AI Enhances Environmental Risk Assessment and Climate Action

Artificial intelligence is reshaping chemical exposomics by moving from a mere discovery engine to a functional prediction tool. Researchers propose assigning a biological‑activity risk score to each detected chemical, allowing scientists to prioritize compounds for laboratory testing and health‑risk assessment. The approach integrates high‑resolution mass‑spectrometry data, toxicology databases and machine‑learning models, though challenges remain around data quality, mixtures and model interpretability. “The future of exposomics is not only about discovering what chemicals are present, but also predicting what those chemicals may do inside biological systems,” said corresponding author Hemi Luan of Guangdong University of Technology.

AI is also being applied to climate intelligence, enabling precise monitoring of land, water and biodiversity at resolutions as fine as 10–15 cm. Companies such as Treefera use the technology to illuminate the “first kilometer” of supply chains, where most costs and environmental impacts occur. Emphasising frugality, they aim to ensure that the environmental benefits of AI‑driven actions outweigh the energy and resource costs of the underlying digital infrastructure. According to Caroline Gray, this shift allows stakeholders to act where it matters most, rather than merely model risk.