Gas Removal Process Research Articles

Reconfiguration of acid gas removal process matching the integration of coal chemical industry with green hydrogen

The focus of the acid gas removal process has shifted from decarbonization and desulfurization to desulfurization in the context of integrating coal chemical technology with green H2 without a water gas shift unit. The conventional Rectisol process, Selexol process, organic amine process, and sulfone-amine process have been reconfigured to form the R-Rectisol process, R-Selexol process, R-MDEA process, and R-Sulfolane-MDEA process to adapt to the shift of acid gas removal target. The removal efficiency of H2S and CO2, process energy consumption, and process cost are investigated to evaluate the technical and economic performance of the above four reconfigured acid gas removal processes. The results indicate that for the R-Recitsol process and R-Selexol process, both high pressure and low temperature increase the relative selectivity of H2S to CO2, thereby enhancing the selective removal of H2S. In contrast, for the R-MDEA process and R-Sulfolane-MDEA process, low pressure and low temperature improve the relative selectivity of H2S to CO2, thereby facilitating the selective removal of H2S. Under optimal operating conditions, the value of relative selectivity of H2S to CO2 of the R-Sulfolane-MDEA process is the largest, and the relative selectivity of H2S to CO2 of the R-Rectisol process, R-Selexol process and R-MDEA process are only 7.64 %, 12.85 %, and 68.40 % of the relative selectivity of H2S to CO2 of the R-Sulfolane-MDEA process, respectively. Compared to the other three reconfigured acid gas removal processes, the R-Sulfolane-MDEA process demonstrates superior advantages in both energy consumption and economic feasibility, provided that the H2S levels remain below 0.1 ppm in purified syngas. This study aims to enhance the decision-making process for gas purification methods in the coal chemical industry by considering integrated green H2 as an alternative to the water gas shift unit.

Development of a selective sequential process for H2S enrichment and CO2 capture in aqueous MDEA solutions

The typical acid gas removal process can simultaneously remove acid gases from the raw gas using an aqueous MDEA solution. But it cannot further separate and capture hydrogen sulfide and carbon dioxide, and increases the burden on subsequent processing. Recovering carbon dioxide from that not only increases the H2S content in the acid gas, but also achieves the CO2 capture. To realize these, acid gas enrichment and carbon dioxide capture are integrated into the typical acid gas removal process. In this study, a novel selective sequential process in aqueous MDEA solutions is proposed for H2S enrichment and CO2 capture. And an optimization framework is proposed to optimize the parameters of the whole process, mainly to improve the efficiency of the column equipment. It is found that small diameter column is suitable for enhancing selectivity and large diameter column is suitable for maximizing productive capacity. To demonstrate the performance of the proposed process, the evaluation results, carbon sulfur ratio (3.81), return on investment (6.26) and carbon dioxide capture ratio (−0.63) are obtained from technical, economic and environmental evaluations. In comparison with the typical process, the novel process can achieve H2S enrichment and CO2 capture while remaining economically viable. This study presents a method for collaborative removal of H2S and CO2 in acid gas removal process. It is advantageous to reduce carbon dioxide emissions.

Transient behavior of the DYNASWIRL® phase separator during cryogenics tank-to-tank transfer operations

In order to separate gas and liquid from a two-phase mixture in space or earth applications, one can generate a strong artificial acceleration field instead of relying on gravity. This can be achieved by generating a swirl flow in a separator. The DYNASWIRL® phase separator is such a passive device, which had been demonstrated in air/water mixtures in the laboratory and on five reduced gravity NASA parabolic flights. In this work, extensive laboratory testing and numerical simulations are conducted to demonstrate the validity of the DYNASWIRL for phase separation with cryogenics. Liquid nitrogen (LN2) is used for extensive testing involving unsteady tank-to-tank transfer with quenching of separator and piping, liquid boil-off and vaporization, phase separation and recovery. This paper describes the separator and testing setups used. It examines the effects of the liquid (water and LN2), geometric parameters, and their effects on the separation and on the pressure loss across the separator, and analyzes the flow dynamics of the gas removal process. Validated numerical simulations support the experimental results and help explain the effects of the design parameters on the results.

