Article pubs.acs.org/EF
Study on the Variance of N2O Concentration after Air Pollution Prevention Facility in Bituminous Coal-Firing Power Plant Chang-Sang Cho,† Min-Wook Kim,‡ Seong-Min Kang,‡ Yoon-jung Hong,† and Eui-Chan Jeon*,‡ †
Climate Change Research Center, Sejong University, Seoul 143-747, Korea Department of Environment & Energy, Sejong University, Seoul 143-747, Korea
‡
ABSTRACT: This study intends to check the effects of air pollutant prevention facilities in bituminous coal-fired power plants on N2O gas emission concentration. Bituminous coal-fired power plants install and operate air pollution prevention facilities to prevent air pollution. The exhaust gases generated by such coal-fired power plants generally pass through a flue gas denitrification facility for removal of nitrogen oxides, a dust collector for removal of suspended matter, and a flue gas desulfurization facility for removal of sulfur oxides and are emitted through a smokestack. To check the effects of prevention facilities on N2O emission concentrations, sampling is necessary at the front end and rear end of each prevention facility. Exhaust gases were collected from the front and rear ends of the flue gas denitrification facility (SCR), the rear end of the electric dust collector (EP), and the measurement hole on the smokestack to analyze the concentrations of the gases. According to the results, it was identified where N2O emission concentrations were affected by air pollution prevention facilities. In which air pollutant prevention facilities these differences occurred was analyzed. N2O emission concentration decreased after flue gases passed the flue gas desulfurization facility (FGD) in all three power plants. The phenomenon of reduction of N2O emission concentrations by bituminous coal-fired power plant FGD is judged attributable to the effect of CaCO3 used in the FGD.
1. INTRODUCTION Global warming causes higher air temperatures and warmer oceans, which contribute to sea level rise by melting of glaciers and ice caps. Due to global warming, the mean temperature of earth has risen by 0.85 °C (0.65−1.06 °C), for the past 133 years (from 1880 to 2012), and the sea level has risen by 19 cm (17−21 cm) from 1902 to 2010. Global warming is mainly caused by excess greenhouse gas (GHG) emissions, typically represented by carbon dioxide (CO2), and the level of global warming is approximately proportional to CO2 emissions.1 Atmospheric CO2 concentrations prior to the industrial revolution were about 290 ppm,2 while the figure has steadily increased since then and reached 395 ppm by 2014, corresponding to a 40% increase.3 This increase was found to be caused mostly by human activity.4 If no action is taken to reduce the greenhouse gas (GHG) emissions, continued emissions will cause the mean temperature of the earth to further rise 3.7 °C by the end of the 21st century (2081−2100), and average sea level rise is predicted as 63 cm by 2100 (based on RES 8.5, IPCC, 2014). To slow this process, the international society has established plans to reduce GHG emissions by encouraging individual countries to take action. For these plans to be successful, the first step should be an accurate quantification and documentation of GHG emissions to develop comprehensive emission inventories. The IPCC (Intergovernmental Panel on Climate Change) has published a guideline for calculating the national GHG emissions and suggests a default value of the emission factors, which has become an important standard for the calculation of GHG. However, for more accurate calculations that reflect the characteristics of each country, the application of countryspecific emission factors is recommended.5 ‘Country-specific emission factors have been developed and used in many developed countries. And, in the “GHG and energy © 2017 American Chemical Society
