The design of high-performance gas filtration and purification products utilizing adsorption must account for the sensitivity of adsorption phenomena to the wide variety of process conditions and parameters which is difficult to know in advance for a particular design. Although building physical prototypes and performing physical testing can be done, it is usually at the expense of time-to-market, reduced number of design alternatives, the absence of true optimization, and financial cost. Therefore, there remains a standing need to develop a suitable parametric optimization tool to capture the effects of related process parameters on purifier performance. Virtual prototyping of gas purification products using Computational Fluid Dynamics (CFD) can complement that by simulating the required physics involved (fluid flow, heat and mass transfer, chemical kinetics, and thermodynamics). To this end, recent efforts demonstrated a novel modeling technique to predict and optimize chemical performances in gas purifiers under a wide range of process parameters. The optimization model is based on three different gas-solid adsorption systems (toluene/activated carbon, moisture/zeolite and CO2/zeolite). The models were first validated with experimental data which were then applied to optimize purifier performance. Based on the modeling data, a set of mathematical correlations was developed that can predict the effects of process parameters on adsorption performance. Using these correlations, a simplified optimization calculator was provided which effectively predicts the parametric effects on purifier performance without performing lengthy experiments or requiring designers to learn CFD.