Multiparameter optimization of the acid gas removal process using self-heat recuperation technology in IGCC system based on genetic algorithm

The acid gas removal (AGR) process in the integrated gasification combined cycle (IGCC) system consumes a large amount of heat and reduces the generation efficiency. Process modification of self-heat recuperation (SHR) technology based on vapor compression heat pumps is expected to reduce the energy consumption of the AGR process. On this basis, this paper conducted a comprehensive and parametric analysis of the AGR process integrated with a vapor compression heat pump. Wherein, two key parameters, the stripper pressure (P1) and the heat pump heat exchanger inlet pressure (P2), were analyzed in detail to understand the energy consumption characteristics of each module of the system. By establishing the optimization objective functions of minimizing system operating cost and exergy loss respectively, the system multi-parameter optimization was conducted based on the genetic algorithm by coding and solving in HYSYS and MATLAB. The corresponding parameter variables for the optimal cases of the two optimization objectives are also comparatively derived. The results showed that P1 mainly changes the SHR capacity of the system by changing the allowable flow rate of the SHR mass under different working conditions, while P2 mainly affects the SHR capacity of the system by changing the heat of the fraction at the top of the stripper. The minimum operating cost of the system decreased to 0.0655 $/kgH2S, which is 1.50 % lower compared to the original case. The minimum exergy loss of the system is reduced from 7788.89 kW to 7398.59 MW, which is about 5.01 % lower than that of the original case.

Solubility of Methane in Ionic Liquids for Gas Removal Processes Using a Single Multilayer Perceptron Model

In this work, four hundred and forty experimental solubility data points of 14 systems composed of methane and ionic liquids are considered to train a multilayer perceptron model. The main objective is to propose a simple procedure for the prediction of methane solubility in ionic liquids. Eight machine learning algorithms are tested to determine the appropriate model, and architectures composed of one input layer, two hidden layers, and one output layer are analyzed. The input variables of an artificial neural network are the experimental temperature (T) and pressure (P), the critical properties of temperature (Tc) and pressure (Pc), and the acentric (ω) and compressibility (Zc) factors. The findings show that a (4,4,4,1) architecture with the combination of T-P-Tc-Pc variables results in a simple 45-parameter model with an absolute prediction deviation of less than 12%.

A comparison between Claus and THIOPAQ sulfur recovery techniques in natural gas plants

A sulfur recovery process is one of the most important processes in the oil and gas industry to get rid of hydrogen sulfide (H2S) which is produced from the acid gas removal process of sour natural gas to convert it into sweet natural gas. Actual data from a gas field is used to obtain a realistic comparison between two sulfur recovery techniques, through which researchers and/or manufacturers can obtain information that will help them choose the most appropriate and cheapest method. A total feed acid gas flow rate of 5.1844 MMSCFD with an H2S concentration of 24.62% by mole percent was produced from amine acid gas removal units. Claus sulfur recovery technique is a traditional chemical process that uses thermal and catalytic reactors. Therefore, an acid gas enrichment unit is applied to increase the H2S concentration to approximately 50% mole to provide reliable and flexible operation in the thermal and catalytic reactors. Moreover, a tail gas treatment unit is applied to increase the overall conversion efficiency to 99.90% with the Claus technique instead of 95.08% without it to achieve high sulfur recovery and reliable operation through the conversion of carbonyl sulfide (COS) and mercaptans. Studies on the safety and simplicity of the Claus technique revealed many important hazards and a large number of transmitters (379) and control loops (128) in one Claus train. THIOPAQ sulfur recovery as a new technology is a biological desulfurization process that uses a natural mixture of sulfide-oxidizing bacteria. It is also a unique H2S removal process with an efficiency of 99.999%. In addition, studies on the safety and simplicity of the THIOPAQ technique have shown that the hazards, the number of transmitters (74), and the number of control loops (29) of a one THIOPAQ train are lower. The THIOPAQ technique showed higher efficiency, was safer, simpler, and had lower CAPEX and OPEX. This study was conducted using Aspen HYSYS V11 and actual data.

Design and analysis for chemical process electrification based on renewable electricity: Coal-to-methanol process as a case study