target management scheme” developed by the Korean government, CO2 emissions from the power generation sector were calculated using national emission factors and plant-specific emission factors. However, CH4 and N2O emissions were calculated by applying the basic emission factors from the IPCC Guidelines.6 Country-specific and plant-specific emission factors should also be developed for CH4 and N2O in the future. CO2 emissions from the power generation sector depend on the carbon content of the fuel. However, the generation mechanisms of CH4 and N2O are not clear, and their emission characteristics vary depending on the type of fuel, carbon or nitrogen content of the fuel, conditions of combustion, and existence of air pollution control equipment. Air pollution control technologies such as selective catalytic reduction (SCR) and selective noncatalytic reduction (SNCR) for the removal of nitrogen oxides were found to partially emit N2O through the oxidation−reduction reaction with the catalysts.7−10 In this study, the influence of the air pollution control equipment in bituminous coal power plants on N 2 O concentrations will be investigated. Field surveys in bituminous coal power plants in Korea were conducted to collect the exhaust gas from the measurement holes in the front and rear ends, and stacks. The N2O concentration analysis was conducted in the laboratory thereafter. N2O concentrations at the front and rear ends of the control equipment were compared, and the influence of the air pollution control equipment on the N2O concentration was determined through statistical analysis. Received: November 18, 2016 Revised: March 3, 2017 Published: March 13, 2017 4173
DOI: 10.1021/acs.energyfuels.6b03014 Energy Fuels 2017, 31, 4173−4178
Article
Energy & Fuels Table 1. Subject Facilities and Sampling Period site
fuel type
air pollution prevention facility
sampling period
plant A
bituminous coal
SCR, EP, FGD
plant B
bituminous coal
SCR, EP, FGD
plant C
bituminous coal
SCR, EP, FGD
first, Jun. 2−4, 2015 second, Aug. 4−6, 2015 third, Oct. 20−22, 2015 first, Jun. 15−17, 2015 second, Aug. 10−12, 2015 third, Oct. 27−29, 2015 first, Jul. 21−23, 2015 second, Sep. 8−10, 2015 third, Nov. 3−5, 2015
Figure 1. Sampling point of air pollution prevention facility.
2. RESEARCH METHOD
Table 2. Analytical Condition of GC-ECD for N2O
2.1. Designation of Subject Facilities and Sampling Period. In this study, the targets for the field survey are three power plants in Korea, which use pulverized bituminous coal combustion boilers. These power plants use SCR as the flue gas denitrator, electric precipitator (EP) as the suspended solid remover, and flue gas desulfurizer (FGD) using limestone. The field surveys were conducted 3 times for 3 days at each power plant, as shown in Table 1. During the field survey, two or three samples were taken from the front and rear ends of the air pollution control equipment 2.2. Sampling Method. In coal power plants, air pollution control systems are installed and used to remove nitrogen oxides, sulfur oxides, debris, and other pollutants. The exhaust gas emitted from these power plants generally passes through the flue gas denitrator for nitrogen oxides removal, EP for suspended solids removal, and FGD for sulfur oxides removal and is emitted through the stacks. Measuring the influence of the equipment on non-CO2 gas concentrations requires collecting samples from both the front and rear ends of the control equipment. However, access to these spots is limited due to safety issues. Therefore, in this study, as shown in Figure 1, the measurement holes of the stacks, which are the front and rear ends of the SCR, the rear end of EP, and the rear end of FGD, were designated as the spots for collecting the exhaust gas. The collected gases were analyzed in the laboratory, and the analyzed data were verified for normality. The influence of the control equipment on N2O concentrations was detected by comparing two population means. 2.3. N2O Concentration Analyzing Method. 2.3.1. Analysis of GC-ECD for N2O Concentration. N2O concentrations were analyzed by GC-ECD. The N2O analysis used 1 and 3 m stainless columns with a 1/8 in. diameter packed with a Porapak Q (80/100) column. The flow rate of the carrier gas was 20 mL/min, while the temperatures of the sample injector and the oven were set as 120 and 70 °C, respectively. The ECD (electron capture detector) was used as the detector, and 10-port, sixport, and four-port gas switching valves were used for removing oxygen and moisture from the gas samples. The detector’s datum temperature was set as 320 °C. The GC-ECD’s conditions for the analysis of N2O are shown in Table 2. For the GHG analysis, the calibration curve concentrations of N2O were fitted to determine the concentrations. In order to draw the calibration curves, concentrations of N2O were set as 1.0, 3.4, 5.1, and
