Subscriber access provided by UNIV OF REGINA
Article
Upgrading the Storage Properties of Bio-Oil by Adding a Compound Additive Liang Zhu, Kai Li, Yiming Zhang, and Xifeng Zhu Energy Fuels, Just Accepted Manuscript • Publication Date (Web): 02 May 2017 Downloaded from http://pubs.acs.org on May 6, 2017
Just Accepted “Just Accepted” manuscripts have been peer-reviewed and accepted for publication. They are posted online prior to technical editing, formatting for publication and author proofing. The American Chemical Society provides “Just Accepted” as a free service to the research community to expedite the dissemination of scientific material as soon as possible after acceptance. “Just Accepted” manuscripts appear in full in PDF format accompanied by an HTML abstract. “Just Accepted” manuscripts have been fully peer reviewed, but should not be considered the official version of record. They are accessible to all readers and citable by the Digital Object Identifier (DOI®). “Just Accepted” is an optional service offered to authors. Therefore, the “Just Accepted” Web site may not include all articles that will be published in the journal. After a manuscript is technically edited and formatted, it will be removed from the “Just Accepted” Web site and published as an ASAP article. Note that technical editing may introduce minor changes to the manuscript text and/or graphics which could affect content, and all legal disclaimers and ethical guidelines that apply to the journal pertain. ACS cannot be held responsible for errors or consequences arising from the use of information contained in these “Just Accepted” manuscripts.
Energy & Fuels is published by the American Chemical Society. 1155 Sixteenth Street N.W., Washington, DC 20036 Published by American Chemical Society. Copyright © American Chemical Society. However, no copyright claim is made to original U.S. Government works, or works produced by employees of any Commonwealth realm Crown government in the course of their duties.
Page 1 of 11
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60
Energy & Fuels
Upgrading the Storage Properties of Bio-Oil by Adding a Compound Additive Liang Zhu, Kai Li, Yiming Zhang, and Xifeng Zhu Key Laboratory for Biomass Clean Energy of Anhui Province, CAS Key laboratory of Urban Pollutant Conversion, University of Science and Technology of China
ABSTRACT: A compound additive consisting of methanol, N, N-dimethylformamide (DMF) and acetone was obtained with the A-Optimal mixture design of Design-Expert. How the solvent effected on the stability of bio-oil was analyzed base on viscosity, moisture content and pH. Bio-oil with the optimal compound additive (1wt% methanol, 5.064wt% DMF and 1.940wt% acetone) with low viscosity, moisture content and high pH after aging (80°C for 24h). The corresponded properties values were 4.36mm2/s, 24.03% and 4.49, respectively, and the result was better than bio-oil with a single solvent. GC-MS analysis revealed that the phenol contents in all the compounds in bio oil were high. After aging, the content of sugars and esters increased, and several chemical compounds, such as 2-ethoxy-5-(1-propen-1-yl) and5-hydroxy-2-methylbenzaldehyde, disappeared in bio-oil with compound additive. Element analysis showed that the content of O and N increased after the addition of the optimal compound additive. The compound additive exerted a positive effect on the bio-oil during storage.
