Energy and nutrient recovery efficiencies in biocrude oil produced via hydrothermal liquefaction of Chlorella pyrenoidosa

Abstract

Biofuels derived from biomass conversion have the potential to mitigate the problems caused by over-exploitation of fossil fuels in recent decades. In this work, Chlorella pyrenoidosa, a fast-growing and low-lipid microalga species, was converted into bio-crude oils via a hydrothermal liquefaction (HTL) process. Response surface methodology (RSM) was applied to investigate the effects of operating conditions including reaction temperature, retention time and total solid ratio of feedstock on bio-crude oil yield and quality. A higher heating value (HHV), carbon recovery (CR) and nitrogen recovery (NR) were used as indicators of bio-crude quality. Reaction temperature was found to be the most influential factor affecting the yield and quality of bio-crude oils. Compared with the bio-crude oil sample obtained at boundary conditions (260 °C, 30 min, 35 wt%), the bio-crude oils at two optimized operating conditions (280 °C, 60 min, 35 wt%; 300 °C, 60 min, 25 wt%) were observed to have higher yields (43.26% and 39.55% versus 25.65%), higher HHV (34.21 MJ kg⁻¹ and 36.51 MJ kg⁻¹ versus 30.59 MJ kg⁻¹), higher carbon recovery (72.18% and 68.18% versus 61.22%) and slightly lower nitrogen recovery (33.15% and 33.28% versus 35.88%). TGA, FT-IR, GC-MS and NMR analysis indicated that the optimized bio-crude oils were observed to have higher boiling point distributions (250–500 °C), a higher percentage of aliphatic functional groups (63–67%), a certain percentage of heteroatomic functionalities (21–26%) and a lower percentage of aromatic groups (1.5–3.3%).

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1 Introduction

Fossil fuel use and environmental protection are two of the most significant topics related to the sustainable development of human society and natural resources.¹ The traditional productions of biofuels mainly rely on food crops and lignocellulosic biomass, which may face limitations in future due to the decreasing amount of land resources and the increasing global population. It is essential to develop and transform renewable abundant and non-food biomass resources into high-performance and low-cost biofuels.² Microalgae have a great potential for biofuel production due to their higher photosynthetic efficiencies compared with terrestrial lignocellulosic biomass. They are increasingly viewed as suitable feedstock for the next-generation biofuels and chemicals.^3,4

A recent evaluation of biofuel production in Science proposed that supercritical fluids may be well-suited to enhance the chemical transformation of biomass to useful liquid and gaseous fuels.⁵ Hydrothermal technologies are physicochemical transformations in high-temperature (200–600 °C) and high-pressure (5–40 MPa) liquids such as water.⁶ When subjected to high temperature and pressure conditions, the dielectric constant of water decreases, rendering the water molecules fairly nonpolar. This makes water more affinitive to organic compounds. Besides, the dissociation constant of water dramatically increases, which promotes the splitting of water into H⁺ and OH⁻ ions to hydrolyze reacting substances and provide a homogeneous phase for reactions. Therefore, a drying pretreatment is not required near and above the critical point of water (372 °C, 22 MPa) since water serves as the solvent and the reactant during hydrothermal processing.⁷ As microalgae usually have a high water content, conventional algae-to-biodiesel technology requires drying which costs up to 75% of the total energy consumption.⁸ Therefore, hydrothermal technologies have an advantage for processing wet microalgae, including hydrothermal gasification⁹ to produce gaseous fuels and hydrothermal liquefaction (HTL)¹⁰ to produce liquid fuels, notably referred to as bio-crude oils.

HTL generally applies lower temperature (200–400 °C) and pressure (5–20 MPa) to convert organic substrates of the feedstock into bio-oils. Besides oil products, three co-products, including aqueous-phase, solid-phase and gaseous-phase products, are obtained during the HTL process. The aqueous phase after the separation of the bio-crude oils contains large quantities of organics, nitrogen, phosphate and other nutrients, which are vital for algae cultivation and unsuitable for a direct discharge into the environment without additional treatment.^11,12 To address this concern, our laboratory is systematically exploring approaches to integrate wastewater treatment through algae growth, carbon capture and bio-crude oil production via HTL into one system, which we call “Environment-Enhancing Energy (E²-Energy)”.^13–15 This provides a novel solution to combine the production of renewable energy with environmental protection in one synergistic process.

