Potentials for Decarbonizing Ammonia Synthesis Plants: Retrofitting of Novel Process Configurations

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Challiwala, Eiman Mohamed, and 2 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7086583/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 15 Dec, 2025 Read the published version in Scientific Reports → Version 1 posted 9 You are reading this latest preprint version Abstract Decarbonizing ammonia production is crucial for reducing industrial greenhouse gas emissions; however, steam methane reforming (SMR) remains the dominant, carbon-intensive pathway. This study proposes a retrofit strategy for large-scale ammonia plants (1,268 tons/day) by replacing the conventional reformer with an advanced dual-reactor system that enables CO₂ utilization and carbon valorization. The novel configuration co-produces synthesis gas and multi-walled carbon nanotubes (MWCNTs), integrating ammonia and CNT production in a single process. Aspen Plus® simulations compare the baseline SMR process with the retrofitted configuration, assessing energy demand, feedstock consumption, CO 2 emissions, and economic performance. The retrofitted system achieves a 76% reduction in lifecycle CO₂-equivalent emissions and a 31% decrease in total energy demand, despite a 2.6-fold increase in methane input. At 25% MWCNT recovery, the Levelized Cost of Ammonia (LCOA) increases to $ 680.90/ton; however, substantial co-product revenue yields a 3.2-fold increase in Net Present Value (NPV), 56% Internal Rate of Return (IRR), and a 4.5-year payback period. Sensitivity analyses support the robustness of the economic potential, confirming the viability of integrated CNT-ammonia production as a pathway for sustainable, low-carbon manufacturing. Physical sciences/Energy science and technology Physical sciences/Engineering Earth and environmental sciences/Environmental sciences Ammonia production retrofitting dual reforming CNTs decarbonization techno-economic analysis Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 1. Introduction Ammonia (NH₃) plays a vital role in modern industry, primarily as a feedstock for nitrogen-based fertilizers and increasingly as a vector for hydrogen storage and energy transport due to its high hydrogen content, ease of liquefaction, and well-established infrastructure 1 , 2 . With over 180 million tons produced globally every year, ammonia production consumes substantial energy resources. It contributes significantly to global emissions, accounting for approximately 1.6% of total CO₂ emissions and 5% of emissions from the chemical industry 3 , 4 , 5 . This carbon intensity primarily stems from the hydrogen production step, typically achieved through steam methane reforming (SMR), which is both energy-intensive and reliant on fossil fuels 6 , 7 , 8 . The traditional Haber–Bosch (HB) process, which reacts hydrogen and nitrogen under high pressures (150–350 bar) and temperatures (250–450°C), remains the cornerstone of ammonia synthesis 7 , 9 . However, its extreme operating conditions and low per-pass conversion rates (~ 24% nitrogen conversion) impose substantial energy and capital demands 10 , 11 , 12 . The hydrogen feedstock, typically derived from natural gas or coal, is responsible for the majority of CO₂ emissions, with SMR-based production resulting in 2.5–2.9 kg CO₂-eq per kg of NH₃. At the same time, coal-based gasification, common in China, produces up to 5.2 kg CO₂-eq/kg NH₃ 13 . Decarbonization of ammonia production is a critical goal in the transition to sustainable chemical processes. Multiple approaches have been explored. One route focuses on improving catalyst efficiency under milder synthesis conditions. Recent work on inverse-structured iron-based catalysts has achieved triple the volumetric activity of conventional Fe systems, enabling ammonia synthesis at temperatures as low as 50°C 14 . Ruthenium-based catalysts on supports such as La₂O₃ and CeO₂, often promoted with alkali metals, have demonstrated high activity at moderate pressures and temperatures 15 , 16 . Although promising, these catalysts remain largely at the experimental stage. Additionally, nanostructured supports and dual-oxide systems, such as MgO–Nd₂O₃, exhibit enhanced selectivity and thermal stability; however, their commercial application remains limited 17 . Process-level innovations have targeted reduced operating pressure and energy consumption through selective ammonia absorption using metal salts and tailored adsorption systems, enabling recycling at pressures as low as 20 bar 9 , 16 . These systems offer alternatives to conventional condensation-based separation, which demands higher pressure and refrigeration energy. Ammonia is also classified based on the source of hydrogen used in its production, leading to descriptors such as grey, blue, and green ammonia. Due to cost advantages, grey ammonia, produced from fossil-derived hydrogen without carbon capture, remains the most prevalent. In contrast, blue ammonia incorporates carbon capture and storage (CCS), reducing net CO₂ emissions to about 0.856 kg CO₂-eq/kg NH₃ but increasing capital and operating costs 18 , 19 . This increase is partially attributed to the energy penalty of CCS systems, which typically ranges between 15% and 20%, depending on capture technology and integration level 18 . Green ammonia, which relies on hydrogen produced from renewable-powered electrolysis, offers the lowest emissions (~ 0.052 kg CO₂-eq/kg NH₃) but is currently constrained by high energy costs, limited electrolyzer efficiency, and challenges in hydrogen compression 9 , 20 , 21 . Even with green hydrogen retrofits, maximum CO₂ reductions in existing grey plants are limited to ~ 10% due to integration and thermal constraints 20 . Alternative technologies have also been evaluated within the reforming step, which is the most emissions-intensive component of ammonia production. Partial oxidation (POX) and autothermal reforming (ATR) offer exothermic or thermally balanced alternatives to SMR 22 , 14 , 23 . Dry reforming of methane (DRM), which utilizes CO₂ as an oxidant, is attractive in theory but suffers from high coke formation, unfavorable syngas ratios, and excessive energy demand 23 , 24 . Hybrid approaches, including tri-reforming and membrane-assisted air separation, have demonstrated improved syngas quality and emission reductions 25 , 26 . For example, a 27% increase in ammonia output and a decrease in CO₂ emissions to near-zero levels were achieved through such integration 25 . A more recent innovation in reforming technology involves integrating CO₂ utilization and carbon valorization within a single process unit. One such configuration is a dual-reactor system in which CH₄, CO₂, and O₂ are partially oxidized at moderate temperatures (~ 550–620°C) to generate syngas while simultaneously precipitating solid carbon in the form of multi-walled carbon nanotubes (MWCNTs). The product gas is subsequently processed in a high-temperature reformer to adjust the H₂/CO ratio for synthesis applications. This approach eliminates the need for steam, reduces oxygen demand, and enables autothermal operation, thereby improving thermal integration. Experimental and simulation studies have demonstrated that such systems can reduce CO₂ emissions by over 70% in certain gas-to-liquid (GTL) applications and enhance overall energy efficiency and process economics compared to conventional reforming routes like DRM and ATR 27 , 28 . Building on these advances, the present study evaluates the integration of such a carbon-valorizing reforming system into a conventional ammonia plant. A specific case study is presented, utilizing a dual-reactor reforming configuration, to assess energy use, lifecycle CO₂ emissions, and techno-economic performance in comparison to a conventional SMR-based facility. Steady-state simulations are conducted using Aspen Plus® for a 1,268 ton/day ammonia plant, and the analysis includes co-production of CNTs alongside ammonia. Economic metrics, such as the Levelized Cost of Ammonia (LCOA), Net Present Value (NPV), Internal Rate of Return (IRR), and payback period, are evaluated under conservative assumptions, with sensitivity analyses conducted across ammonia, carbon credit, CNT, and natural gas prices. The study aims to explore the feasibility of integrated reforming-based retrofits as a potential decarbonization pathway that combines emissions reduction with process intensification and value co-creation. 2. Methodology This study presents a comparative simulation-based assessment of ammonia production using two reforming technologies: the conventional Steam Methane Reforming (SMR) process and a dual-reactor reforming system capable of CO₂ utilization and carbon valorization. A specific dual-reforming configuration, hereafter referred to as the “retrofitted configuration”, is examined as a case study to evaluate the feasibility and performance of an integrated ammonia and carbon product pathway. 2.1 Simulation Framework and Process Modeling All process simulations were developed using Aspen Plus® V12.1 under steady-state conditions, replicating the main stages of an industrial ammonia plant with a nominal production capacity of 1270 metric tons per day. The conventional SMR-based configuration includes feed desulfurization, primary and secondary reforming, high- and low-temperature water-gas shift (WGS), CO₂ removal, methanation, and ammonia synthesis via the Haber–Bosch loop. The complete base-case flowsheet is illustrated in Fig. 1 . This model was validated against benchmark data 29 , ensuring consistency in mass and energy balances. Both the SMR and the retrofitted configuration were simulated using the Redlich-Kwong-Soave equation of state with the Boston-Mathias alpha function (RKS-BM), which provides reliable predictions on thermodynamic properties at elevated pressures and temperatures 30 , 31 . To enhance accuracy in the ammonia synthesis loop, additional modifications were applied to improve vapor–liquid equilibrium and enthalpy predictions. For the retrofitted configuration case, equilibrium-based Gibbs reactors (RGibbs) were employed to simulate the dual-reactor system. This approach is supported by experimental results 32 , which demonstrated near-equilibrium conversions with deviations of less than ± 8% for CH₄ conversion and consistent MWCNT yields across multiple scales. The reactor design utilizes a co-fed mixture of CH₄, CO₂, and O₂ at moderate temperatures (500–650°C) and high pressure to promote rapid syngas formation and carbon nucleation under thermodynamically favorable conditions 28 , 32 . 2.2 Base Case SMR Configuration The SMR-based ammonia plant model represents a conventional facility that utilizes natural gas. The feed composition (Table 1 ) is primarily composed of methane (80.0%), along with 17.7% ethane, 1.25% heavier hydrocarbons (C₃+), and trace components, including nitrogen, oxygen, and sulfur compounds. The gas enters the system at 45°C and 38.2 bar and is first processed in a desulfurization unit to protect downstream catalysts 29 . Table 1 Natural Gas Feed Composition and Inlet Conditions 29 . Component Mole Fraction (%) CH 4 80.0 C 2 H 6 17.7 C 3 + 1.25 N 2 0.8 O 2 0.2 Sulfur Compounds 0.0001 Temperature ( o C) 45 Pressure (bar) 38.2 Following desulfurization, the feed is mixed with steam and introduced into a primary reformer operating at 791°C and 30.7 bar, where partial conversion to H₂, CO, and residual CH₄ occurs over Ni-based catalysts. The resulting gas is then fed to a secondary reformer with preheated air, facilitating complete methane conversion and the addition of nitrogen in a stoichiometric proportion. Table 2 presents the composition of the secondary reformer outlet. Table 2 Secondary Reformer Outlet Stream Properties 29 . Component mole fraction (%) H 2 35.5 H 2 O 35.3 N 2 15.2 CO 8.4 CO 2 5.1 CH 4 0.3 Ar 0.2 Temperature (°C) 980 Pressure (bar) 29 The syngas undergoes WGS to reduce CO content from 8.4% to approximately 0.2%, followed by CO₂ removal using amine scrubbing to achieve < 0.3% CO₂. The purified stream, with a near-ideal 3:1 H₂:N₂ ratio, proceeds to methanation, where trace CO and CO₂ are converted to CH₄ and H₂O. The resulting feed to the ammonia synthesis loop consists of ~ 74% H₂, ~ 25% N₂, and < 1% CH₄. Ammonia synthesis occurs at ~ 292 bar via the Haber–Bosch loop, with single-pass nitrogen conversion of ~ 24%. Reactor effluent contains unreacted H₂, N₂, and ~ 24% NH₃, reflecting equilibrium-limited performance. 2.3 Retrofitted Configuration with Dual-Reactor Reforming In the retrofitted configuration, the conventional SMR and secondary reformers are replaced by a dual-reactor reforming system that simultaneously utilizes CO₂ and valorizes carbon. The first reactor operates at 400–650°C and atmospheric pressure, where CH₄, CO₂, and O₂ (in a molar ratio of 1:0.6:0.1) are partially oxidized to produce syngas and a solid carbon intermediate. The second reactor, operating at elevated temperature, finalizes the syngas composition. The retrofitted system is tuned to match the H₂:N₂ ratio of the base-case outlet, ensuring seamless integration with downstream process units. Simulation results estimate a carbon yield of 0.76 kg of MWCNTs per kg of NH₃ produced, corresponding to a theoretical annual output of 318,000 tons. To reflect commercialization constraints and avoid overestimation, a conservative 25% recovery factor is applied in the economic analysis, consistent with previous studies on similar reforming configurations 28 , 33 . 2.4 Key Modeling Assumptions To streamline comparative analysis, several simplifications were adopted. All process streams were modeled as single-phase with constant specific heat capacities. Phase transitions, latent heat effects, and pressure drops were neglected, a standard practice in early-stage feasibility studies for gas-phase systems 34 , 35 . Reaction kinetics for SMR and WGS were taken from Aspen Plus libraries and validated against literature 29 , 30 . For the dual-reactor retrofitted configuration, the reformers were modeled using RGibbs modules based on published evidence indicating that equilibrium conversion accurately represents system performance under the studied operating conditions 27 , 28 , 32 . 2.5 Performance Evaluation Metrics 2.5.1 Process Performance Four Key Performance Indicators (KPIs) were defined: Natural Gas Consumption (kg/kg NH₃), Steam Demand (kg/kg NH₃), Total Energy Use, including heat duties and compression work (kWh/kg NH₃), CO₂ Emissions, direct (Scope 1) and indirect (Scope 2). 2.5.2 CO₂ Emissions Estimation Direct emissions originate from reforming reactions and combustion. Indirect emissions associated with utilities were estimated using a baseline emission factor of 0.36 kg CO₂/kWh, derived from Aspen Plus simulations of natural gas-fired utilities. All emissions are reported in kg CO₂-eq per kg NH₃ using GWP100 metrics. While this factor provides internal consistency, regional variations (0.05–0.8 kg CO₂/kWh) are acknowledged as a source of uncertainty, particularly relevant for the retrofitted configuration, which exhibits higher electricity demand due to the additional process units 19 . 