2016 International Conference on Power Engineering & Energy, Environment (PEEE 2016) ISBN: 978-1-60595-376-2

Microwave Pyrolysis Parameter Design of Water Hyacinth after Optimization based on Box-Behnken

T. Yang, G. Wei Zhang, W. Zhe Zhu, J. Bin Su, Y. Zhao*

College of Mechanical Engineering and Automation, University, Fuzhou, , 350116, *[email protected]

Keyword: water hyacinth, Box-Behnken, optimization

Abstract. The objective of this study was to maximize the biofuel content of water hyacinth obtained from microwave pyrolysis of. Box-Behnkenof response surface methodology was applied for the experimental design. Under the optimal condition: 1110W of power, 3.5m of reaction time, 2% of the amount of the absorbent, the maximum biofuel content from microwave pyrolysis of water hyacinth was 20.17%.

Introduction Water hyacinth, as waste biomass, can potentially be used to prepare bio-oil and biochar and address pressing issues of energy shortage and serious environmental pollution through microwave pyrolysis [1-3]. Effectively converting water hyacinth biomass into renewable bio-oil, ethanol, hydrogen, and methane biofuels is one of the interesting and promising solutions to the said problem [4-6]. Biomass pyrolysis bio-oil preparation is an important method of biomass energy conversion, In fact, all the investigations using full factorial design for microwave pyrolysis water hyacinth producing bio-oil are tedious and response surface methodology(RSM), which is a collection of statistical and mathematical techniques, has been proved to be an effective way for the desired purpose.[7-9] Most of studies were concerned with the extraction of oil using microwave pyrolysis. Few if any of these studies were directed toward understanding of combined effects of processing variables on the oil content of water hyacinth. We have studied the relationships between the variables (adsorbent amount, time and power of microwave) and the responses (oil content) and obtained satisfactory conditions for pyrolysis using Box-Behnken experimental design.

2. Material and methods 2.1. Materials. The water hyacinthwas collected from reservoir in Youxi county of Fujian Province. Before use, the samples were washed several times with distilled water and dried at 105℃ for 24 h. The samples were then stored in the drying cabinet before utilization. All the chemical reagen used were of analytical grade and all solutions were prepared using deionized water. 2.2. Bio-oil content. Yield of bio-oil was calculated as follows (Eq. 1 ):

m  m  m oil TL 50%e . (1)

Where moil(g) is the weight of bio-oil; mTL (g) is the collect quantity of total liquid in the bottle; m50%e is quality used of the used 50% ethanol solution. Bio-oil content was calculated as follows (Eq. 2 ):

m w  oil 100% oil m T . (2)

Where woil is the bio-oil content (%); mT is the total quality of the raw material before pyrolysis. 2.3. Average molecular weight determination. Water hyacinth composition analysis was determined by raw material component analysis. The proportion of water hyacinth element is shown in table 1. This shows that the water hyacinth is a suitable material for biomass energy.

Table 1.Components analysis of Water Hyacinth. Moisture Molar Molar Ash/% C/% H/% N/% O/% content/% H/C O/C WH 11.15 21.91 35.05 5.10 1.56 34.43 1.75 0.76

100 1

90 0.8 80 TG /% DSC/mW·mg-1 0.6

70

1

60 0.4 -

50 0.2 TG/%

40 0 DSC/mW·mg 30 -0.2 20 10 -0.4 0 -0.6 0 100 200 300 400 500 600 700 800 900 1000 Temperature /℃ Figure 1. The TG and DSC curves of Water Hyacinth at the heating rate of 10 ℃/min.

2.4. Raw material thermogravimetric analysis. Water hyacinth Thermogravimetric Analysis (TG) curves and differential scanning calorimetry (DSC) curves are shown in Fig. 1.It can be seen, the pyrolysis of water hyacinth is divided into 4 stages: first phase at room temperature ~105℃, mainly for drying, the water of water hyacinth begins to evaporate. At this stage the water hyacinth mass loss rate is about 10%, but at 105~240℃ stage, material is almost completely dry, but the temperature of water hyacinth had not been reached, therefore, the material quality remains unchanged; at the time of 240~380℃, pyrolysis stage, weight loss is about 45%. Lignocellulose in the structure begin to crack. When heated to decomposition, internal chemical bonds are broken, producing phenols, ester, and small molecules such as hydrocarbons; at the time temperature rise above 380℃, main stage of carbonization reaction of biological carbon, mass loss rate is about 20%. By differentiating scanning calorimetry (differential scanning calorimetry, DSC for short) curve

samples and the reference for the temperature difference can be seen, water hyacinth in the drying phase is an endothermic process. At 370℃ near the peak for lignin absorption of heat in the water hyacinth material, resulting in structural decomposition. Through the analysis of the composition and process of cracking, microwave power, amount of absorbent and time should be detained researched to analysis cracking product, namely biological oil , biological carbon and biological gas. 2.5 Experimental methodology. Box-Behnken experiment method is the basic idea of the response surface method using the orthogonal experimental data analysis results. Therefore Box–Behnken was employed to determine the optimum conditions for bio-oil content. According to the single factor experiment shown in Fig. 2 results has confirmed the best single factor condition of the microwave power, microwave-absorbent and microwave time of the best single factor condition. Set each condition the best value for the center. The levels of the three retained variables are indicated in Table 2. Biochar rate Biochar rate Biochar rate A Bio-oil rate B Bio-oil rate C Bio-oil rate Biogas rate Biogas rate 100 60 Biogas rate

60

50 80 50

40 40 60 30 30 40

20 20 Productyield 10 20 Productyield 10 Productyield 0 0 0 1000110012001300 0 0.1 0.2 0.3 2.5 3 3.5 4 Microwave power Microwave absorbent Microwave time Figure. 2 Effect of microwave power, absorbent and time on water hyacinth cracking component.

