Home Physical Sciences Effect of CaO on catalytic combustion of semi-coke
Article Open Access

Effect of CaO on catalytic combustion of semi-coke

  • , , EMAIL logo , EMAIL logo and
Published/Copyright: January 8, 2021
Become an author with De Gruyter Brill

Abstract

Generally, adding a certain amount of an additive to pulverized coal can promote its combustion performance. In this paper, the effect of CaO on the combustion characteristics and kinetic behavior of semi-coke was studied by thermogravimetric (TG) analysis. The results show that adding proper amount of CaO can reduce the ignition temperature of semi-coke and increase the combustion rate of semi-coke; with the increase in CaO content, the combustion rate of semi-coke increases first and then decreases, and the results of TG analysis showed that optimal addition amount of CaO is 2 wt%. The apparent activation energy of CaO with different addition amounts of CaO was calculated by Coats–Redfern integration method. The apparent activation energy of semi-coke in the combustion reaction increases first and then decreases with the increase in CaO addition. The apparent activation energies of different samples at different conversion rates were calculated by Flynn–Wall–Ozawa integral method. It was found that the apparent activation energies of semi-coke during combustion reaction decreased with the increase in conversion.

1 Introduction

At present, it has become a routine technology for blast furnace ironmaking to replace coke with pulverized coal. It plays an important role in saving coke, reducing consumption, adjusting furnace conditions, reducing pig iron costs, and reducing environmental pollution [1]. The commonly used pulverized coal for blast furnace injection includes bituminous coal and anthracite. Because of its high volatility and flammability, bituminous coal is widely used in blast furnace injection [2,3]. Bituminous coal has good flammability, but it contains a lot of harmful substances such as S and P [4,5,6]. Anthracite has the characteristics of high fixed carbon and low S and P impurity content, but its combustion performance is poor [7,8]. To increase the amount of coal injected into the blast furnace and ensure that the coal powder is burned as much as possible inside the blast furnace, anthracite is generally mixed with bituminous coal for mixed injection [9,10]; this not only makes use of the high fixed carbon content and high calorific value of anthracite, but also takes advantage of the low ignition point and good combustion characteristics of bituminous coal. With the increasing price of anthracite, the cost of blast furnace ironmaking is also increasing, and therefore it is necessary to find another pulverized coal to replace anthracite. As a new type of carbon material, semi-coke has huge reserves in China [11]. It has the advantages of low ash, low sulfur, low phosphorus, and high fixed carbon. Its pore structure is complex, its combustion performance is good, and its price is lower than anthracite; therefore, the use of semi-coke combined with bituminous coal can further reduce the cost of blast furnace coal injection. However, at present, the blending amount of semi-coke in mixed injection pulverized coal is limited. After excessive addition, the combustion performance of mixed pulverized coal will be reduced, and the unburned pulverized coal will increase, which is not conducive to the blast furnace going forward.

Zhang et al. [12] found that in the mixture of semi-coke and bituminous, when semi-coke accounts for 20%, it has a certain promotion effect on the entire combustion process. Yang et al. [13] used thermogravimetric (TG) analysis to study the co-firing behavior of Fushun low-calorie oil shale and semi-coke. The results showed that with the increase in oil shale mass fraction and oxygen concentration, the combustion characteristics of the sample were improved. Yao et al. [14] used TG analysis to study the combustion characteristics and kinetics of the blend in an oxygen-rich atmosphere. Finally, it was found that CO2 instead of N2 can significantly improve the burnout behavior of semi-coke under the same oxygen concentration. Yang et al. [15] used TG analysis to study the mixed combustion process of several kinds of coal and semi-coke, and found that as the heating rate increased, the combustion performance of mixed coal powder and semi-coke was improved. All the above studies are about the mixed combustion of semi-coke and other combustible materials, and the experimental study on the effect of combustion promoters on their catalytic combustion has not been carried out.

Alkaline earth metals such as Ca, Mg, Ba, and other compounds can promote the interfacial reaction of carbon and oxygen and have a high reactivity. In particular, Ca compounds are very cheap combustion-supporting catalysts. CaO, CaCO3, CaCl2, and other Ca-based catalysts have been widely studied by scholars [16,17]. Jayasekara et al. [18] studied the influence of Ca and Fe content on the reactivity of coke with CO2. Compared with the addition of Fe, the reactivity of Ca added to coke was doubled. Cheng et al. [19] studied the catalytic effects of Na-rich and Ca-rich industrial wastes on coal ignition. The results show that both metals have good catalytic effect on coal ignition, but Na has higher catalytic activity on coal ignition than Ca. Abbasi-Atibeh et al. [20] used TG analyzers to study the effects of K, Ca, and Fe on the catalytic pyrolysis and combustion characteristics of low-calorie Turkish lignite. The results show that the combustion tests conducted under O2/CO2 environmental conditions show that the relative activity of the catalyst is Fe ≫ K > Ca and Fe > Ca ≫ K at O2 concentrations of 30% and 35%, respectively. In addition, potassium catalysts have higher reaction rates at all oxygen concentrations. The above results show that the combustion promoters have good catalytic effect on coal, but there is no specific experimental study on the catalytic combustion of semi-coke.

