This paper presents a response surface methodology approach in the optimizationof the carbon dioxide temperature-programmed adsorption process using a new materialreferred as nitrogen-functionalized graphene oxide. This material was synthesized byloading nitrogen groups to graphene oxide using aqueous ammonia in supercriticalcondition. Later on, it was utilized as a sorbent for carbon dioxide adsorption. This process was optimized by implementing a response surface methodology coupled with a Box- Behnken design for the effects of three factors: adsorption temperature, carbon dioxide flow rate, and the amount of adsorbent. In analyzing the response surface, a model equation was generated based on the experimental data by regression analysis. This model equation was then utilized to predict optimum values of response. Furthermore, response optimizer was also conducted in identifying factor combination settings that jointly optimize the best response.