Abstract
Compound environmental hazards are becoming more frequent as extreme heat, air pollution, and other atmospheric stressors increasingly coincide within populated regions. Early warning systems (EWSs) can reduce these risks only when compound events are clearly defined, forecast with uncertainty, and translated into actionable warning products. This systematic review examines technological advances in compound-event generation for EWS frameworks, with particular attention to heat and air pollution. The review synthesises methods across three connected stages: operational event definition, joint hazard and impact forecasting, and risk communication. Current studies generate compound events through fixed or percentile-based threshold overlap, impact-based interaction models, coupled meteorology-chemistry forecasting, artificial intelligence and machine-learning models, unified risk indices, and probabilistic trigger rules. The evidence shows rapid progress in each stage, but also a persistent integration gap: definitions, forecasts, uncertainty estimates, and public warning triggers are often developed separately. The review proposes a taxonomy and research agenda for more coherent compound-event EWS design, emphasizing shared compound-risk targets, uncertainty-aware model fusion, impact-based warning thresholds, and end-to-end validation against health and service outcomes.