Electrification of traditional large-scale chemical industry based on renewable electricity can greatly reduce process CO2 emission, and store intermittent renewable electricity into chemical products locally to decrease power grid frequency regulation caused by fluctuating renewable electricity. This study presents a framework for electrification of chemical industry from indirect and direct aspects using the state-of-art coal-to-methanol process as a case study. Traditional coal-to-methanol (Process 1) suffers from high CO2 emission due to mismatch of H/C ratio between coal and methanol. A pulverized coal gasification-integrated SOEC process (Process 2) has been investigated, the water–gas-shift unit is avoided and a simplified acid gas removal process is implemented to replace traditional acid gas removal unit in Process 2. Electric heaters and heat pump system are applied in Process 2 as direct electrification methods to form semi-electrified scenario (Process 3). To discuss the effect of electrification levels on process performances, a fully electrified process (Process 4) is also designed. The results show that: CO2 emissions of the four processes are 2.19, 0.71, 0.52 and 0.63 t/t MeOH, and energy efficiency are 57.40 %, 62.32 %, 64.31 % and 57.63 %, respectively. Production costs are 159.1, 294.3, 301.0 and 358.3 $/t MeOH, IRRs are 14, 31, 29 and 14.5 %, respectively. Through this research and analysis, we hope to explore integration potential of renewable electricity and traditional chemical industry, and design a greener methanol production route based on renewable electricity.

Rate-Based Modeling and Assessment of an Amine-Based Acid Gas Removal Process through a Comprehensive Solvent Selection Procedure

In this study, an industrial acid gas removal (AGR) process which uses amine-based solvents was designed and simulated. The selection of suitable absorbents is crucial for an effective AGR process. Therefore, various single and blended amine-based solvents for capturing acid gases were evaluated through a comprehensive procedure, including solvent screening and process design steps. First, various solvents were screened for their CO2 and H2S absorption efficiencies. Promising solvents were then selected for the process design step, in which all process alternatives were simulated and rigorously designed using Aspen Plus. The non-equilibrium rate-based method with an electrolyte non-random two-liquid thermodynamic model was employed for modeling the absorption column. All processes were evaluated in terms of energy requirements, costs, and carbon emissions. The results show that a blend of methyldiethanolamine and piperazine solutions are the most promising solvents for the AGR process, as they can save up to 29.1% and 30.3% of the total annual costs and carbon emissions, respectively, compared to the methyldiethanolamine + diethanolamine solvent process.

Efficient pollutant removal from deodorization wastewater during sludge composting using MBR-CANON process

Sludge composting is one of the most economical and effective sludge disposal method at present. However, the composting process releases massive odorous gas, and the gas removal process produces a large amount of deodorizing wastewater with low C/N ratio (named as composting wastewater). In this study, completely autotrophic nitrogen removal over nitrite (CANON) process was adopted for treating composting wastewater. After treated, the ammonia decreased to 0–5 mg L−1, and the total nitrogen removal achieved to 0.200 kg m−3 d−1. Although the introduction of composting wastewater reduced the hydroxylamine oxidoreductase enzyme activity, heme-c, and hzo gene, all of them could be recovered. Microorganisms secreted more extracellular polymeric substances to counteract the cell-damage caused by harmful substances. Chloroflexi, Proteobacteria, and Planctomycetota were detected as the dominant phyla in the system, and the relative abundances of Candidatus_Kuenenia and Nitrosomonas reached 19.8% and 2.8%, respectively. CANON process could be used for treating composting wastewater.

Application of a Single Multilayer Perceptron Model to Predict the Solubility of CO2 in Different Ionic Liquids for Gas Removal Processes

In this work, 2099 experimental data of binary systems composed of CO2 and ionic liquids are studied to predict solubility using a multilayer perceptron. The dataset includes 33 different types of ionic liquids over a wide range of temperatures, pressures, and solubilities. The main objective of this work is to propose a procedure for the prediction of CO2 solubility in ionic liquids by establishing four stages to determine the model parameters: (1) selection of the learning algorithm, (2) optimization of the first hidden layer, (3) optimization of the second hidden layer, and (4) selection of the input combination. In this study, a bound is set on the number of model parameters: the number of model parameters must be less than the amount of predicted data. Eight different learning algorithms with (4,m,n,1)-type hidden two-layer architectures (m = 2, 4, …, 10 and n = 2, 3, …, 10) are studied, and the artificial neural network is trained with three input combinations with three combinations of thermodynamic variables such as temperature (T), pressure (P), critical temperature (Tc), critical pressure, the critical compressibility factor (Zc), and the acentric factor (ω). The results show that the 4-6-8-1 architecture with the input combination T-P-Tc-Pc and the Levenberg–Marquard learning algorithm is a very acceptable and simple model (95 parameters) with the best prediction and a maximum absolute deviation close to 10%.

