Development and integration of new processes consuming carbon dioxide in multi-plant chemical production complexes

Abstract

Fourteen new energy-efficient and environmentally acceptable catalytic processes have been identified that can use excess high-purity carbon dioxide as a raw material available in a chemical production complex. The complex in the lower Mississippi River Corridor was used to show how these new plants could be integrated into this existing infrastructure using the chemical complex analysis system. Eighty-six published articles of laboratory and pilot plant experiments were reviewed that describe new methods and catalysts to use carbon dioxide for producing commercially important products. A methodology for selecting the new energy-efficient processes was developed based on process operating conditions, energy requirements, catalysts, product demand and revenue, market penetration and economic, environmental and sustainable costs. Based on the methodology for selecting new processes, 20 were identified as candidates for new energy efficient and environmentally acceptable plants. These processes were simulated using HYSYS, and a value-added economic analysis was evaluated for each process. From these, 14 of the most promising were integrated in a superstructure that included plants in the existing chemical production complex in the lower Mississippi River corridor (base case). The optimum configuration of plants was determined based on the triple bottom line that includes sales, economic, environmental and sustainable costs using the chemical complex analysis system. From 18 new processes in the superstructure, the optimum structure had seven new processes including acetic acid, graphite, formic acid, methylamines, propylene and synthesis gas production. With the additional plants in the optimal structure the triple bottom line increased from $343 million per year to $506 million per year and energy use increased from 2,150 TJ/year to 5,791 TJ/year. Multicriteria optimization has been used with Monte Carlo simulation to determine the sensitivity of prices, costs, and sustainability credits/cost to the optimal structure of a chemical production complex. In essence, for each Pareto optimal solution, there is a cumulative probability distribution function that is the probability as a function of the triple bottom line. This information provides a quantitative assessment of the optimum profit versus sustainable credits/cost, and the risk (probability) that the triple bottom line will meet expectations. The capabilities of the chemical complex analysis system have been demonstrated, and this methodology could be applied to other chemical complexes in the world for reduced emissions and energy savings. The system was developed by industry–university collaboration, and the program with users manual and tutorial can be downloaded at no cost from the LSU Mineral Processing Research Institute’s website http://www.mpri.lsu.edu.