Design and Simulation of Pollution Control Units for Improving Sustainability | AIChE

Design and Simulation of Pollution Control Units for Improving Sustainability

The United States Environmental Protection Agency (U.S. EPA) has long advocated for, and mandated regulations on chemical processes to prevent and reduce the life cycle impact the processes have on the environment. Processes in the past have released pollution to the extent that it has affected the environment, human health, and climate of the world around us. To cope with the current pollution challenges caused by the release of various chemicals into the environment, it is required to include suitable pollution control technologies for chemical processes to purify and clean waste streams in order to meet the government standards on emissions.

The design and simulation of pollution control units are critical when assessing, improving, and optimizing the process performance in terms of sustainability. As part of this project, four Pollution Control Unit (PCU) models are developed in Microsoft Visual Basic for Applications (VBA) in Excel to calculate mass and energy balances, equipment sizing, land footprint, and utility demand for a chemical process represented by a CHEMCAD simulation. To better evaluate the life cycle impact of the process regarding the land use, resources consumption and waste releases, Life Cycle Inventory (LCI) results can be obtained rapidly and accurately by the designed PCU simulators.

The chemical process for the production of acetic acid from methanol is used to test the developed PCUs. The waste streams of the acetic acid production process are connected to these units. Such streams are then treated to minimize the harmful outputs, thus increasing the process sustainability, which is reflected in the LCI calculations. Results of this work indicate that the pollutants were removed from the waste gas and mainly converted to carbon dioxide and water. For obtaining this outcome, the pollution control units are sized accordingly in order to achieve the overall LCI improvement for the process.