High-lipid microalgae have been the main feedstock for HTL processing.^16,17 Compared with high-lipid algae, low-lipid algae typically have a higher biomass yield and can grow in harsher environments. Thus, it has greater potential for the production of bio-crude oils via the HTL process. The quality and productivity of bio-crude oils via the HTL process are strongly dependent on the operating conditions. To determine the effect of the operating conditions on the distribution of product streams during the HTL process, researchers have investigated different biomass feedstocks,¹⁸ reaction temperatures,¹⁹ retention times,²⁰ ratios of biomass to water,²¹ operating pressures,²² process gases,²³ organic solvents,²⁴ and homogeneous and heterogeneous catalysts.²⁵ Although there have been many experimental investigations, most of them have been carried out adopting the traditional approach of “one-factor-at-a-time”. This kind of method generally employs a limited number of experiments, which leads to a lack of comprehensive perspective of the entire process. Besides, this classical method cannot be used to investigate the effects of different operating parameters on a variety of targets. Therefore, response surface methodology (RSM)²⁶ was adopted in this study. The objective of this study was to investigate the effect of operation conditions and their interactions on the yield and qualities of bio-crude oils via HTL processing of low-lipid microalgae. The optimum operating conditions for bio-crude oils using Chlorella pyrenoidosa as the feedstock were determined, and the chemical properties of the bio-crude oils were analyzed.

2 Materials and methods

2.1 Materials

Chlorella pyrenoidosa is a spherical, eukaryotic and unicellular alga.²⁷ It is a typical microalga with high-protein and low-lipid content and is cultured worldwide for foods and biofuels. In this study, C. pyrenoidosa was obtained from a health-food store as food-grade material (NOW FOODS, Bloomingdale, IL). The elemental compositions of C. pyrenoidosa were determined using an elemental analyzer (CE-440, Exeter Analytical Inc., North Chelmsford, MA). The macromolecular and chemical compositions of C. pyrenoidosa (Table 1) were analyzed according to the standard methods of the Association of Official Analytical Chemists (AOAC).

Table 1 Characteristics of Chlorella pyrenoidosa

Proximate analysis (%)		Chemical composition analysis (wt%)		Elemental analysis (wt%)
a On the basis of total weight.b Calculated by difference.
Moisture^a (wt%)	6.3	Crude fat	0.1	C	51
Dry solid (wt%)	94	Crude protein	71	H	6.6
Volatile solid	94	Non-fibrous carbohydrate	22	N	11
Ash	5.6	Lignocellulose	1.0	O^b	31.4

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2.2 Experimental design

A face-centered central composite design (FCCCD) was employed to conduct the experiment. Reaction temperature, retention time and total solid ratio were selected as independent factors in this study. The levels of reaction temperature, retention time and total solid ratio were determined to be in the range of 260–300 °C, 30–90 min and 15–35 wt%, respectively. The response variables for bio-crude oils were as follows: yield, higher heating value (HHV), carbon recovery (CR) and nitrogen recovery (NR). HHV, CR and NR were used as the indicators of the bio-crude quality.

2.3 Experimental procedure

The HTL experiments were carried out employing three stainless steel cylindrical reactors of 100 mL capacity (model 4593, Parr Instrument Col, Moline, IL). At the start of each test, 70 g feedstock samples were loaded into the reactor. After the reactor was sealed, pure nitrogen gas was used to purge the reactor three times, and the initial pressure was built up to 0.69 MPa, which is consistent with previous studies.^14,19 Afterwards, the reactor was heated by an electric heater up to the designated reaction temperature. The reaction temperature was maintained for a certain retention time corresponding to the levels of the experimental design. The stirring rate was kept at 300 rpm throughout the reaction. At the end of the reaction, the reactor was rapidly cooled by flowing tap water through the cooling coil located outside the reactor. When the temperature in the reactor decreased to room temperature, the gaseous products inside the reactor were collected using a gas sampling bag for a further analysis of the gas composition by GC. The recovery procedure for the HTL product streams was described in detail previously.¹⁴

2.4 Analytical approach

The HHV of the bio-crude oils was measured using an oxygen bomb calorimeter (model 6200, Parr Instrument Col, Moline, IL). The yield and the carbon and nitrogen recoveries of the bio-crude oils were calculated using the same approaches as those in the literature.^14,19 The CHN analyses of the bio-crude oils were performed using an elemental analyzer (CE-440, Exeter Analytical Inc., North Chelmsford, MA). The boiling point distribution of the bio-crude oils was analyzed using TGA (Q50, TA Instruments, New Castle, DE). Thermogravimetric analysis was carried out from 25 to 800 °C at the heating rate of 10 °C min⁻¹. For suppressing the mass transfer effect to a minimum, pure nitrogen (99.99% purity) was used as the carrier gas, and it was kept at a steady flow rate of 60 mL min⁻¹ during all the experiments. The chemical compositions of the bio-crude oils were analyzed using GC-MS (Agilent 7890A GC-5975C MS, Agilent Technologies, Santa Clara, CA) equipped with a flame ionization detector (FID) and a ZB-WAX column. The mass spectra were interpreted according to the NIST mass spectral database. FTIR and NMR spectroscopic data were processed to investigate the functionalities of the bio-crude oils. The FTIR spectra were collected using a Thermo Nicolet Nexus 670 Fourier-transform infrared spectroscope. A potassium bromide (KBr) beamsplitter was used for each analysis. With a resolution of 0.5 cm⁻¹, 128-scan adsorption interferograms were collected in the 4000–750 cm⁻¹ region for each spectrum. ¹H NMR spectra were collected using a 500 MHz Varian Unity spectrometer. The bio-oil samples (10 wt%) were dissolved in deuterated chloroform (CDCl₃). NMR tubes of 5 mm diameter were used. The ¹H NMR spectra were acquired across 32 transients with a 90° pulse angle, spinner frequency of 20 Hz and a sweep width of 8000 Hz.

