Performance evaluation of discharge plasma process for gaseous pollutant removal

Performance evaluation of discharge plasma process for gaseous pollutant removal

Journal of Electrostatics 55 (2002) 25–41 Performance evaluation of discharge plasma process for gaseous pollutant removal Hyun Ha Kima, Graciela Pri...

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Journal of Electrostatics 55 (2002) 25–41

Performance evaluation of discharge plasma process for gaseous pollutant removal Hyun Ha Kima, Graciela Prietob, Kazunori Takashimaa, Shinji Katsuraa, Akira Mizunoa,* a

Department of Ecological Engineering, Toyohashi University of Technology, Tempaku-cho, Toyohashi 441-8580, Japan b Department of Chemical Engineering, Universidad Nacional De Tucuman, AV. Independencia 1800, 4000 San Miguel De Tucuman, Argentina Received 30 October 1999; received in revised form 3 August 2001; accepted 10 August 2001

Abstract Performance evaluation of non-thermal plasma (NTP) process has been carried out using NO as a model gas. The experimental results were evaluated using a simple model, which relates the change of NO concentration with specific input energy (SIE) (kJ/Nm3). The results were also evaluated using the well-known parameters of energy cost, energy yield (EY) and Gvalue. As the SIE increased, the EY and the G-value decreased while the energy cost increased even under a given reaction condition. Based on these parameters best results were found in the smaller SIE region where the NO removal is poor. An approach has been developed to use the constant (hereafter referred to as energy constant kE (Nm3/kJ)) in a simple model to evaluate the system performance of non-thermal plasma reactor instead of conventional parameters. Unlike the three conventional parameters, the energy constant was not influenced by the SIE level under the range tested in the present work. The effects of various reaction conditions, such as initial concentration of NO, temperature, additive on the energy constant kE have been investigated. The comparison of kE values for different NO concentrations clearly showed that the NTP process is more efficient in treating gaseous pollutant in low concentration. The increase of NO concentration exponentially decreased the energy constant. Gas temperature showed a similar effect. The significance of the influence of the tested parameters on the energy constant kE has been found to be of the order of the gas composition, the initial concentration, and the gas temperature. Among the additives tested in this study, ethylene made the energy constant kE to a maximum value of 242  103. r 2002 Elsevier Science B.V. All rights reserved. Keywords: Non-thermal plasma; Pulse corona discharge; Scaling rule; Energy constant; Nitric oxide

*Corresponding author. 0304-3886/02/$ - see front matter r 2002 Elsevier Science B.V. All rights reserved. PII: S 0 3 0 4 - 3 8 8 6 ( 0 1 ) 0 0 1 8 2 - 6


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1. Introduction Non-thermal plasma (NTP) process is receiving attention for the removal of nitrogen oxides [1–4], sulfur dioxide [4,5], volatile organic compounds [6–8] and dioxins [9,10] from the flue gas streams of atmospheric pressure. NTP is the state where the energy of electron exists far above the ions and neutral molecules. Many published works are consistent with the viewpoint that the primary advantage of NTP process is the selective transfer of electrical energy to electrons instead of driving ions or gas heating [11,12]. This highly non-equilibrium state can be implemented by either an electrical corona discharge or ionizing irradiation. If one focuses only on the production of electrons, the NTP process is highly effective. However, the NTP process consists of many elementary processes such as ionization, excitation, dissociation, charge transfer, attachment, recombination (radical–radical, electron–ion, ion–ion), radical-neutral reactions, etc. [13]. These can be broadly divided into two parts of primary process and secondary process, as shown schematically in Fig. 1, based on the time-scale of streamer propagation. As one can see from Fig. 1 chemical reactions in the NTP process are due to not only radical reactions but also to ionic reaction. The primary process includes ionization, excitation, dissociation and charge transfer. The typical time-scale for the primary processes is around B108 s [14]. The main species resulting from the primary process include electrons, radicals, ions of both negative and positive polarity, and

Fig. 1. Time-scale of elementary processes in non-thermal plasma process.

