Management of missing air pollution data within urban environments using machine learning regressions: a case study for Delhi, India

Leveraging Remote Traffic Data for Local Air Pollutant Estimation: A Scenario-Based Machine Learning Study Across London Monitoring Sites

Vehicular traffic is a major source of air pollution; however, the contribution of remotely acquired traffic information to local machine-learning (ML) air-pollution models remains insufficiently characterised. This study evaluates four interpretable tree-based ML models (Random Forest, Extra Trees, LightGBM, and XGBoo...

Machine Learning-based Spatial Mapping of Urban-Rural Air Quality: A Case Study of Mymensingh district in Bangladesh

Air pollution is one of the most urgent environmental and social health issues in Bangladesh's rapidly urbanizing areas, but secondary cities still lack fine-scale evaluation and forecasting. This paper presents a combined PCA-machine learning-GIS model to quantify, model, and map air quality in urban and rural setting...

Overcoming data shortages through hybrid machine learning in air quality forecasting: a case study of Kağıthane, Istanbul

A hybrid machine-learning framework for AQI prediction in Kağıthane, Istanbul, Türkiye, using a long-term dataset spanning approximately ten years, thereby reducing reliance on dense sensor infrastructures and achieving overall accuracy of approximately 98%, enabling timely health advisories and more efficient allocati...

Machine-learning–driven multi-site PM2.5 forecasting in Hyderabad: spatiotemporal variability, meteorological drivers and predictive uncertainty

Data-driven air quality prediction in Navi Mumbai city using machine learning techniques

K-Means Clustering-Based Random Forest System for Air Quality Management and Pollution Reduction in Smart Cities

Rapid urbanization has significantly affected ecological sustainability, particularly in emerging nations where cities face elevated air pollution levels. The escalating demands from the WHO revised global air quality recommendations and national legislation have heightened the necessity for efficient urban air quality...