3 Results and discussion

3.1 Development of the regression model

The complete design matrix and experimental results are shown in Table 2. Triplicate experiments were performed for each operating condition. The average values and standard deviations are both presented in Table 2. The experimental results from the design matrix are fitted to quantitative surface models using a second-order polynomial regression equation.²⁶ Then the qualities of the models were evaluated by analysis of variance (ANOVA) to establish their statistical significance at a confidence level of 95%. Table 3 shows the corresponding results of three tests of the models for the response variables, including the test of significance of the models and terms,²⁸ the test of lack of fit²⁹ and the coefficient of the determination (R²) test.^30,31 It should be noted that the proposed models are accurate under specified conditions, in terms of employing the specific reactor and the feedstock that were selected in the current study. Nevertheless, the models developed in this study are useful to investigate the effect of the operating conditions and their interactions on the productivity and quality of bio-crude oils from the HTL processing of Chlorella pyrenoidosa.

Table 2 FCCCD matrix of independent factors and response variables

Run no.	Point type	Reaction temperature (°C)	Retention time (min)	Total solid ratio (wt%)	Yield (wt%)	HHV (MJ kg^−1)	CR (%)	NR (%)
1	Factorial	260 (−1)	30 (−1)	15 (−1)	34.9 ± 1.14	30.3 ± 0.22	55.7 ± 0.48	30.6 ± 0.35
2	Factorial	260 (−1)	30 (−1)	35 (+1)	25.7 ± 0.41	30.6 ± 0.57	61.2 ± 1.76	35.9 ± 1.34
3	Factorial	260 (−1)	90 (+1)	15 (−1)	27.8 ± 0.39	31.7 ± 0.32	49.8 ± 0.61	24.3 ± 0.46
4	Factorial	260 (−1)	90 (+1)	35 (+1)	25.7 ± 0.82	31.6 ± 0.62	50.2 ± 1.58	24.9 ± 1.42
5	Factorial	300 (+1)	30 (−1)	15 (−1)	35.6 ± 0.76	34.1 ± 0.13	48.2 ± 0.27	25.3 ± 0.21
6	Factorial	300 (+1)	30 (−1)	35 (+1)	36.7 ± 2.04	35.5 ± 1.29	61.5 ± 1.92	37.6 ± 1.52
7	Factorial	300 (+1)	90 (+1)	15 (−1)	29.5 ± 0.83	34.7 ± 0.55	59.9 ± 0.97	33.8 ± 0.76
8	Factorial	300 (+1)	90 (+1)	35 (+1)	38.4 ± 2.45	35.9 ± 1.71	73.5 ± 2.69	38.9 ± 1.85
9	Axial	260 (−1)	60 (0)	25 (0)	31.8 ± 0.42	31.8 ± 0.11	60.9 ± 0.25	27.9 ± 0.26
10	Axial	300 (+1)	60 (0)	25 (0)	39.6 ± 0.79	36.5 ± 0.18	68.2 ± 0.41	33.3 ± 0.29
11	Axial	280 (0)	60 (0)	15 (−1)	41.7 ± 0.41	33.7 ± 0.13	61.7 ± 0.39	25.4 ± 0.24
12	Axial	280 (0)	60 (0)	35 (+1)	43.3 ± 2.04	34.2 ± 1.54	72.2 ± 2.32	33.2 ± 1.73
13	Axial	280 (0)	30 (−1)	25 (0)	34.5 ± 1.63	31.3 ± 0.71	51.7 ± 1.25	29.7 ± 0.89
14	Axial	280 (0)	90 (+1)	25 (0)	33.3 ± 0.45	32.6 ± 0.29	53.4 ± 0.53	27.7 ± 0.39
15	Center	280 (0)	60 (0)	25 (0)	41.7 ± 0.37	32.8 ± 0.16	61.9 ± 0.38	27.8 ± 0.25
16	Center	280 (0)	60 (0)	25 (0)	42.3 ± 1.23	32.7 ± 0.33	62.3 ± 0.59	27.7 ± 0.48
17	Center	280 (0)	60 (0)	25 (0)	41.2 ± 1.21	33.4 ± 0.15	67.2 ± 0.38	28.9 ± 0.27
18	Center	280 (0)	60 (0)	25 (0)	40.9 ± 2.08	33.2 ± 0.16	62.9 ± 0.39	29.2 ± 0.24
19	Center	280 (0)	60 (0)	25 (0)	42.8 ± 2.86	33.6 ± 0.47	63.7 ± 0.77	27.9 ± 0.53
20	Center	280 (0)	60 (0)	25 (0)	42.7 ± 0.81	33.3 ± 0.32	67.9 ± 0.65	29.4 ± 0.42

