Cargando…

What drives the aerosol distribution in Guangdong - the most developed province in Southern China?

This paper uses Moderate Resolution Imaging Spectroradiometer (MODIS) data to investigate the spatial and temporal variations of aerosol optical thickness (AOT) over Guangdong, the most developed province in China, during 2010–2012. Linear regression and self-organizing maps (SOM) are used to invest...

Descripción completa

Detalles Bibliográficos
Autores principales: Li, Lili, Wang, Yunpeng
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group 2014
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5380013/
https://www.ncbi.nlm.nih.gov/pubmed/25096216
http://dx.doi.org/10.1038/srep05972
_version_ 1782519722973069312
author Li, Lili
Wang, Yunpeng
author_facet Li, Lili
Wang, Yunpeng
author_sort Li, Lili
collection PubMed
description This paper uses Moderate Resolution Imaging Spectroradiometer (MODIS) data to investigate the spatial and temporal variations of aerosol optical thickness (AOT) over Guangdong, the most developed province in China, during 2010–2012. Linear regression and self-organizing maps (SOM) are used to investigate the relationship between AOT and its affecting factors, including Normalized Difference Vegetation Index (NDVI), elevation, urbanized land fraction, and several socio-economic variables. Results show that the highest values of τ(0.55) mainly occur over the rapidly-developing Pearl River Delta (PRD) region and the eastern coast. Seasonal averaged AOT is highest in summer (0.416), followed by spring (0.351), winter (0.292), and autumn (0.254). From unary linear regression and SOM analysis, AOT is shown to be strongly negatively correlated to NDVI (R(2) = 0.782) and elevation (R(2) = 0.731), and positively correlated with socio-economic factors, especially GDP, industry and vehicle density (R(2) above 0.73), but not primary industry. Multiple linear regression between AOT and the contributing factors shows much higher R(2) values (>0.8), indicative of the clear relationships between AOT and variables. This study illustrates that human activities have strong impacts on aerosols distribution in Guangdong Province. Economic and industrial developments, as well as vehicle density, are the main controlling factors on aerosol distribution.
format Online
Article
Text
id pubmed-5380013
institution National Center for Biotechnology Information
language English
publishDate 2014
publisher Nature Publishing Group
record_format MEDLINE/PubMed
spelling pubmed-53800132017-04-10 What drives the aerosol distribution in Guangdong - the most developed province in Southern China? Li, Lili Wang, Yunpeng Sci Rep Article This paper uses Moderate Resolution Imaging Spectroradiometer (MODIS) data to investigate the spatial and temporal variations of aerosol optical thickness (AOT) over Guangdong, the most developed province in China, during 2010–2012. Linear regression and self-organizing maps (SOM) are used to investigate the relationship between AOT and its affecting factors, including Normalized Difference Vegetation Index (NDVI), elevation, urbanized land fraction, and several socio-economic variables. Results show that the highest values of τ(0.55) mainly occur over the rapidly-developing Pearl River Delta (PRD) region and the eastern coast. Seasonal averaged AOT is highest in summer (0.416), followed by spring (0.351), winter (0.292), and autumn (0.254). From unary linear regression and SOM analysis, AOT is shown to be strongly negatively correlated to NDVI (R(2) = 0.782) and elevation (R(2) = 0.731), and positively correlated with socio-economic factors, especially GDP, industry and vehicle density (R(2) above 0.73), but not primary industry. Multiple linear regression between AOT and the contributing factors shows much higher R(2) values (>0.8), indicative of the clear relationships between AOT and variables. This study illustrates that human activities have strong impacts on aerosols distribution in Guangdong Province. Economic and industrial developments, as well as vehicle density, are the main controlling factors on aerosol distribution. Nature Publishing Group 2014-08-06 /pmc/articles/PMC5380013/ /pubmed/25096216 http://dx.doi.org/10.1038/srep05972 Text en Copyright © 2014, Macmillan Publishers Limited. All rights reserved http://creativecommons.org/licenses/by-nc-sa/4.0/ This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License. The images or other third party material in this article are included in the article's Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder in order to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by-nc-sa/4.0/
spellingShingle Article
Li, Lili
Wang, Yunpeng
What drives the aerosol distribution in Guangdong - the most developed province in Southern China?
title What drives the aerosol distribution in Guangdong - the most developed province in Southern China?
title_full What drives the aerosol distribution in Guangdong - the most developed province in Southern China?
title_fullStr What drives the aerosol distribution in Guangdong - the most developed province in Southern China?
title_full_unstemmed What drives the aerosol distribution in Guangdong - the most developed province in Southern China?
title_short What drives the aerosol distribution in Guangdong - the most developed province in Southern China?
title_sort what drives the aerosol distribution in guangdong - the most developed province in southern china?
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5380013/
https://www.ncbi.nlm.nih.gov/pubmed/25096216
http://dx.doi.org/10.1038/srep05972
work_keys_str_mv AT lilili whatdrivestheaerosoldistributioninguangdongthemostdevelopedprovinceinsouthernchina
AT wangyunpeng whatdrivestheaerosoldistributioninguangdongthemostdevelopedprovinceinsouthernchina