til 2015-2020. De fremtidige NO₂ niveauer bliver begrænset af tilstedeværelsen af NO fra trafikken, hvor den tidligere har været begrænset af tilstedeværelsen af ozon.

EU og WHO har samme grænseværdi for CO, som ikke overskrides i referenceåret eller i scenarieårene. Miljøstyrelsen har ikke opstillet luftkvalitetskriterie for CO.

EU’s foreslåede grænseværdi for benzen vil ikke være overskredet i 2010, men den strengere WHO grænseværdi og Miljøstyrelsens luftkvalitetskriterie er overskredet.

Den fremtidige grænseværdi for PM₁₀ i 2005 overskrides ikke i 1998-99, men det kan ikke udelukkes at den skærpede grænseværdi i 2010 vil overskrides. PM₁₀ er partikler under 10 mikrometer dvs. 10 tusindedele af en millimeter. Der er således brug for yderligere forskning i kilderne til partikler, bedre beskrivelse vha. målinger samt modeludvikling for at kunne bestemme fremtidige niveauer og for bedre at kunne vurdere effekten af forskellige tiltag.

Projektresultater

De beregnede årsmiddelkoncentrationer i den regionale baggrund, i bybaggrunden og i gadeniveau på Jagtvej i København er vist i tabellen, og sammenlignet med EU og WHO grænseværdier samt Miljøstyrelsens luftkvalitetskriterier.

Andet væsentligt

Undersøgensen viste også, at det er sandsynligt at de emissionsfaktorer (g/km) som ligger til grund for nationale emissionsopgørelser i EU herunder i Danmark underestimerer NO_x og CO. Luftkvalitetsberegninger med disse emissionsfaktorer viste en underestimering i forhold til målinger af koncentrationer af NO_x og CO i luften. Derfor er der i beregningerne af den fremtidige luftkvalitet kompenseret herfor. Disse forhold bør undersøges nærmere.

Andre kilder

Larsen, P.B., Larsen, J.C., Fenger, J., Jensen, S.S. (1997): Sundhedsmæssig vurdering af luftforurening fra vejtrafik, Miljøprojekt nr. 352, Miljøstyrelsen. 287 s.

Udvikling i regional baggrundsforurening, bybaggrundsforurening og luftkvaliteten i gadeniveau for Jagtvej i København (Indeks og årsniveauer)

1. Introduction

Background and Objectives

The EU Commission has in co-operation with the European Auto- and Oil industry carried out the Auto-Oil Programme. The aim of the programme was to identify cost effective measures to comply to future EU air quality standards in cities in 2010 according to the new EU directive "Council directive 1999/30/EC of 22 April 1999 relating to limit values for sulphur dioxide, nitrogen dioxide and oxides of nitrogen, particulate matter and lead in ambient air". Based on the study, EU directives have been proposed and partly approved to regulate vehicle emissions and fuel qualities. These directives include directive 98/69/EC on emissions from motor vehicles (EC 1998), directive 98/70/EC on the quality of petrol and diesel fuels (EC 1998a), and directive 99/96/EC relating to heavy trucks (EC 1999).

The aim of the present project is to evaluate the impact on the future air quality in selected Danish cities of the new EU directives and proposals on vehicle emissions and fuel qualities. Furthermore, the objective is to compare the estimated future air quality with air quality limit values for protection of human health approved or proposed by EU as well as air quality guidelines by WHO and the Danish EPA.

Overall Methodology

The assessment is carried out for the reference year 1995 and the scenario years: 2000, 2005, 2010, 2015 and 2020.

Modelled substances include health related substances: NO₂ (NO_x), O_3, CO and benzene. Predictions for particles are based on expert judgement.

Future air quality levels are predicted in a selected street in Copenhagen (Jagtvej) that represent a near worst case. Air quality levels in the street is modelled by nested modelling taking into account emissions in the street, urban background levels and regional background levels. Interactions between the street air, the urban background air and the regional background air together with chemical transformations are modelled.

Additionally, calculations are carried out with less detailed input data for 103 other streets in the Copenhagen area with a wide range of traffic loads and street configurations to be able to generalise and relate the results to general traffic conditions in urban areas.

Danish Eulerian Model (DEM)

Regional background levels are predicted by the Danish Eulerian Model (DEM), a large-scale transport model based on 50 x 50 km² emission grids for all Europe and meteorology on a 150 x 150 km² grid. Development in European emissions is based on proposals for the new ECE protocols on regulation of trans-boundary air pollution.

Danish Urban Background Model (UBM) and Urban Emission Model (UBE)

The urban background levels are modelled by the Danish Urban Background Model (UBM) based on a 2 x 2 km² emission grid for the urban area. Grid emissions are determined by a Urban Emission Model (UEM) that takes into account the traffic levels on the road network. The model was originally developed by the Danish Road Directorate but it has been improved as part of the present project. Development in traffic emission factors is based on the EU COPERT III emission model, proposed emission reductions and prediction of the development of the age profile of the Danish car fleet.

Danish Operational Street Pollution Model (OSPM)

Air pollution levels in the street are modelled by the Danish Operational Street Pollution Model (OSPM) as a contribution from the direct traffic emission in the street and a contribution from the urban background. Vehicle emission factors are also based on COPERT III.

Content of Report

Chapter 2 outlines the overall methodology for prediction of future air quality levels. The applied models are shortly described, and this chapter also includes a short description of the selected case areas and scenario studies.

Chapter 3 describes the assumptions for and the development in emission factors based on COPERT III.

Chapter 4 includes a validation study of the prediction of the regional background levels by the DEM model and results from scenario studies.

Chapter 5 comprises a validation study of the prediction of the urban background levels by the UBM and UEM models and results from scenario studies.

Chapter 6 includes a validation study of the prediction of the street levels by the OSPM model and results from scenario studies. The results are compared with EU air quality limit values as well as WHO air quality guidelines and the Danish EPA air quality criteria.

In chapter 7 the results of the present study is compared with the ongoing EU study "Urban Impact Assessment" of the Auto-Oil Programme in 11 European cities as well as national vehicle emission scenarios carried out by the EU Commission.

Appendices include detailed information about the assumed development in traffic and emissions used as input for the different models.

Unit Conversion

The following values are used for conversion between different units:

*As NO₂-units.
**ppm to mg/m³.
***mg/m³ to ppm

2. Methodology

This chapter describes the overall approach and applied air quality models to estimate future air quality concentrations at street level.

Scenario Years

The assessment is carried out for the reference year 1995 and the scenario years: 2000, 2005, 2010, 2015 and 2020. All scenario years are run with meteorological parameters for the reference year 1995.

Species

Modelled substances include health related substances: NO₂ (NO_x), O_3, CO and benzene. Predictions for particles are based on expert judgement since high quality air quality models for prediction of particle concentrations are not available at present but under development.

Cases

Future air quality levels are predicted in a street named Jagtvej in the central part of Copenhagen. Jagtvej is selected because it represents a near worst case situation and because a monitor station is present in the street and in the urban background. Furthermore, detailed traffic data is available. Jagtvej has an average daily traffic of about 24.000 vehicles, the street width is 25 meters with 3-5 storeyed buildings.

Additionally, calculations are carried out with less detailed input data for 103 other streets in the Copenhagen area with a wide range of traffic loads and street configurations to be able to generalise and relate the results to general traffic conditions in urban areas.

Nested Modelling

Nested Modelling

Future air quality levels are predicted in Jagtvej, Copenhagen by nested modelling taking into account emissions in the street, urban background levels and regional air quality levels. Interactions between the street air, the urban background air and the regional background air together with chemical transformations are modelled, see Figure 2.1.

Figure 2.1
Illustration of the overall nested modelling approach estimating regional, urban and street air quality levels

In Figure 2.2 different components of the nesting modelling system is shown in greater details.

Figure 2.2   [Look here]
Illustration of the different components of the nested modelling approach

Regional Background Modelling

Regional Background levels

Figure 2.3
Example of model results from the DEM model shown on a 50x50 km² grid. Annual regional background concentrations of NO₂ in 1995. Left: Europe. Right: close-up of Denmark.

Regional background levels are predicted by the Danish Eulerian Model (DEM), a large-scale transport model based on 50x50 km² emission grids and 150x150 km² meteorological grids for all Europe (Zlatev 1995; Zlatev et al.1998). Development in European emissions is based on proposals for the new ECE protocols on regulation of trans-boundary air pollution, see Appendix 1. The model estimates hourly time-series of NO_x, NO₂, O₃ and CO. The model runs on a super computer at UNI•C in Copenhagen. An example of model results is given in Figure 2.3.

Urban Background Modelling

Urban Background Levels

The urban background levels in Copenhagen are modelled by the dispersion model Urban Background Model (Berkowicz 1999) based on a 2x2 km² emission grid for the urban area. Meteorological parameters are taken from an urban background top-roof mast at a nearby university building (HC Ørsted Institute). Grid emissions are given by the Urban Emission Model (Danish Road Directorate 1996).