2.6 Box-Behnken design. A Box-Behnken design was used to estimate the model coefficients. And by optimizing the parameters, to determine optimum parameters of microwave pyrolysis bio-oil preparation water hyacinth. All calculations and graphics were performed by using the experimental design software Design Expert 8.0. Table 2. Factors and levels of Box-Behnken design. Coded symbols and levels Factors -1 0 1 microwave powerA/ W 1050 1100 1150 microwave-absorbentB/% 1.50 2.00 2.50 microwave timeC/min 3.25 3.50 3.75

3. Results and discussion 3.1. Response measurements. As shown in Fig. 2, Experimental values obtained for the bio-oil content ranged from 15.74 to 20.32%. When the cracking power is set to 1000W, it begin to have drastic reaction. When power boost to 1100W, the bio-oil yield significantly improved to a maximum content of 17.49%, biomass gas are increasing but the solid product is significantly lower. This showns that the water hyacinth was completely reacted. With increasing microwave power, yield of bio-oil begin to decline slightly, solid product reduced and gas products increased after they

have started to stabilize, while the biomass gas increased and solid product is further reduced. With the increase of pyrolysis time, bio-oil production also increase, and reaches a maximum 19.59% in 3.5 min. Without microwave absorbers, water hyacinth is almost doesn’t reacted. And with significant response after adding 1% microwave absorber. After the addition of 2% microwave absorber, bio-oil further enhanced and reach the maximum content 20.70%.This is because with the increase of pyrolysis time, pyrolysis reaction of water hyacinth is more complete, thus the bio-oil production of raw material has been improved.

3.2. Estimated model. By using the Design Expert software to multiple regression quadratic fitting of experimental data analysis, the relationship between the response and the three selected variables were approximated by the following second order polynomial (Eq. 3) function:

Y = 20.02 + 1.53A + 0.63B − 0.29C + 0.082AB − 0.18AC − 1.13A2 − 0.94B2 − 0.80C2. (3) Where Y is the calculated response function bio-oil content and A is the microwave power, B is the amount of microwave-absorbent, C is the microwave time. The results of analysis of equation and variance for Response Surface regression model are given in Table 3. As can be seen, the model P-value less than 0.0001 indicted that the regression equation of fitting is significantly better. The P-value of the lack of fit (0.1468) is not significant showed that the quadratic model was valid for this study. And the model R-Squared equal to 0.9965, AdjR-Squared equal to 0.992. As a result, the regression equation model was valid for this study. From the results in Table 3, three independent variables A, B, C and the quadratic terms AB extremely significant, while the interaction items were significantly smaller. The microwave power had shown to be the most important variable and microwave time the second important factor of this model, and microwave-absorbent in the next place. Table 3. Significance analysis of equation and variance for Response Surface regression model. Sum of Source DF Mean aquare F-value P-value squares model 35.89 9 3.99 220.24 < 0.0001 A 18.76 1 18.76 1035.89 < 0.0001 B 0.69 1 0.69 38.12 0.0005 C 3.18 1 3.18 175.35 <0.0001 AB 0.12 1 0.12 6.77 0.0354 AC 0.027 1 0.027 1.50 0.2598 BC 0.000025 1 0.000025 0.001 0.9714 lack of fit 0.089 3 0.030 3.18 0.1468 determination coefficient 0.9965 correction coefficient 0.992

Figure 3. Surface plots for oil extraction rate of water hyacinth: effect of power and absorbent amount on bio-oil extraction rate.

3.3. Analysis of response surface and contour map. As shown in Table 3, effect of three variables A, B and C on the result from analysis of response surface is very similiar according to the curves shown in Fig. 2 The relationships between the experimental parameters of quadratic coefficient AB and the responses surface and contour map are illustrated in dimensional representations. These plots are presented in Fig. 3. The main task of response surface and contour map is to track efficiently for the optimum values of the three variables and their interactions so that the response can be maximized. By analyzing the plots, the best response range can be calculated. Fig. 3 shown the interaction influence of microwave power A and microwave-absorbent amount B on bio-oil extraction rate. It is evident that as the microwave power and micro-absorbent added gradually increase, bio-oil content were increased then decreased. As can be seen from the contour map Fig. 3B, microwave power of around 1150W and microwave-absorbent adding amount of 2.0% can obtain the highest bio-oil content. The use of the Design-Expert software for experimental data analysis and optimization of experiment parameters obtained optimum parameters of microwave preparation bio-oil cracking water hyacinth: microwave power of 1113.33W; microwave-absorbent adding amount of 2.13% and cracking time of 3.43 min. The predict bio-oil yield was 20.38%. According to the adjusted parameters pyrolysis experiment, and three parallel experiments were conducted. The average oil content of 20.17% is close to the predicted value.

4. Conclusion RSM was used for optimization of oil content. Bio-oil was extracted from dried water hyacinth with 17 combinations of power, time and absorbent amount of microwave pyrolysis. On the basis of single factor experiment and the experiment calculation, the influence of three kinds of variables in the order: microwave power, microwave time, microwave-absorbent. According to the experimental condition, microwave pyrolysis parameter were adjusted to microwave power of 1113.33W, microwave-absorbent adding amount at 2.13% and cracking time of 3.43 min. And experimental verification to obtain oil rate was 20.17% which is more close to predicted value.

Acknowledgements This research was financially supported by Fuzhou Administration of Science and Technology (2014-G-65) and Fujian Provincial Department of Science and Technology (2015H0018).

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