To explore the spatial-temporal distribution characteristics and meteorological factors impacts of PM_2.5, PM₁₀ and O₃ in the urban agglomeration on the northern slope of Tianshan Mountains, the seasonal variation and spatial-temporal distribution pattern of PM_2.5, PM₁₀ and O₃ were analyzed. Pearson correlation analysis method and generalized additive model (GAM)were used to explore the influence of meteorological factors on atmospheric pollutants. The results showed that 1) in terms of time distribution, PM_2.5 and PM₁₀ were similar, showing winter > spring > autumn > summer, while O₃ showed summer > spring > autumn > winter. 2) In terms of spatial pattern, PM_2.5 and PM₁₀ generally showed a pattern of low in the west and high in the east, and the high concentration area of O₃ was mainly in the Tianshan Tianchi area and Shihezi City in Fukang City. 3) The regional PM_2.5 and PM₁₀ showed significant positive spatial autocorrelation, with high-high agglomeration in the east and low-low agglomeration in the west. 4) Correlation analysis and GAM model showed that PM_2.5, PM₁₀ and O₃ had significant nonlinear response relationship with temperature, humidity, wind speed, air pressure and daily rainfall. The interaction terms between temperature and other meteorological factors all passed the significance test, indicating that there was a significant interaction effect on the influence of PM_2.5, PM₁₀ and O₃. This study presented new conclusions on the mechanism of the influence of meteorological factors on air pollutants in the northern slopes of the northern slope of Tianshan Mountains, as well as an scientific basis for the development of regional air quality management strategies in the region. 

为探究天山北坡城市群PM_2.5, PM₁₀和O₃的时空分布特征及气象因素的影响, 对该区域PM_2.5, PM₁₀和O₃的季节变化特征和时空分布格局进行分析。采用皮尔逊相关性分析和广义可加模型GAM, 揭示气象因子与污染物之间复杂的非线性响应及其交互效应。研究结果表明: 1) 在时间分布上, PM_2.5和PM₁₀均呈现冬季>春季>秋季>夏季的特征, 而O₃呈现夏季>春季>秋季>冬季的特点; 2) 在空间格局上, PM_2.5和PM₁₀总体上呈现西低东高的格局, O₃高值集中在阜康市内的天山天池周边以及石河子市; 3) 区域PM_2.5和 PM₁₀表现出显著的正空间自相关性, 在东部呈现高–高集聚, 在西部呈现低–低聚集; 4) 相关性分析及GAM模型表明, PM_2.5, PM₁₀ 和O₃与温度、湿度、风速、气压和日降雨量5个气象因素均呈现显著的非线性响应关系。温度与其他气象因子两两间的交互项均通过显著性检验, 表明温度和其他气象因素对PM_2.5, PM₁₀和O₃的影响有显著的交互效应。研究结果为天山北坡区域气象因素对大气污染物影响机制提供了新认识, 可为制定天山北坡地区的区域性空气质量管理策略提供科学依据。