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Air quality, Human exposure and Health impact

assessment of air pollution in Ljubljana, Slovenia

R.A. Field, M. Gerboles, P. Perez-Ballesta, I. Nikolova, A. Baeza-Caracena, D. Buzica, R. Connolly, N. Cao, L. Amantini, F. Lagler, N. Stilianakis, V. Forcina and E. De Saeger

(European Commission, Joint Research Centre, Institute for Environment and Sustainability, Emissions and Health Unit, Air Quality and Health Sector, European

Reference Laboratory of Air Pollution)

in collaboration with

P. Otorepec and M. Gregoric

(Institute of Public Health of the Republic of Slovenia)

A. Kobe, N. Kovac, A. Planinsek, D. Cemas and S.Zlebir

(Environmental Agency of the Republic of Slovenia)

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Summary An evaluation of outdoor, indoor air quality and human exposure to air pollutants and their human health effects was carried out in Ljubljana, Slovenia. The assessment was undertaken around 4 complimentary activities: AIRPECO, PEOPLE, APHEIS and air pollution monitoring by the Slovenian network of automatic measuring stations. In the AIRPECO project outdoor measurements of benzene, nitrogen dioxide (NO2), sulphur dioxide (SO2), ozone (O3) were made both in winter and in summer. Ambient concentrations were measured at about 100 sampling sites in order to map the distribution of air pollution over the city. At four sampling sites, concentrations of particulate matter (PM10) and its chemical composition were determined. The PEOPLE project assessed outdoor/indoor air quality and population exposure to benzene. Population exposure measurements focused on the influence of emissions from transport and smoking. Measurements were also made at a range of indoor locations including homes, offices, shops, schools, bars, restaurants and public transport, as well as outdoor locations throughout the city. The APHEIS health impact assessment considered a number of indicators, namely: hospital admissions, mortality and morbidity, associated with exposure to black smoke, PM10 and PM2.5. The influence of abatement strategies for the selected air pollutants for the health indicators was calculated for the population of Ljubljana. Besides its role for compliance with air quality legislation, the Slovenian monitoring network data were used to complement and support the outdoor monitoring for PEOPLE and AIRPECO and to provide the air quality data required for APHEIS.

The summer and winter campaigns indicated that the background sites should be below the European limit values for NO2, SO2 and benzene. However, at hot spot sites, NO2 and benzene exceeded this value. While ozone concentration were only measured for one day the limit value was exceeded in a portion of the area under study. PM10 and B[a]P are, at present conditions, likely to exceed their respective proposed European limit values. In contrast, for heavy metals, exceedances are expected to be unlikely. The outdoor spatial mapping indicated that the current air quality network is sufficient to meet applicable European air quality standards. However, a As, Cd, Ni and B[a]P sampling point should be added to comply with the new European Directive on Heavy metals and PAH. The concentration of PM10, PAH and in particular B[a]P in the PM10 fraction were considerably higher in wither compared to summer. Temperature changed the relative contribution of PAH to PM10 levels by increasing the gas-to-particles coefficient as temperature declines. Such an effect is higher for the more volatile species. Notwithstanding the importance of emission source variation the PAH levels were critically dependent upon ambient temperature, wind speed and precipitation.

While indoor pollution levels are controlled by the external air quality, the presence of indoor sources like smoking can elevate pollution concentrations. The city background benzene concentrations were comparable to measurements for both the human exposure control group and the non-smoking homes group. Citizens that are exposed to indoor emissions such as smoking, or move and work in close proximity to traffic are expected to be exposed to much higher levels of pollutants. Regarding the exposure of the commuting population, the walking and biking categories showed the lowest exposure levels, comparable to city background concentrations. Elevated exposure levels were reported from the car-commuting group. For human exposure the most polluted group was, as expected, the smoking category.

In the APHEIS health impact assessment, the reduction of mortality was highest with the long term reduction of the yearly average of PM10 to 15 µg.m-3 and PM2.5 to 15 µg.m-3. In both cases this scenario reduced the total mortality by 76 deaths. The PM2.5 scenario showed a reduction with mortality due to cardiopulmonary and respiratory diseases decreased by 50 and

8 persons, respectively. This corresponds to 67 and 11 years of expected life lost. For PM10, air pollution peaks up to 40 days were shown to have much larger impact on mortality than reduction scenarios of 1-2 days.

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List of Contents 1. Project description....................................................................................................................7

2. Objectives.................................................................................................................................8

3. Air pollution and human health................................................................................................8

4. Methodology ..........................................................................................................................11

4.1 Measurement campaign strategies (AIRPECO and PEOPLE) ............................................11

4.2 Health Impact Assessment (APHEIS)..................................................................................12

4.3 Ljubljana air quality monitoring network design.................................................................14

5. Results and Discussion...........................................................................................................14

5.1 AIRPECO and PEOPLE ......................................................................................................14

5.1.1 Outdoor pollution levels................................................................................................14

5.1.2 Indoor pollution levels ..................................................................................................23

5.1.3 Human exposure............................................................................................................24

5.1.3 Outliers and data checking ............................................................................................26

5.2 APHEIS................................................................................................................................27

5.2.1 Short term Health Impact Assessment scenarios ..........................................................27

5.2.2 Long term Health Impact Assessment scenarios...............................................................29

5.3 Ljubljana Air Quality Networks...........................................................................................30

5.3.1 Requirements of the European legislation ....................................................................30

5.3.2 Air pollution trend, Data Summary for 2000-2003.......................................................31

6. Conclusions ............................................................................................................................32

7. Acknowledgements ................................................................................................................33

8. References ..............................................................................................................................34

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Health effects and population exposure to air pollution in Ljubljana, Slovenia

1. PROJECT DESCRIPTION In the framework of the enlargement of the European Union (EU), new Members States are required to implement air quality Directives. The Emissions and Health Unit of the Joint Research Centre, in collaboration with the Institute of Public Health and the Environmental Agency of the Republic of Slovenia, carried out an air quality assessment in Ljubljana, Slovenia. The project assessed outdoor, indoor and human exposure to air pollutants as well as the human health impact from air pollution. Figure 1 illustrates the project design.

The assessment was undertaken around 4 complimentary activities: PEOPLE (Population exposure to air pollutants in Europe), AIRPECO (Emission and Air Quality Policy in the PECO Countries), APHEIS (Air Pollution and Health: A European Information System) and Slovenian air quality monitoring networks.

The PEOPLE project assessed outdoor/indoor air quality and population exposure to benzene. Exposure measurements focused on the influence of emissions from transport and smoking. Citizens were invited by the media to participate in the project. Approximately 150 volunteers were chosen according to a selection protocol that created distinct categories that were representative of the lifestyle of the population of the city. Measurements were also made at a range of indoor locations including homes, offices, shops, schools, bars, restaurants and public transport, as well as outdoor locations throughout the city.

