Comparison of air pollution in Shanghai and Lanzhou based on wavelet transform.
Air pollution index
Change period
Lanzhou
Shanghai
Time series
Timescale
Wavelet transform
Journal
Environmental science and pollution research international
ISSN: 1614-7499
Titre abrégé: Environ Sci Pollut Res Int
Pays: Germany
ID NLM: 9441769
Informations de publication
Date de publication:
Jun 2019
Jun 2019
Historique:
received:
10
11
2016
accepted:
29
03
2017
pubmed:
23
4
2017
medline:
1
8
2019
entrez:
23
4
2017
Statut:
ppublish
Résumé
For a long-period comparative analysis of air pollution in coastal and inland cities, we analyzed the continuous Morlet wavelet transform on the time series of a 5274-day air pollution index in Shanghai and Lanzhou during 15 years and studied the multi-scale variation characteristic, main cycle, and impact factor of the air pollution time series. The analysis showed that (1) air pollution in the two cities was non-stationary and nonlinear, had multiple timescales, and exhibited the characteristics of high in winter and spring and low in summer and autumn. (2) The monthly variation in air pollution in Shanghai was not significant, whereas the seasonal variation of air pollution in Lanzhou was obvious. (3) Air pollution in Shanghai showed an ascending tendency, whereas that in Lanzhou presented a descending tendency. Overall, air pollution in Lanzhou was higher than that in Shanghai, but the situation has reversed since 2015. (4) The primary cycles of air pollution in these two cities were close, but the secondary cycles were significantly different. The aforementioned differences were mainly due to the impact of topographical and meteorological factors in Lanzhou, the weather process and the surrounding environment in Shanghai. These conclusions have reference significance for Shanghai and Lanzhou to control air pollution. The multi-timescale variation and local features of the wavelet analysis method used in this study can be applied to varied aspects of air pollution analysis. The identification of cycle characteristics and the monitoring, forecasting, and controlling of air pollution can yield valuable reference.
Identifiants
pubmed: 28432621
doi: 10.1007/s11356-017-8959-8
pii: 10.1007/s11356-017-8959-8
pmc: PMC6546662
doi:
Substances chimiques
Air Pollutants
0
Particulate Matter
0
Types de publication
Journal Article
Langues
eng
Pagination
16825-16834Subventions
Organisme : Fundamental Research Funds for the Central Universities of China
ID : 15LZUJBWZD017
Organisme : China Postdoctoral Science Foundation
ID : 2016M600827
Organisme : National Natural Science Foundation of China
ID : 71472079
Organisme : National Natural Science Foundation of China
ID : 71373108
Organisme : Key Project of China Ministry of Education for Philosophy and Social Science
ID : 16JZD023
Organisme : the E-commerce Operation Key Laboratory of Colleges and Universities in Gansu Province
ID : Lanzhou Institute of Technology-2016
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