Vitor Gama, Beatriz Dantas, Oishi Sanyal, Fernando V. Lima
{"title":"基于膜的低纯度二氧化碳生产直接空气捕集工艺可操作性分析","authors":"Vitor Gama, Beatriz Dantas, Oishi Sanyal, Fernando V. Lima","doi":"10.1021/acsengineeringau.3c00069","DOIUrl":null,"url":null,"abstract":"Addressing climate change constitutes one of the major scientific challenges of this century, and it is widely acknowledged that anthropogenic CO<sub>2</sub> emissions largely contribute to this issue. To achieve the “net-zero” target and keep the rise in global average temperature below 1.5 °C, negative emission technologies must be developed and deployed at a large scale. This study investigates the feasibility of using membranes as direct air capture (DAC) technology to extract CO<sub>2</sub> from atmospheric air to produce low-purity CO<sub>2</sub>. In this work, a two-stage hollow fiber membrane module process is designed and modeled using the AVEVA Process Simulation platform to produce a low-purity (≈5%) CO<sub>2</sub> permeate stream. Such low-purity CO<sub>2</sub> streams could have several possible applications such as algae growth, catalytic oxidation, and enhanced oil recovery. An operability analysis is performed by mapping a feasible range of input parameters, which include membrane surface area and membrane performance metrics, to an output set, which consists of CO<sub>2</sub> purity, recovery, and net energy consumption. The base case for this simulation study is generated considering a facilitated transport membrane with high CO<sub>2</sub>/N<sub>2</sub> separation performance (CO<sub>2</sub> permeance = 2100 GPU and CO<sub>2</sub>/N<sub>2</sub> selectivity = 1100), when tested under DAC conditions. With a constant membrane area, both membranes’ intrinsic performances are found to have a considerable impact on the purity, recovery, and energy consumption. The area of the first module plays a dominant role in determining the recovery, purity, and energy demands, and in fact, increasing the area of the second membrane has a negative impact on the overall energy consumption, without improving the overall purities. The CO<sub>2</sub> capture capacity of DAC units is important for implementation and scale-up. In this context, the performed analysis showed that the m-DAC process could be appropriate as a small-capacity system (0.1–1 Mt/year of air), with reasonable recoveries and overall purity. Finally, a preliminary CO<sub>2</sub> emissions analysis is carried out for the membrane-based DAC process, which leads to the conclusion that the overall energy grid must be powered by renewable sources for the technology to qualify within the negative emissions category.","PeriodicalId":29804,"journal":{"name":"ACS Engineering Au","volume":null,"pages":null},"PeriodicalIF":4.3000,"publicationDate":"2024-03-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Process Operability Analysis of Membrane-Based Direct Air Capture for Low-Purity CO2 Production\",\"authors\":\"Vitor Gama, Beatriz Dantas, Oishi Sanyal, Fernando V. 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An operability analysis is performed by mapping a feasible range of input parameters, which include membrane surface area and membrane performance metrics, to an output set, which consists of CO<sub>2</sub> purity, recovery, and net energy consumption. The base case for this simulation study is generated considering a facilitated transport membrane with high CO<sub>2</sub>/N<sub>2</sub> separation performance (CO<sub>2</sub> permeance = 2100 GPU and CO<sub>2</sub>/N<sub>2</sub> selectivity = 1100), when tested under DAC conditions. With a constant membrane area, both membranes’ intrinsic performances are found to have a considerable impact on the purity, recovery, and energy consumption. The area of the first module plays a dominant role in determining the recovery, purity, and energy demands, and in fact, increasing the area of the second membrane has a negative impact on the overall energy consumption, without improving the overall purities. The CO<sub>2</sub> capture capacity of DAC units is important for implementation and scale-up. In this context, the performed analysis showed that the m-DAC process could be appropriate as a small-capacity system (0.1–1 Mt/year of air), with reasonable recoveries and overall purity. 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Process Operability Analysis of Membrane-Based Direct Air Capture for Low-Purity CO2 Production
Addressing climate change constitutes one of the major scientific challenges of this century, and it is widely acknowledged that anthropogenic CO2 emissions largely contribute to this issue. To achieve the “net-zero” target and keep the rise in global average temperature below 1.5 °C, negative emission technologies must be developed and deployed at a large scale. This study investigates the feasibility of using membranes as direct air capture (DAC) technology to extract CO2 from atmospheric air to produce low-purity CO2. In this work, a two-stage hollow fiber membrane module process is designed and modeled using the AVEVA Process Simulation platform to produce a low-purity (≈5%) CO2 permeate stream. Such low-purity CO2 streams could have several possible applications such as algae growth, catalytic oxidation, and enhanced oil recovery. An operability analysis is performed by mapping a feasible range of input parameters, which include membrane surface area and membrane performance metrics, to an output set, which consists of CO2 purity, recovery, and net energy consumption. The base case for this simulation study is generated considering a facilitated transport membrane with high CO2/N2 separation performance (CO2 permeance = 2100 GPU and CO2/N2 selectivity = 1100), when tested under DAC conditions. With a constant membrane area, both membranes’ intrinsic performances are found to have a considerable impact on the purity, recovery, and energy consumption. The area of the first module plays a dominant role in determining the recovery, purity, and energy demands, and in fact, increasing the area of the second membrane has a negative impact on the overall energy consumption, without improving the overall purities. The CO2 capture capacity of DAC units is important for implementation and scale-up. In this context, the performed analysis showed that the m-DAC process could be appropriate as a small-capacity system (0.1–1 Mt/year of air), with reasonable recoveries and overall purity. Finally, a preliminary CO2 emissions analysis is carried out for the membrane-based DAC process, which leads to the conclusion that the overall energy grid must be powered by renewable sources for the technology to qualify within the negative emissions category.
期刊介绍:
)ACS Engineering Au is an open access journal that reports significant advances in chemical engineering applied chemistry and energy covering fundamentals processes and products. The journal's broad scope includes experimental theoretical mathematical computational chemical and physical research from academic and industrial settings. Short letters comprehensive articles reviews and perspectives are welcome on topics that include:Fundamental research in such areas as thermodynamics transport phenomena (flow mixing mass & heat transfer) chemical reaction kinetics and engineering catalysis separations interfacial phenomena and materialsProcess design development and intensification (e.g. process technologies for chemicals and materials synthesis and design methods process intensification multiphase reactors scale-up systems analysis process control data correlation schemes modeling machine learning Artificial Intelligence)Product research and development involving chemical and engineering aspects (e.g. catalysts plastics elastomers fibers adhesives coatings paper membranes lubricants ceramics aerosols fluidic devices intensified process equipment)Energy and fuels (e.g. pre-treatment processing and utilization of renewable energy resources; processing and utilization of fuels; properties and structure or molecular composition of both raw fuels and refined products; fuel cells hydrogen batteries; photochemical fuel and energy production; decarbonization; electrification; microwave; cavitation)Measurement techniques computational models and data on thermo-physical thermodynamic and transport properties of materials and phase equilibrium behaviorNew methods models and tools (e.g. real-time data analytics multi-scale models physics informed machine learning models machine learning enhanced physics-based models soft sensors high-performance computing)