Bioresource Technology 102 (2011) 8295–8303

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Bioresource Technology

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Chemical properties of biocrude oil from the hydrothermal liquefactionof Spirulina algae, swine manure, and digested anaerobic sludge

Derek R. Vardon a,⇑, B.K. Sharma b, John Scott b, Guo Yu c, Zhichao Wang c, Lance Schideman c,Yuanhui Zhang c, Timothy J. Strathmann a

a Dept. of Civil and Environmental Engineering, University of Illinois at Urbana-Champaign, Newmark Lab, 205 N. Mathews Ave., Urbana, IL 61801, USAb Illinois Sustainable Technology Center, University of Illinois at Urbana-Champaign, 1 Hazelwood Dr., Champaign, IL 61820, USAc Dept. of Agricultural and Biological Engineering, University of Illinois at Urbana-Champaign, Agricultural and Engineering Science Building, 1304 West Penn. Ave.,Urbana, IL 61801, USA

a r t i c l e i n f o a b s t r a c t

Article history:Received 15 April 2011Received in revised form 10 June 2011Accepted 10 June 2011Available online 7 July 2011

Keywords:Hydrothermal liquefactionAlgaeSpirulinaSwine manureDigested sludge

0960-8524/$ - see front matter � 2011 Elsevier Ltd. Adoi:10.1016/j.biortech.2011.06.041

⇑ Corresponding author. Tel.: +1 217 766 3916.E-mail address: dvardon2@illinois.edu (D.R. Vardo

This study explores the influence of wastewater feedstock composition on hydrothermal liquefaction(HTL) biocrude oil properties and physico-chemical characteristics. Spirulina algae, swine manure, anddigested sludge were converted under HTL conditions (300 �C, 10–12 MPa, and 30 min reaction time).Biocrude yields ranged from 9.4% (digested sludge) to 32.6% (Spirulina). Although similar higher heatingvalues (32.0–34.7 MJ/kg) were estimated for all product oils, more detailed characterization revealed sig-nificant differences in biocrude chemistry. Feedstock composition influenced the individual compoundsidentified as well as the biocrude functional group chemistry. Molecular weights tracked with obduratecarbohydrate content and followed the order of Spirulina < swine manure < digested sludge. A similartrend was observed in boiling point distributions and the long branched aliphatic contents. These find-ings show the importance of HTL feedstock composition and highlight the need for better understandingof biocrude chemistries when considering bio-oil uses and upgrading requirements.

� 2011 Elsevier Ltd. All rights reserved.

1. Introduction

Hydrothermal liquefaction (HTL) is a promising technology forconverting wastewater biomass into a liquid fuel (Cantrell et al.,2007). HTL has been applied to a wide range of wastewater feed-stocks, including swine manure, cattle manure, microalgae, macro-algae, and sludge (Suzuki et al., 1988; Dote et al., 1994; He et al.,2000; Brown et al., 2010; Xiu et al., 2010a; Yin et al., 2010; Billerand Ross, 2011). During HTL, water serves as the reaction medium,alleviating the need to dewater biomass which can be a majorenergy input for biofuel production. Elevated temperature (200–350 �C) and pressure (5–15 MPa) are used to breakdown and re-form biomass macromolecules into biofuel (Peterson et al., 2008),subsequently referred to as biocrude oil. Self-separation of the bio-crude oil from water is then facilitated as the reaction solution re-turns to standard conditions (Peterson et al., 2008). The recoveredbiocrude oil can be directly combusted or upgraded to approachpetroleum oils (Dote et al., 1991; Elliott, 2007; Duan and Savage,2011a). While the ability of HTL to convert a wide-range of waste-water feedstocks provides a significant waste-disposal benefit, it

ll rights reserved.

n).

also presents a major challenge for optimization and downstreamprocesses due to the diverse biocrude oil chemistry that can result.

HTL biocrude oils contain a diverse range of chemical compoundswhich can include straight and branched aliphatic compounds, aro-matics and phenolic derivatives, carboxylic acids, esters, and nitrog-enous ring structures (Brown et al., 2010; Xiu et al., 2010a; Yin et al.,2010; Zhou et al., 2010; Biller and Ross, 2011). The class of com-pounds identified in HTL biocrude oils has been shown to be influ-enced by the ratio of protein, lipid, and carbohydrate fractions inthe initial biomass feedstock (Biller and Ross, 2011). Biocrude oilsare often characterized by high heteroatom contents, primarily inthe form of oxygenated and nitrogenous compounds. The high het-eroatom content is the main distinguishing factor separating bio-oils from petroleum crude oils (Huber et al., 2006; Peterson et al.,2008; Demirbas, 2009) and results in undesirable biofuel qualitiessuch as oil acidity, polymerization, high viscosity, and high-boilingdistribution (Adjaye et al., 1992; Speight, 2001). Furthermore, the di-verse chemical composition of biocrude oil affects the combustionperformance, storage stability, upgrading response, and economicvalue (Huber et al., 2006). Therefore, the objective of this studywas to examine and compare the influence of wastewater feedstockcomposition for three feedstocks (Spirulina algae, swine manure,and anaerobic digested sludge) on the bulk properties and phys-ico-chemical characteristics of HTL biocrude oil.

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The algal species Spirulina was selected for HTL conversion dueto increased interest in integrating algal cultivation into wastewa-ter treatment from both a water resource and renewable energyperspective (Pittman et al., 2010). Spirulina can thrive in munici-pal and agricultural wastewater effluents and the filamentous cellstructure facilitates harvesting (Kosaric et al., 1974). The highprotein content can also be converted into HTL biocrude oil (Billerand Ross, 2011) and the ability to capture CO2 can be used to re-duce a treatment facility’s environmental footprint (Packer, 2009).Additionally, HTL of low-lipid algae such as Spirulina can providea comparison with contributions focused on HTL of high-lipidspecies (Dote et al., 1994; Brown et al., 2010), which tend to ex-hibit relatively low total lipid content when cultured in wastewa-ters (Pittman et al., 2010). Swine manure was chosen as arepresentative solid waste generated by agricultural livestockfacilities. In the United States alone, livestock manure accountsfor �250 million tons of dry solids annually (Xiu et al., 2010a)and land application of these wastes has been linked to thespread of hormones, pathogens, and nutrient runoff (Cantrellet al., 2007). Swine manure also contains a moderate lipid andhigh carbohydrate content to provide a distinct biochemical com-parison to Spirulina algae. Anaerobically digested sludge was se-lected as the final feedstock to compare the effect of highobdurate carbohydrate content on biocrude oil yields and chem-istry and evaluate HTL as an alternative to current predominantdisposal practices: land application and landfilling. Currently,over 7 million tons of dry anaerobically digested sludge is pro-duced annually with only 60% going towards beneficial use (USEnvironmental Protection Agency, 1999).

