European city air quality viewer

If the city is not represented by a dot on the map, it means that the city could not be included in the viewer for one of the two reasons below.

• The city is not included in the database of cities established under the European Commission’s Urban Audit. 
• The city does not have urban or suburban background or traffic air quality monitoring stations for PM_2.5.

The dot representing a city on the map is grey when:

• PM_2.5 is only monitored at traffic stations; or
• None of the urban/suburban background air quality monitoring stations in the city reported data covering more than 75% of the days in either of the two years considered.

Hover on a city on the map to see:

• the city’s name and country,
• the city’s rank,
• the average PM_2.5 concentration over the past two full years,
• the air quality categorised as good, fair, moderate, poor or very poor,
• the number of stations, regardless of their type, that measured fine particulate matter in the city (please be aware that, according to the description above, the city will be ranked only in the case of having background stations with enough data coverage),
• the population of the city, according to the most recent EUROSTAT data, and
• the city’s JRC Urban PM_2.5 Atlas fact sheet

The table ranks European cities according to their average levels of fine particulate matter over the past two full calendar years.

Using the index to the right, you can click on the air quality categories, good, fair, moderate, poor and very poor, to display the cities with air quality in that category.

Clicking on a city on the map shows a view of the locations of the PM_2.5 monitoring stations, regardless of their type, in the city. The stations on the map are represented according to the average concentration of PM_2.5 for the city as a whole. Hovering on the stations on the map shows:

• the station code,
• the station type,
• the city’s name and country,
• the country name,
• the average PM_2.5 concentration at the station over the past two full years,
• the years included in the average,
• the average data coverage.

The viewer presents cities as defined by the European Commission’s Urban Audit, in its 2020 edition. This geospatial dataset includes cities with a population of over 50,000 inhabitants. A similar dataset is available for download from the Eurostat website (note that the European City Air Quality Viewer uses a processed 2020 version of that dataset with the most recent population numbers from Eurostat).

We use data on concentration of fine particulate matter, or PM_2.5, reported to the EEA by our member countries under the European Union Ambient Air Quality Directives (2008/50/EC). Two types of data are used.

• For the last full calendar year, ‘Up-to-date’ air quality data is used to calculate the annual average. This data is reported to the EEA on an hourly basis by member countries and participating countries (known as dataflow E2a).
• For the calendar year before last, data used has been officially validated by the reporting countries prior to being reported to the EEA (known as dataflow E1a).

In addition to the information available in the city viewer, a pop-up window provides links to country fact sheets from the Urban PM_2.5 Atlas, Air Quality in European Cities, 2023 Report, when you select a city on the map. These fact sheets contain detailed insights into the spatial (e.g., urban or national levels) and sectoral (e.g., transport, residential heating, or agriculture) contributions to air pollution in each urban area. They also highlight how targeted local and national measures can effectively reduce fine particulate matter levels, supporting the objectives of the EU’s Zero Pollution Action Plan.

Particulate matter is the ambient air pollutant that has been most extensively researched and studies show that PM_2.5 has one of the highest impact on health in terms of premature death and disease. Long-term exposure to air pollution is associated with the most serious health outcomes, including cardiovascular and respiratory diseases, along with mortality.  

To produce this tool, we use data from urban background and suburban background air quality monitoring stations that are situated within the boundaries of the cities, as defined by the Urban Audit, and for which countries report data to the EEA. These stations provide a robust picture of the exposure of the population to air pollution in cities.

Air quality is also measured at industrial stations and traffic stations. Data from these stations is not used for this tool, as they are used to measure levels in more polluted areas, such as around industrial sites or near motorways and major roads with dense traffic. As such, they measure the exposure of populations around major industrial areas and roads and do not estimate the exposure of the general population. In addition, industrial and traffic stations are unevenly distributed in cities across Europe, which might introduce bias when making comparisons. Nevertheless, concentrations at traffic stations are shown when clicking on the cities, as explained above.

Air quality is also monitored in rural areas, with the aim, for instance, of understanding the impacts on crops and natural ecosystem. Rural stations, typically situated far from urban centers, are not included in this tool.

1. We calculate the annual mean concentration of fine particulate matter for a city by averaging the daily means for all its urban background stations and suburban background stations over the past calendar year. For this we use the ‘up-to-date’ air quality data (E2a). Unrealistic concentrations above 1000 ug/m³ are removed from the time series prior to the calculation of the average.
2. We calculate the annual mean concentration of fine particulate matter for a city by averaging the daily means for all its urban background stations and suburban background stations over the year before last. For this we used the validated air quality data (E1a).
3. We use the results of step 1 and 2 to calculate the mean concentration across those two calendar years.

For some cities, we do not have data for either step 1 or step 2. In such cases, we use the annual mean for the available year.  

For data from a station to be included, a minimum of 75% temporal data coverage is required. This means that for an individual station, we consider those with more than 274 valid daily values per calendar year (or 275 days in a leap year).

• Cities that are not included in the database of cities established under the European Commission’s Urban Audit.
• Cities that do not have any air quality monitoring stations for PM_2.5 regardless of their type.
• Stations are represented by a grey dot on the map and are excluded from the ranking table under the following conditions:
• The city lacks urban or suburban background PM_2.5 monitoring stations but have traffic monitoring stations.
• Data was reported for urban and/or suburban background PM_2.5 monitoring stations, but the data coverage doesn’t meet the minimum of 75% data coverage.

We display five categories of air quality, including good, fair, moderate, poor and very poor. These are defined by bandwidths of concentrations of fine particulate matter, as shown below.

In their guidelines for air quality, the World Health Organization established an annual air quality guideline for PM_2.5 exposure of 5 μg/m³, as well as several interim targets. These values have been used to define the bandwidths for the five categories of air quality.

Table: WHO air quality guidelines and interim targets for fine particulate matter, annual mean concentrations.

Source: Adapted from WHO, 2021

All measurement methods used have a degree of error. In particular, the up-to-date data (dataflow E2a) is not checked for outlying datapoints, which may be errors, and validated by the countries. This may introduce a limited number of more extreme values to the dataset.    

In reporting the characteristics of monitoring stations to the EEA, countries may interpret the definitions of station types differently. This can reduce comparability between cities.

It is assumed that all the urban and suburban monitoring stations in a single city represent background environments equally. The methodology does not account for the distribution of the urban population across the city. Treating stations equally may lead to an underestimate of the average concentration that the general population is exposed to, in the case where the area around a pollution hotspot is densely populated.

In large cities with dense urban centres, where large parts of the population reside, stations in the city centre are likely to be traffic stations. Such stations are not included in the methodology, and this may lead to an underestimation of concentrations of fine particulate matter.

Only measurements from urban and suburban stations that are in the urban audit geometries are considered in the calculations.