In the AIRPECO project outdoor measurements of benzene, nitrogen dioxide (NO2), sulphur dioxide (SO2), ozone (O3) and particulate matter (PM10) were made. Measurements were performed during winter and summer campaigns, each of a fortnight duration. Ambient concentrations were measured at about 100 sampling sites in order to map the distribution of air pollution over the city. At four sampling sites, particulate matter (PM10) were determined by gravimetry. The chemical composition of the particulate matter was investigated from analysis of anions, cations, polycyclic aromatic hydrocarbons (PAH) and heavy metals.

The APHEIS health impact assessment considered a number of indicators, namely: hospital admissions, mortality and morbidity, associated with exposure to air pollution, namely black smoke, PM10 and PM2.5. Cardiovascular disease, respiratory disease and lung cancer were considered in the assessment. The influence of abatement strategies for the selected air pollutants for the health indicators was calculated for the population of Ljubljana.

Besides determining compliance with EU air quality Directives, the Slovenian monitoring network data was used to complement and support the outdoor monitoring for PEOPLE and AIRPECO and to provide the air quality data required for AIHEIS.

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PEO

PLE

APHE

IS

Mon

itorin

gNe

twor

k

AIRP

ECO

Day YearMonth Healthimpact

12 and 24 hoursmeasurements

based on PM10monitoring data

daily and hourlymeasurements

2 weeks,Summer / Wintermeasurements

HumanExposure

Indoor

Outdoor

BenzeneO3

PM10PAHs

Heavy Metalsions

Benzene

Benzene MortalityMorbidity

BenzeneO3,NO2,SO2,

COPM10

BenzeneNO2,SO2

PM10PAHs

Heavy Metalsions

Non Smokers

Smokers

Commuters

Control GroupWalk/Bike

Public TransportPersonal Car

HomesOfficesShools

Bars/RestaurantsShops

Hot SpotsCity BackgroundSuburban Areas

Figure 1: Project measurement strategy.

2. OBJECTIVES By evaluating the spatial distribution of a number of pollutants typical of the urban environment, the project aims to:

• measure the pollution levels with respect to the established air quality standards;

• provide information to optimise the design of the existing air quality monitoring networks;

• assess the relative influence of outdoor and indoor emission sources, smoking, on human exposure to benzene levels;

• calculate the impact of air quality abatement scenarios for particulate matter upon health indicators, including mortality and morbidity, for the population.

3. AIR POLLUTION AND HUMAN HEALTH The impact of air pollution upon human health is dependent, amongst other factors, upon the pollutant considered and the length of exposure. For the ambient air that the population breathes from the surroundings, acceptable limits are set with respect to whether acute (short term) or chronic (long term) exposure is considered. In order to protect human health from the effects of air pollution, EU legislation has established a series of limit values (LV), which are shown in Table 1. These values are of particular importance for the protection of individuals that are sensitive to the influence of air pollutants. Susceptible people include those with pre-

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existing lung, heart or other disease, including asthma, children and the elderly. The main impacts upon human health for these pollutants are briefly summarised below.

The absorption of sulphur dioxide by the nose and upper respiratory tract can impair various respiratory functions. Sulphur dioxide acts as an irritant by stimulating nerves in the lining of the nose, throat and the lung's airways. This causes a reflex cough, irritation, and a feeling of chest tightness, and may lead to narrowing of the airways (EPAQS, 1995). The mechanism by which nitrogen dioxide acts is most probably related to its properties as an oxidising agent which can damage cell membranes and proteins. Short-term exposure can also affect the immune cells of the airways. Nitrogen dioxide causes acute inflammation of the airways that predisposes people to an increased risk of respiratory infections (EPAQS, 1996). High concentrations of ozone can be noticeable as a slight irritation of the eyes and nose. Ozone is a powerful oxidising agent, able to release free oxygen radicals that damage normal tissue. Damage to the airway lining is followed by an inflammatory reaction that has the potential to cause short term respiratory symptoms. Measurable decrements in lung function may occur on exposure to concentrations of ozone greater than about 100 ppb (EPAQS, 1994a).

Table 1: Limit and Target values of EU regulated pollutants

Compound Limit/Target value,

µg.m-3 Reference period Application period

350 1 hour 2005

125 24 hour 2005 Sulphur dioxide

20 1 year 2001

200 (NO2) 1 hour 2010

40 (NO2) 1 year 2010 Nitrogen oxides

30 (NOx) 1 year 2001

Ozone 120 1 year 2010

Carbon Monoxide 10 mg.m-3 8 hour 2010

Benzene 5 1 year 2010

50 24 hour 2005 PM10

40 1 year 2005

Lead 0.5 1 year 2005/2010

Benzo (a) pyrene 1 ng.m-3 1 year 2007

Arsenic 5 ng.m-3 1 year 2007

Cadmium 6 ng.m-3 1 year 2007

Nickel 20 ng.m-3 1 year 2007 Concentrations are expressed at 20 ºC and 101.3 kPa. Lead, B[a]P, As, Cd & Ni are measured in PM10.

Carbon monoxide interfers with the processes whereby oxygen is utilised in the cells in the body. This effect comes from the formation of carboxyhaemoglobin, and also by blocking essential biochemical reactions. At ambient levels the greatest concern is for the possible effects on the heart and on the brain, since these two organs are crucially dependent upon a high rate of oxygen. Levels of carboxyhaemoglobin of 3-4% shorten duration of exercise needed to induce changes in the electrocardiogram record and to induce angina pain. Studies of brain function in volunteers exposed to carbon monoxide have shown subtle changes when

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carboxyhaemoblogin levels exceed about 5% (EPAQS, 1994b). Benzene is readily absorbed into the body when breathed into the lungs, about half of it being retained. It is distributed in the body to fatty tissues including the brain and the bone marrow where blood cells are made. The effect of long-term exposure to benzene is of most concern for non-lymphocytic leukaemias. Benzene acts on the genetic material of the cells with a genotoxic action that is generally taken to indicate that the possibility of it causing malignant disease exists even with very small exposures. While this could be strictly interpreted as meaning that there is no safe concentration to which people can be exposed, a realistic view is that the risks become increasingly small as the cumulative exposure of an individual is reduced and that, for all practical purposes, there is a concentration at which the risks are exceedingly small and unlikely to be detectable by any practicable method (EPAQS, 1994c). The risk of non-lymphocytic leukaemia, in the form of acute myeloid leukaemia, is increased substantially in cigarette smokers, the risk of this disease is almost doubled in those who smoke 20 cigarettes daily. This effect of smoking is not related to benzene alone, but to the mixture of carcinogens found in cigarette smoke. Benzene is classed as a carcinogenic compound and a risk level established by the World Health Organisation ranges between 3.8 and 7.5 cases of myeloid leukaemia per one million people exposed during lifetime to 1 µg.m-3 of benzene (WHO, 2000).

