Carbon capture and storage (CCS) is widely considered to be an essential technology for reducing carbon dioxide (CO2) emissions from sources such as power plants. It involves isolating CO2 from exhaust gases and then storing it in an appropriate natural reservoir that acts as a sink. Therefore, CCS is able to prevent CO2 from entering the atmosphere. In this work, a continuous-time mixed integer nonlinear programming (MINLP) model for CO2 source sink matching in CCS systems is developed; the initial model is then converted into an equivalent mixed integer linear program (MILP). It is assumed that in CCS systems, CO2 sources have find flow rates and operating lives, while CO2 sinks have an earliest time of availability and a maximum CO2 storage capacity. Thus, the resulting optimization model focuses on important physical and temporal aspects of planning CCS. The usefulness of the model is illustrated using two case studies.