Workplace accidents pose a serious threat to people’s lives and property and hinder social and economic development. Among these accidents, fire accidents are typical due to their sudden occurrence and severe consequences. To better understand accident evolution laws and improve risk prevention, this study analyzes the characteristics of typical national fire accidents based on 2015–2024 accident statistics. A linear-nonlinear combined Autoregressive Integrated Moving Average-Long Short-Term Memory (ARIMA-LSTM) model is established to predict trends of the number of national overall workplace accidents, deaths, injuries, and direct economic losses, and it is compared with Autoregressive Integrated Moving Average (ARIMA), Long Short-Term Memory (LSTM), Seasonal Autoregressive Integrated Moving Average (SARIMA), and Seasonal Autoregressive Integrated Moving Average-Long Short-Term Memory (SARIMA-LSTM) models. The results show that the ARIMA-LSTM model integrates the strengths of linear fitting and nonlinear learning, with stronger explanatory power and higher prediction accuracy, as reflected by lower Mean Squared Error (MSE), Root Mean Squared Error (RMSE), and Mean Absolute Error (MAE) values. This study provides technical support for the precise prevention and control of fire accidents, trend prediction of work safety accidents, and helps to establish a scientific and forward-looking safety risk prevention and control system.

Cellulose-based aerogels are promising sustainable thermal-insulation materials, but their practical application is often limited by insufficient mechanical robustness and intrinsic flammability. Herein, a multiscale network-engineering strategy is proposed to fabricate a cellulose-based composite aerogel integrating structural stability, thermal insulation, and fire safety. By synergistically introducing in situ generated aluminum trihydroxide (ATH) and microencapsulated APP@ATH–MEL into the cellulose scaffold, the flame-retardant components function not only as active fire-safety agents but also as structural regulators that promote the formation of a highly interconnected hierarchical framework. This regulated architecture enhances interfacial interactions, improves load-transfer efficiency, suppresses structural collapse during freeze-drying, and introduces tortuous pathways and abundant interfaces for heat-transfer regulation. As a result, the optimized composite aerogel exhibits a low thermal conductivity of 35 mW·m⁻¹·K⁻¹ together with improved compression resistance. Thermal analysis reveals a reduced mass-loss rate and increased char yield, while cone calorimetry confirms suppressed heat release, reduced gaseous emissions, and improved residue stability. The enhanced fire safety is attributed to a synergistic multi-phase mechanism involving endothermic shielding, gas-phase dilution, condensed-phase char formation, and inorganic-residue reinforcement, which collectively inhibit heat and mass transfer during combustion. This work provides an effective strategy for the design of lightweight, mechanically robust, and fire-safe cellulose-based composite aerogels for advanced thermal-insulation applications.