2.6 Economic Assessment Framework 2.6.1 Assumptions and Input Parameters The economic evaluation is based on a 30-year project horizon and an 8% real discount rate. A nominal production of 1,268 tons NH₃/day (418,440 tons/year) was assumed. Input values are summarized in Table 3 . Table 3 Economic Input Parameters for Techno-Economic Analysis. Parameter Value Reference Natural gas $ 4.0/MMBtu (baseline) 36 Oxygen (retrofitted configuration only) $ 100/ton 37 CO₂ feed (retrofitted configuration only) $ 50/ ton 38 Electricity $ 0.07/KWh 39 Carbon-credit revenue $ 30/ton CO₂ (baseline) 40 , 41 Ammonia selling price $ 450/ton (baseline) 42 MWCNTs selling Price $ 5/kg (baseline) 43 2.6.2 CAPEX and OPEX Estimation The SMR plant CAPEX was derived from an LCOA of $ 229/ton NH₃ 29 , resulting in an estimated investment of $ 454.3 million. For the retrofitted configuration modeled in this study, a 50% CAPEX uplift was applied to reflect additional equipment (e.g., second reformer, CO₂ loop, MWCNT recovery), yielding a total of $ 681.4 million 27 , 11 . OPEX for both configurations was estimated based on process simulation outputs, standard cost heuristics, and market price assumptions. Fixed costs were assumed to represent 10% of total OPEX for direct labor and maintenance. For the retrofit case, an additional 3% was added for chemicals in the retrofitted configuration case 28 . Carbon credit revenue and MWCNT sales were included in the retrofitted configuration. 2.6.3 Economic Performance Indicators The economic viability of both ammonia production configurations was evaluated using three key financial metrics: LCOA, NPV, and IRR. Calculations were performed over a 30-year project lifetime, assuming no salvage value was available. The LCOA, a standardized metric representing the average production cost over the plant’s operational lifetime, was calculated using the following Eq. 4 4 : $$\:LCOA=\frac{CRF\times\:CAPEX+Annual\:OPEX}{Annual\:N{H}_{3}Production\:\left(tons\right)}$$ 1 ……………………………….…… where the Capital Recovery Factor (CRF) is defined as: $$\:CRF=\frac{r{(1+r)}^{n}}{{(1+r)}^{n}-1}$$ 2 ………………….……………………..………………. where: r is the discount rate (8%), and n is the project lifetime (30 years). The NPV was calculated using the discounted cash flow approach: $$\:NPV=\sum\:_{t=1}^{n}\frac{{R}_{t}-{C}_{t}}{{(1+r)}^{t}}-CAPEX$$ 3 ……………………………………………. where R t and C t are the total revenues and costs in year t, respectively. CAPEX is treated as an upfront investment at year t = 0 Inflation rates were differentiated by revenue or cost type, by sector-specific economic trends: A 2% annual inflation was applied to ammonia prices, reflecting historical behavior in the nitrogen fertilizer sector 45 . A 2.5% escalation rate was applied to operating expenditures (OPEX), capturing increases in energy, chemicals, and labor costs 46 . A 1% inflation rate was used for carbon credit revenues, accounting for volatility in carbon pricing and regulatory uncertainty 47 . The IRR, defined as the discount rate at which NPV equals zero 48 , was also computed to assess investment attractiveness. The IRR values were calculated using Microsoft Excel’s built-in financial functions based on the annual net cash flow profiles. Python was used exclusively for generating figures and visualizing economic trends. 3. Results and Discussion A comparative analysis was conducted between the base-case SMR-based ammonia production process and the retrofitted configuration featuring a dual-reactor reforming system for integrated CO₂ utilization and carbon valorization. The comparison focuses on process efficiency, feedstock, energy consumption, and carbon footprint. All simulations were performed under steady-state conditions using Aspen Plus V12.1, with model validation against benchmark literature to ensure the reliability of the results. 3.1 Simulation Validation and Reforming Process Comparison The SMR-based ammonia plant simulation was validated for mass and energy balances against the reference study 29 . As detailed in Table 4 , the differences are less than 3% for most unit operations, including the SRM outlet, the water-gas shift (WGS) section, and the CO₂ removal unit. Larger discrepancies (20–30%) were observed in internal synthesis loop flows, particularly in the recycle feed, reactor inlet gas, and purge stream. These variances are attributed to modeling choices and system sensitivities specific to high-pressure ammonia synthesis loops. Slight differences in CO₂ removal efficiency or inert gas content (e.g., Ar, CH₄) downstream of purification significantly influence hydrogen-to-nitrogen ratios, recycle rates, and purge volumes. Furthermore, assumptions related to vapor–liquid separation, purge ratios, and simplified modeling of the final methanation step for CO/CO₂ removal may introduce compounding effects in loop circulation, without materially affecting ammonia yield or syngas quality. These details are well-documented in simulation studies of ammonia synthesis systems, where internal loop behavior exhibits a nonlinear dependency on purge and separation efficiency 49 . Despite differences, the present model captures all critical performance metrics, natural gas consumption, steam demand, syngas composition, and ammonia production, within an acceptable range, confirming its robustness for comparative analysis. Table 4 Selected Validation Metrics Comparing Simulation Results with benchmark data 29 Stream Benchmark data 29 (kg/kg NH₃) Present Study (kg/kg NH₃) % Deviation Process NG 0.52 0.52 0% Steam Input 1.93 1.93 0% SRM Outlet 3.76 3.76 0% WGS Outlet 3.76 3.76 0% CO₂ Removal Outlet 1.16 1.19 –3% Recycle Feed 2.47 2.97 –20% Reactor Inlet Gas 3.37 4.18 –24% NH₃ Product - 1.00 — The reforming section is the most energy- and carbon-intensive stage of ammonia production, serving as the focal point for retrofitting. In the SMR-based configuration, the primary and secondary reformers produce a syngas stream comprising 35.5% H₂, 15.2% N₂, and 5.1% CO₂ at 980°C and 29 bar. In contrast, the dual reactor retrofitted configuration, which utilizes CH₄, CO₂, and O₂, was tuned to achieve a similar syngas composition, eliminating the need for steam injection. The specific case study presented here achieved thermodynamic equilibrium for syngas generation while also enabling the co-production of MWCNTs, offering both environmental and potential economic benefits. The simulation results were validated against published experimental and scale-up studies 32 , 28 , confirming the reliability of the equilibrium-based approach. Key metrics, including CH₄ and CO₂ conversion, syngas composition, and carbon yield, matched closely with experimental data, as shown in Table 5 . Table 5 Thermodynamic Validation of the Retrofitted Configuration Simulation Against Experimental Data. Parameter Aspen Plus Simulation (This Study) Experimental/Model Data 28 , 32 CH₄:CO₂:O₂ Feed Ratio 1:0.6:0.1 1:0.6:0.1 Reactor 1 Temperature (°C) 550 500–600 CO₂ Conversion (%) 66 ~ 65 CH₄ Conversion (%) 82 ± 8% deviation from experimental H₂/CO Ratio 1.9 ~ 2.0 Carbon Product Yield (kg/kg NH₃) 0.76 Consistent multi-scale yield Energy Reduction vs. DRM 50% 50% 3.2 Energy and Feedstock Utilization The integration of the dual-reactor reforming case study significantly altered the feedstock profile and energy requirements of the ammonia plant. As summarized in Table 6 , the retrofit configuration consumed approximately 1.36 kg of natural gas per kg of ammonia, representing a 161.5% increase compared to the 0.52 kg/kg NH₃ consumption in the conventional SMR-based process. This increase is attributed to the additional methane feedstock required in the first reactor, which supports not only syngas formation but also the production of carbon nanotubes. Despite the elevated methane input, the overall energy consumption of the retrofitted configuration decreased by 31.5%, from 4.51 to 3.09 kWh/kg NH₃. This outcome results from the autothermal operation of the dual-reactor configuration, which eliminates the need for external energy, as used in SMR furnaces. Operating at moderate temperatures (400–650°C) and lower pressures, the system avoids the intense heat duties required in conventional primary reformers (~ 800–900°C), thereby reducing overall furnace duty, steam superheating loads, and compression energy demands. In addition, the process's partial conversion of methane into MWCNTs conserves a portion of the input energy within the solid byproduct rather than dissipating it as combustion heat. This effect, coupled with a 25% reduction in steam demand, contributes substantially to the system’s improved thermal efficiency. Although the increased natural gas requirement may pose economic challenges in high-cost gas regions, the tradeoff is supported by two key factors: (1) reduced net energy consumption per unit of ammonia, and (2) incorporation of CO₂ into a solid value-added product, which improves both environmental impact and economic performance. The airflow rate into the secondary reformer remains constant across both configurations to preserve the stoichiometric balance required for ammonia synthesis. The ammonia production rate was fixed to 1,268 tons per day to ensure direct comparability. Table 6 Key Process Inputs for SMR-Based vs. Retrofitted Ammonia Production. Parameter SMR Configuration Retrofitted Configuration Change (%) Natural Gas Consumption (kg/kg NH₃) 0.52 1.36 + 161.5% Steam Demand (kg/kg NH₃) 1.93 1.45 -24.9% Total energy use (kWh/kg NH₃) 4.51 3.09 -31.5 Air Flowrate (normalized) Constant Constant - NH₃ Yield (tons/day) 1268 1268 0% (matched) 3.3 Carbon Footprint Reduction The primary environmental advantage of retrofitting with an integrated reforming system lies in its substantial reduction of GHG emissions. As shown in Fig. 3 , the total CO₂-equivalent emissions for the conventional SMR-based ammonia process were estimated at 2.35 kg CO₂-eq per kg NH₃, consistent with literature-reported values for large-scale natural gas-based ammonia plants without carbon capture 19 . In contrast, the retrofitted configuration modeled in this study achieved a 76% reduction, lowering net emissions to 0.57 kg CO₂-eq/kg NH₃. This emissions profile surpasses typical “blue ammonia” pathways, which combine SMR with carbon capture and storage (CCS) and report residual emissions in the range of 0.85 to 1.0 kg CO₂-eq/kg NH₃ 18 , 19 . Such findings suggest that integrated reforming configurations with carbon valorization, as demonstrated in this case study, may serve as viable alternatives for achieving deep decarbonization in ammonia production, particularly when assessed within lifecycle assessment (LCA) frameworks and emerging carbon intensity benchmarks. The observed reduction in carbon intensity is attributed to two synergistic mechanisms within the retrofit case: CO₂-reactive reforming chemistry: The first reactor operates under conditions that favor partial oxidation and dry reforming, where CO₂ acts as a chemical reactant, thereby reducing its release to the atmosphere. Carbon sequestration via solid byproduct formation: A portion of the carbon in the methane feed is transformed into MWCNTs. This stable solid byproduct sequesters carbon in a non-emissive form. This permanently removes carbon from the process stream, distinguishing it from CCS strategies that rely on long-term subsurface storage. Under simulation assumptions, the retrofitted configuration demonstrated net-negative direct emissions, with a value of − 0.52 kg CO₂/kg NH₃. This reflects in-process CO₂ utilization and solid carbon formation that reduce total emissions relative to the SMR baseline. Indirect emissions, estimated from total energy use and an emission factor of 0.36 kg CO₂/kWh, were also reduced by 32%, primarily due to lower electricity and steam demand enabled by autothermal reforming and improved heat integration. These results suggest that integrated reforming systems with carbon valorization, such as the one modeled in this study, may offer a viable pathway for decarbonizing ammonia production by coupling CO₂ reactivity with the formation of durable carbon products. However, the long-term carbon permanence and scalability of such pathways require further assessment, which is beyond the scope of this work. 3.4 Process Integration and Infrastructure Compatibility Beyond energy and emissions metrics, the practical feasibility of deploying low-carbon reforming configurations within existing ammonia plants is a critical consideration in evaluating their scalability. The retrofitted configuration modeled in this study exhibits a high degree of compatibility with conventional ammonia plant infrastructure. Following the retrofit, no substantial downstream modifications are required beyond the reforming section, as all subsequent units, including high- and low-temperature shift reactors, CO₂ removal systems, methanation, and the ammonia synthesis loop, continue to operate under pressure-temperature conditions comparable to those in the baseline SMR configuration. This compatibility facilitates integration with minimal capital disruption and preserves established process control schemes. In addition to maintaining process continuity, the modeled retrofit offers potential thermal integration advantages through its autothermal operation. By eliminating the need for fired reformer furnaces typically required in SMR systems, this approach reduces dependence on external fuel combustion and enhances overall thermal efficiency. However, the shift away from flue gas combustion also necessitates a reconfiguration of the plant’s heat recovery strategy. In SMR-based systems, significant heat recovery is achieved using process gas preheaters and flue gas-based Waste Heat Recovery Units (WHRUs), which are not applicable in the retrofitted configuration. Instead, heat recovery is maintained via internal boiler and exchanger configurations within the reforming section, with adjustments to boiler duty and exchanger sizing tailored to the altered thermal profile. Overall, the case study suggests that integrated reforming systems, such as this, can be implemented with minimal infrastructure changes while maintaining operational continuity and improving energy efficiency, subject to the design constraints and boundary conditions modeled here. 3.5 Techno-Economic Comparison To assess the economic viability of the modeled retrofitted configuration using dual-reactor reforming, a comprehensive techno-economic analysis was conducted. This evaluation extends beyond conventional cost metrics by incorporating multiple financial indicators, namely, the LCOA, NPV, IRR, and payback period. Additionally, a sensitivity analysis was conducted to examine the impact of key market drivers, including the prices of MWCNTs, carbon credits, ammonia, and natural gas. Together, these metrics provide a comprehensive view of the comparative performance of the baseline and retrofitted ammonia production scenarios under both baseline and variable conditions. 3.5.1 Levelized Cost of Ammonia (LCOA) The LCOA was calculated to represent the average cost per ton of ammonia produced over the project lifetime, accounting for CAPEX and OPEX. For the SMR-based configuration, the LCOA was estimated at $ 272.5/ton NH₃, which aligns well with values reported for large-scale U.S.