Research priorities for the adverse health effects of emerging contaminants

Accelerated industrialization and urbanization have precipitated the global emergence of persistent, bioaccumulate, and toxic environmental contaminants—collectively termed emerging contaminants (ECs). These substances pose increasingly complex, transboundary, and systemic threats to public health. Therefore, they demand urgent, interdisciplinary, and innovation-driven interventions at the science–policy interface. Against this backdrop, this review synthesizes current evidence on human-exposure patterns, multi-endpoint health effects, molecular toxicodynamics, and predictive risk frameworks for ECs, and critically examines knowledge gaps and methodological limitations in existing research.In the context of China, effective EC management is hindered by fragmented evidence of life-course health effects and inadequate health-oriented regulatory infrastructure. The rapidly evolving chemical landscape and insufficient integration of health data exacerbate these challenges. To address them, we propose an integrated research framework prioritizing the following four transformative domains.(1) Advanced exposure surveillance. Multi-media, high-resolution analytical platforms and nationwide spatiotemporal monitoring networks are needed to capture dynamic EC profiles across environmental matrices and biological samples. This requires overcoming bottlenecks in ultra-trace detection and non-targeted screening, and harmonizing multi-pathway exposure assessments, particularly for vulnerable populations and high-risk occupational cohorts. Leveraging next-generation exposure measurement technologies and real-time data analytics will enable adaptive, precise monitoring and provide early warnings for EC hotspots. Such networks will enhance our ability to track and predict the spread of ECs and allow for targeted interventions.(2) Holistic health impact assessment. A transition from reductionist, single-pollutant models to systems toxicology approaches is essential. Key priorities include constructing population-scale health-effect spectra and exposome-wide biomarker panels to comprehensively account for real-world mixture exposures. Leveraging functional exposomics, integrated with longitudinal cohort studies and multi-omics technologies, will elucidate critical life-course exposure windows and latent health risks. Integrating environmental, clinical, and socio-behavioral data will enable nuanced risk stratification and tailored public health responses. This comprehensive approach will be crucial for developing effective public health strategies.(3) Mechanistic toxicology innovation. New approach methodologies (NAMs) integrating organoids, CRISPR screening, multi-omics, and computational biology can be used to explore non-monotonic dose responses, identify novel toxicity pathways, and decipher mixture interactions. Establishing a robust, open-access localized toxicological database is essential to support next-generation risk assessment and adverse outcome pathway development. Synergizing in vitro, in vivo, and in silico models will accelerate mechanism-based discovery and translational application to improve understanding of the mechanisms underlying EC effects on human health for more precise interventions.(4) Intelligent risk forecasting. Implementing artificial intelligence (AI)-driven predictive frameworks that assimilate multi-omics data streams, environmental monitoring datasets, and population health records through deep-learning architectures will facilitate real-time risk stratification, early intervention, and the development of dynamic health-based guidance values. Concurrently, quantification of EC-attributable disease burdens and intervention benefits is vital to inform evidence-based policy. AI-driven approaches can enhance the speed and accuracy of risk assessments to facilitate proactive public health measures.We advocate for paradigm shifts in environmental health research and governance from hazard identification to prevention-oriented governance, from isolated investigations to transdisciplinary convergence (e.g., exosomomics–AI integration), and from reactive regulation to anticipatory intelligence. Future efforts must prioritize high-risk ECs (e.g., per- and polyfluoroalkyl substances, microplastics, and endocrine disruptors), strengthen “big-data” national biomonitoring alongside “deep-mechanism” granular studies, and foster global data/knowledge sharing. This strategic roadmap aligns scientific rigor, digital innovation, and public health imperatives to catalyze sustainable EC mitigation, safeguard population health, and position China at the forefront of next-generation environmental governance and global stewardship. Embracing these changes will protect public health and promote a sustainable future.