Map Overview

The map presents the 2022 modelled concentrations (per 0.1x0.1degrees grids) of ozone metrics across the EU Member States as reported through the European Monitoring and Evaluation Programme (EMEP). To the left of the map a scale is provided to indicate the range of concentrations. Zooming in enables a view of the concentration for each gridded area. Methane emissions have also been included within the map based on 2022 reported by the European Environment Agency. The colour coding indicates concentration levels relative to the other gridded areas, i.e. compared to other locations within the EU. The colours do not indicate safe or unsafe levels of exposure.

Methodology

The dataset and detailed methodological approach are provided in an accompanying technical report. A brief summary of this approach is also provided below.

The air quality analysis had focused on collating and assessing 2022 O3 concentrations in Europe based on findings provided in the 2024 EMEP report. Reported and validated emissions for all EU27 Member State were collected from European Environment Agency (EEA) datasets. Descriptions of the key metrics include:

  • SOMO35: defined as the yearly sum of the daily maximum of 8-hour running average over 35 ppb.
  • POD: Phyto-toxic ozone dose, is the accumulated stomatal ozone flux over a threshold (1 or 3 mmol.m−2 in our case). POD1 is used for forests and POD3 for the crops' growing seasons assessment.
  • AOT40: Represents the accumulated amount of ozone over the threshold value of 40 ppb. The corresponding unit are ppb.hours.

Health Assessment: Short-term exposure has been assessed using the reported SOMO35 concentrations and long-term exposure has been linked to the peak season metric. As peak season concentrations for 2022 were not available from the EMEP dataset, these were instead sourced from the ‘Burden of disease of air pollution’ dataset published by the European Environment Agency (EEA).

The affected populations, associated risk rates, and baselines health incidences were all identified, and the relevant health pathways were identified. The application on concentration response functions then focused on:

  • Statistical deaths which presents the number of deaths that could be attributed to air pollution at a point in time based on scientific studies exploring the relationship between air pollution and mortality risk.
  • Life Years Lost (LYL) which measures the years of life lost due to premature deaths, i.e., deaths occurring prematurely when compared to baseline or average life expectancy in each geography.
  • Respiratory hospital admissions representing the number of cases and hospital admissions across different health endpoints attributable to exposure to air pollution.

The associated economic impacts are presented using a 2024 price year, and are presented in terms of:

  • Non-market disease burden, which reflects the non-market health and wellbeing costs associated with the Life Year losses and is based on the amount that individuals are willing to pay for an additional year of life lived.
  • Hospital admission costs which represents the costs associated with the respiratory hospital admissions linked to ozone exposure

Environmental Assessment: The study applied concentration response functions to determine the impact upon crops (wheat) and forest biomass as a result of exposure to POD3 and POD1. The economic impact has been based upon the change in wheat production and Eurostat wheat prices. Cost of change in wheat production is presented in with 2022 wheat prices adjusted to the 2024 price year.

The CRF for wheat is, where RY corresponds to relative yield:

RY = 1 - 0.0064POD3

The CRF for forest biomass varied depending on the most common tree species (including Norway spruce, Oak, and Scots Pine) within the Member State.

The below table contains data on a per-member state and an EU-wide level. By default, a select few statistics are presented in the table. Use the checkboxes to show and hide different statistics of interest. The table can be sorted by values in each column by clicking on the column names.

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