To reduce the cost of pig iron in blast furnace and reduce environmental pollution, increasing the amount of semi-coke in the mixed pulverized coal injection is an effective method. At present, there are many studies on the co-combustion characteristics of semi-coke and other combustible substances, but there are few studies on the effect of combustion-supporting additives on the catalytic combustion performance of semi-coke. Although alkali metals such as Na and K have a good catalytic effect on combustion, after being added, they easily cause corrosion to the combustion equipment, which is not conducive to long-term use of the blast furnace [21,22]. Because CaO has obvious combustion-supporting effect on coal powder, the price is cheap and easy to obtain, and it will not cause corrosion to the blast furnace. In this paper, the catalytic combustion of semi-coke was studied using CaO combustion aid, which has certain guiding significance for increasing the amount of semi-coke in mixed injection coal powder.

2 Experimental

2.1 Sample preparation

The semi-coke used in the experiment was obtained from a smelting company in Yunnan, China. First, use a ball mill to grind the semi-coke to 200 meshes, then dry it to a constant weight at 80°C in a constant temperature oven, and then store it in a sealed bag. The industrial analysis of semi-coke is presented in Table 1. The preparation of the experimental sample was as follows: weigh 10 g semi-coke, put it into a beaker, and then add 2 wt% CaO and 150 mL anhydrous ethanol; the mixture was magnetically stirred at room temperature for 1 h, then the sample was dried at 105°C for 24 h, and then taken out and ground for 5 min. The above operation was repeated to prepare mixed semi-coke samples having CaO addition amounts of 0, 2, 4, 6, and 8 wt%, which were designated as K1, K2, K3, K4, and K5, respectively.

Table 1

Proximate and ultimate analysis results of semi-coke, wt%

Proximate analysis Ultimate analysis
Mad% Vad% Aad% FCad Cad Had Oad Nad Sad
5.28 17.57 8.69 70.28 83.74 3.43 0.76 0.72 0.4

Note: ad – air dry basis; M – moisture; V – volatile matter; FC – fixed carbon.

2.2 Sample characterization

The combustion characteristics of the mixed samples were analyzed by a thermal analyzer model STA6000/8000. The temperature deviation of the thermal analyzer was ±0.1°C, and the sensitivity deviation of the balance was less than 0.1 μg. In this experiment, the sample was raised to 1,000°C at room temperature at a heating rate of 10°C/min, 20°C/min, 30°C/min, and 40°C/min under an air flow rate of 50 mL/min.

3 Results and discussion

3.1 Combustion performance

Five samples of K1, K2, K3, K4, and K5 were tested by thermal analyzer. The TG and DTG curves of combustion tests for different samples are shown in Figure 1. It can be seen from the TG curve that the combustion temperature range of the mixed semi-coke sample is between 400°C and 750°C. Ignition temperature ( T i ) of the samples can be determined by TG-DTG tangent method, that is, the vertical point of the X-axis is made at the peak point of the DTG curve, and the TG curve is intersected at one point, and the tangent of the TG curve is made at this point, and the tangent of the point where the initial mass is unchanged on the TG curve, the intersection of the two tangent lines is the ignition point of the samples. T i reflects the ignition performance of the sample, and the smaller the T i , the easier the sample is to catch fire [23]. The burnout temperature ( T b ) indicates the temperature at which the combustibles in the samples are completely burned out within a certain temperature range, and usually the TG curve tends to a horizontal straight line, corresponding to the temperature at which the DTG curve is close to zero. T i and T b reflect changes in combustion performance throughout the combustion process [24]. The burnout temperature and ignition temperature of the sample are presented in Table 2. After the addition of CaO, the burnout temperature and ignition temperature of the semi-coke are reduced. After adding 2 wt% CaO, the ignition temperature of the semi-coke decreased by 23.70°C, and the burnout temperature decreased by 7.23°C. As the amount of CaO added continues to increase, although the ignition temperature of semi-coke is somewhat reduced, the reduction is much smaller than that of semi-coke with 2 wt% CaO.

Figure 1 
                  TG–DTG curves of the sample at the temperature rise rate of 20°C/min: (a) TG and (b) DTG curves.
Figure 1

TG–DTG curves of the sample at the temperature rise rate of 20°C/min: (a) TG and (b) DTG curves.

Table 2

Combustion parameters of mixed semi-coke samples

Sample T i (°C) T b (°C) Combustion rate (%) S × 10 9 (%2 min−2 °C−3)
500°C 600°C 700°C 800°C
K1 439.15 757.52 5.36 24.52 91.99 99.99 0.44
K2 415.45 750.29 6.15 29.47 89.16 99.82 0.69
K3 428.38 753.68 5.53 24.61 87.24 96.96 0.63
K4 428.96 751.48 4.25 22.57 80.21 94.49 0.42
K5 430.96 754.29 4.24 21.71 76.53 91.53 0.35

By analyzing the TG curve, the combustion rate of the sample at different temperatures can be obtained. For the convenience of analysis, the combustion rate of the samples at the combustion temperatures of 500°C, 600°C, 700°C, and 800°C is generally selected. The combustion rate calculation formula is as follows:

(1) R = W i W t W i × η × 100 % ,

where W i is the initial mass of the sample, g; W t is the mass after the sample is burned t min, g; η is the weight loss rate when the sample is completely burned without additives; and R is the combustion rate of the sample.

In the combustion process, integrated combustion characteristic index ( S ) is generally used to reflect the whole process of burnout and ignition of the sample. The larger the S , the better the combustion characteristics of the sample. The calculation formula is as follows:

(2) S = d w d t max × d w d t mean T i 2 × T b ,

where d w d t max is the maximum combustion rate of pulverized coal, %/min; and d w d t mean is the average combustion rate, %/min.

