Combined Flue Gas Cleanup Process for Simultaneous Removal of

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Combined Flue Gas Cleanup Process for Simultaneous Removal of SOx, NOx, and CO2—A Techno-Economic Analysis Amit Hajari, Marktus Atanga, Jeremy L. Hartvigsen, Ali Asghar Rownaghi, and Fateme Rezaei Energy Fuels, Just Accepted Manuscript • DOI: 10.1021/acs.energyfuels.6b02881 • Publication Date (Web): 27 Feb 2017 Downloaded from http://pubs.acs.org on February 28, 2017

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Combined Flue Gas Cleanup Process for Simultaneous Removal of SOx, NOx, and CO2—A Techno-Economic Analysis Amit Hajari, Marktus Atanga, Jeremy L. Hartvigsen, Ali Rownaghi, Fateme Rezaei* Department of Chemical & Biochemical Engineering, Missouri University of Science and Technology, 1101 N State Street, Rolla, MO, 65409, United States Abstract: Flue gas cleanup often requires the removal of SOx, NOx, and CO2 in separate units before emitted into the atmosphere. This step-wise treatment process incurs significant cost and energy penalty to the electricity production. A combined adsorption process based on pressure swing adsorption (PSA) by which these impurities are removed is envisioned as an efficient means of flue gas cleanup that can be applied relatively easily. In this study, the technological and economic feasibility of a combined separation process in which SOx, NOx, and CO2 are simultaneously removed from flue gas streams are assessed. Capital and operating costs are estimated based on sizing the equipment items and utilities needed and the potentials for increased energy efficiency are determined in relation to the required PSA performance. The energy saving potential for the adoption of 2-bed and 4-bed PSA cycle is compared with conventional FGD, SCR, and amine scrubbing units needed to clean up flue gas in a step-wise fashion. The results show that energy savings can be expected when the PSA removal efficiency is greater than 90%. In the case of a 550 MW coal-fired power plant, the proposed system will impose an energy penalty of 24% to the cost of electricity which is lower than that of current individual treatment units associated with SOx, NOx, and CO2 removal. This energy penalty corresponds to a cleanup cost of $57/ton of all impurities captured for a 2-bed, four-step PSA process with cycle time of 400 s, adsorption and desorption pressures of 10 and 1 bar, respectively and a purge flow rate of 100 mol/s. This techno-economic assessment shows that the integrated combined system can be an attractive technology compared to multi-step systems for the removal of flue gas impurities. Keywords: Techno-economic, CO2, SOx, NOx, Flue gas, Combined PSA process

1. Introduction

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It is a general consensus that flue gas emissions derived from coal- and natural gas-fired power plants pose serious environmental and health concerns.1 In particular, sulfur oxides (SOx) and nitrogen oxides (NOx) are regarded as the most toxic gases emitted into the atmosphere during the combustion of fossil fuels while carbon dioxide (CO2) is the major contributor to climate change.2,3 At present, a wide variety of technological options have been commercialized or proposed to capture these acidic gaseous impurities.4–10 The current state-of-the-art technologies for SOx and NOx removal include flue gas desulfurization (FGD) and selective catalytic reduction (SCR), respectively which are placed upstream of the power plant followed by a CO2 capture unit (amine scrubbing) in a sequential, stepwise fashion as demonstrated in Figure 1. These conventional processes are often multi-step and complex which require large land space with high capital cost.5,11–15 Furthermore, they suffer from a variety of operational problems such as equipment fouling and corrosion, solvent losses, liquid channeling, flooding and unwanted foaming.

