Thermogravimetric kinetic analysis of Nannochloropsis oculata combustion in air atmosphere

Abstract

The thermal behavior of Nannochloropsis oculata combustion in air atmosphere were investigated by performing experiments on STA PT1600 Thermal Analyzer at heating rates of 10°C/min, 40°C/min and 70°C/min and range of temperatures from room temperature to 1200°C. The kinetic parameters were evaluated by using Kissinger and Ozawa methods. The result showed that Nannochloropsis oculata combustion occurred in five stages. Started with initial devolatilization, the main thermal decomposition and combustion process, transition stage, the combustion of char and the last stage was the slow burning reaction of residual char. In line with increasing heating rate, the mass loss rate increased as well, but it delayed the thermal decomposition processes toward higher temperatures. The average activation energy at the main thermal decomposition stage and the stage of char combustion were approximately 251 kJ/mol and 178 kJ/mol, respectively.

Graphical abstract

Keywords

Nannochloropsis oculata / combustion / kinetic parameters / air atmosphere / thermogravimetric

1 Introduction

The use of fossil fuels in the long-term faces problems due to the limited amount of resources and their greenhouse effect caused by CO₂ emissions from the combustion processes [1,2]. Fossil fuels have the greatest contribution to greenhouse gas emissions [2,3]. In 2006, fossil fuels CO₂ emissions accounted for nearly 29 billion tons [4] and became a serious threat for the environment and human life because of their global warming impact [5]. Hence, exploring alternative renewable fuels whose sustainability are assured and friendly environment suppressing the greenhouse effect is urgent to replace fossil fuels.

Microalgae are a potential source of alternative fuels for fossil fuels substitution due to two reasons. First, their fast growth rate [6] will continuously ensure the availability. Second, their ability to absorb large amounts of CO₂ in the photosynthesis process will neutralize the CO₂ generated from the combustion process. Microalgae generally double their biomass within 24 h. The times required for the doubling of biomass during the exponential growth are commonly as short as 3.5 h [7]. Commercial cultivation of microalgae can achieve a productivity of 15 g dry biomass/cm²/day or 54 ton/hectare/year [8]. Microalgae produce 30–100 times more energy per hectare than terrestrial crops [9]. Their biomass contains approximately 50% carbon by dry weight and all carbon is usually derived from carbon dioxide [10]. Producing 100 tons of algal biomass requires approximately 183 tons of CO₂ [7]; thereby, microalgal biomass production is essential for global warming mitigation. Thus, microalgae have excellent prospects as a future alternative fuel instead of fossil fuels.

Nannochloropsis oculata (N. oculata) is a single-cell algae that belongs to the Eustigmatophyceae class, usually cultivated in fish hatcheries as feed rotifers. It has a great potential for marine biotechnology exploitation [11] on account of its high lipid content [12]. The maximum biomass and lipid productivity in semicontinuous culture are 0.480 g/l/d and 0.142 g/l/d with 2% of CO₂ aeration, respectively [12]. The abundance and lipid content of the biomass, which are cultivated in the photobioreactor under the dosage of urea and triple superphosphate (TSP) fertilizer of 40–60 part per million, are between 1800× 10⁴−2500×10⁴ cells/mL and between 11%–12%, respectively [13]. This microalgae is rich in proteins, pigments, and polyunsaturated fatty acids [14–16] and is widely used as feed in aquaculture [17,18]. In recent years, Nannochloropsis has become potential microalgae for biofuel production [19,20].

Previous research on microalgae as fuel focuses on the cultivation method for optimization of biomass production, either in open pond [21,22] or in closed photobioreactor [23–27]. Likewise, intensive research has been done relating to the extraction methods to produce biodiesel [28,€29], ethanol [30–33] and biogas [34–37]. However, the study on direct combustion of microalgal biomass as fuel is rarely done.

A proper combustion method of biomass materials is critical to produce maximum energy and minimize the pollution impact on the environment. It requires in-depth knowledge about the thermal decomposition behavior of biomass combustion so that the reactor can be designed according to their characteristics. The characteristics of biomass combustion, which are important to be investigated, include kinetic parameters, because they determine the step of combustion processes. The knowledge of thermal decomposition kinetics of biomass materials is necessary for the design of appropriate combustion reactors. Therefore, it is crucial to perform an experiment for thermal behavior analysis of biomass combustion, in order to predict precisely its characteristic in real combustion systems. For this goal, thermogravimetric analysis (TGA) has been generally used since it is the easiest and the most effective technique to observe the combustion profile of biomass fuel. The temperature at which combustion starts and ends, the maximum reactivity temperature, ash amount and total combustion time can be investigated by this method. Moreover, the kinetic parameters of thermal decomposition reaction can also be estimated by plotting the mass loss rate as a function of temperature and time. However, the kinetics of N. oculata combustion in air atmosphere has not been found in the literature.