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Table 3 ANOVA evaluation of the response variables of bio-crude oils^a

Response variable	Yield		HHV		CR		NR
	SS	P	SS	P	SS	P	SS	P
a SS: sum of squares; p: p value for F test; R^2: determination coefficient; Adj. R^2: adjusted R^2; Adeq. precision: adequate precision.
Model	434.1	<0.0001	53.28	<0.0001	970.2	<0.0001	332.3	<0.0001
XT	114.9	<0.0001	43.07	<0.0001	112.9	0.0004	64.01	<0.0001
XRT	16.38	0.0041	2.093	0.0016	7.223	0.2124	8.842	0.0021
XSR	1.137	0.3764	0.967	0.0159	188.4	<0.0001	98.60	<0.0001
XT^2	68.13	<0.0001	1.521	0.0044	2.553	0.4468	11.87	0.0007
XRT^2	124.5	<0.0001	5.915	<0.0001	331.9	<0.0001	0.045	0.7756
XSR^2	9.642	0.0177	0.863	0.0208	31.11	0.02	1.454	0.1251
XTXRT	0.913	0.4038	0.252	0.1729	206.1	<0.0001	0.045	0.7756
XTXSR	57.78	<0.0001	0.749	0.0291	54.08	0.0045	16.82	0.0002
XRTXSR	27.01	0.0008	0.065	0.4680	2.641	0.4390	17.40	0.0002
Residual	11.99		1.141		40.72		5.193
Lack-of-fit	8.851	0.1399	0.497	0.6125	7.982	0.9262	2.351	0.5795
Pure error	3.142		0.652		32.74		2.842
R squared (R^2)	0.9820		0.9790		0.9597		0.9846
Adj. R^2	0.9658		0.9601		0.9235		0.9708
Predicted R^2	0.9211		0.9266		0.8433		0.8962
Adeq. precision	23.247		24.213		18.032		29.716

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3.2 Energy and nutrient recovery efficiencies in bio-crude oils

3.2.1 Yield. Fig. 1(a) indicates that at any given retention time, the oil yield first increased dramatically from 260 °C to around 280 °C. However, a gradual decrease was observed with a further increment of the temperature from 280 °C to 320 °C. This is because at temperatures higher than 280 °C, secondary decompositions may be triggered, which result in the formation of gases.³² In addition, the recombination reactions may be favored to promote the formation of char.³³ Therefore, the bio-oils decomposed at higher temperatures, which result in the decrease in the yield of bio-crude oils. The experimental results observed in this study showed similar trends to those reported in the literature.^34,35

Fig. 1 Response surface analysis for bio-crude oils via hydrothermal liquefaction of Chlorella pyrenoidosa: (a) yield; (b) HHV; (c) CR; (d) NR.

Fig. 1(a) also shows that the oil yield first increased notably with increasing retention time from 30 min to around 60 min and then decreased gradually for a longer retention time. This is because a shorter retention time may render an incomplete formation of the bio-crude oils, whereas a longer retention time leads to the decomposition of bio-crude oils and the formation of solid residue and gas. These trends agree with the experimental values reported by Yu et al.¹⁴ and Qu et al.³⁶ The authors observed a decrease in the heavy oil yield for longer retention times and concluded that a shorter retention time produced a larger amount of bio-oils.

Total solid ratio is another important factor affecting the yield of bio-crude oils. Fig. 1(a) shows that with an increase in the total solid ratio from 15 wt% to 25 wt%, the yield of bio-crude oils decreased first because the water in the HTL process acts both as a heat-transfer medium and as a reactant. Lower biomass to water ratios reduced the amount of leftover residues³⁷ and gas yield³⁸ during the HTL process, possibly due to enhanced extraction by a denser solvent medium.³⁹ At high biomass to water ratios, the interactions among molecules of biomass and those of water become less influential, which can suppress the dissolution of the biomass components.⁴⁰ Zou et al.⁴¹ investigated the sub- and supercritical water liquefaction of microalgae. It was reported that with an increase in the ratio of biomass to water from 7.5 wt% to 17.5 wt%, the bio-oil yield continuously decreased. According to the experimental results of the hydrothermal liquefaction of brown algae obtained by Li et al.,⁴² it was also observed that an increase in the biomass to water ratio from 3 wt% to 17 wt% led to a decreased yield of bio-oils, from 38.0 ± 1.7% to 26.1 ± 1.0%. This variation at lower total solid ratios showed good agreement with the results published in the literature. However, it can be found that with further increases in the total solid ratio from 25 wt% to 35 wt%, the yield of bio-crude oils goes up again. Besides, it was found that the weight of bio-crude oils obtained at a higher total solid ratio (35 wt%) was far higher than that at a lower total solid ratio (25 wt%), although the oil yields at both the two ratios were higher than that at an intermediate ratio (25 wt%).