-based ammonia plants using SMR and ATR configurations 50 . In contrast, the retrofitted configuration exhibited a significantly higher LCOA of $ 680.9/ton NH₃, driven by a ~ 50% increase in capital costs and substantially elevated operating costs associated with electricity consumption, oxygen supply, and chemical handling for CO₂ utilization and nanomaterial recovery, as supported by earlier GTL case studies 28 , 33 . While LCOA remains a widely cited benchmark, it does not capture the environmental and economic co-benefits of emerging decarbonization technologies. Specifically, co-product revenue streams such as MWCNTs and carbon credits, modeled in the retrofit case, are excluded from LCOA calculations. Thus, LCOA alone may undervalue multi-output decarbonization pathways, especially those involving carbon valorization. To address this limitation, additional metrics, including NPV, IRR, and carbon abatement cost, are used to provide a more comprehensive assessment of long-term value. To quantify the environmental cost-effectiveness of retrofitting, Table 7 presents the estimated cost of carbon abatement. Under the modeled conditions, the retrofit case achieves a 76% reduction in total emissions at an incremental cost of $ 4.75 billion over 30 years, resulting in an abatement cost of $ 212 per ton CO₂-eq avoided, a competitive value for deep decarbonization pathways. This value compares favorably to current carbon market benchmarks: the EU Emissions Trading System (EU ETS) price averaged approximately $ 85– $ 100 per ton in 2025, while U.S. compliance credit values range between $ 30– $ 60 per ton of CO₂ 41 , 50 . The estimated abatement cost is also lower than that of Direct Air Capture (DAC), which typically ranges from $ 250 to $ 600 per ton of CO₂ removed 51 , underscoring its relative advantage among negative-emission technologies. Table 7 Comparative Lifetime Costs and Emissions for SMR and Retrofitted Configuration Ammonia Production Pathways. Metric SMR-Based Process Retrofitted Configuration Difference Total 30-Year Cost (Million USD) 2,664.0 7,413.8 + 4,749.7 Total 30-Year CO₂ Emissions (Million tons CO₂-eq) 29.5 7.3 -22.2 Carbon Abatement Cost (USD/ton CO₂-eq avoided) - - 212 Although the current analysis does not account for tax incentives, it is notable that recent U.S. policy instruments such as 45V significantly enhance the economic competitiveness of blue and hybrid ammonia pathways 50 . 3.5.2 Profitability and Economic Performance Although LCOA favors the SMR route, a complete profitability analysis reveals a different outcome under the modeled conditions. A discounted cash flow (DCF) model was developed for both systems over a 30-year project horizon, using an 8% discount rate and inflation assumptions of 2% for ammonia prices and 2.5% for OPEX. The ammonia production rate was fixed at 418,440 tons/year, with baseline ammonia revenue of $ 188.3 million/year (at $ 450/ton). For the retrofitted configuration, two additional revenue streams were included: Carbon credits: Based on avoided emissions of 1.77 kg CO₂-eq/kg NH₃, monetized at $ 30/ton CO₂, contributing ~ $ 22.2 million/year. MWCNT sales: With a modeled yield of 0.19 kg/kg NH₃ and a conservative 0.25 correction factor applied to account for commercialization constraints, the marketable output (~ 79,500 tons/year) was valued at $ 5/kg, generating approximately $ 397.5 million/year in potential revenue. Under these assumptions, the profitability indicators improve significantly for the retrofit case: NPV increases from $ 1.06 billion (SMR) to $ 3.41 billion (Retrofitted configuration) IRR rises from 27–56% Payback period is reduced from 11.5 to 4.5 years These results, illustrated in Fig. 4 , suggest that integrating a carbon-valorizing reformer may offer long-term economic benefits, particularly when co-products and emission-related incentives are monetized. (Ammonia = $450/ton, MWCNT = $5/kg, Carbon credit = $30/ton CO₂, Natural Gas = $4/MMBtu) 3.5.3 Sensitivity Analysis To better understand the influence of individual market variables on the economic performance of the retrofitted configuration, a sensitivity analysis was conducted across four key factors: MWCNT price, carbon credit value, ammonia price, and natural gas cost. These parameters were selected due to their high volatility and substantial impact on revenue and profitability projections. Sensitivity trends observed in this study reflect those reported in recent techno-economic assessments of blue and hybrid ammonia pathways 51 , particularly regarding the pronounced effect of natural gas price fluctuations on process viability. MWCNT Price Sensitivity MWCNT prices vary significantly by purity, grade, and application, with literature citing a wide range from $ 3/kg to over $ 1,000/kg 43,52–55 . Sensitivity analysis was conducted across a realistic range of $ 2 to $ 80/kg to assess the impact on NPV and IRR. As shown in Fig. 5 , both metrics rise steeply with MWCNT price. At $ 2/kg, the retrofitted configuration still achieves a positive NPV of $ 0.73 billion and an IRR of 20%. At $ 50/kg, the NPV exceeds $ 43 billion, and IRR surpasses 580%; however, such values represent upper-bound theoretical estimates and assume complete market absorption of the co-product at premium prices. The assumed $ 5/kg price reflects a conservative estimate for industrial-grade applications such as polymer additives, coatings, and conductive fillers 43 , 52 . Large-scale deployment would require securing demand in bulk markets such as cement or asphalt, which may offer lower prices but significant volumes. Carbon Credit Sensitivity Carbon credit values varied from $ 30 to $ 100 per ton of CO₂. Results show a modest effect: NPV increased from $ 3.41 to $ 4.10 billion, and IRR from 56–64%. This indicates that while carbon credits improve returns, the economic feasibility of the retrofitted configuration is not dependent on high carbon pricing, a valuable attribute in uncertain policy environments. Ammonia Price Sensitivity Ammonia prices fluctuate considerably depending on regional energy dynamics and international supply-demand balances, with recent global prices ranging from $ 300 to over $ 800 per ton 56 – 58 . Sensitivity analysis conducted across this range revealed strong profitability trends for both the SMR and retrofitted configurations, as illustrated in Fig. 6 . For the SMR pathway, the NPV increases from $ 0.2 billion at $ 300/ton to $ 3.06 billion at $ 800/ton, with the IRR rising from 12–59%, and the payback period shortening from more than 16 years to 4.1 years. In comparison, the retrofitted configuration demonstrates even greater resilience: its NPV improves from $ 2.6 billion to $ 5.41 billion, its IRR increases from 46–78%, and its payback period declines from 6 years to just 3 years over the exact price interval. Notably, the retrofitted system remains economically viable even at the low end of the price spectrum, $ 300/ton, which is well below its calculated LCOA of $ 680.90/ton NH₃. This continued profitability is made possible by its diversified revenue streams from MWCNT sales and carbon credits, highlighting the limitations of relying solely on LCOA when evaluating low-carbon ammonia technologies. Natural Gas Price Sensitivity Natural gas prices varied from $ 1.50 to $ 13.00/MMBtu, reflecting global conditions, from subsidized gas in the Middle East to high import prices in Europe 36 , 59 – 61 . Table 8 summarizes the impact on economic performance for the retrofitted configuration. The system remains economically viable up to $ 10/MMBtu, beyond which the project becomes infeasible, with negative NPV and no payback within the 30-year timeframe. This emphasizes the importance of feedstock price stability when deploying reforming technologies with high methane input requirements, particularly in regions aiming for deep decarbonization. Table 8 Impact of Natural Gas Price on the Economic Viability of the Retrofitted Configuration (Ammonia = $450/ton, MWCNT = $5/kg, Carbon credit = $30/ton CO₂). Natural Gas Price ( $ /MMBtu) NPV (Billion USD) IRR (%) Payback Period (Years) 1.5 4.57 68 3.5 3.0 3.87 61 4.0 4.0 3.41 56 4.5 5.0 2.95 51 4.8 7.0 2.03 41 6.5 10.0 0.64 23 > 30 13.0 < 0 - Not recoverable 4. Conclusions This study investigates the technical, environmental, and economic performance of retrofitting conventional ammonia plants with an advanced dual-reactor reforming system that integrates CO₂ utilization and carbon valorization. Through steady-state process simulation and techno-economic analysis, the retrofitted configuration achieved a 76% reduction in lifecycle CO₂-equivalent emissions and a 31% decrease in total energy consumption compared to a traditional SMR-based process, while maintaining the same ammonia production capacity of 1,268 tons per day. While the LCOA for the retrofitted case is higher than for SMR ( $ 680.9/ton vs. $ 272.5/ton NH₃), additional revenue streams from co-product recovery, including carbon credits and MWCNTs, significantly improve the economic outlook. The resulting NPV exceeds $ 3.4 billion, with an IRR of 56% and a payback period of 4.5 years. Sensitivity analysis confirms that the configuration remains economically viable under conservative pricing scenarios (e.g., $ 300/ton ammonia and $ 2/kg MWCNTs), indicating resilience to market variability. The findings support the feasibility of integrating carbon conversion into existing hydrogen-intensive chemical processes as a scalable approach to decarbonization. The dual-reactor reforming concept may be particularly relevant for regions with access to low-cost methane, concentrated CO₂ sources, and carbon offset markets. By reducing emissions and enhancing energy efficiency, this approach directly contributes to global climate goals and aligns with Sustainable Development Goal 7 (Affordable and Clean Energy), which promotes access to clean energy through improved industrial sustainability. Future research should incorporate a comprehensive life-cycle assessment (LCA), dynamic simulation, and pilot-scale testing to validate performance under operational conditions. Broader applicability may extend to methanol, synthetic fuels, and clean hydrogen production, advancing resource-efficient and low-carbon industrial pathways. Declarations Funding This work was made possible by NPRP, Qatar grant NPRP14S-0328-210106 from the Qatar National Research Fund (a member of the Qatar Foundation), and the Hamad bin Khalifa University (HBKU) CARGEN Bridge Fund. The authors would also like to acknowledge the Qatar National Library for its support of open-access publication. The statements herein are solely the responsibility of the authors. Competing Interest Statement This manuscript presents a simulation-based assessment of a novel retrofit configuration for large-scale ammonia production, integrating dual-reactor reforming technology to significantly reduce the carbon intensity of the final products. By combining CO₂ utilization and carbon valorization into a single unit operation, the proposed system enables the co-production of synthesis gas and multi-walled carbon nanotubes (MWCNTs), offering a transformative approach to decarbonizing the ammonia synthesis process. Our results, based on Aspen Plus® modeling and detailed techno-economic analysis, indicate a 76% reduction in lifecycle CO₂ emissions and a 31% decrease in energy demand, with promising financial metrics including a 56% internal rate of return and a 4.5-year payback period. This study makes a meaningful contribution to the field by offering a scalable and economically viable pathway for retrofitting existing hydrogen-intensive chemical plants. The integration of carbon valorization not only reduces emissions but also enhances profitability, an area of increasing importance as the industry transitions toward net-zero targets. The authors would like to declare that the concept of the two-reactor reformer was developed by them and published in Scientific Reports in 2021 (vol. 11, 1417 (2021)). It is also patented as CARGEN technology. 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Cite Share Download PDF Status: Published Journal Publication published 15 Dec, 2025 Read the published version in Scientific Reports → Version 1 posted Editorial decision: Revision requested 28 Sep, 2025 Reviews received at journal 15 Sep, 2025 Reviews received at journal 11 Sep, 2025 Reviewers agreed at journal 03 Sep, 2025 Reviewers agreed at journal 01 Sep, 2025 Reviewers invited by journal 15 Aug, 2025 Editor assigned by journal 07 Aug, 2025 Submission checks completed at journal 19 Jul, 2025 First submitted to journal 19 Jul, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-7086583","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":501787148,"identity":"2a6beb9f-57f4-46b9-b08b-37fbcabebd37","order_by":0,"name":"Nada Mahmoud","email":"","orcid":"","institution":"Texas A\u0026M University at Qatar","correspondingAuthor":false,"prefix":"","firstName":"Nada","middleName":"","lastName":"Mahmoud","suffix":""},{"id":501787149,"identity":"00de7be7-a939-4578-b86f-2c446f86fca9","order_by":1,"name":"Tagwa Musa","email":"","orcid":"","institution":"Texas A\u0026M University at Qatar","correspondingAuthor":false,"prefix":"","firstName":"Tagwa","middleName":"","lastName":"Musa","suffix":""},{"id":501787153,"identity":"618d07a9-06cd-4252-b8c8-01f910ba4f1d","order_by":2,"name":"Mohamed S. Challiwala","email":"","orcid":"","institution":"Texas A\u0026M University at Qatar","correspondingAuthor":false,"prefix":"","firstName":"Mohamed","middleName":"S.","lastName":"Challiwala","suffix":""},{"id":501787154,"identity":"bac64435-b781-4bc6-a82b-4dd700f07fe0","order_by":3,"name":"Eiman Mohamed","email":"","orcid":"","institution":"Texas A\u0026M University at Qatar","correspondingAuthor":false,"prefix":"","firstName":"Eiman","middleName":"","lastName":"Mohamed","suffix":""},{"id":501787155,"identity":"68278b08-df90-4d0d-9089-d2dd90f1a9cf","order_by":4,"name":"Hanif Choudhury","email":"","orcid":"","institution":"Texas A\u0026M University at Qatar","correspondingAuthor":false,"prefix":"","firstName":"Hanif","middleName":"","lastName":"Choudhury","suffix":""},{"id":501787156,"identity":"89435c8c-ba33-404d-bc25-d5ff2612986a","order_by":5,"name":"Nimir O. Elbashir","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAzElEQVRIiWNgGAWjYFAC5jYgcYCHgb0BKnCAoBZGqBaewyRqYWCQSCZSizl7Y9uDH3/uyJjPfH/w0802Bjm+Gwn4tVj2HGw37G17xiNzO5lZOreNwViSkBaDG4ltErwNh3kkpJMZQFoSNxDUcv9hm+SfP0AtkoeZfwO11BPWcoOxTZqHDahFgpkNZEuCAUEtZxLbjWXbgFp4ks2sc85JGM4884CAluOHjz188+ewvQT7wce3c8ps5PmOE7AFHUiQpnwUjIJRMApGAXYAAPhhRsEsh+hBAAAAAElFTkSuQmCC","orcid":"","institution":"Texas A\u0026M University at Qatar","correspondingAuthor":true,"prefix":"","firstName":"Nimir","middleName":"O.","lastName":"Elbashir","suffix":""}],"badges":[],"createdAt":"2025-07-09 18:08:18","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-7086583/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-7086583/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1038/s41598-025-28598-y","type":"published","date":"2025-12-15T15:58:15+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":89852790,"identity":"ee4c2177-0061-461b-a638-3dcfd670adb1","added_by":"auto","created_at":"2025-08-25 18:02:10","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":496844,"visible":true,"origin":"","legend":"\u003cp\u003eBase Case – SMR-Based Ammonia Production Flowsheet.