In this paper, the thermal decomposition behavior of the N. oculata during the combustion process in air atmosphere was investigated by using the thermogravimetric technique. Besides, the mass loss, the mass loss rate and differential thermal were analyzed at varying heating rates to predict the thermal behavior of the material. Furthermore, the decomposition kinetic parameters were evaluated by Kissinger and Ozawa methods.

2 Methods

2.1 Materials and their properties analyses

The origin of the materials and detail of their properties were presented in Ref. [38]. N. oculata samples were obtained from cultivation in Brackish Water Aquaculture Institute (BBAP) Situbondo, East Java, Indonesia. The medium culture is seawater whose salinity and pH are 3.4€% and 8.6, respectively. The microalgae was cultivated with fertilizers whose compositions were KNO₃ = 1 kg, NaH₂PO₄ = 100 g, Na₂EDTA= 100 g, FeCl₃ = 13 g and were dissolved in 10 L of water. The use of fertilizers in the cultivation medium was 1 ml/liter of media. The cultivation was performed for seven days.

The microalgae harvesting was done by precipitating with caustic soda (NaOH); then they were filtered and washed with distilled water. Thereafter, the biomass sediment was dried in the oven at 80°C for 24 h. The chunks of dried microalgae were pulverized by using mortar to be fine particles, and then were finally stored in desiccators.

The chemical composition of algal biomass was determined by using Energy-dispersive X-ray (EDX) spectrometry. The proximate analysis was conducted by performing an experiment in the Thermal Gravimetric Analyzer (STA PT1600 by Linseis), which was primarily described by Beamish [39] and Mayoral et al.[40].The heating value evaluated by a linear correlation equation, which was proposed previously by Nhuchhen and Abdul Salam [41], as presented in Eq. (1). The respective data shown in Table 1, which are quoted from Ref. [38].

(1)\mathrm{HHV}=\mathrm{19.2880}-{\displaystyle \frac{\mathrm{0.2135}\mathrm{VM}}{\mathrm{FC}}}+{\displaystyle \frac{\mathrm{0.0234}\mathrm{FC}}{A}}-{\displaystyle \frac{\mathrm{1.9584}A}{\mathrm{VM}}},

where HHV is the higher heating value (MJ/kg); VM, FC and A are volatile matter, fixed carbon and ash content of biomass, respectively, by dry weight basis.

2.2 Thermal analyses methods

The thermal analyses of the samples were conducted by using simultaneous thermal analysis (STA) PT1600. The samples weighing approximately 20 mg were loaded into an Al₂O₃ ceramic crucible for each run under non-isothermal conditions at the preselected heating rate from ambient temperature to 1200°C. Three heating rates, namely 10°C/min, 40°C/min and 70°C/min were used to understand the thermal kinetics. The flow rate of oxidizing atmosphere inside the furnace during temperature programmed combustion was determined by a continuous air flow of 100 ml/min. For each experiment, the thermal gravimetric (TG), differential thermal gravimetric (DTG) and differential thermal analysis (DTA) curves as a function of time and temperature were obtained as the output of the experiment.

2.3 Reaction kinetics

The kinetics of the biomass thermal decomposition is extremely complex owing to the presence of the numerous chemical compositions of the components within the biomass material that are simultaneously being pyrolysed and oxidized. However, TGA is a widely used method to investigate the reaction kinetics of biomass decomposition process because of its simplicity and retrieval of a multitude of valuable information from a thermogram. Based on the thermogravimetric data, the thermal behavior of the biomass samples as well as their kinetics can be analyzed from their mass loss as a function of temperature. The kinetic parameters (i.e. activation energy E, pre-exponential factor A and the order of the reaction n ) of the biomass decomposition can be estimated based on thermogravimetric graph by isoconversional method. This method is applied to describe more complicated processes where lots of parallel and consecutive chemical reactions are running concurrently; however, their mechanisms are not precisely understood [42].