Advanced characterization methods were used to assess themolecular properties of biocrude oil and the influence of feed-stock composition. Molecular-level characterization has beencritical for designing engineering approaches to catalytically up-grade low-quality ‘‘heavy’’ petroleum oils (Speight, 2001) andwill be necessary for transitioning to a biomass-based fuel infra-structure (Huber et al., 2006). Previous examples of molecularcharacterization used to better understand HTL chemistry in-clude, but are not limited to, observing the conversion of carbo-hydrates into biocrude oil (Duan and Savage, 2011b), verifyingthe presence of aromatic hydrocarbons tied to increased bio-oilviscosity and density (Yin et al., 2010), determining the effectsof reaction parameters (Xiu et al., 2010a; Yin et al., 2010) andcatalyst addition (Duan and Savage, 2011b), and monitoringthe deoxygenation of fatty acids through catalytic upgrading(Duan and Savage, 2011a). However, further understanding ofthe chemistry involved during HTL biomass conversion andupgrading process is needed to develop more efficient and sus-tainable biofuel and biochemical production methods (Huberet al., 2006).

In this study, both bulk properties (e.g., oil yield, elementalanalysis, and heating value) and physico-chemical characteristics(e.g., molecular constituents, functional group allocation, protonand carbon speciation, molecular weight distribution, and boilingpoint distribution) of biocrude oils produced by liquefaction of dif-ferent wastewater feedstocks were compared with each other aswell as published results for petroleum crudes and tar sand bitu-mens. Low-boiling compounds were identified by gas chromatog-raphy–mass spectroscopy (GC–MS), functional groupcompositions were examined with Fourier Transform infrared(FTIR) and nuclear magnetic resonance (1H and 13C NMR) spectros-copies, and the molecular weight and boiling point distributionswere analyzed with size exclusion chromatography (SEC) and sim-ulated distillation (Sim-Dist), respectively. To our knowledge, thisis the first study to compare the chemical characteristics of biocru-des generated from disparate wastewater feedstocks under identi-cal HTL conditions.

2. Methods

2.1. Feedstock sources and characterization

Spirulina algae (solids content of 95%) were obtained in dry-powder form from Cyanotech (Kailua-Kona, Hawaii). Swine man-ure (solids content of 27%) was sampled from grower-finisherpen floors at the Swine Research Center at the University of Illinoisat Urbana-Champaign. The pens contained a partially slotted floorfor manure collection. Both the swine manure and algal sampleswere stored at 4 �C prior to processing. Digested anaerobic sludge(solids content of 26%) was collected from the outlet of an anaero-bic digester at the Urbana-Champaign Sanitary District wastewatertreatment plant (Urbana, IL) and was processed immediately toavoid compositional decay.

Forage analysis of feedstock samples (Midwest Laboratories;Omaha, NE) was conducted to determine crude protein, crude lipid,neutral detergent fiber (cellulose, lignin, and hemicellulose), aciddetergent fiber (cellulose and lignin), lignin and ash content. Crudeprotein was determined by combustion method (AOAC 990.03).Crude lipids were measured gravimetrically after ether solventextraction (AOAC 945.16). Ash content, representing the inorganicfraction of the feedstock, was determined by heating the sample at600 �C to remove all organic carbon (AOAC 942.05). Totalcarbohydrates were calculated by subtraction. Carbohydrates werealso subdivided into several categories that were measuredseparately and included: neutral detergent fiber (NDF), acid deter-gent fiber (ADF), and lignin fractions by measuring the organic res-idue remaining in an ANKOM Technology filtration apparatus afterdigestion. However, due to differences in the sample preparationand analysis procedures for individual component assays, resultsvaried for each fraction (e.g., swine manure NDF > totalcarbohydrates).

2.2. HTL conversion

Samples were converted into biocrude oil under hydrothermalconditions (300 �C, 10–12 MPa, and 30 min retention time) in sin-gle runs for each feedstock using a Parr 4500 2-L reactor. Approx-imately 800 g of feedstock slurry adjusted to 20% solid content (w/w) was loaded into the reactor vessel, which was then sealed andpurged with nitrogen three times to displace headspace gasesand charged to an initial pressure of 0.65 MPa. Electric resistanceheating was then used to raise the temperature to 300 �C and thefeedstock was continuously mixed by a magnetic drive agitator.After a 30-min reaction time, the reactor was cooled rapidly toroom temperature by circulating water through a cooling coil lo-cated inside the reactor. Reactor headspace gases were then care-fully released into a gas collection assembly and the liquid andsolid phases were removed from the reactor. The non-aqueous li-quid fraction, which also contained visible solid residue, was ex-tracted into dichloromethane (DCM) solvent using a separatoryfunnel. Deionized water (>18 MX) was added to the funnel to forma bi-layer, and the DCM-soluble portion was vacuum filtered(Whatman No. 44 ashless filter paper) to remove particulate mat-ter. The DCM was then removed under a nitrogen stream at 40 �C.The focus of this study was on characterization of the DCM-solublebiocrude phase, so the gas, aqueous, and solid phases were not fur-ther characterized.