GC/ECD column carrier gas flow temperature oven injector detector detector range
Parapack Q 80/100 Mesh N2 (99.999%) 20 mL/min 70 °C 120 °C 320 °C 0
10.3 ppm, in standard conditions. The fitted results showed an excellent linearity, with R2 = 0.9992, as shown in Figure 2. 2.3.2. Repeatability Test for N2O Concentration. The repeatability standard deviation of N2O was determined by repeating the measurements three times. Using the results of these measurements, the relative standard error (RSE) was evaluated. The standard error is determined by the variability of population and sample sizes and is calculated by dividing the standard deviation by the square root of the number of samples. As shown in Table 3, the standard deviation of N2O was 571.26, standard error was 255.48, and RSE was 0.745%. The evaluation of repeatability showed that the RSE of N2O was below 1%. This is even lower than the reproducibility range, 3%, which is suggested by ISO 11564:1998, proving the excellency of the fit. 2.3.3. Method Detection Limit for N2O Concentration. The minimum detectable limit (MDL) for this study refers to the minimum amount which can be detected and does not need to be quantified. The minimum detectable limit can generally be separated into the instrument detection limit (IDL), when the procedure includes the direct injection of the sample into an instrument, and the method detection limit (MDL), when the pretreatment and all other analysis steps are included. The minimum detectable limit includes the following: (1) a method based on visual evaluation; (2) a method based on the signal-to-noise ratio; and (3) a method based on the standard deviation of the reaction and gradient of the calibration curve.11 In this study, at least seven samples with detectable concentrations were analyzed. The standard deviation of each sample and the t-value of 3.143 with n − 1 degrees of freedom (the t-value at the degree of 4174
DOI: 10.1021/acs.energyfuels.6b03014 Energy Fuels 2017, 31, 4173−4178
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Figure 2. Calibration curve by N2O standard. determined. If the air pollution control device does not have any effect on N2O concentrations, then mean concentrations at the front and rear ends will be the same. Otherwise, the concentrations between the front and the rear ends will be different. The flowchart of the statistical analysis of the influence of the control equipment of the bituminous coal power plants on the GHG emissions is shown in Figure 3. For the independent mean test of the rear end
Table 3. Results of Repeatability Test for N2O N2O area first second third average SD SE RSE (%)
33,663 34,500 34,755 34,306 571.26 255.48 0.745
freedom is 6 at the reliability of 98%) are multiplied. This method of calculating the detection limit is constantly used in many experimental methods published by the American Public Health Association (APHA), American Water Works Association (AWWA), and American Society for Testing and Materials (ASTM).11 The minimum detectable limit of N2O was calculated as 40.06 ppb by analyzing 1 ppm of N2O standard gas seven times (Table 4). Since N2O
Table 4. Results of Method Detection Limit for N2O N2O concentration peak area 1 2 3 4 5 6 7 mean SD SD × 3.14 MDL
1.00 ppm 7,163 7,105 7,161 7,024 7,053 7,262 7,078 7,107 81 255 40.06 ppb
Figure 3. Diagram of statistical analysis.
concentrations of the equipment, the normality should first be verified. If the data are normally distributed, then one-way ANOVA is conducted to verify the difference between the three spots (rear ends). If the data are not normally distributed, then the Kruskal−Wallis H. test, a nonparametric test for comparing more than three nonparametric groups, should be conducted. If there are no concentration differences between the rear ends, it can be concluded that “the N2O concentration of bituminous coal power plant is not influenced by the air pollution prevention facility.” General posthoc testing including Tukey, Duncan, LSD, Bonferronil, and Scheffe, which compares two groups, as well as Dunnet which compares the mean of single controlled groups with the means of the other groups, is also conducted. Since the exhaust gas passes through the control equipment, the comparison of N2O concentrations between the front and rear ends of the equipment would determine which equipment is most responsible for N2O emissions.