Novel coal-to-methanol process with near-zero carbon emission: Pulverized coal gasification-integrated green hydrogen process

The coal-to-methanol (CTM) is an important technical route for methanol production. The process suffers from high CO2 emission and low energy efficiency due to the mismatch of H/C (hydrogen-to-carbon) ratio between raw coal and products. Hydrogen production from renewable energy can be introduced into the system to meet the H/C ratio. In this paper, a novel CTM process with near-zero carbon emission has been proposed, the direct CO2 emission is decreased from 1.9 to 0.035 t CO2·t−1 MeOH. The novel process avoids requirement of the water-gas shift unit to reduce the production of CO2 from the source, and a novel acid gas removal process is proposed to remove sour gas while ensuring the reduction of CO2 loss. Compared with traditional CTM, CO2 emission intensity, carbon utilization efficiency and energy efficiency of the novel process are 88.87% lower, 130.77% higher, and 39.64% higher, respectively. The novel process is economically feasible when the H2 price is less than 10.36 CNY·kg−1 H2 and the carbon tax is higher than 223.3 CNY·t−1 CO2. This study will enable both economic and environmental route for methanol production in the future and will facilitate future studies on the integration and management of CTM coupled renewable energy.

Modeling of H2S solubility in ionic liquids using deep learning: A chemical structure-based approach

Hydrogen sulfide (H2S) is a toxic, flammable, corrosive, and acidic gas that can have harmful impacts on the environment. Ionic liquids (ILs) are relatively new solutions that have desirable characteristics such as high thermal and electrochemical stabilities, negligible vapor pressure, non-combustibility, and high solubility, allowing them to be an appropriate choice of liquid solvents in gas removal processes. In this study, deep learning (DL) approaches were utilized to predict the H2S solubility in ionic liquids (ILs). The proposed models include convolutional neural network (CNN), recurrent neural networks (RNNs), deep belief networks (DBN), and deep neural network initialization with decision trees (DJINN). To this end, a large databank in a broad range of pressure and temperature encompassing 1516 data points of H2S solubility in 37 various ILs was used for developing models. In these models, the chemical structure of ILs, temperature, and pressure were considered as the model’s inputs, while H2S solubility was the model’s output. The results reveal that the CNN model provides more accurate, rapid, flexible, and inexpensive estimations for H2S solubility in ILs with an average absolute percent relative error (AAPRE) of 2.92% and a determination coefficient (R2) of 0.99. The results were then compared to those of previously proposed techniques in the literature. According to the results of the sensitivity analysis, it was found that pressure and OH (as substructure) impose the highest positive and the highest negative impacts on the solubility of H2S in ILs, respectively. Also, based on sensitivity analysis, temperature has a reverse effect on the solubility of H2S and with increasing temperature, the H2S solubility decreases. The Taylor diagram illustrated that the CNN approach is very efficient, accurate, and realistic for predicting the solubility of H2S in diverse ILs based on the chemical structure, pressure, and temperature. Finally, trend analysis revealed that the trends of CNN predictions are in great agreement with the measured data of H2S solubility in ILs as a function of pressure. The findings of this work may be used not only to overcome the difficulties of calculating H2S solubility in ILs, but also to develop novel and accurate forecasting algorithms for a large dataset that cover a broad range of temperatures and pressures.

Study of dynamics and mechanism of HCl, SO2, or NO removal by MnO2/Mg–Al layered double hydroxide

The gas exhaust generated by waste incinerators contains toxic acid gases such as HCl, SO2, and NOx, which require appropriate treatment following their release. Although several methods exist for this purpose, they have various drawbacks. Thus, toward the search for a new removal method, the ability of Mg–Al layered double hydroxide (Mg–Al LDH) to eliminate HCl, SO2, and NO gases from simulated exhaust gas was examined. In addition, the impact of the amount of LDH employed was investigated in terms of the toxic gas removal efficiencies and process temperature. Furthermore, the mechanism of removing HCl, SO2, and NO by MnO2/Mg–Al LDH was considered. More specifically, HCl removal proceeded mainly by the reaction of HCl with the CO32− and OH− species present between the Mg-Al LDH layers, while that of SO2 took place through the adsorption of SO2 onto the LDH and MnO2 surfaces. Moreover, NO was removed through the oxidation of NO to NO2 by MnO2, followed by the reaction of NO2 with the CO32− and OH− species present between the Mg–Al LDH layers. These results are expected to help pave the way for the use of Mg–Al LDH to remove toxic acid gases from the gas exhausts of waste incinerators, thereby addressing the various issues related to the use of current technologies.