2.3. Biocrude oil characterization

2.3.1. Bulk characterizationBiocrude oil yield was determined gravimetrically and calcu-

lated as the ratio of the DCM-soluble biocrude mass to dry

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feedstock organic mass (i.e., total dry mass minus ash content)(Suzuki et al., 1988; Dote et al., 1994; Yin et al., 2010; Biller andRoss, 2011). Elemental analysis was conducted at the Universityof Illinois Microanalysis Laboratory (Urbana, IL). Samples wereprocessed for total carbon/hydrogen/nitrogen using an ExeterAnalytical CE-440 Elemental Analyzer. Sulfur was measured byICP-OES in axial mode (PerkinElmer Optima 2000DV) after digest-ing samples (PerkinElmer Multiwave 3000 Digester). Oxygen wasassumed to account for the bulk of the remaining sample massbalance. Higher heating value (HHV; MJ/kg) was estimated usingDulong’s formula (Brown et al., 2010; Zhou et al., 2010; Billerand Ross, 2011; Duan and Savage, 2011a, 2011b):

HHV ¼ 0:3383Cþ 1:422 H� O8

� �ð1Þ

where C, H, and O are the mass percentages of carbon, hydrogen andoxygen, respectively.

2.3.2. GC–MSSeparation was achieved with a Varian VF-5 ms phenyl–methyl

GC column (30 m � 0.25 mm id, 1.0-lm film) using He carrier gaswith flow rate of 1 mL/min. One microlitre of DCM extracts (2 wt.%biocrude) were injected at 270 �C with a split ratio of 30:1. Theoven temperature was initially set to 60 �C with a hold time of4 min, then increased at 5 �C/min until 280 �C and held constantfor 15 min. The source temperature was 210 �C, electron ionizationwas set at 70 eV, and spectra were scanned from 35–550 m/z (0.2 sper scan and interscan delay of 0.1 s). Individual low molecularweight products were identified by matching fragmentation pat-terns against a NIST database. Before peak integration, the totalion chromatogram was baseline corrected and signal noise was fil-tered using Matlab software.

2.3.3. FTIR and NMRAdditional functional group information was derived from FTIR

and NMR spectroscopic data. FTIR spectra were collected using aThermo Nicolet Nexus 670 Fourier Transform Infrared Spectropho-tometer equipped with a single-bounce diamond attenuated totalreflectance (ATR) accessory (Specac Golden Gate) and KBr beamsplitter. Spectra were collected from 4000 to 525 cm�1 with 0.98-cm�1 resolution and averaged over 50 replicate scans using Omnicsoftware. Background scans were conducted of the dry accessory atambient temperature. Biocrudes were applied in thin films and al-lowed to dry to remove any trace solvent. The spectra were thencollected after smearing �30 mg of sample directly on the ATRcrystal surface.

1H NMR spectra were collected using a Varian Unity 400-MHzspectrometer outfitted with a 5-mm broadband probe. Samples(2.5% w/w) were prepared by dissolving 50–75 mg of biocrude oilin deuterated chloroform containing 0.03% tetramethylsilane(TMS) as an internal reference. Samples were then filtered (0.45-lm PTFE) to remove any suspended particulates before loadinginto 5 mm diameter NMR tubes. 1H spectra were acquired with a90� pulse angle, spinner frequency of 20 Hz, sweep width of8000 Hz across 32 transients.

13C NMR spectra were collected using a Varian Unity 600-MHzspectrometer outfitted with a 10-mm broadband probe. Sampleswere prepared at concentration of 7–10% (w/w) in deuterated chlo-roform with 0.03% TMS and filtered (0.45 lm PTFE) before loadinginto 10 mm diameter NMR tubes. Spectra were acquired with a 90�pulse angle at 25 �C with a relaxation time of 7 s and gated protondecoupling. Spectra were accumulated for >3600 transients tomaximize the S/N ratio. Signal processing of NMR spectra was per-formed with NutsPro NMR Utility Transform Software Professional.Processed NMR spectra were exported to Matlab for integration

based on functional group designations for 1H and 13C NMR peaksaccording to Mullen et al. (2009). The signal area of residual dichlo-romethane solvent (5.32 ppm for 1H NMR; 54 ppm for 13C NMR)and trace protons from deuterated chloroform (7.26 ppm for 1HNMR; 77 ppm for 13C NMR) were excluded during spectrumintegration.

2.3.4. SEC analysisMolecular weight distributions were determined by SEC. Analy-

sis was conducted using a Waters 2414 RI detector, Styragel HR1SEC column (7.8 � 300 mm), Waters 600-MS System controllerconnected to a 600-mulitsolvent delivery system, and 717-plusautosampler connected to a Dionex U120 Universal Interface.Retention time calibration was obtained using six polystyrenestandards with peak molecular weights of 250, 600, 1000, 1700,2500, and 7000 Da (Polysciences Inc.). Biocrude samples (3% w/w) were dissolved in tetrahydrofuran and filtered (0.45-lm PTFE)to remove suspended particulates. The pump flow rate was1.0 mL/min with THF as the mobile phase and injection volumeswere set to 50 lL. The resulting chromatographic data was pro-cessed using Matlab according to the equations below. Cumulativesignal intensities were normalized to unity between samples to al-low for relative comparisons. The number-average molecularweight (Mn), weight-average molecular weight (Mw), and polydis-persity index were calculated based on component molecularweights (Mi) determined from the retention time calibration curveand signal intensities (Ni):

Mn ¼P

MiNiPNi

ð2Þ

Mw ¼P

M2i NiP

MiNið3Þ

The polydispersity index (PDI), which is indicative of the spreadin the molecular weight distribution of the biocrude oil constitu-ents, was then calculated according to:

PDI ¼ Mw

Mnð4Þ

2.3.5. Sim-Dist analysisSimulated distillations were modeled after ASTM-7169-05

method and performed using a HP 5890 Series II FID gas chromato-graph and a Durabond DB-HT-SimDis GC column by Agilent-J&WScientific (5 m � 0.53 mm id, 0.15 lm film). Helium (18 mL/min)was used as the carrier gas. The oven temperature was initiallyset to 0 �C, using CO2 cryogenic cooling to improve solvent separa-tion from low-boiling peaks, and raised to 420 �C at 10 �C/min andthen held constant for 10 min. The injector volume was set to 1lLand the injector temperature was oven-tracked and followed theoven temperature program. Detector temperature was set to450 �C, hydrogen gas set to 32 ml/min, airflow set to 400 ml/min,and nitrogen makeup set to 24 ml/min. Samples (1% w/w) andreference standards (0.5% w/w) were dissolved in DCM rather thanthe carbon disulfide outlined in the ASTM method due to improvedbiocrude oil solubility. Samples were filtered (0.45-lm PTFE) to re-move any suspended particulates. Boiling points were determinedby comparison against a series of reference standards purchasedfrom Accustandard, including a DRH-2887 calibration mix, DRH-008S calibration mix, decane, hexadecane, PolyWax 850 and D-6352 Reference Gas Oil. Data were collected at a sampling rate of1 Hz using Varian-STAR software and signal integration and distri-bution analysis was performed using MATLAB. For the Sim-Distanalysis, FID detector intensities were assumed to be directly pro-portional to the weight percent of sample eluted. The boiling

Table 2Conversion yields and bulk properties of HTL biocrude oil obtained from differentwastewater feedstocks.

Feedstock Oil yield% C% H% N% O% S% HHV (MJ/kg)

Spirulina algae 32.6 68.9 8.9 6.5 14.9 0.86 33.2Swine manure 30.2 71.2 9.5 3.7 15.6 0.12 34.7Anaerobic sludge 9.4 66.6 9.2 4.3 18.9 0.97 32.0

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point–retention time relationship is known to be influenced bychemical structure and heteroatom content. Therefore, the Sim-Dist analysis of biocrude samples can only be considered a roughapproximation since the heteroatom contents of the biocrudevolatile components are significantly different from the mixtureof n-alkane reference compounds used for calibration.

3. Results and discussion

3.1. Feedstock composition

Forage analysis of the feedstocks indicated that Spirulina hadthe highest overall organic matter content on a dry weight basis(90%) compared to swine manure (84%) and digested sludge(69%) as shown in Table 1. The organic matter in Spirulina wascomprised primarily of crude protein (64%) with relatively smalleramounts of crude lipids (5%) and fibrous carbohydrates (2%) ac-counted for in the neutral detergent fiber (NDF) fraction (e.g., lig-nin, cellulose, and hemicellulose). Spirulina had a much lowercrude lipid content than other microalgal species examined forHTL biocrude oil production such as Chlorella (25%) (Biller andRoss, 2011), Nannochloropsis (28%) (Brown et al., 2010), andBotryochoacus brauni (50%) (Dote et al., 1994). In contrast, swinemanure had a more uniform nutritional composition with a distri-bution of NDF (44%), crude protein (25%) and crude lipids (22%).Lastly, digested anaerobic sludge consisted primarily of NDF(51%) and crude protein (42%) with very low crude lipid content(<1%) and a much higher acid detergent fiber fraction (ADF)(36%), representative of lignin and cellulose that are poorly biode-gradable during wastewater treatment processes (Jain et al., 1992).

3.2. HTL conversion

3.2.1. Biocrude oil yieldsThe varying feedstock compositions were reflected in the HTL

biocrude oil yields calculated on an ash-free basis as shown in Ta-ble 2. Spirulina had the highest biocrude oil yield (32.6%), withswine manure having a moderately lower yield (30.2%), despitehaving much higher initial lipid content (22%) than Spirulina (5%).Previous research has identified the following general trend forconversion efficiency: lipids > protein > carbohydrates (Biller andRoss, 2011). The slightly lower biocrude oil yield of swine manurein comparison to Spirulina may be explained by the higher carbo-hydrate content of manure, which has a lower conversion effi-ciency compared to protein and offsets the higher lipid contentof the manure feedstock. We suspect that low carbohydrate con-version efficiency is related to higher hemicellulose and lignin con-tent, the latter of which has been shown to decrease HTL oil yields(Zhong and Wei, 2004). Digested anaerobic sludge provided muchlower yield (9.4%), even after accounting for the higher ash content,and may be attributed to the larger carbohydrate content with lowconversion efficiency due to higher hemicellulose and lignin.

Direct comparison of HTL biocrude yields can be difficult due tovarying conversion conditions (e.g., reaction temperature,

Table 1Forage analysis of wastewater biomass feedstocks for HTL.

Forage analysis (%) Spirulina algae Swine manure Anaerobic sludge

Crude protein 64 25 15Crude lipid 5 22 <1Total carbohydrates 21 37 54NDF 2 44 51ADF 1 14 36Lignin <1 3 10Ash 10 16 31

retention time, headspace gas, agitation, solids loading) that cansignificantly impact yields (Yin et al., 2010). However, yields withSpriulina obtained in this study were comparable to those reportedby Biller and Ross (2011) (29%) and lower than those of moderate-to-high lipid species such as Chlorella (36%) (Biller and Ross, 2011),Nannochloropsis (43%) (Brown et al., 2010), and B. brauni (�55%)(Dote et al., 1994). The swine manure biocrude oil yield was some-what higher compared to a recent study by Xiu et al. (2010a) (25%)and considerably lower than results previously reported by mem-bers of our group (54%) (He et al., 2000), with differences likely dueto varying manure compositions, conversion parameters, and biocrude oil recovery methods (e.g., solvent selection, heating, andrecirculation). Lastly, biocrude yield with digested sludge was sig-nificantly lower compared to values reported by Suzuki et al.(1988) (25%), which may be due to disparate feed compositionsor differing extents of digestion before disposal.

These results point to ability of HTL to convert high organic con-tent feedstocks into biocrude oil, regardless of lipid content,through the partial utilization of both protein and carbohydratefractions (Biller and Ross, 2011). This holds promise for utilizinglow-lipid algae, such as Spirulina, that can be cultivated in waste-water environments and processed alongside raw sewage solidsand bacterial sludges. Furthermore, low-lipid algal species tendto have faster growth rates in a wastewater environment com-pared to high-lipid algae (Becker, 1994). Swine manure biocrudeoil yields were also significant, warranting further investigationinto the potential environmental and economic benefits of HTLcompared to typical land application practices. HTL of digestedanaerobic sludge did not yield much oil, suggesting the need tocontinue current disposal methods. Alternatively, wastewatersludges collected earlier in the treatment system (e.g., undigestedprimary or secondary sludge) can produce higher HTL biocrudeoil yields due to higher lipid and protein contents, but comes withthe tradeoff of diverting organic substrate currently used for pro-ducing methane during anaerobic digestion.