Particles are often measured as the mass of the fraction that is considered most likely to be deposited in the lung. These particles are called PM10 (particulate matter which passes through a size-selective inlet with a 50 % efficiency cut-off at 10 µm aerodynamic diameter) and are considered more important than coarser matter. Particles exert their effects by causing oxidative stress which leads to inflammation. This drives the respiratory and cardiovascular effects. In the case of ultrafine particles, this may include systemic effects from direct transfer into the vascular system. The mechanistic link to cancer is less clear. There is considerable evidence for adverse human health effects associated with both acute, short term (days), and chronic, long term (many years) exposure to ambient PM10 (COMEAP, 1998; WHO, 2000; EPAQS, 2001; WHO, 2003; USEPA, 2004). Health effects include respiratory morbidity and mortality, cardiovascular morbidity and mortality, and cancer. Quantitative estimation of health impacts from exposure to PM10 assumes linearity in the relationship between exposure and responses. It is also not possible to discern whether there is a threshold particle concentration below which there are no adverse effects on health for the whole population. Estimates of population exposure-response relationships indicate that deaths are brought forward, and hospital admissions due to respiratory disorders are either brought forward or additionally caused. Epidemiology has consistently demonstrated an association between adverse health effects and PM10. A World Health Organisation (WHO) meta-analysis of 33 time-series studies in Europe gives an increase in total mortality effect estimate of 0.6 % (95 % CI: 0.4-0.8 %) for a 10 µg.m-3 increase in daily PM10 (WHO, 2004). The corresponding values for respiratory and cardiovascular deaths are 1.3 % (0.5–2.0 %) and 0.9 % (0.5–1.3 %), respectively.

Ambient PM10 is physically and chemically diverse. Carbon and organic compounds are major constituents of combustion-generated particles and these, together with secondary organic aerosol, comprise a substantial proportion of PM10. The balance of evidence overall suggests that it is combustion-derived components of PM10, which are comprised predominantly of fine and ultrafine particles that may be metal and PAH (and other organic compound) enriched, that are most responsible for harmful health effects. PAH and their oxy- and nitro-derivatives, are known to exert inflammatory and mutagenic and carcinogenic effects.

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Most gentoxic carcinogenic PAH occur almost exclusively in the particulate phase. It is known that PAH are rapidly absorbed and can be activated in the lung (IARC, 1983). The International Agency for Research on Cancer has classified three potent animal carcinogens benzo[a]pyrene, benz[a]anthracene and dibenz[ah]anthracene as classified as 'probably carcinogenic to humans'. Moreover, benzo[b]fluoranthene, Benzo[k]fluoranthene, Indeno[123cd]pyrene are classified as 'possibly carcinogenic to humans'. The unit risk level as a carcinogen of a lifetimes exposure to a mixture of PAH represented by 1 ng.m-3 benzo(a)pyrene (B[a]P) is estimated by the WHO to be 87 cases per one million people (EC, 2001).

Heavy metals are known to negatively affect human health. The species differ considerably in respect to their toxicity, carcinogenic potency and uptake mechanisms. The unit risk level as a carcinogen of a lifetime exposure to 1 ng.m-3 of arsenic is estimated by the World Health Organisation to be 1.5 cases per one million people. The corresponding value for nickel is 1.8 cases. For cadmium the WHO does not consider epidemiological evidence suitable for risk assessment. Once absorbed some lead accumulates in blood. It is this fraction that is biologically active and leads to harmful effects. The toxic effects are a consequence of its ability to inhibit the actions of certain enzymes and to damage chemicals in the nuclei of cells. Lead is associated with a number of health effects but the most substantial evidence of the effect of low levels of lead on health relates to effects on the central nervous system and, in particular, on the developing brain of children (EPAQS, 1998).

4. METHODOLOGY

4.1 MEASUREMENT CAMPAIGN STRATEGIES (AIRPECO AND

PEOPLE)

Vapour and gaseous pollutants were measured using commercially available diffusive samplers (Perkin Elmer for fortnightly benzene measurements; Radiello for 12 and 24 hr. benzene and 8 hr. ozone measurements and Palmes tubes for fortnightly NO2 and SO2 measurements). The diffusive sampling techniques used in this study have been evaluated under laboratory conditions with the control of factors including humidity, temperature, wind velocity and pollutant concentration level (Baldan et al. 1999, Gerboles et al. 2002, Gerboles et al. 2005). Particulate matter (PM10 fraction) was sampled using PM10 sequential samplers. Different techniques were used for the determination and quantification of the pollutants reported. Benzene was analysed by thermal desorption gas chromatography. Ozone was analysed by UV/Visible spectrometry and nitrogen doxide and sulphur dioxide were analysed by ion-chromatography. After quantification of the PM10 filter by gravimetry, PAHs were analysed by HPLC and fluorescence detection. Heavy metals were determined by polarography and ICP-MS, while anions and cations analysis utilized ion chromatography.

The AIRPECO study area covered about 120 km² with 92 sampling sites for NO2/SO2 while for benzene 48 sites were used covering a smaller area that encompassed the city centre.

The study area was divided in different zones according to the following criteria:

• Urban areas: a homogeneous grid with meshes of about 0.76 km²; 34 sites for both NO2/SO2 and benzene;

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• Suburban areas: a homogeneous grid with meshes of about 1.52 km²; 41 sites for NO2/SO2 and 7 sites for benzene;

• Hot spot locations: sites selected according to emission sources with preference to city centre locations; 10 sites for NO2/SO2 and 6 sites for benzene;

• Rural locations: sites selected around the city in a symmetrical manner; 7 sites for NO2/SO2.

The sampling sites were randomly distributed covering each defined zone (see Figure 3, Figure 4 and Figure 6).

The summer sampling campaign for benzene and NO2/SO2 was carried out from 20th May to 3rd June 2003, while during the winter sampling was from 10th to 23rd February 2004. Samplers were installed in protective boxes placed on lamp-posts at a height of 3 m high in order to avoid sampler losses by vandalism (see Figure 2).

Ozone samplers were installed in concentric circles around the city (see Figure 5). The sampling was carried on 16th July 2004, for 8 hours from 10:00 to 18:00. PM10 sequential samplers were installed at four urban background sites (see position in Figure 3, Figure 4 and Figure 6), operating from 20th May to 3rd June 2003 (summer campaign) and from 10th to 24th February 2004 (winter campaign). From the filters used for determination of PM10, PAH, heavy metals and anion/cation compositions were quantified.

AIRPECO : Radiello Radiello shelter

AIRPECO : Perkin Elmer tube for benzene

AIRPECO : Palmes diffusive tubes for Noand SO

2

2

PEOPLE : Radiello sampler for benzene

sampler for NO and S2 O2

Figure 2: Protective box with diffusive samplers for benzene, NO2 and SO2 On 27th May 2003 the human exposure campaign was carried out, involving approximately 150 citizens from Ljubljana. They were selected according to well-defined criteria, as a function of their specific activities:

• Control group (non-smoking citizens not directly exposed to transport sources);

• Smokers;

• Commuters: walk, bike, car, bus or mixed transport.

