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Updated: Jun 28, 2025

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[Ozone Sensitivity Analysis in Urban Beijing Based on Random Forest].

Hong Zhou1, Ming Wang1, Wen-Xuan Chai2

  • 1Collaborative Innovation Center of Atmospheric Environment and Equipment Technology, Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution Control, School of Environmental Science and Engineering, Nanjing University of Information Science & Technology, Nanjing 210044, China.

Huan Jing Ke Xue= Huanjing Kexue
|April 17, 2024
PubMed
Summary

This study analyzed ozone (O3) and its precursors in Beijing, finding that temperature and nitrogen oxides (NOx) significantly impact O3 levels. The research indicates Beijing

Keywords:
BeijingO3-VOCs-NOx sensitivitySHAP valueozone（O3）random forest （RF）

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Area of Science:

  • Atmospheric Chemistry and Air Pollution
  • Environmental Science
  • Data Science and Machine Learning Applications

Context:

  • Ozone (O3) pollution is a significant environmental challenge, particularly in urban areas.
  • Understanding the complex, non-linear relationship between O3 and its precursors, volatile organic compounds (VOCs) and nitrogen oxides (NOx), is crucial for effective control strategies.
  • Previous studies often rely on traditional models, necessitating exploration of advanced methods for improved accuracy.

Purpose:

  • To analyze the pollution characteristics of O3 and its precursors in Beijing using observational data.
  • To identify key factors influencing O3 formation using the Random Forest (RF) model and SHAP values.
  • To determine the O3-VOCs-NOx sensitivity regime in urban Beijing through multi-scenario analysis.

Summary:

  • Observational data from Beijing revealed significant positive correlations between O3 and temperature (T), and daily TVOCs and NOx, while hourly O3 showed negative correlations with TVOCs and NOx.
  • The RF model accurately simulated O3 concentrations, with SHAP values indicating T and NOx as the most influential factors (positive and negative effects, respectively).
  • Multi-scenario analysis using the RF model and an observation-based box model (OBM) confirmed that urban Beijing operates under a VOCs-limited regime for O3 formation.

Impact:

  • The study demonstrates the effectiveness of the RF model combined with SHAP values as a complementary tool for O3-VOCs-NOx sensitivity analysis.
  • Findings provide critical insights for developing targeted O3 prevention and control measures in Beijing.
  • The research contributes to a better understanding of atmospheric chemistry and pollution dynamics in rapidly developing urban environments.