3.2.2. Elemental analysis and higher heating valueDespite the varying biocrude oil yields, bulk elemental analysis

(Table 2) resulted in only small differences in estimated higherheating values (HHV) of the product oils, ranging from 32.0 to34.7 MJ/kg. Previous HTL reports with microalgae, manure, andsludge feedstocks show a somewhat wider range of HHVs (25–39 MJ/kg) (Suzuki et al., 1988; Brown et al., 2010; Xiu et al.,2010a; Yin et al., 2010; Biller and Ross, 2011), with the exceptionof the high-hydrocarbon algal species B. brauni (45.9 MJ/kg) (Doteet al., 1994). Petroleum crude oils, in contrast, can range from 41 to48 MJ/kg (Speight, 2001). The lower HHV values of the wastewaterbiocrudes are a byproduct of the much higher nitrogen (3.7–6.5%)and oxygen (14.9–18.9%) contents in comparison with petroleumcrudes (Speight, 2001) and North American tar sand bitumens(Bunger et al., 1979), which typically have less than 2.0% of eachelement. The high protein content of Spirulina carried over intothe biocrude which had the highest nitrogen content (6.5%) ofthe three oils. Anaerobic sludge, with its high ADF content (ligninand cellulose), produced a biocrude with the greatest oxygen con-tent (18.9%) and lowest HHV. In contrast to the oxygen and

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nitrogen data, the sulfur content of the HTL biocrudes were rela-tively low (<1%) compared to many petroleum crudes, which canrange from 0.05% to 6.0% (Speight, 2001). The high oxygen andnitrogen content is a primary factor that distinguishes biocrudeoils from petroleum crudes, and upgrading processes for loweringheteroatom content represent a significant challenge to the biofuelindustry.

3.3. Physico-chemical characterization

3.3.1. Gas chromatography–mass spectroscopyIn contrast to bulk elemental analysis, chemical characteriza-

tion of HTL biocrude oils from different feedstocks exhibited amarked degree of variation. With GC–MS, >40 compounds wereidentified for each biocrude sample that comprised >50% of the to-tal ion chromatogram (TIC) peak area. Compounds that repre-sented >1% of the total peak area of the chromatograms arelisted in Table 3 with spectra and identified peaks provided inthe Supplemental Information (Fig. S1). It should be noted thatonly a fraction of the products formed by HTL are identifiable byGC–MS due to the high molecular weights and boiling point distri-butions of the biocrude (see sections below) and the temperaturelimit of the instrument (maximum boiling point detected�350 �C). Furthermore, some low boiling point compounds mayhave been masked by the solvent peak or lost when evaporatingthe DCM used to recover the biocrude oil.

The high protein content of Spirulina produced biocrude oil thatcontained a high percentage of nitrogenous compounds, similar tofindings by Biller and Ross (2011). The most prevalent peak in thespectrum was O-decylhydroxylamine (11.8% of the total ion chro-matogram), which may result from the decomposition of proteins,followed by tridecene (4.7%), dimethyl-dioxaspiro-undecanone,(4.6%), and trimethyl-dodecanol (4.0%). Strikingly, no straight-chain hydrocarbons were identified among the major compounds,though several minor hydrocarbons were identified, includingpentadecene (0.5%), heptadecene (0.9%), and docecane (0.4%). Themost prevalent compound, O-decylhydroxylamine, contained a10-carbon chain backbone with an amine moiety, which may bederived from the decarboxylation and rearrangement of aminoacids that can occur under HTL conditions (Peterson et al., 2008).Catalytic upgrading can be used to remove nitrogen through hyd-rodenitrogenation (HDN) and limit regulated NOx emissions duringbiofuel combustion. However, due to their basicity, nitrogen com-pounds are highly problematic for conventional hydro-treatmentcatalysts since they strongly adsorb to active acidic sites and re-quire more severe treatment conditions (Furimsky and Massoth,1999).

The swine manure feedstock, with a more balanced distributionof bulk carbohydrates and crude lipids, produced biocrude oil thatcontained a mix of phenolic- and lipid-derived compounds, similarto findings by Xiu et al. (2010b). The major GC–MS peaks in theswine biocrude were identified as pentanoic acid (11.1%), ethyl-phenol (10.1%), hexanoic acid (5.2%), methylphenol, (3.9%) andcholesterol compounds (2.5%). The phenol compounds are likelyderived from the carbohydrate and protein fraction, which havebeen identified during the HTL degradation of lignin (Demirbas,2000) and model protein compounds (Biller and Ross, 2011). Sim-ilarly, the fatty acid and cholesterol compounds (2.5%) are likelyderived from the crude lipid fraction, with fatty acids being identi-fied during the decomposition of triglycerides under HTL condi-tions (Peterson et al., 2008; Biller and Ross, 2011). The crudeprotein in the manure also led to nitrogenous compounds, includ-ing succinimide, indole, and pyrazine, however to a lesser extent(<2% peak area) than for Spirulina biocrude. The oxygen-rich com-pounds are of particular concern since they can polymerize, lead-ing to storage instability (Adjaye et al., 1992). Profiling of the

oxygenated compounds prior to application of hydrodeoxygen-ation (HDO) upgrading processes is beneficial, since hydrogen con-sumption and operation severity are highly dependent on theconcentration and structure of oxygenated compounds present inoil (Furimsky, 2000).

The digested anaerobic sludge feedstock, which was mainlycomprised of ADF (cellulose and lignin) and crude protein, resultedin biocrude oil containing a high percentage of ester, phenolic andnitrogenous compounds. To our knowledge, no GC–MS informationhas previously been reported on digested sludge biocrude oil. Themajor compounds identified were dodecyl acrylate (3.8%), benzo-ylformic acid (3.5%), phenol (2.9%), and O-decylhydroxylamine(2.7%). Interestingly, no compounds were identified with a peakarea >4% in the sludge biocrude. Cholesterol derivatives were alsoobserved despite a very low crude lipid content (<1%) measured inthe initial feedstock.