The solid state decompositions can be represented by the reaction scheme in which the biomass degrades thermally, and forms solid residue and volatiles [43]. Hence, the kinetic analysis of solid state decompositions is usually based on a single-step kinetic reaction. The mass loss data of thermogravimetric curve can be recalculated as the following conversion degree (\alpha):

(2)\alpha ={\displaystyle \frac{\mathrm{\Delta }m}{\mathrm{\Delta }{m}_{\mathrm{tot}}}}={\displaystyle \frac{m_i-m_T}{m_i-m_{\infty }}},

where m_i is the initial mass of biomass, m_T is the mass at temperature T and m_{\infty } is the residual mass at the end of the particular stage of reaction. This conversion declares the amount of samples having been decomposed.

Isoconversional method uses linear heating rate to raise the temperature, so the temperature rise is calculated by

(3)T=T_i+\beta t,

where \beta unit is °C/min, T_i is the initial temperature, and t is time.

Decomposition rates as a function of temperature and conversion degree can be expressed as

(4){\displaystyle \frac{\mathrm{d}\alpha }{\mathrm{d}t}}=k\left(T\right)f\left(\alpha \right).

Reaction rate constants as a function of temperature is described in the Arrhenius equation:

(5)k\left(T\right)=A{\mathrm{e}}^{-E/RT},

where E is the activation energy (J/mol), R is the ideal gas constant (8.314 J/mol·K), T is the absolute temperature in Kelvin (Kelvin= °C+ 273), and A is the pre-exponential factor (min^–1).

If the decomposition reactions of solids are considered as the one-step reaction [44,45], the function of conversion degree f\left(\alpha \right) can be expressed as

(6)f\left(\alpha \right)={\left(\mathrm{1}-\alpha \right)}^n,

where n is the order of the reaction.

Thus, the decomposition reaction rate equation can be written as

(7){\displaystyle \frac{\mathrm{d}\alpha }{\mathrm{d}t}}=A{\mathrm{e}}^{-E/RT}{\left(\mathrm{1}-\alpha \right)}^n.

For the dynamic process, the heating rate is \beta ={\displaystyle \frac{\mathrm{d}T}{\mathrm{d}t}} ; thus, the substitution to Eq. (7) gives the following relationship:

(8){\displaystyle \frac{\mathrm{d}\alpha }{\mathrm{d}T}}={\displaystyle \frac{A}{\beta }}{\mathrm{e}}^{-E/RT}{\left(\mathrm{1}-\alpha \right)}^n.

There are a number of methods that have been developed for deriving kinetic parameters A, E and n from dynamic TG experiments based on Eq. (8). In this paper, kinetic parameters were solved by differential methods of Kissingerand integral method of Ozawa.

3 Results and discussion

3.1 Thermal analyses results

The proximate, chemical composition and calorific value analysis of N. oculata biomass are listed in Table 1. Figure 1 showed the TG, DTG and DTA curves obtained from thermogravimetric experiments in the decomposition process of approximately 20 mg samples, in the air atmosphere, at a heating rate of 10°C/min. According to these results, it could be observed that the combustion of N. oculata samples were the kind of severe chemical change releasing plenty of heat, whose process was divided into five stages. Each stage was determined by the relation to approximate starting and end points of DTG curve changes which denote that the thermal breakdown of organic matters of samples has occurred [46]. Of the overall thermal degradation stages of the sample, there were two main stages attributed to devolatilization and combustion, namely at Stage 2 and Stage 4.

Stage 1 was the temperature of initial devolatilization, indicated by the presence of the first basin in DTG curve and an unapparent endothermic peak was found in DTA curve. This stage corresponds to the loss of moisture and the very light volatile compounds [47].

Stage 2 was characterized by the major weight loss. At the beginning of Stage 2, the endothermic process decomposed the samples and released volatile. With the mass losing, the endothermic peak on DTA signal turned to an exothermic one at around 300°C associated with the combustion of volatiles. The energy released by combustion sparked a subsequent decomposition process shown by the sudden increase of mass loss rate. According to the previous study, this stage corresponds to the main decomposition, release and combustion of organic components, especially resulted from the thermal cracking of proteins, carbohydrates and lipids [48]. Plenty of volatiles which were released in a short time, shifted the diffusion layer between volatiles and oxygen away from the surface of particles. Therefore, the lower diffusion of oxygen could not burn char at such a low temperature.

