Source apportionment of heavy metals via PMF-space auto-correlation and source-oriented human health risk assessment: identification of priority control factors

Integrated PMF-XGBoost analysis of heavy metal source contributions and associated predictor patterns in a polymetallic mining region.

Heavy metal (HM) contamination in mining-impacted soils poses persistent ecological and human health risks, yet the relationships between source contributions and associated environmental variables remain poorly understood. To address the limitations of previous studies, we used an integrated Positive Matrix Factorizat...

Source-oriented probabilistic risk assessment of sediment heavy metal(loid)s in a typical fireworks-production basin with mixed industrial and agricultural influences.

Fireworks production introduces persistent heavy metals and metalloids into river sediments, yet source-specific ecological and health risks under mixed land uses remain unclear. Here, we developed an integrated framework coupling Positive Matrix Factorization (PMF) with Fractional Moment-Maximum Entropy (FM-MEM)-based...

Source apportionment and source-oriented health risk assessment of heavy metal(loid)s in soils of Zibo City, a typical industrial City in China: insights from APCS-MLR and Monte Carlo simulation

Heavy metal contamination, source apportionment and health risk in soil-crop systems of high-geochemical-background Pb-Zn mining area

Summary Mining and smelting, combined with high-geochemical-backgrounds, cause heavy metal accumulation in soil-crop systems, endangering food-chain health. Topsoil (0–20 cm) and three local crops were sampled from Yunnan’s Huize lead-zinc mining area. Pb, Zn, Cu, Cd contamination, spatial patterns, source contribution...

PMF Coupled With Random Forest Method Reveals Detailed PM2.5 Sources and Their Synergistic Effects on Air Pollution Control

Understanding the sources of emerging PM2.5 pollution is crucial for developing effective air quality management strategies. This study combines positive matrix factorization (PMF) with random forest (RF) classification to reveal a detailed PM2.5 source identification for both day and night samples collected in Tianjin...

Quantitative source apportionment of soil heavy metals on a regional scale: Integrating input inventory, dual-isotope analysis and spatial decomposition modeling.

Quantifying the sources of soil heavy metal (HM) contaminants in mining-affected agricultural land is vital for effective pollution control and preventing food security issues. However, over large-scale agricultural regions, geogenic inputs, diffuse agricultural pollution (e.g., from fertilisation and irrigation), and...