KEYWORDS: Mixture design 1. INTRODUCTION
Optima compound additive
Bio-oil
Stability
Economic development and lack of energy resources promote the booming evolution of alternative fuels. Biomass is a promising power sources and possesses the advantages of renewable sustainability and extensive usage1. Thermochemical conversion is a relative simple method for the efficient use of biomass2. Fast pyrolysis of biomass in the absence of air/oxygen can produce three products: bio-oil, volatile gaseous components and bio-char3. Bio-oil is a free-flowing, dark-brown organic liquid with a distinctive smoky odor4. Compared with solid biomass, bio-oil is easier to store and transport. Bio-oil is easy to produce and a potential fuels for numerous applications; it may also be an alternative to petroleum5. Furthermore, bio-oil is also considered as a promising chemical feedstock6. Bio-oil consists of many oxygen compounds, such as water, acids, alcohols, ketones, aldehydes, carbohydrates and degraded lignin7. Bio-oil presents instability, is prone to corrosion, and possesses high moisture content, high viscosity, low pH because of these oxygen-containing compounds8. During long periods of storage, the viscosity of bio-oil increases due to polymerization reactions, which results in the formation of sludge at the bottom; the percentage of water also increases for the reason of condensation reactions and esterification reactions9. The increase in moisture content leads to a decrease in the heating value. Although the industrial application of bio-oil is limited, bio-oil is still a potential substitute for fossil fuel. Many researchers have studied various aspects of bio-oil, including bio-oil production technologies10, upgrading11, storage12, transportation13, and application14. Bio-oil utilization faces several challenges15. The primary challenge in using bio-oil as fuel is long storage periods. Many researchers have attempted to upgrade its properties through feedstock pretreatment 16, hydrodeoxygenation17, esterification18, emulsification19, steam reforming20, catalytic cracking21, fractional distillation22 and react with supercritical fluid18. A polar solvent has been demonstrated that can reduce bio-oil viscosity and enhance stability23. The effect of water24, methanol25, ethanol26 and acetone8b has been investigated based on quantitative data, and results have shown that the stability of bio-oil was effected greatly by methanol. Therefore a polar solvent 1
ACS Paragon Plus Environment
Energy & Fuels
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60
can be used as an alternative technique to improve bio-oil performance. However, studied on upgrading bio-oil by adding compound additives are insufficient. A compound additive containing of organic solvents exerts a positive effect on the stability of bio-oil. Using Design-Expert software is convenient for the design and validation of optimal compound additives. Several studies used a design software to obtain compound additives with three components, such as methanol, acetone, ethyl acetate27 and ethanol, acetonitrile methyl acetate28. In this study, a compound additive consisting of methanol, DMF and acetone was acquired with the Design-Expert software.
2. MATERIALS AND METHODS 2.1 Bio-oil and Solvent. The walnut shell was used as material for fast pyrolysis. A homemade pilot plant equipped with spouted bed reactor which was full of N2 was operated at 500-550°C to get pyrolysis gas. Finally, bio-oil was obtained through rapid condensation of pyrolysis gas. Methanol (≥99.5%, AR), DMF (≥99.5%, AR) and acetone (≥99.5%, AR) were purchased from Sinopharm Chemical Reagent Co. Ltd. 2.2 Bio-oil analysis. All experimental bio-oil were sealed in bottles and putted in the 80°C incubator aging 24h. The viscosity is an important physical property parameter of bio-oil. The viscosity was determined by SYD-265H petroleum product kinematic viscosity tester at 40°C. The moisture content was determined by Karl Fischer titration ZDJ-35. The solvent is composed of methanol and dichloromethane, with the ratio of 1:3. The bio-oil was mixed thoroughly each time. The pH was determined by a pHB-8 pH meter at normal temperature. Before the test, the standard cushion solution of monopotassium phosphate and potassium biphthalate is used to adjust the apparatus. The density was determined by SYD-1884 petroleum product density meter at 25°C. The elementary compositions of carbon, hydrogen, nitrogen and sulfur were analyzed by a Macro Elemental Analyzer with helium as carrier gas. The oxygen percentage was computed by the total element 100% subtract the amount of C, H, N and S. Bio-oil samples were analyzed through gas chromatography-mass spectrometry (GC-MS) equipped with an SE-30MS capillary column (50 m × 0.25 mm i.d × 0.25µm film thickness) and a quadrupole analyzer in electron impact mode at 70 eV. Split injection was performed at a split ratio of 50 with helium (99.999%) as a carrier gas. The GC heating ramp was: (1) maintained at 40 °C for 5 min, (2) heated to 180 °C at 5 °C/min and maintained for 2 min, (3) heated to 280 °C at 10°C/min, and (4) maintained at 280 °C for 5 min. The chemical components of samples were detected by using the NIST library, Wiley library and literature data. The temperature of injector is set to 250 °C. 0.25µl sample was injected. 