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Object <p>This study evaluates the environmental impact of petroleum oil contamination in soil using an integrated mathematical and metabolomics approach. The aim was to determine the phytotoxicity and spatial dispersion of petroleum pollutants.</p> Methods <p>Soil samples were collected from four distances relative to the contamination source: S1 (at the source), S2 (1&#xa0;m away), S3 (3&#xa0;m away), and S4 (5&#xa0;m away). Metabolomic analysis focused on primary metabolites of plants, specifically alpha-amylase and protease, using MetaboAnalyst and supervised partial least squares (PLS) techniques. Additionally, mathematical models were used to compute growth parameters and germination velocity.</p> Results <p>The analysis revealed that the standard error of the mathematical model decreased as petroleum hydrocarbon concentration increased (S1 to S4), indicating a more pronounced toxic effect on germination with higher contamination levels. Principal component analysis showed that Treatment S4 had the highest metabolite concentrations, while S1 had the lowest due to higher contamination. The analysis using GC-MS of the contaminated soil shows the presence of 12 different hazardous hydrocarbons which include tetradecane, tridecane, and hexadecane. The presence of these compounds poses serious threats to both human and environmental health. Heat map analysis demonstrated a decreasing order of metabolite levels: S4 ≥ S3 ≥ S2 ≥ S1.</p> Conclusion <p>Integrated approach combining mathematics and metabolomics provides an efficient method for assessing the ecological toxicity of petroleum-contaminated soils, highlighting its commercial potential for environmental monitoring.</p>

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Spatial and toxicological impacts of petroleum contamination in soil: insights from integrated mathematical and metabolomic approaches

  • 期刊论文

  • 发表日期：

    2025年11月3日

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  • Amar Jyoti Das,
  • Souvik Kumar Paul,
  • Rajesh Kumar,
  • Shweta Ambust,
  • Debashish Ghosh

摘要

Object

This study evaluates the environmental impact of petroleum oil contamination in soil using an integrated mathematical and metabolomics approach. The aim was to determine the phytotoxicity and spatial dispersion of petroleum pollutants.

Methods

Soil samples were collected from four distances relative to the contamination source: S1 (at the source), S2 (1 m away), S3 (3 m away), and S4 (5 m away). Metabolomic analysis focused on primary metabolites of plants, specifically alpha-amylase and protease, using MetaboAnalyst and supervised partial least squares (PLS) techniques. Additionally, mathematical models were used to compute growth parameters and germination velocity.

Results

The analysis revealed that the standard error of the mathematical model decreased as petroleum hydrocarbon concentration increased (S1 to S4), indicating a more pronounced toxic effect on germination with higher contamination levels. Principal component analysis showed that Treatment S4 had the highest metabolite concentrations, while S1 had the lowest due to higher contamination. The analysis using GC-MS of the contaminated soil shows the presence of 12 different hazardous hydrocarbons which include tetradecane, tridecane, and hexadecane. The presence of these compounds poses serious threats to both human and environmental health. Heat map analysis demonstrated a decreasing order of metabolite levels: S4 ≥ S3 ≥ S2 ≥ S1.

Conclusion

Integrated approach combining mathematics and metabolomics provides an efficient method for assessing the ecological toxicity of petroleum-contaminated soils, highlighting its commercial potential for environmental monitoring.