Urban Emission Model (UBE)

The Urban Emission Model (UEM) estimates vehicle emissions on a 2 x 2 km² grid. The emission model takes into account the traffic levels on each road in each grid cell. The model covers an urban area of 151 km² around Jagtvej in Copenhagen. The model was originally developed by the Danish Road Directorate (Danish Road Directorate 1996) but it has been improved as part of the present project with more vehicle categories, more detailed diurnal variation in traffic loads and new emission factors based on COPERT III.

The model domain is illustrated in Figure 2.4.

Figure 2.4   [Look here]
Model domain of the Urban Background Model (UBM) and the Urban Emission Model (UEM). Identification No. for each 2x2 km² grid cell are also shown. Jagtvej in Copenhagen is located in cell d4.

Species and Time Resolution

The following species are included: CO, NO_x, NMVOC, particulates, and also CO₂. The diurnal variation in emissions on an hourly basis is estimated for working days, Saturdays and Sundays further sub-divided in July and remaining months. CO and NO_x emissions are used in the Urban Background Model to produce a time-series of these pollutants.

Road Types

Road types includes residential streets (30 km/h), traffic roads (50 km/h), arterial roads (60 km/h) and motorways (110 km/h).

Vehicle categories

The following vehicle types are included:

	Conventional gasoline passenger cars
	Closed loop catalyst gasoline passenger cars
	Conventional gasoline light duty vehicles (vans)
	Closed loop catalyst gasoline light duty vehicles (vans)
	Diesel passenger cars
	Diesel light duty vehicles (vans)
	Lorries (3.5-7.5 tonnes)
	Lorries (7.5-16 tonnes)
	Lorries (16-32 tonnes)
	Lorries (> 32 tonnes)
	Urban buses.

Emissions

Development in traffic emission factors is based on the EU COPERT III emission model (see chapter 3).

Street Pollution Modelling

Danish Operational Street Pollution Model (OSPM)

Air pollution levels in the street are modelled by the Danish Operational Street Pollution Model (OSPM) as a contribution from the direct traffic emission in the street and a contribution from the urban background. (Berkowicz et al. 1997; Jensen 1997, 1998). The urban background is determined by the UBM model.

The OSPM model calculates hourly concentration levels of: CO, NO₂, NO_x (NO + NO₂), O₃ and benzene.

The model describes the physical and chemical process in the street. The model takes into account the street configuration (street orientation, width, building height etc.) and simple photo-chemistry between NO, NO₂ and O₃.

Figure 2.5    [Look here]
The OSPM model describes the recirculation of air in a street canyon and simple photo-chemistry.

Traffic data and Emissions

The diurnal variation in hourly traffic loads has to be given for working days, Saturdays and Sundays and further sub-divided in July and remaining months. Emission factors are also based on COPERT III.

3. Vehicle Emission Factors

3.1 Background Data for Vehicle Emissions
3.2 Calculated Emission Factors for the Scenario Years

To provide the present study with emission data a simplified model has been made to forecast the emission factors for vehicles in the years 2000, 2005, 2010, 2015 and 2020 using 1995 as a reference year. The model covers the hot, cold and evaporative (running loss) emission types respectively for the emission species: CO, NO_x, VOC (NMVOC and CH₄), particulates, CO₂ and N₂O. CO and NO_x emission factors are used for air quality modelling of urban background and street levels.

The following vehicle types are included in the model:

	Conventional gasoline passenger cars
	Closed loop catalyst gasoline passenger cars
	Conventional gasoline light duty vehicles (vans)
	Closed loop catalyst gasoline light duty vehicles (vans)
	Diesel passenger cars
	Diesel light duty vehicles (vans)
	Lorries (3.5-7.5 tonnes)
	Lorries (7.5-16 tonnes)
	Lorries (16-32 tonnes)
	Lorries (> 32 tonnes)
	Urban buses.

3.1 Background Data for Vehicle Emissions

The travel speed dependent hot emission factors from the European road traffic emission model COPERT III are used as background emission data for all of today’s and future vehicle types (Ntziachristos, 1999). An overview of the different emission legislation levels for present and future vehicle layers are given in Table 3.1 and Table 3.2. A vehicle layer consists of the vehicles with comparable data for emissions and fuel consumption. In the present study the emission factors are picked out from COPERT III at a travel speed of 50 km/h. This choice of travel speed facilitates the subsequent use of data in models for air quality, where the single set of emission factors are scaled to represent the emission factors at travel speeds found in the selected case study streets.

An exception to the use of original emission data from COPERT III is made for conventional gasoline light duty vehicles. In this situation no classification is made in COPERT III to take into account vehicle age and technology levels. Instead the emission factors for these vehicles are represented by the emission factors from conventional gasoline light duty vehicles corresponding to first registration years, and emissions are multiplied with a factor of 1.5.

COPERT III does not give emission factors for benzene. Benzene emission factors have been established by so-called invert calculations by the OSPM model assuming that the OSPM gives a perfect description of the dispersion whereby emission factors for light and heavy vehicles can be estimated. In the reduction of benzene emission factors in the different scenario years, it is taken into account that the benzene content in petrol has decreased from 3% to 1% between 1995 and 2000.

The emissions from catalyst equipped vehicles increase with increasing mileage due to wear of the catalytic converter. Emissions continue to increase until a certain cut-off mileage is reached. At this time the emissions stabilise at a constant level due to On Board Diagnostics (OBD) in future catalyst cars and the implementation of the Danish inspection and maintenance programme. This is true when the emissions from the entire fleet is considered on average. For the individual vehicles the emission curves may be serrated. The deterioration factors and cut-off mileage from COPERT III are used in the present project to simulate the influence on emissions and fuel consumption due to catalyst ageing, OBD and the Danish inspection and maintenance programme.

In general the cold start emission factors are calculated as the hot emission factors times the hot/cold emission ratio, the latter ratio, see Appendix 1, is given in COPERT III. For catalyst gasoline vehicles the ratios exist for three engine sizes of passenger cars and one ratio for vans. The ratios are equivalent for gasoline fuelled conventional passenger cars and vans, and for diesel passenger cars and vans, respectively. Even though, the hot/cold ratios are constant for each of the individual vehicle classes, the cold start emission factors will decrease in the future. This is due to the gradually decrease in the emissions from the hot engines as stricter emission standards come into force. Additionally, the average length of each trip driven with a cold engine will gradually become shorter in the future due to stricter emission legislation for cold starts. The cold driven part of the trip length for trips starting with cold engines are expressed by the so-called beta-factors.

Table 3.1
Vehicle Layers for Passenger Cars According to EU Emission Legislation

Table 3.2
Vehicle Layers for Vans, Lorries and Buses According to EU emission Legislation

3.2 Calculated Emission Factors for the Scenario Years

The core in the simulation of emission factors for future years is the hot emission factors from COPERT III for the different vehicle types. The hot emission factors are further processed taking into account lower emissions for future new registered vehicles, and for each layer the number of vehicles and their corresponding annual mileage. Catalyst vehicle emissions are also simulated taking into account the decline in catalyst efficiency (deterioration factors). The lowering of emissions for vehicles in compliance with future EU emission legislation levels compared to EURO I levels are given in Table 3.3 and Table 3.4 for passenger cars and vans, and lorries and buses, respectively.

No forecast of the vehicle stock and annual mileage in layers for the future scenario years could be made available for the present study. The absence of fleet and mileage projections is partly compensated for by the use of the baseline year (1997) distributions of vehicle stock and annual mileage per first registration year (see Appendix 2). The use of 1997 distributions assume constant percentage shares for all future scenario years of the number of one-year old, two-years old etc. vehicles and correspondent mileage.

For all scenario years the emission factors for this study’s vehicle categories are subsequently calculated taking into account the implementation dates for new vehicle technologies and the number of km’s driven by vehicles of a certain age; this approach keeps track on the number of vehicles in each layer and the degree of catalyst wear, which in turn affects the aggregated results.

The calculated hot and cold emission factors for the present study’s vehicle categories are listed in Appendix 3 together with the weighted beta-factors (which represent the cold driven part of the trip length for trips starting with cold engines). Table 3.5 and Table 3.6 shows the development in the hot and cold emission factor levels and the beta-factors for the future scenario years with 1995 as base.

