The source parameters estimation, based on environment pollution monitoriing, and assessment of regions with high potential risk and vulnerability from nuclear sites are the two important problems for nuclear emergency preparedness systems and for long-term planning of socio-economical development of territories. For the discussed problems, most of modelers use the common back-trajectory techniques, suitable only for Lagrangian models. This paper discusses another approach for inverse modeling, based on variational principles and adjoint equations, and applicable for Eulerian and Lagrangian models. The presented methodology is based on both direct and inverse modeling techniques. Variational principles combined with decomposition, splitting and optimization techniques are used for construction of numerical algorithms. The novel aspects are the sensitivity theory and inverse modeling for environmental problems which use the solution of the corresponding adjoint problems for the given set of functionals. The Methodology proposed provides optimal estimations for objective functionals. The methodology proposed provides optimal estimations for objective functionals, which are criterion of the atmospheric quality and informative content of measurements. Some applications of the suggested methods for source parameters and vulnerability zone estimations are discussed for important regions with environmental risk sites.