3.2.2 HHV. Fig. 1(b) demonstrates the response surfaces of the HHV of bio-crude oils. It can be clearly seen that the factor of reaction temperature has the greatest effect on HHV. The HHV increased dramatically when the temperature increased from 260 to 300 °C. Table 2 shows that the maximum value of HHV of the bio-crude oils was 36.5 ± 0.18 MJ kg⁻¹, which was obtained at the temperature of 300 °C. The result is similar to that of bio-oils obtained by the literatures.^8,19 Ross et al.⁸ carried out the HTL of microalgae and concluded that the HHV of bio-oils at 300 °C using Chlorella ranged from 34.2 to 37.2 MJ kg⁻¹. Yu et al.¹⁹ investigated the HTL of Chlorella and reported that the HHV of bio-crude oils varied from 34.25 to 38.54 MJ kg⁻¹ within the temperature range of 260 to 300 °C. The HHV underwent a slight fall after a gradual rise with the increment of the retention time from 30 min to 90 min. This variation is consistent with that reported by previous studies.^19,43 Fig. 1(b) also shows the effect of the total solid ratio on the HHV of bio-crude oils. It can be observed that the total solid ratio does not affect the HHV of bio-crude oils, which could also be verified by the developed model of HHV.

3.2.3 Carbon recovery. Fig. 1(c) illustrates the response surfaces of the carbon recovery of bio-crude oil. It can be observed that the carbon recovery decreased with increasing reaction temperature at a shorter retention time, whereas a reverse trend was observed at a longer retention time. In terms of the effect of the retention time, the carbon recovery always increased first and then decreased gradually at any given reaction temperature. This indicates that an excessively long or short retention time was disadvantageous for the carbon recovery of bio-crude oils. It can also be seen that at a moderate retention time, there was an increase in the carbon recovery with increasing temperature. This increase was mainly due to the increased yield of bio-crude oils. As for the effect of the total solid ratio, it can be found that an increase in the total solid ratio could increase the carbon recovery of bio-crude oils. In summary, a higher carbon recovery of bio-crude oils could be obtained at high temperatures, moderate retention time, and a high total solid ratio.

3.2.4 Nitrogen recovery. Fig. 1(d) presents the response surfaces of the nitrogen recovery of bio-crude oils. It shows that the nitrogen recovery decreased with an increase in the reaction temperature at a shorter retention time, while a reverse trend was found at a longer retention time, which indicates the same effect of temperature as that in the case of carbon recovery. As for the effect of the retention time, the nitrogen recovery decreased with increasing retention time at lower temperatures, whereas the nitrogen recovery increased gradually with increasing retention time at higher temperatures. In terms of the effect of the total solid ratio, it can be found that the nitrogen recovery of bio-crude oils increased with increasing total solid ratio, which indicates the same effect as that in the case of carbon recovery. Therefore, a lower nitrogen recovery of bio-crude oils was obtained at a low temperature, long retention time, and low total solid ratio.

Overall, it can be seen from Fig. 1(a), (c) and (d) that there is a close resemblance between the response surfaces of carbon recovery and the bio-crude oil yield, whereas a slight resemblance could be observed between the response surfaces of nitrogen recovery and the bio-crude oil yield. This indicates that the carbon recovery of bio-crude oils is highly dependent on the oil yield rather than the carbon content of the bio-crude oils. For the nitrogen recovery of bio-crude oils, the nitrogen content seems to be a more crucial factor instead of the bio-crude oil yield.

In addition, as can be seen from Fig. 1(c) and (d), under the condition of a shorter retention time (e.g. 30 min) or a longer time (e.g. 90 min), the variations of carbon and nitrogen recoveries are identical with increasing reaction temperatures, irrespective of the total solid ratio. Yu et al.¹⁴ investigated the effect of reaction temperature and retention time on the distributions of carbon and nitrogen in the bio-crude oils. It was observed that with a 30 min retention time, the increase in carbon recovery was usually accompanied with an increase in the nitrogen recovery. Anastasakis et al.⁴⁴ investigated the product streams of the HTL of brown macroalgae. It was concluded that when the reaction temperature was increased from 250 °C to 370 °C at a retention time of 15 min, there was an increase in the carbon and nitrogen contents of the bio-crude oils. Both studies verified one of the observations of the current study. In other words, it is feasible to produce bio-crude oils with a higher carbon recovery and a lower nitrogen recovery if only a moderate retention time (probably around 60 min) is selected first. If we choose the boundary conditions of retention time, then an additional denitrogenation process is inevitable to reduce the nitrogen content of the HTL oil due to the NO_x emissions released during the direct combustion.

