Full
Outline
In this study, based on the urban statistical yearbook and multi-source remote sensing data—including pollutant concentrations, nighttime light intensity, and land cover—the spatiotemporal distribution characteristics of PM2.5-O3 compound pollution across 274 prefecture-level cities in China were examined from an integrated perspective of meteorological, socioeconomic, and urban form factors. The results showed that from 2005 to 2020, PM2.5 concentrations in Chinese cities followed a 'rise-then-fall' trend, while O3 exhibited a 'rise-fall- rise' trend. Both the spatial distribution and the synergistic relationship between PM2.5 and O3 displayed pronounced regional heterogeneity. High PM2.5 concentrations were mainly concentrated in the North China Plain, whereas high O3 concentrations occurred in both the North China Plain and the eastern coastal urban agglomerations. Positive correlations between PM2.5 and O3 concentrations were predominant in the humid regions of southern and northeastern China, while negative correlations were more common in the semi-humid and semi-arid regions of northern China. Geodetector analysis revealed that the spatial differentiation drivers of PM2.5 and O3 concentrations was primarily shaped by urban form factors, followed by meteorological and socioeconomic conditions. Specifically, PM2.5 concentrations were strongly influenced by the proportion of ecological space (q=0.627) and agricultural land (q=0.610), whereas O3 concentrations were significantly affected by the proportion of ecological space (q=0.512) and topography (q = 0.466). The synergistic relationship between PM2.5 and O3 was mainly controlled by the single factors such as precipitation (q=0.396) and temperature (q=0.374), with significant enhancement observed under dual-factor interactions, such as temperature-topography (q=0.718) and precipitation-Shannon's evenness index (q=0.708). These findings highlight the nonlinear synergistic effects arising from the coupling of 'urban form constraints' and 'meteorological disturbances' on PM2.5-O3 compound pollution, and provide a scientific basis for the precise and coordinated prevention and control of such pollution.
90
13
| 科 Family | 属数 Number of genus | 种数 Number of species | 占总种数比例 Percentage of total species (%) | 属 Genus | 种数 Number of species | 占总种数比例 Percentage of total species (%) |
|---|---|---|---|---|---|---|
| 鹅膏菌科Amanitaceae | 2 | 11 | 5.26 | 鹅膏菌属 Amanita | 10 | 4.78 |
| 小菇科 Mycenaceae | 2 | 12 | 5.74 | 丝盖伞属 Inocybe | 5 | 2.39 |
| 多孔菌科 Polyporaceae | 8 | 14 | 6.70 | 蜡蘑属 Laccaria | 5 | 2.39 |
| 红菇科 Russulaceae | 3 | 23 | 11.00 | 小皮伞属 Marasmius | 6 | 2.87 |
| 小菇属 Mycena | 11 | 5.26 | ||||
| 光柄菇属 Pluteus | 5 | 2.39 | ||||
| 红菇属 Russula | 17 | 8.13 | ||||
| 栓菌属 Trametes | 5 | 2.39 |
关闭全屏
No. 86 Xueyuan South Road, Haidian District, Beijing
010-62662699(Operation and Technical Support)
qkjq@cast.org.cn
Copyright © 2025 China Association for Science and Technology. All rights reserved. For all open access content, the relevant licensing terms apply.
Sponsored by the Office of the Leading Group for Cybersecurity and Informatization of CAST, and supported by Science and Technology Review Publishing House
