Python toolkit for automated download of ERA5 daily statistics from Copernicus Climate Data Store (CDS). Simplifies climate data acquisition for research.

PCA-based network dynamics for assigning new observations to learned clusters and generating 60×60 relevancy maps (MATLAB).

Analysis of PM2.5 from 2000 to 2025 for 5 target States - California, Texas, West Virginia, Colorado New York

Short-term air quality prediction using machine learning and deep learning models, with a comparative analysis on the UCI Air Quality dataset.

Geostatistical modeling of urban air pollutants (NO₂ and PM₁₀) across Los Angeles County using the Hidden Dynamic Geostatistical Model (HDGM) framework implemented in MATLAB with the D-STEM package. Includes full data processing, model fitting, cross-validation, and spatial prediction workflow.

Análisis de series temporales de contaminantes en Seúl (2017-2020): 25 estaciones, 6 contaminantes. Limpieza de datos, detección de errores instrumentales y visualización de patrones temporales. Identificación de picos de NO₂ asociados al tráfico vehicular.

Data-driven waste management study using PySpark: explores policy, descriptions, and real-world datasets to analyze waste streams and inform sustainable interventions.

Official documentation and code examples for integrating with the LSI Lastem CUBE cloud platform via REST APIs. Access environmental monitoring data from ENVIRO-CUBE and INDOOR-CUBE applications using secure, header-based authentication. Ideal for developers building custom data pipelines or dashboards.