[Publication] GRASP contribution to Environmental Mining, a novel approach for open-pit PM10 emission monitoring

GRASP’s role in advancing remote sensing for PM2.5–10

GRASP technology was applied to process data from Sentinel-3/OLCI, Sentinel-5P/TROPOMI, and PARASOL/POLDER. The algorithm retrieved particulate matter properties with resolutions down to 300 m, enabling unprecedented detail in the spatial characterization of PM2.5 and PM10 around mining sites. The results confirmed the capacity of GRASP-based retrievals to detect gradients and emission hotspots, providing independent datasets that complement ground-based monitoring.

Integration of methodologies

The study highlights the complementarity of three approaches. Inverse modelling provided improved emission factors for blasting in copper mines, overcoming the overestimations typical of standard databases. Machine learning nowcasting (Temporal Fusion Transformer) produced short-term forecasts of PM concentrations, enhancing operational management. GRASP retrievals supplied independent, high-resolution spatial data that broaden the coverage and reinforce the robustness of conclusions.

Outlook for environmental mining

This work illustrates how the integration of modelling, machine learning, and satellite remote sensing establishes a powerful framework for environmental mining. GRASP’s unique capacity to deliver satellite-based PM2.5–10 retrievals of high accuracy and resolution strengthens scientific tools for evaluating mining impacts. In doing so, GRASP contributes directly to evidence-based strategies for balancing industrial activity with sustainability and public health protection.