\u003c/p\u003e","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-7086583/v1/cfcee0c41c7c209e11e57af7.png"},{"id":89853800,"identity":"77d3436b-17ce-4b7d-865e-ccf55ede6533","added_by":"auto","created_at":"2025-08-25 18:18:11","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":574249,"visible":true,"origin":"","legend":"\u003cp\u003eRetrofitted case – Ammonia flowsheet with retrofitted configuration\u003c/p\u003e","description":"","filename":"floatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-7086583/v1/b3856eeb3c21e5fabb6bcb39.png"},{"id":89853799,"identity":"3bd1fa65-de26-4d88-b4f0-30cc8d8ed90a","added_by":"auto","created_at":"2025-08-25 18:18:10","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":35282,"visible":true,"origin":"","legend":"\u003cp\u003eBreakdown of CO₂-equivalent emissions for SMR and the retrofitted configuration case modeled in this study\u003c/p\u003e","description":"","filename":"floatimage3.png","url":"https://assets-eu.researchsquare.com/files/rs-7086583/v1/6a1dc01f02304adab77514d3.png"},{"id":89853395,"identity":"646a95c3-e45b-42f0-b9fd-8dc696c65228","added_by":"auto","created_at":"2025-08-25 18:10:11","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":54457,"visible":true,"origin":"","legend":"\u003cp\u003eComparison of Economic Metrics for SMR and Retrofitted Configuration Ammonia Production\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e(Ammonia = $450/ton, MWCNT = $5/kg, Carbon credit = $30/ton CO₂, Natural Gas = $4/MMBtu)\u003c/em\u003e\u003c/p\u003e","description":"","filename":"floatimage4.png","url":"https://assets-eu.researchsquare.com/files/rs-7086583/v1/5e4f6b49c6983b62b6b47c4e.png"},{"id":89852794,"identity":"eb37ecd6-6bc7-4dd1-b18a-711427396639","added_by":"auto","created_at":"2025-08-25 18:02:10","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":41429,"visible":true,"origin":"","legend":"\u003cp\u003eSensitivity of NPV and IRR to MWCNT Price for the Retrofitted Configuration (Ammonia = $450/ton, Carbon credit = $30/ton CO₂, Natural Gas = $4/MMBtu)\u003c/p\u003e","description":"","filename":"floatimage5.png","url":"https://assets-eu.researchsquare.com/files/rs-7086583/v1/d7fdde2214603da80efb43f6.png"},{"id":89854515,"identity":"c237c312-2fb8-4d6a-befd-73cbac7c13fd","added_by":"auto","created_at":"2025-08-25 18:26:11","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":75687,"visible":true,"origin":"","legend":"\u003cp\u003eSensitivity of NPV, IRR, and Payback to Ammonia Price for SMR and the Retrofitted Configuration \u003cem\u003e(MWCNT = $5/kg, Carbon credit = $30/ton CO₂, Natural Gas = $4/MMBtu).\u003c/em\u003e\u003c/p\u003e","description":"","filename":"floatimage6.png","url":"https://assets-eu.researchsquare.com/files/rs-7086583/v1/1a20b7728b43921ac08fb63e.png"},{"id":98814115,"identity":"78d7b7d1-2474-4b9a-891d-690b236ee5d4","added_by":"auto","created_at":"2025-12-22 16:11:13","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2258154,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7086583/v1/6f04fb10-58d9-4f82-acd1-7e729e75788a.pdf"}],"financialInterests":"Competing interest reported. The authors have patented a similar concept and technology known as CARGEN.","formattedTitle":"Potentials for Decarbonizing Ammonia Synthesis Plants: Retrofitting of Novel Process Configurations","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eAmmonia (NH₃) plays a vital role in modern industry, primarily as a feedstock for nitrogen-based fertilizers and increasingly as a vector for hydrogen storage and energy transport due to its high hydrogen content, ease of liquefaction, and well-established infrastructure\u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e,\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e. With over 180\u0026nbsp;million tons produced globally every year, ammonia production consumes substantial energy resources. It contributes significantly to global emissions, accounting for approximately 1.6% of total CO₂ emissions and 5% of emissions from the chemical industry\u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e,\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e,\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u003c/sup\u003e. This carbon intensity primarily stems from the hydrogen production step, typically achieved through steam methane reforming (SMR), which is both energy-intensive and reliant on fossil fuels\u003csup\u003e\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e,\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e,\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eThe traditional Haber\u0026ndash;Bosch (HB) process, which reacts hydrogen and nitrogen under high pressures (150\u0026ndash;350 bar) and temperatures (250\u0026ndash;450\u0026deg;C), remains the cornerstone of ammonia synthesis\u003csup\u003e\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e,\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u003c/sup\u003e. However, its extreme operating conditions and low per-pass conversion rates (~\u0026thinsp;24% nitrogen conversion) impose substantial energy and capital demands\u003csup\u003e\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e,\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e,\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u003c/sup\u003e. The hydrogen feedstock, typically derived from natural gas or coal, is responsible for the majority of CO₂ emissions, with SMR-based production resulting in 2.5\u0026ndash;2.9 kg CO₂-eq per kg of NH₃. At the same time, coal-based gasification, common in China, produces up to 5.2 kg CO₂-eq/kg NH₃\u003csup\u003e\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eDecarbonization of ammonia production is a critical goal in the transition to sustainable chemical processes. Multiple approaches have been explored. One route focuses on improving catalyst efficiency under milder synthesis conditions. Recent work on inverse-structured iron-based catalysts has achieved triple the volumetric activity of conventional Fe systems, enabling ammonia synthesis at temperatures as low as 50\u0026deg;C\u003csup\u003e\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u003c/sup\u003e. Ruthenium-based catalysts on supports such as La₂O₃ and CeO₂, often promoted with alkali metals, have demonstrated high activity at moderate pressures and temperatures\u003csup\u003e\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e,\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u003c/sup\u003e. Although promising, these catalysts remain largely at the experimental stage. Additionally, nanostructured supports and dual-oxide systems, such as MgO\u0026ndash;Nd₂O₃, exhibit enhanced selectivity and thermal stability; however, their commercial application remains limited\u003csup\u003e\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eProcess-level innovations have targeted reduced operating pressure and energy consumption through selective ammonia absorption using metal salts and tailored adsorption systems, enabling recycling at pressures as low as 20 bar\u003csup\u003e\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e,\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u003c/sup\u003e. These systems offer alternatives to conventional condensation-based separation, which demands higher pressure and refrigeration energy.\u003c/p\u003e\u003cp\u003eAmmonia is also classified based on the source of hydrogen used in its production, leading to descriptors such as grey, blue, and green ammonia. Due to cost advantages, grey ammonia, produced from fossil-derived hydrogen without carbon capture, remains the most prevalent. In contrast, blue ammonia incorporates carbon capture and storage (CCS), reducing net CO₂ emissions to about 0.856 kg CO₂-eq/kg NH₃ but increasing capital and operating costs \u003csup\u003e\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e,\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u003c/sup\u003e. This increase is partially attributed to the energy penalty of CCS systems, which typically ranges between 15% and 20%, depending on capture technology and integration level\u003csup\u003e\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u003c/sup\u003e. Green ammonia, which relies on hydrogen produced from renewable-powered electrolysis, offers the lowest emissions (~\u0026thinsp;0.052 kg CO₂-eq/kg NH₃) but is currently constrained by high energy costs, limited electrolyzer efficiency, and challenges in hydrogen compression\u003csup\u003e\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e,\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e,\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u003c/sup\u003e. Even with green hydrogen retrofits, maximum CO₂ reductions in existing grey plants are limited to ~\u0026thinsp;10% due to integration and thermal constraints\u003csup\u003e\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eAlternative technologies have also been evaluated within the reforming step, which is the most emissions-intensive component of ammonia production. Partial oxidation (POX) and autothermal reforming (ATR) offer exothermic or thermally balanced alternatives to SMR\u003csup\u003e\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e,\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e,\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e\u003c/sup\u003e. Dry reforming of methane (DRM), which utilizes CO₂ as an oxidant, is attractive in theory but suffers from high coke formation, unfavorable syngas ratios, and excessive energy demand\u003csup\u003e\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e,\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e\u003c/sup\u003e. Hybrid approaches, including tri-reforming and membrane-assisted air separation, have demonstrated improved syngas quality and emission reductions\u003csup\u003e\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e,\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e\u003c/sup\u003e. For example, a 27% increase in ammonia output and a decrease in CO₂ emissions to near-zero levels were achieved through such integration\u003csup\u003e\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eA more recent innovation in reforming technology involves integrating CO₂ utilization and carbon valorization within a single process unit. One such configuration is a dual-reactor system in which CH₄, CO₂, and O₂ are partially oxidized at moderate temperatures (~\u0026thinsp;550\u0026ndash;620\u0026deg;C) to generate syngas while simultaneously precipitating solid carbon in the form of multi-walled carbon nanotubes (MWCNTs). The product gas is subsequently processed in a high-temperature reformer to adjust the H₂/CO ratio for synthesis applications. This approach eliminates the need for steam, reduces oxygen demand, and enables autothermal operation, thereby improving thermal integration. Experimental and simulation studies have demonstrated that such systems can reduce CO₂ emissions by over 70% in certain gas-to-liquid (GTL) applications and enhance overall energy efficiency and process economics compared to conventional reforming routes like DRM and ATR\u003csup\u003e\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e,\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eBuilding on these advances, the present study evaluates the integration of such a carbon-valorizing reforming system into a conventional ammonia plant. A specific case study is presented, utilizing a dual-reactor reforming configuration, to assess energy use, lifecycle CO₂ emissions, and techno-economic performance in comparison to a conventional SMR-based facility. Steady-state simulations are conducted using Aspen Plus\u0026reg; for a 1,268 ton/day ammonia plant, and the analysis includes co-production of CNTs alongside ammonia. Economic metrics, such as the Levelized Cost of Ammonia (LCOA), Net Present Value (NPV), Internal Rate of Return (IRR), and payback period, are evaluated under conservative assumptions, with sensitivity analyses conducted across ammonia, carbon credit, CNT, and natural gas prices. The study aims to explore the feasibility of integrated reforming-based retrofits as a potential decarbonization pathway that combines emissions reduction with process intensification and value co-creation.\u003c/p\u003e"},{"header":"2. Methodology","content":"\u003cp\u003eThis study presents a comparative simulation-based assessment of ammonia production using two reforming technologies: the conventional Steam Methane Reforming (SMR) process and a dual-reactor reforming system capable of CO₂ utilization and carbon valorization. A specific dual-reforming configuration, hereafter referred to as the \u0026ldquo;retrofitted configuration\u0026rdquo;, is examined as a case study to evaluate the feasibility and performance of an integrated ammonia and carbon product pathway.\u003c/p\u003e\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003e2.1 Simulation Framework and Process Modeling\u003c/h2\u003e\u003cp\u003eAll process simulations were developed using Aspen Plus\u0026reg; V12.1 under steady-state conditions, replicating the main stages of an industrial ammonia plant with a nominal production capacity of 1270 metric tons per day. The conventional SMR-based configuration includes feed desulfurization, primary and secondary reforming, high- and low-temperature water-gas shift (WGS), CO₂ removal, methanation, and ammonia synthesis via the Haber\u0026ndash;Bosch loop. The complete base-case flowsheet is illustrated in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. This model was validated against benchmark data\u003csup\u003e\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e\u003c/sup\u003e, ensuring consistency in mass and energy balances.\u003c/p\u003e\u003cp\u003eBoth the SMR and the retrofitted configuration were simulated using the Redlich-Kwong-Soave equation of state with the Boston-Mathias alpha function (RKS-BM), which provides reliable predictions on thermodynamic properties at elevated pressures and temperatures\u003csup\u003e\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e,\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e\u003c/sup\u003e. To enhance accuracy in the ammonia synthesis loop, additional modifications were applied to improve vapor\u0026ndash;liquid equilibrium and enthalpy predictions.