Post-combustion Carbon Capture Process Research Articles

MODELING AND SIMULATION OF POST-COMBUSTION CO 2 CAPTURE PROCESS FOR 6.4 MWE BAGASSE FUELED POWER PLANT

The emission of carbon dioxide, a greenhouse gas, contributes to the phenomenon of climate change; the largest source of carbon dioxide emissions are fossil fuel power plants. Post-combustion carbon capture (PCC) technology, which is based on solvents, is currently the most advanced technology for reducing carbon dioxide emissions from power plants. The Post-combustion Process, which uses conventional solvents, has a number of disadvantages, including high energy consumption for regeneration, solvent losses, corrosion of equipment, thermal instability, and environmental impact. Ionic liquids (ILs) and IL-based solvents have produced a novel method of CO 2 capture that is highly efficient, economical, and environmentally friendly. A rate-based steady-state model of the PCC process using the ionic liquid 1-hexyl-3-methylimidazolium glycine ([Hmim] [Gly]) was investigated using Aspen Plus ®. In Aspen Plus ® Electrolyte NRTL method and RK equation of state are used to compute liquid and vapor properties. From the process analysis carried out, it was found that the height and diameter of the absorber packing, the liquid-to-gas ratio and the solvent and flue gas temperatures have a positive effect on the CO 2 capture efficiency. The result showed a maximum CO 2 capture efficiency of 92% at a packed height of 12m and diameter of 0.9m. The best capture efficiency of 98.82% was achieved at an L/G ratio of 4.0.the process simulation study examined five key parameters for ([Hmim] [Gly]) solvent which may reduce the energy and cost required for CO 2 capture. The results show that aqueous ([Hmim] [Gly]) is a promising absorbent for CO 2 capture. Offering a pathway towards more sustainable and efficient carbon capture technologies. This study contributes to the advancement of carbon capture technologies and underscores their significance in mitigating climate change impacts.

Post-combustion carbon capture process modeling, simulation, and assessment of synergistic effect of solvents

Post-combustion carbon capture appears to be a promising solution to reduce the emission of carbon dioxide (CO2) from power plants that generate electricity using either coal or natural gas. In addition, carbon capture process efficiency, capacity, and energy consumption have become challenging against the performance of the capture process. However, synergistic effect due to solvents blend has gained attention to reduce the process energy consumption and enhance process efficiency. In this study, blends of methyldiethanolamine (MDEA) and piperazine (PZ) at different concentrations were investigated using a validated post-combustion capture process model using Aspen HYSYS. Results were compared with 30 wt% monoethanolamine (MEA) as reference case. The effective process variables are concentration of solvents, the amount of water and solvent in the makeup section, viscosity of solvent, energy consumed in different process stages, and the amount of lean solvent flow rate. These variables were studied against fixed process variables using rate-based model. The study shows that using (43 wt% MDEA/7 wt% PZ) for post-combustion carbon capture needs 2.53 MJ/kgCO2 regeneration energy for 88.5% process efficiency compared to 4.003 MJ/kgco2 for 30 wt% MEA without the need for any process modifications. In addition, it was found that solvents synergistic effect contributes to resolving the drawbacks of post-combustion capture that will enable the high utilization of the process and contribution to reduce the consequences effect of climate change. Therefore, the study will help policymakers, industries and encourage researchers towards the large-scale commissioning of blended solvent -based post-combustion capture process.

Technical and economic performance assessment of blue hydrogen production using new configuration through modelling and simulation

Steam methane reforming (SMR) is the dominant process for hydrogen production, which produce large amount of carbon dioxide (CO2) as a by-product. To address concerns about carbon emissions, there is an increasing focus on blue hydrogen to mitigate carbon emissions during hydrogen production. However, the commercialization of blue hydrogen production (BHP) is hindered by the challenges of high cost and energy consumption. This study proposes a new configuration to address these challenges, which is characterized by: (a) the use of piperazine (PZ) as a solvent, which has a high CO2 absorption efficiency; (b) a more efficient heat exchange configuration which recovers the waste exergy from flue gas; (c) the advanced flash stripper (AFS) was adopted to reduce the capital cost due to its simpler stripper configuration. In addition, the technical and economic performance of the proposed energy and cost-saving blue hydrogen production (ECSB) process is investigated and compared with the standard SMR process. The detailed models of the SMR process and the post-combustion carbon capture (PCC) process were developed and integrated in Aspen plus® V11. The results of the technical analysis showed that the ECSB process with 30 wt.% PZ achieves a 36.3 % reduction in energy penalty when compared to the standard process with 30 wt.% Monoethanolamine (MEA). The results of the economic analysis showed that the lowest levelized cost of blue hydrogen (LCBH) was achieved by the ECSB process with 30 wt.% PZ. Compared to the BHP process with 30 wt.% MEA, the LCBH was reduced by 19.7 %.