2.3 Design Experiments. Experiments were designed to identify the important variables and explain the relations among them. Design-Expert is a professional software for experiment design and related analysis. This software can design an efficient experimental program and provide a comprehensive visual model and together with the optimization results. Design-Expert has three functions: design, analysis and optimization. The A-Optimal mixture design in Design-Expert is a special type of response surface experimentation29. This method can solve mixed problems and reduce the number of experiment30. It involves the variation of blend composition, explores the effect of the change of research target on properties and chooses the optimal composition for achieving the prediction mixture. 2
ACS Paragon Plus Environment
Page 2 of 11
Page 3 of 11
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60
Energy & Fuels
The experiments were performed with the A-optimal mixture design in Design-Expert. The optimal composition was obtained with the software. The experiments are shown in Table 1. The design experiments involved 16 experimental groups. The compound additive consisted of methanol, DMF and acetone. The amount of solvent in the experiments was maintained 8 wt.%, and bio-oil accounted for 92 wt.%. The three primary components were varied from a lower threshold of 1 wt.% and upper threshold of 6 wt.%. The response variables of viscosity, moisture content, pH were used as the experimental results, the samples were measured before and after aging. All experimental results were repeated thrice and the data was averaged as the final result. The indexes are defined in Eqs (1) and (2), respectively. (1) Viscosity index (40 °C, %)=(η2−η1)/ η1 × 100% (2) Moisture content index (%)=(M2−M1)/M1 × 100% Where η1 and η2 are the viscosity before and after aging, mm2/s; M1 and M2 are the moisture content before and after aging, wt.%. Table 1. Results of Each Run with the compound Additive Run Components 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16
Methanol (wt.%)
DMF (wt.%)
Acetone (wt.%)
1.000 3.500 1.000 3.500 1.833 3.500 1.000 1.000 3.500 6.000 1.000 6.000 4.333 3.083 1.833 1.833
1.000 3.500 1.000 1.000 1.833 3.500 3.500 6.000 1.000 1.000 6.000 1.000 1.833 1.833 4.333 3.083
6.000 1.000 6.000 3.500 4.333 1.000 3.500 1.000 3.500 1.000 1.000 1.000 1.833 3.083 1.833 3.083
The mixture design was used to select the final optimal compound additive with the test results as response values. Several steps were performed in the optimization experiment, and these steps included model selection, regression analysis and analysis of variance (ANOVA). The software selected the suitable regression model from the experiment scheme in Table 1. Manual regressions were carried out continuously and appropriate models were acquired afterward. When diagnosing the statistical properties of the models, the data points should be approximately linear. Afterward, the response surface contour plots were generated through model graphs. The mathematical models were affected by the experimental results. The final formula of compound additive was verified by the experiments. 2.4 Verification of the Optimal Compound Additive. Optimal formula of methanol, DMF and acetone were studied under same aging conditions. Bio-oil without an organic solvent served as control group, and that with the compound additive served as experimental group. The results 3
ACS Paragon Plus Environment
Energy & Fuels
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60
Page 4 of 11
of two groups were compared. The samples were characterized through GC-MS and element analysis. The results of analysis of the properties of the samples with each solvent (8wt.%) were compared with those of the sample with the optimal compound additive.
3 RESULTS AND DISCUSSION 3.1 Optimal Compound Additive. Experimental data analysis was performed with design software. The experimental results before and after aging were given in Table 2. The mass loss percentages of all samples were lower than 5%. The viscosity and moisture content of the blank group (without addition) increased after aging from 4.22mm2/s to 6.58mm2/s and from 25.43% to 27.82%, respectively, the corresponded indexes were 56% and 9.4%; meanwhile, pH decreased from 4.22 to 4.05. In all the experimental groups after aging, the highest and lowest response values were 5.12mm2/s and 4.39mm2/s, 24.68% and 23.89%, 4.60 and 4.22. The indexes of viscosity and moisture content decreased from 51.8% and 6.03% to 37.01% and 2.41%, respectively. Table 2 shows that the compound additive exerted a positive result on the bio-oil during storage. Table 2. Results of the Experimental Samples Run
