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July 15, 2026Applied SciencesOpen Access

The Spatiotemporal Evolution Patterns and Spatial Differentiation Mechanisms of PM2.5 Concentrations in East China Based on Multi-Source Fused Data

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Authors

YLYuwei LeiTYTiange YouJCJ K Chen

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Overview

Randomized trial reveals PM2.5 concentration trends in East China, indicating the need for tailored emission strategies.

Key Points

  • The study aims to explore the changes in PM2.5 concentrations in East China over time and identify the factors influencing these changes.
  • Integrated satellite-derived and ground-based data to construct a multi-source dataset.
  • Analyzed spatiotemporal patterns using Theil–Sen trend, Hurst index, and Moran’s I.
  • Employed geographic detector and MGWR to quantify the driving mechanisms.
  • PM2.5 concentrations declined significantly with a Sen slope of -1.29 μg m−3 a −1 to -0.03 μg m−3 a −1.
  • Strongest explanatory power for spatial variation was observed for temperature (q = 0.804) and precipitation (q = 0.724).
  • Regional differences were noted, with northern areas experiencing greater negative effects of temperature and precipitation.

Cite This Study

Lei et al. (2026) studied this question.

synapsesocial.com/papers/6a5722be88b21df87547f9c1https://doi.org/10.3390/app16147024
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