Previous studies showed that the hydrothermal liquefaction of microalgae using alkaline catalysts leads to lower nitrogen contents in the oil phase compared with the use of organic acids. It was reported by Ross et al.⁸ that the bio-crude oils produced using organic acids contain a higher nitrogen content (up to 7 wt%), whereas the amount of nitrogen in the bio-crude oils is relatively constant for alkaline catalysts (4 to 6 wt%). Dote et al.⁴⁵ investigated the liquefaction of egg albumin. It was also found that the use of sodium carbonate as a catalyst prevented the distribution of nitrogen to the oil phase. In terms of model compounds, Dote et al.⁴⁶ also investigated the nitrogen distribution during the liquefaction of amino acids. It was concluded that the decomposition of proteins in the feedstock to amino acids before liquefaction could result in a bio-crude oil with a relatively low nitrogen content. According to the results of the HTL of model compounds by Biller et al.,⁴⁷ the amount of nitrogen in the oil for the amino acids (0.3–3.7%) was considerably lower than for the protein (4–10%), which verified this conclusion. Therefore, the pre-treatment of the high-protein feedstock by hydrolysis provides another efficient method to reduce the high amount of nitrogen in a bio-crude oil before its application. However, it should be noted that the energy recovery may decrease as well.

3.3 Physical–chemical characterization of bio-crude oils

To evaluate the conversion efficiency of the hydrothermal liquefaction process, the energy recovery (ER) for all the operation conditions was calculated. According to the results obtained in Table 4, no. 12 (ER: 69.54%) and no. 10 (ER: 67.86%) were the two samples with the highest ER, while no. 2 (ER: 36.88%) was the sample with the lowest ER. To make a comparison, the chemical properties of these three bio-crude oil samples (ERS1, ERS2 and ERS3) under the same operating conditions were investigated to reveal the differences in bio-crude chemistry.

Table 4 Energy recoveries of bio-crude oils in the FCCCD matrix

Run no.	T (°C)	RT (min)	SR (wt%)	ER (%)	Run no.	T (°C)	RT (min)	SR (wt%)	ER (%)
1	260	30	15	49.8	11	280	60	15	66.1
2	260	30	35	36.9	12	280	60	35	69.5
3	260	90	15	41.5	13	280	30	25	50.8
4	260	90	35	38.1	14	280	90	25	50.9
5	300	30	15	57.1	15	280	60	25	64.3
6	300	30	35	61.3	16	280	60	25	65.0
7	300	90	15	48.2	17	280	60	25	64.7
8	300	90	35	64.6	18	280	60	25	63.9
9	260	60	25	47.5	19	280	60	25	67.6
10	300	60	25	67.9	20	280	60	25	66.7

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3.3.1 CHN analysis. Based on a CHN analysis, Fig. 2 shows the Van Krevelen diagram of the feedstock, bio-oils obtained from HTL and fast pyrolysis. It can be observed that the N/C ratios and O/C ratios of the bio-crude oils were much lower than those of the raw material of C. pyrenoidosa, while the H/C ratios did not differ considerably between the two substances. This indicates that certain amounts of nitrogen (40 wt%) and oxygen (60 wt%) were removed during the hydrothermal liquefaction process. This is most likely due to the promoted decarboxylation and deamination under hydrothermal conditions that remove nitrogen and oxygen from the amino acids, which are mainly produced through protein hydrolysis.⁴⁸ Klingler et al.⁴⁹ investigated the hydrothermal liquefaction of glycine and alanine, which are two of the simplest amino acids. On the basis of the experimental results, the authors concluded that amino acids degraded via two main paths: (1) decarboxylation to produce carbonic acid and amines, and (2) deamination to produce ammonia and organic acids.

Fig. 2 Van Krevelen diagram of feedstock, bio-crude oils obtained from HTL and fast pyrolysis: (a) O/C–H/C; (b) N/C–H/C.

Compared with the bio-crude oils produced from C. vulgaris⁵⁰ and green algae⁵¹ via fast pyrolysis, the bio-crude oils discussed in this paper have lower ratios of N/C and O/C. This suggests that the bio-crude oils produced from HTL have lower nitrogen and oxygen contents than those obtained from fast pyrolysis, which is a promising conversion option for biofuel applications due to the high energy density. However, according to the elemental analysis of petroleum,⁵² the O/C ratio, H/C ratio, and N/C ratio were 0.008, 1.532, and 0.005, respectively. This implies that the bio-crude oils still have much higher nitrogen and oxygen contents than petroleum-crude oils. Biller et al.⁴⁷ observed the high fraction of nitrogen heterocycles, pyrroles and indoles in the bio-crude oils during the hydrothermal liquefaction of algal feedstock with high-protein contents. According to the reaction network of the hydrothermal decomposition of amino acids established by Kruse et al.,⁵³ the nitrogen-containing cyclic organic compounds in bio-oils are mainly formed by the reaction between amino acids and glucose/fructose, which is called the Maillard reaction. Zou et al.⁵⁴ reported that the high oxygen content of the bio-crude oils was mainly due to the production of oxygen functional groups (e.g., ketones, phenols, and esters) through the decomposition of proteins and cellulose in the feedstock. Therefore, upgrading processes such as denitrogenation and deoxygenation are necessary for the bio-crude oils to be used as transportation fuel.

