Abstract: Based on the data of PM_2.5 and PM₁₀ from air quality monitoring stations and national meteorological stations in Lhasa from 2018 to 2022, the multi-time scale variation characteristics of PM_2.5, PM₁₀ and PM_2.5/PM₁₀ and their relationships with wind speed, relative humidity and precipitation were comprehensively analyzed by means of mathematical statistics and correlation analysis methods. The results indicate that the average annual concentration of PM₁₀ and PM_2.5 showed a significant decreasing trend (5.88 μg·m⁻³/ year and 1.57 μg·m⁻³/ year, respectively). The seasonal changes were lower in summer and autumn, higher in winter and spring, with the order being winter > spring > autumn > summer. The monthly variation showed a significant U-shaped distribution, with the low value area appearing from June to October, and the high value area from November to May of the following year. The diurnal variation characteristics were characterized by double peaks and double valleys. The peak-to-trough ratios for PM₁₀ and PM_2.5 reached 2.44 and 2.22, respectively, with significant peak-valley variation characteristics. Meteorological conditions significantly influenced the concentration distribution of particulate matter. Among them, wind speed showed a strong negative correlation with PM_2.5 concentration distribution, but a weak negative correlation with PM₁₀. Relative humidity had a significant negative correlation with PM₁₀ and PM_2.5 concentration distribution, and the influence of relative humidity was most significant in autumn. Precipitation had a significant negative correlation with the concentration distribution of PM₁₀ and PM_2.5, and the average clearance rates were 4.18% and 3.11%, respectively.