Volunteers carried a sensor for 12 hours to measure their personal exposure to benzene. Measurements were also performed for 24 hours over a wide range of indoor locations, such as homes, offices, shops, schools, bars and restaurants. Outdoor measurements were further performed in a limited number of outdoor urban sites.

4.2 HEALTH IMPACT ASSESSMENT (APHEIS)

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The health impact assessment (HIA) used three pollutants, namely black smoke (BS), PM10 and PM2.5 (Medina, 2002). The year 2000 was selected as the base year from which projections were made. Measurements from the Slovenian Air Quality network background sites were used to provide baseline data. Since PM2.5 was not monitored its level was estimated from PM10 data. This network data was considered to be equal to the level of exposure of the general population.

The impact of population exposure to air pollution, considered as a primary indicator, attributed deaths per year. This can be termed as total premature mortality or all causes mortality. This term excludes accidents and violent death but includes cardiovascular and respiratory mortality. The latter two forms of death, along with lung cancer, are known to be related to air pollution and as such were also considered separately. Another primary indicator, besides mortality, was hospital admissions. Two main approaches for the health impact assessment were adopted namely short term or long term.

Short term assessments refer to the impact of acute exposure whereas long term is chronic exposure. The short term assessment used one of two exposure response functions; acute exposure (1 or 2 days, ST) or cumulative acute exposure (up to 40 days, DL). Long term (LT) assessments refer to the mortality cases over one year. The further step of calculating increase of life expectancy was also possible for PM2.5.

For both short and long term assessments a number of key scenarios were set. This ensured a common approach and thereby consistency with other APHEIS city assessments. The general scenarios applied are given in Table 2.

These short term scenarios used the following indicators: • All causes mortality, • Cardiovascular mortality, • Respiratory mortality, • Hospital admissions (Cardiac and Respiratory).

The long term scenario for PM10 used the following indicator:

• All causes mortality.

The long term scenario for PM2.5 used the following indicator: • All causes mortality, • Cardiopulmonary mortality, • Lung cancer mortality.

Furthermore an assessment of years of life lost for the population of over 30 years of age was also included for PM2.5. This assessment used the same indicators as given above.

Table 2: Scenarios for the APHEIS Health Impact Assessment in Ljubljana

Senarios Term Pollutant

reduction of 24-hour values to 50 µg.m-3 ST, DL BS, PM10

reduction of 24-hour values to 20 µg.m-3 ST, DL BS, PM10

reduction of 24-hour values by 5 µg.m-3 ST, DL BS, PM10

reduction of 24-hour values to 40 µg.m-3 LT PM10

reduction of 24-hour values to 20 µg.m-3 LT PM10

reduction of 24-hour values by 5 µg.m-3 LT PM10

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reduction of 24-hour values to 20 µg.m-3 LT PM2.5

reduction of 24-hour values to 15 µg.m-3 LT PM2.5

reduction of 24-hour values by 3.5 µg.m-3 LT PM2.5

ST = short term, DL = cumulative acute, LT = long term add DL

4.3 LJUBLJANA AIR QUALITY MONITORING NETWORK DESIGN

The national air quality monitoring network is managed by the Environmental Agency of the Republic of Slovenia, while a complementary network is managed by the city of Ljubljana. The automatic air quality monitoring network consists of 10 different field sampling sites spread all over Slovenia and one mobile station. Two fixed stations are located in Ljubljana and at the time of the measuring campaigns, the mobile station was also operating in the city. The station in Bežigrad is classified as urban background within a residential/commercial district. The Station in Figoveč ARSO is also classified as an urban background site however it is situated in the city centre. The mobile station was placed near a busy main street and as such was a hot spot site.

The monitoring station of the City of Ljubljana consists of two stations, one traffic oriented station (Figoveč) placed in the city centre and one rural station (Vnajnarje) used to monitor air pollution due to emission from larger point sources. Further information on these monitoring stations are given in Table 3.

Table 3: Structure of the monitoring networks in Ljubljana Stations Area

Type

Place Type Area characteristic

Elevation SO2 O3 NOx PM BTX CO meteo.

Bežigrad Urban Background RC 298 m x x x x x x x Figoveč

ARSO

Urban Background RC 298 m x

AR

SO

Mobile station

Urban Traffic RC 298 m x x x x x x x

Figoveč Urban Traffic RC 298 m x x x x x x

City

Vnajnarje Regional Industrial Agricultural 630 m x x x x x BTX = benzene, toluene and xylenes, Meteo. = meteorological data, RC = residential/commercial

5. RESULTS AND DISCUSSION

5.1 AIRPECO AND PEOPLE

5.1.1 Outdoor pollution levels The spatial distribution of the monitored pollutants in the urban area, were determined using Universal Krigging method of interpolation (Clark and Harper, 2000). The annual average values for both benzene and NO2 were obtained by normalizing the average value calculated over the two sampling periods to the annual time series of the Bežigrad and Figoveč automatic monitoring stations. During the winter campaign the average ratio was 1.2 ± 0.05

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(winter/annual average), whilst in the summer campaign the ratio was 0.85 ± 0.05 (summer/annual average). These ratios were also applicable to SO2, benzene and CO.

The distribution of benzene concentration over the city of Ljubljana in summer (see Figure 3) shows, that apart from one hot spot with 6 µg.m-3, the benzene concentration was lower than the yearly average value of 5 µg⋅m-3 limit set by Directive 2000/69/EC to be met in 2010. In summer, the average two-week background concentrations ranged from 1.5 to 2 µg.m-3. The median corresponding background concentration of benzene on the day of the PEOPLE campaign (27 may 03) was 3.1 µg.m-3. In winter (see Figure 3), benzene concentrations were higher than in summer, in particular in the city centre and in the northern part of the ring road and towards the motorway coming from Austria where the limit value is exceeded in the surrounding areas. The majority of the hot spot sites also breaches the limit value with values approaching 10 µg.m-3. Winter benzene concentrations exceed those of summer due to the influence of temperature inversions. In these conditions emissions are dispersed into a mixing layer of reduced height. One such episode occurred during the two-week sampling campaign. Nevertheless, the annual average distribution (see Figure 3) indicates that the benzene limit value is unlikely to be exceeded at the background sites. However hot spot sites (close to traffic) in the city centre are consistently exceeding the limit value.

The NO2 concentrations in summer (see Figure 4) were lower than the annual LV 40 µg.m-3 apart from at the hot spot sites. The NO2 concentration was higher in the inner part of the city delimited by the ring road and the motorways coming from Austria and Italy, excluding the two elevated and rural areas in the west and south-east of the city. The same distribution was also evident in winter. However the winter background NO2 concentrations were higher, with the city centre breaching the limit value. The concentrations of NO2 at hot spot sites nearly always exceeded the limit value in both summer and winter. The annual average distribution indicates that the NO2 limit value is, however, unlikely to be exceeded at the background sites.