Table 3.3
Future Emissions of Passenger Cars and Vans Compared to EURO I

Table 3.4
Future Emissions of Lorries and Buses Compared to EURO I

Table 3.5
Levels of Hot and Cold Emission Factors and Beta-factors (Index) for Passenger Cars and Vans

* Exhaust

Table 3.6
Levels of Hot and Cold Emission Factors and Beta-factors (Index) for Lorries and Buses

* Exhaust

4. Regional Air Quality Levels

4.1 Scenario Emission data
4.2 Validation of DEM-Predictions for 1995
4.3 Future Regional Air Quality

Introduction

This chapter describes the future regional background levels as predicted by the Danish Eulerian Model (DEM). For the present study, the model predicts hourly air quality levels of NO_x, NO₂, O₃ and CO on a 50 x 50 km² grid. The model is not able to predict benzene levels. The levels represent average levels in the grid due to long-range transport of air pollution and the influence of local emission sources are not taking into account. The development in European emissions is based on EMEP data and ECE proposed developments in future national emission ceilings. The output of the DEM model is applied as input to the Urban Background Model (UBM) for prediction of urban background levels.

4.1 Scenario Emission data

The development in European emissions is based on EMEP data for 1990 and proposed national reductions in 2010 for all European countries under ECE. The national reductions are taking from an analysis by the International Institute for Applied Systems Analysis (IIASA) in Austria that carries out the preparatory work that leads to ECE protocols (IIASA 1999). In Autumn 1999, the ECE has proposed national emission ceilings for 2010 in a new multi-effect, multi-pollutant protocol on nitrogen oxides and related substances addressing photochemical pollution, acidification and eutrophication. This protocol is also referred to as the draft Protocol to Abate Acidification, Eutrophication and Ground-level Ozone which was approved in Gothenburg (Sweden) on 29 November - 3 December 1999 (ECE 1999).

The difference between the emissions by EMEP and IIASA applied in the project and the emission ceilings in the new ECE protocol for the reference year 1990 and the scenario year 2010 is given in Table 4.1. NO_x and VOCs are the main substances that form ozone in the atmosphere. The difference in reference data for 1990 is due to slightly difference emission data for some countries but also due to inclusion of emission from sea areas (ships) in the EMEP/IIASA data. There are also minor differences in the pro cent reduction assumed for the different countries. It is seen that the difference in emissions between the two scenarios is less than about 10 per cent. Therefore, all scenario studies have been carried out with the EMEP/IIASA data that was available to the project at an earlier stage than the new draft ECE protocol.

The national emissions in 1990 and the proposed emission ceilings in 2010 are given in Appendix 1 for all countries for EMEP/IIASA and for the new ECE protocol including the percentage reduction for each country.

For the reference year 1995 and the scenario years 2000 and 2005 it is assumed that the known reductions between 1990 and 2010 can be transferred to scenario years by linear interpolation. For the scenario years 2015 and 2020 the emissions for 2010 have been assumed since no data is available for these scenario years.

Table 4.1
The Difference Between the European Emissions (EMEP/IIASA) Applied in the Project and the New ECE Protocol Emissions (thousands of tonnes per year)

The predictions by the DEM model in 1995 have been validated against measurements at two regional background stations in the rural areas of the Greater Copenhagen Area: Frederiksborg and Lille Valby. A regional remote background stations in Jutland is also shown (Ulborg). Comparisons between modelled and measured values have been carried out for annual means, and seasonal and diurnal variation.

The differences in observed ozone levels in Denmark are minor since ozone formation is a large-scale phenomenon. The levels are slightly higher in Ulborg compared to Lille Valby and Frederiksborg since Ulborg is not influenced by ozone depletion due to local NO_x emissions. Levels are slightly lower at the forest station of Frederiksborg compared to the rural Lille Valby station probably due to a higher dry deposition of ozone on forest compared to agricultural land at Lille Valby (Jensen 1998).

Table 4.2
Comparisons Between Modelled and Measured Annual Means at Regional Stations in 1995 (ppb)

*Years with limited observations are given in brackets.

The DEM model overestimates O₃ levels in the regional background areas of Copenhagen compared to measurements. However, the model gives average predictions on a 50 x 50 km² grid and it is not able to reflect the influence of local NO_x emissions. The modelled levels are in better agreement with the remote station of Ulborg that is not influenced by local NO_x emissions.

The DEM model underestimates NO₂ levels for the regional Copenhagen area.

Few measurements are available for CO on Danish rural areas. Data from the Dutch monitoring programme shows that rural CO levels are about half of urban levels. The same ratio between urban and rural levels have been applied for the Danish rural background corresponding to 0.17 ppm in 1995 (Jensen 1998). The DEM model predicts about 0.5 ppm which is greatly overestimated. However, the DEM model has a crude estimation of CO emissions based on a ratio of VOC emissions. It is possible to obtain CO emission from EMEP for improving predictions but it has not been possible within the time frame of the present project. Therefore, the regional background annual level has been assumed to be 0.17 ppm in 1995. Measurements of CO at Frederiksværk in the background of Sealand during 1995 showed 0.33 ppm for a limited record during the year. This level seems to be overestimated since 0.34 ppm is measured in the urban background of Copenhagen. The monitor station of Frederiksværk is operated by the Greater Copenhagen Air Monitoring Unit.

Since the DEM model does not predict benzene the annual level of benzene is assumed to be the same ratio between CO and benzene as measured in the urban background of Copenhagen. The method for prediction of regional benzene is depending on urban background benzene described in greater details in Chapter 5.

The predicted seasonal variation of ozone is compared to measurements at Frederiksborg and Lille Valby in Figure 4.1 and 4.2. There is a good agreement between modelled and measured levels during spring and summer but the model overestimates levels in February and in autumn.

The overestimation in February reflects that there are predicted relatively few low values during this month. It does not reflect that the highest values are predicted during February, see Figure 4.3. Therefore, the monthly mean becomes relatively high. Within the time frame of the present project it was not possible to modify the DEM model to obtain better predictions for February. The average overestimation in February will have little impact on the estimation of the highest NO₂ concentrations at street level in Copenhagen since the highest ozone levels are not predicted in February.

Figure 4.1    [Look here]
Validation of seasonal variation of ozone at Frederiksborg

Figure 4.2    [Look here]
Validation of seasonal variation of ozone at Lille Valby

Figure 4.3    [Look here]
DEM predicted seasonal variation of hourly regional ozone levels for the regional background of Copenhagen in 1995

The predicted seasonal variation of NO₂ is compared to measurements at Frederiksborg and Lille Valby in Figure 4.4 and 4.5. There is generally a fair agreement although predicted levels are underestimated during spring and summer months and overestimated during November and December. As expected, the seasonal variation of predicted NO_x shows similar results as NO₂ just with higher levels.

Figure 4.4    [Look here]
Validation of seasonal variation of NO₂ at Frederiksborg.

Figure 4.5    [Look here]
Validation of seasonal variation of NO₂ regional background levels for Copenhagen at Lille Valby.

The predicted seasonal variation of CO showed almost no variation which is unlikely. Therefore, it is assumed that the seasonal variation is similar to the seasonal variation in the urban background in Copenhagen where the only available measurements are carried out.

Since the DEM model does not predict benzene the seasonal variation of benzene is assumed to be similar to CO.

The predicted diurnal variation of ozone is only compared to measurements at Frederiksborg in Figure 4.6 since the diurnal variation of ozone at Lille Valby is similar to Frederiksborg (Jensen 1998). There is generally a good agreement between modelled and measured levels although predicted levels show less relative difference between night and day time compared to measurements.

Figure 4.6    [Look here]
Validation of diurnal variation of regional background concentrations of ozone for Copenhagen at Frederiksborg.

The predicted diurnal variation of NO₂ is only compared to measurements at Lille Valby in Figure 4.7 since measurements are not available for Frederiksborg where only 24 hour samples are collected. NO₂ measurements at Lille Valby show a distinct diurnal variation with high levels in the morning and in the evening. The variation in measurements shows that Lille Valby is influenced by local traffic NO_x emissions from the nearby city of Roskilde and from the Copenhagen area. The predicted diurnal variation of NO₂ is smother since the DEM model is not able to take into account the influence of local emissions. As expected, the predicted diurnal variation of NO_x shows similar results although levels are slightly higher than NO₂.

Figure 4.7    [Look here]
Validation of diurnal variation of regional background concentrations of NO₂ for Copenhagen at Lille Valby.

The predicted diurnal variation of CO showed almost no variation which is unlikely. Therefore, it is assumed that the diurnal variation is similar to the diurnal variation in the urban background in Copenhagen where the only available measurements are carried out (Jensen 1999).

Since the DEM model does not predict benzene the diurnal variation of benzene is assumed to be similar to CO.

4.3 Future Regional Air Quality

Copenhagen Regional Background

Table 4.3 sums up the DEM model runs for the different scenario years for the future regional background in the rural Copenhagen area.

The table gives the predicted development in annual levels in ppb/ppm, µg/m³/mg/m³ and as an index. The index is defined as the level in the scenario years divided by the level in 1995.

Future predicted levels are also given for the regional background station Ll. Valby about 40 km outside Copenhagen using observed levels from 1995 as a base.