concentrations emitted by the power plant were above 1 ppm, this minimum detectable limit was suitable for measuring N2O concentrations in the exhaust gas emitted from the power plants. 2.3.4. Statistic Analysis Methods of Effect of N2O Concentration by Air Pollution Prevention Facility. In the investigation of the changes in N2O concentrations affected by the air pollution control equipment, equipment was assumed to be independent of each other. As shown in Figure 1, the differences in N2O concentrations between the entrance and the rear end of the equipment (SCR, EP, and FGD) will be 4175
DOI: 10.1021/acs.energyfuels.6b03014 Energy Fuels 2017, 31, 4173−4178
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3. RESEARCH RESULTS 3.1. Result of N2O Concentration before and after Air Pollution Prevention Facility. The samples collected from the front and rear ends of the air pollution control equipment in the target power plants were analyzed in the laboratory, and the results are shown in Table 5. N2O concentrations at the front and
power plants decreased by 2.24, 0.62, and 0.64 ppm, respectively. N2O concentrations at the rear end of the FGD showed the largest decrease for each power plant. 3.2. Result of Normality Test of N2O Concentration before and after Air Pollution Prevention Facility. To confirm the statistical significance of N2O concentration differences between the front and rear ends of equipment, first, the normality of the concentration data should be verified. The statistical analysis is typically based on the assumption of normality. If the data are not normally distributed, then a nonparametric statistical analysis should be conducted. Normality test results from the SPSS statistical computation software are shown in Table 6. The N2O concentration distribution at the front end of the SCR showed a p-value below 0.05 suggesting a non-normal distribution, while N2O concentration data at the rear end were normally distributed with a p-value above 0.05. The data at the rear ends of the EP and FGD were also normally distributed while the distribution at the rear end of the EP from power plant B was non-normal. The rest of the data were normally distributed in power plant C. 3.3. Result of Kruskal−Wallis Test for N2O Concentration after Air Pollution Prevention Facility. Kruskal− Wallis H test, a nonparametric statistical test, was applied to compare the groups of data. The Kruskal−Wallis H test is a ranksum test where the data are first ranked and then ranks are decided to obtain the rank sum of each group. If there are no differences between the means of the groups, the rank sum is also bound to be similar. The rank sum shows differences, if there are differences between the group means. During the process, the original values of the data are not used; only the ranks are used in the statistical analysis. The results of the Kruskal−Wallis H test are shown in Table 7. The results of power plant A show that the χ2 value of the N2O concentration was 18.662 and p-value was 0.0000, which is below 0.05 (α = 5%), so the null hypothesis is rejected. Therefore, the mean N2O concentration at the control equipment in power plant A has at least one different mean value. The Kruskal−Wallis H test results for power plants B and C showed that the p-values were also below 0.05. The χ2 of the N2O concentration at power plant C was 20.501. In summary, the Kruskal−Wallis H test results of N2O concentrations at the rear end of the air pollution control equipment in all power plants showed that N2O concentrations are influenced by the control equipment.
Table 5. N2O Concentration before and after Air Pollution Prevention Facility facilities
point
N2O concentration (ppm)
n
power plant A
SCR IN SCR OUT difference SCR IN SCR OUT difference SCR IN SCR OUT difference EP IN EP OUT difference EP IN EP OUT difference EP IN EP OUT difference FGD IN FGD OUT difference FGD IN FGD OUT difference FGD IN FGD OUT difference
3.02 3.37 +0.35 1.35 1.61 +0.26 3.27 3.35 +0.08 3.37 3.10 −0.27 1.61 1.14 −0.47 3.35 2.89 −0.46 3.10 0.86 −2.24 1.14 0.62 −0.52 2.89 0.64 −2.26
10 10
power plant B
power plant C
power plant A
power plant B
power plant C
power plant A
power plant B
power plant C
9 9 9 9 10 10 9 9 9 9 p 10 10 9 9 9 9
rear ends of the SCR in power plants A, B, and C increased by 0.35, 0.26, and 0.08 ppm, respectively. N2O concentrations at the front and rear ends of the EP in power plants A, B, and C decreased by 0.27, 0.47, and 0.46 ppm, respectively. N2O concentrations at the front and rear end of the FGD in three
Table 6. Result of Normality Test for N2O Concentration before and after Air Pollution Prevention Facility Kolmogorov−Smirnov power plant A
power plant B
power plant C
a
Shapiro−Wilk
sampling point
statistic
df
sig.a
statistic
df
sig.