High accuracy prediction of the post-combustion carbon capture process parameters using the Decision Forest approach

This paper investigates the relationships among the important process parameters that impact Post-combustion Carbon Capture (PCC) carbon dioxide (CO2) separation. A better understanding of the complex relationships among those parameters can support optimization and performance enhancement of the separation process. Being able to precisely predict the process parameters will enable the operator to determine the current state of the process, forecast any potential changes or events, and adjust process parameters to enhance the plant's performance. With the objective of studying the process parameters' correlations in the amine-based PCC process, we modeled the multi-year historical production data of the Clean Energy Technologies Research Institute (CETRi) (formerly known as the International Test Center for PCC or ITC) in Regina, Saskatchewan, Canada, using a Decision Forest approach. The model validation process revealed that the Decision Forest model produced higher predictive accuracy than previous efforts. The Decision Forest models we developed also represent knowledge about the importance of parameters involved in the capture process, and such knowledge is useful for further optimization of the capture process in the future.

A technical and environmental comparison of novel silica PEI adsorbent-based and conventional MEA-based CO2 capture technologies in the selected cement plant

The cement industry accounts for almost 7 % of anthropogenic carbon dioxide emissions globally. Therefore, it is imperative to identify innovative solutions to mitigate carbon dioxide emissions from the cement industry.This study aims to evaluate and compare the technical and environmental aspects of integrating two post-combustion carbon capture processes (CCS) into a cement plant: the conventional monoethanolamine (MEA)-based CCS process and the novel silica-alkoxylated polyethyleneimine (SPEI)-based CCS process. Three scenarios were considered: (i) a reference cement plant without CCS, (ii) the conventional MEA-based CCS system integrated into a cement plant and (iii) the novel SPEI-based CCS system integrated into a cement plant. The technical evaluation results showed that the regeneration energy requirements for the conventional MEA and novel SPEI-based CCS processes were 3.53 GJ/tonne CO2 and 2.36 GJ/tonne CO2, respectively, to achieve a capture rate of 90 %. However, the performance of MEA-based carbon capture processes can be improved by using advanced amine formulations that offer lower regeneration heat requirements at 3.3 GJ/tonne CO2, although this is still higher than the SPEI-based carbon capture processes.The novel SPEI-based CCS process showed superior environmental performance compared to the conventional MEA-based CCS process. The endpoint single score was conducted which showed that the SPEI-based CCS process had a lower impact on human health, ecosystems, and resources (7 %, 9 %, and 26 % lower, respectively) compared to the MEA-based CCS process.

Cost optimization methodology based on carbon-techno-economic analysis: An application to post-combustion carbon capture process

Recently, a carbon tax has been introduced to encourage emissions reduction, and it has become an additional cost burden. To evaluate the carbon emissions and process costs simultaneously in a single indicator, a carbon-techno-economic analysis (CTEA) methodology that combines carbon tax and process cost was developed in this study. The proposed CTEA model was used to optimize the post-combustion carbon capture (PCC) process, which is an energy- and cost-intensive process. In CTEA optimization, as the carbon tax price increases from $12.5/tonne CO2 to $250/tonne CO2, more energy is provided to the PCC process to increase the carbon capture level from 58.92 % to 99.64 %. This results in a decrease in power generation of the natural gas combined cycle power plant from 462.33 MW to 436.07 MW, and an increase in the incremental cost of electricity from $14.05/MWh to $17.74/MWh. The decrease in profit from CTEA optimization is only 8.75 %, which is relatively smaller than the 11.68 % and 32.32 % decrease in profit from energy and TEA optimization, respectively. The results demonstrate that CTEA-based process optimization is beneficial and highlight the trade-off relationship among carbon tax, process cost, and profit. The results of this study can guide commercial companies in setting operational strategies for their processes as carbon tax prices change and can also assist governments in establishing carbon tax policies to encourage carbon emission reductions in industries.