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Figure 1: Process flow diagram of FGD, SCR and CO2 capture units. Efficient and cost-effective removal of flue gas impurities is of prime importance in various key industrial applications pertaining to energy, environment, and health. One possibility to intensify the efficiency and to address the drawbacks of current abatement processes is to integrate two or more separation processes into a single-step process for the simultaneous removal of CO2, SOx, and NOx from flue gas. This novel approach will lead to significant reduction in capital and operating cost and dramatically enhance the process efficiency, and ease of operation. Among several alternative separations, adsorptive removal of impurities is a potentially attractive route to the flue gas cleanup due to high capture efficiency, less environmental foot print and low cost, as compared to absorption and membrane technologies.2,7 Some common solid adsorbents including calcium-based materials, zeolites, activated carbons, metal-oxides, 3 ACS Paragon Plus Environment

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metal-organic frameworks (MOFs), and organic-inorganic hybrid materials have been used successfully in many studies for capturing CO2, SOx, and NOx. However, most past studies have focused primarily on the single-component adsorption,16–25 and only a few studies have addressed the simultaneous removal of these aforementioned gases.26–30 The success of the proposed combined cleanup process is heavily dependent on the ability of the adsorbent to effectively remove these impurities without dramatic capacity loss over many cycles. Among various solid adsorbents investigated so far, Mg-MOF-74,31,32 K-NaX,33 and secondary aminebased solid adsorbents34,35 have been theoretically and experimentally shown as promising candidates capable of removing these three types of acid gas impurities from flue gas. Therefore, such conceptual design is not far from reality and with the advancement in materials science and development of highly efficient adsorbents with long-term stability, it would be actually possible to implement this technology at a large industrial scale. In this work, the techno-economic analysis of a PSA system for CO2/SOx/NOx removal from flue gas was developed and compared with the current technologies to assess the potential implementation of the proposed system along with identifying the possible operational challenges. We considered the specific energy and capital requirements associated with building and implementing the PSA system while considering the impact of different design choices. Based on initial mass/energy balance equations and stream tables, an Aspen Plus flowsheet model was generated initially to establish the technological and economic feasibility of the process. Furthermore, a sensitivity analysis was performed by taking into account the impact of process parameters such as adsorption pressure, cycle time, purge flow rate, and working capacities on cleanup cost and recovery of the impurity gases. Often the biggest impediment to the implementation of lab-scale technologies at commercial scale is cost. This current study seeks to provide evidence that low-

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cost flue gas cleanup is possible with the use of combined PSA system that is capable of simultaneously capturing CO2, SOx, and NOx. 2. Methodology 2.1. Combined Flue Gas Cleanup Process Configuration and Simulation The proposed single-step flue gas cleanup process that simultaneously removes SOx, NOx, and CO2 in a PSA unit is schematically shown in Figure 2. This process is comprised of several units such as compressor, heat exchanger, turbine, flash separator, PSA adsorption and desorption beds, switching valves, and pumps. For this assessment, no post-treatment option for processing the captured impurities was considered, however, various follow-up technologies could be deployed to treat the captured CO2/SOx/NOx mixture. One of these follow-up treatment strategies is that after removing CO2/SOx/NOx impurities, the concentrated stream can be used to produce chemical by-products in a photobioreactor. Briefly, in this proposed post-treatment approach, the concentrated CO2/SOx/NOx stream from the PSA unit is directed to a water scrubber in which SOx and NOx gases are removed first by simply washing the stream with water. During this stage, the adsorbed oxides react with water to form the corresponding acids H2SO4, H2SO3, HNO3, and HNO2 as saleable by-products. In this manner, the SOx and NOx contaminants are captured in the liquid phase. In the next step, the gas enters a dryer followed by entering into a photobioreactor where CO2 is converted to other chemicals by algae species. The proposed post-treatment unit that includes water scrubber, dryer, and photobioreactor was not considered in this study since its influence on the process performance is expected to be relatively small. Therefore, we established the models mainly based on compression, dehydration, adsorption, and desorption units.

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Figure 2. Schematic diagram of 2-bed PSA system for combined flue gas cleanup.

