Long-Term Variation Assessment of Aerosol Load and Dominant Types over Asia for Air Quality Studies Using Multi-Sources Aerosol Datasets
Long-term (2000–2019) assessment of aerosol loads and dominant aerosol types at spatiotemporal scales using multi-source datasets can provide a strong impetus to the investigation of aerosol loads and to the targeted prevention control of atmospheric pollution in densely populated regions with frequ...
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ftdoajarticles:oai:doaj.org/article:673f7f6799014a289a6059d3b3ecf803 2023-05-15T13:06:52+02:00 Long-Term Variation Assessment of Aerosol Load and Dominant Types over Asia for Air Quality Studies Using Multi-Sources Aerosol Datasets Chunlin Huang Junzhang Li Weiwei Sun Qixiang Chen Qian-Jun Mao Yuan Yuan 2021-08-01T00:00:00Z https://doi.org/10.3390/rs13163116 https://doaj.org/article/673f7f6799014a289a6059d3b3ecf803 EN eng MDPI AG https://www.mdpi.com/2072-4292/13/16/3116 https://doaj.org/toc/2072-4292 doi:10.3390/rs13163116 2072-4292 https://doaj.org/article/673f7f6799014a289a6059d3b3ecf803 Remote Sensing, Vol 13, Iss 3116, p 3116 (2021) MERRA-2 MODIS heavy load frequency change and trend dominant aerosol types Science Q article 2021 ftdoajarticles https://doi.org/10.3390/rs13163116 2022-12-31T01:05:10Z Long-term (2000–2019) assessment of aerosol loads and dominant aerosol types at spatiotemporal scales using multi-source datasets can provide a strong impetus to the investigation of aerosol loads and to the targeted prevention control of atmospheric pollution in densely populated regions with frequent anthropogenic activities and heavy aerosol emissions. This study uses multi-source aerosol datasets, including Modern-Era Retrospective Analysis for Research and Applications version 2 (MERRA-2), Moderate Resolution Imaging Spectroradiometer (MODIS), and Aerosol Robotic Network (AERONET), to conduct a long-term variation assessment of aerosol load, high aerosol load frequency, and dominant aerosol types over Asia. The results indicate that regional aerosol type information with adequate spatial resolution can be combined with aerosol optical depth (AOD) values and heavy aerosol load frequency characterization results to explore the key contributors to air pollution. During the study period, the aerosol load over the North China Plain, Central China, Yangtze River Delta, Red River Delta, Sichuan Basin, and Pearl River Delta exhibited an increasing trend from 2000–2009 due to a sharp rise in aerosol emissions with economic development and a declining trend from 2010–2019 under stricter energy conservation controls and emissions reductions. The growth of urban/industrial (UI) type and biomass burning (BB) type aerosol emissions hindered the improvement of the atmospheric environment. Therefore, in future pollution mitigation efforts, focus should be on the control of UI-type and BB-type aerosol emissions. The Indus–Ganges River Plain, Deccan Plateau, and Eastern Ghats show a continuously increasing trend; however, the aerosol load growth rate of the last decade was lower than that of the first decade, which was mainly due to the decrease in the proportion of the mixed type aerosols. Article in Journal/Newspaper Aerosol Robotic Network Directory of Open Access Journals: DOAJ Articles Merra ENVELOPE(12.615,12.615,65.816,65.816) Remote Sensing 13 16 3116 |
institution |
Open Polar |
collection |
Directory of Open Access Journals: DOAJ Articles |
op_collection_id |
ftdoajarticles |
language |
English |
topic |
MERRA-2 MODIS heavy load frequency change and trend dominant aerosol types Science Q |
spellingShingle |
MERRA-2 MODIS heavy load frequency change and trend dominant aerosol types Science Q Chunlin Huang Junzhang Li Weiwei Sun Qixiang Chen Qian-Jun Mao Yuan Yuan Long-Term Variation Assessment of Aerosol Load and Dominant Types over Asia for Air Quality Studies Using Multi-Sources Aerosol Datasets |
topic_facet |