SCR IN N2O SCR OUT N2O EP OUT N2O FGD OUT N2O SCR IN N2O SCR OUT N2O EP OUT N2O FGD OUT N2O SCR IN N2O SCR OUT N2O EP OUT N2O FGD OUT N2O
0.310 0.239 0.255 0.252 0.268 0.243 0.225 0.139 0.256 0.222 0.195 0.201
10 10 10 10 9 9 9 9 9 9 9 9
0.007 0.110 0.063 0.072 0.061 0.133 0.200 0.200 0.092 0.200 0.200 0.200
0.790 0.900 0.827 0.887 0.824 0.904 0.816 0.954 0.866 0.906 0.934 0.908
10 10 10 10 9 9 9 9 9 9 9 9
0.011 0.220 0.031 0.158 0.038 0.278 0.031 0.737 0.112 0.290 0.519 0.305
Significance probabillity. 4176
DOI: 10.1021/acs.energyfuels.6b03014 Energy Fuels 2017, 31, 4173−4178
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Paired comparisons of N2O concentrations at the front and rear ends of both the SCR and EP in power plant B showed that the p-value is bigger than 0.05, suggesting that the concentrations at the front and rear ends were the same. The p-value for the SCR was 0.059. If the level of significance was set as 0.05 (5%), the null hypothesis could not be rejected. However, if the level of significance was set as 0.10 (10%), the null hypothesis could be rejected and N2O concentrations at the front and rear ends of the SCR would be different. Also, since the Z value is based on negative ranks, the N2O concentration could be interpreted as increasing. Paired comparisons of N2O concentrations at the front and rear ends of the FGD in power plant B shows that the pvalue was 0.008, which is lower than 0.05. This suggests that “N2O concentrations at the front and rear ends of the FGD are different.” The Z value, which is the deduction from the concentration at the FGD’s rear end by the concentration of FGD’s front end, was −2.547 and based on positive ranks. This meant that the N2O concentration at the front end was higher and that it decreases as the exhaust gas passes through the FGD. Paired comparisons of N2O concentrations at the front and rear ends of both the SCR and EP in power plant C showed that the p-value was bigger than 0.05, which suggests that the concentrations at both ends are the same. N2O concentrations at the front and rear ends of the FGD in power plant C showed that the p-value from the paired comparison was 0.004, which is smaller than 0.05, so N2O concentrations at both ends of the FGD were different. The Z value was −2.547 and based on positive ranks meaning that the N2O concentration at the front end of the FGD was higher and it decreased as the gas passed through the FGD. Generally, limestone (CaCO3) is used to remove sulfur oxides from the exhaust gas of a power plant. The limestone is converted into CaSO4 by the reaction of calcium oxide (CaO) with sulfur oxides (SOx) and oxygen (O2), removing sulfur oxides from the system. According to a previous study, some free CaO surfaces cause the decomposition of N2O, through the catalytic reaction with the N2O.12 Influence of limestone and calcium carbonate on the N2O and NO concentrations have been actively studied for power plants with high N2O concentrations.13−19 Through laboratory-scale reactor experiments, calcium carbonate was found to act as a strong catalyst in the decomposition of N2O.20−24 As the CaO content of ash among the filler inside the furnace of CFBC increases, the catalytic decomposition of N2O increases.25,26 The reaction catalyzed on the CaO surface is shown in the following equation.23
Table 7. Result of Kruskal−Wallis Test for N2O Concentration N2O power plant A
power plant B
power plant C
a
χ2 df asymp sig.a χ2 df asymp sig. χ2 df asymp sig.
18.662 3 0.000 13.460 3 0.003 20.501 3 0.000
Asymptotic significance.