2.1.1. Process Description

The proposed simultaneous SOx, NOx, and CO2 removal unit is shown in Figure 2. According to this design, the flue gas, which is typically emitted from a fossil-fuel power station, enters the plant at 1 bar and 110 °C with a flow rate of 2.4×106 m3/h and then it is compressed to 10 bar using a compressor (1→2). The compressed gas is cooled down by passing through a heat exchanger in which it exchanges heat with the clean flue gas stream (2→3). Consequently, the gas temperature drops to approximately 35 °C. Flue gas from a typical power plant contains 7 vol% water vapor, which must be removed from the stream before entering the PSA columns. The water removal from flue gas will be carried out in a flash separator unit (3→4) with the unit efficiency of 99%. In the next step, the dry gas stream is fed into a set of PSA columns. It should be pointed out here that no dryer was considered after the flash separator based on the high removal efficiency of the separator and also based on the assumption that the adsorbent is a water-tolerant material. Under high-pressure conditions, the toxic components in the gas stream 6 ACS Paragon Plus Environment

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are captured by the adsorbent material and clean flue gas (mainly N2 and O2) leaves from the top (5→6). The clean flue gas is then sent to a heat exchanger to cool down the compressed gas before emitting to the atmosphere (7→8). After adsorption step, the bed is depressurized from the bottom (9→10) during blowdown step. During purge step, the desorbed gas is collected from the bottom and pumped into the post-treatment unit (10→11). The conventional 2-bed, four-step design with cycle configuration shown in Figure 3 was considered here to demonstrate the economic feasibility of using a pressure swing adsorption for simultaneous flue gas cleanup, and more complex and advanced cycle designs are possible to enhance the efficiency of the process. To demonstrate this, a four-bed, six-step cycle design (the cycle configuration is shown in Figure S1, Supporting Information) was also considered and compared with the base case (i.e., 2-bed, four-step cycle).

2.1.2. Cycle Configuration

The 2-bed PSA cycle configuration considered here consists of four steps with the cycle duration of 400 s. The scheme and time schedule of this conventional PSA cycle is presented in Figure 3. The four steps are adsorption (AD) at high pressure (10 bar), countercurrent blowdown (BD) from 10 to 1 bar, countercurrent purge with light product (PR) at low pressure (1 bar) and finally, repressurization with light product (LPP) from 1 to 10 bar.

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Bed 1 Bed 2

BD 70 s

AD PR 60 s

BD LPP 70 s

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PR AD 200 s

LPP

Figure 3. Cycle scheme and time schedule for a 2-bed, four-step PSA process. AD: adsorption, BD: blowdown, PR: purge, and LPP: light product pressurization.

2.1.3. Process Simulation

The process design calculations for this study were performed using Aspen Plus 8.6 software, a commercial process simulator, coupled with an Aspen Adsim code for dynamic simulation of the PSA process. The PSA simulation was based on centered finite difference analysis while the thermodynamic method used in the model was based on Peng-Robinson equation of state (PREOS). Table 1 summarizes the feed stream conditions and composition used in the simulation which were obtained from a typical 550 MW coal-fired power plant. Other simulation parameters are presented in Table S1 (Supporting Information). Additionally, the mass, energy, and momentum balance equations used in simulation are presented in Supporting Information. In this study, SO2 and NO were considered as the representatives of SOx and NOx families, respectively because these oxides are the most prevalent forms of each family.34 Our design

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objective here was to achieve a removal efficiency of greater than 90% for all three components (i.e., CO2, SO2, and NO).

Table 1. Flue gas feed stream conditions and composition Target net power plant size (MW) Volumetric flow rate (m3/h) Temperature (°C) Pressure (kPa) Removal efficiency (%) Composition N2 (vol%) CO2 (vol%) O2 (vol%) H2O (vol%) SOx (ppm) NOx (ppm)

550 2.4×106 110 101.3 90 75 13 5 7 2000 2000

In addition, the system parameters and adsorbent properties for the PSA process are summarized in Table 2. Initially, a base pressure of 10 and 1 bar were assumed for adsorption and desorption steps, respectively with the cycle time on the order of 400 s. However, a sensitivity analysis was employed later to show the impacts of these parameters on the economics of the system. For our base case (Table 2), the adsorbent material considered was Mg-MOF-74, as an adsorbent of choice capable of selecting acidic gas impurities in flue gas. Recent molecular simulation studies indicated that Mg-MOF-74 is a promising material for simultaneous removal of CO2, SOx, NOx from flue gas mixtures.31,36 This material was demonstrated to show equilibrium capacities of 7.95, 1.60, and 1.60 mmol/g for CO2, SO2, and NO, respectively at 25 °C and 1 atm. The working capacities estimated at base conditions were also presented in Table 1. However, the working capacities of the selected adsorbent were subject to sensitivity analysis to investigate their effect on economic and technical performance of the process. The isotherm data taken from the literature31 were fitted by Extended Langmuir 9 ACS Paragon Plus Environment

