this work addresses the methodological challenges of undertaking techno-economic assessments of very early stage (technology readiness level 3–4) CO2 capture technologies. It draws lessons from a case study on CO2 capture from a natural gas combined cycle with exhaust gas recycle and electric swing adsorption technology. The paper shows that also for very early stage technologies it is possible to conduct techno-economic studies that give a sound first indication of feasibility, providing certain conditions are met. These conditions include the availability of initial estimates for the energy use of the capture technology, either from bench scale measurements, or from rigorous process models, and the possibility to draw up a generic (high level) equipment list. The paper shows that for meaningful comparison with incumbent technologies, the performance of very early stage technologies needs to be projected to a future, commercial state. To this end, the state of the art methods have to be adapted to control for the development and improvements that these technologies will undergo during the R&D cycle. We call this a hybrid approach. The paper also shows that CO2 capture technologies always need to be assessed in sympathy with the CO2 source (e.g. power plant) and compression plant, because otherwise unreliable conclusions could be drawn on their feasibility. For the case study, it is concluded that electric swing adsorption is unlikely to become economically competitive with current technologies, even in a highly optimised future state, where 50% of the regeneration duty is provided by LP steam and 50% by electricity: the net efficiency of an NGCC with EGR and optimised ESA (49.3%LHV; min–max 45.8–50.4%LHV) is lower than that of an NGCC with EGR and standard MEA (50.4%LHV). Also, investment and operational costs are higher than MEA, which together with ESA's lower efficiency leads to an unfavourable levelised cost of electricity: 103 €/MWh (min–max 93.89–117.31 €/MWh) for NGCC with ESA, versus 91 €/MWh for NGCC with MEA.@en

We studied the possibility of converting waste toilet paper (WTP) into electricity. WTP is a waste stream with continuous availability and negative cost, but it is difficult to handle, as it contains fecal matter. The process we explored had two stages: WTP gasification followed by direct conversion into electricity in a high-temperature solid-oxide fuel cell (SOFC). The process was studied on a 10 ktpa scale by using real-life parameter values obtained from industrial sources. We presented the basic system design, as well as its electricity yield and overall efficiency on the basis of detailed mass- and energy-balance calculations. By explorative technoeconomic analysis and sensitivity analysis, we found an electric efficiency of 57 %, which is similar to that of a natural gas combined cycle plant. The levelized cost of electricity (LCOE) was 20.3 ¢ kWh−1, which is comparable at present to that of residential photovoltaic installations. The system's capital costs are relatively high, mainly as a result of SOFC investment costs, but we expect these costs to decrease as the market of cells develops. The operating costs are relatively low, partly thanks to the high thermodynamic efficiency (≈70 %). Currently, the fuel costs are negative (because we use waste as a raw material), yet this could change if the value of WTP would increase as a result of this process. Learning effects could make the system more competitive in the future with an LCOE of approximately 11 ¢ kWh−1.@en

Uncertainty analysis is a key element of sound techno-economic analysis (TEA) of CO2 Capture and Storage (CCS) technologies and systems, and in the communication of TEA results. Many CCS technologies are relatively novel, with only few large-scale projects constructed and in operation to date. Therefore, uncertainties in technology performance and costs are often substantial, making it imperative that they be characterized and reported. Although uncertainty analysis itself is not novel, with some methods already frequently used by the CCS TEA community, a document that provides a comprehensive overview of methods and approaches, as well as guidance on their selection and use, is still lacking. Given its importance, we seek to fill this gap by providing a critical review of uncertainty analysis methods along with guidance on the selection and use of these methods for CCS TEAs, highlighting good practice and examples from the CCS literature. The paper starts by identifying the different audiences for CCS TEAs, the different modelling approaches available for CCS technology performance and cost analysis, and the different roles that uncertainty analysis may play. It then continues to discuss established, as well as emerging, uncertainty analysis methods and addresses how and when each method is best used, as well as common pitfalls. We argue that the most commonly used method of one-parameter-at-a-time ‘local’ sensitivity analysis may often be a suboptimal choice, and that other approaches may be more suitable or lead to more insight, especially since uncertainty analysis software is becoming more widespread and easier to use. Finally, the paper discusses the benefits of advanced uses of uncertainty analysis in, for instance, the design of CCS experiments or in the design and planning of CCS infrastructure. Sound uncertainty analysis has an important role to play in TEAs of CCS technologies and systems, and there are many opportunities to bring the use of uncertainty analysis to a higher level than currently practiced. This review of and guidance on available methods is intended to help accelerate continued methods development and their application to more robust and meaningful CCS performance and costing studies.@en