Heat integration, process design and techno-economic assessment of post-combustion carbon capture using piperazine for large-scale ethylene plant

With the development of increasingly larger ethylene plants and the associated requirement to reduce carbon emissions effectively, there is a growing need to explore approaches that reduce the cost and energy consumption in carbon capture from ethylene plants. In this study, the flue gas heat recovery (FHR) strategy was proposed and implemented for different configurations of piperazine (PZ)-based post-combustion carbon capture (PCC) process applied to an ethylene plant with a capacity of 60,000 t/year. Four different cases of the PZ-based PCC process with or without FHR were simulated in Aspen Plus® V11 to explore the cost reductions and energy saving potential. The advanced flash stripper (AFS) configuration with FHR and absorber inter-cooling achieves a minimum regeneration energy requirement of 2.28 GJ/tonCO2, a reduction of 37.71 % compared to standard PCC configuration using MEA solvent. The economic evaluation was carried out using Aspen Process Economic Analyzer® (APEA). The results show that the carbon capture cost using AFS configuration with FHR and inter-cooling can reduce to 47.27 $/tonCO2, a reduction of 36.76 % against the standard PCC process using MEA. The proposed technology presents significant technical and economic benefits for the large-scale deployment of carbon capture for ethylene plants.

Application of post-combustion carbon capture process in marine diesel engine

ABSTRACT This study has investigated the effect of using a waste heat recovery system and carbon capture process on carbon reduction efficiency and the Energy Efficiency Design Index (EEDI) to reduce carbon emissions from ships. Organic Rankine Cycle (ORC) was used as waste heat recovery and ORC system turbine power was determined at variable engine loads. The effect of system parameters such as exhaust absorber inlet temperature, MEA concentration and flow rate, number of columns on carbon capture performance has been revealed in the carbon capture process. Furthermore, the EEDI was estimated using the existing system, the ORC system configuration, and the utilization of the carbon capture system. It has been determined that the optimal exhaust absorber inlet temperature is 50°C and the carbon capture performance is 95% on average. In the applied system, the EEDI is reduced by 14% with the ORC system and by 90% with the carbon capture system. ORC system turbine output power ranges from approximately 414 kW to 606 kW for variable CCS inlet temperatures for 100% load condition. Thus, the study predicts that the carbon capture system can effectively meet the regulations in case of using fossil fuels in the future.

Machine learning based modelling and optimization of post-combustion carbon capture process using MEA supporting carbon neutrality

The role of carbon capture technology using monoethanolamine (MEA) is critical for achieving the carbon-neutrality goal. However, maintaining the efficient operation of the post-combustion carbon capture is challenging considering the hyperdimensional design space and nonlinear characteristics of the process. In this work, CO2 capture level from the flue gas in the absorption column is investigated for the post-combustion carbon capture process using MEA. Artificial neural network (ANN) and support vector machine (SVM) models are constructed to model CO2 capture level under extensive hyperparameters tuning. The comparative performance analysis based on external validation test confirmed the superior modelling and generalization ability of ANN for the carbon capture process. Later, partial derivative-based sensitivity analysis is carried out and it is the found that absorbent-based input variables like lean solvent temperature and lean solvent flow rate are the two most significant input variables on CO2 capture level in the absorption column. The optimization problem with the ANN model embedded in the nonlinear programming-based optimization environment is solved under different operating scenarios to determine the optimum operating ranges for the input variables corresponding to the maximum CO2 capture level. This research presents the optimum operating conditions for CO2 removal from the flue gas for the post-combustion carbon capture process using MEA that contributes to achieving the carbon neutrality goal.