Comprehensive combustion characteristic index and combustion rate of different samples at different temperatures are presented in Table 2. It can be seen from Table 2 that the combustion rates at the combustion temperatures of 500°C and 600°C are improved when the addition amount of CaO in the semi-coke is 2 wt% and 4 wt% compared with the semi-coke without the additive. With the further increase in CaO addition, when the added amount of CaO in the semi-coke is 6 wt% and 8 wt%, the combustion rates between 500°C and 800°C are lowered. It shows that CaO can promote the combustion of semi-coke, but adding too much of CaO will inhibit its combustion. With the increase in the amount of CaO, the comprehensive combustion characteristics of the samples first increase and then decrease; when the amount of CaO added is 2 wt%, the ignition temperature and burnout temperature of the sample are the lowest, probably because CaO will adsorb the macromolecular volatile components in the semi-coke, which will cause the fixed carbon to locally overheat, resulting in a decrease in the fixed carbon ignition temperature [25,26]. Therefore, the oxidation reaction is more likely to occur, but excessive CaO will inhibit the combustion of semi-coke.

3.2 Impact of heating rates

Considering the impact of different heating rates of the thermal analyzer on the samples, the K1, K2, K3, K4, and K5 were tested in air atmospheres with heating rates of 10°C/min, 20°C/min, 30°C/min, and 40°C/min. The combustion process of the mixed samples having similar trends at different heating rates is shown in Figures 26, which indicates that the variation trend of combustion process of mixed samples is similar under different heating rates, but it has little impact on the whole combustion reaction process of pulverized coal. The TG curve is constantly shifting to the right as the rate of temperature rises, causing T i and T b to increase accordingly. For K3 sample, when the heating rate rises from 10°C/min to 40°C/min, the T i of the sample rises from 428.38°C to 450.25°C, and the T b rises from 753.68°C to 836.27°C. This is because the propagation and heat transfer of the medium take some time. If the heating rate of the program is too fast, the time for the combustion reaction of the sample will be insufficient, and then the entire TG curve will shift to the high temperature area. It can be obtained from the DTG curve that the mass loss rate of the sample also decreases as the rate of temperature rises. With the increase in the heating rate from 10°C/min to 40°C/min, the maximum weight loss rate of the sample decreases from 0.91% to 0.36% per degree Celsius.

Figure 2 
                  TG–DTG curves of K1 sample at different heating rates: (a) TG and (b) DTG curves.
Figure 2

TG–DTG curves of K1 sample at different heating rates: (a) TG and (b) DTG curves.

Figure 3 
                  TG–DTG curves of K2 sample at different heating rates: (a) TG and (b) DTG curves.
Figure 3

TG–DTG curves of K2 sample at different heating rates: (a) TG and (b) DTG curves.

Figure 4 
                  TG–DTG curves of K3 sample at different heating rates: (a) TG and (b) DTG curves.
Figure 4

TG–DTG curves of K3 sample at different heating rates: (a) TG and (b) DTG curves.

Figure 5 
                  TG–DTG curves of K4 sample at different heating rates: (a) TG and (b) DTG curves.
Figure 5

TG–DTG curves of K4 sample at different heating rates: (a) TG and (b) DTG curves.

Figure 6 
                  TG–DTG curves of K5 sample at different heating rates: (a) TG and (b) DTG curves.
Figure 6

TG–DTG curves of K5 sample at different heating rates: (a) TG and (b) DTG curves.

3.3 Dynamic analysis results

The Coats–Redfern integration method belongs to a single scan rate method and is a method for kinetic analysis of data results of a TG curve measured by an experiment at a fixed heating rate [27]. According to Arrhenius’s law, if the initial mass of the coal powder involved in the reaction is m 0 , the mass after the reaction t time is m , and the final mass is m after the reaction is completed, the expression of the reaction rate can be obtained as follows:

(3) d α d t = A ( 1 α ) n exp E α R T f ( α ) ,

(4) α = m 0 m m 0 m ,

where A refers to the pre-exponential factor, min−1; α is the conversion rate of coal powder; n is the reaction order; E α is the activation energy, kJ/mol; and R is the gas constant.

If the rate of temperature raises, β = d T d t is brought to Eq. 3, and a temperature approximation is made, then there is:

(5) 0 α d α ( 1 α ) n = A R T 2 1 2 R T E α exp E α R T β E α .

After Eq. 5, the Coats–Redfern equation can be obtained: when n ≠ 1,

(6) ln 1 ( 1 α ) 1 n T 2 ( 1 n ) = ln A R 1 2 R T E α β E α E α R T ,

when n = 1,

(7) ln ln ( 1 α ) T 2 = ln A R 1 2 R T E α β E α E α R T .

In the combustion process of pulverized coal samples, the result of E α R T is much larger than 1; therefore, the result of 1 2 R T E α is about equal to 1, that is, the expression of the first term on the right-hand side of the Coats–Redfern equation is independent of temperature. When n = 1, in Eq. 7, ln ln ( 1 α ) T 2 is plotted against 1 T , and the graph is approximated as a straight line, E α R is the slope, and ln A R β E α is the intercept. Therefore, in the end, the value of the exponential pre-factor and the activation energy of the combustion reaction of the semi-coke mixed sample can be obtained.

