CCSI researchers from NETL and CMU published a paper in Industrial & Engineering Chemistry Research that describes how spatially distributed first-principles process models which provide an accurate physical description of chemical processes, but can be challenging and computationally expensive to solve can be converted into fast reduced order models for model-based real-time applications, such as advanced process control and dynamic real- time optimization. The paper focuses on the model reduction of a bubbling fluidized bed (BFB) adsorber previously developed under CCSI, which is a key component of a post-combustion solid sorbent based carbon capture system.