Stage 3, indicated by the slight decrease of TG curve, was the transition stage. In this stage, the decomposition rate of volatile began to decrease so that the char was surrounded by a thin layer of volatile. Therefore, the diffusion layer between volatile components and oxygen was very close to the char surface. Consequently, a large number of oxygen diffused into char surface. The char could be burned when the temperature reached the char ignition temperature. Therefore, in this stage the remaining volatile and char were burned at the same time.

The char was degraded slowly in Stage 3, and then it was decomposed and burned rapidly in Stage 4 since the temperature reached char ignition temperature. It could be seen from the DTA curve that the initial reaction of Stage 4 was endothermic and then turned into exothermic. Since the combustion of volatile was close to the end, sufficient oxygen was diffused into the surface of char, resulting in the fast combustion of char and producing a lot of heat, which was characterized by the appearance of an exothermic peak on the DTA curve at around 750°C. It could be observed from the DTG curve that the rate of mass loss of Stage 4 was lower than that of Stage 2.This might have been affected by the fact that the burning of char produced ash, which surrounded the surface of char. This ash layer inhibited the diffusion of oxygen to the surface of char. Consequently, the burning rate at this stage decreased and caused a decrease of mass loss rate, as well.

Stage 5 was a slow burning reaction of residual char surrounded by ash, and coupled with very slow decomposition which was characterized by a very slight decrease of the TG curve, indicating that the mass loss was very slow. The peak of the DTG curve in this stage was attributable to the decomposition of ash.

3.2 Effect of heating rate

Figure 2 is the diagrammatic model of TG-DTG curves of N. oculata combustion. The initial decomposition temperature of the Stage 2 (T₁) to the end of the decomposition temperature of Stage 4 (T₆) and residual mass at 1200°C could be obtained from Fig. 2 at each heating rate as tabulated in Table 2.

Figure 3 and Table 2 indicated that the heating rates influenced the temperature ranges in the combustion processes. Figure 3 showed that as the heating rate increased, the initial decomposition temperature decreased and tended to delay the thermal decomposition processes toward higher temperatures, so that the range between the initial decomposition temperature of Stage 2 (T₁) to the end of the decomposition temperature of Stage 4 (T₆) was widening. As discussed by Vamvuka and Sfakianakis [49], this phenomenon is caused by the fact that, at a given temperature, higher heating rate makes the material reach that temperature in a shorter time. The shorter induction time was liable to push volatile evolution to a higher temperature.

Table 2 revealed that the residual mass at 1200°C increased in line with the increasing heating rate. This phenomenon was caused by the fact that at higher heating rate, the temperature gradient between inside and outside was greater. Consequently, there was limited time for the structure of particle to relax and respond to the thermal input, which did not support the release of the volatile matter. Furthermore, when there is less time to burn, at a given temperature, there is insufficient time to burn out the particle [50]. Conversely, at lower heating rate, there is sufficient time for the biomass particles to experience gradual heating that causes the improvement and more effective heat transfers to the inner portions and among particles. Thus, the thermal cracking of particle occurred more effectively with the result of more weight loss in the form of volatiles. Therefore, the residue at the end of combustion reactions decreased due to the decreased heating rate.

Figure 3 showed that the mass loss rate increased with the increasing heating rate. As discussed earlier, the combustion of N. oculata samples was the kind of severe chemical change. These include softening (similar to phase change) and swelling particles, bond breaking, evaporation, volatile evolution and combustion, char forming and burning [51]. The majority of these mechanisms required thermal input. As a consequence of an escalation in heating rate, there was an adequate thermal shock to the particle; thus the average kinetic energy and speed of molecules increased and provided more molecule energy to break any existing bonds and formed new ones in a short time. As a result, there was an increase in the reaction rate of samples with oxygen.

At the heating rate of 70°C/min, starting from the beginning of Stage 3, the DTA curve showed a very steep slope (see Fig. 4). This indicated that, at high heating rate, volatile products in Stage 2 were burned out and continued by the rapid decomposition reaction of char. In these cases, residual volatiles and char were not burned at the same time; hence, there was no heat released. This was in contrast with what occurred at the heating rate of 10°C/min and 40°C/min, in which the DTA curve encountered a slight slope in Stage 3.