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excited molecules. The efficiency of the primary process is highly dependent on the energization method such as pulse, DC+pulse, AC, DC+AC, and electron-beam. In the case of pulse corona discharge, several other parameters of full width at half maximum (FWHM), polarity of voltage, pulse rising time also have a great influence on the primary process. The secondary process is the subsequent chemical reactions involving the primary products of electrons, radicals, excited molecules, and ions. Some radical species such as O3 and HO2 are also generated through radical– neutrals recombination in the secondary process. The secondary process is usually completed within approximately 103 s, leaving the neutralization and the thermal reaction in De–NOx/SO2 processes out of consideration. In treating gaseous pollutants in ppmv (parts per million by volume) range, it is hard to expect that a direct decomposition of dilute pollutant through collisions with energetic electrons play an important role. The majority of the electron energy is transferred to the dominant gas molecules of nitrogen and oxygen through many inelastic collisions and then leads to the formation of radicals. The decomposition of gaseous pollutants starts to occur only after the formation of radicals is initiated. As a result, the total efficiency ZT of an NTP process will be the product of the efficiencies of the primary process (ZPrimary ) and the chemical reactions in the secondary process (ZSecondary ): ZT ¼ ZPrimary ZSecondary :


When it comes to industrial use of NTP process, the question as to what are the key parameters in the system design arises. However, there have been few parametric studies on this subject [15]. Theoretical approaches of the non-thermal plasma process using plasma physical/chemical modeling have been developed not only to obtain a detailed removal mechanism but also to evaluate how much the NTP process is effective [11,16]. In many previous works, the energy cost (EC; eV per removed molecule), the G-value (removed molecules per 100 eV input) and the energy yield (EY; g-removed per kWh input) have been used for the performance evaluation of the discharge plasma systems. The major problem one encounters when evaluating the system performance of NTP process using these parameters is that the values vary with the change of SIE even under a given reaction conditions as shown later. One of the first approaches to explain the experimental result using an empirical model was reported by Slater and Douglas-Hamilton, who investigated the decomposition of vinyl chloride in an electron-beam reactor [17]. Nickelsen et al. reported a more simple formula for the treatment of organic compounds in an aqueous solution using a low-energy electron beam reactor [18]. Rosocha et al. [19] and Hosokawa [20] reported simple models for the removal of VOCs and odors in the dielectric barrier discharge and pulsed corona discharge. Vitale et al. carried out further investigations for the removal of TCA and TCE in an e-beam plasma reactor based on Rosocha’s formula [21]. They also proposed that the rate constant should be corrected according to the initial concentration. Masuda et al. [22] and Yan et al. [23] reported empirical correlations between the NO removal and the input energy. In an earlier study by Tokunaga et al., a dose-related equation for NO removal was


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proposed [24]. However, these equations were used to describe the experimental results that were obtained under limited reaction conditions. These semi-empirical approaches treat the behavior of pollutants as a function of the specific input energy (SIE; kJ/Nm3, Wh/Nm3, kGy, and Mrad) dissipated in the plasma reactors. The main purpose of this work is to introduce a new parameter to evaluate the system performance of NTP process. We focused on the chemical reaction efficiency under positive pulse corona discharge and the effect of energization methods was not included in this study. The experimental results were evaluated based on the conventional parameters of energy cost, energy yield, and G-value. Problems related to these parameters will be presented. Under tested conditions, in this study the results could be well explained using a simple model. An attempt was made to use the energy constant kE as an evaluating parameter of NTP processes. The effects of various reaction conditions such as temperature, initial concentration, type of additive will also be presented.

2. Model for NOx removal Removal of nitrogen oxides from combustion flue gas has been one of the important research subjects of the NTP process. The typical reaction pathways of NOx in the NTP process are summarized in Fig. 2. Initially NO is oxidized to NO2, and then further oxidized to HNO3 by the OH radicals, while part of the NO2 is converted to NO due to back reaction by the O radicals. Nitrous acid (HNO2) is easily decomposed to NO through photolysis or surface reaction. These back reactions play an important role as radicals sink, resulting in a low energy efficiency of the NTP processes. The reduction of NO to N2 by N radical is also possible under low oxygen content. In real exhaust gases, where the oxygen content is usually larger than 5%, the reduction of NOx into N2 is negligible [23,24]. Although the solubility

Fig. 2. Typical reaction pathways of NOx in a non-thermal plasma reactor [24–27].

