According to Sawyer Merritt, researchers have leveraged AI-powered analysis of satellite data to monitor nitrogen dioxide (NO₂) levels in California. As reported, the study found that increased adoption of electric vehicles and plug-in hybrids significantly reduced NO₂ concentrations in densely populated urban areas. This demonstrates the practical application of AI in environmental monitoring and highlights business opportunities for AI-driven air quality analytics as cities prioritize clean transportation solutions.

According to DeepLearning.AI, Google has launched AlphaEarth Foundations, a comprehensive set of AI-driven time embeddings representing every 10-meter square of Earth from 2017 to 2024. These embeddings are trained using optical, radar, and thermal satellite data, and further aligned with geotagged text, enabling precise tracking of global climate, land use, vegetation, and water resources. The dataset is available for free download under the CC BY 4.0 license, and Google is offering grants to teams that leverage this data for AI research and development. This release presents significant opportunities for businesses and researchers in climate technology, environmental monitoring, and geospatial AI applications (Source: DeepLearning.AI on Twitter, Oct 9, 2025).