Response variables (before/after aging) 2
Viscosity (mm /s)
Moisture content (%)
Viscosity index (%) moisture content index (%) pH
Density (g/cm 3)
1
3.29/4.97
23.29/24.48
4.28/4.32
0.9587/0.9576
51.06
5.11
2
3.32/4.59
23.20/24.68
4.34/4.50
0.9691/0.9680
38.25
5.95
3
3.63/5.05
23.13/24.35
4.24/4.34
0.9420/0.9413
39.12
5.27
4
3.34/5.07
23.27/24.08
4.30/4.28
0.9483/0.9463
51.80
3.48
5
3.67/5.02
23.08/24.13
4.23/4.22
0.9444/0.9421
40.87
4.55
6
3.07/4.60
23.23/24.63
4.31/4.47
0.9518/0.9509
49.84
6.03
7
3.11/4.42
23.10/24.00
4.23/4.45
0.9637/0.9621
51.77
3.90
8
3.16/4.72
23.23/24.10
4.38/4.60
0.9571/0.9560
39.87
3.75
9
3.55/5.12
23.15/24.17
4.28/4.30
0.9470/0.9453
44.23
4.41
10
3.18/4.49
23.34/23.93
4.30/4.35
0.9533/0.9513
50.67
2.53
11
3.08/4.67
23.33/23.89
4.35/4.59
0.9624/0.9603
44.48
2.41
12
3.02/4.57
23.18/24.03
4.34/4.31
0.9501/0.9489
51.32
3.67
13
3.43/4.90
23.47/24.45
4.36/4.30
0.9617/0.9573
42.86
4.18
14
3.53/5.02
23.29/24.19
4.37/4.25
0.9641/0.9620
42.22
3.86
15
3.13/4.39
23.50/24.33
4.36/4.48
0.9560/0.9513
40.26
3.53
16
3.35/4.59
23.37/24.36
4.39/4.43
0.9613/0.9573
37.01
4.24
Blank group
4.22/6.58
25.43/27.82
4.20/4.05
0.9817/0.9801
55.92
9.40
Regression models were obtained through data analysis and optimization. ANOVA analysis demonstrated that the response values were suitable for the corresponding equations. The equations of response variables were obtained by regression analysis Equation 1: Viscosity=3.91743A+5.12352B+5.21810C+0.031733AB+4.00686 AC-4.20107BC Equation 2: Moisture content =23.18952A+23.29332B+24.90606C+7.12722AB-0.72117AC -1.51053BC Equation 3: pH = 4.31773A+4.55489B+4.20870C Where A is methanol fraction, B is the DMF fraction, and C is the acetone fraction. The ANOVA tables (Table S1, S2 and S3) provide details on Eqs. (1), (2) and (3). In the ANOVA table of Eq. (1) (Table S1), the value of "Prob > F" less than 0.01 indicate Eq. (1) is 4
ACS Paragon Plus Environment
Page 5 of 11
significant. The t-results and P-values show that the interactions between A and C, and between B and C are significant. Table S2 shows that Eq. (2) is also significant (p furans > aldehydes > alcohols > esters > ketones > sugars. As shown in Figure 3, phenols (36.69%, 36.24, 41.06% and 39.21%) were the strongest group in the bio-oil samples. Phenols are high-value products and widely used in in many areas. Phenols can be extracted from bio-oil, and these can substitute for phenols acquired from petroleum. After aging, the content of phenols increased; the content in blank group increased more than that in the experimental group. The content of sugars and esters increased, the content of furans and aldehydes decreased, and the content of acid, alcohols and ketones did not change significantly. Comparison of the two groups after aging showed that several compounds, such as 2-ethoxy-5-(1-propen-1-yl) and 5-hydroxy-2-methylbenzaldehyde disappeared in the experimental group after aging. This result may be due to the fact that the compound additive reacted with these compounds.
40 Blank group before aging Experiment group beforeaging
35
Relative peak areas（ %）
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60
Blank group after aging Experiment group after aging
30 25 20 15 10 5 0 Phenols
Acids
Furans AldehydesAlcohols Esters Ketones Sugars
Group
Figure 3. Group distribution of relative peak areas 8
ACS Paragon Plus Environment
Page 8 of 11
Page 9 of 11
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60
Energy & Fuels
4. CONCLUSION The Design-Expert software effectively reduces the number of experiments when the number of variables is three or more. An optimal compound additive consisting of 1 wt.% methanol, 5.064 wt.% DMF and 1.940 wt.% acetone was obtained through simulation with the Design-Expert software. The result on response variables indicated that the optimal compound additive was better than a single additive in terms of improving the stability of bio-oil. The GC-MS results indicated that phenols had the highest content in bio-oil. The molecular mass weight of bio-oil increased after aging. Compared of the experimental and blank groups after aging showed that the content of phenols increased; the content in the blank group increased more than that in the experimental group, several compounds, such as 2-ethoxy-5-(1-propen-1-yl) and 5-hydroxy-2-methylbenzaldehyde, disappeared in the experimental group. Element analysis indicated that the content of O and N increased after the addition of the optimal compound additive.