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eFor the retrofitted configuration case, equilibrium-based Gibbs reactors (RGibbs) were employed to simulate the dual-reactor system. This approach is supported by experimental results\u003csup\u003e\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e\u003c/sup\u003e, which demonstrated near-equilibrium conversions with deviations of less than \u0026plusmn;\u0026thinsp;8% for CH₄ conversion and consistent MWCNT yields across multiple scales. The reactor design utilizes a co-fed mixture of CH₄, CO₂, and O₂ at moderate temperatures (500\u0026ndash;650\u0026deg;C) and high pressure to promote rapid syngas formation and carbon nucleation under thermodynamically favorable conditions\u003csup\u003e\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e,\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec4\" class=\"Section2\"\u003e\u003ch2\u003e2.2 Base Case SMR Configuration\u003c/h2\u003e\u003cp\u003eThe SMR-based ammonia plant model represents a conventional facility that utilizes natural gas. The feed composition (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e) is primarily composed of methane (80.0%), along with 17.7% ethane, 1.25% heavier hydrocarbons (C₃+), and trace components, including nitrogen, oxygen, and sulfur compounds. The gas enters the system at 45\u0026deg;C and 38.2 bar and is first processed in a desulfurization unit to protect downstream catalysts\u003csup\u003e\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eNatural Gas Feed Composition and Inlet Conditions\u003csup\u003e\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"2\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eComponent\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMole Fraction (%)\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCH\u003csub\u003e4\u003c/sub\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e80.0\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eC\u003csub\u003e2\u003c/sub\u003eH\u003csub\u003e6\u003c/sub\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e17.7\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eC\u003csub\u003e3\u003c/sub\u003e+\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.25\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eN\u003csub\u003e2\u003c/sub\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.8\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eO\u003csub\u003e2\u003c/sub\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.2\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSulfur Compounds\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.0001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTemperature (\u003csup\u003eo\u003c/sup\u003eC)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e45\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePressure (bar)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e38.2\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eFollowing desulfurization, the feed is mixed with steam and introduced into a primary reformer operating at 791\u0026deg;C and 30.7 bar, where partial conversion to H₂, CO, and residual CH₄ occurs over Ni-based catalysts. The resulting gas is then fed to a secondary reformer with preheated air, facilitating complete methane conversion and the addition of nitrogen in a stoichiometric proportion. Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e presents the composition of the secondary reformer outlet.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eSecondary Reformer Outlet Stream Properties\u003csup\u003e\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"2\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eComponent\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003emole fraction (%)\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eH\u003csub\u003e2\u003c/sub\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e35.5\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eH\u003csub\u003e2\u003c/sub\u003eO\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e35.3\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eN\u003csub\u003e2\u003c/sub\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e15.2\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCO\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e8.4\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCO\u003csub\u003e2\u003c/sub\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e5.1\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCH\u003csub\u003e4\u003c/sub\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.3\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAr\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.2\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTemperature (\u0026deg;C)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e980\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePressure (bar)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e29\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eThe syngas undergoes WGS to reduce CO content from 8.4% to approximately 0.2%, followed by CO₂ removal using amine scrubbing to achieve\u0026thinsp;\u0026lt;\u0026thinsp;0.3% CO₂. The purified stream, with a near-ideal 3:1 H₂:N₂ ratio, proceeds to methanation, where trace CO and CO₂ are converted to CH₄ and H₂O. The resulting feed to the ammonia synthesis loop consists of ~\u0026thinsp;74% H₂, ~\u0026thinsp;25% N₂, and \u0026lt;\u0026thinsp;1% CH₄.\u003c/p\u003e\u003cp\u003eAmmonia synthesis occurs at ~\u0026thinsp;292 bar via the Haber\u0026ndash;Bosch loop, with single-pass nitrogen conversion of ~\u0026thinsp;24%. Reactor effluent contains unreacted H₂, N₂, and ~\u0026thinsp;24% NH₃, reflecting equilibrium-limited performance.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec5\" class=\"Section2\"\u003e\u003ch2\u003e2.3 Retrofitted Configuration with Dual-Reactor Reforming\u003c/h2\u003e\u003cp\u003eIn the retrofitted configuration, the conventional SMR and secondary reformers are replaced by a dual-reactor reforming system that simultaneously utilizes CO₂ and valorizes carbon. The first reactor operates at 400\u0026ndash;650\u0026deg;C and atmospheric pressure, where CH₄, CO₂, and O₂ (in a molar ratio of 1:0.6:0.1) are partially oxidized to produce syngas and a solid carbon intermediate. The second reactor, operating at elevated temperature, finalizes the syngas composition. The retrofitted system is tuned to match the H₂:N₂ ratio of the base-case outlet, ensuring seamless integration with downstream process units.\u003c/p\u003e\u003cp\u003eSimulation results estimate a carbon yield of 0.76 kg of MWCNTs per kg of NH₃ produced, corresponding to a theoretical annual output of 318,000 tons. To reflect commercialization constraints and avoid overestimation, a conservative 25% recovery factor is applied in the economic analysis, consistent with previous studies on similar reforming configurations\u003csup\u003e\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e,\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec6\" class=\"Section2\"\u003e\u003ch2\u003e2.4 Key Modeling Assumptions\u003c/h2\u003e\u003cp\u003eTo streamline comparative analysis, several simplifications were adopted. All process streams were modeled as single-phase with constant specific heat capacities. Phase transitions, latent heat effects, and pressure drops were neglected, a standard practice in early-stage feasibility studies for gas-phase systems\u003csup\u003e\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e,\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eReaction kinetics for SMR and WGS were taken from Aspen Plus libraries and validated against literature\u003csup\u003e\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e,\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e\u003c/sup\u003e. For the dual-reactor retrofitted configuration, the reformers were modeled using RGibbs modules based on published evidence indicating that equilibrium conversion accurately represents system performance under the studied operating conditions\u003csup\u003e\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e,\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e,\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec7\" class=\"Section2\"\u003e\u003ch2\u003e2.5 Performance Evaluation Metrics\u003c/h2\u003e\u003cdiv id=\"Sec8\" class=\"Section3\"\u003e\u003ch2\u003e2.5.1 Process Performance\u003c/h2\u003e\u003cp\u003eFour Key Performance Indicators (KPIs) were defined:\u003c/p\u003e\u003cp\u003e\u003col\u003e\u003cspan\u003e\u003cli\u003e\u003cp\u003eNatural Gas Consumption (kg/kg NH₃),\u003c/p\u003e\u003c/li\u003e\u003c/span\u003e\u003cspan\u003e\u003cli\u003e\u003cp\u003eSteam Demand (kg/kg NH₃),\u003c/p\u003e\u003c/li\u003e\u003c/span\u003e\u003cspan\u003e\u003cli\u003e\u003cp\u003eTotal Energy Use, including heat duties and compression work (kWh/kg NH₃),\u003c/p\u003e\u003c/li\u003e\u003c/span\u003e\u003cspan\u003e\u003cli\u003e\u003cp\u003eCO₂ Emissions, direct (Scope 1) and indirect (Scope 2).\u003c/p\u003e\u003c/li\u003e\u003c/span\u003e\u003c/ol\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec9\" class=\"Section3\"\u003e\u003ch2\u003e2.5.2 CO₂ Emissions Estimation\u003c/h2\u003e\u003cp\u003eDirect emissions originate from reforming reactions and combustion. Indirect emissions associated with utilities were estimated using a baseline emission factor of 0.36 kg CO₂/kWh, derived from Aspen Plus simulations of natural gas-fired utilities. All emissions are reported in kg CO₂-eq per kg NH₃ using GWP100 metrics. While this factor provides internal consistency, regional variations (0.05\u0026ndash;0.8 kg CO₂/kWh) are acknowledged as a source of uncertainty, particularly relevant for the retrofitted configuration, which exhibits higher electricity demand due to the additional process units\u003csup\u003e\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv id=\"Sec10\" class=\"Section2\"\u003e\u003ch2\u003e2.6 Economic Assessment Framework\u003c/h2\u003e\u003cdiv id=\"Sec11\" class=\"Section3\"\u003e\u003ch2\u003e2.6.1 Assumptions and Input Parameters\u003c/h2\u003e\u003cp\u003eThe economic evaluation is based on a 30-year project horizon and an 8% real discount rate. A nominal production of 1,268 tons NH₃/day (418,440 tons/year) was assumed. Input values are summarized in Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eEconomic Input Parameters for Techno-Economic Analysis.\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"3\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eParameter\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eValue\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eReference\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNatural gas\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cspan\u003e$\u003c/span\u003e4.0/MMBtu (baseline)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003csup\u003e\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eOxygen (retrofitted configuration only)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cspan\u003e$\u003c/span\u003e100/ton\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003csup\u003e\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCO₂ feed (retrofitted configuration only)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cspan\u003e$\u003c/span\u003e50/ ton\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003csup\u003e\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eElectricity\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cspan\u003e$\u003c/span\u003e0.07/KWh\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003csup\u003e\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCarbon-credit revenue\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cspan\u003e$\u003c/span\u003e30/ton CO₂ (baseline)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003csup\u003e\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e,\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAmmonia selling price\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cspan\u003e$\u003c/span\u003e450/ton (baseline)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003csup\u003e\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMWCNTs selling Price\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cspan\u003e$\u003c/span\u003e5/kg (baseline)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003csup\u003e\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec12\" class=\"Section3\"\u003e\u003ch2\u003e2.6.2 CAPEX and OPEX Estimation\u003c/h2\u003e\u003cp\u003eThe SMR plant CAPEX was derived from an LCOA of \u003cspan\u003e$\u003c/span\u003e229/ton NH₃\u003csup\u003e\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e\u003c/sup\u003e, resulting in an estimated investment of \u003cspan\u003e$\u003c/span\u003e454.3\u0026nbsp;million. For the retrofitted configuration modeled in this study, a 50% CAPEX uplift was applied to reflect additional equipment (e.g., second reformer, CO₂ loop, MWCNT recovery), yielding a total of \u003cspan\u003e$\u003c/span\u003e681.4 million\u003csup\u003e\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e,\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eOPEX for both configurations was estimated based on process simulation outputs, standard cost heuristics, and market price assumptions. Fixed costs were assumed to represent 10% of total OPEX for direct labor and maintenance. For the retrofit case, an additional 3% was added for chemicals in the retrofitted configuration case\u003csup\u003e\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e\u003c/sup\u003e. Carbon credit revenue and MWCNT sales were included in the retrofitted configuration.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec13\" class=\"Section3\"\u003e\u003ch2\u003e2.6.3 Economic Performance Indicators\u003c/h2\u003e\u003cp\u003eThe economic viability of both ammonia production configurations was evaluated using three key financial metrics: LCOA, NPV, and IRR. Calculations were performed over a 30-year project lifetime, assuming no salvage value was available.\u003c/p\u003e\u003cp\u003eThe LCOA, a standardized metric representing the average production cost over the plant\u0026rsquo;s operational lifetime, was calculated using the following Eq.\u0026nbsp;4\u003csup\u003e4\u003c/sup\u003e:\u003cdiv id=\"Equ1\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equ1\" name=\"EquationSource\"\u003e\n$$\\:LCOA=\\frac{CRF\\times\\:CAPEX+Annual\\:OPEX}{Annual\\:N{H}_{3}Production\\:\\left(tons\\right)}$$\u003c/div\u003e\u003cdiv class=\"EquationNumber\"\u003e1\u003c/div\u003e\u003c/div\u003e\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;.\u0026hellip;\u0026hellip;\u003c/p\u003e\u003cp\u003ewhere the Capital Recovery Factor (CRF) is defined as:\u003cdiv id=\"Equ2\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equ2\" name=\"EquationSource\"\u003e\n$$\\:CRF=\\frac{r{(1+r)}^{n}}{{(1+r)}^{n}-1}$$\u003c/div\u003e\u003cdiv class=\"EquationNumber\"\u003e2\u003c/div\u003e\u003c/div\u003e\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;.\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;..\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;.\u003c/p\u003e\u003cp\u003ewhere: r is the discount rate (8%), and n is the project lifetime (30 years).\u003c/p\u003e\u003cp\u003eThe NPV was calculated using the discounted cash flow approach:\u003cdiv id=\"Equ3\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equ3\" name=\"EquationSource\"\u003e\n$$\\:NPV=\\sum\\:_{t=1}^{n}\\frac{{R}_{t}-{C}_{t}}{{(1+r)}^{t}}-CAPEX$$\u003c/div\u003e\u003cdiv class=\"EquationNumber\"\u003e3\u003c/div\u003e\u003c/div\u003e\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;.