Multiyear Typology of Long-Range Transported Aerosols over Europe
In this study, AERONET (Aerosol Robotic Network) and EARLINET (European Aerosol Research Lidar Network) data from 17 collocated lidar and sun photometer stations were used to characterize the optical properties of aerosol and their types for the 2008–2018 period in various regions of Europe. The ana...
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ftmdpi:oai:mdpi.com:/2073-4433/10/9/482/ 2023-08-20T03:59:11+02:00 Multiyear Typology of Long-Range Transported Aerosols over Europe Victor Nicolae Camelia Talianu Simona Andrei Bogdan Antonescu Dragoș Ene Doina Nicolae Alexandru Dandocsi Victorin-Emilian Toader Sabina Ștefan Tom Savu Jeni Vasilescu agris 2019-08-22 application/pdf https://doi.org/10.3390/atmos10090482 EN eng Multidisciplinary Digital Publishing Institute Meteorology https://dx.doi.org/10.3390/atmos10090482 https://creativecommons.org/licenses/by/4.0/ Atmosphere; Volume 10; Issue 9; Pages: 482 aerosol typing lidar photometry EARLINET AERONET Text 2019 ftmdpi https://doi.org/10.3390/atmos10090482 2023-07-31T22:32:30Z In this study, AERONET (Aerosol Robotic Network) and EARLINET (European Aerosol Research Lidar Network) data from 17 collocated lidar and sun photometer stations were used to characterize the optical properties of aerosol and their types for the 2008–2018 period in various regions of Europe. The analysis was done on six cluster domains defined using circulation types around each station and their common circulation features. As concluded from the lidar photometer measurements, the typical aerosol particles observed during 2008–2018 over Europe were medium-sized, medium absorbing particles with low spectral dependence. The highest mean values for the lidar ratio at 532 nm were recorded over Northeastern Europe and were associated with Smoke particles, while the lowest mean values for the Angstrom exponent were identified over the Southwest cluster and were associated with Dust and Marine particles. Smoke (37%) and Continental (25%) aerosol types were the predominant aerosol types in Europe, followed by Continental Polluted (17%), Dust (10%), and Marine/Cloud (10%) types. The seasonal variability was insignificant at the continental scale, showing a small increase in the percentage of Smoke during spring and a small increase of Dust during autumn. The aerosol optical depth (AOD) slightly decreased with time, while the Angstrom exponent oscillated between “hot and smoky” years (2011–2015) on the one hand and “dusty” years (2008–2010) and “wet” years (2017–2018) on the other hand. The high variability from year to year showed that aerosol transport in the troposphere became more and more important in the overall balance of the columnar aerosol load. Text Aerosol Robotic Network MDPI Open Access Publishing Atmosphere 10 9 482 |
institution |
Open Polar |
collection |
MDPI Open Access Publishing |
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ftmdpi |
language |
English |
topic |
aerosol typing lidar photometry EARLINET AERONET |
spellingShingle |
aerosol typing lidar photometry EARLINET AERONET Victor Nicolae Camelia Talianu Simona Andrei Bogdan Antonescu Dragoș Ene Doina Nicolae Alexandru Dandocsi Victorin-Emilian Toader Sabina Ștefan Tom Savu Jeni Vasilescu Multiyear Typology of Long-Range Transported Aerosols over Europe |
topic_facet |
aerosol typing lidar photometry EARLINET AERONET |
description |
In this study, AERONET (Aerosol Robotic Network) and EARLINET (European Aerosol Research Lidar Network) data from 17 collocated lidar and sun photometer stations were used to characterize the optical properties of aerosol and their types for the 2008–2018 period in various regions of Europe. The analysis was done on six cluster domains defined using circulation types around each station and their common circulation features. As concluded from the lidar photometer measurements, the typical aerosol particles observed during 2008–2018 over Europe were medium-sized, medium absorbing particles with low spectral dependence. The highest mean values for the lidar ratio at 532 nm were recorded over Northeastern Europe and were associated with Smoke particles, while the lowest mean values for the Angstrom exponent were identified over the Southwest cluster and were associated with Dust and Marine particles. Smoke (37%) and Continental (25%) aerosol types were the predominant aerosol types in Europe, followed by Continental Polluted (17%), Dust (10%), and Marine/Cloud (10%) types. The seasonal variability was insignificant at the continental scale, showing a small increase in the percentage of Smoke during spring and a small increase of Dust during autumn. The aerosol optical depth (AOD) slightly decreased with time, while the Angstrom exponent oscillated between “hot and smoky” years (2011–2015) on the one hand and “dusty” years (2008–2010) and “wet” years (2017–2018) on the other hand. The high variability from year to year showed that aerosol transport in the troposphere became more and more important in the overall balance of the columnar aerosol load. |
format |
Text |
author |
Victor Nicolae Camelia Talianu Simona Andrei Bogdan Antonescu Dragoș Ene Doina Nicolae Alexandru Dandocsi Victorin-Emilian Toader Sabina Ștefan Tom Savu Jeni Vasilescu |
author_facet |
Victor Nicolae Camelia Talianu Simona Andrei Bogdan Antonescu Dragoș Ene Doina Nicolae Alexandru Dandocsi Victorin-Emilian Toader Sabina Ștefan Tom Savu Jeni Vasilescu |
author_sort |
Victor Nicolae |
title |
Multiyear Typology of Long-Range Transported Aerosols over Europe |
title_short |
Multiyear Typology of Long-Range Transported Aerosols over Europe |
title_full |
Multiyear Typology of Long-Range Transported Aerosols over Europe |
title_fullStr |
Multiyear Typology of Long-Range Transported Aerosols over Europe |
title_full_unstemmed |
Multiyear Typology of Long-Range Transported Aerosols over Europe |
title_sort |
multiyear typology of long-range transported aerosols over europe |
publisher |
Multidisciplinary Digital Publishing Institute |
publishDate |
2019 |
url |
https://doi.org/10.3390/atmos10090482 |
op_coverage |
agris |
genre |
Aerosol Robotic Network |
genre_facet |
Aerosol Robotic Network |
op_source |
Atmosphere; Volume 10; Issue 9; Pages: 482 |
op_relation |
Meteorology https://dx.doi.org/10.3390/atmos10090482 |
op_rights |
https://creativecommons.org/licenses/by/4.0/ |
op_doi |
https://doi.org/10.3390/atmos10090482 |
container_title |
Atmosphere |
container_volume |
10 |
container_issue |
9 |
container_start_page |
482 |
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1774719582599118848 |