ACKNOWLEDGMENTS Funding for this research was provided by the National Basic Research Program of China (2013CB228103) and the National Natural Science Foundation of China (51676179).
NOMENCLATURE DMF = N, N-dimethylformamide η = viscosity M = moisture content ANOVA = analysis of variance GC-MS = gas chromatography-mass spectrometer
REFERENCES 1. Chen, T.; Wu, C.; Liu, R.; Fei, W.; Liu, S., Effect of hot vapor filtration on the characterization of bio-oil from rice husks with fast pyrolysis in a fluidized-bed reactor. Bioresource Technology 2011, 102 (10), 6178-85. 2. Czernik, S.; Scahill, J.; Diebold, J., The production of liquid fuel by fast pyrolysis of biomass. Journal of solar energy engineering 1995, 117 (1), 2-6. 3. Aysu, T.; Durak, H.; Güner, S.; Bengü, A. Ş.; Esim, N., Bio-oil production via catalytic pyrolysis of Anchusa azurea : Effects of operating conditions on product yields and chromatographic characterization. Bioresource Technology 2016, 205, 7-14. 4. Bridgwater, A. V., Principles and practice of biomass fast pyrolysis processes for liquids. Journal of Analytical & Applied Pyrolysis 1999, 51 (1–2), 3-22. 5. Aysu, T.; Sanna, A., Nannochloropsis algae pyrolysis with ceria-based catalysts for production of high-quality bio-oils. Bioresource Technology 2015, 194, 108-116. 6. Bridgwater, A. V., Review of fast pyrolysis of biomass and product upgrading. Biomass & Bioenergy 2012, 38 (2), 68-94. 7. Oasmaa, A.; Kuoppala, E.; Solantausta, Y., Fast pyrolysis of forestry residue. 2. physicochemical composition of product liquid. Energy 2003, 17 (2), 433--443. 8. (a) Diebold, J. P.; Milne, T. A; Czernik, S.; Oasmaa, A.; Bridgwater, A. V.; Cuevas, A.; Gust, S.; Huffman, D.; Piskorz, J., Proposed specifications for various grades of pyrolysis oils. Developments in thermochemical biomass conversion, Springer Netherlands 1997, 433-447; (b) Diebold, J. P., A review of the chemical and physical mechanisms of the storage stability of fast 9
ACS Paragon Plus Environment
Energy & Fuels
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60
pyrolysis bio-oils. Golden, CO: National Renewable Energy Laboratory 2000. 9. Oasmaa, A.; Kuoppala, E., Fast pyrolysis of forestry residue. 3. Storage stability of liquid fuel. Energy & Fuels 2003, 17 (4), 1075-1084. 10. Kim, S. W.; Koo, B. S.; Ryu, J. W.; Lee, J. S.; Kim, C. J.; Dong, H. L.; Kim, G. R.; Sun, C., Bio-oil from the pyrolysis of palm and Jatropha wastes in a fluidized bed. Fuel Processing Technology 2013, 108, 118-124. 11. (a) Yu, W. J.; Tang, Y.; Mo, L. Y.; Chen, P.; Lou, H.; Zheng, X. M., One-step hydrogenation-esterification of furfural and acetic acid over bifunctional Pd catalysts for bio-oil upgrading. Bioresource Technology 2011, 102 (17), 8241-6; (b) Xiu, S.; Shahbazi, A., Bio-oil production and upgrading research: A review. Renewable & Sustainable Energy Reviews 2012, 16 (7), 4406-4414. 12. Wang, S.; Gu, Y.; Liu, Q.; Yao, Y.; Guo, Z.; Luo, Z.; Cen, K., Separation of bio-oil by molecular distillation. Fuel Processing Technology 2009, 90 (5), 738-745. 13. Zhang, Y. N.; Hu, G. P.; Brown, R. C., Life cycle assessment of the production of hydrogen and transportation fuels from corn stover via fast pyrolysis. Environmental Research Letters 2013, 8 (8), 221-229. 14. Stanzione III, J. F. S.; Giangiulio, P. A.; Sadler, J. M.; Scala, J. J. L.; Wool, R. P., Lignin-based bio-oil mimic as biobased resin for composite applications. Acs Sustainable Chem Eng 2013, 1 (4), 419-426. 