\u003c/p\u003e\u003cp\u003ewhere R\u003csub\u003et\u003c/sub\u003e and C\u003csub\u003et\u003c/sub\u003e are the total revenues and costs in year t, respectively. CAPEX is treated as an upfront investment at year t\u0026thinsp;=\u0026thinsp;0\u003c/p\u003e\u003cp\u003eInflation rates were differentiated by revenue or cost type, by sector-specific economic trends:\u003c/p\u003e\u003cp\u003e\u003cul\u003e\u003cli\u003e\u003cp\u003eA 2% annual inflation was applied to ammonia prices, reflecting historical behavior in the nitrogen fertilizer sector\u003csup\u003e\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003c/li\u003e\u003cli\u003e\u003cp\u003eA 2.5% escalation rate was applied to operating expenditures (OPEX), capturing increases in energy, chemicals, and labor costs\u003csup\u003e\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003c/li\u003e\u003cli\u003e\u003cp\u003eA 1% inflation rate was used for carbon credit revenues, accounting for volatility in carbon pricing and regulatory uncertainty\u003csup\u003e\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003c/li\u003e\u003c/ul\u003e\u003c/p\u003e\u003cp\u003eThe IRR, defined as the discount rate at which NPV equals zero\u003csup\u003e\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e\u003c/sup\u003e, was also computed to assess investment attractiveness. The IRR values were calculated using Microsoft Excel\u0026rsquo;s built-in financial functions based on the annual net cash flow profiles. Python was used exclusively for generating figures and visualizing economic trends.\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e"},{"header":"3. Results and Discussion","content":"\u003cp\u003eA comparative analysis was conducted between the base-case SMR-based ammonia production process and the retrofitted configuration featuring a dual-reactor reforming system for integrated CO₂ utilization and carbon valorization. The comparison focuses on process efficiency, feedstock, energy consumption, and carbon footprint. All simulations were performed under steady-state conditions using Aspen Plus V12.1, with model validation against benchmark literature to ensure the reliability of the results.\u003c/p\u003e\u003cdiv id=\"Sec15\" class=\"Section2\"\u003e\u003ch2\u003e3.1 Simulation Validation and Reforming Process Comparison\u003c/h2\u003e\u003cp\u003eThe SMR-based ammonia plant simulation was validated for mass and energy balances against the reference study\u003csup\u003e\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e\u003c/sup\u003e. As detailed in Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e, the differences are less than 3% for most unit operations, including the SRM outlet, the water-gas shift (WGS) section, and the CO₂ removal unit. Larger discrepancies (20\u0026ndash;30%) were observed in internal synthesis loop flows, particularly in the recycle feed, reactor inlet gas, and purge stream.\u003c/p\u003e\u003cp\u003eThese variances are attributed to modeling choices and system sensitivities specific to high-pressure ammonia synthesis loops. Slight differences in CO₂ removal efficiency or inert gas content (e.g., Ar, CH₄) downstream of purification significantly influence hydrogen-to-nitrogen ratios, recycle rates, and purge volumes. Furthermore, assumptions related to vapor\u0026ndash;liquid separation, purge ratios, and simplified modeling of the final methanation step for CO/CO₂ removal may introduce compounding effects in loop circulation, without materially affecting ammonia yield or syngas quality.\u003c/p\u003e\u003cp\u003eThese details are well-documented in simulation studies of ammonia synthesis systems, where internal loop behavior exhibits a nonlinear dependency on purge and separation efficiency\u003csup\u003e\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e\u003c/sup\u003e. Despite differences, the present model captures all critical performance metrics, natural gas consumption, steam demand, syngas composition, and ammonia production, within an acceptable range, confirming its robustness for comparative analysis.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eSelected Validation Metrics Comparing Simulation Results with benchmark data\u003csup\u003e\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"4\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eStream\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eBenchmark data\u003csup\u003e\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e\u003c/sup\u003e (kg/kg NH₃)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003ePresent Study (kg/kg NH₃)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003e% Deviation\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eProcess NG\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.52\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.52\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSteam Input\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.93\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e1.93\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSRM Outlet\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e3.76\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e3.76\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eWGS Outlet\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e3.76\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e3.76\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCO₂ Removal Outlet\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.16\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e1.19\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u0026ndash;3%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eRecycle Feed\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2.47\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e2.97\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u0026ndash;20%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eReactor Inlet Gas\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e3.37\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e4.18\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u0026ndash;24%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNH₃ Product\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e1.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u0026mdash;\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eThe reforming section is the most energy- and carbon-intensive stage of ammonia production, serving as the focal point for retrofitting. In the SMR-based configuration, the primary and secondary reformers produce a syngas stream comprising 35.5% H₂, 15.2% N₂, and 5.1% CO₂ at 980\u0026deg;C and 29 bar. In contrast, the dual reactor retrofitted configuration, which utilizes CH₄, CO₂, and O₂, was tuned to achieve a similar syngas composition, eliminating the need for steam injection.\u003c/p\u003e\u003cp\u003eThe specific case study presented here achieved thermodynamic equilibrium for syngas generation while also enabling the co-production of MWCNTs, offering both environmental and potential economic benefits. The simulation results were validated against published experimental and scale-up studies\u003csup\u003e\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e,\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e\u003c/sup\u003e, confirming the reliability of the equilibrium-based approach. Key metrics, including CH₄ and CO₂ conversion, syngas composition, and carbon yield, matched closely with experimental data, as shown in Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab5\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eThermodynamic Validation of the Retrofitted Configuration Simulation Against Experimental Data.\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"3\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eParameter\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eAspen Plus Simulation (This Study)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eExperimental/Model Data\u003csup\u003e\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e,\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCH₄:CO₂:O₂ Feed Ratio\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1:0.6:0.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1:0.6:0.1\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eReactor 1 Temperature (\u0026deg;C)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e550\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e500\u0026ndash;600\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCO₂ Conversion (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e66\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e~\u0026thinsp;65\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCH₄ Conversion (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e82\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u0026plusmn;\u0026thinsp;8% deviation from experimental\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eH₂/CO Ratio\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e~\u0026thinsp;2.0\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCarbon Product Yield (kg/kg NH₃)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.76\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eConsistent multi-scale yield\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eEnergy Reduction vs. DRM\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e50%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e50%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec16\" class=\"Section2\"\u003e\u003ch2\u003e3.2 Energy and Feedstock Utilization\u003c/h2\u003e\u003cp\u003eThe integration of the dual-reactor reforming case study significantly altered the feedstock profile and energy requirements of the ammonia plant. As summarized in Table\u0026nbsp;\u003cspan refid=\"Tab6\" class=\"InternalRef\"\u003e6\u003c/span\u003e, the retrofit configuration consumed approximately 1.36 kg of natural gas per kg of ammonia, representing a 161.5% increase compared to the 0.52 kg/kg NH₃ consumption in the conventional SMR-based process. This increase is attributed to the additional methane feedstock required in the first reactor, which supports not only syngas formation but also the production of carbon nanotubes.\u003c/p\u003e\u003cp\u003eDespite the elevated methane input, the overall energy consumption of the retrofitted configuration decreased by 31.5%, from 4.51 to 3.09 kWh/kg NH₃. This outcome results from the autothermal operation of the dual-reactor configuration, which eliminates the need for external energy, as used in SMR furnaces. Operating at moderate temperatures (400\u0026ndash;650\u0026deg;C) and lower pressures, the system avoids the intense heat duties required in conventional primary reformers (~\u0026thinsp;800\u0026ndash;900\u0026deg;C), thereby reducing overall furnace duty, steam superheating loads, and compression energy demands.\u003c/p\u003e\u003cp\u003eIn addition, the process's partial conversion of methane into MWCNTs conserves a portion of the input energy within the solid byproduct rather than dissipating it as combustion heat. This effect, coupled with a 25% reduction in steam demand, contributes substantially to the system\u0026rsquo;s improved thermal efficiency.\u003c/p\u003e\u003cp\u003eAlthough the increased natural gas requirement may pose economic challenges in high-cost gas regions, the tradeoff is supported by two key factors: (1) reduced net energy consumption per unit of ammonia, and (2) incorporation of CO₂ into a solid value-added product, which improves both environmental impact and economic performance. The airflow rate into the secondary reformer remains constant across both configurations to preserve the stoichiometric balance required for ammonia synthesis. The ammonia production rate was fixed to 1,268 tons per day to ensure direct comparability.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab6\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 6\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eKey Process Inputs for SMR-Based vs. Retrofitted Ammonia Production.\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"4\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eParameter\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eSMR Configuration\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eRetrofitted Configuration\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eChange (%)\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNatural Gas Consumption (kg/kg NH₃)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.52\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.36\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e+\u0026thinsp;161.5%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSteam Demand (kg/kg NH₃)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.93\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.45\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-24.9%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTotal energy use (kWh/kg NH₃)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e4.51\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e3.09\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-31.5\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAir Flowrate (normalized)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eConstant\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eConstant\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNH₃ Yield (tons/day)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1268\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1268\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0% (matched)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec17\" class=\"Section2\"\u003e\u003ch2\u003e3.3 Carbon Footprint Reduction\u003c/h2\u003e\u003cp\u003eThe primary environmental advantage of retrofitting with an integrated reforming system lies in its substantial reduction of GHG emissions. As shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e, the total CO₂-equivalent emissions for the conventional SMR-based ammonia process were estimated at 2.35 kg CO₂-eq per kg NH₃, consistent with literature-reported values for large-scale natural gas-based ammonia plants without carbon capture\u003csup\u003e\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u003c/sup\u003e. In contrast, the retrofitted configuration modeled in this study achieved a 76% reduction, lowering net emissions to 0.57 kg CO₂-eq/kg NH₃.\u003c/p\u003e\u003cp\u003eThis emissions profile surpasses typical \u0026ldquo;blue ammonia\u0026rdquo; pathways, which combine SMR with carbon capture and storage (CCS) and report residual emissions in the range of 0.85 to 1.0 kg CO₂-eq/kg NH₃\u003csup\u003e\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e,\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u003c/sup\u003e. Such findings suggest that integrated reforming configurations with carbon valorization, as demonstrated in this case study, may serve as viable alternatives for achieving deep decarbonization in ammonia production, particularly when assessed within lifecycle assessment (LCA) frameworks and emerging carbon intensity benchmarks.