Sustainability criteria as a game changer in the search for hybrid solvents for CO2 and H2S removal

• Robust multi-criteria screening for CO 2 and H 2 S absorption in water-free solvents. • Polar soft-SAFT validated for a wide range of solvent properties and conditions. • Water-free solvents have a competitive technical edge over aqueous solvents. • Sustainability metrics of water-free solvents calls for greener options. • Holistic solvent evaluation is essential for proper selection. The appearance of hybrid solvents in recent years introduced a potential replacement for aqueous amines for acid gas removal in order to mainly overcome the high energy of regeneration. Yet, the assessment of solvent potentiality remains haphazard with limited information and assessment criteria. In this contribution, we develop and apply a multi-criteria assessment approach built on the use of a molecular-based equation of state, namely, polar soft-SAFT, in combination with sustainability indicators to examine the performance of hybrid solvents for acid gas removal (CO 2 and H 2 S). The first stage of the approach relies on the robust development of the thermodynamic model with available experimental data. Subsequently, with assured fidelity, the model is used in a fully predictive manner to obtain relevant assessment criteria for technical performance evaluation. This is inclusive of standard key performance indicators such as cyclic capacity and energy of regeneration, along with key solvent properties at conditions representative of acid gas removal processes. Additionally, we examine the environmental, health and safety impact of the investigated solvents as a sustainability criteria to select them. This framework has been applied for the first time to six solvents for acid gas removal, including the benchmark solvents aqueous monoethanolamine (MEA) and aqueous diethanolamine (DEA), along with hybrid solvents formulated from chemical solvents such as MEA, or DEA, with physical co-solvents including N-methyl-2-pyrrolidone (NMP), or sulfolane (SFL). The results of the multi-criteria assessment demonstrate that among the six solvents investigated in this work, the overall best performer remains to be the benchmark aqueous MEA. Results also indicate the potentiality of MEA + NMP hybrid solvent in terms of an acceptable compromise between reduced absorption capability and reduced energy of regeneration, compared to aqueous MEA; however, the hybrid solvents fail when applying the sustainability metrics. This work clearly indicates that potential solvents for acid gas removal should be examined following a holistic approach, inclusive of their technical performance and environmental footprint.

New Solvents for CO2 and H2S Removal from Gaseous Streams

Acid gas removal from gaseous streams such as flue gas, natural gas and biogas is mainly performed by chemical absorption with amines, but the process is highly energy intensive and can generate emissions of harmful compounds to the atmosphere. Considering the emerging interest in carbon capture, mainly associated with increasing environmental concerns, there is much current effort to develop innovative solvents able to lower the energy and environmental impact of the acid gas removal processes. To be competitive, the new blends must show a CO2 uptake capacity comparable to the one of the traditional MEA benchmark solution. In this work, a review of the state of the art of attractive solvents alternative to the traditional MEA amine blend for acid gas removal is presented. These novel solvents are classified into three main classes: biphasic blends—involving the formation of two liquid phases, water-lean solvents and green solvents. For each solvent, the peculiar features, the level of technological development and the main expected pros and cons are discussed. At the end, a summary on the most promising perspectives and on the major limitations is provided.

Towards process, environment and economic based criteria for multi-objective optimization of industrial acid gas removal process

Acid gas removal is an important process to meet environmental regulations and protect machinery and pipelines. Non-dominated Sorting Genetic Algorithm-II (NSGA-II) is used to optimize the process considering economic and environmental objectives. The optimization was carried out using excel-based multi-objective optimization (EMOO). Acid gas removal process using dimethyl ethers of polyethylene glycol is optimized considering profit, global warming potential and Human Toxicity. At the same time, the amount of sulfide removed from the gas and that of methane gas recovered also need to be maximized. The trade-offs are investigated by reviewing the effects of the process variables on the objectives. Two-objective cases are considered and the Pareto optimal solutions are obtained. A comparison and a three-objective case was carried out. Two-objective optimization gave better results in all the cases but the three-objective solutions would be more practical, given that industries generally operate around more than two objectives.

