<p>Natural disasters create compound threats to emergency response systems by simultaneously damaging critical infrastructure and transportation networks, leading to interdependent failure risks that challenge traditional emergency facilities location-routing problem. To address this complexity, this paper develops Multi-Objective Emergency Facility Location-Routing Problem with Failure Risk (MOELRP-FR) that simultaneously considers facility vulnerability, road degradation, and cascading failure interdependencies, capturing risk propagation dynamics, allowing for the joint optimization of system reliability, response time, and rescue cost. Simultaneously, this paper first proposes the Multi-category Multi-objective Ripple Spreading Algorithm (MCMORSA) for solving the above-mentioned MOELRP-FR model, which efficiently generates a complete Pareto front by embedding real-time failure risk probabilities into ripple propagation, synchronizing risk-adaptive routing and cascading failure prevention through a category-aware ripple relay mechanism. To validate the feasibility and effectiveness of MCMORSA, we apply it to real-world scenarios in Beijing and Chengdu, China. MOELRP-FR model is solved using 13 benchmark algorithms to compare site selection accuracy and computational efficiency. Results demonstrate that MCMORSA consistently achieves superior computational efficiency and solution accuracy, offering practical engineering value for disaster-resilient emergency planning.</p>