Since the DEM model does not predict benzene levels, the development for benzene is assumed to be similar to CO. CO and benzene in 1995 are not DEM predictions but estimated based on measurement in the urban background of Copenhagen. Levels of CO and benzene in a scenario year are estimated based on the 1995 level and the index determined by DEM calculations.

Table 4.3
DEM Predictions of Development in Future Regional Air Quality forthe Rural Copenhagen Area

From 1995 to 2010, NO_x and NO₂ levels are predicted to decrease about 40%. Ozone levels will only decrease by 2%, and CO and benzene by about 30% and 70%, respectively. Levels are the same from 2010-2020 since no information is available about future European emission ceilings beyond 2010.

5. Urban Background Levels

5.1 Urban Vehicle Emission Inventory
5.2 Validation of UBM Predictions for 1995
5.3 Future Urban Background Air Quality

The Urban Background Model (UBM) is used to predict urban background air quality levels in Copenhagen. Apart from data about the regional background described in the previous chapter, the UBM model also requires inputs about urban emissions on a 2 x 2 km² grid. The Urban Emission Model (UBE) is used to estimate these emissions.

The urban emissions are depended on the development in traffic on the urban road network and in vehicle emission factors. The development in emission factors are described in chapter 3.

For each grid cell, the Urban Emission Model requires traffic loads and vehicle composition on fire road types: local roads, traffic roads, arterial roads and motorways.

An analysis of the development in traffic loads in the city centre of Copenhagen shows that traffic loads have been constant during 1960-1994 with minor decreases and increases (Jensen 1997). The Municipality of Copenhagen has found similar results for 1970-1998 with a minor increasing trend since 1993 (Municipality of Copenhagen 1998). The geographic variation in traffic development has been uneven since traffic loads have increased by about 20% over the borders of the municipality and decreased 10% over the borders of the city centre. The regional roads within the municipality have had an increase of about 40% and other roads an decrease of about 15% (Municipality of Copenhagen 1997). The development in traffic loads has been characterised by stagnation in the city centre, increase on urban arterial roads and on the regional roads.

The Municipality of Copenhagen has carried out traffic forecast for 1992-2010 based on a traffic model for the Greater Copenhagen Area (HTM) and a traffic model (ØTM) developed for evaluating the impact of a new major development area in Copenhagen (Ørestad) (Municipality of Copenhagen 1997). Based on these traffic models the municipality assumes a 10 per cent traffic increase during 1992-2010 on the road network and the increase is expected to be on regional roads.

The regional roads have been identified (Municipality of Copenhagen 1999) and traffic increases on regional roads and other roads have been estimated based on the km travelled on these two road types assuming a traffic increase of 10 per cent on the entire road network during 1995-2010. Traffic increases for 2000 and 2005 have been estimated by interpolation, and traffic loads have been assumed to be constant after 2010. The increase on regional roads is 17 per cent from 1995-2010. The assumed development in traffic loads is given in Table 5.1.

Table 5.1
Assumed Development in Traffic Loads on Different Road Types (Index)

The Danish Road Directorate has carried out a forecast of the development in national km travelled broken down on different vehicle categories for 1997-2016 (Danish Road Directorate 1998). The analysis showed very small changes in traffic composition, therefore, the future vehicle composition on the urban road network is assumed to similar to 1995.

The number of catalyst vehicles has a major impact on emissions. The Danish Road Directorate was requested to supply data on the future penetration of catalyst vehicles based on km travelled which is given in Table 5.2

Table 5.2
Development in Penetration of Catalyst Vehicles for Petrol-powered Passenger Cars and Vans in Per Cent

The number of vehicles with cold engines has also a major impact on emissions. The assumed development in km travelled with cold engines based on data from COPERT III is given in Table 5.3

Table 5.3
Development in Km Travelled with Cold Engines

Diurnal Traffic Variation

Diurnal traffic variations are assumed to be similar for all scenario years since no data is available to establish trends.

The development in urban emissions is estimated using the Urban Emission Model based on the traffic input outlined above and emission factors given in chapter 3. In Table 5.4 the total emissions for all grids are given for the different scenario years. NO_x and CO emissions are estimated to decrease by a factor of 7 and benzene by a factor of 10 from 1995 to 2020. The sharp decrease in emissions is a result of stringent emission standards, decrease in cold starts times and penetration of catalyst vehicles which greatly counterbalance the assumed 10% increase in traffic.

Table 5.4    [Look here]
Development in Urban Emissions Estimated by the UBE Model. Distribution on Working Days, Saturdays and Sundays, July and not July.

The Urban background Model (UBM) is used to predict urban background concentrations based on input from the regional background levels produced by the DEM model and urban emissions produced by the UBE model.

A method has been set up to estimate benzene concentrations in the regional background as input for the UBM model since the DEM model does not predict benzene levels in the regional background. Benzene measurements have only been carried out at street level (Jagtvej in Copenhagen). An analysis of measurements shows that the ratio between benzene (ppb) and CO (ppm) was 4.0 before 1996 and 1.6 in 1999. Therefore, the benzene levels in the urban background are estimated based on the ratio of 4.0 for 1995 and 1.6 for scenario years 2000-2020 assuming that these ratios also are valid for the urban background. The ratio decreases due to a shift from 3 to 1 per cent of benzene in gasoline. To estimate the regional background levels of benzene the UBM model was run with the assumption that the UBM model gives a perfect prediction of measurements, whereby, the regional levels are measured urban background levels minus modelled urban background concentrations. In this way, the average ratio between the regional and urban background was established as Bnz_reg = Bnz_urban*0.36. That is, on average the regional background levels of benzene are 64% less that urban background levels of benzene. All in all, regional and urban background levels of benzene are ratios of urban background levels of CO.

Annual Means

In Table 5.5 the annual means predicted by the UBM model is compared with measurements at the Copenhagen urban background station. Table 5.5
Comparison Between Modelled and Measured Annual Means for the Urban Background in Copenhagen in 1995 (ppb)

The UBM model underestimates NO_x, NO₂ and CO air quality levels, and overestimates ozone levels. Observed benzene levels are actually modelled and therefore equivalent to modelled benzene levels.

The predicted seasonal variation of ozone is compared to measurements in Figure 5.2. There is generally a good agreement between modelled and observed levels although levels are overestimated in February due to too high predictions by the DEM model. It is also seen that urban background levels of ozone are highly dependent on the regional levels. Urban background levels are slightly lower than regional levels because urban NO_x emission deplete urban ozone levels.

Figure 5.1    [Look here]
Modelled and measured urban background levels of ozone in Copenhagen. Regional background levels are also shown.

The predicted seasonal variation of NO_x and NO₂ is compared to measurements in Figure 5.2. There is generally a good agreement between modelled and observed levels although levels are generally underestimated.

Figure 5.2    [Look here]
Modelled and measured urban background levels of NO_x and NO₂ in Copenhagen. Regional background levels are also shown.

CO and Benzene

The predicted seasonal variation of CO and benzene is compared to measurements in Figure 5.3. There is generally a good agreement between modelled and observed levels although CO levels are underestimated.

Figure 5.3    [Look here]
Modelled and measured urban background levels of CO and benzene. Regional background levels are also shown.

The predicted diurnal variation of ozone is compared to measurements at the Copenhagen urban background station in Figure 5.4. There is generally a good agreement between modelled and measured levels although predicted levels are overestimated during the evening and night.

Figure 5.4    [Look here]
Modelled and measured urban background levels of O₃. Regional background levels are also shown.

The predicted diurnal variation of NO_x and NO₂ is compared to measurements at the Copenhagen urban background station in Figure 5.5. There is generally a good agreement between modelled and measured levels although predicted levels are generally underestimated.

Figure 5.5    [Look here]
Modelled and measured urban background levels of NO_x and NO₂. Regional background levels are also shown.

The predicted diurnal variation of CO and benzene is compared to measurements at the Copenhagen urban background station in Figure 5.6. There is generally a good agreement between modelled and measured CO levels although predicted levels are generally underestimated. There is also a general good agreement between modelled and measured benzene levels although benzene levels are underestimated during night and overestimated during afternoon rush hours.

Figure 5.6    [Look here]
Modelled and measured urban background levels of CO and benzene. Regional background levels are also shown.

The general underestimation of NO_x and NO₂ (and therefore overestimation of ozone) may be due to too low vehicle emission factors for NO_x. The general underestimation of CO may also be due to underestimation of vehicle emissions for CO. Emission factors were based on COPERT III that may be too low for Danish conditions because a validation of the Urban Background Model was carried out with much better agreement between modelled and observed levels using emission factors based on Danish studies (Jensen 1992, 1995; Krawack 1991) and fitting of emission factors to obtain better agreement with measurements. The validation study is published in Berkowicz (1999). The main difference is the these emission factors have about a factor 2 higher CO values for passenger cars without catalysts and also about at factor 2 higher NO_x values for lorries. A possible underestimation of emission factors by COPERT III is further investigated in the next chapter.

