## 2 Materials and Methods  
### Data Source  
We acquire time series gas dispersion data using the NBC-RAMS simulator, which simulates gas diffusion distribution following a gas bomb explosion under specific meteorological and experimental conditions in predefined spatial regions. NBC-RAMS established by the Agency for Defense Development of the Republic of Korea is a simulation program with purposes and functions similar to the Hazard Prediction and Assessment Capability software (version 6) [31] developed by the Defense Threat Reduction Agency in the United States. Previous studies have utilized NBC-RAMS for similar purposes [27; 32]. NBC-RAMS comprises a meteorological model and a pollution diffusion model. The meteorological model generates a three-dimensional gridded meteorological field, incorporating factors such as wind orientation, wind velocity, and temperature, accounting for topography, land cover, and building heights within the calculation area based on input weather information. The pollution diffusion model calculates the transport and diffusion process of pollutants, including chemical, biological, radiological, and smoke agents within the calculation area, utilizing the generated meteorological field. The data generation area encompasses a 5 km \(\times\) 5 km region within the metropolitan area of South Korea, divided into grids of 200 m \(\times\) 200 m. Gas concentrations are computed at the center of each grid. Simulations extend for 30 min from the time of the gas incident, with data recorded every minute starting from 1 min post-explosion. Each incident scenario yields gas diffusion data comprising 30 frames of size \((H,W,C)\), where \(H\) = 25, \(W\) = 25, and \(C\) = 1. To diversify the gas diffusion data, we vary parameters such as the gas generation grid, warhead payload mass, and meteorological environments. SF6 is used as the gas in the diffusion simulation, with the payload mass ranging from 0.0005 kg to 0.0025 kg in 0.0005 kg increments. Meteorological conditions are set by adjusting the wind speed from 1 m/s to 3 m/s in 0.5 m/s intervals and the wind direction from 0\({}^{\circ}\) to 315\({}^{\circ}\) in 45\({}^{\circ}\) intervals. The temperature remains constant at 10 \({}^{\circ}\)C. We generate data by performing the various experimental conditions described above for each \(N_{C}=H\times W\) grid, representing a potential gas source. The generated dataset comprises 200 experimental conditions per 625 grids, totaling 125,000 instances comprising 3.75 million frames. Of these, 70% are allocated for training, 20% for validation, and 10% for testing. Figure 1 presents a sample of data generated using NBC-RAMS. Frames depict gas dispersion at 2 min intervals from 1 to 27 min post-explosion. The gradual spread of gas over time and its varying distribution across each time step are discernible. The presence of a gas source point, represented by a white flask, and its subsequent diffusion are apparent, illustrating the influence of both inherent chemical properties and the weather environment on dispersion. As time progresses, gas disperses, and concentrations at the source diminish due to atmospheric dilution. We conduct data preprocessing, encompassing sequence extraction and normalization, on the acquired data. During sequence extraction, we extract \(T\) consecutive frames from each simulation data. Following gas generation, the immediate environment experiences dynamic instability due to the sudden introduction of chemical substances, potentially causing irregularities in gas diffusion distribution. These irregularities may induce data instability, thereby impeding model generalization. As time elapses post-explosion, the surrounding environment stabilizes, and the gas diffusion pattern becomes consistent. Hence, we commence the extraction process from the 6 th frame among the 30 frames obtained for each scenario. The extracted consecutive frames undergo validation.