Cargando…

Spatiotemporal Variability and Influencing Factors of Aerosol Optical Depth over the Pan Yangtze River Delta during the 2014–2017 Period

Large amounts of aerosol particles suspended in the atmosphere pose a serious challenge to the climate and human health. In this study, we produced a dataset through merging the Moderate Resolution Imaging Spectrometers (MODIS) Collection 6.1 3-km resolution Dark Target aerosol optical depth (DT AOD...

Descripción completa

Detalles Bibliográficos
Autores principales: Cheng, Liang, Li, Long, Chen, Longqian, Hu, Sai, Yuan, Lina, Liu, Yunqiang, Cui, Yifan, Zhang, Ting
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6801425/
https://www.ncbi.nlm.nih.gov/pubmed/31547200
http://dx.doi.org/10.3390/ijerph16193522
_version_ 1783460568385978368
author Cheng, Liang
Li, Long
Chen, Longqian
Hu, Sai
Yuan, Lina
Liu, Yunqiang
Cui, Yifan
Zhang, Ting
author_facet Cheng, Liang
Li, Long
Chen, Longqian
Hu, Sai
Yuan, Lina
Liu, Yunqiang
Cui, Yifan
Zhang, Ting
author_sort Cheng, Liang
collection PubMed
description Large amounts of aerosol particles suspended in the atmosphere pose a serious challenge to the climate and human health. In this study, we produced a dataset through merging the Moderate Resolution Imaging Spectrometers (MODIS) Collection 6.1 3-km resolution Dark Target aerosol optical depth (DT AOD) with the 10-km resolution Deep Blue aerosol optical depth (DB AOD) data by linear regression and made use of it to unravel the spatiotemporal characteristics of aerosols over the Pan Yangtze River Delta (PYRD) region from 2014 to 2017. Then, the geographical detector method and multiple linear regression analysis were employed to investigate the contributions of influencing factors. Results indicate that: (1) compared to the original Terra DT and Aqua DT AOD data, the average daily spatial coverage of the merged AOD data increased by 94% and 132%, respectively; (2) the values of four-year average AOD were high in the north-east and low in the south-west of the PYRD; (3) the annual average AOD showed a decreasing trend from 2014 to 2017 while the seasonal average AOD reached its maximum in spring; and that (4) Digital Elevation Model (DEM) and slope contributed most to the spatial distribution of AOD, followed by precipitation and population density. Our study highlights the spatiotemporal variability of aerosol optical depth and the contributions of different factors over this large geographical area in the four-year period, and can, therefore, provide useful insights into the air pollution control for decision makers.
format Online
Article
Text
id pubmed-6801425
institution National Center for Biotechnology Information
language English
publishDate 2019
publisher MDPI
record_format MEDLINE/PubMed
spelling pubmed-68014252019-10-31 Spatiotemporal Variability and Influencing Factors of Aerosol Optical Depth over the Pan Yangtze River Delta during the 2014–2017 Period Cheng, Liang Li, Long Chen, Longqian Hu, Sai Yuan, Lina Liu, Yunqiang Cui, Yifan Zhang, Ting Int J Environ Res Public Health Article Large amounts of aerosol particles suspended in the atmosphere pose a serious challenge to the climate and human health. In this study, we produced a dataset through merging the Moderate Resolution Imaging Spectrometers (MODIS) Collection 6.1 3-km resolution Dark Target aerosol optical depth (DT AOD) with the 10-km resolution Deep Blue aerosol optical depth (DB AOD) data by linear regression and made use of it to unravel the spatiotemporal characteristics of aerosols over the Pan Yangtze River Delta (PYRD) region from 2014 to 2017. Then, the geographical detector method and multiple linear regression analysis were employed to investigate the contributions of influencing factors. Results indicate that: (1) compared to the original Terra DT and Aqua DT AOD data, the average daily spatial coverage of the merged AOD data increased by 94% and 132%, respectively; (2) the values of four-year average AOD were high in the north-east and low in the south-west of the PYRD; (3) the annual average AOD showed a decreasing trend from 2014 to 2017 while the seasonal average AOD reached its maximum in spring; and that (4) Digital Elevation Model (DEM) and slope contributed most to the spatial distribution of AOD, followed by precipitation and population density. Our study highlights the spatiotemporal variability of aerosol optical depth and the contributions of different factors over this large geographical area in the four-year period, and can, therefore, provide useful insights into the air pollution control for decision makers. MDPI 2019-09-20 2019-10 /pmc/articles/PMC6801425/ /pubmed/31547200 http://dx.doi.org/10.3390/ijerph16193522 Text en © 2019 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Cheng, Liang
Li, Long
Chen, Longqian
Hu, Sai
Yuan, Lina
Liu, Yunqiang
Cui, Yifan
Zhang, Ting
Spatiotemporal Variability and Influencing Factors of Aerosol Optical Depth over the Pan Yangtze River Delta during the 2014–2017 Period
title Spatiotemporal Variability and Influencing Factors of Aerosol Optical Depth over the Pan Yangtze River Delta during the 2014–2017 Period
title_full Spatiotemporal Variability and Influencing Factors of Aerosol Optical Depth over the Pan Yangtze River Delta during the 2014–2017 Period
title_fullStr Spatiotemporal Variability and Influencing Factors of Aerosol Optical Depth over the Pan Yangtze River Delta during the 2014–2017 Period
title_full_unstemmed Spatiotemporal Variability and Influencing Factors of Aerosol Optical Depth over the Pan Yangtze River Delta during the 2014–2017 Period
title_short Spatiotemporal Variability and Influencing Factors of Aerosol Optical Depth over the Pan Yangtze River Delta during the 2014–2017 Period
title_sort spatiotemporal variability and influencing factors of aerosol optical depth over the pan yangtze river delta during the 2014–2017 period
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6801425/
https://www.ncbi.nlm.nih.gov/pubmed/31547200
http://dx.doi.org/10.3390/ijerph16193522
work_keys_str_mv AT chengliang spatiotemporalvariabilityandinfluencingfactorsofaerosolopticaldepthoverthepanyangtzeriverdeltaduringthe20142017period
AT lilong spatiotemporalvariabilityandinfluencingfactorsofaerosolopticaldepthoverthepanyangtzeriverdeltaduringthe20142017period
AT chenlongqian spatiotemporalvariabilityandinfluencingfactorsofaerosolopticaldepthoverthepanyangtzeriverdeltaduringthe20142017period
AT husai spatiotemporalvariabilityandinfluencingfactorsofaerosolopticaldepthoverthepanyangtzeriverdeltaduringthe20142017period
AT yuanlina spatiotemporalvariabilityandinfluencingfactorsofaerosolopticaldepthoverthepanyangtzeriverdeltaduringthe20142017period
AT liuyunqiang spatiotemporalvariabilityandinfluencingfactorsofaerosolopticaldepthoverthepanyangtzeriverdeltaduringthe20142017period
AT cuiyifan spatiotemporalvariabilityandinfluencingfactorsofaerosolopticaldepthoverthepanyangtzeriverdeltaduringthe20142017period
AT zhangting spatiotemporalvariabilityandinfluencingfactorsofaerosolopticaldepthoverthepanyangtzeriverdeltaduringthe20142017period