5.3 Future Urban Background Air Quality

Copenhagen Urban Background

Table 5.1 sums up the UBM model runs for the difference scenario years for the future urban background air quality in Copenhagen. The table gives the predicted development in annual levels in ppb/ppm, µg/m³/mg/m³ and as an index. The index is defined as the levels in scenario years divided by the levels in 1995. Future predicted levels are also given for the urban background station in Copenhagen using observed levels from 1995 as a base and the index for the development.

Table 5.6
UBM Predictions for Annual Levels of Future Urban Background Air Quality in Copenhagen

6. Air Quality at Street Level

The OSPM model is used to predict air pollution levels in the street of Jagtvej in Copenhagen. The hourly time-series produced by the Urban Background Model is used as input to the OSPM model together with COPERT III based emission factors, and parameters on traffic in the street, street configuration and meteorology.

6.1 Validation of OSPM Predictions

Table 6.1 shows that the OSPM model underestimates the observed levels for NO_x, NO₂ and CO, especially for CO. Ozone levels are overestimated as a consequence of the underestimation of NO_x. Benzene levels are well predicted since benzene emission factors are determined by invert calculations with the OSPM.

Table 6.1    [Look here]
Modelled and Measured Annual Means at Street Level in 1995 (ppb) (Jagtvej, Copenhagen)

Figure 6.1    [Look here]
Scatter plots of modelled and observed NO_x, NO₂, CO and benzene hourly concentrations in Jagtvej, Copenhagen. One to one lines are also drawn.

Figure 6.1 shows a general good agreement between modelled and observed concentrations although predicted levels are systematically underestimated for NO_x, NO₂ and CO possible due to underestimation of emission factors.

As discussed in the previous chapter, COPERT III emission factors may underestimate real world emissions on the road since better results were obtained with the Urban Background Model using emission factors that were about a factor 2 higher for CO for passenger cars without catalysts and about at factor 2 higher for NO_x for lorries.

In Figure 6.2, the possibility of underestimation is further investigated by comparison of COPERT III emission factors (new emissions) and the formerly used emission factors (old emissions) as input for OSPM calculations.

The figure shows the ratio between CO and NO_x for modelled and measured values in Jagtvej, Copenhagen for working days, Saturdays and Sundays. If the ratio between vehicle emissions of CO and NO_x is correct then the slope of the regression lines of modelled air quality levels will be identically to the measured concentrations in the street air.

It is seen that the slope of modelled air quality levels using COPERT III emission factors is very different from the measured ratio between CO and NO_x in the street air. Much better results are obtained with the old emission factors.

This indicates that the ratio between COPERT III emission factors for CO and NO_x is incorrect since it does not comply with the ratio found in the measured street air.

The emission factors in the OSPM model are adjusted according to travel speed during working days based on emission factors at 50 km/h. The same method has been applied for both new and old emission factors. For Saturdays, the travel speed is assumed to be 50 km/h, and the old emissions give almost a perfect fit in this situation between modelled and measured ratios of CO and NO_x indicating that the ratio between CO and NO_x is correct for the old emission factors and questionable for COPERT III, see Figure 6.2.

Nevertheless, COPERT III emission factors have been applied throughout the study although predicted air quality levels become underestimated. For prediction of future concentrations in the urban background or in the street, observed levels have been applied from 1995 as a baseline for calibration, and the modelled trend as an index has been used to estimate future levels to give realistic predicted air quality levels that can be compared to air quality limit values.

Figure 6.2    [Look here]
Comparison of the ratio between modelled CO and NO_x levels in the street with COPERT III emission factors (new emissions) and formerly applied emission factors (old emissions).

6.3 Future Air Quality at Street Level

Table 6.2 sums up the OSPM model runs for the difference scenario years for the future air quality at street level in Copenhagen.

Table 6.2    [Look here]
OSPM Predictions for Future Air Quality at Street Level in Copenhagen (Jagtvej)

The table gives the predicted development in annual levels, and 98- and 99.8-percentiles in ppb/ppm, µg/m³/mg/m³ and as an index with the reference year equals 100. Future predicted levels are also given for Jagtvej in Copenhagen using observed levels from 1995 as a base and the development represented by the index. The calibration is required to give realistic future air quality predictions that can be compared to limit values because too low air quality levels are predicted using COPERT III emission factors without calibration.

Catalyst cars were introduced in Denmark in 1990/91 and reduce NO_x emissions (NO and NO₂).

NO₂ observed levels in Jagtvej were more or less constant during 1990-95 indicating that ozone was the limiting factor in forming NO₂ in reactions between NO and ozone.

From 1995 to 1998, measurements show a downward trend in NO₂ levels, and this trend is also reproduced by the OSPM model.

During 1995-2010/2020, 98- and 99.8-percentiles of NO₂ are predicted to decrease about 50% and 35%, respectively.

The predictions show that NO becomes the limiting factor in forming NO₂ in reactions with ozone in the future due to the steadily decreasing NO_x emissions (NO and NO₂, NO constitutes about 95% of NO_x vehicle emissions).

Ozone levels increase because less NO emitted from vehicles in the street is available for ozone depletion.

CO levels are predicted to decrease by a factor of 4 and benzene levels by a factor of 10 from 1995 to 2010. The predicted downward trends of CO and benzene are also support by observed levels during 1995-1998.

A summary of present EU air quality limit values, WHO guidelines and Danish EPA criteria for the modelled pollutants is presented in Table 6.3.

The Danish EPA air quality criteria were set up to minimize of adverse health effects. The air quality criteria are not administrative limit values but should be regarded as desired long-term objectives (Larsen et al. 1997).

New EU limit values have to be met in 2010. A margin of tolerance has been defined to secure that limit values will be met in 2010. The margin of tolerance given as a percentage in the table refers to the year the directive entries into force. The margin of tolerance is equally stepped down each year to reach 0% in 2010. Member states have to take local action if the margin of tolerance is exceeded.

Table 6.3
EU Air Quality Limit Values, WHO Guidelines and Danish EPA Criteria for Protection of Human Health

¹ Not to be exceeded on more than 20 days per calendar year averaged over three years

NO₂

The EU limit value for NO₂ for long-term exposure was exceeded in 1995 and the limit value for short-term exposure is tangent. However, the margin of tolerance of 50% in 1999 is not exceeded.

The predicted NO₂ levels in 2010 at Jagtvej are about half of the EU limit value in 2010. The Danish EPA criteria for short-term and long-term exposure is exceeded for all scenario years until 2015-2020.

The EU limit value for CO will be between the 98- and 99.8-percentile. The EU limit value for CO was not exceeded in 1995, and the margin of tolerance of 50% will not be exceeded in the expected year of entry into force of the directive (2000). In 2010 the predicted CO levels will be 10-20% of the EU limit value in 2010. The EU limit value and WHO guidelines are identically for CO. The Danish EPA has not suggested criteria for CO.

The EU limit value for benzene was exceeded in 1995. The margin of tolerance of 100% will not be exceeded based on modelled levels in 2000, the expected year of entry into force of the proposed directive. The predicted levels in 2010 will be about half of the EU limit value. WHO guidelines and Danish EPA criteria are exceeded for all scenario years.

The average ozone levels in the street will increase due to a decrease in NO vehicle emissions in the street leaving less NO for depletion of ozone in forming NO₂, see Table 6.2. However, the sum of NO₂ and O₃ will decrease.

The highest levels calculated as a 8 hour running maximum will slightly decrease over the years because the highest ozone levels in the regional background are predicted to decrease. The proposed EU limit value for ozone is 120 m g/m³ as a 8 hour running maximum not to be exceeded on more than 20 days per calendar year averaged over three years. This short-term limit value was not exceeded in 1995 nor is it predicted to be exceeded in 2010 and the following years despite an increase in average ozone levels in the street.

In Table 6.4 exceedances of the ozone threshold of 120 m g/m³ are given for the urban background. The urban background is a better indicator for ozone exposure of the population than levels in the streets since ozone levels are influenced by NO emissions.

Since the number of exceedances are less than 20, the EU limit value is not violated in the urban background. The number of exceedances of the threshold value of 120 m g/m³ increases over the years. This is due to the general increase in ozone levels in the urban background that will cause more peak values to exceed the 120 m g/m³ threshold. However, the model overestimates ozone levels as was seen in the previous Chapter 5, Table 5.5, and the presented exceedances in Table 6.4 are based on modelled ozone data that have not been adjusted to the observed level in 1995. Furthermore, since several modelled values are close to the threshold value 120 m g/m³ and the model overestimates ozone levels, it is likely that there will be few exceedances of this threshold in future observed ozone levels in the urban background.