Figure 5 shows the distribution of ozone concentration over the city of Ljubljana on 16 July 2003. The 8-hours LV of 120 µg.m-3 is only exceeded in the northern part of the city. The absence of ozone reduction in the city centre can be explained by the low levels of reductive agents, in particular nitrogen oxide (NO). With NO levels as low as 1 µg.m-3 titration of ozone is limited through photochemical processes. City centre ozone values remained above 100 µg.m-3. The slight increase of ozone (upwind direction) in the northern part of the city is probably due to the influence of the ozone precursors from the city.

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a

b

Figu24 FThenum

c

re 3: Benzene concentration levels in Ljubljana. a) : Summer (20 May- 03 June 03); b) : Winter (10- ebruary 04); c) : Annual average. F and B indicate the location of the automatic monitoring stations. numbers in blue circles correspond to the concentrations measured at hot spots. The rhomboidal bers show the positions for the PM10 sampling sites.

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a

b

FiguFebThenum

c

re 4: NO2 concentration levels in Ljubljana. a) : Summer (20 May- 03 June 03); b) : Winter (10- 24 ruary 04); c) : Annual average. F and B indicate the location of the automatic monitoring networks. numbers in blue circles correspond to the concentrations measured at hot spots. The rhomboidal bers show the positions for the PM10 sampling sites

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Figure 5: Ozone concentration levels in Ljubljana on 16 July ’03 from 10:00 to 18:00. The positions of the sampling sites are shown with blue dots

Figure 6: SO2 concentration levels in Ljubljana (10-24 February 2004)

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The distribution of SO2 in winter is presented in Figure 6. The concentrations are, in general, lower than 20 µg.m-3. Areas of significantly elevated SO2 concentrations in the city were not evident, indicating that neither traffic nor central heating systems were important emission sources for this pollutant. Indeed, a trend of decreasing concentration of SO2 was detected from the South East to the North West direction, i.e. following the predominant wind direction for that period. This suggests that emissions of SO2 may come from a region to the

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Benzo[a]pyrenePM10PM10 OCESNA KLINICAPM10 GIMNAZIJA SENTVIDPM10 GIMNAZJA VIC

PRIVAT

igure 7: Trend of PM10 and B[a]P measured at 4 sampling sites during summer and winter campaigns

uring the winter campaign, up to 7 days exceeding 50 µg.m-3 (LV) of PM10 were observed at ne of the 4 monitoring sites, while none was registered during the summer campaign (see igure 7). EC legislation will allow only 7 ‘exceedances for daily measurements in 2010.

rom Figure 7, it can be noted that the PM10 measurement values determined at the 4 sampling ites were very similar with an average relative standard deviation (RSD) of about 6% in ummer and 9 % in winter.

olycyclic aromatic hydrocarbons were measured on PM10 filters during summer and winter ampaigns. Figure 7 illustrates the B[a]P trend during both periods with the corresponding M10 measurements. During the winter period, B[a]P concentration was usually higher than

he annual LV of the Directive (2004/107/EC). PAHs concentrations were higher in winter han in summer by an order of magnitude as illustrated in Figure 8.

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Figure 8: Concentrations of PAH during summer and winter campaign

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Figure 9: Fraction of B[a]P in the PM10 fraction versus ambient temperature

Apart of the obvious increase of emissions due to heating systems during winter season (70 % Road and 30 % Heating); the winter campaign was characterised by a period of temperature inversion and high stability, which increased the pollution level. Furthermore, the lower temperature increased the condensation of volatiles on the particulate matter. This effect can

20

be observed in Figure 9, where the decimal logarithmic of the ratio B[a]P/PM10 is represented with respect to the temperature recorded during both campaigns.

Additionally, the influence of temperature is highlighted for all PAH in Figure 10 where the different relative contributions of “light” and “heavy” PAHs are contrasted.

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Figure 10: Relative percentage of PAH in the PM10 fraction of particulate matter.

As a consequence the concentrations of PAH in the particulate matter are not always proportional to the level of PM10. The levels of PAH in the particulate matter depend on the source and fate of the particulate matter. PAHs concentrations change from day to day. An assessment of meteorological parameters (see annex I) reveals the importance of wind speed and precipitation to the variation of measured concentrations. During winter campaign, the heaviest PAHs decrease in the particulate fraction (12, 13, 19, 20 and 21 of February).

In summer conditions, lower concentrations of PAH in PM10 fraction corresponded to rainy (20 and 26 of May) or windy conditions (31 May and 1 June). The importance of meteorological conditions to the behaviour of PM10 particulate fraction of PAH is also highlighted in Figure 11, where the ratio NO3

-/SO42- versus the concentration of

Benzo[ghi]Perylene, B[ghi]P, in PM10 as one per thousand (‰) is represented. It is expected that the concentration of B[ghi]P in PM10 increases with higher NO3

-/SO42- ratios. Deviations

from this trend implie changes in meteorological conditions or emission sources. A careful assessment of the prevalent conditions reveals that the days of February 12th and 19th, corresponded to relatively high solar radiation. This condition produced an increase in NO2 and consequently an increase in the percent contribution of nitrate in the particulate matter. During the 23rd and 24th February snow falls reduced the content of nitrate in the particulate matter.

21

Table 4: Percentage of ions in the PM10 fraction during the winter campaign

Nitrate sulphate Amonium sea salt Average 14.6 9.0 8.3 4.0Min 7.3 4.2 1.2 2.4Max 24.8 14.2 42.3 7.2

The trend of anions/cations in PM10 for the winter campaign is shown in Figure 12. Ca2+, sea salt (NaCl) and non-sea salt SO4

2- are indicative of the coarse fractions, while ammonium and nitrate are more linked to the fine fractions. As shows Table 4, the average values are typical of urban background levels (Van Dingenen, 2004).

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igure 11: Relative percentage of PAH (B[ghi]P) in the PM10 fraction of particulate matter. enzo[g,h,i]perylene versus ratio NO3

-/SO42-.

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Figure 12: Trend of ions during the winter campaign

Heavy metals contained in PM10 were determined on two heavily loaded PM10 filters placed in Ocensa klinika between 14 to 15 February and between 17 to 18 February. The results for heavy metals are given on Table 5. The concentration of lead in PM10 measured in Ljubljana was only 10 % of the LV defined in the 1st European Daughter Directive (1999). The concentration of Cd and Ni was lower than the proposed LV in the 4th European daughter Directive (2004) for heavy metals and PAH (see Table 1) by a factor 6 and 2, respectively.

Table 5: Analysis of heavy metals in ng/m-3 in Ocensa klinika on two different days

14 to 15 Feb 17 to 18 Feb

Fe 1207 2511Ni 12 10Cu 42 62Zn 101 120Rh < 0.2 < 0.2Cd 1 0.6Pt < 0.2 < 0.2Pb 52 26

5.1.2 Indoor pollution levels Benzene levels were measured in a number of typical indoor locations and compared in terms of median value. Measurements at these sites are important as, in general, people are known to spend most of their day indoors (Figure 13).