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of NO2 into water is small compared to that of its acid species (HNO2, HNO3), it could occur at high water content in the gas stream. The presence of these back reactions and the heterogeneous reactions make the modeling of plasma chemical reactions difficult. NO2 converted from NO could be effectively removed when the plasma reactor is combined with a chemical scrubber or catalyst. In many previous studies, the EY (g/kWh), the G-value (molecules/100 eV) or the EC (eV/molecule) have been used to evaluate the system performance of NTP process [2–4,16,23,25,26]. These parameters can be expressed as a function of the SIE (kJ/Nm3, energy input to the unit gas volume) and the amount of gas molecules removed (D½C in ppm) as shown in the Eqs. (2)–(4). Energy cost ¼

G-value ¼

kJ=Nm3 250 D½C

D½C kJ=Nm3

Energy yield ¼


D½Cm kJ=Nm3



ðmolecules=100 eVÞ;





where m is the molecular weight of a gas compound. The factors of 250, 0.4 and 0.15 in the equations are the conversion factors at 201C and 1 atm. As one can see in Eqs. (2)–(4) the nature of these parameters will be determined depending on whether the removed amount is linearly proportional to the SIE or not. If the removed amount of gas molecule is a linear function of an SIE, then the values of G-value, EC, and EY will be constant for a given reaction condition. In most cases, however, these trends are far from a linear relation as found in many papers [1,4,5,17,18,29,30]. This has motivated us to develop more reasonable parameters to explain the experimental results obtained at various reaction conditions. Previous studies on the behavior of gaseous pollutants in NTP reactors are summarized in Table 1. The common factor in all the models is the specific input energy (Mrad, kJ/Nm3, J/l or Wh/m3), which means that the SIE is the most important factor in determining the behavior of pollutants in a plasma reactor. As shown in the previous works [16,22,26,28], NO removal is a function of the SIE and NO concentration decreased exponentially with increasing SIE. This observation is sufficient to establish a general equation for the NO removal as expressed in Eq. (5). d½NO ¼ kE ½NO; dPSIE


where [NO], PSIE and kE represent the NO concentration (ppm), the specific input energy (kJ/Nm3), and the energy constant (Nm3/kJ), respectively. The integration of Eq. (5) gives ln

½NO ¼ kE PSIE : ½NO0



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Table 1 Models for the gas removal in the non-thermal plasma reactorsa Target gas

Equation mD=½V0


½V ¼ ½V0 e

  E ½X ¼ ½X0 exp  b


Reactor type




Silent discharge



t S þ C ¼ C0 exp T QK

Surface discharge



ZNO ¼ 1  exp½kðP=QÞLð1=CNO Þð1=DÞ

Pulsed corona



pffiffiffiffi DNO ¼ k E

Radical injection


a Note: D ¼ Str =m; m ¼ 0:0367G=r; P=input energy, Q=flow rate, E=energy density (P=Q), b=exponential-folding factor, D=diameter, ½V; ½X and C represent concentration, N=hourly circulation, k=constant, DNO=removed amount of NO in ppm.

In the semi-log plot of Eq. (6), the slope of the linear line is equal to the energy constant kE : Therefore, the removal efficiency of NO is then given as Z¼

½NO0  ½NO ¼ 1  expðkE PSIE Þ: ½NO0


The energy constant kE is a function of many parameters such as temperature, gas composition, additive, etc. as shown below: kE-ho ¼ f ðT; Cin ; A; etc:Þ;


where kE-ho ; is the energy constant of homogeneous reactions, T the temperature (1C), Cin the initial concentration and A the additive. For heterogeneous reactions, other characteristics, such as the nature of the catalyst, specific surface area (m2/g), droplet size etc., should also be considered. Although this approach does not provide precise information about the detailed reaction mechanism, useful information on scale-up capability can be derived. In addition, the energy constant kE can be used for the comparison of various experimental results.

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3. Experimental system and method The experimental setup used in this study is shown in Fig. 3. The plasma reactor used in this study consists of a glass tube (29 mm diameter, 150 mm length), a stainless steal wire (0.3 mm diameter) and aluminum foil. We used two reactors connected in parallel. The plasma reactor was set in an oven to control the temperature condition. The test gas was prepared by mixing each gas component from gas cylinders. The gas flow rate was set with mass flow controllers (STEC Inc. SEC-400MK3) at 4 SLPM (201C, 1 atm). The corresponding gas residence time in the plasma reactor was 3 s. For the additive injection, a micro feeder was used for H2O2, methanol and HCHO. These were evaporated using a ribbon heater before entering the plasma reactor. Ethylene (C2H4) was prepared from a gas cylinder. The flow rate of ethylene was determined with a needle valve and a bubble flow meter. The NO concentration was varied from 100 to 400 ppm. The contents of O2 and CO2 were kept constant at 10% throughout this study. Positive pulsed corona has been used for gas energization because there is a general agreement on its better performance than negative corona. A pulsed high

Fig. 3. Schematic diagram of the experimental setup.


