Establishing a partition interpolation method for PAHs in site soil based on different pollution causes

Area of Science:

• Environmental Science
• Geochemistry
• Soil Science

Background:

• Polycyclic Aromatic Hydrocarbons (PAHs) are recognized carcinogens.
• Accurate spatial distribution data is crucial for soil pollution control.
• High PAH concentrations (outliers) hinder predictive accuracy.

Purpose of the Study:

• To analyze spatial distribution and influencing factors of specific PAHs (FLT, BaP, BbF, InP).
• To develop a novel partition interpolation method to address outlier challenges.
• To enhance the accuracy of PAH spatial distribution prediction in contaminated sites.

Main Methods:

• Geostatistical analysis and geodetectors.
• Solute transport models for outlier zones.
• Multiple linear regression for non-outlier zones.
• Development of a new partition interpolation method.

Main Results:

• Benzo[a]pyrene (BaP) exceeded thresholds more frequently than other PAHs.
• Outliers were concentrated in coking areas and wastewater treatment stations, linked to leaks.
• Atmospheric deposition was the primary driver in non-outlier zones.
• The new method reduced RMSE by over 90% compared to traditional methods.

Conclusions:

• The developed partition interpolation method effectively models PAH spatial distribution, even with outliers.
• This approach improves prediction accuracy for site soil remediation planning.
• Understanding outlier sources (leaks) and background drivers (atmospheric deposition) is key for effective PAH management.