Fine particulate matter (PM2.5) is a major source of air pollution in China. Although there have been many studies of the drivers of PM2.5 pollution in the megacities clustered in eastern China, the behavior of PM2.5 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 PM2.5 in the urban agglomeration on the northern slopes of the Tianshan Mountains (UANSTM). Two-factor interaction provided new insights into the dominant factors of PM2.5 in the study region. The annual average PM2.5 concentrations over the study period was 54.3 μg/m3, 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 SO2, NO2, relative humidity, sunshine duration and temperature. The two most primary variables, NO2 and SO2, 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 NO2 and other factors had the strongest effect on PM2.5. 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 PM2.5 compared with individual factors, which can provide a scientific basis for developing effective emission reduction strategies in UANSTM.
Keywords: Generalized additive model; PM(2.5); Urban agglomeration on the northern slope of tianshan mountains (UANSTM); Wavelet analysis.
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