Table 6.4
Exceedances of Proposed Threshold for EU Limit Value for Ozone Based on Modelled Ozone Data

OSPM Calculation for 103 Copenhagen Streets

Based on OSPM calculations for 103 different streets in the Copenhagen Area, an empirical relation between traffic density and street air quality for NO₂ and benzene was established in 2000 and 2010, see figure 6.3-5. The streets represent a wide range of traffic loads and street configurations however with a little less detailed information about traffic and street configuration data compared to data available for Jagtvej. Traffic density is here defined as average daily traffic divided by the width of the street. The modelled emission reductions and predicted urban background levels in 2000 and 2010 by the present study has been applied.

This relation can be applied for crude assessment of the air quality in a street just knowing the traffic density as defined. Since urban background data for Copenhagen was used, the street levels will be overestimated in other Danish cities where the urban background concentrations are lower. Since the relation was established for urban streets in built-up areas, air quality levels will be overestimated if applied for rural roads where dispersion characteristics are different.

It is seen that annual levels of NO₂ and benzene in 2000 are exceeding the limit value for 2010.

Figure 6.3    [Look here]
Model calculations for annual mean of NO₂ in 2000 for 103 Copenhagen streets with the OSPM model. Jagtvej is marked with a bold dot. The new EU limit value for 2010 is also shown.

Figure 6.4    [Look here]
Model calculations for 99.8-percentile of NO₂ in 2000 for 103 Copenhagen streets with the OSPM model. Jagtvej is marked with a bold dot. The new EU limit value for 2010 is also shown.

Figure 6.5    [Look here]
Model calculations for annual levels of benzene in 2000 for 103 Copenhagen streets with the OSPM model. Jagtvej is marked with a bold dot. The new EU limit value for 2010 is also shown.

The predicted development in future air quality levels in 2010 for NO₂ and benzene for the 103 Copenhagen streets is given in Figure 6.6-8.

Similar to the scenario 2010, it is assumed that traffic loads are constant in the streets considered while an increase on main roads of 17% is assumed corresponding to a general traffic increase in the road network considered of 10% 1995-2010.

Air quality levels in 2010 are predicted to decrease for NO₂ and benzene, and none of the considered Copenhagen streets will violate the limit values of NO₂ and benzene for 2010.

Figure 6.6    [Look here]
Model calculations for annual levels of NO₂ in 2010 for 103 Copenhagen streets with the OSPM model. Jagtvej is marked with a bold dot. The new EU limit value for 2010 is also shown.

Figure 6.7    [Look here]
Model calculations for 99.8-percentile of NO₂ in 2010 for 103 Copenhagen streets with the OSPM model. Jagtvej is marked with a bold dot. The new EU limit value for 2010 is also shown.

Figure 6.8    [Look here]
Model calculations for annual levels of benzene in 2010 for 103 Copenhagen streets with the OSPM model. Jagtvej is marked with a bold dot. The new EU limit value for 2010 is also shown.

6.6 Preliminary Assessment of Particulate Air Pollution at Street Level

Introduction

In this section, a preliminary assessment of the particle levels in selected streets in Denmark is carried out and levels are related to the new EU limit values for PM₁₀. The impacts of future particle emission reductions are also briefly discussed. The assessment is based on measurements since air quality models for particles are not fully developed.

Health Effects

It is recognised that particles in urban air are responsible for serious health effects, i.e. long-term effects like cancer, and cadio-vascular decease and acute effects like allergy or irritation of eyes, nose and throat (Larsen et al. 1997). Particles are often characterised by the mass determined as PM₁₀ or PM_2.5, particulate matter less than 10 m m and 2.5 m m, respectively.

New EU Limit Values

The regulation from the Danish Ministry of Environment no. 836 dated 10.12.1986 on air quality includes limit values for TSP (Total Suspended Particles), i.e. 300 µg/m³ as 24 hour average and 150 µg/m³ as annual average. A new EU directive "Council directive 1999/30/EC of 22 April 1999 relating to limit values for sulphur dioxide, nitrogen dioxide and oxides of nitrogen, particulate matter and lead in ambient air" gives limit values for particulate matter (PM₁₀). The Member States have to comply with the 24 hour limit value 50 µg/m³ - not to be exceeded more than 35 times per year and 7 times per year - before 2005 and 2010, respectively. For annual averages the limit values are 40 µg/m³ and 20 µg/m³ for 2005 and 2010, respectively.

WHO has not recommended a limit value for PM, because knowledge is missing and no lower observed effect level has been identified. Consequently, the EU Commission has also realised that our knowledge about adverse health effect and the sources and chemical/physical characteristics of particles is too limited; therefore it has been decided to revise the limit values for particles within a few years when more information is available. The directive also includes obligations for the Member States to collect data on smaller particles PM_2.5. However, investigations have shown that the correlation between particle concentration and health effect increases with decreasing particle diameter. It is therefore important to determine the concentration given as number of particles in many size intervals.

Characteristics of Particles

The particle size distribution is an important factor that needs to be addressed whenever the PM pollution is concerned. A major contribution to particulate pollution in urban areas is believed to be from traffic, especially diesel powered vehicles. Particles emitted from car engines, petrol as well as diesel engines, are formed at high temperatures in the engine, in the exhaust pipe or immediately after emission to the atmosphere. These particles are in the so-called nucleation mode and the diameter of the particles is < 0.2 m m, ultrafine particles. Other particle modes are accumulation mode (fine particles), > 0.2 m m - 2 m m, which typically are formed by chemical reactions of (e.g. SO₂ and NO_x to form sulphate and nitrate), coagulation, condensation of gases on particles or other relatively slow processes. The last mode is the coarse particles > 2 m m, which typically are formed mechanically by traffic turbulence, wind erosion etc. These larger particles may also cause health effect. The size distribution and the main characteristics of urban particles are shown schematically in Figure 6..

Figure 6.9    [Look here]
Schematics of the size distribution of urban particles. The vertical scale is arbitrary. The shape of the distribution will change for a specific vertical axis; if the vertical axis is mass, then the ultrafine part of the distribution will be insignificant and if the vertical axis is number, then the coarse part of the distribution will be small.

Trends and Levels of TSP and PM Pollution in Denmark

The total suspended particulate matter (TSP) is determined in the National Air Quality Monitoring Programme (LMP) (Kemp and Palmgren, 1999) by weighing of the aerosol filters. The samplers collect particles up to an aerodynamical diameter of around 25 µm, but this cut-off varies from about 10 to 50 µm depending on the wind speed (Kemp 1993). The particles are a mixture from the different source types, but the coarse particles (> 2.5 µm) of windblown dust of local origin are expected to dominate. The fine particle fraction includes contributions of long range transported soil dust and particles from combustion processes, e.g. sulphate and nitrate particles.

TSP was measured in 1998 as 24 hour average values at street stations in the major Danish cities: Copenhagen, Odense and Aalborg and at the regional background station of Lille Valby about 40 km outside Copenhagen. The measurements at Lille Valby started in the beginning of 1995. Statistics from 1998 are shown in Table 6.5 (Kemp and Palmgren, 1999). The old limit values were not exceeded.

Table 6.5.
Annual Values, 95-percentiles and Maximum Values for TSP in 1998. The Numbers are Calculated for 24-hour Average Values

Trends

The trends of TSP are shown in Figure 6.10. The general trend has been a decrease of about 30-50% during 1988-1998 for the street stations. A major part of the mass of the particles (coarse particles in Figure 6.) is windblown dust and may be considered to be either of "natural" origin, constructions or re-suspended particles from the roads. The particles from combustion processes are in the fine particle fraction, and it is expected to decrease in the future due to emission reductions.

The observed trend in TSP may be a result of i.e. better cleaning of emissions from power plants, obligatory three way catalysts (TWC) on petrol cars, restrictions on the diesel exhaust, and more green agricultural fields during winter (less soil dust).

TSP has been measured at the rural station Lille Valby for almost 4 years. The levels are between on third to half of the levels at the urban street stations.

Figure 6.10     [Look here]
Average values and 95-percentiles for TSP in Denmark from 1988 to 1998.

PM₁₀

Continuous measurement of PM₁₀ was started in July 1998. Sampling in 24 hour intervals is performed using an OPSIS SM200 sampler at Jagtvej, Copenhagen. The particles are collected on membrane filters (Millipore type AA). The PM₁₀ is determined both on-line with the build-in b -gauge and gravimetric, using the same procedure, as for TSP. TSP is approx. 35% higher than PM₁₀, that is, PM₁₀ constitutes about 74% of TSP.

Figure 6.11     [Look here]
The relationship between TSP and PM₁₀ at Jagtvej in Copenhagen, 1998.

In Table 6.6, the PM₁₀ level in selected streets in Denmark have been estimated based on the above relation between TSP and PM₁₀.

Tabel 6.6
Estimated Annual PM₁₀ Levels in Selected Streets in Danmark¹

¹ PM₁₀ equals 74% of TSP

It is seen that the estimated PM₁₀ levels in 1998-99 are below the new limit value for 2005 but exceed the limit value for 2010.