The Flynn–Wall–Ozawa integration method belongs to the multiple scan rate method, which analyzes the experimental data obtained by samples at different heating rates [28,29]. The basic equation of the model is as follows:

(8) ln β = ln A E α G ( α ) 5.331 1.052 E α R T .

At different heating rates, if the same conversion rate is chosen, integral form of reaction mechanism mode function G ( α ) is a fixed value, plotted as ln β versus 1 T , the data is fitted by least squares method, and the activation energy of the reaction can be determined from the slope.

Assume that the combustion reaction of the sample in this experiment is a first-order reaction, that is, n = 1. Figure 7 shows the Coats–Redfern kinetic analysis curve of different samples at a programmed temperature rate of 20°C/min. The activation energy and pre-exponential factor calculation results are presented in Table 3.

Figure 7 
                  Coats–Redfern method plots of different samples at 20°C/min.
Figure 7

Coats–Redfern method plots of different samples at 20°C/min.

Table 3

Combustion kinetic parameters of different samples

Sample E α (kJ/mol) A (min−1) R 2
K1 93.74 3.70 × 105 0.998
K2 82.86 1.16 × 107 0.998
K3 87.24 1.36 × 105 0.998
K4 87.25 3.56 × 104 0.999
K5 93.58 2.72 × 105 0.996

It can be seen from Figure 7 that the linearity of the curve of ln ln ( 1 α ) T 2 with 1000 T is very good, indicating that it is reasonable to assume that the combustion reaction of the sample under the experimental conditions is a first-order reaction. It can be obtained from Table 3 that the activation energy of semi-coke has a certain degree of reduction after adding CaO. When the addition amount is 2, 4, 6, and 8 wt%, the activation energy is reduced by 10.88, 6.50, 6.49, and 0.16 kJ/mol. This indicates that CaO promotes the combustion of semi-coke, and the activation energy is also relatively reduced. When the CaO addition amount is 2 wt%, the reaction activation energy is the smallest, which is consistent with the K2 sample combustion characteristics of the mixed sample obtained above.

The kinetic analysis of different samples was performed by multi-scan FWO integration method. This method is to fit the experimental data by the conversion rate α within a certain range. In the experiment, α is between 0.1 and 0.7, and the fitting data exceeding this range are discarded because it is unreasonable. Figures 812 show the FWO kinetic analysis curves of the different samples reacted at different temperature programmed rates, and Tables 48 present the activation energy calculation and pre-exponential factor calculation results.

Figure 8 
                  FWO method plots of sample K1 in different conversion degrees.
Figure 8

FWO method plots of sample K1 in different conversion degrees.

Figure 9 
           FWO method plots of sample K2 in different conversion degrees.
Figure 9

FWO method plots of sample K2 in different conversion degrees.

Figure 10 
                  FWO method plots of sample K3 in different conversion degrees.
Figure 10

FWO method plots of sample K3 in different conversion degrees.

Figure 11 
                  FWO method plots of sample K4 in different conversion degrees.
Figure 11

FWO method plots of sample K4 in different conversion degrees.

Figure 12 
                  FWO method plots of sample K5 in different conversion degrees.
Figure 12

FWO method plots of sample K5 in different conversion degrees.

Table 4

Combustion kinetic parameters of sample K1

Conversion E α (kJ/mol) A (min−1) R 2
0.1 58.35 2.16 × 106 0.996
0.2 57.89 0.97 × 105 0.998
0.3 56.68 3.03 × 107 0.997
0.4 56.13 3.82 × 105 0.993
0.5 55.47 3.62 × 107 0.994
0.6 54.69 2.57 × 107 0.991
0.7 53.29 1.62 × 106 0.992
Average 56.07
Table 5

Combustion kinetic parameters of sample K2

Conversion E α (kJ/mol) A (min−1) R 2
0.1 47.35 2.63 × 106 0.988
0.2 46.89 1.19 × 105 0.995
0.3 45.68 3.71 × 107 0.995
0.4 45.13 4.75 × 105 0.998
0.5 44.47 4.52 × 107 0.994
0.6 43.69 3.28 × 107 0.994
0.7 43.29 1.99 × 106 0.996
Average 45.21
Table 6

Combustion kinetic parameters of sample K3

Conversion E α (kJ/mol) A (min−1) R 2
0.1 53.25 2.35 × 106 0.995
0.2 52.39 1.07 × 105 0.993
0.3 51.79 3.28 × 107 0.995
0.4 50.22 4.27 × 105 0.997
0.5 50.47 3.98 × 107 0.995
0.6 49.61 2.89 × 107 0.994
0.7 49.18 1.76 × 106 0.996
Average 50.99
Table 7

Combustion kinetic parameters of sample K4

Conversion E α (kJ/mol) A (min−1) R 2
0.1 54.16 2.31 × 106 0.995
0.2 53.26 1.05 × 105 0.993
0.3 52.33 3.24 × 107 0.995
0.4 51.69 4.14 × 105 0.997
0.5 49.87 4.04 × 107 0.995
0.6 48.69 2.88 × 107 0.994
0.7 47.86 1.81 × 106 0.996
Average 51.12
Table 8

Combustion kinetic parameters of sample K5

Conversion E α (kJ/mol) A (min−1) R 2
0.1 59.35 2.11 × 106 0.995
0.2 58.28 0.98 × 105 0.993
0.3 57.63 2.97 × 107 0.995
0.4 56.38 3.79 × 105 0.997
0.5 55.74 3.61 × 107 0.995
0.6 54.69 2.56 × 107 0.994
0.7 53.89 1.61 × 106 0.996
Average 56.57

