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Open access Aug 2026

Machine Learning-Based Estimation of Surface PM2.5 in Nigeria Using Integration of Satellite, Ground Observations and Reanalysis Data

It is demonstrated that multi-source machine learning data fusion substantially improves surface PM2.5 estimation over Nigeria with scalable framework and identifies relative humidity as the dominant predictor, followed by MERRA-2 PM2.5.

M. Sani, Anass Houdou, R. Sa'id · 0 citations
Conference 2026

Mapping seasonal PM2.5 distribution in Novi Sad: From sensor-based observations to land use regression modelling

Air pollution in Serbia is characterized by pronounced seasonal variability, with the heating period representing the most critical phase in terms of fine particulate matter (PM2.5). Understanding both short-term dynamics and the spatial distribution of PM2.5 in urban environments remains a key challenge. This study fo...

Sonja Dmitrašinović, Miljan Šunjević, Maja Brborić et al. · 0 citations
Open access Sep 2026

Dynamics of the spatiotemporal correlation between Aerosol Optical Depth satellite data and PM2.5 surface monitoring: An exploratory approach

PM2.5 is a major air pollutant with diverse natural and anthropogenic sources, which significantly impacts human health and the environment. Remote sensing serves as a complementary resource for air-monitoring networks, providing valuable information on the spatiotemporal patterns of air pollutants at a global scale Th...

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Aug 2026

Evaluating the suitability of sentinel-5P satellite data for air quality monitoring in Tehran.

This study evaluates the applicability of Sentinel-5P TROPOspheric Monitoring Instrument (TROPOMI) satellite observations for air quality monitoring in Tehran, a megacity characterized by complex topography and persistent air pollution challenges. A comprehensive comparison was conducted between ground-based measuremen...

Amir Mohammad Kafi, Mahdi Hosseinipoor, M. Z. Shahne · 0 citations
Open access Sep 2026

Satellite-Based Seasonal Monitoring of PM2.5-Related Trace Gases and Aerosol Loading over the Lazio Region

Ground-based monitoring networks often provide uneven spatial coverage, limiting the characterization of air-quality in heterogeneous regions. This study proposes a data-driven framework that identifies spatially coherent atmospheric regimes from multi-gas satellite observations. The framework is applied to investigate...

Flaminia Fois, Valentina Terenzi, P. Tratzi et al. · 0 citations
Open access Aug 2026

Model Estimation of Ground-based PM2.5 Concentration Over Nigeria and Its Assessment Using MERRA-2 Reanalysis

Accurate estimation of fine particulate matter (PM2.5) remains a major challenge in data-sparse regions such as West Africa because of limited ground-based monitoring networks and highly variable atmospheric conditions. This study evaluated statistical and machine-learning models for predicting ground-level PM2.5 conce...

M. Sani, R. Sa'id · 0 citations

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