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isotherm and the corresponding isotherm parameters are presented in Table S2 (Supporting Information). Further, the selectivity of these gases over nitrogen was assumed to be high (i.e., above 20), as this is the case for most of MOF materials, thus in our analysis, the influence of gas selectivity on the cleanup cost was ignored. Moreover, it should be mentioned here that for our base case, the PSA adsorber volume was estimated to be 92 m3 (9 m height and 2 m diameter) by assuming a flue gas volumetric flow rate of 2.4×106 m3/h, a bed packing density of 75%, and capture rate of 90%. The adsorbent was assumed to have pellet shape with diameter of 0.75 cm.

Table 2. System model parameters for 2-bed, four-step PSA process analysis PSA cycle Cycle time (s) Adsorption pressure (bar) Desorption pressure (bar) Purge flow rate (mol/s) Adsorbent bulk density (kg/m3) Adsorbent porosity CO2, SO2, NO working capacity (mol/kg) Adsorbent pellet diameter (cm)

four-step cycle 400 10 1 100 960 0.4 6.3, 0.8, 0.8 0.75

2.2. Combined Flue Gas Cleanup Process Economic Analysis 2.2.1. Capital Cost Estimation

The capital cost of the combined flue gas cleanup process was determined using module costing technique that relates the global cost to the purchase cost of the major units under base conditions.37 The additional direct and indirect costs such as instrumentation, piping foundations, construction overheads, and auxiliary facilities were also incorporated into the total module cost. Based on this analysis, the bare cost of each module was estimated using CBM = C0p FBM where C 0p and FBM are respectively, reference equipment cost and equipment unit bare module cost factor. The reference equipment cost was adjusted to the price level of 2015 using chemical engineering 10 ACS Paragon Plus Environment

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plant cost index (CEPCI) with the value of 547.4 compared to 382 in 1996.38 It should also be noted here that the capital cost estimations were based on the assumption of construction of a new plant (grassroots design) which can be broken into the following contributions: •

Total bare module cost ( ∑ i C BM,i ), which is the sum of the capital and installation costs of main equipment items.



The contingency costs (CC), which include unexpected expenses related to data cost uncertainty and flowsheet completeness and estimated at 15% of the total bare module cost ( C C = 0.15∑ i C BM,i ).39,40



The auxiliary facility costs (CAF), which take into account structures, services, and equipment not directly involved in the process.41 Such complementary items include land purchase, utility systems, off-sites, and site development.41,42 There are two main classifications of auxiliaries, utilities, and services. For this study, they were assumed to be 35% of the total bare module cost ( C AF = 0.35∑ i C BM,i ).



Total module cost (CTM) which was computed using C TM =



i

C BM,i + C C , whereas the

overall grassroots cost was obtained by CGR = CTM + C AF . The time required for the construction of the plant was assumed to be 2 years with finance distribution of 60% in the first year and 40% in the second year. 2.2.2. O&M Cost Estimation

Operation and maintenance (O&M) costs are typically estimated by considering all expenses associated with manufacturing, labor, insurance, and consumables. Generally, the O&M costs are broadly divided into two major categories, namely variable and fixed costs. Variable or direct costs consist of cost of consumables including raw materials (CRM), utility costs (CUT), operating

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labor fees (COL), and maintenance and repairs. Fixed or indirect O&M costs on the other hand include the local taxes, insurances, storage, and plant overhead costs. Local taxes and insurances were taken as 3.2% of fixed capital cost (CGR),42 whereas plant overhead costs were taken as 70.8% of operating labor cost plus 3.6% of fixed capital cost to cover the costs associated with operating auxiliary facilities that support the manufacturing process.42 Maintenance and repair costs that account for the costs of labor and materials associated with maintenance and repair were assumed to be 6% of fixed capital cost. The total O&M costs were given by CO&M = C RM + C UT + C OL + 0.13CGR .

