Published June 1, 2019 | Version v1
Journal article

Comparison of air pollution in Shanghai and Lanzhou based on wavelet transform

  • 1. Lanzhou University, School of Management (China)
  • 2. Lanzhou Institute of Technology, College of Economics and Management (China)

Description

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.

Additional details

Identifiers

Publishing Information

Journal Title
Environmental Science and Pollution Research International
Journal Volume
26
Journal Issue
17
Journal Page Range
p. 16825-16834
ISSN
0944-1344

INIS

Country of Publication
Germany
Country of Input or Organization
International Atomic Energy Agency (IAEA)
INIS RN
52005210
Subject category
S54: ENVIRONMENTAL SCIENCES;
Descriptors DEI
AIR POLLUTION; ENVIRONMENT; FORECASTING; MONITORING; MONTHLY VARIATIONS; SEASONAL VARIATIONS; URBAN AREAS; WEATHER
Descriptors DEC
POLLUTION; VARIATIONS

Optional Information

Copyright
Copyright (c) 2017 The Author(s)