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Based on the observation from Automatic Weather Stations (AWS) and atmospheric environment monitoring stations, along with ERA5 reanalysis data between 2015 and 2020, the variation characteristics of main pollutants, as well as the relationship between synoptic pattern and meteorological elements in Yuncheng, a city of the eastern Fenwei Plain are comprehensively analyzed. The results show that the annual average concentrations of PM_2.5, PM₁₀, SO₂, NO₂, and CO in the city from 2015 to 2020 show a downward trend, while the annual average concentration of O₃ shows an upward trend. The air quality in winter and summer is relatively poor, with PM_2.5 and O₃ as the major pollutant in winter and summer, respectively. There is a close relationship between the variation of Boundary Layer Height (BLH) and wind direction, wind speed and pollutant concentration in the eastern Fenwei Plain. In the winter, heavy PM_2.5 pollution usually happens on the days with low BLH and relatively small northwesterly prevailing winds. In contrast, the heavy pollution in summer usually occurs on the days with tall BLH and relatively large south-easterly prevailing winds. Finally, using the Self-Organizing Map neural (SOM) network algorithm, the synoptic patterns are identified from geopotential height fields at the height of 925 hPa in winter and summer, and the relationship between the variation of pollutant concentration and meteorological elements under different synoptic patterns are elucidated. It is shown that the weather partterns characterized by weak northeasterly prevailing winds are found to be associated with heavy PM_2.5 pollution, which is transported from the heavily polluted regions to Yuncheng, while O₃ pollution in summer is linked to the synoptic pattern featured by heat low pressure and strong radiation, which is conductive to the gathering of O₃ precursor.