Inventory of African desert dust events in the north-central Iberian Peninsula in 2003–2014 based on sun-photometer–AERONET and particulate-mass–EMEP data
A reliable identification of desert dust (DD) episodes over north-central Spain is carried out based on the AErosol RObotic NETwork (AERONET) columnar aerosol sun photometer (aerosol optical depth, AOD, and Ångström exponent, α ) and European Monitoring and Evaluation Programme (EMEP) surface partic...
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ftdoajarticles:oai:doaj.org/article:bfd13f3db48440158f5dcbe01e4a0ec8 2023-05-15T13:07:09+02:00 Inventory of African desert dust events in the north-central Iberian Peninsula in 2003–2014 based on sun-photometer–AERONET and particulate-mass–EMEP data V. E. Cachorro M. A. Burgos D. Mateos C. Toledano Y. Bennouna B. Torres Á. M. de Frutos Á. Herguedas 2016-07-01T00:00:00Z https://doi.org/10.5194/acp-16-8227-2016 https://doaj.org/article/bfd13f3db48440158f5dcbe01e4a0ec8 EN eng Copernicus Publications https://www.atmos-chem-phys.net/16/8227/2016/acp-16-8227-2016.pdf https://doaj.org/toc/1680-7316 https://doaj.org/toc/1680-7324 doi:10.5194/acp-16-8227-2016 1680-7316 1680-7324 https://doaj.org/article/bfd13f3db48440158f5dcbe01e4a0ec8 Atmospheric Chemistry and Physics, Vol 16, Pp 8227-8248 (2016) Physics QC1-999 Chemistry QD1-999 article 2016 ftdoajarticles https://doi.org/10.5194/acp-16-8227-2016 2022-12-31T15:37:43Z A reliable identification of desert dust (DD) episodes over north-central Spain is carried out based on the AErosol RObotic NETwork (AERONET) columnar aerosol sun photometer (aerosol optical depth, AOD, and Ångström exponent, α ) and European Monitoring and Evaluation Programme (EMEP) surface particulate-mass concentration (PM x , x = 10, 2.5, and 2.5–10 µm) as the main core data. The impact of DD on background aerosol conditions is detectable by means of aerosol load thresholds and complementary information provided by HYSPLIT (Hybrid Single Particle Lagrangian Integrated Trajectory Model) air mass back trajectories, MODIS (Moderate Resolution Imaging Spectroradiometer) images, forecast aerosol models, and synoptic maps, which have been carefully reviewed by a human observer for each day included in the DD inventory. This identification method allows the detection of low and moderate DD intrusions and also of mixtures of mineral dust with other aerosol types by means of the analysis of α . During the period studied (2003–2014), a total of 152 DD episodes composed of 418 days are identified. Overall, this means ∼ 13 episodes and ∼ 35 days per year with DD intrusion, representing 9.5 % days year −1 . During the identified DD intrusions, 19 daily exceedances over 50 µg m −3 are reported at the surface. The occurrence of DD event days during the year peaks in March and June, with a marked minimum in April and lowest occurrence in winter. A large interannual variability is observed showing a statistically significant temporal decreasing trend of ∼ 3 days year −1 . The DD impact on the aerosol climatology is addressed by evaluating the DD contribution in magnitude and percent (in brackets) for AOD, PM 10 , PM 2.5 , and PM 2.5 − 10 , obtaining mean values of 0.015 (11.5 %), 1.3 µg m −3 (11.8 %), 0.55 µg m −3 (8.5 %) and 0.79 µg m −3 (16.1 %), respectively. Annual cycles of the DD contribution for AOD and PM 10 present two maxima – one in summer (0.03 and 2.4 µg m −3 for AOD in June and PM 10 in August) and another in ... Article in Journal/Newspaper Aerosol Robotic Network Directory of Open Access Journals: DOAJ Articles Atmospheric Chemistry and Physics 16 13 8227 8248 |
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Directory of Open Access Journals: DOAJ Articles |
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English |
topic |
Physics QC1-999 Chemistry QD1-999 |
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Physics QC1-999 Chemistry QD1-999 V. E. Cachorro M. A. Burgos D. Mateos C. Toledano Y. Bennouna B. Torres Á. M. de Frutos Á. Herguedas Inventory of African desert dust events in the north-central Iberian Peninsula in 2003–2014 based on sun-photometer–AERONET and particulate-mass–EMEP data |
topic_facet |
Physics QC1-999 Chemistry QD1-999 |