Uncertainty analysis is a key element of sound techno-economic analysis (TEA) of CO2 Capture and Storage (CCS) technologies and systems, and in the communication of TEA results. Many CCS technologies are relatively novel, with only few large-scale projects constructed and in operation to date. Therefore, uncertainties in technology performance and costs are often substantial, making it imperative that they be characterized and reported. Although uncertainty analysis itself is not novel, with some methods already frequently used by the CCS TEA community, a document that provides a comprehensive overview of methods and approaches, as well as guidance on their selection and use, is still lacking. Given its importance, we seek to fill this gap by providing a critical review of uncertainty analysis methods along with guidance on the selection and use of these methods for CCS TEAs, highlighting good practice and examples from the CCS literature. The paper starts by identifying the different audiences for CCS TEAs, the different modelling approaches available for CCS technology performance and cost analysis, and the different roles that uncertainty analysis may play. It then continues to discuss established, as well as emerging, uncertainty analysis methods and addresses how and when each method is best used, as well as common pitfalls. We argue that the most commonly used method of one-parameter-at-a-time ‘local’ sensitivity analysis may often be a suboptimal choice, and that other approaches may be more suitable or lead to more insight, especially since uncertainty analysis software is becoming more widespread and easier to use. Finally, the paper discusses the benefits of advanced uses of uncertainty analysis in, for instance, the design of CCS experiments or in the design and planning of CCS infrastructure. Sound uncertainty analysis has an important role to play in TEAs of CCS technologies and systems, and there are many opportunities to bring the use of uncertainty analysis to a higher level than currently practiced. This review of and guidance on available methods is intended to help accelerate continued methods development and their application to more robust and meaningful CCS performance and costing studies.@en

Uncertainty analysis is a key element of sound techno-economic analysis (TEA) of CO2 Capture and Storage (CCS) technologies and systems, and in the communication of TEA results. Many CCS technologies are relatively novel, with only few large-scale projects constructed and in operation to date. Therefore, uncertainties in technology performance and costs are often substantial, making it imperative that they be characterized and reported. Although uncertainty analysis itself is not novel, with some methods already frequently used by the CCS TEA community, a document that provides a comprehensive overview of methods and approaches, as well as guidance on their selection and use, is still lacking. Given its importance, we seek to fill this gap by providing a critical review of uncertainty analysis methods along with guidance on the selection and use of these methods for CCS TEAs, highlighting good practice and examples from the CCS literature. The paper starts by identifying the different audiences for CCS TEAs, the different modelling approaches available for CCS technology performance and cost analysis, and the different roles that uncertainty analysis may play. It then continues to discuss established, as well as emerging, uncertainty analysis methods and addresses how and when each method is best used, as well as common pitfalls. We argue that the most commonly used method of one-parameter-at-a-time ‘local’ sensitivity analysis may often be a suboptimal choice, and that other approaches may be more suitable or lead to more insight, especially since uncertainty analysis software is becoming more widespread and easier to use. Finally, the paper discusses the benefits of advanced uses of uncertainty analysis in, for instance, the design of CCS experiments or in the design and planning of CCS infrastructure. Sound uncertainty analysis has an important role to play in TEAs of CCS technologies and systems, and there are many opportunities to bring the use of uncertainty analysis to a higher level than currently practiced. This review of and guidance on available methods is intended to help accelerate continued methods development and their application to more robust and meaningful CCS performance and costing studies.@en

