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We propose a methodology to estimate single and multiple emission sources of atmospheric contaminants. It combines hybrid metaheuristic/gradient-descent optimization techniques and Tikhonov-type regularization. The dispersion problem is solved by the Galerkin/Least-squares finite element formulation, which allows more realistic modeling. The accuracy of the proposed inversion model is tested under different contexts with experimental data. To identify single and multiple emissions, we use experimental field data. We consider different conf