Analysis of CO2 capture process from flue-gases in combined cycle gas turbine power plant using post-combustion capture technology

Combined cycle gas turbine power plants (CCGTs) are a combined cycle consisting of a gas turbine and a steam turbine to generate electricity. Sometimes CCGTs incorporate cogeneration to produce both heat and power. After the gas fuel combustion in the gas turbine combustion chamber, the flue gases are passed through the Heat Recovery Steam Generator (HRSG) to extract heat and generate additional electrical power using the steam turbine. The CCGT technology is recognized for its highest efficiency of 58% in electricity production among the power production technology. A highly efficient CCGT power plant with 60% efficiency produces even 2.5 times less CO2 than a modern coal power plant with an efficiency of 45% because of the use of gas fuel and electrical efficiency. The CO2 emission can be reduced further when the post-combustion CO2 capture methods are applied. To perform CO2 capture and to reduce the CO2 emission from power plants, the CO2 mass fraction in flue gas is the crucial parameter for the operation of the Post-combustion Carbon Capture and Storage (PCCS) technology. The PCCS technology uses solvents, which is the aqueous solution of amine that reacts with flue gas and absorbs the CO2, which is treated and separated later. The paper presents the results of the energy analysis of a post-combustion carbon capture process when integrated with a combined cycle gas power plant. The study considered two different gas fuels such as methane and syngas. Syngas composition was determined from the sewage sludge gasification process and can be treated as zero-emission CO2 gas fuel. When the flue gas produced from the syngas is used in PCCS at more than 50% of load conditions, the negative CO2 emission level in large-scale CCGT power plants can be reached. The paper presents the results of mass and energy balance analysis of HRSG of a CCGT integrated with PCCS to perform CO2 capture. The analysis of HRSG using flue gases from methane and syngas is performed by calculating the enthalpy of flue gas, rate of heat exchange, and temperature distribution of each component of HRSG. The comparison of the result shows slight differences due to the different composition and flow rates of flue gases. The flue gas at the outlet of two HRSG is used in the PCCS at different load conditions. An aqueous solution of 30 wt% Monoethanolamine (MEA) with rich loading of 0.5 mol-CO2/mol-MEA and a mixture of 16 wt% 2-amino-2-methyl-1-propanol (AMP) – 14 wt% Piperazine (PZ) with rich loading of 0.62 and 0.86 mol-CO2/mol-amine respectively are used in the PCCS. Due to the reboiler duty of amines, the steam consumed by the PCCS for AMP-PZ regeneration is less compared to MEA. Depending upon the flue gas and solvent used in the PCCS, the power consumed by the PCCS from CCGT power plant is measured from 9.6% to 11.6%. For the given operating condition of the CCGT and PCCS at more than 50% load condition, the negative CO2 emission level can be achieved.

Demonstration of CO2 Capture Process Monitoring and Solvent Degradation Detection by Chemometrics at the Technology Centre Mongstad CO2 Capture Plant

Solvent management is one of the important current challenges in post combustion carbon capture (PCC) technology development. Using large-scale 1960 h test campaign data (Technology Centre Mongstad, Norway, 2015 MEA Test), we demonstrate a combination of multivariate methods (PLS-R, MSPC) and process analytical spectroscopy (FT-IR) as a tool to monitor and control PCC process performance. Two MEA solvent monitoring models, total inorganic carbon (TIC) content and total alkalinity (TA), were prepared. In long-term solvent monitoring, PLS-R model prediction uncertainty increased due to gradual solvent changes, e.g., solvent degradation and impurity accumulation. Hence, we show a specific model update methodology to keep the models updated, leading to good long-term monitoring ability of the TIC and TA models. In addition to reliable long-term solvent monitoring ability, a new principle for follow-up of thermal solvent reclaiming was demonstrated. This shows that the need for solvent reclaiming can be quantified. Furthermore, this methodology is an indicator to see the actual solvent deviation from the fresh solvent. This quantification may provide an input for “start” and “end of reclaiming operation” identification. Hence, we demonstrate that it is possible to extract information for process performance follow-up, solvent monitoring, and solvent reclaiming from a single spectroscopic instrument.