Uncertainty analysis is a key element of sound techno-economic analysis (TEA) of CO2 Capture and Storage (CCS) technologies and systems, and in the communication of TEA results. Many CCS technologies are relatively novel, with only few large-scale projects constructed and in operation to date. Therefore, uncertainties in technology performance and costs are often substantial, making it imperative that they be characterized and reported. Although uncertainty analysis itself is not novel, with some methods already frequently used by the CCS TEA community, a document that provides a comprehensive overview of methods and approaches, as well as guidance on their selection and use, is still lacking. Given its importance, we seek to fill this gap by providing a critical review of uncertainty analysis methods along with guidance on the selection and use of these methods for CCS TEAs, highlighting good practice and examples from the CCS literature. The paper starts by identifying the different audiences for CCS TEAs, the different modelling approaches available for CCS technology performance and cost analysis, and the different roles that uncertainty analysis may play. It then continues to discuss established, as well as emerging, uncertainty analysis methods and addresses how and when each method is best used, as well as common pitfalls. We argue that the most commonly used method of one-parameter-at-a-time ‘local’ sensitivity analysis may often be a suboptimal choice, and that other approaches may be more suitable or lead to more insight, especially since uncertainty analysis software is becoming more widespread and easier to use. Finally, the paper discusses the benefits of advanced uses of uncertainty analysis in, for instance, the design of CCS experiments or in the design and planning of CCS infrastructure. Sound uncertainty analysis has an important role to play in TEAs of CCS technologies and systems, and there are many opportunities to bring the use of uncertainty analysis to a higher level than currently practiced. This review of and guidance on available methods is intended to help accelerate continued methods development and their application to more robust and meaningful CCS performance and costing studies.@en

Uncertainty analysis is a key element of sound techno-economic analysis (TEA) of CO2 Capture and Storage (CCS) technologies and systems, and in the communication of TEA results. Many CCS technologies are relatively novel, with only few large-scale projects constructed and in operation to date. Therefore, uncertainties in technology performance and costs are often substantial, making it imperative that they be characterized and reported. Although uncertainty analysis itself is not novel, with some methods already frequently used by the CCS TEA community, a document that provides a comprehensive overview of methods and approaches, as well as guidance on their selection and use, is still lacking. Given its importance, we seek to fill this gap by providing a critical review of uncertainty analysis methods along with guidance on the selection and use of these methods for CCS TEAs, highlighting good practice and examples from the CCS literature. The paper starts by identifying the different audiences for CCS TEAs, the different modelling approaches available for CCS technology performance and cost analysis, and the different roles that uncertainty analysis may play. It then continues to discuss established, as well as emerging, uncertainty analysis methods and addresses how and when each method is best used, as well as common pitfalls. We argue that the most commonly used method of one-parameter-at-a-time ‘local’ sensitivity analysis may often be a suboptimal choice, and that other approaches may be more suitable or lead to more insight, especially since uncertainty analysis software is becoming more widespread and easier to use. Finally, the paper discusses the benefits of advanced uses of uncertainty analysis in, for instance, the design of CCS experiments or in the design and planning of CCS infrastructure. Sound uncertainty analysis has an important role to play in TEAs of CCS technologies and systems, and there are many opportunities to bring the use of uncertainty analysis to a higher level than currently practiced. This review of and guidance on available methods is intended to help accelerate continued methods development and their application to more robust and meaningful CCS performance and costing studies.@en

