Abstract
<strong class="journal-contentHeaderColor">Abstract.</strong> This paper describes a 16-year dataset of air pollution concentrations and air quality indicators over France. Using a kriging method that combines background air quality measurements and modeling with the CHIMERE chemistry transport model, hourly concentrations of NO<span class="inline-formula"><sub>2</sub></span>, O<span class="inline-formula"><sub>3</sub></span>, PM<span class="inline-formula"><sub>10</sub></span> and PM<span class="inline-formula"><sub>2.5</sub></span> are produced with a spatial resolution of about 4âkm. Regulatory indicators (annual average, SOMO35 (sum of ozone means over 35âppb), AOT40 (accumulated ozone exposure over a threshold of 40âppb), etc.) are also calculated from these hourly data. The NO<span class="inline-formula"><sub>2</sub></span> and O<span class="inline-formula"><sub>3</sub></span> datasets cover the period 2000â2015, as well as the annual PM<span class="inline-formula"><sub>10</sub></span> data. Hourly PM<span class="inline-formula"><sub>10</sub></span> concentrations are not available from 2000 to 2007 due to known artifacts in PM<span class="inline-formula"><sub>10</sub></span> measurements. PM<span class="inline-formula"><sub>2.5</sub></span> data are only available from 2009 onwards due to the limited number of measuring stations available before this date. The overall dataset was evaluated over all years by a cross-validation process against background stations (rural, sub-urban and urban) to take into account the data fusion between measurement and models in the method. The results are very good for PM<span class="inline-formula"><sub>10</sub></span>, PM<span class="inline-formula"><sub>2.5</sub></span> and O<span class="inline-formula"><sub>3</sub></span>. They show an overestimation of NO<span class="inline-formula"><sub>2</sub></span> concentrations in rural areas, while NO<span class="inline-formula"><sub>2</sub></span> background values in urban areas are well represented. Maps of the main indicators are presented over several years, and trends are calculated. Finally, exposure and trends are calculated for the three main health-related indicators: annual averages of PM<span class="inline-formula"><sub>2.5</sub></span>, NO<span class="inline-formula"><sub>2</sub></span> and SOMO35. The DOI link for the dataset is <a href="https://doi.org/10.5281/zenodo.5043645">https://doi.org/10.5281/zenodo.5043645</a> (Real et al., 2021). We hope that the publication of this open dataset will facilitate further studies on the impacts of air pollution.
Highlights
Air pollution is a major environmental risk for human health and ecosystems in Europe
In response of emissions reductions, concentrations of SO2, NO2 and particles measured over Europe show a clear decrease (EEA, 2018)
European background concentrations decreases have been recently evaluated by the EMEP Task Force on Measurements and Monitoring (TFMM) through analysis of measurements from the EMEP monitoring network over the period 1990-2012 (EMEP, 2016)
Summary
Air pollution is a major environmental risk for human health and ecosystems in Europe. Union (EU) has put in place several measures to reduce anthropogenic emissions of pollutants. In response of emissions reductions, concentrations of SO2, NO2 and particles measured over Europe show a clear decrease (EEA, 2018). European background concentrations decreases have been recently evaluated by the EMEP Task Force on Measurements and Monitoring (TFMM) through analysis of measurements from the EMEP monitoring network (representatives of rural background concentrations) over the period 1990-2012 (EMEP, 2016). Sulphur compounds show the largest decrease in response to strong sulfur emissions abatement. NO2, NMVOC and acidifying and eutrophying nitrogen pollutant emissions (NOx and NH3) decreased over the period 1990-2012 with reductions
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