As shown in Figures 812, the straight line fitted by the FWO integral method agrees well with the original data, which indicates that the linearity of the kinetic curve obtained by this method is high and the result is reliable. Moreover, the slope of the fitted straight line changes with the change in α of the conversion, that is, the reaction activation energy also changes. It can be seen from Tables 48 that the activation energy decreases with the increase in conversion in the same sample. This is because the whole experimental process is carried out under programmed temperature. As the temperature rises gradually, the gas–solid reaction will transition from the initial power control zone to the diffusion control zone, and finally the resulting activation energy is reduced [30,31]. Five samples were tested at different heating rates, when the conversion rate α exceeds 0.7, under the condition of high temperature programming rate, the sample is not completely converted, so the subsequent fitting data are unreasonable and discarded.

4 Conclusions

In this paper, the characteristics and kinetic behavior of semi-coke mixed with CaO were studied by TG analysis. In the TG analyzer, the combustion characteristics of semi-coke are obviously different because of the catalytic combustion supporting characteristics of CaO. The main conclusions are as follows:

  1. The addition of a certain amount of CaO can lower the burnout and ignition temperature of the semi-coke. When the addition amount was 2 wt%, the burnout and ignition temperature of the semi-coke decreased the most, which were 23.70°C and 7.23°C, respectively. With the further increase in CaO addition, although the burnout and ignition temperature of semi-coke decreased, it was significantly lower than the semi-coke when the CaO addition amount was 2 wt%.

  2. The combustion rate and comprehensive combustion characteristic index of different samples at different temperatures indicate that the addition of CaO can promote the combustion of semi-coke, but adding too much of CaO will inhibit its combustion.

  3. The apparent activation energy of semi-coke with different addition amounts of CaO was calculated by Coats–Redfern integration method. In this experiment, the apparent activation energy decreases first and then increases with the increase in CaO addition. When the added amount is 2 wt%, the apparent activation energy is reduced to 82.86 kJ/mol. The apparent activation energies of different samples at four heating rates were calculated by FWO integration method. In this experiment, the apparent activation energy of the combustion reaction of different samples decreased with the increase in conversion. The calculated apparent activation energy is closer to the real activation energy at lower conversion, that is, the lower the reaction gas temperature.

Acknowledgments

This work was supported by the National Nature Science Foundation of China (51764034), Yunnan Provincial Science and Technology Talents Program (202005AC160033)and Yunnan Ten Thousand Talents Plan Young & Elite Talents Project (No. YNWRQNBJ-2019-222).

References

[1] Mathieson JG, Truelove JS, Rogers H. Toward an understanding of coal combustion in blast furnace tuyere injection. Fuel. 2005;84(10):1229–37. 10.1016/j.fuel.2004.06.036.Search in Google Scholar

[2] Gupta S, Al-Omari Y, Sahajwalla V, French D. Influence of carbon structure and mineral association of coals on their combustion characteristics for pulverized coal injection (PCI) application. Metall Mater Trans B. 2006;37(3):457–73. 10.1007/s11663-006-0030-y.Search in Google Scholar

[3] Saha M, Dally BB, Medwell PR, Chinnici A. Burning characteristics of Victorian brown coal under MILD combustion conditions. Combust Flame. 2016;172:252–70. 10.1016/j.combustflame.2016.07.026.Search in Google Scholar

[4] Koene AC, Buke T. Forecasting of CO2 emissions from fuel combustion using trend analysis. Renew Sust Energ Rev. 2010;14(9):2906–15. 10.1016/j.rser.2010.06.006.Search in Google Scholar

[5] Dmitrienko MA, Nyashina GS, Strizhak PA. Major gas emissions from combustion of slurry fuels based on coal, coal waste, and coal derivatives. J Clean Prod. 2018;177:284–301. 10.1016/j.jclepro.2017.12.254.Search in Google Scholar

[6] Li Q, Jiang JK, Wang SX, Rumchev K, Mead-Hunter R, Morawska L, et al. Impacts of household coal and biomass combustion on indoor and ambient air quality in China: Current status and implication. Sci Total Env. 2017;576:347–61. 10.1016/j.scitotenv.2016.10.080.Search in Google Scholar PubMed

[7] Fan WD, Lin ZC, Li YY, Kuang JG, Zhang MC. Effect of air-staging on anthracite combustion and Nox formation. Bound Value Probl. 2009;23(1):111–20. 10.1021/ef800343j.Search in Google Scholar

[8] Wang QX, Chen ZC, Han H, Zeng LY, Li ZQ. Experimental characterization of anthracite combustion and NOx emission for a 300-MWe down-fired boiler with a novel combustion system: Influence of primary and vent air distributions. Appl Energ. 2019;238:1551–62. 10.1016/j.apenergy.2019.01.080.Search in Google Scholar

[9] Kim DW, Lee JM, Kim JS. Co-combustion of Korean anthracite with bituminous coal in two circulating fluidized bed combustors. Korean J Chem Eng. 2007;24(3):461–5. 10.1007/s11814-007-0080-0.Search in Google Scholar

[10] Lee JM, Kim DW, Kim JS. Characteristics of co-combustion of anthracite with bituminous coal in a 200-MWe circulating fluidized bed boiler. Energy. 2011;36(9):5703–9. 10.1016/j.energy.2011.06.051.Search in Google Scholar