Uncertainty analysis is a key element of sound techno-economic analysis (TEA) of CO2 Capture and Storage (CCS) technologies and systems, and in the communication of TEA results. Many CCS technologies are relatively novel, with only few large-scale projects constructed and in operation to date. Therefore, uncertainties in technology performance and costs are often substantial, making it imperative that they be characterized and reported. Although uncertainty analysis itself is not novel, with some methods already frequently used by the CCS TEA community, a document that provides a comprehensive overview of methods and approaches, as well as guidance on their selection and use, is still lacking. Given its importance, we seek to fill this gap by providing a critical review of uncertainty analysis methods along with guidance on the selection and use of these methods for CCS TEAs, highlighting good practice and examples from the CCS literature. The paper starts by identifying the different audiences for CCS TEAs, the different modelling approaches available for CCS technology performance and cost analysis, and the different roles that uncertainty analysis may play. It then continues to discuss established, as well as emerging, uncertainty analysis methods and addresses how and when each method is best used, as well as common pitfalls. We argue that the most commonly used method of one-parameter-at-a-time ‘local’ sensitivity analysis may often be a suboptimal choice, and that other approaches may be more suitable or lead to more insight, especially since uncertainty analysis software is becoming more widespread and easier to use. Finally, the paper discusses the benefits of advanced uses of uncertainty analysis in, for instance, the design of CCS experiments or in the design and planning of CCS infrastructure. Sound uncertainty analysis has an important role to play in TEAs of CCS technologies and systems, and there are many opportunities to bring the use of uncertainty analysis to a higher level than currently practiced. This review of and guidance on available methods is intended to help accelerate continued methods development and their application to more robust and meaningful CCS performance and costing studies.@en

Uncertainty analysis is a key element of sound techno-economic analysis (TEA) of CO2 Capture and Storage (CCS) technologies and systems, and in the communication of TEA results. Many CCS technologies are relatively novel, with only few large-scale projects constructed and in operation to date. Therefore, uncertainties in technology performance and costs are often substantial, making it imperative that they be characterized and reported. Although uncertainty analysis itself is not novel, with some methods already frequently used by the CCS TEA community, a document that provides a comprehensive overview of methods and approaches, as well as guidance on their selection and use, is still lacking. Given its importance, we seek to fill this gap by providing a critical review of uncertainty analysis methods along with guidance on the selection and use of these methods for CCS TEAs, highlighting good practice and examples from the CCS literature. The paper starts by identifying the different audiences for CCS TEAs, the different modelling approaches available for CCS technology performance and cost analysis, and the different roles that uncertainty analysis may play. It then continues to discuss established, as well as emerging, uncertainty analysis methods and addresses how and when each method is best used, as well as common pitfalls. We argue that the most commonly used method of one-parameter-at-a-time ‘local’ sensitivity analysis may often be a suboptimal choice, and that other approaches may be more suitable or lead to more insight, especially since uncertainty analysis software is becoming more widespread and easier to use. Finally, the paper discusses the benefits of advanced uses of uncertainty analysis in, for instance, the design of CCS experiments or in the design and planning of CCS infrastructure. Sound uncertainty analysis has an important role to play in TEAs of CCS technologies and systems, and there are many opportunities to bring the use of uncertainty analysis to a higher level than currently practiced. This review of and guidance on available methods is intended to help accelerate continued methods development and their application to more robust and meaningful CCS performance and costing studies.@en

Uncertainty analysis is a key element of sound techno-economic analysis (TEA) of CO2 Capture and Storage (CCS) technologies and systems, and in the communication of TEA results. Many CCS technologies are relatively novel, with only few large-scale projects constructed and in operation to date. Therefore, uncertainties in technology performance and costs are often substantial, making it imperative that they be characterized and reported. Although uncertainty analysis itself is not novel, with some methods already frequently used by the CCS TEA community, a document that provides a comprehensive overview of methods and approaches, as well as guidance on their selection and use, is still lacking. Given its importance, we seek to fill this gap by providing a critical review of uncertainty analysis methods along with guidance on the selection and use of these methods for CCS TEAs, highlighting good practice and examples from the CCS literature. The paper starts by identifying the different audiences for CCS TEAs, the different modelling approaches available for CCS technology performance and cost analysis, and the different roles that uncertainty analysis may play. It then continues to discuss established, as well as emerging, uncertainty analysis methods and addresses how and when each method is best used, as well as common pitfalls. We argue that the most commonly used method of one-parameter-at-a-time ‘local’ sensitivity analysis may often be a suboptimal choice, and that other approaches may be more suitable or lead to more insight, especially since uncertainty analysis software is becoming more widespread and easier to use. Finally, the paper discusses the benefits of advanced uses of uncertainty analysis in, for instance, the design of CCS experiments or in the design and planning of CCS infrastructure. Sound uncertainty analysis has an important role to play in TEAs of CCS technologies and systems, and there are many opportunities to bring the use of uncertainty analysis to a higher level than currently practiced. This review of and guidance on available methods is intended to help accelerate continued methods development and their application to more robust and meaningful CCS performance and costing studies.@en