The high heteroatom compounds that comprised the majorclasses for all HTL biocrudes are in stark contrast to the aliphaticand aromatic compounds that predominate in GC–MS analysis ofpetroleum crude oil (Speight, 2001). As mentioned previously,the high heteroatom content of HTL compounds is a major concern,particularly in the low boiling fraction that is traditionally used forthe transportation-grade fuel production.

3.3.2. FTIR spectroscopyFTIR analysis of the biocrude oils (spectra provided in Fig. S2,

Supplemental Information) allowed for a more comprehensivecomparison of ‘‘whole’’ oil functional group characteristics whencompared to GC–MS, with spectral band assignments and interpre-tation based on previous studies (Xiu et al., 2010a,b; Yin et al.,2010; Zhou et al., 2010; Duan and Savage, 2011b). Similar to ele-mental analysis, the high carbon and hydrogen content of HTL bio-crude oil produced prominent CAH stretch (3000–2840 cm�1), CH2

bending (1465 cm�1), and CH3 bending (1375 cm�1). Significantheteroatom functionality (1730–1150 cm�1) was also observedfor all biocrude samples as expected from the elemental analysisand GC–MS characterization. The high protein content of Spirulinaalgae produced biocrude oil with prominent NAH bending peaks(1680–1600 cm�1 and 1575–1525 cm�1), consistent with nitroge-nous compounds identified by GC–MS. In contrast, the moderate li-pid and fibrous carbohydrate content of swine manure producedbiocrude oil with strong C@O stretch (1730–1700 cm�1), CAOstretch (1320–1210 cm�1), and CAO alcohol stretch peaks (1260–1000 cm�1), consistent with the fatty acids/esters and carbohy-drate derivatives identified by GC–MS and previous FTIR peaksidentified in HTL biocrude derived from swine manure (Xiu et al.,2010a,b). Lastly, digested sludge had the highest ADF (lignin andcellulose) and produced biocrude oil with CAO stretch peaks(1320–1210 cm�1). The moderate protein of sludge was alsoreflected in the biocrude with weaker NAH bending peaks(1680–1600 cm�1) compared to those found in oil produced fromSpirulina. The biocrude oil spectra are distinct from spectrareported for conventional petroleum crudes (Wilt et al., 1998)and heavy asphaltic crudes (Akrami et al., 1997), which displaystronger alkane peaks (3000–2800 cm�1) and exhibit weakerheteroatom associated peaks congruent with their higher hydro-carbon and lower heteroatom contents.

3.3.3. NMR spectroscopyNMR spectra (Figs. S3 and S4, Supplemental Information) pro-

vided complementary functional group information to FTIR spec-tra and the ability to quantify and compare integration areasbetween spectra. Similar to FTIR, 1H NMR spectra showed a highpercentage of aliphatic functional groups for all HTL biocrude oils;a summary of integrated peak area regions assigned to differentfunctional group classes is provided Fig. 1a. The swine manure

Table 3Major compounds representing >1% of the GC–MS total ion chromatogram areas from HTL biocrude oils generated from different wastewater feedstocks.

No. ofID

Spirulina algae Swine manure Anaerobic sludge

RT(min)

Compound Area(%)a

RT(min)

Compound Area(%)a

RT(min)

Compound Area(%)a

1 6.9 Phenylglyoxal 2.7 7.3 Pentanoic acid 11.1 6.9 Benzoylformic acid 3.52 7.3 Phenol 3.0 7.3 Hexanoic acid 5.2 7.3 Phenol 2.03 10.3 Phenol, 4-methyl 2.5 8.0 Pyrazine 1.3 10.3 Phenol, 4-methyl 2.94 13.1 Phenol, 4-ethyl 1.1 10.3 Phenol-4 methyl 3.9 13.1 Phenol, 4-ethyl 2.05 16.8 Indole 1.8 10.6 Mequinol 2.8 19.3 4-Methylindole 1.36 18.5 Naphthalene, 1,2,3,4-tetrahydro-1,1,6-

trimethyl-1.6 13.1 Phenol, 4-ethyl 2.9 21.5 1-Tridecanol 2.2

7 19.1 2,5-Pyrrolidinedione, 1-propyl 3.1 16.2 Phenol, 4-ethyl-2-methoxy-

10.1 22.1 Hydroxylamine, O-decyl-

2.7

8 19.4 1,5-Dioxaspiro[5.5]undecan-9-one, 3,3-dimethyl-

4.6 19.1 N-2-Hydroxyethyl-succinimide

1.4 23.4 7-Tetradecene 1.7

9 21.6 Benzonitrile, 2,4,6-trimethyl- 1.0 19.3 1H-Indole, 4-methyl 1.1 26.6 Dodecyl acrylate 3.810 26.7 Hydroxylamine, O-decyl- 11.8 21.9 1-Hexadecanol 1.3 45.7 Cholest-4-ene 2.211 29.2 1-Dodecanol, 3,7,11-trimethyl- 1.0 26.6 2-Propenoic acid, tridecyl

ester3.2 46.1 Cholest-2-ene 1.5

12 29.5 1-Dodecanol, 3,7,11-trimethyl- 4.0 45.7 Cholest-4-ene 1.3 46.3 Cholest-7-ene,(5.alpha.)-

1.3

13 29.7 5-Tridecene, (Z)- 4.7 48.3 5.alpha.-Ergost-8(14)-ene 1.2

a Area represents percent of total ion chromatogram.

