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ORIGINAL RESEARCH article

Front. Environ. Sci.

Sec. Atmosphere and Climate

This article is part of the Research TopicRemote Sensing and Data Science for Mapping Climate Change Impacts in Mountainous RegionsView all articles

Spatiotemporal Trends and Ecological Disparities of PM2.5 and Vegetation Coverage in Anhui Province

Provisionally accepted
Yunhao  LiYunhao Li1Jia  GuoJia Guo2Chenyang  HanChenyang Han1Xiangge  WangXiangge Wang1Mingjie  ShiMingjie Shi1*
  • 1Xinjiang Agricultural University, Ürümqi, China
  • 2Xinjiang University, Urumqi, China

The final, formatted version of the article will be published soon.

Vegetation in natural ecosystems plays a significant role in regulating atmospheric PM2.5 pollution; however, systematic and comprehensive research on the spatiotemporal heterogeneity of PM2.5 and its dominant driving mechanisms in Anhui Province remains limited. To address this gap, this study utilized PM2.5 concentration and fractional vegetation cover (FVC) data with a spatial resolution of 1 km and a monthly temporal resolution from 2015 to 2023, and employed multiple analytical methods, including slope trend analysis, hotspot analysis, standard deviation ellipse, and Spearman correlation analysis, to reveal the spatiotemporal characteristics of PM2.5 and its relationship with FVC across Anhui Province.The results demonstrated a consistent downward trend in annual average PM2.5 concentrations from 2015 to 2023, indicating continuous air quality improvement. Seasonal variations displayed a periodic pattern characterized by significant increases in winter and marked decreases in summer, inversely corresponding to the seasonal variation trend of FVC. Spatially, PM2.5 pollution hotspots were predominantly concentrated in northern urban areas, whereas cold spots were primarily distributed in southern mountainous regions, and the centroid of pollution shifted southwestward. Spearman correlation analysis showed a significant negative correlation between PM2.5 and FVC at the seasonal temporal scale (r = -0.80, P < 0.01). Pixel-wise correlation analysis further indicated significant negative correlations in most regions, with mountainous areas exhibiting stronger negative correlations due to higher FVC. These findings provide theoretical support for formulating region-specific air pollution control measures and ecological planning strategies in Anhui Province.

Keywords: PM2.5, spatiotemporal evolution, Anhui Province, Fractional vegetation cover, Correlation analysis

Received: 03 Oct 2025; Accepted: 29 Nov 2025.

Copyright: © 2025 Li, Guo, Han, Wang and Shi. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

* Correspondence: Mingjie Shi

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