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Homes The benzene concentrations were similar to the city background levels in 21 houses of non-smoking sedentary citizens (control group) (median value of 2.2 µg⋅m-3), confirming that when indoor sources were not present the outdoor levels controlled the measured concentrations at these locations.

Schools, restaurants and offices The median levels of benzene (2.5 µg⋅m-3, 2.9 µg⋅m-3 and 3.4 µg⋅m-3 respectively) were similar to city background measurements. Emission sources of benzene for in these schools, restaurants and offices were not identified.

Shops and bars In 5 bars and 10 shops, where tobacco smoke could be present, the benzene concentration was higher (median values of 5.1 µg⋅m-3and 3.8 µg⋅m-3) than in other sites sampled indoors.

BENZENE CONCENTRATIONS IN LJUBLJANA ENVIRONMENTS

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Figure 13: Indoor pollution levels for Ljubljana PEOPLE project (27 May 2003)

5.1.3 Human exposure The personal exposure measurements of benzene represent the average concentrations to which citizens were exposed during a twelve hour daytime period that included the transit to and from work. Exposure to benzene is anticipated to be related to a person’s life style and the types of environments they encounter. The main factors that affect benzene exposure for urban populations are the presence of tobacco smoke and exposure to transport emissions. The former is important in terms of both personal behaviour and the presence of environmental tobacco smoke. The latter is important to consider in terms of the time of travelling. Exposure to rush hour traffic can be expected to elevate exposure to traffic emissions (Figure 14).

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BENZENE PERSONAL CONCENTRATIONS IN LJUBLJANA

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Figure 14: Personal exposure levels for Ljubljana PEOPLE project (27 May 2003)

Control group The 21 non-smoking sedentary citizens, who acted as control group in the study, yielded the lowest levels of exposure (median value of 2.7 µg⋅m-3). These values were in close agreement with corresponding measurements from inside their homes (see Figure 15). This was expected as not only did these volunteers not commute to or from work but they also spent practically all of the sampling period inside their homes where emission sources were expected to be absent. The limited time they did spend outside was walking. To be included in the control group, time spent outdoors was limited to no more than an hour and was usually less, thus reducing any bias that may be caused by proximity to emissions from traffic.

Smokers Smokers were the most polluted class of citizens, exhibiting a median value of 5.7 µg⋅m-3 in a sample of 18 persons. The strong variation in concentration levels can be expected to depend on a number of factors including the number of cigarettes smoked and the confinement space (e.g. indoor, outdoor). In this sample set, an average number of 9 cigarettes were smoked during sampling. The highest exposed smokers were those that travelled by car.

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It should be understood that the exposure value of benzene determined for smokers corresponds to their surrounding area, not to inhaled concentrations that can be expected to be

higher.

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Figure 15: Indoor home concentrations versus human exposure control group

Commuters In situations with the absence of smoking or other indoor pollution sources, commuting is the main factor affecting personal exposure in cities where the main emission source is traffic. Amongst the categories of commuters, car users were the most exposed group (24 volunteers with a median value of 5.0 µg⋅m-3). The level decreased when the mode of transport changed. People that used mixed transport and travelled by bus and car (15 persons with a median value of 4.4 µg⋅m-3) were more exposed than those that travelled only by bus (6 persons with a median value of 4.0 µg⋅m-3). The walk and bicycle categories had the lowest levels of exposure (8 walkers and 11 bikers with median values of 3.6 µg⋅m-3and 3.1µg⋅m-3 respectively). These categories also had the lowest average daily commuting time of 80 minutes, 20 minutes less than those who travelled by bus or car.

5.1.3 Outliers and data checking A number of outliers were removed from the data set that is presented. These were excluded using standard statistical techniques and as such were not representative of the group that they formerly represented. The data were indicated by either Leverage and/or Cook exclusion (Anderson, 1984). The values and groups from which they were removed are given in Table 6.

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Table 6: Outliers excluded as such they were not representative of their groups

Category Nº. of outliers Benzene(µg.m-3) * Bus commuter 2 60, 30 Car commuter 5 81, 68, 47, 35, 27 Mixed transport commuter 2 44, 16 Office 2 120, 51

* Values above 75 were extrapolated from the calibration line and as such should be considered as estimates.

It is clear that while the results presented in Figure 13 and Figure 14 are representative of typical conditions, there are occasions when individuals or locations can become highly polluted. While these outliers are not considered in the results they are valid measurements in terms of analytical procedures.

5.2 APHEIS

Daily mean levels for year 2000 in Ljubljana were as follows:

- daily mean levels (SD) of BS were 15.3 µg.m-3

- daily mean levels (SD) of PM10 were 31.5 µg.m-3

- daily mean levels (SD) of PM2.5 were 22.1 µg.m-3 (estimated as 70% of PM10 value).

5.2.1 Short term Health Impact Assessment scenarios

Black Smoke Figure 16 illustrates the anticipated impact of the reducing BS concentrations to 50 µg.m-3, 20 µg.m-3, or by 5 µg.m-3 for mortality indicators. In all three scenarios the number of cases of mortality is, as anticipated, highest for all causes mortality, followed by cardiovascular mortality and then respiratory mortality. The highest reduction of mortality is predicted for the scenario that envisages a reduction of all the 24-hour values by 5 µg.m-3. In this scenario a reduction of all causes mortality of 3 persons per year per 100,000 inhabitants is calculated. As expected reduction of the annual mean levels of BS to 20 µg.m-3 yields greater influence upon mortality than reduction to 50 µg.m-3 with all causes mortality reduced by 2 persons compared to 1 person per year per 100,000 inhabitants. Hospital data for both cardiac and respiratory admissions follow the same trends as for the mortality data. Again the highest impact is for the reduction of all the 24-hour values by 5 µg.m-3 with a reduction of 13 cardiac and 3 respiratory admissions, respectively. Also the reduction of the annual mean levels of BS to 20 µg.m-3 yields greater influence than reduction to 50 µg.m-3.

27

gerboles

It is clear that while the results presented in Figure 3 are representative of typical conditions when individuals or locations can become highly polluted. It should be noted that most of these outliers are valid measurements in terms of analytical procedures.

Figure 16: Black smoke: reductions to 50-20-by 5 µg.m-3. Short-term health impact on total* and specific mortality. * Cardiac (ICD9 390-429) and respiratory hospital admissions (ICD9 460-519). ** Black smoke data for 2000, hospital admissions data for 2000.