3.3 Kinetic analysis of the combustion process

The kinetic parameters (activation energy and pre-exponential factor) in this study were estimated by using both Kissinger and Ozawa methods. These methods are two sorts of non-isothermal kinetics analysis, which benefits for fast measurement, a wide range of temperature and broad usage.

3.3.1 Kissinger method

Kissinger’s method [52] is one of the non-isothermal methods to determine the activation energy at some heating rates. It is based on the fact that the decomposition reaction rate (dα/dt) increases toward a maximum value by increasing the reaction temperature, indicated by the peak mass loss rate in DTG curve [53]. When the temperature achieves the maximum value, the effect of heating rate on the peak temperature follows Eq. (9) [45].

(9)\ln \left({\displaystyle \frac{\beta }{T_{\mathrm{P}}^{\mathrm{2}}}}\right)=-{\displaystyle \frac{E}{R{T}_{\mathrm{p}}}}+\mathrm{l}\mathrm{n}\left({\displaystyle \frac{AE}{R}}\right).

By assuming

Y=\ln \left({\displaystyle \frac{\beta }{T_{\mathrm{P}}^{\mathrm{2}}}}\right),\hspace{0.17em}X={\displaystyle \frac{\mathrm{1}}{T_{\mathrm{p}}}},\hspace{0.17em}m=-{\displaystyle \frac{E}{R}},\hspace{0.17em}C=\ln \left({\displaystyle \frac{AE}{R}}\right)

Equation (9) expresses the straight-line equation

Y=mX+C

with a slope of m=-E/R obtained from the plot between X=\mathrm{1}/T_{\mathrm{p}} and Y=\ln \left(\beta /T_{\mathrm{p}}^{\mathrm{2}}\right). As stated by Kissinger, the activation energy is determined by Eq. (10).

(10){\displaystyle \frac{\mathrm{d}\left(\ln \left(\beta /T_{\mathrm{p}}^{\mathrm{2}}\right)\right)}{\mathrm{d}\left(\mathrm{1}/T_{\mathrm{p}}\right)}}=-{\displaystyle \frac{E}{R}},

where T_{\mathrm{p}} is the peak temperature.

Equation (10) is used to calculate the activation energy, E, for a simple decomposition reaction without regard to the reaction order by performing differential thermal analysis patterns at a number of heating rates [52]. By obtaining the values of E, the pre-exponential factor A can be obtained from the intercept of isoconversional line with Y axis.

According to Figs. 2 and 3, the maximum reaction temperature of Stage 2 (T₂) and Stage 4 (T₅) of each heating rate was listed in Table 2. The plots of activation energy determination for each main stage of mass loss corresponding to the combustion of the sample with the heating rates of 10°C/min, 40 °C/min and 70°C/min were depicted in Fig. 5. The parameter values, activation energy and pre-exponential factor (lnA) in Kissinger formula were compiled in Table 3.

3.3.2 Ozawa method

Ozawa’s method is an integral technique, which does not need the information of the reaction mechanism to calculate the activation energy. This method reveals straight lines at different heating rates based on the relationship between the logarithm of heating rate and inverse temperature at constant mass loss. The activation energy of degradation is determined from the slope of linear relationships. It should be mentioned that this method can be used only for one-step reaction [54]. For the constant degree of conversion \alpha, the formula for calculating the activation energy E related to heating rate, temperature and the constant of an ideal gas (R) of the Ozawa method is expressed in Eq. (11) [55].

(11)\ln \beta =\ln \left(\mathrm{0.0048}{\displaystyle \frac{AE}{Rg\left(\alpha \right)}}\right)-\mathrm{1.052}{\displaystyle \frac{E}{RT}}.

According to Eq. (11), activation energy could be derived from the slope of \ln \beta versus \mathrm{1}/T. The peaks of temperature change in DTG curves as the effect of increasing heating rate followed Eq. (11). In relation to Figs. 2 and 3, parameter values of Ozawa were displayed in Table 4, while the graph of \ln \beta depending on \mathrm{1}/T_{\mathrm{p}} was illustrated in Fig. 6.

Based on these two methods, the results of kinetics parameters were almost equal, as well as the fitting degree (R²) of both Kissinger and Ozawa methods, which were close to each other, namely 0.9809 and 0.9974 for Kissinger and 0.9824 and 0.9978 for Ozawa in Stage 2 and Stage 4, respectively. Hence, in the present study, the values of activation energy and pre-exponential factor were calculated from the average value of both methods.

