The chemical reactor network (CRN) approach is a practical tool for precisely predicting the species concentration in combustion processes with low computational cost. This work examines the capability of the emerging Julia programming language and its ecosystem in solving large CRNs. The packages DifferentialEquations.jl and ModelingToolkit.jl are employed to defining and solving stiff ordinary differential equations, for which the implicit time-integration methods Rodas5 and TRBDF2 with the GMRES linear solver are used. The graph structure of reactor networks is constructed by LightGraphs.jl and SimpleWeightedGraphs.jl. The differential equation solver and the graph data structure are connected via NetworkDynamics.jl. It is concluded that Julia is a competent tool for CRNs containing up to 1000 nodes each with 4 species. Julia is capable of simulating pollutant formation in large reactor networks with reasonable time and memory space.