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[Scale Dependence Between PM2.5 and Meteorological Factors and Its Influencing Factors in "2+26" Cities].
Wu, Shu-Qi; Jin, Jian-Nan; Zheng, Dong-Yang; Gu, Yang-Yang; Zhao, Wen-Ji.
Afiliación
  • Wu SQ; College of Resource Environment and Tourism, Capital Normal University, Beijing 100048, China.
  • Jin JN; College of Resource Environment and Tourism, Capital Normal University, Beijing 100048, China.
  • Zheng DY; College of Resource Environment and Tourism, Capital Normal University, Beijing 100048, China.
  • Gu YY; College of Resource Environment and Tourism, Capital Normal University, Beijing 100048, China.
  • Zhao WJ; College of Resource Environment and Tourism, Capital Normal University, Beijing 100048, China.
Huan Jing Ke Xue ; 44(12): 6441-6451, 2023 Dec 08.
Article en Zh | MEDLINE | ID: mdl-38098373
ABSTRACT
Based on the PM2.5 concentration and meteorological data of "2+26" cities, the variations in PM2.5 time series were analyzed by the continuous wavelet transform(CWT) and discrete wavelet transform(DWT). Wavelet coherence(WTC) and multiple wavelet coherence(MWC) were used to quantify the response relationship between PM2.5 and single/multiple meteorological factors in the time-frequency domain. Partial wavelet coherence(PWC) was used to quantitatively evaluate the influence of atmospheric teleconnection factors on the response relationship. The results showed that① the concentration of PM2.5 in the "2+26" cities had the spatial distribution characteristics of high in the middle area and low in the peripheral area. The PM2.5 mutation events were mainly concentrated before 2018 and mostly occurred in winter when the meteorological conditions were stable. The annual scale period of 256-512 d was relatively stable, and it was also the dominant period of the PM2.5 time series. ② The coherences between PM2.5 and meteorological factors depended on the time-frequency scale and variable combination. At all time-frequency scales, PM2.5 had strong coherences with relative humidity and temperature. At small and medium time-frequency scales, PM2.5 had strong coherences with wind speed. At large scales, PM2.5 had strong coherences with temperature. The combination of precipitation, temperature, and relative humidity could explain the variation in PM2.5 at all time-frequency scales. ③ At different time-frequency scales, the enhancement/weakening effects of atmospheric teleconnection factors on the response relationship were not the same. At all time-frequency scales, the El Niño-Southern Oscillation(ENSO) had a greater impact on the response relationship between PM2.5 and precipitation/temperature, and the Pacific decadal oscillation(PDO) had a greater impact on the response relationship between PM2.5 and relative humidity/wind speed. These results provide reference for regional air pollution control.
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Texto completo: 1 Banco de datos: MEDLINE Idioma: Zh Revista: Huan Jing Ke Xue Año: 2023 Tipo del documento: Article País de afiliación: China

Texto completo: 1 Banco de datos: MEDLINE Idioma: Zh Revista: Huan Jing Ke Xue Año: 2023 Tipo del documento: Article País de afiliación: China