MERRA-2 MODIS heavy load frequency change and trend dominant aerosol types Science Q |
description |
Long-term (2000–2019) assessment of aerosol loads and dominant aerosol types at spatiotemporal scales using multi-source datasets can provide a strong impetus to the investigation of aerosol loads and to the targeted prevention control of atmospheric pollution in densely populated regions with frequent anthropogenic activities and heavy aerosol emissions. This study uses multi-source aerosol datasets, including Modern-Era Retrospective Analysis for Research and Applications version 2 (MERRA-2), Moderate Resolution Imaging Spectroradiometer (MODIS), and Aerosol Robotic Network (AERONET), to conduct a long-term variation assessment of aerosol load, high aerosol load frequency, and dominant aerosol types over Asia. The results indicate that regional aerosol type information with adequate spatial resolution can be combined with aerosol optical depth (AOD) values and heavy aerosol load frequency characterization results to explore the key contributors to air pollution. During the study period, the aerosol load over the North China Plain, Central China, Yangtze River Delta, Red River Delta, Sichuan Basin, and Pearl River Delta exhibited an increasing trend from 2000–2009 due to a sharp rise in aerosol emissions with economic development and a declining trend from 2010–2019 under stricter energy conservation controls and emissions reductions. The growth of urban/industrial (UI) type and biomass burning (BB) type aerosol emissions hindered the improvement of the atmospheric environment. Therefore, in future pollution mitigation efforts, focus should be on the control of UI-type and BB-type aerosol emissions. The Indus–Ganges River Plain, Deccan Plateau, and Eastern Ghats show a continuously increasing trend; however, the aerosol load growth rate of the last decade was lower than that of the first decade, which was mainly due to the decrease in the proportion of the mixed type aerosols. |
format |
Article in Journal/Newspaper |
author |
Chunlin Huang Junzhang Li Weiwei Sun Qixiang Chen Qian-Jun Mao Yuan Yuan |
author_facet |
Chunlin Huang Junzhang Li Weiwei Sun Qixiang Chen Qian-Jun Mao Yuan Yuan |
author_sort |
Chunlin Huang |
title |
Long-Term Variation Assessment of Aerosol Load and Dominant Types over Asia for Air Quality Studies Using Multi-Sources Aerosol Datasets |
title_short |
Long-Term Variation Assessment of Aerosol Load and Dominant Types over Asia for Air Quality Studies Using Multi-Sources Aerosol Datasets |
title_full |
Long-Term Variation Assessment of Aerosol Load and Dominant Types over Asia for Air Quality Studies Using Multi-Sources Aerosol Datasets |
title_fullStr |
Long-Term Variation Assessment of Aerosol Load and Dominant Types over Asia for Air Quality Studies Using Multi-Sources Aerosol Datasets |
title_full_unstemmed |
Long-Term Variation Assessment of Aerosol Load and Dominant Types over Asia for Air Quality Studies Using Multi-Sources Aerosol Datasets |
title_sort |
long-term variation assessment of aerosol load and dominant types over asia for air quality studies using multi-sources aerosol datasets |
publisher |
MDPI AG |
publishDate |
2021 |
url |
https://doi.org/10.3390/rs13163116 https://doaj.org/article/673f7f6799014a289a6059d3b3ecf803 |
long_lat |
ENVELOPE(12.615,12.615,65.816,65.816) |
geographic |
Merra |
geographic_facet |
Merra |
genre |
Aerosol Robotic Network |
genre_facet |
Aerosol Robotic Network |
op_source |
Remote Sensing, Vol 13, Iss 3116, p 3116 (2021) |
op_relation |
https://www.mdpi.com/2072-4292/13/16/3116 https://doaj.org/toc/2072-4292 doi:10.3390/rs13163116 2072-4292 https://doaj.org/article/673f7f6799014a289a6059d3b3ecf803 |
op_doi |
https://doi.org/10.3390/rs13163116 |
container_title |
Remote Sensing |
container_volume |
13 |
container_issue |
16 |
container_start_page |
3116 |
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1766024032367411200 |