Abstract: To improve emergency rescuers’ safety and disaster response capabilities, emergency rescuers’ working efficiency assessment and safety warning were investigated. Concentration prediction and hazard level classification models for toxic and flammable gases were proposed. The human vulnerability model was used to quantitatively determine the association between lethal factors, gas concentration, and exposure time. The genetic algorithm was back-calculated using a nonlinear Gaussian model to determine gas concentration distribution prediction and hazard level classification. A human thermal model used in a wide range of ambient temperatures in disaster environments, a multi-layer fabric heat and moisture transfer model, and a skin burn model were proposed to predict typical physiological responses, heat flux, and skin burn injuries. A multi-source information fusion model was developed to predict rescuers' working effectiveness level with human physiological, psychological, and cognitive inputs. Integrating the proposed series of models of environments and physiological responses, a software platform for emergency rescuers’ working efficiency and safety warning was developed to simulate gas concentration distribution, hazard level classification, physiological responses, skin burn time and level, working efficiency level, and safety warning. This study helps transform personal protective equipment from ‘passive protection’ to ‘active protection’, solves the issues of lack of a decision-making system and insufficient integration of multi-source information in emergency rescue, and provides theoretical and software support for scientific rescue.

Key words: personal protection, emergency rescuers, working efficiency assessment, safety warning, personal protective clothing