Ionic liquid screening for CO2 capture and H2S removal from gases: The syngas purification case

A systematic ionic liquid (IL) screening approach for acid gas removal processes was developed by taking into account a wide range of process performance-determining factors. Selective and non-selective absorption of CO2 and H2S from syngas in conceptual low- and high-temperature processes was investigated to explore the optimal solvents, among 5980 ILs, for each process. Making use of the COSMO-RS and other suitable IL-systems predictive models, the process thermal efficiency (absorption enthalpy and sensible heat) and absorption–desorption working capacity were addressed in the selection of IL candidates along with the primary factors such as solubilities and selectivities. Meanwhile, the COSMO-RS predicted results were validated, and σ-profile and σ-potential of CO2, H2S, H2, CO and the featured ILs were analyzed to provide theoretical insights into intermolecular interactions between gas and IL. The same IL screening method can be extended to CO2 capture and H2S removal from natural gas, biogas, and other sources.

Combined energy consumption and CO2 capture management: Improved acid gas removal process integrated with CO2 liquefaction

Energy management is always facing a trade-off among the constrains of efficiency, energy consumption and CO2 capture rate. For example, the Rectisol wash is a promising and efficient purification process for acid gas removal. However, this process has the problems of high cold energy consumption and low CO2 capture rate. To solve the problems, this paper proposed an improved integrated Rectisol (Int-Rectisol) process with CO2 partial liquefaction. This paper demonstrated how to comprehensively reduce the energy consumption by liquefying part of the CO2 from the treated syngas before absorption. The decreased CO2 concentration in the syngas consequently reduced the methanol solvent consumption and regeneration in the process. Meanwhile, less solvent circulation and regeneration further reduced the energy consumption of the overall process. Process modeling and simulation was conducted in Aspen Plus. The techno-economic performance was then evaluated and compared with the conventional process. The results showed that the solvent circulation in the Int-Rectisol process reduced by 46.5% and the energy consumption decreased from 389.1 MJ to 204.3 MJ for capturing 1 kg of CO2. Meanwhile, the CO2 capture rate also increased from 46.7% to 85%. The exergy analysis showed that the exergy destruction in the Int-Rectisol was 20.95 MW less than the Rectisol process. As for the economic benefit, the Int-Rectisol process reduced the total capital investment and the total product cost by 12.4% and 8.7%, respectively.

Multilevel screening of ionic liquid absorbents for simultaneous removal of CO2 and H2S from natural gas

For the selection of practically attractive ionic liquids (ILs) as absorbents for simultaneous CO2 and H2S removal from natural gas (NG), a multilevel screening method combining Henry′s law constant (H) and vapor–liquid equilibria (VLE) based prediction of thermodynamic properties, physical properties estimation, and process simulation is presented. To begin with, an H-based Absorption-Selectivity-Desorption index (ASDI) is employed to prescreen potential ILs that have promising target properties at infinite dilution condition. Following this, their simultaneous CO2 and H2S removal performances are further evaluated from the VLE of {IL + NG} systems at the specific composition of interest. After the thermodynamic screening, key physical properties of the obtained ILs are estimated by group contribution methods and the IL stability is assessed empirically to find out solvents suitable for practical application. Finally, continuous acidic gas removal processes based on the remaining ILs are simulated and compared by Aspen Plus, thereby identifying the best ILs from the process point of view.

Study on the Oxidant Effect for Nitrogen Trifluoride Abatement by Using a 2.45 GHz Microwave Plasma Torch

Among the fluorinated compounds (FCs) used in the semiconductor and display industries, NF3 gas is a popular gas for etching processes, and due to the high global warming potential (GWP), emission regulations are becoming more stringent. In the semiconductor process, a point of use (POU) scrubber is attached to the rear stage to remove fluorinated compounds. The field industry continues to increase degassing flow rates and strives to reduce energy consumption for degassing. In order to save energy, researchers have reduced the energy consumption by using a reverse vortex reactor (RVR) and have analyzed the removal efficiency according to the oxidant by using oxygen and steam as additional gases in the gas removal process. Removal rates were measured using Fourier transform infrared (FTIR) spectroscopy and detailed experiments on nitrogen trifluoride (NF3) reduction were performed in terms of the destruction and removal efficiency (DRE). In order to measure the decomposition rate, nitrogen was injected at 250 SLM and NF3 was 1.25 SLM, and the experiment was performed at a concentration of 5,000 ppm. Oxygen and steam were injected as oxidants, and an injection amount was 12 SLM with steam at 2 g/min. In the case of steam injection, there was a difference in the decomposition rate differed according to the injection port, and when injected into the view port (front part of the reactor), the decomposition rates were 90% at 6 kW and more than 98% at 7 kW. When oxygen and steam were used as oxidants, the energy consumption was reduced by 8.3% and 21.4%, respectively, depending on the location at while steam was injected.