Results of the 18-month test with MEA at the post-combustion capture pilot plant at Niederaussem – new impetus to solvent management, emissions and dynamic behaviour

Moser, Peter; Wiechers, Georg; Schmidt, Sandra; Monteiro, Juliana Garcia Moretz‐Sohn; Charalambous, Charithea; García, Susana; Fernández, Eva Sánchez

doi:10.1016/j.ijggc.2019.102945

Cited by 63 publications

(43 citation statements)

References 17 publications

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“…Thermal degradation is a result of the high temperatures and pressures in the stripping column, hence the limitation of 120°C [66]. As shown in Figure 12 this value is not exceeded at any point in the simulation, and Moser et al [67] showed minimal thermal degradation at 120°C during the 18 month test campaign at RWE's pilot-scaled capture plant in Niederaussem, Germany. Interestingly, the inlet stripper temperature directly correlates to the flowrate changes, shown more so in Scenario B and C as the magnitude of change is greater.…”

Section: Operating Scenariosmentioning

confidence: 83%

Transient CO2 capture for open-cycle gas turbines in future energy systems

Wilkes

Mukherjee

Brown

2021

Energy

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Section: Operating Scenariosmentioning

confidence: 83%

Transient CO2 capture for open-cycle gas turbines in future energy systems

Wilkes

Mukherjee

Brown

2021

Energy

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“…Another recent application of 30 wt.% MEA in a post‐combustion capture pilot plant was demonstrated at Niederaussem from August 2017 to February 2019 71 . The capture capacity of this facility is approximately 0.25 tons CO 2 /d with a capture efficiency of 90%.…”

Section: Chemical Absorption Absorbentmentioning

confidence: 99%

“…Another recent application of 30 wt.% MEA in a post-combustion capture pilot plant was demonstrated at Niederaussem from August 2017 to February 2019. 71 The capture capacity of this facility is approximately 0.25 tons CO 2 /d with a capture efficiency of 90%. This study focuses on the degradation of MEA which is defined by the formation of oxidative degradation products (acetate, formate and oxalate) and the accumulation of trace elements (chloride, sulphur, sulphate, nitrate and iron) in the solvent.…”

Section: Amine-based Absorbent Primary Aminesmentioning

confidence: 99%

“…or in terms of solvent consumption rate is approximately 0.21-0.35 kg MEA per ton of CO 2 . To reduce the degradation of solvent, Moser et al 71 proposed a solvent management strategy, namely an ion exchange-based reclaiming process to control the concentration of anionic degradation products and trace elements in MEA. In this process, a proprietary anion exchange resin was used to remove anionic trace elements from the solvent reducing the degradation degree of MEA.…”

Section: Amine-based Absorbent Primary Aminesmentioning

confidence: 99%

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Review of carbon capture absorbents for CO₂utilization

2022

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Carbon capture technologies have been recognized as a potential alternative to alleviate global warming. Carbon capture and storage (CCS) is preferred over carbon conversion and utilization (CCU) due to its lower operating costs and higher CO2 reduction capability. Nevertheless, CO2 utilization has the potential to be more economical if value‐added products are produced. This highlights the importance of assessing CO2 utilization routes and alternatives in carbon management. This review paper aims to evaluate the carbon utilization potential of major CO2‐capturing absorbents including amine, hydroxide, ionic liquid, amino acids and carbonate absorbents. All absorbents show potential application for CO2 utilization except for ionic liquids (ILs) due to their unclear CO2 capture mechanisms. Absorbents that require a desorption process for CO2 utilization include MEA, MDEA, K2CO3 and Na2CO3 due to their high absorption capacity. Industries have utilized the desorbed CO2 as chemical feedstocks, enhanced oil recovery (EOR) and mineral carbonation. For hydroxide absorbents and CaCO3, desorption of CO2 is unnecessary as the absorbed CO2 can be directly utilized to produce construction materials. Apart from that, the incorporation of advanced technologies and business models introduced by the fourth industrial revolution are plausible considerations to accelerate the development of carbon capture technologies. © 2022 Society of Chemical Industry and John Wiley & Sons, Ltd.

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“…The most well-known and broadly used benchmark solvent is monoethanolamine (MEA). 9 Its main disadvantages are that a significant amount of energy is required for its regeneration 10 and the comparatively high degradation rate. Research has focused on amine mixtures that have better energy performance, e.g., the CESAR1 solvent, which is a blend of 2-amino-2-methyl-1-propanol (AMP) and piperazine (Pz).…”

Section: Mainmentioning

confidence: 99%

Deep learning for industrial processes: Forecasting amine emissions from a carbon capture plant

Jablonka

Charalambous²,

Fernández³

et al. 2021

Preprint

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One of the main environmental impacts of amine-based carbon capture processes is the emission of the solvent and degradation products into the atmosphere. To mimic the mounting importance of intermittent operations of power plants we performed a stress test in which we measured the amine emissions from a pilot plant that has been in operation using a mixture of amines (CESAR1) in a slipstream from a coal-fired power plant. Understanding how changes in the operation far from the steady-state of the plant affect the emissions is key to designing emission mitigation strategies. However, conventional process modelling techniques struggle to capture the full dynamic, multivariate, and non-linear nature of this data. In this work, we report how a data-intensive approach can be used to learn the mapping between process and emissions from data. The resulting model can forecast the emissions, can be used to analyse the data and also perform in silico stress tests. By doing so, we reveal that emission mitigation strategies that work well for single component solvents (e.g. monoethanolamine) need to be revised for a mixture of solvents such as CESAR1. We expect that the combination of large amounts of data with flexible learning algorithms will impact the way we design and operate industrial processes, as we can now harvest information at conditions where conventional approaches fail.

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Results of the 18-month test with MEA at the post-combustion capture pilot plant at Niederaussem – new impetus to solvent management, emissions and dynamic behaviour

Cited by 63 publications

References 17 publications

Transient CO2 capture for open-cycle gas turbines in future energy systems

Transient CO2 capture for open-cycle gas turbines in future energy systems

Review of carbon capture absorbents for CO₂utilization

Deep learning for industrial processes: Forecasting amine emissions from a carbon capture plant

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Results of the 18-month test with MEA at the post-combustion capture pilot plant at Niederaussem – new impetus to solvent management, emissions and dynamic behaviour

Cited by 63 publications

References 17 publications

Transient CO2 capture for open-cycle gas turbines in future energy systems

Transient CO2 capture for open-cycle gas turbines in future energy systems

Review of carbon capture absorbents for CO2utilization

Deep learning for industrial processes: Forecasting amine emissions from a carbon capture plant

Contact Info

Product

Resources

About

Review of carbon capture absorbents for CO₂utilization