PM10 Figure 17 illustrates the anticipated impact of the reducing PM10 concentrations; to 50 µg.m-3, 20 µg.m-3, or by 5 µg.m-3 for mortality indicators. In all three scenarios the number of cases of mortality is, as anticipated, highest for all causes mortality, followed by cardiovascular mortality and then respiratory mortality. The highest reduction of mortality is predicted for the senario that envisages a reduction annual mean levels of PM10 levels to 30 µg.m-3. In this senario a reduction of cardiovascular and respiratory mortality per year per 100,000 inhabitants are calculated as 5 and 1 cases, respectively for short term exposure. For cumulative exposure the corresponding values are calculated as 6 cases for cardiovascular and 4 cases for respiratory mortality. As expected reduction of the annual mean levels of PM10 to 50 µg.m-3 yields less influence upon mortality than reduction to 30 µg.m-3 with for example short term cardiovascular mortality only reduced by 1 person per year per 100,000 inhabitants. Reduction by 5 µg.m-3 is relatively less significant for PM10 compared to BS due to the higher ambient levels of PM10. Hospital data for both cardiac and respiratory admissions follow the same trends as for the mortality data. Again the highest impact is for the reduction of the annual mean levels of PM10 to 20 µg.m-3 with a reduction of 30 cardiac and 20 respiratory admissions, respectively. Also the reduction of all the 24-hour values by 5 µg.m-3 yields greater influence than the reduction of annual mean levels to 50 µg.m-3.

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Figure 17: PM10: Reductions to 50/40-20-by 5 µg.m-3. Short term (ST), cumulative (DL), long term (LT) health impact on all causes mortality (ICD 9 <800)* and on specific mortality**. * Cardiovascular mortality (ICD9 390-459), respiratory mortality (ICD9 460-519). ** PM10 data for 2000, mortality data for 2000.

5.2.2 LONG TERM HEALTH IMPACT ASSESSMENT SCENARIOS

PM10 For all causes mortality the anticipated impact of the reducing PM10 concentrations; to 40 µg.m-3, 20 µg.m-3, or by 5 µg.m-3 is calculated as approximately 5, 75 and 20 cases respectively.

PM2.5

Figure 18 illustrates the anticipated impact of the reducing PM2.5 concentrations; to 20 µg.m-3, 15 µg.m-3, or by 3.5 µg.m-3 for mortality indicators. In all three senarios the number of cases

29

of mortality is, as anticipated, highest for all causes mortality, followed by cardiopulmonary mortality and then respiratory mortality. The highest reduction of mortality is predicted for the senario that envisages a reduction of annual mean levels of PM2.5 to 15 µg.m-3.

In this senario a reduction of all causes mortality of 76 persons per year per 100,000 inhabitants is calculated. The corresponding values for cardiopulmonary and lung cancer mortality were 50 and 8 cases, respectively. As expected reduction of the annual mean levels of PM2.5 to 20 µg.m-3 yields less influence upon mortality than reduction to 15 µg.m-3. Reducing of all the 24-hour values by 3.5 µg.m-3 yields the least influence upon the mortality indicators. An assessment of years of life lost for the population of over 30 years of age revealed trends similar to that for the health impact assessment. The greatest impact is given by the reduction of annual mean levels of PM2.5 to 15 µg.m-3 with a mean expected gain in life expectancy of 0.63 years for a person of 30 years of age.

Figure 18: PM2.5: reductions to 20-15-by 3.5 µg.m-3. Long-term health impact on total and specific mortality**. for selected abatement scenarios. * All causes mortality (ICD9 0-999), cardiopulmonary mortality (ICD9 401-440 and 460-519), lung cancer mortality (ICD9 162). ** PM2,5 data for 2000, mortality data for 2000

5.3 LJUBLJANA AIR QUALITY NETWORKS

5.3.1 Requirements of the European legislation Ljubljana falls in the category of cities between 250,000 and 500,000 inhabitants. The annex VII of the 1st daughter Directive and annex V of the 2nd daughter Directive states that for this type of city, a minimum of 2 stations (one urban background and one traffic-oriented) are required for the monitoring of NO2, PM10 and benzene because the upper assessment threshold is exceeded. As for SO2 and lead, it is likely that the lower assessment threshold is not exceeded; only one station would be mandatory for these pollutants.

Annex V of the ozone Directive (2002) states that one suburban station is necessary for monitoring ozone in an agglomeration. Additionally, one rural station is recommended for the area outside the city.

30

In the new Directive about heavy metals and PAH (Directive, 2004), it is foreseen that in agglomeration of less than 750 000 inhabitants, at least one sampling point is used for the monitoring of the annual average concentration of As, Cd, Ni and B[a]P. The network is missing such a sampling point.

5.3.2 Air pollution trend, Data Summary for 2000-2003 The trend of air pollution for Ljubljana (monitoring station of Bežigrad) is given in Figure 19. NO2 air pollution levels generally continue to slowly fall in Ljubljana. The SO2 concentrations have declined significantly up to 2000 when a baseline value was reached (Otorepec and Gale, 2004). The central heating plant has reduced SO2 emissions with the use of higher quality coal and the introduction of a sophisticated cleaning system (Otorepec and Gale, 2004). This is shown by the profile of SO2 concentration over the last 10 years (see Figure 19). The annual daily mean level of BS has also been decreasing in the same manner during the last 10 years and has probably reached a baseline level of 15 µg.m-3 (Otorepec and Gale, 2004). The annual daily mean level of PM10 was 35,7 µg.m-3 in 1999 and remained at a similar level (32 µg.m-3) between 2000 and 2002. Ozone does not show any significant decrease during the last 10 years.

Most of the large industrial emission sources are already controlled in Ljubljana. Transportation is still the main source of air pollution in the city. No major changes regarding the sources of pollution are expected in the coming years. This trend of air pollution suggests that the findings of the APHEIS study are still applicable today.

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6. CONCLUSIONS • The summer and winter campaigns indicate that the background sites should be below

the limit values for NO2, SO2 and benzene. However hot spot sites are anticipated to exceed this value for NO2 and benzene.

• For heavy metals included in the 4th air quality directive, exceedances are expected to be unlikely. In contrast PM10 and B[a]P are, at present conditions, likely to exceed their respective proposed limit values. This suggests that an action plan in view of the abbatment of PM10 is needed to decrease the number of possible “exceedances”.

• The concentrations of SO2 have reached stability since 2000 after the significant decrease in the nineties. On the contrary, the general trend of NO2 is a steady and moderate decline. Ozone concentrations have appeared relatively stable since 1990. PM10 concentrations have only been reported for 4 years so trend cannot be determined.

• In spatial terms the lowest variation of concentration was evident for PM10, indicating the importance of regional transport to city background concentrations. A similar behaviour was apparent for ozone. While ozone concentration were only measured for one day the limit value was exceeded in a portion of the area under study.

• With the exception of ozone, winter levels exceeded those measured in summer, in particular for B[a]P.

• The level of B[a]P in the PM10 fraction of the particulate phase was, as expected, highly dependent upon ambient temperature. This effect changes the relative contribution of PAH to PM10 levels and is dependent on a species to species basis upon the mass. Lighter species are more affected than heavier ones.

