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- 1Xinjiang Agricultural University, Ürümqi, China
- 2Xinjiang University, Urumqi, China
Select one of your emails
You have multiple emails registered with Frontiers:
Notify me on publication
Please enter your email address:
If you already have an account, please login
You don't have a Frontiers account ? You can register here
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
Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.