Denmark has a national objective to reduce particle vehicle emission by 50% in urban areas 1988-2010, and further reductions after 2010. The increase in penetration of catalyst converters reduce particle emissions for petrol powered vehicles due to unleaded petrol. Catalysts become mandatory in 1990. New stringent particulate emission standards for especially diesel powered vehicle will reduce particle emissions. The conversion to diesel with a low content of sulphur will also reduce particulate emissions.

Previous assessments indicate that the total particulate emissions (as mass) from vehicle within the EU will decrease by about 70% 1995-2010 including expected increases in traffic (Iversen 1999). Based on a few number of European studies, WHO has estimated that the particulate emission from vehicles in urban areas contributes about 40-60% of PM₁₀ (WHO 1999).

Due to the above mentioned vehicle particulate emissions regulation it is likely that the PM₁₀ will decrease in the future but it is difficult to predict how much based on existing knowledge and to predict if the limit value of 2010 will be met. The above figures indicate that it might be a problem.

Fine and Ultrafine Particles

The fine and especially the ultrafine particles emitted directly from the diesel and petrol fuelled vehicles contribute only a little to the particle mass TSP and PM₁₀.

It is therefore necessary to use other measurement techniques to measure these particles. In addition, we have some indication that the number of ultrafine particles, which can penetrate into the deepest parts of the lungs, is important to assess the health risk of particulate air pollution. A precise determination of the emission of particles from the actual car fleet is necessary for analysis of the problem in urban areas, investigations of the health impacts, and recommendations of abatement measures to be taken to reduce the pollution.

Particle Size Distribution

In order to characterise the particle pollution emitted directly from car engines, a method to measure the ultrafine particle mode has been developed. The method uses a Differential Mobility Analyser, DMA. This method is based on particle size fraction separation by the particles’ mobility, determined by movement of charged particles in electrical fields. The DMA measures with a high time resolution which is necessary for identification of traffic air pollution in order to separate this source from other types of air pollution.

Measurements have been carried in busy streets in Copenhagen (Jagtvej) and Odense (Albanigade) comprising long time-series of particle spectra in connection with the normal monitoring of air pollutants, i.e. NO_x/NO₂, CO, benzene, O₃ and SO₂. In this way it was possible to determine the contribution from local traffic in the street by subtraction of the urban background concentration from the concentration measured in the street, and by inverse model calculation by the street pollution model OSPM (Berkowicz et al. 1997). The method has been used on stable pollutants like NO_x, CO and benzene (Palmgren et al. 1999). Preliminary investigations have shown that the ultrafine particles do not change size significantly during the residence time in the street, i.e. less than a few minutes (Vignati et al., 1999). The DMA method gives the size distribution in the range 0.01 – 0.7 m m. However, the distribution is not determined simultaneously, but by sweeping over the size range during a few minutes. The DMA was also applied for laboratory studies of the emissions from vehicles.

Examples of results are shown in Figure 6.. It is seen that particles from diesel powered vehicles are a little smaller than particles from petrol powered vehicles. Analysis shows that diesel vehicles on average emit about 25 times as many particles as petrol vehicles. The contribution from diesel and petrol vehicles was almost the same at Jagtvej because of few diesel vehicles. The contribution of ultrafine particle from diesel vehicles at Albanigade in Odense, which is a more typical city street, was much higher than from petrol vehicles (Palmgren and Wåhlin, 1999).

Figure 6.12   [Look here]
The particle number spectrum at Jagtvej in Copenhagen during rush hour.

The particle number spectrum at Albanigade in Odense during rush hour.   [Look here]

The number distribution can be translated to volume distribution (or mass distribution assuming mass density 1), see Figure 6.13. It is seen that the relatively few larger particles (Figure 6.12) contributes significantly to the mass. Traffic contributes about Ÿ of the mass of ultrafine particles (PM_0.2). In this case, it is also seen that the petrol powered vehicle mass contribution is comparable with the non-traffic contribution for ultrafine particles.

Figure 6.13    [Look here]
The particle number translated to volume at Albanigade in Odense.

Further investigations needed

The knowledge about the air pollution with particulate matter is still rather limited. By the new PM₁₀/PM_2.5 methods and the application of DMA for measurement of ultrafine particles from traffic, possibilities have opened to obtain valuable data. Systematic measurements, including long time-series, by these methods at representative sites will improve the possibilities for health studies substantially. However, more knowledge is needed about the chemical/physical properties of the particle, e.g. chemical composition, surface properties and morphology; for this purpose it is necessary to include other analytical techniques, e.g. SEM and micro probe analysis. The characterisation of the particles is also important for quantification of the contribution from different sources and parameterisation of the properties of the particles to be included in air quality models. This is necessary for decisions on abatement measures to be taken to reduce the health impacts of particulate air pollution and to evaluate the effects of the measures taken.

7. Comparison with EU Predictions

In this chapter, a comparison between the results of the present study and work carried out by the EU Commission is undertaken for emissions and air quality.

The EU Commission has carried out an impact assessment of the Auto-oil II programme on the total vehicle emissions. The task has been undertaken by Senco - Sustainable Environment Consultants - based on the TREMOVE model (AOPII Emissions Base Case). For further details see Senco (1999). The emission factors of the present study are derived for the different vehicle categories (g/km) based on COPERT 3 and Danish traffic characteristics. To be able to compare these emission factors with the results of the EU Commission, Danish national emissions were calculated by Risoe National Laboratory, Denmark and NERI (Fenhann 2000). The comparison is shown in Table 7.1.

Table 7.1
Comparison of Total Vehicle Emission Predictions

The comparison shows that the predicted total emissions are more or less similar. The observed differences may be due to differences in approach and assumptions about emission factors and traffic development.

Comparison of the results of the present study with EU predictions and another Danish study has been carried out. The comparison includes urban background and street predictions.

EU and Danish Studies

Urban Impact Assessment Study, AOPII

The EU Commission has undertaken the Urban Impact Assessment study including ten larger European cities to estimate the impact of the Auto-oil II proposals for vehicle emission reductions on urban air quality 1995-2010 (EU Commission 1999). The urban background air quality has been modelled by different urban scale models: CALGRID, Urban Airshed Model (UAM) v. IV, and the European Urban Airshed Model (EUAM). The regional background is the boundary conditions for the urban models. Data on the regional background has been derived from work carried out by IIASA with the RAINS model as part of the ongoing EU strategy to reduce trans-boundary air pollution.

As part of the project, street canyon modelling has been carried out in two of the cities: Milan and Berlin using the MICROCALGRID and the Danish OSPM model. The results for OSPM calculations are given in Berkowicz (1999a). Copenhagen is not included in the case studies.

Impact Assessment at Seven Streets in Copenhagen

A minor Danish study has carried out an impact assessment of the future air quality related to the new EU limit values in 2010 for seven streets in Copenhagen with reference year 1997 . This study did not model future vehicle emissions nor did it model the urban background. Crude assumptions were applied for future vehicle emission factors and the urban background (Berkowicz & Palmgren 1999).

Air Quality in the Urban Background

In Table 7.2, findings of the present study are compared with results from the urban background predictions in ten European cities based on preliminary results from the Urban Impact Assessment Study.

Table 7.2
Urban Background Predictions for NO₂ and Benzene in Ten European Cities (EU Commission 1999)

Comparison with Ten European Cities

For the ten European cities, the results are preliminary based on EU Commission (1999). For each city, the modelled concentrations reflect the highest modelled levels in a grid cell of all the grid cells considered. It is seen that the annual NO₂ urban background levels in Copenhagen are the lowest compared to the other European cities. There is a tendency to high NO₂ levels in Southern Europe cities compared to Northern European cities due to high ozone levels in Southern Europe. Modelled annual benzene levels in the urban background are also relatively low in Copenhagen in 1995 and the lowest in 2010.

Comparison with Milan, Berlin and Danish Study

The urban background was also modelled as part of the project on street canyon modelling in Milan and Berlin (Berkowicz 1999a), and as part of a Danish study (Berkowicz & Palmgren 1999). Results of the present study are compared with these studies in Table 7.3.

Table 7.3
Comparison of Annual Levels of Urban Background Predictions

¹ based on Berkowicz (1999a), ² based on Berkowicz & Palmgren (1999)

Berlin and Milan

It is seen that the results of the present study are similar to findings for Berlin and that much higher levels are modelled for Milan except for ozone due to depletion of ozone by the high NO_x levels in Milan. All pollutions decreases except ozone from 1995 to 2010.