Uncertainty analysis is a key element of sound techno-economic analysis (TEA) of CO2 Capture and Storage (CCS) technologies and systems, and in the communication of TEA results. Many CCS technologies are relatively novel, with only few large-scale projects constructed and in operation to date. Therefore, uncertainties in technology performance and costs are often substantial, making it imperative that they be characterized and reported. Although uncertainty analysis itself is not novel, with some methods already frequently used by the CCS TEA community, a document that provides a comprehensive overview of methods and approaches, as well as guidance on their selection and use, is still lacking. Given its importance, we seek to fill this gap by providing a critical review of uncertainty analysis methods along with guidance on the selection and use of these methods for CCS TEAs, highlighting good practice and examples from the CCS literature. The paper starts by identifying the different audiences for CCS TEAs, the different modelling approaches available for CCS technology performance and cost analysis, and the different roles that uncertainty analysis may play. It then continues to discuss established, as well as emerging, uncertainty analysis methods and addresses how and when each method is best used, as well as common pitfalls. We argue that the most commonly used method of one-parameter-at-a-time ‘local’ sensitivity analysis may often be a suboptimal choice, and that other approaches may be more suitable or lead to more insight, especially since uncertainty analysis software is becoming more widespread and easier to use. Finally, the paper discusses the benefits of advanced uses of uncertainty analysis in, for instance, the design of CCS experiments or in the design and planning of CCS infrastructure. Sound uncertainty analysis has an important role to play in TEAs of CCS technologies and systems, and there are many opportunities to bring the use of uncertainty analysis to a higher level than currently practiced. This review of and guidance on available methods is intended to help accelerate continued methods development and their application to more robust and meaningful CCS performance and costing studies.@en

Uncertainty analysis is a key element of sound techno-economic analysis (TEA) of CO2 Capture and Storage (CCS) technologies and systems, and in the communication of TEA results. Many CCS technologies are relatively novel, with only few large-scale projects constructed and in operation to date. Therefore, uncertainties in technology performance and costs are often substantial, making it imperative that they be characterized and reported. Although uncertainty analysis itself is not novel, with some methods already frequently used by the CCS TEA community, a document that provides a comprehensive overview of methods and approaches, as well as guidance on their selection and use, is still lacking. Given its importance, we seek to fill this gap by providing a critical review of uncertainty analysis methods along with guidance on the selection and use of these methods for CCS TEAs, highlighting good practice and examples from the CCS literature. The paper starts by identifying the different audiences for CCS TEAs, the different modelling approaches available for CCS technology performance and cost analysis, and the different roles that uncertainty analysis may play. It then continues to discuss established, as well as emerging, uncertainty analysis methods and addresses how and when each method is best used, as well as common pitfalls. We argue that the most commonly used method of one-parameter-at-a-time ‘local’ sensitivity analysis may often be a suboptimal choice, and that other approaches may be more suitable or lead to more insight, especially since uncertainty analysis software is becoming more widespread and easier to use. Finally, the paper discusses the benefits of advanced uses of uncertainty analysis in, for instance, the design of CCS experiments or in the design and planning of CCS infrastructure. Sound uncertainty analysis has an important role to play in TEAs of CCS technologies and systems, and there are many opportunities to bring the use of uncertainty analysis to a higher level than currently practiced. This review of and guidance on available methods is intended to help accelerate continued methods development and their application to more robust and meaningful CCS performance and costing studies.@en