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eThe observed reduction in carbon intensity is attributed to two synergistic mechanisms within the retrofit case:\u003c/p\u003e\u003cp\u003e\u003cul\u003e\u003cli\u003e\u003cp\u003eCO₂-reactive reforming chemistry: The first reactor operates under conditions that favor partial oxidation and dry reforming, where CO₂ acts as a chemical reactant, thereby reducing its release to the atmosphere.\u003c/p\u003e\u003c/li\u003e\u003cli\u003e\u003cp\u003eCarbon sequestration via solid byproduct formation: A portion of the carbon in the methane feed is transformed into MWCNTs. This stable solid byproduct sequesters carbon in a non-emissive form. This permanently removes carbon from the process stream, distinguishing it from CCS strategies that rely on long-term subsurface storage.\u003c/p\u003e\u003c/li\u003e\u003c/ul\u003e\u003c/p\u003e\u003cp\u003eUnder simulation assumptions, the retrofitted configuration demonstrated net-negative direct emissions, with a value of \u0026minus;\u0026thinsp;0.52 kg CO₂/kg NH₃. This reflects in-process CO₂ utilization and solid carbon formation that reduce total emissions relative to the SMR baseline.\u003c/p\u003e\u003cp\u003eIndirect emissions, estimated from total energy use and an emission factor of 0.36 kg CO₂/kWh, were also reduced by 32%, primarily due to lower electricity and steam demand enabled by autothermal reforming and improved heat integration.\u003c/p\u003e\u003cp\u003eThese results suggest that integrated reforming systems with carbon valorization, such as the one modeled in this study, may offer a viable pathway for decarbonizing ammonia production by coupling CO₂ reactivity with the formation of durable carbon products. However, the long-term carbon permanence and scalability of such pathways require further assessment, which is beyond the scope of this work.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec18\" class=\"Section2\"\u003e\u003ch2\u003e3.4 Process Integration and Infrastructure Compatibility\u003c/h2\u003e\u003cp\u003eBeyond energy and emissions metrics, the practical feasibility of deploying low-carbon reforming configurations within existing ammonia plants is a critical consideration in evaluating their scalability. The retrofitted configuration modeled in this study exhibits a high degree of compatibility with conventional ammonia plant infrastructure. Following the retrofit, no substantial downstream modifications are required beyond the reforming section, as all subsequent units, including high- and low-temperature shift reactors, CO₂ removal systems, methanation, and the ammonia synthesis loop, continue to operate under pressure-temperature conditions comparable to those in the baseline SMR configuration. This compatibility facilitates integration with minimal capital disruption and preserves established process control schemes.\u003c/p\u003e\u003cp\u003eIn addition to maintaining process continuity, the modeled retrofit offers potential thermal integration advantages through its autothermal operation. By eliminating the need for fired reformer furnaces typically required in SMR systems, this approach reduces dependence on external fuel combustion and enhances overall thermal efficiency.\u003c/p\u003e\u003cp\u003eHowever, the shift away from flue gas combustion also necessitates a reconfiguration of the plant\u0026rsquo;s heat recovery strategy. In SMR-based systems, significant heat recovery is achieved using process gas preheaters and flue gas-based Waste Heat Recovery Units (WHRUs), which are not applicable in the retrofitted configuration. Instead, heat recovery is maintained via internal boiler and exchanger configurations within the reforming section, with adjustments to boiler duty and exchanger sizing tailored to the altered thermal profile.\u003c/p\u003e\u003cp\u003eOverall, the case study suggests that integrated reforming systems, such as this, can be implemented with minimal infrastructure changes while maintaining operational continuity and improving energy efficiency, subject to the design constraints and boundary conditions modeled here.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec19\" class=\"Section2\"\u003e\u003ch2\u003e3.5 Techno-Economic Comparison\u003c/h2\u003e\u003cp\u003eTo assess the economic viability of the modeled retrofitted configuration using dual-reactor reforming, a comprehensive techno-economic analysis was conducted. This evaluation extends beyond conventional cost metrics by incorporating multiple financial indicators, namely, the LCOA, NPV, IRR, and payback period. Additionally, a sensitivity analysis was conducted to examine the impact of key market drivers, including the prices of MWCNTs, carbon credits, ammonia, and natural gas. Together, these metrics provide a comprehensive view of the comparative performance of the baseline and retrofitted ammonia production scenarios under both baseline and variable conditions.\u003c/p\u003e\u003cdiv id=\"Sec20\" class=\"Section3\"\u003e\u003ch2\u003e3.5.1 Levelized Cost of Ammonia (LCOA)\u003c/h2\u003e\u003cp\u003eThe LCOA was calculated to represent the average cost per ton of ammonia produced over the project lifetime, accounting for CAPEX and OPEX. For the SMR-based configuration, the LCOA was estimated at \u003cspan\u003e$\u003c/span\u003e272.5/ton NH₃, which aligns well with values reported for large-scale U.S.-based ammonia plants using SMR and ATR configurations\u003csup\u003e\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eIn contrast, the retrofitted configuration exhibited a significantly higher LCOA of \u003cspan\u003e$\u003c/span\u003e680.9/ton NH₃, driven by a\u0026thinsp;~\u0026thinsp;50% increase in capital costs and substantially elevated operating costs associated with electricity consumption, oxygen supply, and chemical handling for CO₂ utilization and nanomaterial recovery, as supported by earlier GTL case studies\u003csup\u003e\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e,\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eWhile LCOA remains a widely cited benchmark, it does not capture the environmental and economic co-benefits of emerging decarbonization technologies. Specifically, co-product revenue streams such as MWCNTs and carbon credits, modeled in the retrofit case, are excluded from LCOA calculations. Thus, LCOA alone may undervalue multi-output decarbonization pathways, especially those involving carbon valorization. To address this limitation, additional metrics, including NPV, IRR, and carbon abatement cost, are used to provide a more comprehensive assessment of long-term value.\u003c/p\u003e\u003cp\u003eTo quantify the environmental cost-effectiveness of retrofitting, Table\u0026nbsp;\u003cspan refid=\"Tab7\" class=\"InternalRef\"\u003e7\u003c/span\u003e presents the estimated cost of carbon abatement. Under the modeled conditions, the retrofit case achieves a 76% reduction in total emissions at an incremental cost of \u003cspan\u003e$\u003c/span\u003e4.75\u0026nbsp;billion over 30 years, resulting in an abatement cost of \u003cspan\u003e$\u003c/span\u003e212 per ton CO₂-eq avoided, a competitive value for deep decarbonization pathways.\u003c/p\u003e\u003cp\u003eThis value compares favorably to current carbon market benchmarks: the EU Emissions Trading System (EU ETS) price averaged approximately \u003cspan\u003e$\u003c/span\u003e85\u0026ndash;\u003cspan\u003e$\u003c/span\u003e100 per ton in 2025, while U.S. compliance credit values range between \u003cspan\u003e$\u003c/span\u003e30\u0026ndash;\u003cspan\u003e$\u003c/span\u003e60 per ton of CO₂\u003csup\u003e\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e,\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e\u003c/sup\u003e. The estimated abatement cost is also lower than that of Direct Air Capture (DAC), which typically ranges from \u003cspan\u003e$\u003c/span\u003e250 to \u003cspan\u003e$\u003c/span\u003e600 per ton of CO₂ removed\u003csup\u003e\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e\u003c/sup\u003e, underscoring its relative advantage among negative-emission technologies.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab7\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 7\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eComparative Lifetime Costs and Emissions for SMR and Retrofitted Configuration Ammonia Production Pathways.\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"4\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMetric\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eSMR-Based Process\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eRetrofitted Configuration\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eDifference\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTotal 30-Year Cost (Million USD)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2,664.0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e7,413.8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e+\u0026thinsp;4,749.7\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTotal 30-Year CO₂ Emissions (Million tons CO₂-eq)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e29.5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e7.3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-22.2\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCarbon Abatement Cost (USD/ton CO₂-eq avoided)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e212\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eAlthough the current analysis does not account for tax incentives, it is notable that recent U.S. policy instruments such as 45V significantly enhance the economic competitiveness of blue and hybrid ammonia pathways\u003csup\u003e\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec21\" class=\"Section3\"\u003e\u003ch2\u003e3.5.2 Profitability and Economic Performance\u003c/h2\u003e\u003cp\u003eAlthough LCOA favors the SMR route, a complete profitability analysis reveals a different outcome under the modeled conditions. A discounted cash flow (DCF) model was developed for both systems over a 30-year project horizon, using an 8% discount rate and inflation assumptions of 2% for ammonia prices and 2.5% for OPEX.\u003c/p\u003e\u003cp\u003eThe ammonia production rate was fixed at 418,440 tons/year, with baseline ammonia revenue of \u003cspan\u003e$\u003c/span\u003e188.3\u0026nbsp;million/year (at \u003cspan\u003e$\u003c/span\u003e450/ton). For the retrofitted configuration, two additional revenue streams were included:\u003c/p\u003e\u003cp\u003e\u003cul\u003e\u003cli\u003e\u003cp\u003eCarbon credits: Based on avoided emissions of 1.77 kg CO₂-eq/kg NH₃, monetized at \u003cspan\u003e$\u003c/span\u003e30/ton CO₂, contributing ~\u003cspan\u003e$\u003c/span\u003e22.2\u0026nbsp;million/year.\u003c/p\u003e\u003c/li\u003e\u003cli\u003e\u003cp\u003eMWCNT sales: With a modeled yield of 0.19 kg/kg NH₃ and a conservative 0.25 correction factor applied to account for commercialization constraints, the marketable output (~\u0026thinsp;79,500 tons/year) was valued at \u003cspan\u003e$\u003c/span\u003e5/kg, generating approximately \u003cspan\u003e$\u003c/span\u003e397.5\u0026nbsp;million/year in potential revenue.\u003c/p\u003e\u003c/li\u003e\u003c/ul\u003e\u003c/p\u003e\u003cp\u003eUnder these assumptions, the profitability indicators improve significantly for the retrofit case:\u003c/p\u003e\u003cp\u003e\u003cul\u003e\u003cli\u003e\u003cp\u003eNPV increases from \u003cspan\u003e$\u003c/span\u003e1.06\u0026nbsp;billion (SMR) to \u003cspan\u003e$\u003c/span\u003e3.41\u0026nbsp;billion (Retrofitted configuration)\u003c/p\u003e\u003c/li\u003e\u003cli\u003e\u003cp\u003eIRR rises from 27\u0026ndash;56%\u003c/p\u003e\u003c/li\u003e\u003cli\u003e\u003cp\u003ePayback period is reduced from 11.5 to 4.5 years\u003c/p\u003e\u003c/li\u003e\u003c/ul\u003e\u003c/p\u003e\u003cp\u003eThese results, illustrated in Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e, suggest that integrating a carbon-valorizing reformer may offer long-term economic benefits, particularly when co-products and emission-related incentives are monetized.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003cem\u003e(Ammonia = $450/ton, MWCNT = $5/kg, Carbon credit = $30/ton CO₂, Natural Gas = $4/MMBtu)\u003c/em\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec22\" class=\"Section3\"\u003e\u003ch2\u003e3.5.3 Sensitivity Analysis\u003c/h2\u003e\u003cp\u003eTo better understand the influence of individual market variables on the economic performance of the retrofitted configuration, a sensitivity analysis was conducted across four key factors: MWCNT price, carbon credit value, ammonia price, and natural gas cost. These parameters were selected due to their high volatility and substantial impact on revenue and profitability projections. Sensitivity trends observed in this study reflect those reported in recent techno-economic assessments of blue and hybrid ammonia pathways\u003csup\u003e\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e\u003c/sup\u003e, particularly regarding the pronounced effect of natural gas price fluctuations on process viability.\u003c/p\u003e\u003cp\u003e\u003cb\u003eMWCNT Price Sensitivity\u003c/b\u003e\u003c/p\u003e\u003cp\u003eMWCNT prices vary significantly by purity, grade, and application, with literature citing a wide range from \u003cspan\u003e$\u003c/span\u003e3/kg to over \u003cspan\u003e$\u003c/span\u003e1,000/kg\u003csup\u003e43,52\u0026ndash;55\u003c/sup\u003e. Sensitivity analysis was conducted across a realistic range of \u003cspan\u003e$\u003c/span\u003e2 to \u003cspan\u003e$\u003c/span\u003e80/kg to assess the impact on NPV and IRR.\u003c/p\u003e\u003cp\u003eAs shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e, both metrics rise steeply with MWCNT price. At \u003cspan\u003e$\u003c/span\u003e2/kg, the retrofitted configuration still achieves a positive NPV of \u003cspan\u003e$\u003c/span\u003e0.73\u0026nbsp;billion and an IRR of 20%. At \u003cspan\u003e$\u003c/span\u003e50/kg, the NPV exceeds \u003cspan\u003e$\u003c/span\u003e43\u0026nbsp;billion, and IRR surpasses 580%; however, such values represent upper-bound theoretical estimates and assume complete market absorption of the co-product at premium prices.\u003c/p\u003e\u003cp\u003eThe assumed \u003cspan\u003e$\u003c/span\u003e5/kg price reflects a conservative estimate for industrial-grade applications such as polymer additives, coatings, and conductive fillers\u003csup\u003e\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e,\u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e\u003c/sup\u003e. Large-scale deployment would require securing demand in bulk markets such as cement or asphalt, which may offer lower prices but significant volumes.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003cb\u003eCarbon Credit Sensitivity\u003c/b\u003e\u003c/p\u003e\u003cp\u003eCarbon credit values varied from \u003cspan\u003e$\u003c/span\u003e30 to \u003cspan\u003e$\u003c/span\u003e100 per ton of CO₂. Results show a modest effect: NPV increased from \u003cspan\u003e$\u003c/span\u003e3.41 to \u003cspan\u003e$\u003c/span\u003e4.10\u0026nbsp;billion, and IRR from 56\u0026ndash;64%. This indicates that while carbon credits improve returns, the economic feasibility of the retrofitted configuration is not dependent on high carbon pricing, a valuable attribute in uncertain policy environments.