Modeling of hollow fiber facilitated transport membrane modules for post combustion carbon capture process: Evaluation of non-ideal effect and module characteristic

Membrane separation technology has been regarded as a promising alternative for carbon capture process due to its low consumption and low footprint. Facilitated transported membranes exhibit attractive CO2/N2 separation performance due to the existence of CO2-philic reactive carriers. However, the highly pressure and temperature dependent CO2 permeance of it, as well as non-ideal effect, make the simulation of carbon capture process based on simplifying model challenging. Herein, we established a rigorous model for hollow fiber facilitated transport membrane considering both non-ideal effect and variable permeance. This rigorous model was applied for post-combustion carbon capture, and compared with simple model which only considering variable permeance. It was found that rigorous model has a 44%-55% lower carbon capture capacity due to the declined driving force and permeance. Pressure loss accounts for the deviation at low stage cut (10%), while Joule-Thomson effect and concentration polarization effect become greater at high stage cut (20%). Thanks to the mild condition of post combustion flue gas, the impact of real gas behavior can be neglected. Moreover, the attractive configuration of hollow fiber facilitated transport membrane was found to be with relative short fiber length, moderate packing fraction and large fiber inner diameter.

Environmental and Economic Analysis of a Natural Gas Combined Cycle Power Plant Using CO2 Utilization Technologies and Ecosystem Services

Power plants are major contributors to CO2 emissions. Post-combustion carbon capture (PCC) processes are commonly integrated, but the capture effectiveness is limited. In this work, four conversion technologies for CO2 utilization from a power plant plus PCC to produce formic acid, methanol, and syngas as value-added chemicals are analyzed. We also analyze the implications of implementing forest ecosystems, for which trees with three types of maturity are considered. The results show that the environmental implications of process utilization technologies may lack desired effectiveness, since the emissions of the utilization plant may still be significant with respect to the amount of captured CO2. Ecological systems are more effective from environmental considerations, but the number of trees and land use may be too high to process the amount of CO2 produced by power plants. A hybrid scheme that integrates a suitable transformation technology with forest ecosystems shows that they may have benefits from both economic and sustainability considerations.

Reduction of energy consumption in post-combustion carbon capture process via amine-functionalized metal-organic frameworks

In this study, CO2 capture performance of ethylenediamine-functionalized Mg-MOF-74 (EDMOF-74) suspended in 30 wt% monoethanolamine (MEA) aqueous solution is analyzed. A CO2 absorption experiment was performed in a bubble column reactor based on EDMOF-74 concentrations of 0.005, 0.01, 0.05, and 0.1 wt% for different ethylenediamine loadings. It shows that EDMOF-74/30 wt% MEA mixtures improve CO2 absorption performance by a maximum of 7.18 % as compared with the base fluid. Subsequent experiment based on large-volume feed gas reveals a less volatile CO2 absorption rate. By adding EDMOF-74 to the 30 wt% MEA aqueous solution in a cyclic CO2 absorption experiment to evaluate its industrial application, an increase in durability is indicated, which implies a reduction in energy consumption during CO2 regeneration. A feasibility study on the reduction of CO2 regeneration energy was investigated in terms of the results of cyclic experiment and the facility status of Boryeong power plant. The CO2 regeneration energy can be reduced by 13.64 %, which corresponds to a decrease of 484,233 MWht/year for 1 unit of the Boryeong power plant. The abovementioned approach is expected to compensate for the disadvantages of MEA in the industrial CO2 capture process, i.e., low CO2 capacity and high CO2 regeneration energy input.

Robust control and flexible operation for commercial-scale coal-fired power plant with solvent-based post-combustion carbon capture

Coal-fired power plant integrated with post-combustion carbon capture (CFPP-PCC) process exhibits strong nonlinearity and multi-variable connections. These dynamics along with unknown disturbances make it a challenging task to realize robust control and flexible operation in CFPP-PCC system. For this reason, this paper develops an extended state observer based stable model predictive control (ESOSMPC) in order to reject unknown disturbances and to achieve flexible operation with closed-loop stability. In the proposed control structure, an extended state observer is utilized to give accurate estimation for plant behavior change and unknown disturbances. This information will be used in active disturbance rejection, which aims to alleviate negative effects of disturbances and to enhance control performance. Stable model predictive control with infinite input-output based objective function is developed in order to fulfill Lyapunov stability condition, guaranteeing a stable operation for the integrated process. The proposed controller is compared with conventional MPC/PID controller under varying working conditions. Simulation results show that the presented ESOSMPC is able to achieve robust control in a multi-disturbance situation and to attain flexible operation in a broad-range load variation scenario.

