Universitat Politècnica de Catalunya

CIMNE International Center for Numerical Methods in Engineering

Atmospheric Pollution Research is an international journal designed for the publication of articles on air pollution and atmospheric processes. Papers should present novel measurement and modeling results, theory and modeling of air pollution on local, regional, or global scales. Topics covered are research on inorganic, organic, and persistent organic air pollutants, air quality monitoring, air quality management, atmospheric dispersion and transport, air-surface (soil, water, and vegetation) exchange of pollutants, dry and wet deposition, indoor air quality, exposure assessment, health effects, satellite measurements, natural emissions, atmospheric chemistry, greenhouse gases, and effects on climate change.

Atmospheric Pollution Research

Evaluation of different machine learning approaches for predicting high concentration episodes of ground-level ozone: A case study in Catalonia, Spain

Predictive modeling of Enterococcus sp. removal with limited data from different Advanced Oxidation Processes: A Machine Learning approach

Elsevier BV

Among the various ML algorithms available, we have chosen the RF algorithm in our study due its advantages such as low computational complexity, robust predictive capabilities for unseen data (generalization), and automatic feature importance selection during training [29]. Furthermore, RF has been successfully implemented in studies related to AOP [20,23,26] and other fields [29][30][31][32]. 

C. Soriano's scientific contributions

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