Uncertainty analysis is a key element of sound techno-economic analysis (TEA) of CO2 Capture and Storage (CCS) technologies and systems, and in the communication of TEA results. Many CCS technologies are relatively novel, with only few large-scale projects constructed and in operation to date. Therefore, uncertainties in technology performance and costs are often substantial, making it imperative that they be characterized and reported. Although uncertainty analysis itself is not novel, with some methods already frequently used by the CCS TEA community, a document that provides a comprehensive overview of methods and approaches, as well as guidance on their selection and use, is still lacking. Given its importance, we seek to fill this gap by providing a critical review of uncertainty analysis methods along with guidance on the selection and use of these methods for CCS TEAs, highlighting good practice and examples from the CCS literature. The paper starts by identifying the different audiences for CCS TEAs, the different modelling approaches available for CCS technology performance and cost analysis, and the different roles that uncertainty analysis may play. It then continues to discuss established, as well as emerging, uncertainty analysis methods and addresses how and when each method is best used, as well as common pitfalls. We argue that the most commonly used method of one-parameter-at-a-time ‘local’ sensitivity analysis may often be a suboptimal choice, and that other approaches may be more suitable or lead to more insight, especially since uncertainty analysis software is becoming more widespread and easier to use. Finally, the paper discusses the benefits of advanced uses of uncertainty analysis in, for instance, the design of CCS experiments or in the design and planning of CCS infrastructure. Sound uncertainty analysis has an important role to play in TEAs of CCS technologies and systems, and there are many opportunities to bring the use of uncertainty analysis to a higher level than currently practiced. This review of and guidance on available methods is intended to help accelerate continued methods development and their application to more robust and meaningful CCS performance and costing studies.@en

After a 13,000-hour test campaign with aqueous 30 wt% MEA (2-aminoethanol) solvent at the CO2 capture pilot plant at Niederaussem, another long-term test was carried out as part of the ALIGN-CCUS project. This test ran for more than 12,275 hours with aqueous AMP/PZ (2-Amino-2-methyl-1-propanol/piperazine) solvent, named CESAR1 (3.0 molar AMP (~26.74 wt%) and 1.5 molar PZ (~12.92 wt. %)). A minimum specific reboiler duty of 2,970 MJ/tCO2 was identified for the capture plant operation with four active absorber beds (total 16 m packing height) and intercooling (40°C). Neither a lower desorber pressure of 1.5 bar(a), instead of 1.75 bar(a), nor a change of the different positions of intercooling had a significant effect on energy consumption. Reduction of the active packing height to three beds (i.e., 12 m), resulted in a moderately higher specific energy demand (+100 MJ/tCO2). Tests with CO2 capture rates between 90 and 98% showed only a small increase of the specific energy demand at 95% (+20 MJ/tCO2) and four active packings (98%: +250 MJ/tCO2). The average solvent consumption of CESAR1 during 400 days of operation was 0.45 kg/tCO2 and is lower than for MEA if the phase of accelerated non-linear degradation of MEA is taken into account. CESAR1 follows a slow-progressing linear degradation behavior; neither a critical metal ion concentration threshold value could be found that triggers fast degradation nor a correlation between accumulated trace components or metal ion concentrations in the solvent and the degradation rate was observed. Highly transient tests were conducted to investigate the dynamic behavior of the capture plant and subsequently special settings were chosen to stimulate high emissions for the investigation of aerosol-based emissions, connected with performance tests of several emission mitigation measures: single water wash, double water wash, acid wash, dry bed, wet electric precipitator and flue gas pre-treatment. When applying the dry bed configuration, emissions of AMP between 15 - 20 mg/Nm3, PZ between 3 - 7 mg/Nm3, and NH3 below 3 mg/Nm3 were achieved.@en