3.3.2 TG analysis. The three bio-crude oil samples (ERS1, ERS2 and ERS3) were analyzed using thermal gravimetric analysis (TGA) in nitrogen to determine the boiling point distribution. Fig. 3 shows the TG-DTG curves of the bio-crude oils. A mass loss of approximately 90 wt% could be observed for all three bio-crude oils after heating the samples from 25 to 800 °C under an inert atmosphere. Samples ERS1 and ERS2 acquired at a higher temperature had two weight loss peaks at approximately 290 °C and 410 °C. As a comparison, sample ERS3 obtained at a lower temperature had two weight loss peaks at around 270 °C and 400 °C, which is a bit earlier than that in the case of ERS1 and ERS2. This indicates that the bio-crude oils with higher ERs probably have a higher boiling point distribution.

Fig. 3 TG/DTG curves of bio-crude oils.

Table 5 lists the boiling point distribution for three samples. It can be observed that the distillation range of 170–500 °C is the major mass loss interval for all samples. Bio-crude oil samples ERS1 and ERS2 had less distribution at 170–250 °C but more distribution at 250–500 °C, compared with sample ERS3. This suggests that all bio-crude oils contain a large fraction of materials with a higher molecular weight and longer carbon chain, particularly for samples ERS1 and ERS2 with higher ERs. This may be due to the fact that re-polymerization is promoted more for ERS1 and ERS2.

Table 5 Boiling point distribution of bio-crude oils identified by TGA

Distillation range (°C)	Carbon chain	Coke oil type^a	Boiling point of bio-crude oils (wt%)
			ERS1	ERS2	ERS3
a Ref. Handbook of petroleum product analysis, JG Speight, 2008.b Fuel for ships, factories and central heating.
<70	C1–C9	Gases and naphtha	0.091	0.438	0.786
70–120	C5–C10	Gasoline	0.341	0.441	0.520
120–170	C10–C16	Kerosene	1.17	2.46	2.38
170–250	C14–C20	Diesel oils	23.8	27.7	37.7
250–500	C20–C50	Lubricating oils	60.7	57.9	48.2
500–600	C20–C70	Fuel oils^b	0.347	0.694	0.693
>600	>C70	Residue	0.337	0.425	0.494

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3.3.3 GC-MS analysis. The three bio-crude oil samples (ERS1, ERS2 and ERS3) were analyzed using GC/MS to identify the chemical composition. The NIST mass spectral database was used to identify the main peaks in the total ion chromatograms of bio-crude oils. As shown in Fig. 4, the major chemical components are categorized into groups, such as hydrocarbons (including straight and branched hydrocarbons), esters, ketones and alcohols (including piperidine and pyrimidinone), organic acids (including fatty acids), straight and branched amides, cyclic oxygenates (including phenols, phenol derivatives and fused ring compounds) and N- and O-heterocyclic compounds. It should be noted that each component was categorized in only one group, irrespective of the number of functional groups it contained. The total chromatograms and the major chemical compositions (the relative percentage of peak areas over 1%) for the three bio-crude oils are given in Fig. S1 and Table S1.†

Fig. 4 Major groups of chemical compounds in bio-crude oils.

Among the three samples, sample ERS2 with the highest HHV contained the most species and the highest content of hydrocarbons, which were partially produced from organic acids via decarboxylation.⁵⁵ Some straight-chain hydrocarbons were identified among the major compounds for all three samples, such as 2-hexadecene, 3,7,11,15-tetramethyl-, and [R-[R*,R*-(E)]]- (RT 22.59). A high percentage of nitrogenous compounds could be observed in all three bio-crude oil samples due to the high protein content of C. pyrenoidosa, which shows similar results as those obtained by Biller et al.⁴⁷ Compared with the oil sample with the lowest energy recovery (ERS3), the two best oil samples with the highest energy recovery (ERS2) contained a higher fraction of nitrogenous compounds in terms of straight/branched amides and N- and O-heterocyclic compounds. According to the TGA analysis, all three bio-crude oils contained only about 25–40% substances with boiling points lower than 250 °C. Therefore, the GC-MS results only represent a fraction of the bio-crude oils, and it could be speculated that the oil samples with a higher energy recovery probably have a lesser content of nitrogenous compounds with higher boiling points. Besides, it was observed that the oil samples with higher energy recoveries have a relatively high fraction of cyclic oxygenates, including phenol (RT 24.74) and phenolic-derived compounds such as 4-methylphenol (RT 26.14). The phenol compounds are likely derived from the carbohydrates.¹⁸ The differences in the contents of oxygenate compounds in the three oil samples may be due to the same reason as that for nitrogenous compounds.

