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Drivers of PM 2.5 in the urban agglomeration on the northern slope of the Tianshan Mountains, China

Environmental Pollution, ISSN: 0269-7491, Vol: 309, Page: 119777
2022
  • 21
    Citations
  • 0
    Usage
  • 10
    Captures
  • 0
    Mentions
  • 0
    Social Media
Metric Options:   Counts1 Year3 Year

Metrics Details

  • Citations
    21
    • Citation Indexes
      21
  • Captures
    10

Article Description

Fine particulate matter (PM 2.5 ) is a major source of air pollution in China. Although there have been many studies of the drivers of PM 2.5 pollution in the megacities clustered in eastern China, the behavior of PM 2.5 in the northwestern urban agglomeration is not well understood. This study used near-surface observation data for 2015–2019 obtained from the national air environmental monitoring network to examine variation in PM 2.5 in the urban agglomeration on the northern slopes of the Tianshan Mountains (UANSTM). Two-factor interaction provided new insights into the dominant factors of PM 2.5 in the study region. The annual average PM 2.5 concentrations over the study period was 54.3 μg/m 3, with an exceedance rate of 23.3%. Wavelet analysis showed two dominant cycles of 320–370 d and 150–200 d with high pollution events occurring in winter. The generalized additive model (GAM) contained linear functions of pressure, non-linear functions of SO 2, NO 2, relative humidity, sunshine duration and temperature. The two most primary variables, NO 2 and SO 2, represent 20.65% and 19.54% of the total deviance explained, respectively, while the meteorological factors account for 36.1% of the total deviance explained. In addition, the interaction between NO 2 and other factors had the strongest effect on PM 2.5. The deviance explained in the two factor interaction model (88.5%) was higher than that in the single factor model (78.4%). Our study emphasized that interaction between meteorological factors and pollutant emissions enhanced the impact on PM 2.5 compared with individual factors, which can provide a scientific basis for developing effective emission reduction strategies in UANSTM.

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