15. Oasmaa, A.; Czernik, S., Fuel oil quality of biomass pyrolysis oils state of the art for the end users. Energy & Fuels 1999, 13 (4), 914-921. 16. Kuzhiyil, N.; Dalluge, D.; Brown, R. C.; Kuzhiyil, N.; Dalluge, D.; Brown, R. C. In Biomass Pretreatment to Improve Bio-Oil Stability, Aiche Meeting, 2010. 17. Li, Y.; Zhang, C.; Liu, Y.; Hou, X.; Zhang, R.; Tang, X., Coke deposition on Ni/HZSM-5 in bio-oil hydrodeoxygenation processing. Energy & Fuels 2015, 29(3), 1722-1728. 18. Peng, J.; Chen, P.; Lou, H.; Zheng, X., Upgrading of bio-oil over aluminum silicate in supercritical ethanol. Energy & Fuels 2008, 22 (5), 3489-3492. 19. Jiang, X.; Ellis, N., Upgrading bio-oil through emulsification with biodiesel: thermal stability. Energy & Fuels 2009, 24 (4), 2699-2706. 20. Hu, X.; Lu, G., Bio-oil steam reforming, partial oxidation or oxidative steam reforming coupled with bio-oil dry reforming to eliminate CO2 emission. International Journal of Hydrogen Energy 2010, 35 (13), 7169-7176. 21. (a) Zhu, J. F.; Wang, J. C.; Li, Q. X., Transformation of bio-oil into BTX by bio-oil catalytic cracking. Chinese Journal of Chemical Physics 2013, 26 (4), 477-483; (b) Diebold, J.; Phillips, S.; Dan, T.; Scahill, J.; Feik, C.; Czernik, S., catalytic Catalytic upgrading of biocrude oil vapors to produce hydrocarbons for oil refinery applications. A.C.S. Division of Fuel Chemistry 1994, 39, 1043-1043 22. Capunitan, J. A.; Capareda, S. C., Characterization and separation of corn stover bio-oil by fractional distillation. Fuel 2013, 112 (10), 60-73. 23. Diebold, J. P.; Czernik, S., Additives to lower and stabilize the viscosity of pyrolysis oils during storage. Energy & Fuels 1997, 11 (5), 1081-1091. 24. Oasmaa, A.; Kuoppala, E.; Selin, J. F.; Gust, S. A.; Solantausta, Y., Fast pyrolysis of forestry residue and pine. 4. Improvement of the product quality by solvent addition. Energy & Fuels 2004, 18 (5), 1578-1583. 10
ACS Paragon Plus Environment
Page 10 of 11
Page 11 of 11
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60
Energy & Fuels
25. Kim, T. S.; Kim, J. Y.; Kim, K. H.; Lee, S.; Choi, D.; Choi, I. G.; Choi, J. W., The effect of storage duration on bio-oil properties. Journal of Analytical & Applied Pyrolysis 2012, 95, 118–125. 26. Mante, O. D.; Agblevor, F. A., Storage stability of biocrude oils from fast pyrolysis of poultry litter. Waste Management 2012, 32 (1), 67-76. 27. Zhang, L.; Liu, R.; Yin, R.; Mei, Y.; Cai, J., Optimization of a mixed additive and its effect on physicochemical properties of bio-oil. Chemical Engineering & Technology 2014, 37 (7), 1181–1190. 28. Yin, R.; Zhang, L.; Liu, R.; Mei, Y.; Yu, W., Optimization of composite additives for improving stability of bio-oils. Fuel 2016, 170, 1-8. 29. Anderson-Cook, C. M.; Borror, C. M.; Montgomery, D. C., Response surface design evaluation and comparison. Journal of Statistical Planning & Inference 2009, 139 (2), 629-641. 30. Brown, J. N.; Brown, R. C., Process optimization of an auger pyrolyzer with heat carrier using response surface methodology. Bioresource Technology 2012, 103 (1), 405-14. 31. Mugendiran, V.; Gnanavelbabu, A.; Ramadoss, R., Parameter optimization for surface roughness and wall thickness on AA5052 aluminium alloy by incremental forming using response surface methodology. Procedia Engineering 2014, 97, 1991-2000.
11
ACS Paragon Plus Environment