3.3.4 FT-IR analysis. FTIR spectra of the three bio-crude oils (ERS1, ERS2 and ERS3) are shown in Fig. 5. Prominent C–H stretching (3000–2800 cm⁻¹), –CH₂ bending (1456 cm⁻¹) and –CH₃ bending (1377 cm⁻¹) could be observed in all three oil samples, suggesting the presence of alkyl C–H. The carbonyl stretching C=O appeared at 1750–1690 cm⁻¹, consistent with the ketones, aldehydes, and carboxylic acids identified in the GC-MS spectrum such as methyl 7,10-hexadecadienoate (RT 43.77) and butyl 9,12-octadecadienoate (RT 46.54). The adsorption peaks at 1300–950 cm⁻¹ were related to C–O stretching and O–H bending from alcohols, esters, and ethers. The C=O stretching (1690–1600 cm⁻¹) and N–H bending (1575–1525 cm⁻¹) are observed for all bio-crude oil samples, indicating the presence of amide compounds. The N–H stretching (3700–3100 cm⁻¹) for all bio-crude oils suggest the presence of amine compounds. Besides, some adsorption peaks could be observed at 950–700 cm⁻¹, which is ascribed to the C–H bending from aromatics and their derivatives such as phenol (RT 24.74) and phenol, 4-methyl- (RT 26.14) that could be observed in the total ion chromatograms of the three oil samples.

Fig. 5 FT-IR spectra of bio-crude oils.

3.3.5 ¹H NMR analysis. The ¹H NMR spectra of the three bio-oils (ERS1, ERS2 and ERS3) and the corresponding classification of function groups are shown in Fig. 6 and 7, respectively. The major peaks at 1.5–0 ppm could be observed in all spectrums, indicating a high percentage of aliphatic functional groups for all three oil samples, including the large peaks of aliphatic methyl (0.83 ppm) and methylene protons (1.21 ppm). This is consistent with the C–H peaks identified by FTIR and hydrocarbons in the total ion chromatogram. It can be seen that samples ERS1 and ERS2 with the highest ERs displayed a higher percentage (63–67%) of alkane protons (1.5–0.5 ppm) than that of sample ERS3 (59%), which is in accordance with the high HHV of the two samples. The high percentage of aliphatic functionality (59–67%) in the current study were identical to other bio-oils derived from different feedstocks such as the spirulina algae (53%)⁵⁶ and duckweed lemna (60%).⁵⁷ The obvious peaks at 3.0–1.5 ppm are related to heteroatomic functionalities, including the major peaks of protons in the β-position (1.5–1.6 ppm) and α-position (2.1–2.3 ppm). This is probably due to the abundant nitrogenous and oxygenated compounds identified in straight/branched amides and the N- and O-heterocyclic compounds from the total ion chromatogram, which mainly originate from the high contents of protein in the feedstock.⁵⁸ The integration areas of protons resonating at the chemical shift of 3.0–1.5 ppm for ERS1 and ERS2 were smaller (21–26%) than those of ERS3 (32%), which verified the lesser nitrogen recovery of ERS1 and ERS2 as compared to ERS3. Apart from the relative high content of the aliphatic and heteroatom/unsaturated functionality, no significant peaks were observed in the chemical shift of 8.0–3.0 ppm for the optimized samples ERS1 and ERS2. These regions represent other aromatic and unsaturated functional groups derived from ketones, esters, ethers, alcohols and methoxy carbohydrate compounds. This fact is consistent with the observations of the GC-MS and FT-IR analyses.

Fig. 6 ¹H-NMR spectra of bio-crude oils.

Fig. 7 Distribution of functional groups present in bio-crude oils.

4 Conclusions

The RSM results have demonstrated the effects of reaction temperature, retention time and total solid ratio on the productivity and quality of bio-crude oils produced via the hydrothermal liquefaction of a low-lipid content microalgae Chlorella pyrenoidosa. The reaction temperature was found to be the most influential factor affecting the yield and quality of bio-crude oils. Molecular-level information obtained from a multi-method characterization of optimized bio-crude oil samples indicates that different operating conditions may have a great influence on the qualities of bio-crude oils. Functional group-specific chemical strategies are recommended to further increase the aliphatic functionalities as well as reduce the heteroatom contents to improve the properties of HTL bio-crude oils.

Acknowledgements

The authors acknowledge the China Scholarship Council for the financial support and USDA for covering the experimental expenses for the research. The authors also thank Yangchun Lan and Dr Paul J. A. Kenis from the Department of Chemical and Biomolecular Engineering at University of Illinois at Urbana-Champaign for their kind assistance during the project.

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Footnote

† Electronic supplementary information (ESI) available. See DOI: 10.1039/c3ra46607h

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