3.4. Result of Wilcoxon Signed Ranks Test of Each Air Pollution Prevention Facility. Next, the specific air pollution control equipment responsible for the difference should be identified. For this purpose, N2O concentrations at the front and rear ends of equipment were compared in pairs. Since some of the distributions do not satisfy normal distribution, Wilcoxon signed ranks test, which is a nonparametric paired-comparison test, was conducted for those samples. The results of the Wilcoxon test for the front and rear ends of the control equipment in power plant A are shown in Table 8. Table 8. Result of Wilcoxon Signed Ranks Test of Each Air Pollution Prevention Facility SCR OUT N2O−SCR IN N2O site Z asymp sig (two-tailed) exact sig (two-tailed) site Z asymp sig (two-tailed) exact sig (two-tailed)
A
B
C
−1.897a −0.415a −1.274a 0.203 0.058 0.678 0.232 0.059 0.734 EP OUT N2O−EP IN N2O A
B
C
−2.549b −2.194b −1.020b 0.308 0.110 0.280 0.334 0.180 0.230 FGD OUT N2O−FGD IN N2O
site
A
B
C
Z asymp sig (two-tailed) exact sig (two-tailed)
−2.805b 0.005 0.002
−2.547b 0.011 0.008
−2.666b 0.008 0.004
a Based on negative ranks. bBased on positive ranks. cWilcoxon signed ranks test.
N2O + O2 −(CaO)→N2 + O2 2 −(CaO) O2 2 −(CaO) + O2 2 −(CaO) → O2 + 2O2 −
Since the p-values of N2O concentrations at the front and rear ends of both the SCR and EP are above 0.05, the null hypothesis that N2O concentrations are not influenced by the SCR and EP cannot be rejected. Paired comparisons between the front and rear ends of the FGD in power plant A showed that the p-value was 0.02, which is smaller than 0.05 and suggests that “N2O concentrations at the front and rear ends of the FGD are different”. The Z value, the deducted concentration from the rear end concentration by the front end concentration, was −2.313 and was based on positive ranks. This suggests that N2O concentrations at the front end of the FGD were greater than the concentrations at the rear end. In other words, N 2 O concentrations decreased as the exhaust gas passed through the FGD.
Therefore, the decrease in N2O concentrations by the FGD in the bituminous coal power plant was caused by CaCO3 used in the FGD.
4. CONCLUSION To effectively reduce GHG emissions, the first step should be an accurate quantification and documentation of GHG emissions to develop comprehensive emission inventories. CO2, which is emitted by fuel combustion, is dependent on the carbon content of the fuel and is generated by a relatively accurate mechanism. However, the generation mechanism of non-CO2 gases such as CH4 and N2O is not as straightforward and known to be influenced by the combustion technique, type of fuel, contents of 4177
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(9) Madia, G.; Elsener, M.; Koebel, M.; Raimondi, F.; Wokaun, A. Thermal Stability of Vanadia-Tungsta-Titania Catalysis in the SCR Process. Appl. Catal., B 2002, 39, 181−190. (10) Hou, X.; Zhang, H.; Pilawska, M.; Lu, J.; Yue, G. The formation of N2O during the reduction of NO by NH3. Fuel 2008, 87, 3271−3277. (11) The handbook of Environmental testing QA/QC in Korea; National Institute of Environmental Research: Incheon, Republic of Korea, 2011. (12) Wu, L.; Hu, X.; Qin, W.; Dong, C.; Yang, Y. Effect of sulfation on the surface activity of CaO for N2O decomposition. Appl. Surf. Sci. 2015, 357, 951−960. (13) Lyngfelt, A.; Leckner, B. SO2 capture and N2O reduction in a circulating fluidized-bed boiler: influence of temperature and air staging. Fuel 1993, 72, 1553−1561. (14) Bonn, B.; Pelz, G.; Baumann, H. Formation and decomposition of N2O in fluidized bed boilers. Fuel 1995, 74, 165−171. (15) Hayhurst, A. N.; Lawrence, A. D. The effect of solid CaO on the production of NOx and N2O in fluidized bed combustors: studies using pyridine as a prototypical nitrogenous fuel. Combust. Flame 1996, 105, 511−527. (16) Shen, B.; Mi, T.; Liu, D.; Feng, B.; Yao, Q.; Winter, F. N2O emission under fluidizedbed combustion condition, Fuel Process. Fuel Process. Technol. 