Air pollution is a major global health threat, contributing to millions of premature deaths annually and driving chronic respiratory diseases such as asthma, COPD, and lung cancer. This presentation demonstrates how satellite remote sensing and GIS provide powerful, scalable tools for monitoring atmospheric pollutants and assessing their health impacts. Modern satellite missions—including Sentinel‑5P, MODIS, MISR, VIIRS, and upcoming MAIA—enable high‑resolution detection of aerosols and trace gases (PM₂.₅, PM₁₀, NO₂, SO₂, O₃), while GIS integrates these observations with meteorological, land‑use, and health data to model surface exposure and identify vulnerable populations. Analytical methods such as spatiotemporal kriging, land‑use regression, and machine learning enhance exposure estimation, and WebGIS platforms support real‑time visualization, early warning systems, and risk communication. Case studies highlight the role of urban morphology, environmental justice, and anthropogenic activity—such as mobility reductions during COVID‑19 lockdowns—in shaping pollution patterns. The work underscores the importance of satellite‑GIS fusion for respiratory disease surveillance, policy development, and equitable public‑health interventions.