After a 13,000-hour test campaign with aqueous 30 wt% MEA (2-aminoethanol) solvent at the CO2 capture pilot plant at Niederaussem, another long-term test was carried out as part of the ALIGN-CCUS project. This test ran for more than 12,275 hours with aqueous AMP/PZ (2-Amino-2-methyl-1-propanol/piperazine) solvent, named CESAR1 (3.0 molar AMP (~26.74 wt%) and 1.5 molar PZ (~12.92 wt. %)). A minimum specific reboiler duty of 2,970 MJ/tCO2 was identified for the capture plant operation with four active absorber beds (total 16 m packing height) and intercooling (40°C). Neither a lower desorber pressure of 1.5 bar(a), instead of 1.75 bar(a), nor a change of the different positions of intercooling had a significant effect on energy consumption. Reduction of the active packing height to three beds (i.e., 12 m), resulted in a moderately higher specific energy demand (+100 MJ/tCO2). Tests with CO2 capture rates between 90 and 98% showed only a small increase of the specific energy demand at 95% (+20 MJ/tCO2) and four active packings (98%: +250 MJ/tCO2). The average solvent consumption of CESAR1 during 400 days of operation was 0.45 kg/tCO2 and is lower than for MEA if the phase of accelerated non-linear degradation of MEA is taken into account. CESAR1 follows a slow-progressing linear degradation behavior; neither a critical metal ion concentration threshold value could be found that triggers fast degradation nor a correlation between accumulated trace components or metal ion concentrations in the solvent and the degradation rate was observed. Highly transient tests were conducted to investigate the dynamic behavior of the capture plant and subsequently special settings were chosen to stimulate high emissions for the investigation of aerosol-based emissions, connected with performance tests of several emission mitigation measures: single water wash, double water wash, acid wash, dry bed, wet electric precipitator and flue gas pre-treatment. When applying the dry bed configuration, emissions of AMP between 15 - 20 mg/Nm3, PZ between 3 - 7 mg/Nm3, and NH3 below 3 mg/Nm3 were achieved.@en

After a 13,000-hour test campaign with aqueous 30 wt% MEA (2-aminoethanol) solvent at the CO2 capture pilot plant at Niederaussem, another long-term test was carried out as part of the ALIGN-CCUS project. This test ran for more than 12,275 hours with aqueous AMP/PZ (2-Amino-2-methyl-1-propanol/piperazine) solvent, named CESAR1 (3.0 molar AMP (~26.74 wt%) and 1.5 molar PZ (~12.92 wt. %)). A minimum specific reboiler duty of 2,970 MJ/tCO2 was identified for the capture plant operation with four active absorber beds (total 16 m packing height) and intercooling (40°C). Neither a lower desorber pressure of 1.5 bar(a), instead of 1.75 bar(a), nor a change of the different positions of intercooling had a significant effect on energy consumption. Reduction of the active packing height to three beds (i.e., 12 m), resulted in a moderately higher specific energy demand (+100 MJ/tCO2). Tests with CO2 capture rates between 90 and 98% showed only a small increase of the specific energy demand at 95% (+20 MJ/tCO2) and four active packings (98%: +250 MJ/tCO2). The average solvent consumption of CESAR1 during 400 days of operation was 0.45 kg/tCO2 and is lower than for MEA if the phase of accelerated non-linear degradation of MEA is taken into account. CESAR1 follows a slow-progressing linear degradation behavior; neither a critical metal ion concentration threshold value could be found that triggers fast degradation nor a correlation between accumulated trace components or metal ion concentrations in the solvent and the degradation rate was observed. Highly transient tests were conducted to investigate the dynamic behavior of the capture plant and subsequently special settings were chosen to stimulate high emissions for the investigation of aerosol-based emissions, connected with performance tests of several emission mitigation measures: single water wash, double water wash, acid wash, dry bed, wet electric precipitator and flue gas pre-treatment. When applying the dry bed configuration, emissions of AMP between 15 - 20 mg/Nm3, PZ between 3 - 7 mg/Nm3, and NH3 below 3 mg/Nm3 were achieved.@en

