Formulation of a Network and the Study of Reaction Paths for the Sustainable Reduction of CO2 Emissions

Abstract

Various organizations, especially the Intergovernmental Panel on Climate Change, have stated that global warming is an ever-increasing threat to the environment and poses a problem if not addressed. Therefore, efforts are being made to find methods of reducing contributors to global warming, primarily greenhouse gas emissions. Of these, carbon dioxide (CO2) is the largest source and, hence, the reduction of the amount emitted is primary focus of developments [1]. A new and promising process that reduces the emissions is the conversion of CO2 into useful products, such as methanol and dimethyl carbonate (DMC) [2]. In this work, through a computer-aided framework for process network synthesis-design, a network of conversion processes that all use emitted CO2 is investigated. CO2 is emitted into the environment from various sources: power generation, industrial processes, transportation and commercial processes. Within these there are high-purity emissions and low-purity emissions. Rather than sending these to the atmosphere, it is possible to collect them and use them for other purposes. Targeting some of the largest contributors: power generation, manufacturing, chemical industry, it is possible to determine the amounts available. Once the CO2-sources are known, it is possible to determine how to utilize these through process network optimization. In addition to the source information, reaction details are vital. Understanding the conversions that are thermodynamically feasible, process co-reactants, catalysts necessary, operating conditions and reactions, is the next step. The products that are formed fall into categories: fuels, bulk chemicals and specialty chemicals. While fuels, such as methanol (MeOH), have the largest market, this network will include a variety of thermodynamically feasible conversion paths [3]. From reviews of work previously done, there are ranges of possible products that are formed directly from CO2 and another co-reactant. Methanol, dimethyl ether, dimethyl carbonate and ethylene carbonate are just some of the products that can be formed. With the information of sources and reactions, a tree of reaction paths is formed and investigated. This forms a superstructure of CO2 utilization to a variety of products. Each of the paths in the network involves CO2 and a co-reactant, such as hydrogen, which may also be captured from process purge streams. The process network evolves as some of the reactions involve products from other reactions as a reactant. Combining the possible products that can be formed and the reactants that are required yields a network of products that can be created using only the CO2 emissions and not adding any CO2 emissions through the reactions. Studies and detailed simulations have been performed on CO2 conversion to methanol, synthesis gas processes, dimethyl carbonate production, and other processes. The detailed simulations are performed on the paths that are selected based on basic calculations on each path. Then, those paths that are targeted from base calculations are further simulated for detailed information. From these detailed simulations, results are provided, enhancing the superstructure for an improved analysis. In addition, the aim is to create sustainable alternatives for the production of these products with an overall reduction of CO2, both in the material and energy streams. With the use of computer-aided tools, this network, and the information contained within it, is generated. The detailed simulations, of CO2 conversion to methanol, synthesis gas production and DMC manufacture, provide in-depth knowledge of the various paths that are most promising. The economic feasibility and sustainability are assessed to identify the final, more sustainable network. Overall, the target is the formation of a network that reduces emissions by forming desirable chemical products without emitting noticeable amounts of CO2 and other greenhouse gases, and creating more energy efficient processes.