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SO(2) Emissions in China – Their Network and Hierarchical Structures
SO(2) emissions lead to various harmful effects on environment and human health. The SO(2) emission in China has significant contribution to the global SO(2) emission, so it is necessary to employ various methods to study SO(2) emissions in China with great details in order to lay the foundation for...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5384192/ https://www.ncbi.nlm.nih.gov/pubmed/28387301 http://dx.doi.org/10.1038/srep46216 |
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author | Yan, Shaomin Wu, Guang |
author_facet | Yan, Shaomin Wu, Guang |
author_sort | Yan, Shaomin |
collection | PubMed |
description | SO(2) emissions lead to various harmful effects on environment and human health. The SO(2) emission in China has significant contribution to the global SO(2) emission, so it is necessary to employ various methods to study SO(2) emissions in China with great details in order to lay the foundation for policymaking to improve environmental conditions in China. Network analysis is used to analyze the SO(2) emissions from power generation, industrial, residential and transportation sectors in China for 2008 and 2010, which are recently available from 1744 ground surface monitoring stations. The results show that the SO(2) emissions from power generation sector were highly individualized as small-sized clusters, the SO(2) emissions from industrial sector underwent an integration process with a large cluster contained 1674 places covering all industrial areas in China, the SO(2) emissions from residential sector was not impacted by time, and the SO(2) emissions from transportation sector underwent significant integration. Hierarchical structure is obtained by further combining SO(2) emissions from all four sectors and is potentially useful to find out similar patterns of SO(2) emissions, which can provide information on understanding the mechanisms of SO(2) pollution and on designing different environmental measure to combat SO(2) emissions. |
format | Online Article Text |
id | pubmed-5384192 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | Nature Publishing Group |
record_format | MEDLINE/PubMed |
spelling | pubmed-53841922017-04-11 SO(2) Emissions in China – Their Network and Hierarchical Structures Yan, Shaomin Wu, Guang Sci Rep Article SO(2) emissions lead to various harmful effects on environment and human health. The SO(2) emission in China has significant contribution to the global SO(2) emission, so it is necessary to employ various methods to study SO(2) emissions in China with great details in order to lay the foundation for policymaking to improve environmental conditions in China. Network analysis is used to analyze the SO(2) emissions from power generation, industrial, residential and transportation sectors in China for 2008 and 2010, which are recently available from 1744 ground surface monitoring stations. The results show that the SO(2) emissions from power generation sector were highly individualized as small-sized clusters, the SO(2) emissions from industrial sector underwent an integration process with a large cluster contained 1674 places covering all industrial areas in China, the SO(2) emissions from residential sector was not impacted by time, and the SO(2) emissions from transportation sector underwent significant integration. Hierarchical structure is obtained by further combining SO(2) emissions from all four sectors and is potentially useful to find out similar patterns of SO(2) emissions, which can provide information on understanding the mechanisms of SO(2) pollution and on designing different environmental measure to combat SO(2) emissions. Nature Publishing Group 2017-04-07 /pmc/articles/PMC5384192/ /pubmed/28387301 http://dx.doi.org/10.1038/srep46216 Text en Copyright © 2017, The Author(s) http://creativecommons.org/licenses/by/4.0/ This work is licensed under a Creative Commons Attribution 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 to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ |
spellingShingle | Article Yan, Shaomin Wu, Guang SO(2) Emissions in China – Their Network and Hierarchical Structures |
title | SO(2) Emissions in China – Their Network and Hierarchical Structures |
title_full | SO(2) Emissions in China – Their Network and Hierarchical Structures |
title_fullStr | SO(2) Emissions in China – Their Network and Hierarchical Structures |
title_full_unstemmed | SO(2) Emissions in China – Their Network and Hierarchical Structures |
title_short | SO(2) Emissions in China – Their Network and Hierarchical Structures |
title_sort | so(2) emissions in china – their network and hierarchical structures |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5384192/ https://www.ncbi.nlm.nih.gov/pubmed/28387301 http://dx.doi.org/10.1038/srep46216 |
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