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voltage generator with a rotary spark gap (RSG) switch was used that could produce fast rising (about 20 ns) pulsed high voltage up to 30 kV. The pulse repetition frequency was in the range of 250–370 Hz. Waveforms of the voltage and current were measured using a digital oscilloscope (Tektronix TDS 350) with a voltage divider (Tektronix P6015) and a current probe (Tektronix P6021). The energy per each pulse was calculated by integrating the product of the pulse voltage and the current waveform. The discharge power was obtained by multiplying the energy per pulse and the pulse repetition frequency and/or by the method reported previously [1]. The concentration of NO/NOx and SOx were determined using a gas analyzer (Horiba, PG-250), which is based on chemiluminescence (NO/NOx) and NDIR (SOx). FT-IR (Bio Rad, FTS-30), GC/FID (Shimadzu, GC-17A) and a gas detection tube (GASTEC) were used in the byproduct analysis.

4. Results and discussion Fig. 4 shows the experimental results of NO removal as a function of the specific input energy (kJ/Nm3) under three different gas compositions. The use of H2O2 enhanced the NO removal due to the production of more radicals, which can react with NO. The presence of SO2 further enhanced the NO removal. In this case, as soon as the injection of H2O2 started, SO2 concentration was rapidly dropped to around less than 100 ppm even without the pulse corona discharge whereas the decrease of NO concentration was not observed. NO removal was only possible under the presence of pulse corona discharge. For three tested conditions, NO removal with respect to the SIE did not show a linear trend. This is consistent with many previous results.

Fig. 4. NO removal under different gas compositions (300 ppm NO). (a) Dry at 501C, (b) 1000 ppm H2O2 at 1001C, (c) 1000 ppm H2O2+500 ppm SO2 at 1001C.

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Fig. 5. Energy cost, G-value and energy yield vs. SIE in NO removal. (Data from Fig. 4).

The data of Fig. 4(c) were replotted in Fig. 5 to show the behavior of the energy yield, the G-value and the EC with respect to the SIE range tested. The values of EY, EC and G-value were changing as the SIE increased even under a fixed reaction condition. The EY and the G-value (G) are decreasing with increasing SIE, while the EC is increasing with SIE. For example, the EY decreases from 80 to 40 g-NO/kWh when the SIE is increased from 10 to 30 kJ/Nm3. The corresponding removal efficiencies were 53% at 10 kJ/Nm3 and 90% at 30 kJ/Nm3. Similar trends were observed for the G-value and the EC. The best results based on these parameters (smaller EC, larger G-value and EY) are found in the small SIE region where the removal rate is low. As also pointed out above the nature of the EC, G-value and EY are determined from the relationship between the removed amount D½C and the SIE. Non-linear relation between the two is the main reason why these parameters are changing with SIE. It should be noted that careful attention must be paid while using the parameters EY, G-value or EC in comparing the performance of a non-thermal plasma process even under a given reaction condition. To arrive at a meaningful conclusion by comparing the EC, EY and G-value from different authors, one should pay attention to the detailed conditions: initial concentration, temperature, gas composition and the SIE level etc. Also shown in Fig. 6 are the semi-logarithm plots of the results shown in Fig. 4 according to Eq. (6). Logarithm NO concentration with respect to the specific input energy fell on a straight line for each condition. The slopes of each straight line correspond to energy constants of each condition. Unlike the three conventional parameters, the energy constant was not influenced by the SIE level up to 60 kJ/Nm3. The calculated energy constants for each conditions were 11.7  103 (Nm3/kJ) for (a), 25.3  103 (Nm3/kJ) for (b) and 77.7  103 (Nm3/kJ) for (c), respectively. In the dry condition, however, the experimental data diverge from the model fit when the specific input energy was larger than around 50 kJ/Nm3. The reduction of NO to N2 by N radical is negligible under the oxygen rich condition [22]. The removal of


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Fig. 6. Semi-logarithm plot of data shown in Fig. 4.