The CRM was estimated from the current prices listed in chemical market report. Amount of adsorbent required per cycle was estimated from process material balance. The CUT includes the costs of major utility such as electricity and cooling water which were obtained from simulation data. The technique used for estimating the COL was based on the approach given by Ulrich.37 According to this method, COL depends on the number of both the processing units (Nnp) and operators (Nop) per shift. Assuming an annual operating salary of $56,000 and three shifts per day, the COL can be calculated as COL = $56,000 × Nop (6.29 + 0.23N np ) . The overall plant cost (COP) was calculated by summing the total capital (CTC) and O&M (CO&M) costs. The CTC was given by C TC = C GR + C land + C work where Cland and Cwork are respectively, land cost ($500,000) and working capital, estimated as C work = 0.1(CGR + C RM + C OL ) . All assumptions used in the cost estimation are summarized in Table 3. The costs estimations were done using CAPCOST software.42 Moreover, the cost of impurities removal using the proposed cleanup cost =

combined

process

was

estimated

using

this

equation:

COP . CO 2 /SO x /NO x avoided 12 ACS Paragon Plus Environment

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Table 3. Assumptions for capital and O&M costs estimation Base year Construction time period Finance distribution Cost estimation Contingency Auxiliary facility costs Operating hours Electricity price Cooling water price Adsorbent cost Maintenance and repair Insurances Operator wage No of operating labor

2015 2 years 0.6 in first and 0.4 in second year Module costing technique 15% of CBM 35% of CBM 365 day × 24 h $16.8/GJ $4.43/GJ $20/kg 6% of CGR 3.2% of CGR $56,000/year 8

3. Results and Discussion 3.1. Techno-Economic Evaluation The suitability of the combined flue gas cleanup process for a 550 MW power plant in terms of energy cost and capture efficiency is discussed. The capital cost components corresponding to each equipment are listed in Table S3 (Supporting Information) for our base case. It was assumed that the equipment units were made of nickel, mainly on the basis of corrosive nature of SOx/NOx gases.37 The results show that the major portion of the capital cost comes from the flue gas compressor (required to pressurize the feed to 10 bar) which makes up about 84% of the CGR whereas, the cost of PSA adsorbers is only 9% of the CGR. Thus, a noticeable reduction in cleanup cost could be observed if adsorption pressure is reduced. The techno-economic indicators of the combined cleanup process for 2-bed and 4-bed PSA design configurations along with conventional FGD, SCR, and amine scrubbing (MEA scrubbing), as separate units, are reported in Table 4. The cleanup cost using the proposed process is $57/ton of combined impurities avoided (CO2, SO2, NO). This will incur 24% energy

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penalty to the power plant. A 4-bed PSA process will result in a cleanup cost of $59/ton and an energy penalty of 24%. The higher cleanup cost for the 4-bed PSA design is primarily due to the higher capital cost requirement compared to the 2-bed design. In comparison, the published analyses suggest that for a typical 550 MW coal-fired power plant, a SO2 removal cost of up to $350/ton will be incurred for a $400/kW FGD capital cost.43,44 Similarly, the retrofit of a SCR unit will incur $300/kW capital cost and will expend about $2000/ton to remove NOx.43,44 Furthermore, the retrofit of a CO2 capture unit based on the benchmark MEA scrubbing technology with the removal rate of 65% will incur capital cost between $1000-1200/kW with $53/ton energy requirements, corresponding to 30% energy penalty.45,46 It is worth noting here that the high cleanup cost of SCR and FGD units could be justified by considering the low concentration of SOx/NOx gases in flue gas compared to CO2. Furthermore, due to the higher cost of ammonia and catalysts used in SCR process, the capture cost per ton of NOx is significantly higher than that of SOx (almost 10 times) with comparable concentrations in flue gas.