An approach for the techno-economic assessment of power plants with and without carbon capture and storage (CCS) is proposed. A state-of-the-art natural gas combined cycle (NGCC) power plant is selected equipped with post-combustion CO2 capture technology (MEA). The technoeconomic indicators are calculated using both the conventional and part load approaches. The economic results also show significant differences between the full load and the part load approaches. The results show that the levelized cost of electricity (LCOE) of gas-based power generation with CCS will more likely be above 100 €/MWh than below this value. This inherently also leads to an increase of the cost of CO2 avoided in the order of 20-100%. The observed differences between the full load and part load approaches showcase the necessity for including real dispatch profiles when calculating the technoeconomic performance of CCS power.@en

CO2 utilisation is gaining interest as a potential element towards a sustainable economy. CO2 can be used as feedstock in the synthesis of fuels, chemicals and polymers. This study presents a prospective assessment of carbon capture from a hydrogen unit at a refinery, where the CO2 is either stored, or partly stored and partly utilised for polyols production. A methodology integrating technical, economic and environmental models with uncertainty analysis is used to assess the performance of carbon capture and storage or utilisation at the refinery. Results show that only 10% of the CO2 captured from an industrial hydrogen unit can be utilised in a commercial-scale polyol plant. This option has limited potential for large scale CO2 mitigation from industrial sources. However, CO2 capture from a hydrogen unit and its utilisation for the synthesis of polyols provides an interesting alternative from an economic perspective. The costs of CO2-based polyol are estimated at 1200 €/t polyol, 16% lower than those of conventional polyol. Furthermore, the costs of storing the remaining CO2 are offset by the benefits of cheaper polyol production. Therefore, the combination of CO2 capture and partial utilisation provides an improved business case over capture and storage alone. The environmental assessment shows that the climate change potential of this CO2 utilisation system is 23% lower compared to a reference case in which no CO2 is captured at the refinery. Five other environmental impact categories included in this study present slightly better performance for the utilisation case than for the reference case.@en

This paper addresses the uncertainty and variability in techno-economic studies of carbon capture technologies, based on a detailed comparison of the results of different studies on postcombustion CO2 capture with advanced amines, and on an in-depth uncertainty analysis using a combination of sensitivity and pedigree analyses. The results show that despite efforts to harmonize capital cost estimates, the capital cost results of the same PCC carbon capture systems can still show large (65%) differences. This uncertainty may simply be inherent to early stage cost estimates. Amongst the most important causes for the variability shown in this work are differences in equipment sizing methods and purchased equipment cost estimates. This capital cost variability only mildly propagates into the Levelised Cost of Electricity and Cost of CO2 Avoided, more so in case of low power plant utilisation scenarios. To enhance insight into these uncertainties and enable their communication, the paper argues to use in-depth uncertainty evaluation for early stage techno-economic studies. It suggests to complement current practice of sensitivity analysis with pedigree analysis and to combine the results of both analyses in diagnostic diagrams. This may lead to more informed interpretation of the results of techno-economic studies, and helps focus techno-economic research efforts towards the parameters that most influence final performance indicators.@en

This paper addresses the uncertainty and variability in techno-economic studies of carbon capture technologies, based on a detailed comparison of the results of different studies on postcombustion CO2 capture with advanced amines, and on an in-depth uncertainty analysis using a combination of sensitivity and pedigree analyses. The results show that despite efforts to harmonize capital cost estimates, the capital cost results of the same PCC carbon capture systems can still show large (65%) differences. This uncertainty may simply be inherent to early stage cost estimates. Amongst the most important causes for the variability shown in this work are differences in equipment sizing methods and purchased equipment cost estimates. This capital cost variability only mildly propagates into the Levelised Cost of Electricity and Cost of CO2 Avoided, more so in case of low power plant utilisation scenarios. To enhance insight into these uncertainties and enable their communication, the paper argues to use in-depth uncertainty evaluation for early stage techno-economic studies. It suggests to complement current practice of sensitivity analysis with pedigree analysis and to combine the results of both analyses in diagnostic diagrams. This may lead to more informed interpretation of the results of techno-economic studies, and helps focus techno-economic research efforts towards the parameters that most influence final performance indicators.@en