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DOI: https://doi.org/10.7523/j.ucas.2025.063

京津冀城市群PM2.5浓度的时空动态及驱动机制分析研究*

  • 肖睿 ,
  • 黄庆旭 ,
  • 于佳睿 ,
  • 王艺锦 ,
  • 眭颖菲 ,
  • 郭文达
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  • 1.地表过程与水土风沙灾害风险防控全国重点实验室,北京师范大学地理科学学部,北京, 100875;
    2.北京师范大学地理科学学部自然资源学院,北京, 100875
†E-mail：qxhuang@bnu.edu.cn

收稿日期: 2025-05-29

  修回日期: 2025-12-22

  网络出版日期: 2025-12-29

基金资助

*北京市科技新星项目（20220484163）和北京师范大学唐仲英青年学者项目资助

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Spatiotemporal dynamic and driving mechanisms of PM2.5 concentration in the Beijing-Tianjin-Hebei urban agglomeration

  • XIAO Rui ,
  • HUANG Qingxu ,
  • YU Jiaui ,
  • WANG Yijin ,
  • SUI Yingfei ,
  • GUO Wenda
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  • 1. State Key Laboratory of Earth Surface Processes and Hazards Risk Governance (ESPHR), Faculty of Geographical Science, Beijing Normal University, Beijing, 100875, China;
    2. School of Natural Resources, Faculty of Geographical Science, Beijing Normal University, Beijing, 100875, China

Received date: 2025-05-29

  Revised date: 2025-12-22

  Online published: 2025-12-29

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摘要

PM2.5污染对大气环境和人类健康造成严重危害,而供暖季与全年PM2.5污染特征及其驱动机制的差异性尚未得到充分研究。本研究基于20002021年京津冀地区PM2.5浓度遥感数据,运用曼-肯德尔趋势检验、Pettitt检验、逐步回归和方差分解分析等方法,在全年、供暖季与非供暖季尺度下系统分析了PM2.5浓度的时空演变特征及其驱动机制差异。研究结果表明：过去21年,京津冀地区PM2.5年均浓度呈现先增后减的变化趋势;供暖季PM2.5浓度整体比全年平均高 3.3% 到 45.1%。空间上,PM2.5浓度呈现显著的“南高北低”分布特征,浓度梯度明显。驱动机制方面,社会经济因素在所有时间尺度下均占主导地位,其中第二产业占比和人口密度的影响最为显著。人口密度与温度之间的交互作用最为显著,且在供暖季下更为明显,二产占比与温度之间也存在较为显著的交互作用,但供暖季略低于非供暖季。未来,建议强化供暖季污染精准治理,建立分时响应管控机制,并完善区域协同治理体系。

关键词： 京津冀城市群; 空气污染; 雾霾; 城市可持续发展

本文引用格式

肖睿 , 黄庆旭 , 于佳睿 , 王艺锦 , 眭颖菲 , 郭文达 . 京津冀城市群PM2.5浓度的时空动态及驱动机制分析研究*[J]. 中国科学院大学学报, 0 : 251228 . DOI: 10.7523/j.ucas.2025.063

Abstract

PM2.5 pollution causes severe harm to the atmospheric environment and human health, yet the differences in PM2.5 pollution characteristics and driving mechanisms between the heating season and annual periods remain insufficiently studied. Based on remotely sensed PM2.5 concentration data from 2000 to 2021 in the Beijing-Tianjin-Hebei region, this study uses Mann-Kendall (MK) trend test, Pettitt test, stepwise regression, and Variance Partitioning Analysis (VPA) to systematically analyze the spatiotemporal evolution characteristics of PM2.5 concentrations and differences in their driving mechanisms across annual, heating season, and non-heating season temporal scales. The results show that over the 21-year study period, the annual average PM2.5 concentration in the Beijing-Tianjin-Hebei region exhibited an initial increase followed by a subsequent decrease; heating season PM2.5 concentrations were overall 3.3% to 45.1% higher than the annual average. Spatially, PM2.5 concentrations displayed a significant “high in the south and low in the north” distribution pattern with distinct concentration gradients. Regarding driving mechanisms, socioeconomic factors dominated across all time scales, with the proportion of secondary industry and population density having the most significant influence. The interaction between population density and temperature exhibited the strongest effect, which was more pronounced during the heating season; a relatively significant interaction also existed between the proportion of secondary industry and temperature, but this effect was slightly weaker during the heating season compared to the non-heating season. Based on these findings, it is recommended to strengthen precise pollution control during the heating season, establish time-specific response control mechanisms, and improve the regional collaborative governance system.

Key words： Beijing-Tianjin-Hebei urban agglomeration; air pollution; fog and haze; sustainable urban development

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