Health effects of ozone in Europe

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EBoDE project
This page is a product of the EBoDE project. The final report of the EBoDE project has been published as a report in 2011[1] and also as web pages in Opasnet. These links lead to parts of the report.

EBoDE project: main page | overview | contributors | data overview | Parma meeting | abbreviations | all pages

Methods: environmental burden of disease calculation | selection of exposures and health effects | data needed | impact calculation tool

Health effects in Europe: benzene | dioxins | formaldehyde | lead | ozone | particulate matter | radon | second-hand smoke | transport noise | environmental burden of disease | results by country


About ozone

Ozone in the lower atmosphere (or tropospheric ozone) is not emitted directly, but is formed in the atmosphere in photochemical reactions from anthropogenic and natural emissions of precursor components involving mostly volatile organic compounds (VOCs) and nitrogen oxides (mainly NO and NO2). These substances react to form ozone under the influence of sunlight. Ozone is highly reactive and therefore other air pollutants also easily consume the ozone present in the air. Therefore, the highest ozone levels are typically found in background regions and levels in urban areas are generally lower than in the countryside.

Exposure to ozone can lead to a variety of respiratory health effects, such as coughing, throat irritation and reduced lung function. In addition, it can worsen bronchitis, emphysema, and asthma (WHO, 2006a). Ozone levels are increasing over time, and are cause for political concern. [1]

Selected health endpoints and exposure-response functions

For ozone, as well as for PM (see section 3.9), we followed the health impact assessment approach as laid out in the Clean Air For Europe (CAFE) project and based on WHO European Centre for Environment and Health and CLTRAP Task Force on Health consultations. Health effects that are taken into consideration include total non-violent mortality, minor restricted activity days (MRADs), and cough and lower respiratory symptoms (LRS) in children aged 5–14 years. The choice of these endpoints was guided by Cost Benefit Analysis as carried out in the CAFE project (Hurley et al, 2005, WHO 2008). The health endpoints considered and the corresponding exposure-response functions are summarized in Table 3-19 in section 3.12. [1]

Exposure data

The exposure metric used for ozone calculations is the sum of ozone maximum 8-h levels above 35 ppb, called SOMO35 (WHO, 2008). SOMO35 (expressed in μg m-3 × hours) is the sum of the maximum daily 8-hour concentrations that are exceeding 35 ppb (70 μg m-3) for each day in the calendar year, i.e. e.g. a daily level of 100 μg m-3 would contribute 30 to the SOMO35 calculation. Regardless of the name referring to the ppb unit of measurement, the values are expressed as mass concentrations (μg m-3).

For ozone (as well as for PM, see section 3.9), exposures were estimated by the European Topic Centre on Air and Climate Change (ETC/ACC) using AirBase data and air quality maps (SOMO35) (de Leeuw & Horalek, 2009). The European Environment Agency (EEA) has recently published an evaluation of new monitoring-based methods to estimate population weighted spatial distributions of ambient PM and ozone levels (EEA, 2009). These methods are based on interpolated maps using 10×10 km spatial resolution and using observed concentrations from national monitoring networks as primary data source. These are combined with regional chemistry transport modelling (CTM) and other supplemental data sources to improve estimates in observation-sparse areas. Maps for rural and urban areas were created separately and were subsequently merged. This approach aims to provide an objective method for dealing with the differences found between the rural and urban interpolated concentration fields in most areas of Europe (EEA, 2009). It is different from the earlier Clean Air for Europe (CAFE) work, which relied on modelling as its primary source of information and uses monitoring only to calibrate the European Monitoring and Evaluation Programme (EMEP) chemical transportation model. The modelling approach is better suitable for prospective scenario analyses, while the monitoring based approach may be considered more reliable for retrospective analyses.

The air quality maps were prepared for 2005 with interpolation methodology using co-kriging of observed concentrations using additional spatial information (EMEP model results, meteorological data, altitude, population density map). The year 2005 instead of 2004 was chosen as the modelling year by EEA for practical purposes. Description of the maps is given by Horálek et al (2007) and de Leeuw and Horalek (2009). A brief introduction to AirBase and a description of the state of and recent trends in European air quality is presented by Mol et al (2009).

Population weighted ambient ozone concentrations were calculated using population data for year 2005. The population density map (resolution 10x10 km) is based on the detailed population map prepared by JRC (reference year 2002, see Horalek et al., 2008 for further description of this dataset). The population density map for 2005 is made by scaling the 2002-reference map using the 2005/2002 ratio of national population numbers. Within a country the same age distribution is assumed in all grid cells. Resulting population-weighted ozone exposure values for the participating countries are shown in Table 3-12 and are also summarized in Table 3-21 in section 3.12. The geographical distribution of the SOMO35 levels in Europe is shown in Figure 3-5. [1]

TABLE 3-12.: National population weighted averages of ambient ozone levels (SOMO35) in 2005 for the six EBoDE countries (de Leeuw and Horalek, 2009).
Country SOMO35

(μg m-3)

Belgium 2 787
Germany 4 164
Finland 2 580
France 4 756
Italy 8 134
Netherlands 1 920
Ozone SOMO35-levels in Europe in 2005

FIGURE 3-5. Ozone SOMO35-levels in Europe in 2005 (EEA, 2009).

Uncertainties per stressor and comparison with other studies

A list of the most important sources of uncertainty for each stressor in the EBoDE calculations is provided in Table 5-1. Some of these are further explained below. In addition, we will compare our estimates to results of a selection of similar studies. Comparison of different studies on environmental burden of disease helps to understand the role of various methodological and strategic selections made in each study, like the selection of stressors or health endpoints.

PM and ozone

The methodology developed in Clean Air for Europe -project (CAFE) (Hurley et al., 2005) was applied using updated exposure estimates. The updated exposures are based on ambient air quality monitoring data that contain, besides the anthropogenic components that CAFE focused on, also natural sources of PM2.5. The spatial resolution of the updated model is 25 times higher (grid size 10x 10 km² instead of 50x50 km²). Compared to the CAFE estimates the current work adds estimation of the impacts in DALYs. The WHO Environmental Burden of Disease programme uses a non-linear exposure-response function (Ostro, 2004) that at higher exposures yields lower impacts than the linear CAFE model. WHO also sets a threshold level at 7.5 μg m-3.[1]

Excluded health endpoints and related assumptions Exposure data Exposure response function Calculation method Level of overall uncertainty a) Likely over- or underestimation b)
Ozone Possible long-term effects Spatial interpolation. Impact of urban areas YLL not known ** Overestimation (YLL set to 12 months). Underestimation due to exclusion of potential long-term effects


  1. 1.0 1.1 1.2 1.3 1.4 Otto Hänninen, Anne Knol: European Perspectives on Environmental Burden of Disease: Esimates for Nine Stressors in Six European Countries, Authors and National Institute for Health and Welfare (THL), Report 1/2011 [1] [2] Cite error: Invalid <ref> tag; name "EBoDe" defined multiple times with different content