Dynamic modeling and coupling characteristics analysis of biomass power plant integrated with carbon capture process

Biomass direct-fired circulating fluidized bed boiler has distinguished advantages of strong fuel adaptability, high combustion efficiency and low NOX emission, thus has been regarded as one of the important pathways for biomass utilization. Retrofitting the biomass direct-fired circulating fluidized bed boiler power plant (BCFBP) with carbon capture can strongly support the goal of carbon neutrality, because negative CO2 emission is achieved during the power generation. Nevertheless, the biomass direct-fired circulating fluidized bed boiler is sensitive to the combustion condition, high in operating costs, slow in dynamic response and poor in regulating capability. The integration of carbon capture may pose significant changes on the operating safety, efficiency and flexibility. A comprehensive analysis is thus required to understand the interactions between the BCFBP and carbon capture under various operating conditions. To this end, this paper develops a plant-wide dynamic model for a 130 ton/h BCFBP integrated with solvent-based post-combustion carbon capture (PCC) system. Multi-stage models of biomass combustion, steam generation and steam turbine-feedwater heater systems are developed to represent the dynamic interactions among biomass, heat, electricity and carbon, so that the impacts of BCFBP operation on the PCC process can be evaluated. Detailed BCFBP-PCC connecting system model are also developed to reflect the dynamic changes of steam/water flowrate, pressure and temperature in the steam turbine system caused by the integration of PCC. The developed model is then used to analyze the system interactions, operating costs, negative carbon capability and load ramping flexibility of the integrated BCFBP-PCC. Results show that the integration of PCC 1) causes significant impacts on the water/steam parameters of the steam turbine-feedwater heaters behind the reboiler steam extraction point; 2) reduces the power output of BCFBP by 26.12 % under 95 % CO2 capture level condition; 3) expands the power output variation range of the BCFBP from 22.3 to 36.6 MWe and provides the negative CO2 emission capacity from 2.2 to 6.9 kg CO2/s; 4) offers a feasible way to improve the power ramping performance through flexible distribution of the water/steam in the steam turbine-feedwater heater system. This paper provides specific guidance for the design, retrofit and operation of the BCFBP-PCC plant.

Evaluating the thermodynamic potential for carbon capture from internal combustion engines

This work explores the potential for use of carbon dioxide separation processes, colloquially known as carbon capture, to accelerate decarbonization of the transport sector. Thermal swing absorption processes using an aqueous, CO2-selective solvent, provide an efficient means of separating CO2 from other exhaust gas constituents. Amine-based solvents–well known from acid gas treating and other post-combustion carbon capture processes–are highly selective, have a fast rate of reaction with CO2, and can use waste heat to drive the separation process. This work demonstrates how amine-based processes can be deployed for carbon removal from a generic exhaust gas source produced by an internal combustion engine (ICE) using waste heat in the exhaust. It includes an estimation of the exhaust enthalpy-limited capture rate for various sources considering the capture system performance, the CO2 concentration, and the exhaust temperature.CO2 capture rates of around 25–80% are shown to be thermodynamically feasible for various ICE applications using waste exhaust heat for solvent regeneration. Rates of around 15–50% are attainable without providing additional energy, if exhaust heat is also used to power the capture system pump and compressor. Although a higher exhaust CO2 concentration reduces the specific energy requirements of the separation process, the total energy required for a given capture rate increases due to the greater amount of CO2 removed. Thus, maximum capture rates are highest for applications with high exhaust temperature and low CO2 concentration (such as diesel generators), and lowest for applications with very low exhaust temperature such as ships. This analysis also shows that the potential for CO2 avoidance using carbon capture systems far exceeds that of organic rankine cycle waste heat recovery systems. Overall, expanding the use of carbon capture to ICE applications can provide an efficient means of utilizing waste exhaust heat while providing significant reductions in the energy industry's scope 3 greenhouse gas emissions.