8300 D.R. Vardon et al. / Bioresource Technology 102 (2011) 8295–8303

and sludge-derived biocrude contained the highest percentage(68–69%) of alkane functional groups (0.5–1.5 ppm). The high al-kane content may be attributed to the fatty acids and alkanes inswine manure biocrude, derived from decomposition of feedstocktriglycerides under HTL conditions (Peterson et al., 2008; Billerand Ross, 2011), and the high percentage of aliphatic estersidentified in the sludge biocrude GC–MS spectra. Spirulina bio-crude exhibited the lowest alkane functionality but the highestpercentage (53%) of a-to-heteroatom/unsaturated functionality(1.5–3.0 ppm), possibly due to the large number of nitrogenousand oxygenated compounds derived from the feedstock’s highprotein that have been shown to resonate in this area (Mullenet al., 2009; Zhou et al., 2010). All biocrudes displayed a low per-centage (<2%) of methoxy/carbohydrate functionality (4.4–6.0 ppm), which is consistent with carbohydrates converting intobiocrude oil (Duan and Savage, 2011b) or partitioning into theaqueous phase (Anastasakis and Ross, 2011). In general, the rangeof alkane percentages for all feedstocks (53–69%) was similar toprior 1H NMR analyses of HTL biocrudes produced from themicroalgae Nannochloropsis (Duan and Savage, 2011b) and themacroalgae Enteromorpha prolifera (Zhou et al., 2010). Aromatic/hetero-aromatic functionality was also observed in all biocrudeoils (6.0–8.5 ppm) in agreement with findings from FTIR. Alde-hyde functionality (9.5–10.0 ppm) was absent from all samplesdespite the observed C@O functional groups (1730–1700 cm�1)by FTIR. The appearance of such FTIR bands can also be due toother carbonyl-bearing groups like protonated carboxylic acids,carboxylic acid esters, amides, and ketones.

13C NMR spectra provided greater detail due to their largechemical shift regions and pointed to a high aliphatic content (0–55 ppm) for all biocrude oils as shown in the integrated peak arearegions in Fig. 1b. All samples displayed greater than 65% total ali-phatic carbon with sludge biocrude containing the highest propor-tion (76%), followed by swine manure (71%) and algae (66%)biocrude. Aliphatics were further subdivided into short (0–28 ppm) and long-branched aliphatics (28–55 ppm), with Spirulinabiocrude containing the highest proportion of short aliphatics (27%of total spectrum area) and sludge biocrude containing the highestproportion of long-branched aliphatics (54%). All spectra also con-tained a high proportion of aromatic and olefin carbon assignments(95–165 ppm) which was evident in the FTIR spectra (1600 and1475 cm�1). The aromatic-olefin ranking between biocrudes was

in the opposite order of the total aliphatics, with the Spirulina bio-crude containing the highest percentage (32%), followed by swinemanure (19%) and sludge biocrude (18%). This ranking was re-flected in a-to-heteroatom/unsaturated functionality determinedby 1H NMR (1.5–3.0 ppm) and followed a similar order (Spirulinaalgae > swine manure � digested sludge). Low percentages of alco-hol/ethers/carbohydrates (55–95 ppm) were also observed in all13C NMR spectra, prompting further inquiry into the extent thatcarbohydrates in the feedstock are converted into biocrude oil(Duan and Savage, 2011b) or partition into the aqueous phase(Anastasakis and Ross, 2011). Ketones/aldehydes were also presentin low amounts, similar to findings with HTL algal biocrude oil(Duan and Savage, 2011b). Although minor, swine manure bio-crude contained the highest percentage of esters/carboxylic acids(165–180 ppm), consistent with the fatty acids identified by GC–MS and similar to findings with the moderate lipid algal speciesNannochloropsis (Duan and Savage, 2011b).

Direct comparison of HTL biocrude with conventional petro-leum sources is rather difficult due to differing reported spectraintegration ranges; however, the work conducted by Gupta et al.(1986) with Bombay petroleum crude and synthetic coal-derivedoil is rather revealing. These authors reported that Bombay petro-leum crude 13C NMR spectra area contained 87% total aliphaticcontent (9–60 ppm) while the synthetic coal-derived oil only dis-played 56% of the spectra area, placing HTL biocrudes in betweenthe two sources.

3.3.4. SEC analysis of molecular weightThe molecular weight (MW) distributions measured by SEC

(Fig. 2) further emphasize the distinctive properties of HTL biocru-des produced from various feedstocks. The weight-average molec-ular weights (Mw), which are more heavily biased by high MWmolecules in the oil mixtures, were similar for biocrudes generatedfrom Spirulina (1870 Da) and swine manure (1890 Da), but signifi-cantly higher for the digested sludge biocrude (3470 Da) (Table 4).The number-average molecular weights (Mn), which are morebiased by low MW molecules, followed a similar trend withSpirulina (890 Da) and swine manure biocrude (780 Da) exhibitingsimilar values, and sludge biocrude having a much higher value(1340 Da). The HTL biocrude MWs were significantly higher thanthat of conventional petroleum crudes (�Mn 250) (Speight, 2001)while Spirulina and swine manure biocrude fell within the

Percent of Distributed Protons (%)

0 15 30 45 60 75 0 15 30 45 60

Spirulina Algae

Swine Manure

Anaerobic Sludge

(0.5-1.5 ppm)Alkanes

(1.5-3.0 ppm)α-to-Hetero,Unsaturated

(3.0-4.4 ppm)Alcohols,

Methylene-dibenzene

(4.4-6.0 ppm)Methoxy,

Carbohydrates

(6.0-8.5 ppm)Aromatics, Hetero -

aromatics

Percent of Distributed Carbon (%)

(0-28 ppm)Short Aliphatics

(28-55 ppm)Long Branched

Aliphatics

(55-95 ppm)Alcohols, Ethers,

Carbohydrates

(95-165 ppm)Aromatics, Olefins

(165-180 ppm)Esters, Carboxylic

Acids

(180-215 ppm)Ketones,

Aldehydes

Spirulina Algae

Swine Manure

Anaerobic Sludge

(b)(a)

Fig. 1. 1H NMR (a) and 13C NMR (b) spectral distribution of functional groups present in biocrude oils produced from different wastewater feedstocks based on integratedpeak areas assigned to characteristic spectral regions.

0.00

0.05

0.10

0.15

0.20

0.25

10 100 1000 10000

Nor

mal

ized

Sig

nal I

nten

sity

Molecular Weight

Spirulina Algae

Swine Manure

Anaerobic Sludge

Fig. 2. SEC molecular weight distributions of HTL biocrude oils produced fromdifferent wastewater feedstocks.