[11] Li Q, Li XH, Jiang JK, Duan L, Ge S, Zhang Q, et al. Semi-coke briquettes: Towards reducing emissions of primary PM2.5, particulate carbon, and carbon monoxide from household coal combustion in China. Sci Rep UK. 2016;6(19306). 10.1038/srep19306.Search in Google Scholar PubMed PubMed Central

[12] Zhang JP, Jia XW, Wang CA, Zhao N, Wang PQ, Che DF. Experimental investigation on combustion and NO formation characteristics of semi-coke and bituminous coal blends. Fuel. 2019;247:87–96. 10.1016/j.fuel.2019.03.045.Search in Google Scholar

[13] Yang Y, Lu XF, Wang QH. Investigation on the co-combustion of low calorific oil shale and its semi-coke by using thermogravimetric analysis. Energ Convers Manage. 2017;136:99–107. 10.1016/j.enconman.2017.01.006.Search in Google Scholar

[14] Yao HF, He BS, Ding GC, Tong WX, Kuang YC. Thermogravimetric analyses of oxy-fuel co-combustion of semi-coke and bituminous coal. Appl Therm Eng. 2019;156:708–21. 10.1016/j.applthermaleng.2019.04.115.Search in Google Scholar

[15] Yang GS, Yang ZH, Zhang JL, Yang ZH, Shao JG. Combustion characteristics and kinetics study of pulverized coal and semi-coke. High Temp Mat PR-ISR. 2019;38:783–91. 10.1515/htmp-2019-0034.Search in Google Scholar

[16] Wu XX, Radovic LR. Catalytic oxidation of carbon/carbon composite materials in the presence of potassium and calcium acetates. Carbon. 2005;43(2):333–44. 10.1016/j.carbon.2004.09.025.Search in Google Scholar

[17] Sanahuja-Parejo O, Veses A, Lopez JM, Murillo R, Callen MS, Garcia T. Ca-based catalysts for the production of high-quality bio-oils from the catalytic co-pyrolysis of grape seeds and waste tyres. Catalysts. 2019;9(12):992. 10.3390/catal9120992.Search in Google Scholar

[18] Jayasekara AS, Monaghan BJ, Longbottom RJ, Mahoney MR, Hockings K. The study of the Ca dispersion in coke and effect of Ca and Fe on the coke reactivity using the sole heated oven cokes. Fuel. 2020;264:116818. 10.1016/j.fuel.2019.116818.Search in Google Scholar

[19] Cheng J, Zhou F, Xuan XX, Liu JZ, Zhou JH, Cen KF. The catalytic effect of the Na and Ca-rich industrial wastes on the thermal ignition of coal combustion. Chin J Chem Eng. 2019;27(10):2467–71. 10.1016/j.cjche.2019.02.037.Search in Google Scholar

[20] Abbasi-Atibeh E, Yozgatligil A. A study on the effects of catalysts on pyrolysis and combustion characteristics of Turkish lignite in oxy-fuel conditions. Fuel. 2014;115:841–9. 10.1016/j.fuel.2013.01.073.Search in Google Scholar

[21] Bhattacharyya A, Schenk J, Rantitsch G, Thaler C, Stocker H. Effect of alkaline elements on the reactivity, strength and structural properties of blast furnace cokes. Metalurgija. 2015;54(3):503–6.Search in Google Scholar

[22] Humad AM, Habermehl-Cwirzen K, Cwirzen A. Effects of fineness and chemical composition of blast furnace slag on properties of alkali-activated binder. Materials. 2019;12(20):3447. 10.3390/ma12203447.Search in Google Scholar

[23] Jiang LB, Yuan XZ, Li H, Xiao ZH, Liang J, Wang H, et al. Pyrolysis and combustion kinetics of sludge-camphor pellet thermal decomposition using thermogravimetric analysis. Energ Convers Manage. 2015;106:282–9. 10.1016/j.enconman.2015.09.046.Search in Google Scholar

[24] Kok MV. Temperature-controlled combustion and kinetics of different rank coal samples. J Therm Anal Calorim. 2005;79(1):175–80. 10.1007/s10973-004-0581-6.Search in Google Scholar

[25] Linares-Solano A, Almela-Alarcón M, Lecea CS-Md. CO2 chemisorption to characterize calcium catalysts in carbon gasification reactions. J Catal. 1990;125(2):401–10. 10.1016/0021-9517(90)90313-9.Search in Google Scholar

[26] Marquez-Montesinos F, Cordero T, Rodriguez-Mirasol J, Rodriguez JJ. CO2 and steam gasification of a grapefruit skin char. Fuel. 2002;81(4):423–9. 10.1016/S0016-2361(01)00174-0.Search in Google Scholar

[27] Carroll B, Manche EP. Kinetic parameters from thermogravimetric data. Nature. 1964;201(4914):68–9. 10.1038/201068a0.Search in Google Scholar

[28] Šesták J. Philosophy of non-isothermal kinetics. J Therm Anal Calorim. 1979;16(2):503–20. 10.1007/BF01910714.Search in Google Scholar

[29] Starink MJ. A new method for the derivation of activation energies from experiments performed at constant heating rate. Thermochim Acta. 1996;288(1):97–104. 10.1016/S0040-6031(96)03053-5.Search in Google Scholar

[30] Starink MJ. The determination of activation energy from linear heating rate experiments: A comparison of the accuracy of isoconversion methods. Thermochim Acta. 2003;404(1–2):163–76. 10.1016/S0040-6031(03)00144-8.Search in Google Scholar

[31] Chisato Y, Shinichi S, Syu H, Koji T, Yoshimasa K, Syusaku K, et al. Fundamental study on combustion of pulverized coal injected into coke bed at high rate. ISIJ Int. 2007;32(6):725–32. 10.2355/isijinternational.32.725.Search in Google Scholar

Received: 2020-08-24
Revised: 2020-10-12
Accepted: 2020-11-08
Published Online: 2021-01-08

© 2021 Luyao Kou et al., published by De Gruyter

This work is licensed under the Creative Commons Attribution 4.0 International License.