Danish Study

It is surprising that predicted urban background levels in 2010 for the Danish study are very close to the predictions of the present study because crude assumptions were applied in Berkowicz & Palmgren (1999). The study assumed that urban background levels decreased 70% for NO_x, CO and benzene, and that regional background levels of NO₂ and ozone decreased by 50%. The NO_x emissions from trucks were assumed to decrease by 50% and 90% of passenger cars were assumed to have catalyst converters in 2010. The present study modelled a reduction in the urban background of NO_x, CO and benzene of 61%, 43% and 82%, respectively (see Table 5.6). The regional NO₂ background was modelled to decrease by 36%, and for ozone by only 2% (see Table 4.3). NO_x emissions from trucks were modelled to decrease by 61-67% (see Table 3.6). A combination of under- and overestimations that neutralizes each other explains why Berkowicz & Palmgren (1999) estimate similar results as the present study. Underestimation of the regional and urban background levels of NO_x and overestimation of NO_x emission explains the similar NO_x levels. NO₂ levels are similar although regional NO₂ and also urban NO_x are assumed to be lower. The reason is the combination of overestimated NO_x emissions and overestimated ozone levels raising NO₂ levels in the urban background.

Air Quality at Street Level

In Table 7.4, findings of the different studies are shown at street level. The selected roads in Milan, Berlin and Copenhagen are different with respect to traffic loads, vehicle composition, fraction of catalyst cars, and street configurations, and therefore air quality levels will vary.

Table 7.4
Comparison of Predicted Annual Levels at Street Level

¹ based on Berkowicz (1999a), ² based on Berkowicz & Palmgren (1999)

Berlin and Milan

It is seen that the results of the present study are similar to findings for Berlin (except for NO_x)and that much higher levels are modelled for Milan.7

Danish Study

Compared to the present study, the assessment of the 7 Copenhagen streets finds higher NO_x levels due to overestimation of NO_x emissions. NO₂ levels are similar for the same reasons given as for the urban background. Benzene levels are overestimated because the reduction of the content of benzene in petrol to 1% in 2010 is not fully taken into account in the assumptions.

All in all, the findings of the present study for Copenhagen are in accordance with the EU Urban Impact Assessment study for a comparable city like Berlin.

List of References

Berkowicz, R., Hertel, O., Sørensen, N.N., Michelsen, J.A. (1997): Modelling Air Pollution from Traffic in Urban Areas. In proceedings from IMA meeting on "Flow and Dispersion Through Obstacles", Cambridge, England, 28-30 March, 1994 (eds.) Perkins, R.J., Belcher, S.E., pp. 121-142.

Berkowicz, R. (1999): A simple model for urban background pollution. 2^nd International Conference on Urban Air Quality, Measurement, Modelling & Management, 3-5 March 1999, Madrid. 3 p.

Berkowicz, R. (1999a): Case Study of Traffic Pollution in Urban Streets in the Framework of AOPII. Application of the Operational Street Pollution Model (OSPM) for two Streets in Milan and Berlin. 34 p.

Berkowicz, R. & Palmgren, F. (1999): Beregninger af luftforurening fra trafik i udvalgte gader i København. Undersøgelse udført af Danmarks MIljøundersøgelser, Afdeling for Atmosfærisk Miljø for Københavns Kommune, Miljøkontrollen. (In Danish. Calculation of Traffic Air Pollution in Selected Streets in Copenhagen. NERI for the EPA of the Municipality of Copenhagen).

Danish Road Directorate (1996): Byområders trafikskabte luftforurening. (In Danish. Traffic Air Pollution in Urban Areas. A Method for Emission Mapping. Report 43. Vejdirektoratet, Denmark. 147 p.

Danish Road Directorate (1998): Fremskrivning af vejtrafikken 1997-2016. Rapport 164, 28 s. (Forecasting Road Traffic 1997-2016. In Danish).

EC (1998): Directive 98/69/EC of the European Parliament and of the Council of 13 October 1998 relating to measures to be taken against air pollution by emissions from motor vehicles and amending Council Directive 70/220/EEC.

EC (1998a): Directive 98/70/EC of the European Parliament and of the Council of 13 October 1998 relating to the quality of petrol and diesel fuels and amending Council Directive 93/12/EEC.

EC (1999): Directive 1999/96/EC of the European Parliament and of the Council on the approximation of the laws of the member states relating to measures to be taken against the emission of gaseous and particulate pollutants from compression ignition engines for use in vehicles, and the emission of gaseous pollutants from positive ignition engines fuelled with natural gas or liquified petroleum gas for use in vehicles and amending council directive 88/77/EEC.

ECE (1999): Draft Protocol to the 1979 Convention on Long-range Transboundary Air Pollution to Abate Acification, Eutrofication and Ground-level Ozone. UN Economic Commission for Europe. EB.AIR/1999/1. 15 October 1999.

EU Commission (1999): The Auto-Oil II Programme. A Report form the Services of the European Commission. Report by the Directorates General for: Economic and Financial Affairs, Enterprise, Transport and Energy, Environment, Research and Taxation and Customs Union. Draft version 5.0. November 1999. 110 p.

Fenhann (2000): Projections of Emissions of Greenhouse Gases, Ozone Precursors and Sulphur Dioxide from Danish Sources until 2012, Risoe National Laboratory, Roskilde, Denmark (to be published).

IIASA (1999): Cost-effective Control of Acidification and Ground-level Ozone. Seventh Interim Report to the European Commission, DG-XI. International Institute for Applied Systems Analysis (IIASA), Austria. January 1999.

Iversen, E. (1999): Status for det europæiske auto/olie-program (Status for the Auto-oil Programme) in Proceedings of "Trafikdage på Aalborg Universitet" (Nordic Traffic Conference, Aalborg, Denmark) 30-31 August 1999. pp. 391-398.

Jensen, S.S. (1992): Køremønstre og luftforurening - i provinsen. Rapport 105. Vejdirektoratet. 75 s. + 56 s. (In Danish. Driving Patterns and Emissions. Danish Road Directorate. Report No. 105. In Danish).

Jensen, S.S. (1995): Driving Patterns and Emissions from Different Types of Roads. The Science of the Total Environment 169. pp. 123-128.

Jensen, S.S. (1997): Standardised Traffic Inputs for Use in the Operational Street Pollution Model (OSPM), NERI Technical Report No. 197, 1997. 54 p.

Jensen, S.S. (1998): Background Concentrations for Use in the Operational Street Pollution Model (OSPM), NERI Technical Report No. 234. 109 p.

Kemp, K. and Palmgren, F. (1999) The Danish Air Quality Monitoring Programme. Annual Report for 1998. National Environmental Research Institute. NERI Technical Report 296, 66 p.

Krawack (1991): Luftforurening fra individuel og kollektiv trafik. Undersøgelse i 4 Københavnske bygader. Udarbejdet for Miljøstyrelsen og Vejdatalaboratoriet. Miljøstyrlesens miljøprojekt nr. 165. 153 s. (Air Pollution From Individual and Public Transportation in Four Copenhagen Streets. Prepared for the Danish EPA and the Danish Road Directorate. Danish EPA Environmental Report No. 165. In Danish).

Larsen, P.B., Larsen, J.C., Fenger, J., Jensen, S.S. (1997): Sundhedsmæssig vurdering af luftforurening fra vejtrafik, Miljøprojekt nr. 352, Miljøstyrelsen. (Evaluation of health impacts of air pollution from road traffic, Danish EPA, Report No. 352. In Danish with English summary).

Municipality of Copenhagen (1997): Trafik- og miljøplan for København, 54 s. (Local Action Plan for Traffic and Environment. In Danish).

Municipality of Copenhagen (1998): Trafikudviklingen i København. Københavns Kommune, 35 s. (Development in Traffic In Copenhagen. In Danish).

Municipality of Copenhagen(1999): Færdselstællinger og andre trafikundersøgelser 1994-1998. Vejafdelingen, Trafikkontoret. 47 s. (Traffic Counts and other Traffic Surveys. In Danish).

Ntziachristos, L., Samaras, Z., Eggleston, S., Gorib en, N., Hassel, D., Hickman, A.-J., Joumard, R., Rijkeboer, R., & Zierock, K.-H. (1999). COPERT III Computer Programme to Calculate Emissions from Road Transport - Methodology and Emission Factors. Final Draft Report. European Environment Agency, July 1999, Copenhagen.

Palmgren, F., Berkowicz, R. , Ziv, A. and Hertel, O. (1999). Emission Estimates from the Actual Car Fleet by Air Quality Measurements in Streets and Street Pollution Models. Presented at the 6th International Conference on Highway and Urban Pollution, 18-21 May 1998, Baveno Italy, The Science of the Total Environment, 235, 101-109.

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Appendix 1:
Emission Data for DEM Model

EMEP and IIASA data

The development in European emissions is based on EMEP data for 1990 and proposed national reductions in 2010 for all European countries under ECE. The national reductions are taking from an analysis by the International Institute for Applied Systems Analysis (IIASA) in Austria that carries out the preparatory work that leads to ECE protocols (IIASA 1999). Emission levels in 1990 and 2010 and reduction factors 1990-2010 are given in Table 1.

Table 1
Emission Levels in 1990 and 2010 and Reductions 1990-2010 (thousand tonnes per year)