北京大学学报自然科学版 ›› 2025, Vol. 61 ›› Issue (2): 240-252.DOI: 10.13209/j.0479-8023.2024.117

上一篇    下一篇

天山北坡城市群颗粒物及臭氧时空分布及气象因素的影响

苗元露1,2, 耿春梅1, 纪元3, 谷超3,†, 王胜利2, 杨文1,†   

  1. 1. 中国环境科学研究院环境基准与风险评估国家重点实验室, 北京 100012 2. 兰州大学资源环境学院, 兰州 730000 3. 新疆维吾尔自治区生态环境监测总站, 乌鲁木齐 830000
  • 收稿日期:2024-07-15 修回日期:2024-10-16 出版日期:2025-03-20 发布日期:2025-03-20
  • 通讯作者: 谷超, E-mail: 57901436(at)qq.com, 杨文, E-mail: yangwen(at)craes.org.cn
  • 基金资助:
    新疆维吾尔自治区生态环境监测总站“新疆重污染天气应急管控能力建设”项目(2022-地方科研-1065)和“新疆大气综合观测站运维及质控保障”项目(ZZCD-2024-0401)资助

Spatial-Temporal Distribution of Particulate Matter and Ozone in the Urban Agglomeration on the Northern Slope of Tianshan Mountains and Influences of Meteorological Factors

MIAO Yuanlu1,2, GENG Chunmei1, JI Yuan3, GU Chao3,†, WANG Shengli2, YANG Wen1,†   

  1. 1. State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing 100012 2. College of Earth and Environmental Sciences, Lanzhou University, Lanzhou 730000 3. Ecological Environment Monitoring Station of Xinjiang Uygur Autonomous Region, Urumqi 830000
  • Received:2024-07-15 Revised:2024-10-16 Online:2025-03-20 Published:2025-03-20
  • Contact: GU Chao, E-mail: 57901436(at)qq.com, YANG Wen, E-mail: yangwen(at)craes.org.cn

摘要:

为探究天山北坡城市群PM2.5, PM10和O3的时空分布特征及气象因素的影响, 对该区域PM2.5, 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, PM2.5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, PM2.5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PM2.5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, PM2.5, 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PM2.5, 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。

关键词: PM2.5, PM10, O3, 时空分布, 广义可加模型(GAM), 气象因素

Abstract:

To explore the spatial-temporal distribution characteristics and meteorological factors impacts of PM2.5, PM10 and O3 in the urban agglomeration on the northern slope of Tianshan Mountains, the seasonal variation and spatial-temporal distribution pattern of PM2.5, 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, PM2.5 and PM10 were similar, showing winter > spring > autumn > summer, while O3 showed summer > spring > autumn > winter. 2) In terms of spatial pattern, PM2.5 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 PM2.5 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 PM2.5, 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 PM2.5, 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. 

Key words: PM2.5, PM10, O3, spatial-temporal distribution, generalized additive model (GAM), meteorological factors