NO proceeds mainly via the reactions with oxygen species (O and O3) in air-like mixtures, leading to the formation of NO2. However, further oxidation pathway to NO3 is very slow and the formation of acid (reaction 11) is prohibited due to the absence of OH radical. As a result, the amount of NO2 keeps increasing as the SIE increases. This back reaction (12) is especially important at dry conditions where further oxidation of NO2 does not occur. NO þ O-NO2 þO2 NO þ O3 -NO2 þO2 NO2 þ OH-HNO3 NO2 þ O-NO þ O2

ðk ¼ 3:0  1011 Þ; ðk ¼ 1:8  1014 Þ; ðk ¼ 1:1  1011 Þ; ðk ¼ 9:7  1012 Þ:

ð9Þ ð10Þ ð11Þ ð12Þ

In the presence of H2O2 a good agreement between the model fit and experimental results was obtained up to 60 kJ/Nm3. In these conditions, further removal paths of NO2 existed and the build-up of NO2 was limited compared to that in the dry condition. The use of H2O2 enhanced the NO removal and the presence of SO2 caused a further enhancement. The energy constant kE with NO–H2O2–SO2 mixture was 3 times larger than that for NO–H2O2 mixture. In Fig. 7, the effect of NO concentrations on the removal efficiency was examined. For both temperature conditions of 501C and 1001C, the removal rates are decreasing with the increase in the NO concentration. For 100 ppm NO, more than 90% of NO removal efficiency was achieved with 36 kJ/Nm3 at 501C and 80% at 1001C. As the NO concentration increased, the removed amount of NO increased at identical SIE. Table 2 summarizes the values of G-value, EY, and EC for an NO concentration in the range of 100–400 ppm. Although the results shown in Table 2 are for a fixed SIE of 36 kJ/Nm3, the dependences of EC, EY and G-value on the SIE were consistent with the results of Fig. 5. As the SIE increased the EC became large,


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Fig. 7. Effect of initial concentrations on removal efficiency: (a) at 501C (b) at 1001C (symbols: ’ 100 ppm, K 200 ppm, m 300 ppm, J 400 ppm).

Table 2 Effect of NO concentration on the G-value, the energy cost (EC) and the energy yield (EY) (SIE was 36 kJ/ Nm3) Conditions

NO concentration 100 (ppm)

200 (ppm)

300 (ppm)

400 (ppm)

At 501C

Removal efficiency EC (eV/molecule) EY (g-NO/kWh) G-value (molecules/100 eV)

92% 97.8 11.5 1.02

55% 81.8 13.8 1.22

36% 78.9 13.5 1.27

29% 77.5 14.5 1.29

At 1001C

Removal efficiency EC (eV/molecule) EY (g-NO/kWh) G-value (molecules/100 eV)

80% 112.5 10.0 0.89

41% 109.7 10.3 0.91

29% 103.4 109 0.97

22% 102.3 11 0.98

whereas the EY and G-value became small. The ECs became large with the increase of NO removal efficiency while the EYs and the G-values decreased. The increase in temperature had adverse effect on all the parameters.


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Fig. 8. Effect of NO concentration on energy constant at various conditions. (a) Without additive at 501C and 1001C, (b) energy constant in the presence of 2000 ppm H2O2 at 1501C.

The effect of varying the NO concentrations on the energy constant is shown in Fig. 8: (a) without additive at 501C and 1001C, (b) energy constant in the presence of 2000 ppm of H2O2 at 1501C. The behavior of NO removal shows a trend similar to that of the dry condition. The broken line in the figure indicates the necessary kE value to achieve 80% removal using 3% (36 kJ/Nm3) of the output power assuming that this system is used in flue gas cleaning of a power plant. This value of 36 kJ/Nm3 is obtained from the following assumptions: gas flow rate of 300,000 Nm3/h for a 100 MW of coal-burning power plant, thus 12 kJ/Nm3 is equal to 1% of the total output power. The removal rate is decreasing with the increase in the NO initial

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concentration, and the relating energy constant decreases exponentially. The change of the energy constant in the H2O2 injection is larger (13.7 times) than that in the dry condition (5.9 times) when the NO concentration is increased from 100 to 400 ppm. Similarly, the temperature increase also reduced the energy constant kE resulting in a low removal rate. An exponential decrease of the energy constant kE was observed with increase of NO concentration and the temperature. The energy required to obtain certain removal efficiency is reduced when the NTP is used at a low temperature and low initial concentration. The relations of kE with the initial NO concentration in the presence of 2000 ppm H2O2 (1501C) and in dry conditions (501C, 1001C) can be expressed in Eqs. (13)–(15): kH2 O2 ¼ 601:7 expð8:85103 Cin Þ

ðR2 ¼ 0:998Þ;


kd50 ¼ 72:36 expð5:76  103  Cin Þ ðR2 ¼ 0:96Þ;


kd100 ¼ 71:47 expð2:47  103  Cin Þ ðR2 ¼ 0:93Þ:


