Exploring the Spatio-Temporal Dynamics and Factors Influencing PM<sub>2.5</sub> in China’s Prefecture-Level and Above Cities
Fine particulate matter (PM<sub>2.5</sub>) plays a major role in haze, and studying its spatio-temporal dynamics and influencing factors is crucial for improving air quality. However, previous studies have often obscured the spatio-temporal interactions of PM<sub>2.5</sub> an...
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| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2025-06-01
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| Series: | Remote Sensing |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2072-4292/17/13/2212 |
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| Summary: | Fine particulate matter (PM<sub>2.5</sub>) plays a major role in haze, and studying its spatio-temporal dynamics and influencing factors is crucial for improving air quality. However, previous studies have often obscured the spatio-temporal interactions of PM<sub>2.5</sub> and neglected local spatio-temporal differences in influencing factors. To address these limitations, this research utilized PM<sub>2.5</sub> concentration data derived from satellite remote sensing and employed exploratory spatio-temporal data analysis (ESTDA) methods to investigate the spatio-temporal evolution patterns of PM<sub>2.5</sub> in Chinese cities from 2000 to 2021. Furthermore, the effects of natural environmental and socioeconomic factors on PM<sub>2.5</sub> were analyzed from both global and local perspectives using a spatial econometric model and the geographically and temporally weighted regression (GTWR) model. Key findings include (1) The annual value of PM<sub>2.5</sub> from 2000 to 2021 ranged between 27.4 and 42.6 µg/m<sup>3</sup>, exhibiting a “bimodal” variation trend and phased evolutionary characteristics. Spatially, higher concentrations were observed in the central and eastern regions, as well as along the northwestern border, while lower concentrations were prevalent in other areas. (2) The spatial–temporal distribution of PM<sub>2.5</sub> was generally stable, demonstrating a strong spatial dependence during its growth process, with significant path dependence characteristics in local spatial clusters of PM<sub>2.5</sub>. (3) Precipitation, temperature, wind speed, and the Normalized Difference Vegetation Index (NDVI) significantly reduced PM<sub>2.5</sub> levels, whereas relative humidity, per capita Gross Domestic Product (GDP), industrialization level, and energy consumption exerted positive effects. These factors exhibited distinct local spatio-temporal variations. These findings aim to provide scientific evidence for the implementation of coordinated regional efforts to reduce air pollution across China. |
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| ISSN: | 2072-4292 |