description |
A reliable identification of desert dust (DD) episodes over north-central Spain is carried out based on the AErosol RObotic NETwork (AERONET) columnar aerosol sun photometer (aerosol optical depth, AOD, and Ångström exponent, α ) and European Monitoring and Evaluation Programme (EMEP) surface particulate-mass concentration (PM x , x = 10, 2.5, and 2.5–10 µm) as the main core data. The impact of DD on background aerosol conditions is detectable by means of aerosol load thresholds and complementary information provided by HYSPLIT (Hybrid Single Particle Lagrangian Integrated Trajectory Model) air mass back trajectories, MODIS (Moderate Resolution Imaging Spectroradiometer) images, forecast aerosol models, and synoptic maps, which have been carefully reviewed by a human observer for each day included in the DD inventory. This identification method allows the detection of low and moderate DD intrusions and also of mixtures of mineral dust with other aerosol types by means of the analysis of α . During the period studied (2003–2014), a total of 152 DD episodes composed of 418 days are identified. Overall, this means ∼ 13 episodes and ∼ 35 days per year with DD intrusion, representing 9.5 % days year −1 . During the identified DD intrusions, 19 daily exceedances over 50 µg m −3 are reported at the surface. The occurrence of DD event days during the year peaks in March and June, with a marked minimum in April and lowest occurrence in winter. A large interannual variability is observed showing a statistically significant temporal decreasing trend of ∼ 3 days year −1 . The DD impact on the aerosol climatology is addressed by evaluating the DD contribution in magnitude and percent (in brackets) for AOD, PM 10 , PM 2.5 , and PM 2.5 − 10 , obtaining mean values of 0.015 (11.5 %), 1.3 µg m −3 (11.8 %), 0.55 µg m −3 (8.5 %) and 0.79 µg m −3 (16.1 %), respectively. Annual cycles of the DD contribution for AOD and PM 10 present two maxima – one in summer (0.03 and 2.4 µg m −3 for AOD in June and PM 10 in August) and another in ... |
format |
Article in Journal/Newspaper |
author |
V. E. Cachorro M. A. Burgos D. Mateos C. Toledano Y. Bennouna B. Torres Á. M. de Frutos Á. Herguedas |
author_facet |
V. E. Cachorro M. A. Burgos D. Mateos C. Toledano Y. Bennouna B. Torres Á. M. de Frutos Á. Herguedas |
author_sort |
V. E. Cachorro |
title |
Inventory of African desert dust events in the north-central Iberian Peninsula in 2003–2014 based on sun-photometer–AERONET and particulate-mass–EMEP data |
title_short |
Inventory of African desert dust events in the north-central Iberian Peninsula in 2003–2014 based on sun-photometer–AERONET and particulate-mass–EMEP data |
title_full |
Inventory of African desert dust events in the north-central Iberian Peninsula in 2003–2014 based on sun-photometer–AERONET and particulate-mass–EMEP data |
title_fullStr |
Inventory of African desert dust events in the north-central Iberian Peninsula in 2003–2014 based on sun-photometer–AERONET and particulate-mass–EMEP data |
title_full_unstemmed |
Inventory of African desert dust events in the north-central Iberian Peninsula in 2003–2014 based on sun-photometer–AERONET and particulate-mass–EMEP data |
title_sort |
inventory of african desert dust events in the north-central iberian peninsula in 2003–2014 based on sun-photometer–aeronet and particulate-mass–emep data |
publisher |
Copernicus Publications |
publishDate |
2016 |
url |
https://doi.org/10.5194/acp-16-8227-2016 https://doaj.org/article/bfd13f3db48440158f5dcbe01e4a0ec8 |
genre |
Aerosol Robotic Network |
genre_facet |
Aerosol Robotic Network |
op_source |
Atmospheric Chemistry and Physics, Vol 16, Pp 8227-8248 (2016) |
op_relation |
https://www.atmos-chem-phys.net/16/8227/2016/acp-16-8227-2016.pdf https://doaj.org/toc/1680-7316 https://doaj.org/toc/1680-7324 doi:10.5194/acp-16-8227-2016 1680-7316 1680-7324 https://doaj.org/article/bfd13f3db48440158f5dcbe01e4a0ec8 |
op_doi |
https://doi.org/10.5194/acp-16-8227-2016 |
container_title |
Atmospheric Chemistry and Physics |
container_volume |
16 |
container_issue |
13 |
container_start_page |
8227 |
op_container_end_page |
8248 |
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