The average activation energy in Stage 2 was greater than that of Stage 4, which was approximately 251 kJ/mol and 178 kJ/mol, respectively. Activation energy is an obstacle that must be overcome before a chemical reaction is generated, and higher value of activation energy means more difficult of a reaction occurs [55]. This result indicated that the reactivity and sensitivity of reaction rate in Stage 2 were lower than those in Stage 4. It was probably related to the thermal breakdown of organic components in Stage 2 constrained by a tough cell wall, which caused decomposition having taken more energy. This phenomenon will be revealed in future studies.

4 Conclusions

Thermal decomposition of N. oculata combustion under the air atmosphere was investigated by using TGA at different heating rates. Kinetic parameters in terms of apparent activation energy and pre-exponential factor were determined. Thermal decomposition of N. oculata combustion occurred in five stages with two major mass loss stages due to devolatilization and combustion. Increasing the heating rate resulted in increasing mass loss rates, but it delayed thermal decomposition processes toward higher temperatures. The average activation energy was approximately 251 kJ/mol at the first major mass loss stage and approximately 178 kJ/mol at the second one.

References

[1] Khan S A, Rashmi , Hussain M Z, Prasad S, Banerjee U C. Prospects of biodiesel production from microalgae in India. Renewable & Sustainable Energy Reviews, 2009, 13(9): 2361–2372

[2] Tabatabaei M, Tohidfar M, Jouzani G S, Safarnejad M, Pazouki M. Biodiesel production from genetically engineered microalgae: future of bioenergy in Iran. Renewable & Sustainable Energy Reviews, 2011, 15(4): 1918–1927

[3] De La Torre Ugarte D, Walsh M E, Shapouri, H, Slinsky, S P. The economic impacts of bioenergy crop production on US agriculture. Oak Ridge National Laboratory, 2000, 292(5519):41

[4] Banerjee A, Sharma R, Chisti Y, Banerjee U C. Botryococcus braunii: a renewable source of hydrocarbons and other chemicals. Critical Reviews in Biotechnology, 2002, 22(3): 245–279

[5] Sawayama S, Minowa T, Yokoyama S. Possibility of renewable energy production and CO₂ mitigation by thermochemical liquefaction of microalgae. Biomass and Bioenergy, 1999, 17(1): 33–39

[6] Ross A B, Biller P, Kubacki M L, Li H, Lea-Langton A, Jones J M. Hydrothermal processing of microalgae using alkali and organic acids. Fuel, 2010, 89(9): 2234–2243

[7] Chisti Y. Biodiesel from microalgae. Biotechnology Advances, 2007, 25(3): 294–306

[8] Metting F B Jr. Biodiversity and application of microalgae. Journal of Industrial Microbiology & Biotechnology, 1996, 17(5-6): 477–489

[9] Demirbas A. Use of algae as biofuel sources. Energy Conversion and Management, 2010, 51(12): 2738–2749

[10] Mirón A S, García M C C, Gómez A C, Camacho F G, Grima E M, Chisti Y. Shear stress tolerance and biochemical characterization of phaeodactylum tricornutum in quasi steady-state continuous culture in outdoor photobioreactors. Biochemical Engineering Journal, 2003, 16(3): 287–297

[11] Poncet J M, Véron B. Cryopreservation of the unicellular marine alga, Nannochloropsis oculata. Biotechnology Letters, 2003, 25(23): 2017–2022

[12] Chiu S Y, Kao C Y, Tsai M T, Ong S C, Chen C H, Lin C S. Lipid accumulation and CO₂ utilization of Nannochloropsis oculata in response to CO₂ aeration. Bioresource Technology, 2009, 100(2): 833–838

[13] Suryanto H., Sukarni , Yanuhar U. Design Development of Effective Photobioreactor for Cultivation of Marine Microalgae as a Source of Renewable Energy (in Indonesian). The Research Report of National Strategic Grant, State University of Malang, Malang (2009)

[14] Volkman J K, Brown M R, Dunstan G A, Jeffrey S. The biochemical composition of marine microalgae from the class eustigmatophyceae. Journal of Phycology, 1993, 29(1): 69–78

[15] Lubián L M, Montero O, Moreno-Garrido I, Huertas I E, Sobrino C, González-del Valle M, Parés G. Nannochloropsis (eustigmatophyceae) as source of commercially valuable pigments. Journal of Applied Phycology, 2000, 12(3-5): 249–255