Articles in the same Issue

  1. Research Articles
  2. MW irradiation and ionic liquids as green tools in hydrolyses and alcoholyses
  3. Effect of CaO on catalytic combustion of semi-coke
  4. Studies of Penicillium species associated with blue mold disease of grapes and management through plant essential oils as non-hazardous botanical fungicides
  5. Development of leftover rice/gelatin interpenetrating polymer network films for food packaging
  6. Potent antibacterial action of phycosynthesized selenium nanoparticles using Spirulina platensis extract
  7. Green synthesized silver and copper nanoparticles induced changes in biomass parameters, secondary metabolites production, and antioxidant activity in callus cultures of Artemisia absinthium L.
  8. Gold nanoparticles from Celastrus hindsii and HAuCl4: Green synthesis, characteristics, and their cytotoxic effects on HeLa cells
  9. Green synthesis of silver nanoparticles using Tropaeolum majus: Phytochemical screening and antibacterial studies
  10. One-step preparation of metal-free phthalocyanine with controllable crystal form
  11. In vitro and in vivo applications of Euphorbia wallichii shoot extract-mediated gold nanospheres
  12. Fabrication of green ZnO nanoparticles using walnut leaf extract to develop an antibacterial film based on polyethylene–starch–ZnO NPs
  13. Preparation of Zn-MOFs by microwave-assisted ball milling for removal of tetracycline hydrochloride and Congo red from wastewater
  14. Feasibility of fly ash as fluxing agent in mid- and low-grade phosphate rock carbothermal reduction and its reaction kinetics
  15. Three combined pretreatments for reactive gasification feedstock from wet coffee grounds waste
  16. Biosynthesis and antioxidation of nano-selenium using lemon juice as a reducing agent
  17. Combustion and gasification characteristics of low-temperature pyrolytic semi-coke prepared through atmosphere rich in CH4 and H2
  18. Microwave-assisted reactions: Efficient and versatile one-step synthesis of 8-substituted xanthines and substituted pyrimidopteridine-2,4,6,8-tetraones under controlled microwave heating
  19. New approach in process intensification based on subcritical water, as green solvent, in propolis oil in water nanoemulsion preparation
  20. Continuous sulfonation of hexadecylbenzene in a microreactor
  21. Synthesis, characterization, biological activities, and catalytic applications of alcoholic extract of saffron (Crocus sativus) flower stigma-based gold nanoparticles
  22. Foliar applications of plant-based titanium dioxide nanoparticles to improve agronomic and physiological attributes of wheat (Triticum aestivum L.) plants under salinity stress
  23. Simultaneous leaching of rare earth elements and phosphorus from a Chinese phosphate ore using H3PO4
  24. Silica extraction from bauxite reaction residue and synthesis water glass
  25. Metal–organic framework-derived nanoporous titanium dioxide–heteropoly acid composites and its application in esterification
  26. Highly Cr(vi)-tolerant Staphylococcus simulans assisting chromate evacuation from tannery effluent
  27. A green method for the preparation of phoxim based on high-boiling nitrite
  28. Silver nanoparticles elicited physiological, biochemical, and antioxidant modifications in rice plants to control Aspergillus flavus
  29. Mixed gel electrolytes: Synthesis, characterization, and gas release on PbSb electrode
  30. Supported on mesoporous silica nanospheres, molecularly imprinted polymer for selective adsorption of dichlorophen
  31. Synthesis of zeolite from fly ash and its adsorption of phosphorus in wastewater
  32. Development of a continuous PET depolymerization process as a basis for a back-to-monomer recycling method
  33. Green synthesis of ZnS nanoparticles and fabrication of ZnS–chitosan nanocomposites for the removal of Cr(vi) ion from wastewater
  34. Synthesis, surface modification, and characterization of Fe3O4@SiO2 core@shell nanostructure
  35. Antioxidant potential of bulk and nanoparticles of naringenin against cadmium-induced oxidative stress in Nile tilapia, Oreochromis niloticus
  36. Variability and improvement of optical and antimicrobial performances for CQDs/mesoporous SiO2/Ag NPs composites via in situ synthesis
  37. Green synthesis of silver nanoparticles: Characterization and its potential biomedical applications
  38. Green synthesis, characterization, and antimicrobial activity of silver nanoparticles prepared using Trigonella foenum-graecum L. leaves grown in Saudi Arabia
  39. Intensification process in thyme essential oil nanoemulsion preparation based on subcritical water as green solvent and six different emulsifiers
  40. Synthesis and biological activities of alcohol extract of black cumin seeds (Bunium persicum)-based gold nanoparticles and their catalytic applications
  41. Digera muricata (L.) Mart. mediated synthesis of antimicrobial and enzymatic inhibitory zinc oxide bionanoparticles
  42. Aqueous synthesis of Nb-modified SnO2 quantum dots for efficient photocatalytic degradation of polyethylene for in situ agricultural waste treatment
  43. Study on the effect of microwave roasting pretreatment on nickel extraction from nickel-containing residue using sulfuric acid
