Trends in aerosol optical properties over Eastern Europe based on MODIS-Aqua
This study provides characteristics of aerosol columnar properties, measured over ten countries in Eastern Europe from 2002 to 2019. Aerosol optical depth (AOD) and Ångström exponent (AE) were obtained with the Moderate Resolution Imaging Spectroradiometer (MODIS) Collection 6.1 merged Dark Target a...
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ftdoajarticles:oai:doaj.org/article:205e40e5d7be49fa87cc94fe6f365d9f 2023-10-01T03:49:49+02:00 Trends in aerosol optical properties over Eastern Europe based on MODIS-Aqua Mikalai Filonchyk Volha Hurynovich Haowen Yan 2020-11-01T00:00:00Z https://doi.org/10.1016/j.gsf.2020.03.014 https://doaj.org/article/205e40e5d7be49fa87cc94fe6f365d9f EN eng Elsevier http://www.sciencedirect.com/science/article/pii/S1674987120300864 https://doaj.org/toc/1674-9871 1674-9871 doi:10.1016/j.gsf.2020.03.014 https://doaj.org/article/205e40e5d7be49fa87cc94fe6f365d9f Geoscience Frontiers, Vol 11, Iss 6, Pp 2169-2181 (2020) MODIS AERONET Eastern Europe Aerosol optical depth Aerosol-type classification Geology QE1-996.5 article 2020 ftdoajarticles https://doi.org/10.1016/j.gsf.2020.03.014 2023-09-03T00:46:15Z This study provides characteristics of aerosol columnar properties, measured over ten countries in Eastern Europe from 2002 to 2019. Aerosol optical depth (AOD) and Ångström exponent (AE) were obtained with the Moderate Resolution Imaging Spectroradiometer (MODIS) Collection 6.1 merged Dark Target and Deep Blue aerosol product. The product is validated using ground-based Aerosol Robotic Network (AERONET) situated at Minsk, Belsk, Moldova and Kyiv. The results showed that 76.15% of retrieved AOD data are within the expected error. It was established that 64.2% of AOD points are between 0 and 0.2 and 79.3% of all AE points are over 1. Mean AOD values in the region vary from 0.130 ± 0.04 (Moldova) to 0.193 ± 0.03 (Czech Republic) with mean value in the region 0.162 ± 0.05. Seasonal mean AOD (AE) values were at the maximum during the summer from 0.231 ± 0.05 (1.482 ± 0.09 in winter) to minimum 0.087 ± 0.04 during the winter (1.363 ± 0.17 in summer). Gradual AOD reduction is observed in all countries with annual trend from −0.0050 (Belarus) to −0.0029 (Russia). Finally, the relationship between AOD and AE was studied to classify various aerosol types and showed seasonal non-uniformity of their contribution depending on variation in sources. The entire region is under significant impact of various aerosol types, including clean continental (СС), mixed (MX) and anthropogenic/burning (AB) aerosols types that are at 59.77%, 24.72%, and 12.97% respectively. These results form an important basis for further regional studies of air quality and distribution of sources of pollution. Article in Journal/Newspaper Aerosol Robotic Network Directory of Open Access Journals: DOAJ Articles Geoscience Frontiers 11 6 2169 2181 |
institution |
Open Polar |
collection |
Directory of Open Access Journals: DOAJ Articles |
op_collection_id |
ftdoajarticles |
language |
English |
topic |
MODIS AERONET Eastern Europe Aerosol optical depth Aerosol-type classification Geology QE1-996.5 |
spellingShingle |
MODIS AERONET Eastern Europe Aerosol optical depth Aerosol-type classification Geology QE1-996.5 Mikalai Filonchyk Volha Hurynovich Haowen Yan Trends in aerosol optical properties over Eastern Europe based on MODIS-Aqua |
topic_facet |
MODIS AERONET Eastern Europe Aerosol optical depth Aerosol-type classification Geology QE1-996.5 |
description |
This study provides characteristics of aerosol columnar properties, measured over ten countries in Eastern Europe from 2002 to 2019. Aerosol optical depth (AOD) and Ångström exponent (AE) were obtained with the Moderate Resolution Imaging Spectroradiometer (MODIS) Collection 6.1 merged Dark Target and Deep Blue aerosol product. The product is validated using ground-based Aerosol Robotic Network (AERONET) situated at Minsk, Belsk, Moldova and Kyiv. The results showed that 76.15% of retrieved AOD data are within the expected error. It was established that 64.2% of AOD points are between 0 and 0.2 and 79.3% of all AE points are over 1. Mean AOD values in the region vary from 0.130 ± 0.04 (Moldova) to 0.193 ± 0.03 (Czech Republic) with mean value in the region 0.162 ± 0.05. Seasonal mean AOD (AE) values were at the maximum during the summer from 0.231 ± 0.05 (1.482 ± 0.09 in winter) to minimum 0.087 ± 0.04 during the winter (1.363 ± 0.17 in summer). Gradual AOD reduction is observed in all countries with annual trend from −0.0050 (Belarus) to −0.0029 (Russia). Finally, the relationship between AOD and AE was studied to classify various aerosol types and showed seasonal non-uniformity of their contribution depending on variation in sources. The entire region is under significant impact of various aerosol types, including clean continental (СС), mixed (MX) and anthropogenic/burning (AB) aerosols types that are at 59.77%, 24.72%, and 12.97% respectively. These results form an important basis for further regional studies of air quality and distribution of sources of pollution. |
format |
Article in Journal/Newspaper |
author |
Mikalai Filonchyk Volha Hurynovich Haowen Yan |
author_facet |
Mikalai Filonchyk Volha Hurynovich Haowen Yan |
author_sort |
Mikalai Filonchyk |
title |
Trends in aerosol optical properties over Eastern Europe based on MODIS-Aqua |
title_short |
Trends in aerosol optical properties over Eastern Europe based on MODIS-Aqua |
title_full |
Trends in aerosol optical properties over Eastern Europe based on MODIS-Aqua |
title_fullStr |
Trends in aerosol optical properties over Eastern Europe based on MODIS-Aqua |
title_full_unstemmed |
Trends in aerosol optical properties over Eastern Europe based on MODIS-Aqua |
title_sort |
trends in aerosol optical properties over eastern europe based on modis-aqua |
publisher |
Elsevier |
publishDate |
2020 |
url |
https://doi.org/10.1016/j.gsf.2020.03.014 https://doaj.org/article/205e40e5d7be49fa87cc94fe6f365d9f |
genre |
Aerosol Robotic Network |
genre_facet |
Aerosol Robotic Network |
op_source |
Geoscience Frontiers, Vol 11, Iss 6, Pp 2169-2181 (2020) |
op_relation |
http://www.sciencedirect.com/science/article/pii/S1674987120300864 https://doaj.org/toc/1674-9871 1674-9871 doi:10.1016/j.gsf.2020.03.014 https://doaj.org/article/205e40e5d7be49fa87cc94fe6f365d9f |
op_doi |
https://doi.org/10.1016/j.gsf.2020.03.014 |
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Geoscience Frontiers |
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11 |
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6 |
container_start_page |
2169 |
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2181 |
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