[16] Lee M Y, Min B S, Chang C S, Jin E. Isolation and characterization of a xanthophyll aberrant mutant of the green alga Nannochloropsis oculata. Marine Biotechnology (New York, N.Y.), 2006, 8(3): 238–245

[17] Osinga R, Kleijn R, Groenendijk E, Niesink P, Tramper J, Wijffels R H. Development of in vivo sponge cultures: particle feeding by the tropical sponge pseudosuberites aff. andrewsi. Marine Biotechnology (New York, N.Y.), 2001, 3(6): 544–554

[18] Ferreira M, Coutinho P, Seixas P, Fábregas J, Otero A. Enriching rotifers with “premium” microalgae. Nannochloropsis gaditana. Marine Biotechnology (New York, N.Y.), 2009, 11(5): 585–595

[19] Rodolfi L, Chini Zittelli G, Bassi N, Padovani G, Biondi N, Bonini G, Tredici M R. Microalgae for oil: strain selection, induction of lipid synthesis and outdoor mass cultivation in a low-cost photobioreactor. Biotechnology and Bioengineering, 2009, 102(1): 100–112

[20] Griffiths M J, Harrison S T L. Lipid productivity as a key characteristic for choosing algal species for biodiesel production. Journal of Applied Phycology, 2009, 21(5): 493–507

[21] Sanchez A, González A, Maceiras R, Cancela Á, Urrejola S. Raceway pond design for microalgae culture for biodiesel. Chemical Engineering Transactions, 2011, 25: 845–850

[22] Park J B K, Craggs R J, Shilton A N. Wastewater treatment high rate algal ponds for biofuel production. Bioresource Technology, 2011, 102(1): 35–42

[23] Sierra E, Acién F G, Fernández J M, García J L, González C, Molina E. Characterization of a flat plate photobioreactor for the production of microalgae. Chemical Engineering Journal, 2008, 138(1–3): 136–147

[24] Sato T, Yamada D, Hirabayashi S. Development of virtual photobioreactor for microalgae culture considering turbulent flow and flashing light effect. Energy Conversion and Management, 2010, 51(6): 1196–1201

[25] Hsieh C H, Wu W T. A novel photobioreactor with transparent rectangular chambers for cultivation of microalgae. Biochemical Engineering Journal, 2009, 46(3): 300–305

[26] Briassoulis D, Panagakis P, Chionidis M, Tzenos D, Lalos A, Tsinos C, Berberidis K, Jacobsen A. An experimental helical-tubular photobioreactor for continuous production of Nannochloropsis sp. Bioresource Technology, 2010, 101(17): 6768–6777

[27] Das P, Obbard J P. Incremental energy supply for microalgae culture in a photobioreactor. Bioresource Technology, 2011, 102(3): 2973–2978

[28] Wahlen B D, Willis R M, Seefeldt L C. Biodiesel production by simultaneous extraction and conversion of total lipids from microalgae, cyanobacteria, and wild mixed-cultures. Bioresource Technology, 2011, 102(3): 2724–2730

[29] Gong Y, Jiang M. Biodiesel production with microalgae as feedstock: from strains to biodiesel. Biotechnology Letters, 2011, 33(7): 1269–1284

[30] John R P, Anisha G S, Nampoothiri K M, Pandey A. Micro and macroalgal biomass: a renewable source for bioethanol. Bioresource Technology, 2011, 102(1): 186–193

[31] Harun R, Danquah M K. Influence of acid pre-treatment on microalgal biomass for bioethanol production. Process Biochemistry, 2011, 46(1): 304–309

[32] Harun R, Jason W S Y, Cherrington T, Danquah M K. Exploring alkaline pre-treatment of microalgal biomass for bioethanol production. Applied Energy, 2011, 88(10): 3464–3467

[33] Harun R, Danquah M K, Forde G M. Microalgal biomass as a fermentation feedstock for bioethanol production. Journal of Chemical Technology and Biotechnology (Oxford, Oxfordshire), 2010, 85(2): 199–203

[34] Mussgnug J H, Klassen V, Schlüter A, Kruse O. Microalgae as substrates for fermentative biogas production in a combined biorefinery concept. Journal of Biotechnology, 2010, 150(1): 51– 56