Table 4. Economic results for combined proposed process and comparison with individual units.

2-bed PSA 4-bed PSA MEA scrubbing47 FGD2 SCR2 a b

Recovery rate (%) >91a 90b 90 90 90

CTC (M$)

CO&M (M$)

129.5 138.2 96.2 0.6

88.1 88.3 2.7 1.65×10-2

Energy penalty (%) 24 24 30 1 -

Cleanup cost ($/ton) 56 59 53 350 3500

Year

2015 2015 2013 2001 1999

CO2/SO2/NO: 93/92/91 CO2/SO2/NO: 90/90/90

The economic results for the 2-bed and 4-bed PSA systems are shown in Figure 4a-b and

Figure S2a-b (Supporting Information), respectively. As evident from these Figures, for both 14 ACS Paragon Plus Environment

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cases, CTC represents approximately 57% of COP which is M$129.5 for 2-bed and M$138.2 for the 4-bed PSA system. The results show that adding two additional beds to improve the capture performance of the combined process increases the COP only marginally. The breakdown of the CO&M presented in Figure 4a reveals that the CUT contributes to 81.4% of the CO&M followed by maintenance and repair costs, plant overhead costs, tax and insurance, CRM, and COL with 8.0, 5.2, 4.2, 0.7, and 0.5% contributions to CO&M, respectively. As also shown in Figure 4b, for the 2-bed PSA system, the CTC and CO&M account for 60 and 40% of the overall plant cost (COP), respectively. It should be mentioned here that the energy from expansion of clean flue gas (10 to 1 bar) was used to offset some of the energy consumption of the flue gas compressor.48 100

100 Centrifugal pump

Plant overhead

80

CO&M

Maintenance &

Flash seprator

80

90

Tax and insurance

Adsorption column

repair

Heat exchanger

COL CRM

70 Flue gas compressor

CUT

% Contribution

90

% Contribution

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70 60 50 40 30

CTC

20

60

10 0

50

CGR

CO&M

COP

(a) (b) Figure 4. (a) Capital and O&M costs and (b) the overall plant cost of the 2-bed PSA process.

Considering the proposed post-treatment option for utilizing the concentrated CO2/SOx/NOx stream to make acid by-products (H2SO4, H2SO3, HNO3 and HNO2) before utilization in photobioreactor, the cleanup cost could be further reduced by $4/ton reaching $52/ton. This cost reduction was estimated based on the assumption that the commercial prices of H2SO4 and HNO3 are $70/ton and $225/ ton, respectively.

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3.2. Sensitivity Analysis Sensitivity analysis was performed in order to assess the effects of uncertainties of several key factors such as adsorption pressure, PSA cycle time, purge flow rate, and adsorbent working capacities on technological and economic performance of the combined cleanup process with respect to recovery and cleanup cost. It should be noted that for our sensitivity analyses purity was not considered as a metric here mainly because of dealing with three impurity gases instead of just one gas. Nevertheless, for our base case, the purity of CO2 alone (as the major component of the concentrated stream) was found to be about 73%. In addition, for our sensitivity analyses, only a 2-bed PSA system was considered.

3.2.1. Effect of Adsorption Pressure One of the key parameters affecting the adsorption performance of any PSA system is the adsorption pressure (or pressure ratio) which plays an important role in the recovery and purity of the enriched product. The effect of adsorption pressure at fixed desorption pressure (1 bar) on the recovery of the components and cleanup cost is presented in Figure 5. A pressure range of 510 bar was considered for analysis. It can be observed that at adsorption pressure of 5 bar, the recovery of CO2, SOx, and NOx reached 55, 56, and 55%, respectively with the cleanup cost of $66/ton. As the pressure increased, the recovery of gases was also increased reaching 93, 92, and 92%, respectively at 10 bar while the capture cost dropped to $57/ton. However, further increase in adsorption pressure to 15 bar drastically increased the cleanup cost from $57/ton to $73/ton while the recovery of the components remained above 90%. The higher cleanup cost at low pressure (i.e., 5 bar) could be attributed to decrease in recovery and the amount of impurities avoided, whereas the reduction in cleanup cost with pressure is due to increase in the recovery of