D.R. Vardon et al. / Bioresource Technology 102 (2011) 8295–8303 8301

upper-range of North American tar sand bitumens (Mn 538–820)(Bunger et al., 1979).

Polydispersity values (PDI) are indicative of the spread in themolecular weight distribution, with higher PDI values correlatingto greater differences in the minimum and maximum molecularweights from the average molecular weight. Digested sludge bio-crude exhibited the largest spread in molecular weights(PDI = 2.59) followed by swine manure (PDI = 2.42) and Spirulinabiocrude (2.10). The high MW and PDI of sludge biocrude are con-sistent with the high oxygen content derived from polymer-linkingfunctional groups (e.g., esters, ethers) (Adjaye et al., 1992). Theseparameters also tracked with the percentage of long-chainbranched aliphatics identified by 13C NMR and were closely tied

to the boiling point distributions discussed in the followingsection.

3.3.5. Simulated distillation (Sim-Dist)Sim-Dist was used to estimate the boiling point distribution for

HTL biocrudes (Fig. 3), which fell predominantly within the rangeof heavy vacuum gas oil (343–538 �C). Spirulina biocrude had thegreatest percentage (30%) of low boiling point compounds(bp < 343 �C), corresponding to heavy naphtha, kerosene, and gasoil fractions. In contrast, sludge-derived biocrude had the highestpercentage (21%) of high boiling point compounds (bp > 538 �C),corresponding to vacuum residua. Swine manure biocrude fell inbetween, with the greatest percentage (69%) of mid-boiling pointcompounds (bp 343–538 �C) and the lowest percentage of theother two categories. The order of bulk boiling fraction was similarto the order of weight-average molecular weights (MWw) and thepercentage of long-branched aliphatics identified by 13C NMR(Spirulina algae < swine manure < digested sludge).

The compound boiling point-retention time relationship forSim-Dist is a function of structure and heteroatom content, so onlyqualitative comparisons can be made since the Sim-Dist data wascalibrated using n-alkane standards. It is notable that similar trendswere observed for SEC and Sim-Dist data. For example, the vacuumresidua fraction (bp > 538 �C), corresponding to n-alkane com-pounds greater than or equal to n-C43H88 (604 Da), follows theorder of biocrudes derived from swine manure < Spirulinaalgae < anaerobic sludge. Analogously, the MW distribution per-centage between 604 and 11,000 Da follows the same trend. Thedistillable fraction of HTL biocrude oils (bp < 538 �C) ranged from77% to 83% and is comparable to conventional petroleum crudeoil sources that vary by region (e.g., 66% distillable for Venezuelancrude, 98% for Pennsylvania crude) (Speight, 2001). In addition, itis greater than the distillable fraction of North American tar sandbitumens (44–65%) (Bunger et al., 1979).

Table 4Molecular weight distribution parameters of HTL biocrude oil from differentwastewater feedstocks.

MW dist Spirulina algae Swine manure Anaerobic sludge

Mw 1870 1890 3470Mn 890 780 1340PDI 2.10 2.42 2.59

0

10

20

30

40

50

60

70

80

90

100

Heavy Naptha(<193°C)

Kerosene(193-271°C)

Gas Oil(271-343°C)

Vac Gas Oil(343-538°C)

Vac Residua(>538°C)

Perc

ent o

f Sa

mpl

e (%

)

Spirulina Algae

Swine Manure

Anaerobic Sludge

Fig. 3. Sim-Dist boiling point fractions of HTL biocrude oils derived from differentwastewater feedstocks.

8302 D.R. Vardon et al. / Bioresource Technology 102 (2011) 8295–8303

Based on these results, raw HTL biocrude oil produced from thestudied wastewater feedstocks may be best suited for bunker crude,boiler, or asphalt applications, similar to vacuum gas oil and vac-uum residua fractions produced from petroleum crude. The highheteroatom content (oxygenated and nitrogenous compounds),molecular weight, and boiling point distribution of the biocrudesemphasize the need for bio-oil upgrading before HTL biocrudescan serve as a transportation fuel substitute for conventional petro-leum. Several bio-oil upgrading routes have been pursued, includ-ing hydrodeoxygenation (HDO), hydrodenitrogenation (HDN), andhydrocracking with catalysts in conventional hydrotreatment oper-ations and supercritical water (Huber et al., 2006; Elliott, 2007;Peterson et al., 2008; Demirbas, 2009; Duan and Savage, 2011a).The use of molecular-level characterization techniques describedin this work will be beneficial for tracking and better understandingimprovements in biocrude oil chemistry that occur during theupgrading process. However, further research is needed to improvethe control of biomass conversion chemistry, enhance upgradingcatalyst activity, selectivity, and longevity, and scale-up of bothprocess technologies to demonstrable scales (Huber et al., 2006;Elliott, 2007; Demirbas, 2009).

4. Conclusion

Detailed multi-method characterization demonstrates thatfeedstock organic content and nutritional composition greatly af-fect HTL biocrude oil yields and chemistry, despite having similarbulk elemental distributions. The feedstock nutritional profilewas reflected in the heteroatom content, type of compounds, andfunctionality observed in the resulting HTL biocrude oils. The tiebetween feedstock nutritional profile and HTL biocrude molecularmakeup emphasizes the need for feedstock characterization andselection based on the intended downstream application. Themolecular-level information gained from complementary methodscan also help researchers design functional group-specific chemicalstrategies and processes to further reduce heteroatom content andimprove HTL biocrude properties.

Acknowledgements

The research described in this paper has been funded in part bythe United States Environmental Protection Agency (EPA) underthe Science to Achieve Results (STAR) Graduate Fellowship Pro-gram. The EPA has not officially endorsed this publication andthe views expressed herein may not reflect the views of the EPA.Financial support was also provided by the Department of Civiland Environmental Engineering at the University of Illinois andthe National Science Foundation Division of Chemical, Bioengi-neering, Environmental, and Transport Systems (CBET-0746453).

Appendix A. Supplementary data

Supplementary data associated with this article can be found, inthe online version, at doi:10.1016/j.biortech.2011.06.041.

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