  44. Green nanotechnology synthesized silver nanoparticles: Characterization and testing its antibacterial activity
  45. Phyto-fabrication of selenium nanorods using extract of pomegranate rind wastes and their potentialities for inhibiting fish-borne pathogens
  46. Hydrophilic modification of PVDF membranes by in situ synthesis of nano-Ag with nano-ZrO2
  47. Paracrine study of adipose tissue-derived mesenchymal stem cells (ADMSCs) in a self-assembling nano-polypeptide hydrogel environment
  48. Study of the corrosion-inhibiting activity of the green materials of the Posidonia oceanica leaves’ ethanolic extract based on PVP in corrosive media (1 M of HCl)
  49. Callus-mediated biosynthesis of Ag and ZnO nanoparticles using aqueous callus extract of Cannabis sativa: Their cytotoxic potential and clinical potential against human pathogenic bacteria and fungi
  50. Ionic liquids as capping agents of silver nanoparticles. Part II: Antimicrobial and cytotoxic study
  51. CO2 hydrogenation to dimethyl ether over In2O3 catalysts supported on aluminosilicate halloysite nanotubes
  52. Corylus avellana leaf extract-mediated green synthesis of antifungal silver nanoparticles using microwave irradiation and assessment of their properties
  53. Novel design and combination strategy of minocycline and OECs-loaded CeO2 nanoparticles with SF for the treatment of spinal cord injury: In vitro and in vivo evaluations
  54. Fe3+ and Ce3+ modified nano-TiO2 for degradation of exhaust gas in tunnels
  55. Analysis of enzyme activity and microbial community structure changes in the anaerobic digestion process of cattle manure at sub-mesophilic temperatures
  56. Synthesis of greener silver nanoparticle-based chitosan nanocomposites and their potential antimicrobial activity against oral pathogens
  57. Baeyer–Villiger co-oxidation of cyclohexanone with Fe–Sn–O catalysts in an O2/benzaldehyde system
  58. Increased flexibility to improve the catalytic performance of carbon-based solid acid catalysts
  59. Study on titanium dioxide nanoparticles as MALDI MS matrix for the determination of lipids in the brain
  60. Green-synthesized silver nanoparticles with aqueous extract of green algae Chaetomorpha ligustica and its anticancer potential
  61. Curcumin-removed turmeric oleoresin nano-emulsion as a novel botanical fungicide to control anthracnose (Colletotrichum gloeosporioides) in litchi
  62. Antibacterial greener silver nanoparticles synthesized using Marsilea quadrifolia extract and their eco-friendly evaluation against Zika virus vector, Aedes aegypti
  63. Optimization for simultaneous removal of NH3-N and COD from coking wastewater via a three-dimensional electrode system with coal-based electrode materials by RSM method
  64. Effect of Cu doping on the optical property of green synthesised l-cystein-capped CdSe quantum dots
  65. Anticandidal potentiality of biosynthesized and decorated nanometals with fucoidan
  66. Biosynthesis of silver nanoparticles using leaves of Mentha pulegium, their characterization, and antifungal properties
  67. A study on the coordination of cyclohexanocucurbit[6]uril with copper, zinc, and magnesium ions
  68. Ultrasound-assisted l-cysteine whole-cell bioconversion by recombinant Escherichia coli with tryptophan synthase
  69. Green synthesis of silver nanoparticles using aqueous extract of Citrus sinensis peels and evaluation of their antibacterial efficacy
  70. Preparation and characterization of sodium alginate/acrylic acid composite hydrogels conjugated to silver nanoparticles as an antibiotic delivery system
  71. Synthesis of tert-amylbenzene for side-chain alkylation of cumene catalyzed by a solid superbase
  72. Punica granatum peel extracts mediated the green synthesis of gold nanoparticles and their detailed in vivo biological activities
  73. Simulation and improvement of the separation process of synthesizing vinyl acetate by acetylene gas-phase method
  74. Review Articles
  75. Carbon dots: Discovery, structure, fluorescent properties, and applications
  76. Potential applications of biogenic selenium nanoparticles in alleviating biotic and abiotic stresses in plants: A comprehensive insight on the mechanistic approach and future perspectives
  77. Review on functionalized magnetic nanoparticles for the pretreatment of organophosphorus pesticides
  78. Extraction and modification of hemicellulose from lignocellulosic biomass: A review
  79. Topical Issue: Recent advances in deep eutectic solvents: Fundamentals and applications (Guest Editors: Santiago Aparicio and Mert Atilhan)
  80. Delignification of unbleached pulp by ternary deep eutectic solvents
  81. Removal of thiophene from model oil by polyethylene glycol via forming deep eutectic solvents
  82. Valorization of birch bark using a low transition temperature mixture composed of choline chloride and lactic acid
  83. Topical Issue: Flow chemistry and microreaction technologies for circular processes (Guest Editor: Gianvito Vilé)
  84. Stille, Heck, and Sonogashira coupling and hydrogenation catalyzed by porous-silica-gel-supported palladium in batch and flow
  85. In-flow enantioselective homogeneous organic synthesis
Downloaded on 25.3.2026 from https://www.degruyterbrill.com/document/doi/10.1515/gps-2021-0002/html
Scroll to top button