Supervised machine learning approaches for predicting key pollutants and for the sustainable enhancement of urban air quality: A systematic review

I Essamlali, H Nhaila, M El Khaili - Sustainability, 2024 - mdpi.com
Urban air pollution is a pressing global issue driven by factors such as swift urbanization,
population expansion, and heightened industrial activities. To address this challenge, the …

[HTML][HTML] VAR-tree model based spatio-temporal characterization and prediction of O3 concentration in China

H Dai, G Huang, J Wang, H Zeng - Ecotoxicology and environmental safety, 2023 - Elsevier
Ozone (O 3) pollution in the atmosphere is getting worse in many cities. In order to improve
the accuracy of O 3 prediction and obtain the spatial distribution of O 3 concentration over a …

[HTML][HTML] Full-coverage spatiotemporal estimation of surface ozone over China based on a high-efficiency deep learning model

X Mu, S Wang, P Jiang, B Wang, Y Wu, L Zhu - International Journal of …, 2023 - Elsevier
Ozone concentration Monitoring is essential to atmospheric pollution prevention and control.
Against the background of severe ozone pollution over China in recent years, a …

A synchronized estimation of hourly surface concentrations of six criteria air pollutants with GEMS data

Q Yang, J Kim, Y Cho, WJ Lee, DW Lee… - Npj Climate and …, 2023 - nature.com
Abstract Machine learning is widely used to infer ground-level concentrations of air
pollutants from satellite observations. However, a single pollutant is commonly targeted in …

Understanding the variability of ground-level ozone and fine particulate matter over the Tibetan plateau with data-driven approach

H Zhong, L Zhen, L Yang, C Lin, Q Yao, Y **ao… - Journal of Hazardous …, 2024 - Elsevier
Abstract The Tibetan Plateau, known as the “Third Pole”, is susceptible to ground-level
ozone (O 3) and fine particulate matter (PM 2.5) pollution due to its unique high-altitude …

NO2-sensing proprieties of WS2/WO3 heterostructures obtained by hydrothermal treatment of tungsten oxide seed materials

MS Barbosa, DNO Barbosa, RA da Silva… - Chemical Physics …, 2023 - Elsevier
This work reports on the preparation of WS 2/WO 3 heterostructures for the development of
nitrogen dioxide (NO 2) sensors via a novel wet-chemical hydrothermal route approach …

Revisiting the impact of temperature on ground-level ozone: A causal inference approach

B Chen, L Zhen, L Wang, H Zhong, C Lin… - Science of The Total …, 2024 - Elsevier
It has been widely acknowledged that high temperatures and heatwaves promote ozone
concentration, worsening the ambient air quality. However, temperature can impact ozone …

[HTML][HTML] Causal-inference machine learning reveals the drivers of China's 2022 ozone rebound

L Wang, B Chen, J Ouyang, Y Mu, L Zhen… - Environmental Science …, 2025 - Elsevier
Ground-level ozone concentrations rebounded significantly across China in 2022,
challenging air quality management and public health. Identifying the drivers of this rebound …

Data imbalance causes underestimation of high ozone pollution in machine learning models: A weighted support vector regression solution

L Zhen, B Chen, L Wang, L Yang, W Xu… - Atmospheric …, 2025 - Elsevier
Abstract Machine learning (ML) models have been widely utilized for the prediction of
ground-level ozone (O 3), one of the most concerning air pollutants in China. However …

Estimation of near-ground ozone with high Spatio-temporal resolution in the Yangtze River Delta region of China based on a temporally ensemble model

Z Li, H Dong, Z Zhang, L Luo… - IEEE Journal of Selected …, 2023 - ieeexplore.ieee.org
Recently, the near-ground ozone pollution has become an important factor restricting
economic development and ecological environment protection. Due to the aging equipment …