[35] Doušková I, Kaštánek F, Maléterová Y, Kaštánek P, Doucha J, Zachleder V. Utilization of distillery stillage for energy generation and concurrent production of valuable microalgal biomass in the sequence: biogas-cogeneration-microalgae-products. Energy Conversion and Management, 2010, 51(3): 606–611

[36] Razon L F, Tan R R. Net energy analysis of the production of biodiesel and biogas from the microalgae: haematococcus pluvialis and nannochloropsis. Applied Energy, 2011, 88(10): 3507–3514

[37] Collet P, Hélias A, Lardon L, Ras M, Goy R A, Steyer J P. Life-cycle assessment of microalgae culture coupled to biogas production. Bioresource Technology, 2011, 102(1): 207–214

[38] Sukarni, Sudjito, Hamidi N, Yanuhar U, Wardana I N G. Potential and properties of marine microalgae Nannochloropsis oculata as biomass fuel feedstock. International Journal of Energy and Environmental Engineering, 2014, 5(4): 279–290

[39] Beamish B B. Proximate analysis of New Zealand and Australian coals by thermogravimetry. New Zealand Journal of Geology and Geophysics, 1994, 37(4): 387–392

[40] Mayoral M C, Izquierdo M T, Andres J M, Rubio B. Different approaches to proximate analysis by thermogravimetry analysis. Thermochimica Acta, 2001, 370(1–2): 91–97

[41] Nhuchhen D R, Abdul Salam P. Estimation of higher heating value of biomass from proximate analysis: a new approach. Fuel, 2012, 99: 55–63

[42] Gašparovič L, Koreňová Z, Jelemenský Ľ. Kinetic study of wood chips decomposition by TGA. Chemical Papers, 2010, 64(2): 174–181

[43] Açıkalın K. Thermogravimetric analysis of walnut shell as pyrolysis feedstock. Journal of Thermal Analysis and Calorimetry, 2011, 105(1): 145–150

[44] Slopiecka K, Bartocci P, Fantozzi F. Thermogravimetric analysis and kinetic study of poplar wood pyrolysis. Applied Energy, 2012, 97: 491–497

[45] Biagini E, Fantei A, Tognotti L. Effect of the heating rate on the devolatilization of biomass residues. Thermochimica Acta, 2008, 472(1–2): 55–63

[46] Sonibare O O, Ehinola O A, Egashira R, KeanGiap L. An investigation into the thermal decomposition of Nigerian coal. Journal of Applied Sciences, 2005, 5(1): 104–107

[47] Chen C, Ma X, Liu K. Thermogravimetric analysis of microalgae combustion under different oxygen supply concentrations. Applied Energy, 2011, 88(9): 3189–3196

[48] Tang Y, Ma X, Lai Z. Thermogravimetric analysis of the combustion of microalgae and microalgae blended with waste in N₂/O₂ and CO₂/O₂ atmospheres. Bioresource Technology, 2011, 102(2): 1879–1885

[49] Vamvuka D, Sfakiotakis S. Combustion behaviour of biomass fuels and their blends with lignite. Thermochimica Acta, 2011, 526(1–2): 192–199

[50] Wang Q, Zhao W, Liu H, Jia C, Xu H. Reactivity and kinetic analysis of biomass during combustion. Energy Procedia, 2012, 17: 869–875

[51] Maloney D, Sampath R, Zondlo J. Heat capacity and thermal conductivity considerations for coal particles during the early stages of rapid heating. Combustion and Flame, 1999, 116(1–2): 94–104

[52] Kissinger H. Reaction kinetics in differential thermal analysis. Analytical Chemistry, 1956, 1957(29): 1702–1706

[53] Jiang G, Nowakowski D J, Bridgwater A V. A systematic study of the kinetics of lignin pyrolysis. Thermochimica Acta, 2010, 498(1–2): 61–66

[54] Hu S, Jess A, Xu M. Kinetic study of chinese biomass slow pyrolysis: comparison of different kinetic models. Fuel, 2007, 86(17–18): 2778–2788

[55] Ounas A, Aboulkas A, El Harfi K, Bacaoui A, Yaacoubi A. Pyrolysis of olive residue and sugar cane bagasse: non-isothermal thermogravimetric kinetic analysis. Bioresource Technology, 2011, 102(24): 11234–11238

RIGHTS & PERMISSIONS

Higher Education Press and Springer-Verlag Berlin Heidelberg