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impurity gases. When the adsorption pressure is increased from 5 to 10 bar, the amount of gas impurities in the product stream increases (i.e., recovery). Moreover, at higher feed pressures, the partial pressure of impurities increases which implies a higher adsorption capacity for the adsorbent, thus a smaller bed. However, further increase to 15 bar offsets any cost savings from improved recovery or smaller bed by the cost for a larger feed gas compressor. Clearly, a tradeoff exists between capital cost and recovery which dictates the cleanup cost, according to the equation of cleanup cost (see section 2.2.2.). The results show that the optimal cleanup cost could be obtained at feed pressures around 10 bar. Figure S3 (Supporting Information) also shows the variation in product throughput as a function of adsorption pressure. It is apparent from this Figure that throughput remains unaffected when the adsorption pressure varies from 5 to 15 bar, showing a constant value of 113 mol/kg/h.

70

Cleanup cost CO2

95

SO2

90

NO

85 80

65

75 70

60

Recovery (%)

100

75

Cleanup Cost ($/ton of impurity)

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65 60

55

55 50

50

5

6

7

8

9

10

12.5

15

Pressure (bar)

Figure 5. Effect of adsorption pressure on recovery and cleanup cost of the 2-bed PSA system, cycle time: 400 s, purge flow rate: 100 mol/s.

3.2.2. Effect of Cycle Time Another important parameter influencing both the performance and economic of the process is cycle time. Faster cycles mean higher throughput and smaller adsorber volume, thus lower

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capital cost. In addition, recovery is higher at shorter cycle times. This is clearly demonstrated in

Figure 6 which shows the cleanup cost and recovery as a function of cycle time. The cycle time was varied by keeping the step time ratios (shown in Figure 3) constant. The cycle time was varied from 200 to 600 s and the obtained results indicated that the recovery of the three impurity gases first increased slightly upon increasing cycle time from 200 to 400 s and then decreased marginally from 400 to 600 s. Notably, a three-fold increase in cycle time resulted in a cleanup cost increase of only 5%. Operating a 2-bed, four-step PSA for a cycle duration of 200 s results in a cleanup cost of $56.3/ton compared to our base case with $56.5/ton with 400 s cycle duration. The results show that for our proposed system, a cycle time on the order of 300-400 s can satisfy the recovery constraint with a reasonable cleanup cost. Moreover, the effect of cycle time on throughput is presented in Figure S4 (Supporting Information). As expected, a decreasing trend with cycle time was obtained for throughput from 227 to 75 mol/kg/h. 60

100.0

Cleanup cost CO2

97.5

SO2

59

NO 95.0 58 92.5 57 90.0 56

Recovery (%)

Cleanup Cost ($/ton of impurity)

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87.5

55

85.0 200

300

400

500

600

Cycle Time (s)

Figure 6. Effect of cycle time on recovery and cleanup cost of the 2-bed PSA system, adsorption pressure: 10 bar, purge flow rate: 100 mol/s.

3.2.3. Effect of Purge Flow Rate

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Figure 7 illustrates the variation in cleanup cost and product recovery with respect to changes in purge flow rate from 10 to 900 mol/s. Notably, the results showed that the recovery and cleanup cost are both insensitive to the purge flow rate. On the contrary, and as expected, the purge flow rate had a large impact on the purity of CO2 (dropped from 73 to 45%). Increasing the N2 purge flow rate dilutes the product stream resulting in dramatic drop in purity of the product (all three components together). Moreover, as demonstrated in Figure S5 (Supporting Information), the purge flow rate has no effect on the throughput and its value remains constant (113 mol/kg/h) over the flow rate range studied.