\u003c/p\u003e\u003cp\u003e\u003cb\u003eAmmonia Price Sensitivity\u003c/b\u003e\u003c/p\u003e\u003cp\u003eAmmonia prices fluctuate considerably depending on regional energy dynamics and international supply-demand balances, with recent global prices ranging from \u003cspan\u003e$\u003c/span\u003e300 to over \u003cspan\u003e$\u003c/span\u003e800 per ton\u003csup\u003e\u003cspan additionalcitationids=\"CR57\" citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e58\u003c/span\u003e\u003c/sup\u003e. Sensitivity analysis conducted across this range revealed strong profitability trends for both the SMR and retrofitted configurations, as illustrated in Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e.\u003c/p\u003e\u003cp\u003eFor the SMR pathway, the NPV increases from \u003cspan\u003e$\u003c/span\u003e0.2\u0026nbsp;billion at \u003cspan\u003e$\u003c/span\u003e300/ton to \u003cspan\u003e$\u003c/span\u003e3.06\u0026nbsp;billion at \u003cspan\u003e$\u003c/span\u003e800/ton, with the IRR rising from 12\u0026ndash;59%, and the payback period shortening from more than 16 years to 4.1 years. In comparison, the retrofitted configuration demonstrates even greater resilience: its NPV improves from \u003cspan\u003e$\u003c/span\u003e2.6\u0026nbsp;billion to \u003cspan\u003e$\u003c/span\u003e5.41\u0026nbsp;billion, its IRR increases from 46\u0026ndash;78%, and its payback period declines from 6 years to just 3 years over the exact price interval.\u003c/p\u003e\u003cp\u003eNotably, the retrofitted system remains economically viable even at the low end of the price spectrum, \u003cspan\u003e$\u003c/span\u003e300/ton, which is well below its calculated LCOA of \u003cspan\u003e$\u003c/span\u003e680.90/ton NH₃. This continued profitability is made possible by its diversified revenue streams from MWCNT sales and carbon credits, highlighting the limitations of relying solely on LCOA when evaluating low-carbon ammonia technologies.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003cb\u003eNatural Gas Price Sensitivity\u003c/b\u003e\u003c/p\u003e\u003cp\u003eNatural gas prices varied from \u003cspan\u003e$\u003c/span\u003e1.50 to \u003cspan\u003e$\u003c/span\u003e13.00/MMBtu, reflecting global conditions, from subsidized gas in the Middle East to high import prices in Europe\u003csup\u003e\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e,\u003cspan additionalcitationids=\"CR60\" citationid=\"CR59\" class=\"CitationRef\"\u003e59\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e61\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab8\" class=\"InternalRef\"\u003e8\u003c/span\u003e summarizes the impact on economic performance for the retrofitted configuration. The system remains economically viable up to \u003cspan\u003e$\u003c/span\u003e10/MMBtu, beyond which the project becomes infeasible, with negative NPV and no payback within the 30-year timeframe. This emphasizes the importance of feedstock price stability when deploying reforming technologies with high methane input requirements, particularly in regions aiming for deep decarbonization.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab8\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 8\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eImpact of Natural Gas Price on the Economic Viability of the Retrofitted Configuration \u003cem\u003e(Ammonia = $450/ton, MWCNT = $5/kg, Carbon credit = $30/ton CO₂).\u003c/em\u003e\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"4\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNatural Gas Price (\u003cspan\u003e$\u003c/span\u003e/MMBtu)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNPV (Billion USD)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eIRR (%)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003ePayback Period (Years)\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e1.5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e4.57\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e68\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e3.5\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e3.0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e3.87\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e61\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e4.0\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e4.0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e3.41\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e56\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e4.5\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e5.0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2.95\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e51\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e4.8\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e7.0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2.03\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e41\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e6.5\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e10.0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.64\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e23\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u0026gt;\u0026thinsp;30\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e13.0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eNot recoverable\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e"},{"header":"4. Conclusions","content":"\u003cp\u003eThis study investigates the technical, environmental, and economic performance of retrofitting conventional ammonia plants with an advanced dual-reactor reforming system that integrates CO₂ utilization and carbon valorization. Through steady-state process simulation and techno-economic analysis, the retrofitted configuration achieved a 76% reduction in lifecycle CO₂-equivalent emissions and a 31% decrease in total energy consumption compared to a traditional SMR-based process, while maintaining the same ammonia production capacity of 1,268 tons per day.\u003c/p\u003e\u003cp\u003eWhile the LCOA for the retrofitted case is higher than for SMR (\u003cspan\u003e$\u003c/span\u003e680.9/ton vs. \u003cspan\u003e$\u003c/span\u003e272.5/ton NH₃), additional revenue streams from co-product recovery, including carbon credits and MWCNTs, significantly improve the economic outlook. The resulting NPV exceeds \u003cspan\u003e$\u003c/span\u003e3.4\u0026nbsp;billion, with an IRR of 56% and a payback period of 4.5 years.\u003c/p\u003e\u003cp\u003eSensitivity analysis confirms that the configuration remains economically viable under conservative pricing scenarios (e.g., \u003cspan\u003e$\u003c/span\u003e300/ton ammonia and \u003cspan\u003e$\u003c/span\u003e2/kg MWCNTs), indicating resilience to market variability.\u003c/p\u003e\u003cp\u003eThe findings support the feasibility of integrating carbon conversion into existing hydrogen-intensive chemical processes as a scalable approach to decarbonization. The dual-reactor reforming concept may be particularly relevant for regions with access to low-cost methane, concentrated CO₂ sources, and carbon offset markets. By reducing emissions and enhancing energy efficiency, this approach directly contributes to global climate goals and aligns with Sustainable Development Goal 7 (Affordable and Clean Energy), which promotes access to clean energy through improved industrial sustainability.\u003c/p\u003e\u003cp\u003eFuture research should incorporate a comprehensive life-cycle assessment (LCA), dynamic simulation, and pilot-scale testing to validate performance under operational conditions. Broader applicability may extend to methanol, synthetic fuels, and clean hydrogen production, advancing resource-efficient and low-carbon industrial pathways.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eFunding\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis work was made possible by NPRP, Qatar grant NPRP14S-0328-210106 from the Qatar National Research Fund (a member of the Qatar Foundation), and the Hamad bin Khalifa University (HBKU) CARGEN Bridge Fund. The authors would also like to acknowledge the Qatar National Library for its support of open-access publication. The statements herein are solely the responsibility of the authors.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting Interest Statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis manuscript presents a simulation-based assessment of a novel retrofit configuration for large-scale ammonia production, integrating dual-reactor reforming technology to significantly reduce the carbon intensity of the final products. By combining CO₂ utilization and carbon valorization into a single unit operation, the proposed system enables the co-production of synthesis gas and multi-walled carbon nanotubes (MWCNTs), offering a transformative approach to decarbonizing the ammonia synthesis process. Our results, based on Aspen Plus® modeling and detailed techno-economic analysis, indicate a 76% reduction in lifecycle CO₂ emissions and a 31% decrease in energy demand, with promising financial metrics including a 56% internal rate of return and a 4.5-year payback period.\u003c/p\u003e\n\u003cp\u003eThis study makes a meaningful contribution to the field by offering a scalable and economically viable pathway for retrofitting existing hydrogen-intensive chemical plants. The integration of carbon valorization not only reduces emissions but also enhances profitability, an area of increasing importance as the industry transitions toward net-zero targets. The authors would like to declare that the concept of the two-reactor reformer was developed by them and published in Scientific Reports in 2021 (vol. 11, 1417 (2021)). It is also patented as CARGEN technology. This study demonstrates the potential for integrating similar technology in ammonia production to reduce its carbon intensity (CI) and cost, thereby decarbonizing the industry.\u0026nbsp;\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eNM Methodology, Investigation, Validation, Data Curation, TM Formal Analysis, Writing \u0026ndash; Original Draft, Visualization, MC Concept development, Investigation, Methodology, Writing \u0026ndash; Review \u0026amp; Editing, and EM Resources, Writing \u0026ndash; Review \u0026amp; Editing. HC Writing \u0026ndash; Review \u0026amp; Editing, and NE Concept development, Supervision, Project Administration, Writing \u0026ndash; Review \u0026amp; Editing.\u003c/p\u003e\u003ch2\u003eData Availability\u003c/h2\u003e\u003cp\u003eThe ASPEN models and the sumilation packages as well as the economic asssesment data.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eRajender, I., Abdullah, B. \u0026amp; Asiri, M. \u003cem\u003eSustainable ammonia production\u003c/em\u003e. Green Energy and Technology. [Online]. Available: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://www.springer.com/series/8059\u003c/span\u003e\u003cspan address=\"http://www.springer.com/series/8059\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eHosseini, H. 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Available: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://ycharts.com/indicators/europe_natural_gas_price\u003c/span\u003e\u003cspan address=\"https://ycharts.com/indicators/europe_natural_gas_price\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (accessed.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Ammonia production, retrofitting, dual reforming, CNTs, decarbonization, techno-economic analysis","lastPublishedDoi":"10.21203/rs.3.rs-7086583/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7086583/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eDecarbonizing ammonia production is crucial for reducing industrial greenhouse gas emissions; however, steam methane reforming (SMR) remains the dominant, carbon-intensive pathway. This study proposes a retrofit strategy for large-scale ammonia plants (1,268 tons/day) by replacing the conventional reformer with an advanced dual-reactor system that enables CO₂ utilization and carbon valorization. The novel configuration co-produces synthesis gas and multi-walled carbon nanotubes (MWCNTs), integrating ammonia and CNT production in a single process. Aspen Plus\u0026reg; simulations compare the baseline SMR process with the retrofitted configuration, assessing energy demand, feedstock consumption, CO\u003csub\u003e2\u003c/sub\u003e emissions, and economic performance. The retrofitted system achieves a 76% reduction in lifecycle CO₂-equivalent emissions and a 31% decrease in total energy demand, despite a 2.6-fold increase in methane input. At 25% MWCNT recovery, the Levelized Cost of Ammonia (LCOA) increases to \u003cspan\u003e$\u003c/span\u003e680.90/ton; however, substantial co-product revenue yields a 3.2-fold increase in Net Present Value (NPV), 56% Internal Rate of Return (IRR), and a 4.5-year payback period. Sensitivity analyses support the robustness of the economic potential, confirming the viability of integrated CNT-ammonia production as a pathway for sustainable, low-carbon manufacturing.\u003c/p\u003e","manuscriptTitle":"Potentials for Decarbonizing Ammonia Synthesis Plants: Retrofitting of Novel Process Configurations","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-08-25 18:02:06","doi":"10.21203/rs.3.rs-7086583/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-09-28T19:47:23+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-09-15T10:12:11+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-09-11T19:54:43+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"299772267868061167188940638282405127211","date":"2025-09-03T18:27:40+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"215617468401201280741576038405589391077","date":"2025-09-01T12:09:57+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-08-16T03:40:07+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-08-07T12:59:52+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-07-19T13:43:01+00:00","index":"","fulltext":""},{"type":"submitted","content":"Scientific Reports","date":"2025-07-19T13:39:21+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"ffea7604-5dcd-41ff-b93f-64203226f2ff","owner":[],"postedDate":"August 25th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[{"id":53293148,"name":"Physical sciences/Energy science and technology"},{"id":53293149,"name":"Physical sciences/Engineering"},{"id":53293150,"name":"Earth and environmental sciences/Environmental sciences"}],"tags":[],"updatedAt":"2025-12-22T16:05:56+00:00","versionOfRecord":{"articleIdentity":"rs-7086583","link":"https://doi.org/10.1038/s41598-025-28598-y","journal":{"identity":"scientific-reports","isVorOnly":false,"title":"Scientific Reports"},"publishedOn":"2025-12-15 15:58:15","publishedOnDateReadable":"December 15th, 2025"},"versionCreatedAt":"2025-08-25 18:02:06","video":"","vorDoi":"10.1038/s41598-025-28598-y","vorDoiUrl":"https://doi.org/10.1038/s41598-025-28598-y","workflowStages":[]},"version":"v1","identity":"rs-7086583","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7086583","identity":"rs-7086583","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}