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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Published in:Remote Sensing
Main Authors: Chunlin Huang, Junzhang Li, Weiwei Sun, Qixiang Chen, Qian-Jun Mao, Yuan Yuan
Format: Text
Language:English
Published: Multidisciplinary Digital Publishing Institute 2021
Subjects:
Online Access:https://doi.org/10.3390/rs13163116
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spelling ftmdpi:oai:mdpi.com:/2072-4292/13/16/3116/ 2023-08-20T03:59:13+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 2021-08-06 application/pdf https://doi.org/10.3390/rs13163116 EN eng Multidisciplinary Digital Publishing Institute Environmental Remote Sensing https://dx.doi.org/10.3390/rs13163116 https://creativecommons.org/licenses/by/4.0/ Remote Sensing; Volume 13; Issue 16; Pages: 3116 MERRA-2 MODIS heavy load frequency change and trend dominant aerosol types Text 2021 ftmdpi https://doi.org/10.3390/rs13163116 2023-08-01T02:22:50Z 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. Text Aerosol Robotic Network MDPI Open Access Publishing Merra ENVELOPE(12.615,12.615,65.816,65.816) Remote Sensing 13 16 3116
institution Open Polar
collection MDPI Open Access Publishing
op_collection_id ftmdpi
language English
topic MERRA-2
MODIS
heavy load frequency
change and trend
dominant aerosol types
spellingShingle MERRA-2
MODIS
heavy load frequency
change and trend
dominant aerosol types
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
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 Text
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 Multidisciplinary Digital Publishing Institute
publishDate 2021
url https://doi.org/10.3390/rs13163116
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; Volume 13; Issue 16; Pages: 3116
op_relation Environmental Remote Sensing
https://dx.doi.org/10.3390/rs13163116
op_rights https://creativecommons.org/licenses/by/4.0/
op_doi https://doi.org/10.3390/rs13163116
container_title Remote Sensing
container_volume 13
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