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中国科学院大学学报 ›› 2024, Vol. 41 ›› Issue (3): 334-344.DOI: 10.7523/j.ucas.2023.025

• 环境科学与地理学 • 上一篇    下一篇

京津冀地区大气PM2.5污染时空分布特征及成因分析

苏孟倩1,2, 石玉胜1   

  1. 1. 中国科学院空天信息创新研究院, 北京 100094;
    2. 中国科学院大学, 北京 100049
  • 收稿日期:2022-12-05 修回日期:2023-03-27 发布日期:2023-04-23
  • 通讯作者: 石玉胜,E-mail:shiys@aircas.ac.cn
  • 基金资助:
    风云三号03批气象卫星工程地面应用系统生态监测评估应用项目(第一期)(ZQC-R22227)、国家自然科学基金(42071398)、国家重点研发计划(2021YFB3901000)和中国科学院人才项目(Y8YR2200QM)资助

Spatial and temporal distribution characteristics and influential factors of PM2.5 pollution in Beijing-Tianjin-Hebei

SU Mengqian1,2, SHI Yusheng1   

  1. 1. Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, China;
    2. University of Chinese Academy of Sciences, Beijing 100049, China
  • Received:2022-12-05 Revised:2023-03-27 Published:2023-04-23

摘要: 基于PM2.5浓度数据、自然因素数据和人类活动因素数据,采用克里金插值法和统计分析法探究2017年京津冀地区13个城市大气PM2.5污染的时空分布特征,并采用相关分析模型和因子分析模型探究其成因。结果表明,京津冀地区:1)PM2.5浓度空间分布呈现“北低南高”的特点,南部和北部城市的年平均浓度梯度最高可达到64μg/m3;2)PM2.5浓度时间分布呈现“冬高夏低”、“早晚高午后低”的特点,冬季PM2.5浓度是夏季的1.3~2.8倍,四季PM2.5浓度日较差介于11~29μg/m3;3)大气PM2.5污染与自然因素关系密切。地势地形影响PM2.5的聚集、传输和扩散过程。风速、日照时数和相对湿度是影响大气PM2.5污染的主导气象因素,冬季PM2.5浓度与气象因素的相关性最强;4)大气PM2.5污染与人类活动关系密不可分,具体可归为:社会经济因素、工业污染排放因素和城市建设因素。研究结果将有助于为京津冀地区大气污染防治查漏补缺。

关键词: 京津冀地区, PM2.5, 时空分布, 相关分析, 因子分析

Abstract: The fine particulate matter PM2.5 could be harmful to human health and the atmospheric environment. Beijing-Tianjin-Hebei is one of the most serious regions in China in terms of atmospheric PM2.5 pollution. Based on PM2.5 concentrations data, natural factors data, and human activity factors data, this study used kriging interpolation and statistical analysis to explore the spatial and temporal distribution characteristics of atmospheric PM2.5 pollution in 13 cities of Beijing-Tianjin-Hebei in 2017 and then used correlation analysis models and factor analysis models to explore its influential factors. The results show that in Beijing-Tianjin-Hebei, 1) PM2.5 concentrations are low in the north and high in the south. The gradient of annual average concentrations between the southern and northern cities can reach up to 64μg/m3. 2) PM2.5 concentrations are high in winter and low in summer, high in the morning and evening, and low in the afternoon. PM2.5 concentration in winter is 1.3-2.8 times higher than in summer, and the daily differences in PM2.5 concentrations in all seasons are between 11-29μg/m3. 3) Atmospheric PM2.5 pollution is closely related to natural factors. Terrain and topography affect the processes of PM2.5 aggregation, transport, and dispersion. Wind speed, sunshine hours, and relative humidity are the dominant meteorological factors affecting atmospheric PM2.5 pollution, and PM2.5 concentrations have the strongest correlation with meteorological factors in winter. 4) Atmospheric PM2.5 pollution is closely related to human activities, which can be summarized into social economy factor, industrial pollutant discharge factor, and urban construction factor. The results of this study will help fill the gaps in air pollution prevention and control in Beijing-Tianjin-Hebei.

Key words: Beijing-Tianjin-Hebei, PM2.5, spatial-temporal distribution, correlation analysis, factor analysis

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