• Notwithstanding the importance of emission source variation the PAH levels were critically dependent upon meteorological conditions. Ambient temperature, wind speed and precipitation changes accounted for differences in the range of an order of magnitude.

• The ratio of B(ghi)P to (nitrate/sulphate) was used to indicate the influence of either meteorological or emission source changes upon a stable emission source matrix dominated by traffic.

• The current air quality network is sufficient to meet current air quality standards for benzene, NO2 and SO2. However a new monitoring site must be set up for heavy metals and B[a]P by 2007. It is recommended that a further rural O3 station is implemented to ensure compliance with the European legislation.

• While indoor pollution levels are controlled by the external air quality it is clear that the presence of indoor sources like smoking can elevate pollution concentrations. This factor was evident for a number of individual sites but is highlighted in this project by bar locations. This is expected in due to the influence of tobacco smoke.

• The city background benzene concentrations were comparable to measurements for both the human exposure control group and the non smoking homes group. The urban background levels appear to be a good representation of the level for the human exposure control group. Citizens that are exposed to indoor emissions such as smoking, or move and work in close proximity to traffic (hot spots and busy traffic roads) are expected to be exposed to much higher levels of pollutants.

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• Regarding the exposure of the commuting population, the walking and biking categories showed the lowest exposure levels, comparable to city background concentrations. Elevated exposure levels were reported from the car commuting group. For human exposure the most polluted group was, as expected, the smoking category.

• The removal of a number of outliers from the graphical results for indoor and in particular human exposure data-set show that some measurements deviate from normal behaviour. Further analysis of the movement diaries from individuals whose measurements were identified as outliers could not always explain the elevated concentrations. In these cases either the presence of unknown sources or unusual proximity to known sources are possible explanations of elevated exposure levels.

• For the short term health impact assessments of black smoke the highest level of reduced mortality is with reduction of levels by 5 µg.m-3 since ambient levels are relatively low for the baseline condition.

• For the short term health impact assessments of PM10 the highest level of reduced mortality is with reduction of annual mean levels to 20 µg.m-3 since ambient levels are already below 50 µg.m-3 and reducing to this level would require a reduction of more than 5 µg.m-3 as the baseline condition is 31.5 µg.m-3.

• The long term health impact assessments of PM10 follows the trends given by the short term work. However the number of cases is increased due to the time frame considered.

• For the long term health impact assessments of PM2.5 the highest level of reduced mortality is with reduction of annual mean levels to 15 µg.m-3.

7. ACKNOWLEDGEMENTS The authors would like to acknowledge Fondazione S. Maugeri in Padua and Metrohm Italia for the analysis of heavy metals by ICP-MS and voltammetry, respectively. The organisers of the project would like to record their sincere thanks to all those who volunteered to take part in the project, without their involvement this work would not have been possible.

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WHO, (2000) World Health Organisation. Air Quality Guidelines for Europe. WHO Regional Publications, European Series No.23, Copenhagen, WHO Regional Office for Europe; 1987 ISBN 9289013583.

WHO, (2003) Health aspects of air pollution with particulate matter, ozone and nitrogen dioxide. Report on a WHO Working Group, EUR/03/5042688, World Health Organisation.

WHO, (2004) Meta-analysis of time-series studies and panel studies of particulate matter (PM) and ozone (O3), EUR/04/5042688, World Health Organisation.

35

ftp://ftp.ei.jrc.it/pub/erlap/ERLAPDownload.htm

http://cfpub.epa.gov/ncea/cfm/partmatt.cfm

Annex 1 : Meteorological parameters in Ljublana (Bežigrad)

Solar Radiation

0100200300400500600700800900

10001100

20-May 21-May 22-May 23-May 24-May 25-May 26-May

W

/m2

Rainfall

0

5

10

15

20


mm

Relative Humidity

0

20

40

60

80

100


%

RH

Air Temperature

-10-505

10152025303540


de

g C

Grass Temperature

-10-505

10152025303540


de

g C

36

Daily Wind Run (km)

-250

-150

-50

50

150

250

-250 -150 -50 50 150 250

Series1

Series2

Series3

Series4

Series5

Series6

Series7

TuesWedThurFriSatSunMon0%

5%

10%

15%

20%N

NE

E

SE

S

SW

W

NW

Wind Speed

012345678


m

/s

Wind Direction

0

90

180

270

360


d

eg

Sector N NE E SE S SW W NW Calm% of time 6% 11% 14% 17% 17% 2% 4% 8% 20%

37

Solar Radiation

0100200300400500600700800900

10001100

27-May 28-May 29-May 30-May 31-May 01-Jun 02-Jun

W

/m2

Rainfall

0

5

10

15

20


mm

Relative Humidity

0

20

40

60

80

100


%

RH

Air Temperature

-10-505

10152025303540


de

g C

Grass Temperature

-10-505

10152025303540


de

g C

38

Daily Wind Run (km)

-100

-75

-50

-25

0

25

50

75

100

-300 -200 -100 0 100 200 300

Tues

Wed

Thur

Fri

Sat

Sun

Mon0%5%

10%15%20%25%

N

NE

E

SE

S

SW

W

NW

Wind Speed

012345678


m

/s

Wind Direction

0

90

180

270

360


d

eg


39

Solar Radiation

0100200300400500600700800900

10001100

10-Feb 11-Feb 12-Feb 13-Feb 14-Feb 15-Feb 16-Feb

W

/m2

Rainfall

0

5

10

15

20


mm

Relative Humidity

0

20

40

60

80

100


%

RH

Air Temperature

-10-505

10152025303540


de

g C

Grass Temperature

-10-505

10152025303540


de

g C

40

Daily Wind Run (km)

-250

-150

-50

50

150

250

-300 -200 -100 0 100 200 300

Series1

Series2

Series3

Series4

Series5

Series6

Series7

TuesWedThurFriSatSunMon0%

10%

20%

30%N

NE

E

SE

S

SW

W

NW

Wind Speed

012345678


m

/s

Wind Direction

0

90

180

270

360


d

eg


41

Solar Radiation

0100200300400500600700800900

10001100


W

/m2

Rainfall

0

5

10

15

20


mm

Relative Humidity

0

20

40

60

80

100


%

RH

Air Temperature

-10-505

10152025303540


de

g C

Grass Temperature

-10-505

10152025303540


de

g C

42

Daily Wind Run (km)

-300

-200

-100

0

100

200

300

-500 -300 -100 100 300 500

Tues

Wed

Thur

Fri

Sat

Sun

Mon0%

10%

20%

30%

40%N

NE

E

SE

S

SW

W

NW

Wind Speed

012345678


m

/s

Wind Direction

0

90

180

270

360


d

eg


43

Mission of the JRC

The mission of the JRC is to provide customer-driven scientific and technical support for the conception, development, implementation and monitoring of EU policies. As a service of the European Commission, the JRC functions as reference centre of science and technology for the Union. Close to policy-making process, it serves the common interest of the Member States, while being independent of special interests, whether private or national.

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