An Empirical Mode Decomposition for Establishing Spatiotemporal Air Quality Trends in Shandong Province, China
Air pollution is a serious problem in China, and the government has taken a series of steps to solve it. However, it is still u2nclear how the situation has improved after years of atmospheric pollution control. Shandong Province, which has the second largest population and the highest coal consumpt...
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2021
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oai:doaj.org-article:560da6ce9ce2450980a1f5a86d41a9052021-11-25T19:05:23ZAn Empirical Mode Decomposition for Establishing Spatiotemporal Air Quality Trends in Shandong Province, China10.3390/su1322129012071-1050https://doaj.org/article/560da6ce9ce2450980a1f5a86d41a9052021-11-01T00:00:00Zhttps://www.mdpi.com/2071-1050/13/22/12901https://doaj.org/toc/2071-1050Air pollution is a serious problem in China, and the government has taken a series of steps to solve it. However, it is still u2nclear how the situation has improved after years of atmospheric pollution control. Shandong Province, which has the second largest population and the highest coal consumption in China, was chosen to analyze the spatiotemporal air quality trends. We obtained daily air quality index (AQI) values from 91 stations in the province from 1 January 2014, to 31 December 2019, based on an adaptive data analysis method, empirical mode decomposition (EMD). The distribution of AQI in Shandong Province was heterogeneous at both spatial and temporal scales. All the stations could be divided into four clusters whose AQI trends decreased from 75 to 53, 95 to 68, 128 to 82, and 148 to 82, respectively. The overall trend of pollution became more serious from east to west in the province. The AQI is the largest in winter, followed by spring and autumn, and the smallest index occurs in summer. There are four types of annual trends of the AQI of each city. The overall downward trend indicates that the air quality of each city was improving annually.Huisheng WuMaogui HuYaping ZhangYuan HanMDPI AGarticleair pollutionspatial patterntemporal trenddecompositionEnvironmental effects of industries and plantsTD194-195Renewable energy sourcesTJ807-830Environmental sciencesGE1-350ENSustainability, Vol 13, Iss 12901, p 12901 (2021) |
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air pollution spatial pattern temporal trend decomposition Environmental effects of industries and plants TD194-195 Renewable energy sources TJ807-830 Environmental sciences GE1-350 |
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air pollution spatial pattern temporal trend decomposition Environmental effects of industries and plants TD194-195 Renewable energy sources TJ807-830 Environmental sciences GE1-350 Huisheng Wu Maogui Hu Yaping Zhang Yuan Han An Empirical Mode Decomposition for Establishing Spatiotemporal Air Quality Trends in Shandong Province, China |
description |
Air pollution is a serious problem in China, and the government has taken a series of steps to solve it. However, it is still u2nclear how the situation has improved after years of atmospheric pollution control. Shandong Province, which has the second largest population and the highest coal consumption in China, was chosen to analyze the spatiotemporal air quality trends. We obtained daily air quality index (AQI) values from 91 stations in the province from 1 January 2014, to 31 December 2019, based on an adaptive data analysis method, empirical mode decomposition (EMD). The distribution of AQI in Shandong Province was heterogeneous at both spatial and temporal scales. All the stations could be divided into four clusters whose AQI trends decreased from 75 to 53, 95 to 68, 128 to 82, and 148 to 82, respectively. The overall trend of pollution became more serious from east to west in the province. The AQI is the largest in winter, followed by spring and autumn, and the smallest index occurs in summer. There are four types of annual trends of the AQI of each city. The overall downward trend indicates that the air quality of each city was improving annually. |
format |
article |
author |
Huisheng Wu Maogui Hu Yaping Zhang Yuan Han |
author_facet |
Huisheng Wu Maogui Hu Yaping Zhang Yuan Han |
author_sort |
Huisheng Wu |
title |
An Empirical Mode Decomposition for Establishing Spatiotemporal Air Quality Trends in Shandong Province, China |
title_short |
An Empirical Mode Decomposition for Establishing Spatiotemporal Air Quality Trends in Shandong Province, China |
title_full |
An Empirical Mode Decomposition for Establishing Spatiotemporal Air Quality Trends in Shandong Province, China |
title_fullStr |
An Empirical Mode Decomposition for Establishing Spatiotemporal Air Quality Trends in Shandong Province, China |
title_full_unstemmed |
An Empirical Mode Decomposition for Establishing Spatiotemporal Air Quality Trends in Shandong Province, China |
title_sort |
empirical mode decomposition for establishing spatiotemporal air quality trends in shandong province, china |
publisher |
MDPI AG |
publishDate |
2021 |
url |
https://doaj.org/article/560da6ce9ce2450980a1f5a86d41a905 |
work_keys_str_mv |
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