Transport codes are beginning to be parallelized in order to allow more complex add-ons, such as geochemical packages, to utilize finer, more accurate grids, and to reduce solution times making stochastic and Monte Carlo simulations more feasible. Most codes parallelized via MPI (message passing interface) offer good results, but require the development of a new parallel code. OpenMP, the shared-memory standard, offers incremental parallelization, allowing sequential codes to remain relatively intact with minimal changes or additions. OpenMP allows speedup to be seen on personal computers with dual processors or greater, unlike some other parallelization approaches that require a supercomputer. An operator-split strategy creates an environment for easy parallelization by decoupling the transport and reactions of species. The transport, when decoupled from the reactions, is dependent on surrounding nodes and not on species. Therefore, each species transport can be solved on a different processor. The reactions, when decoupled from the transport, are dependant on the other species concentrations and not on the surrounding nodes, allowing the concentrations for all species to be solve for at a given node as if in a batch reactor. This allows a parallelization of the nodes. Two codes are parallelized in this work. The first is a 100-species 1D theoretical problem. The second is RT3D, a modular computer code for simulating reactive multi-species transport in 3-dimensional groundwater systems written and developed by Dr. T. Prabhakar Clement. RT3D is a sub-component of a parent code, MT3DMS, which utilizes RT3D to solve reaction terms. A speedup factor of 3.91 is seen on four processors, accomplishing a processor efficiency of approximately 98% while spent in RT3D itself.