Historical reconstruction of background air pollution over France for 2000–2015
<p>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="in...
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Copernicus Publications
2022-05-01
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author | E. Real F. Couvidat A. Ung L. Malherbe B. Raux A. Gressent A. Colette |
author_facet | E. Real F. Couvidat A. Ung L. Malherbe B. Raux A. Gressent A. Colette |
author_sort | E. Real |
collection | DOAJ |
description | <p>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 4 km.
Regulatory indicators (annual average, SOMO35 (sum of ozone means over 35 ppb), AOT40 (accumulated ozone exposure over a threshold of 40 ppb), 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 2000–2015, 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.</p> |
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issn | 1866-3508 1866-3516 |
language | English |
last_indexed | 2024-12-12T05:55:50Z |
publishDate | 2022-05-01 |
publisher | Copernicus Publications |
record_format | Article |
series | Earth System Science Data |
spelling | doaj.art-11db7dba603941e3a9c664c163f92a4f2022-12-22T00:35:34ZengCopernicus PublicationsEarth System Science Data1866-35081866-35162022-05-01142419244310.5194/essd-14-2419-2022Historical reconstruction of background air pollution over France for 2000–2015E. RealF. CouvidatA. UngL. MalherbeB. RauxA. GressentA. Colette<p>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 4 km. Regulatory indicators (annual average, SOMO35 (sum of ozone means over 35 ppb), AOT40 (accumulated ozone exposure over a threshold of 40 ppb), 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 2000–2015, 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.</p>https://essd.copernicus.org/articles/14/2419/2022/essd-14-2419-2022.pdf |
spellingShingle | E. Real F. Couvidat A. Ung L. Malherbe B. Raux A. Gressent A. Colette Historical reconstruction of background air pollution over France for 2000–2015 Earth System Science Data |
title | Historical reconstruction of background air pollution over France for 2000–2015 |
title_full | Historical reconstruction of background air pollution over France for 2000–2015 |
title_fullStr | Historical reconstruction of background air pollution over France for 2000–2015 |
title_full_unstemmed | Historical reconstruction of background air pollution over France for 2000–2015 |
title_short | Historical reconstruction of background air pollution over France for 2000–2015 |
title_sort | historical reconstruction of background air pollution over france for 2000 2015 |
url | https://essd.copernicus.org/articles/14/2419/2022/essd-14-2419-2022.pdf |
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