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Historical reconstruction of background air pollution over France for 2000–2015
Earth System Science Data ( IF 11.4 ) Pub Date : 2022-05-24 , DOI: 10.5194/essd-14-2419-2022 Elsa Real, Florian Couvidat, Anthony Ung, Laure Malherbe, Blandine Raux, Alicia Gressent, Augustin Colette
Earth System Science Data ( IF 11.4 ) Pub Date : 2022-05-24 , DOI: 10.5194/essd-14-2419-2022 Elsa Real, Florian Couvidat, Anthony Ung, Laure Malherbe, Blandine Raux, Alicia Gressent, Augustin Colette
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 NO2, O3, PM10 and
PM2.5 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 NO2 and O3 datasets
cover the period 2000–2015, as well as the annual PM10 data. Hourly
PM10 concentrations are not available from 2000 to 2007 due to known
artifacts in PM10 measurements. PM2.5 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 PM10, PM2.5 and
O3. They show an overestimation of NO2 concentrations in rural
areas, while NO2 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 PM2.5, NO2 and
SOMO35. The DOI link for the dataset is https://doi.org/10.5281/zenodo.5043645 (Real et al., 2021). We hope that
the publication of this open dataset will facilitate further studies on the
impacts of air pollution.
中文翻译:
2000-2015 年法国背景空气污染的历史重建
本文描述了法国 16 年的空气污染浓度和空气质量指标数据集。使用将背景空气质量测量和建模与 CHIMERE 化学传输模型相结合的克里金方法,可以产生大约 4 公里空间分辨率的NO 2、O 3、PM 10和 PM 2.5的小时浓度。监管指标(年平均值、SOMO35(臭氧总和超过 35 ppb)、AOT40(累积臭氧暴露超过 40 ppb 的阈值)等)也根据这些每小时数据计算。NO 2和 O 3数据集涵盖 2000-2015 年期间以及年度 PM 10数据。每小时10点由于 PM 10测量中的已知伪影,无法获得 2000 年至 2007 年的浓度。由于在此日期之前可用的测量站数量有限, PM 2.5数据只能从 2009 年开始获得。多年来,通过针对背景站(农村、郊区和城市)的交叉验证过程对整个数据集进行了评估,以考虑该方法中测量值和模型之间的数据融合。对于 PM 10、PM 2.5和 O 3 ,结果非常好。他们高估了农村地区的 NO 2浓度,而 NO 2城市地区的背景值得到了很好的体现。主要指标的地图呈现了几年的情况,并计算了趋势。最后,计算三个主要健康相关指标的暴露和趋势:PM 2.5、NO 2和 SOMO35 的年平均值。数据集的 DOI 链接是 https://doi.org/10.5281/zenodo.5043645(Real et al., 2021)。我们希望这个开放数据集的发布将有助于进一步研究空气污染的影响。
更新日期:2022-05-24
中文翻译:
2000-2015 年法国背景空气污染的历史重建
本文描述了法国 16 年的空气污染浓度和空气质量指标数据集。使用将背景空气质量测量和建模与 CHIMERE 化学传输模型相结合的克里金方法,可以产生大约 4 公里空间分辨率的NO 2、O 3、PM 10和 PM 2.5的小时浓度。监管指标(年平均值、SOMO35(臭氧总和超过 35 ppb)、AOT40(累积臭氧暴露超过 40 ppb 的阈值)等)也根据这些每小时数据计算。NO 2和 O 3数据集涵盖 2000-2015 年期间以及年度 PM 10数据。每小时10点由于 PM 10测量中的已知伪影,无法获得 2000 年至 2007 年的浓度。由于在此日期之前可用的测量站数量有限, PM 2.5数据只能从 2009 年开始获得。多年来,通过针对背景站(农村、郊区和城市)的交叉验证过程对整个数据集进行了评估,以考虑该方法中测量值和模型之间的数据融合。对于 PM 10、PM 2.5和 O 3 ,结果非常好。他们高估了农村地区的 NO 2浓度,而 NO 2城市地区的背景值得到了很好的体现。主要指标的地图呈现了几年的情况,并计算了趋势。最后,计算三个主要健康相关指标的暴露和趋势:PM 2.5、NO 2和 SOMO35 的年平均值。数据集的 DOI 链接是 https://doi.org/10.5281/zenodo.5043645(Real et al., 2021)。我们希望这个开放数据集的发布将有助于进一步研究空气污染的影响。