Envisioning AI-empowered ecological, environmental, and health protection: Welcome submissions of interdisciplinary research

Eco-Environmental systems are dynamic and interconnected, while health outcomes often arise from multi-scale interactions among exposure and biological response.The increasing uncertainty of climate change, the expansion of chemical use, together with the growing burden of long-term, low-dose and mixture exposures are challenging conventional research paradigms.AI offers new opportunities to integrate environmental monitoring, exposure assessment, chemical analysis, toxicological evidence and cohort data, thereby supporting early prediction, deep mechanistic understanding and proactive risk prevention.Recent advances in deep learning, generative AI, large language models and AI agents are shifting environmental and health research from isolated analysis toward integrated prediction, reasoning and decision support.AI technologies can link remote sensing images, monitoring networks, chemical structures, spectral data, toxicological assays, omics profiles, epidemiological data and scientific literature into more comprehensive knowledge systems.More importantly, they may enable environmental and health protection to move beyond retrospective assessment toward early warning, source prevention, intelligent control and adaptive governance.In this context, the journal Eco-Environment & Health (EEH) is committed to bridging AI, ecology, environmental science and technology, chemistry, toxicology and