As indicated above, the energy constant kE is affected by the reaction conditions. This influence can be expressed as follows:       qkE qkE qkE dkE ¼ dT þ dCin þ dA: ð16Þ qT Cin ;A qCin T;A qA Cin ;T In designing the pollutant control device, first we should know the gas flow rate and the initial concentration of pollutants and then estimate the initial and operating cost to achieve the related regulations. For example, bio-filter can be a good candidate for the gas cleaning of low concentration. However, in the case of the NTP process, the gas flow rate has a negligible effect as long as the SIE value is maintained identical at lower flow rates condensation, thermal oxidation, or catalytic oxidation can be a cost-effective method. In the case of the NTP process, the effect of flow rate is negligible because the amount of gas removed is mostly determined by the energy transferred to the gas stream (i.e. SIE). In this sense, if we know the relationship between the reaction conditions and the energy constant, we can obtain the energy constant as indicated in Eqs. (13)–(15), and the total energy can be estimated to achieve a certain removal rate. The use of a proper additive can enhance the removal efficiency of NOx removal resulting in low energy consumption. The enhancement of NO removal in terms of the energy constant is shown in Fig. 9, where the concentration of the additives was fixed at 1000 ppm. Among the additives tested in the present study, the highest reactivity was obtained with C2H4 (ethylene) and followed by HCHO (formaldehyde), methanol, H2O2. The energy constant for C2H4 (242  103, Nm3/kJ)) was 20 times larger than that for the dry condition. These results indicate that the gas composition, especially the use of additives, has a significant influence on the energy constant. The formation of byproducts, that causes secondary pollution from the use of additives, should be considered. Although the enhancement becomes large with the


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Fig. 9. Comparison of energy constant for different additives. The concentration of each additives was fixed at 1000 ppm. (300 ppm NO, 1001C).

hydrocarbons of larger carbon number, it will be counterbalanced by a byproduct formation. As reported in a previous paper [31], CH3COOH (acetic acid), ethanol, CO and HCHO are produced from C2H4 after exposure to a pulsed corona discharge. In the case of HCHO, the main byproduct was found to be CO. When methanol was used, HCHO, CO and CH3CHO (acetaldehyde) were detected. Although H2O2 is favored in terms of a byproduct, its reactivity was too small to be of any significance in comparison with other additives tested in this study. The difference in the energization method (AC, DC+AC, DC+, etc.) and the types of plasma reactor were not considered in this study due to the limitation of laboratory test. For a complete evaluation of the NTP process, it is inevitable to consider the efficiency of chemical reaction together with the energy transfer efficiency for producing NTP. These are subjects for our future study. 5. Conclusions In this work, an attempt has been made to find a reasonable parameter to evaluate the NTP process for the removal of gaseous pollutant. Experimental results using NO as a model gas under various conditions have been evaluated using the conventional parameters of EC, G-value, and EY. An empirical approach to explain the behavior of NO in the pulsed discharge plasma reactor has been attempted. The energy constant kE was defined in the model and it was used for comparing the removal performance. The main conclusions derived from the present work are as follows: (1) Conventional parameters of EC, EY and G-value were found to have critical problems because they vary with the operating SIE range. The EY and the Gvalue decreased with the increase of SIE while the EC increased as the SIE increased. Based on these values best results were obtained at smaller SIE region where the removal rates were low.

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(2) At given gas conditions NO removal showed first-order kinetic to the SIE (kJ/ Nm3) and the energy constant was found to be a reasonable parameter as a performance index. Unlike the three conventional parameters, the energy constant was not influenced by the SIE up to around 60 kJ/Nm3 tested in this study. (3) A strong dependence of energy constant kE on the NO concentration, temperature condition and additives has been observed. An exponential decrease of kE value with the increase of temperature and initial concentration was observed. These observations clearly indicate that the NTP process is particularly efficient in treating dilute pollutants at low a temperature condition. (4) Among the additives tested in the present study, ethylene showed the highest effect in terms of the energy constant, followed by HCHO, methanol and H2O2.

Acknowledgements The authors wish to thank Mr. Noguchi and Mr. Nakui of Electric Power Development Co, and Prof. T. Oda and Prof. M. Sadakata at the University of Tokyo, Prof. J.S. Chang of McMaster University and Prof. T. Ohkubo of Oita University for valuable discussions. The authors are also very grateful for the support by the NEDO international joint research program. This work was also partly supported by the Strategic Basic Research of Science and Technology Agency.

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