An overview on the corrosion mechanisms and inhibition techniques for amine-based post-combustion carbon capture process

Among the available carbon capture technologies, post-combustion carbon capture based on amine has become a well-proven and efficient means of reducing greenhouse gas emissions on an industrial scale to address global climate issues. However, corrosive behavior inevitably occurs during the trapping process, which could lead to operational problems, shorten the life of the equipment, compromise the production of products, affect economic efficiency, or even threaten human health. In order to present a comprehensive overview of corrosion behavior in the process of CO2 absorption into amines, this paper covers the corrosion mechanisms, measurement techniques, and influencing factors. In addition, topics also cover in detail the corrosion mitigation measures of types of corrosion inhibitors and corrosion mitigation mechanisms. All exhibited information could provide a comprehensive knowledge of corrosion and corrosion inhibition in the carbon capture process and gave a pavement to facilitate further research in solving corrosion issues.

A comprehensive multidisciplinary investigation on CO2 capture from diesel engine.

Climate change and global warming are the visible consequences of the increased amount of carbon dioxide (CO2) in the atmosphere. Among the various sources of anthropogenic CO2 emission, the diesel engine has a significant contribution. The development of a reliable system to efficiently minimize CO2 emissions from diesel engines to the safest level is lacking in the open literature. Therefore, a comprehensive multidisciplinary approach has been applied in this paper to investigate the efficacy of the post-combustion carbon capture (PCC) process for the diesel engine. The experiments have been performed on the exhaust of a direct injection diesel engine at five different brake powers with blends of aqueous ammonia (AQ_NH3), monoethanolamine (MEA), N,N-dimethylethanolamine (DMEA), and 1-ethyl-3-methylimidazolium tetrafluoroborate (C2mim BF4) ionic liquid (IL) as an absorbent for CO2 capture. The reaction mechanism of these absorbent with CO2 are also studied by the geometrical, energetical, MESP, frontier molecular orbitals, and NBO analysis using the first-principles density functional theory (DFT) calculations. The maximum CO2 absorption efficiency of almost 97% was achieved for the blend consisting of 67% of AQ_NH3 and 33% of MEA. Moreover, AQ_MEA and blend of AQ_NH3, DMEA, and C2mim BF4 ionic liquid showed 96% and 94% CO2 absorption efficiency, respectively.

Study of cryogenic CO2 capture with solar-assisted VAR system

One of the major contributors to the rise in global warming potential (GWP) is the continuous accumulation of carbon dioxide (CO2) in the atmosphere. Carbon capture and storage (CCS) is a modern approach to capture CO2 from various industrial processes and store it efficiently for further use. In the cryogenic carbon capture method, CO2 is liquefied by condensation and separated from the CO2 contained gas. The CO2 capture by the cryogenic method can yield high purity CO2 and negligible secondary emissions. However, huge energy is required for the condensation process. In the present study, a low energy penalty method for a post-combustion carbon capture process by the application of the cryogenic technique is performed using process simulation. To reduce energy consumption, a solar integrated vapor absorption refrigeration (VAR) system is designed. The designed solar VAR system provides the required refrigeration cooling load for condensing CO2 in a flue gas stream. For this purpose, the flue gas mixture composed of CO2, N2, and water vapor with respective molar fractions of 15%, 75%, and 10% is considered. The mass flow rate of the flue gas considered is 673.4 kg/s at 1.1 bar and 40 °C. CO2 is separated by condensing the gas at a pressure of 40 bar and temperature of −28 °C. The heat energy required to operate the VAR is 83.3 MW at 75 °C which is supplied by the solar collector. The simulation result indicates that for a post-combustion process, a high-grade electrical energy penalty is found to be about 1.26 MJ/kg CO2 captured, which is better than the most common approaches like absorption, adsorption, and membrane methods. It is also observed that with the increase in the CO2 concentration from 15 to 25 mol% in the flue gas, the energy penalty is reduced by about 37.5%. The performance analysis is also carried out by varying the CO2 recovery rate and purity. It is observed that the energy penalty is decreased by about 10.3% with the increase of CO2 recovery from 90% to 100%. Also, the energy penalty is increased by 4.2% with the increase of CO2 purity from 95% to 100%. The specific CO2 capture process cost is found to be about 1.008 million USD/(kg.s−1).