98

58.0

Cleanup cost CO2

57.5

SO2

96

NO

57.0

97

95 56.5

94 56.0

93 55.5

Recovery (%)

Cleanup Cost ($/ton of impurity)

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92

55.0

91 90

54.5

10

50

100

150

300

600

900

Purge Flow Rate (mol/s)

Figure 7. Effect of purge flow rate on recovery and cleanup cost of the 2-bed PSA system, adsorption pressure: 10 bar, cycle time: 400 s.

3.2.4. Effect of Working Capacities Working capacity of the adsorbent used in PSA process has a direct impact on both the capital and operating costs and it is usually assumed that the higher working capacity, the lower the capture cost. Thus, one of the practical ways of reducing the cleanup cost is to use materials that display high working capacity for the impurity gases at given process conditions. Our

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simulation results revealed the same trend, as demonstrated in Figure 8. For our base case, MgMOF-74 with CO2, SO2, and NO working capacities of 6.3, 0.8, and 0.8 mmol/g was assumed and as shown in previous sections, under the base conditions, a removal rate of 90% was achieved for all three impurities. To further assess the importance of this factor on economics of the cleanup process, the variation in working capacities was conducted by considering another three sets of capacities (see Table S4 (Supporting Information)). The observed trend in Figure 8 reveals that upon increasing the working capacities, the cleanup cost dropped from $62/ton for the worst scenario (set 1) to $57/ton for the best scenario (set 4). The impact of CO2 capacity is more pronounced than the other two gases, mainly due to the higher concentration of this gas in flue gas. It should be mentioned here that the values were assigned arbitrary, however, they were varied in such a way that a wide range of capacities could be covered. Investigating the data shown in Figure S6 (Supporting Information) reveals that working capacities have a positive effect on system throughput, resulting in an increase from 45 mol/kg/h for the set 1 to 113 mol/kg/h for the set 3. This could be rationalized by the fact that as working capacity increases more amount of feed gas can be processed with less amount of adosrbent. From above observation, it can be concluded that utilizing adsorbents with high working capacities will reduce the cleanup cost dramatically. The same trend was also observed by Ho et al.48

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64

100

Cleanup cost CO2

62

98

SO2 96

NO 60

94 58

92

56

90

Recovery (%)

Cleanup Cost ($/ton of impurity)

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88

54

86 52 Set 1

set 2

Set 3

Set 4

Working Capacity (mmol/g)

Figure 8. Effect of working capacities on recovery and cleanup cost of the 2-bed PSA system, adsorption pressure: 10 bar, purge flow rate: 100 mol/s, cycle time: 400 s.

4. Conclusion A combined flue gas cleanup system based on PSA process was designed to remove CO2, SOx, and NOx simultaneously for the purpose of reducing the energy penalty of current flue gas treatment technologies. Our techno-economic results indicated that for a capture rate of greater than 90%, the system incurs an energy penalty of 24% to a 550 MW power plant which is lower than the current individual unit operations. This corresponds to a cleanup cost of $57/ton of impurities. The sensitivity analysis results showed that the cleanup cost is very sensitive to the adsorbent characteristics (i.e., adsorption capacity), adsorption pressure, and cycle time. The development of new adsorbents that exhibit high adsorption capacity for all three types of impurities should be the focus of future work in the context of simultaneous flue gas cleanup. Overall, this techno-economic analysis shows that the combined cleanup technology can be attractive and cost-effective technology compared to individual FGD, SCR, and amine scrubbing units for simultaneous removal of CO2, SOx, and NOx.

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Supporting Information Mass, energy, and momentum balance equations, simulation parameters used in simulations, adsorption isotherms parameters, additional 4-bed, six-step PSA cycle scheme, capital cost data for major components, capital, O&M, and overall plant costs for the 4-bed PSA, as well as effects of adsorption pressure, cycle time, purge flow rate, and working capacities on system throughput, CO2, SO2, and NO working capacities.

Author Information Corresponding Author *Email: [email protected] Notes The authors declare no competing financial interest.

Acknowledgement The authors would like to thank the University of Missouri Research Board (UMRB) for supporting this work.

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