To address the dual uncertainties of transit time and transportation risk in hazardous materials multimodal routing optimization under carbon trading policies, this paper proposed a path decision-making method based on hybrid robust optimization. First, a deterministic model aiming at minimizing the total system cost was constructed by comprehensively considering transportation, transshipment, risk costs and carbon emission reduction requirements. Second, a box uncertainty set was adopted to describe the fluctuation characteristics of transit time and transportation risk, on which a robust optimization model was established, and a multi-strategy enhanced ant colony optimization (MSE-ACO) algorithm was designed to solve the model. A case study of an enterprise located in a chemical industrial park in Jiangsu Province verified that the MSE-ACO algorithm possesses outstanding robustness under complex environments. The intensity of time constraints acts as a crucial regulating factor for path decision-making. In addition, each uncertain parameter as well as their synergistic effects imposes significantly heterogeneous impacts on decision results. Moreover, the influence of carbon constraints on the optimal path presents an obvious threshold characteristic.