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Risk assessment of atmospheric emissions using machine learning

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Fig. 2. Illustration of the definition of local direction of the plume.
Fig. 3. Flowchart illustrating the proposed method. The input pa- pa-rameters are the set of meteorological observations, remote sensing measurements, and the output of a global scale numerical weather prediction model used to initialize the mesoscale mete
Fig. 5. Map of the area with overlay of the 53 simulations per- per-formed. The source of the emissions is located at the entrance of the Istanbul channel (Black sea side).
Table 1. Distribution of the simulations across clusters and proba- proba-bility of the occurrence of each cluster.
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