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Separation and Identification of Conventional Microplastics from Farmland Soils
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How microplastics affect nitrogen removal in nature-based stormwater infrastructures: A machine learning and

Dehua Du1, Qiming Cheng1, Niling Zou1

  • 1School of River and Ocean Engineering, Chongqing Jiaotong University, Chongqing 400074, China.

Journal of Hazardous Materials
|May 11, 2026
PubMed
Summary

Microplastics (MPs) significantly impair nitrogen removal in nature-based stormwater infrastructures (NBSIs), primarily affecting ammonium removal. Environmental factors like pH and C/N ratio play a larger role in total nitrogen removal than microplastic properties.

Keywords:
Interpretable machine learningMeta-analysisMicroplasticsNature‑based stormwater infrastructuresNitrogen removal

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Area of Science:

  • Environmental Science
  • Water Quality Engineering
  • Ecotoxicology

Background:

  • Microplastics (MPs) are emerging contaminants impacting ecosystem functions.
  • Their effects on nitrogen removal in nature-based stormwater infrastructures (NBSIs) are not well understood.
  • NBSIs are crucial for managing stormwater runoff and improving water quality.

Purpose of the Study:

  • To systematically investigate how microplastic properties, system characteristics, and environmental conditions affect nitrogen removal in NBSIs.
  • To elucidate the stage-specific mechanisms of microplastic interference in nitrogen removal processes.
  • To identify key factors regulating nitrogen removal performance in microplastic-contaminated NBSIs.

Main Methods:

  • A meta-analysis of 19 published studies was conducted.
  • Five machine learning models (XGBoost, RF, LightGBM, MLP, KAN) were trained and evaluated.
  • SHapley Additive exPlanations (SHAP) analysis was used to determine variable importance.

Main Results:

  • Microplastics significantly interfere with ammonium-nitrogen (NH4+-N) removal, influenced by particle size, concentration, and polymer type.
  • Nitrate-nitrogen (NO3--N) removal is co-regulated by environmental factors (pH, C/N ratio) and plant species.
  • Total nitrogen (TN) removal is predominantly controlled by C/N ratio and pH (cumulative contribution > 60%), with microplastics primarily impeding nitrification.

Conclusions:

  • Environmental regulation (C/N ratio, pH) has a stronger influence on TN removal than microplastic variables.
  • Microplastics mainly disrupt the nitrification stage of nitrogen removal in NBSIs.
  • XGBoost demonstrated the highest predictive accuracy (R2 > 0.86), providing a robust model for NBSIs performance prediction.