Spatiotemporal Evolution and Influencing Factors of Air Pollutants in the Three Major Urban Agglomerations of the Yellow River Basin

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Authors: Yanli Yin, Fan Zhang, Qifan Wu, Linan Sun, Yuanzheng Li, Peng Wang, Zilin Liu, Tian Cui, Zhaomeng Zhou, Runjing Hou, Mingyang Zhang, Jinping Liu
+1 more Qingfeng Hu
Cited by: 1
References: 75

Abstract

Against the backdrop of the ongoing advancement of China’s dual-carbon goals and the coordinated strategy for ecological protection and high-quality development in the Yellow River Basin (YRB), it is important to clarify the spatiotemporal dynamics of air pollution in the densely populated urban agglomerations of the mid–lower YRB. Using station-based daily observations from 2015 to 2024, this study examines six major air pollutants (PM2.5, PM10, CO, NO2, O3 and SO2) across the Shandong Peninsula, Central Plains, and Guanzhong Plain urban agglomerations. Sen’s slope estimator and the Mann–Kendall test are applied to quantify long-term trends, while partial correlation analysis and the GeoDetector model are used to diagnose pollutant co-variations and the drivers of spatial heterogeneity. Results indicate that while PM2.5, PM10, NO2, SO2, and CO concentrations significantly decreased, O3 exhibited a statistically significant upward trend (Z = 2.32, p = 0.02), particularly with pronounced summer maxima. PM2.5 shows clear seasonal variation, with elevated levels during winter and reduced levels during summer. Marked spatial contrasts are also observed: elevated particulate matter and CO are concentrated in the northern part of the Central Plains, while higher O3 levels are more evident in coastal areas, particularly within the Shandong Peninsula urban agglomeration. In terms of inter-pollutant relationships, particulate matter and CO are positively associated with SO2, whereas O3 is negatively correlated with NO2. GeoDetector results further suggest that air temperature, wind speed, and topography are the key factors associated with the spatial differentiation of pollutant levels; notably, the interaction between wind speed and temperature provides the greatest explanatory power, with effects that vary seasonally. These findings provide a scientific basis for region-specific air-pollution control and for advancing the co-benefits of carbon reduction and pollution mitigation in the YRB.

Fields of Study & Subjects

Atmospheric chemistry and aerosols Air Quality and Health Impacts Urban Heat Island Mitigation

Publication details

Journal / source
Atmosphere
Publisher
MDPI AG
Volume
17
Issue
3
Pages
242–242
Publication date
26 February 2026
Language
EN