2003, 84, 13−21. (17) Tarelho, L. A. C.; Matos, M. A. A.; Pereira, F. J. M. A. Influence of limestone addition on the behaviour of NO and N2O during fluidised bed coal combustion. Fuel 2006, 85, 967−977. (18) Hu, X.; Wu, L.; Ju, S.; Dong, C.; Yang, Y.; Qin, W. Mechanistic study of catalysis on the decomposition of N2O. Environ. Eng. Sci. 2014, 31, 308−31. (19) Fu, S.; Song, Q.; Yao, Q. Experimental and kinetic study on the influence of CaO on the N2O + NH3 + O2 system. Energy Fuels 2015, 29, 1905−1912. (20) Hansen, P. F. B.; Dam-Johansen, K.; Johnsson, J. E.; Hulgaard, T. Catalytic reductionof NO and N2O on limestone during sulfur capture under fluidized bed combustion conditions. Chem. Eng. Sci. 1992, 47, 2419−2424. (21) Shimizu, T.; Inagaki, M. Decomposition of N2O over limestone under fluidizedbed combustion conditions. Energy Fuels 1993, 7, 648− 654. (22) Kapteijn, F.; Rodriguez-Mirasol, J.; Moulijn, J. A. Heterogeneous catalytic decomposition of nitrous oxide. Appl. Catal., B 1996, 9, 25−64. (23) Snis, A.; Miettinen, H. Catalytic decomposition of N2O on CaO and MgO: experiments and ab initio calculations. J. Phys. Chem. B 1998, 102, 2555−2561. (24) Hou, X.; Zhang, H.; Yang, S.; Lu, J.; Yue, G. N2O decomposition over the circulating ashes from coal-fired CFB boilers. Chem. Eng. J. 2008, 140, 43−51. (25) Barisíc, V.; Neyestanaki, A. K.; Klingstedt, F.; Kilpinen, P.; Eränen, K.; Hupa, M. Catalytic decomposition of N2O over the bed material from circulating fluidized-bed (CFB) boilers burning biomass fuels and wastes. Energy Fuels 2004, 18, 1909−1920. (26) Barisíc, V.; Klingstedt, F.; Naydenov, A.; Stefanov, P.; Kilpinen, P.; Hupa, M. Catalytic activity of bed materials from industrial CFB boilers for the decomposition of N2O. Catal. Today 2005, 100, 337−342.
carbon and nitrogen inside the fuel, combustion conditions, and air pollution control equipment. In this study, the influence of the air pollution control equipment of bituminous power plants on N2O concentrations was investigated. Toward this purpose, N2O concentrations on the rear end of each control equipment in target power plants were measured and were found to be influenced by the air pollution control equipment. To find out which specific air pollution control equipment affects N2O concentration most, the front and rear ends of each prevention facility in the power plants were analyzed using paired comparisons. The results showed that N2O concentrations at the front and rear ends of the FGD were different and that N2O concentrations decreased as the exhaust gas passed through the FGD. Since the limestone (CaCO3) was decomposed into calcium oxide (CaO) and oxygen, N2O was decomposed on the free CaO surface, during the reactions inside the FGD, according to previous studies. In Korea, there are eight bituminous coal power plants currently in operation. In this study, three of the bituminous coal power plants were selected for the field survey. The results of this study confirmed the influence of air pollution control equipment on N 2 O concentrations caused by the emissions from the power plants. It would be very valuable to perform a similar study for power plants other than the bituminous coal power plants, such as LNG, heavy oil, and hard coal power plants.
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AUTHOR INFORMATION
Corresponding Author
*Tel.: +82-2-3408-3388. E-mail:
[email protected]. ORCID
Seong-Min Kang: 0000-0001-8628-8241 Eui-Chan Jeon: 0000-0002-6620-2380 Notes
The authors declare no competing financial interest.
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ACKNOWLEDGMENTS This subject is supported by the Korea Ministry of Environment as “Climate Change Correspondence R&D Program (2016001300004)”.
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REFERENCES
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DOI: 10.1021/acs.energyfuels.6b03014 Energy Fuels 2017, 31, 4173−4178
