How do hydrothermal liquefaction conditions and feedstock type

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How do hydrothermal liquefaction conditions and feedstock type influence product distribution and elemental composition? Rene Bjerregaard Madsen, and Marianne Glasius Ind. Eng. Chem. Res., Just Accepted Manuscript • DOI: 10.1021/acs.iecr.9b02337 • Publication Date (Web): 20 Aug 2019 Downloaded from pubs.acs.org on August 26, 2019

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Industrial & Engineering Chemistry Research

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How do hydrothermal liquefaction conditions and feedstock type influence product

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distribution and elemental composition?

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René B. Madsen and Marianne Glasius*

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Interdisciplinary Nanoscience Center, Department of Chemistry, and Centre for Circular Bioeconomy, Aarhus

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University, Langelandsgade 140, Aarhus, Denmark

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* corresponding author: [email protected]

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Abstract

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We investigated the effects of temperature (250-350 ˚C), reaction time (5-31 min), and solid loading (5-25 wt.%)

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on hydrothermal liquefaction (HTL) of Spirulina, Miscanthus, and primary sewage sludge using a central

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composite study design. Response surface methodology was used to identify maxima/minima for yields of gas,

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bio-crude, aqueous phase (AqP), and solid residue (SR), while the coefficients were used to identify the flux the

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four product fractions. Effects on carbon recovery and contents of nitrogen and oxygen of the bio-crude were

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also assessed. The high bio-crude yields of Miscanthus and Sewage sludge mainly resulted from low yields of

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SR. Higher solid loading of Spirulina and Miscanthus increased bio-crude yields, while carbon recovery often

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improved with higher temperature and longer reaction time. Common to all feedstocks, the amount of degraded

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biomass displaced to the AqP decreased with increasing solid loading but simultaneously resulted in more

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nitrogen in the bio-crude.

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1. Introduction

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Mitigation of climate change and dwindling fossil oil reserves are the key drivers behind development of a circular

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economy with sustainable production of renewable chemicals and fuels. The continuing growth of the human

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population (estimated at 8.25 ± 2.5 billion in 2030)1 and increasing wealth will further increase the demand for

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transportation fuel. While several potential solutions exist for replacement of fuel for road vehicles, such as

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electricity and hydrogen, the aviation sector will rely on the current liquid fuel options in 2050 where the aviation

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fuel consumption is projected to outpace the fuel consumption reduction.2 Studies have pointed to hydrothermal

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liquefaction (HTL) as a suitable technique for production of a bio-crude, which can be further upgraded to aviation

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fuel with considerable reduction of greenhouse gas emission.3,

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compressed water by employing typical conditions of 250-350 ˚C and 200-300 bar pressure.5 At these conditions,

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the dielectric constant decreases and the self-dissociation constant increases allowing acid-base catalysis and

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solvation of less polar compounds resulting in a bio-crude with reduced contents of oxygen and nitrogen.6 The use

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of water as reaction media makes HTL highly flexible to diverse feedstocks with the only requirement that it can

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be suspended in water for effective pumping at high pressure. The feedstock flexibility has been demonstrated in

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batch experiments where numerous biomasses have been explored including lignocellulosics (e.g. Miscanthus,

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HTL exploits the unique properties of hot

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pine, willow, aspen, bagasse, spent coffee ground), microalgae (e.g. Spirulina, Chlorella pyridenosa), macroalgae

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(e.g. laminaria hyperborea), and residues (e.g. manure, sludge, digestate, pomace, dairy effluent). The

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biochemical composition of the feedstock is one of the most important contributing factors of bio-crude yields,

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which is obtained in descending order lipid > protein > carbohydrate > lignin7, 8 while temperature, reaction time,

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solid loading, and the use of additives have lesser but in many cases still significant effects.9 Although multiple

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factors influence the outcome of HTL, most studies that have systematically investigated the effects of varying

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process parameters have performed a one variable at a time approach. A few studies have employed central

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composite designs to allow investigation of interactions of process parameters for a single feedstock while mixed

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model designs have been used to investigate the use of model compounds.7, 10-12 Previous studies have shown

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that the bio-crude yield from microalgae can be predicted based on the biochemical content.13 Recently, Yang, et

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al. 14 combined a mixed model design for model compounds with a fractional factorial design to develop a model

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estimating the yields of bio-crude and solid residue. Hence, previous studies have either focused on single

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biomasses or specific product fractions, which limits insights into the flux of degradation products to the different

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fractions.

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Parameter studies using batch reactors are the preferred mode for optimizing bio-crude yields but the viscosity of

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the bio-crude means that organic solvents are required to recover it from the reactor. However, the diverse

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feedstocks and parameter settings applied for HTL also means that the yield and composition of the bio-crude

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varies greatly and the ideal solvent is dependent hereof making comparison of literature values difficult. Several

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studies have investigated the effects of recovery solvents where dichloromethane often performs well as shown

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for microalgae and duckweed while acetone has been the solvent of choice for lignocellulosics.15-18 Hence, direct

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comparison of different feedstocks for HTL should preferably rely on a standardized work up procedure where a

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combination of solvents is used.

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In this study, three of the most widely applied feedstocks (Spirulina, Miscanthus, and primary sewage sludge) for

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HTL were systematically investigated. Each biomass was subjected to a circumscribed central composite design

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with variation of temperature, reaction time, and solid loading, which allows for investigation of linear effects and

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interactions among process variables along with potential identification of maximum or minimum yields of all four

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different product fractions as well as content of heteroatoms, and carbon recovery of the bio-crude. The aim was

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to provide a detailed investigation of the effect of process parameters for each feedstock and to allow direct

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comparison of the feedstocks by using a standardized product work up with acetone and dichloromethane as

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recovery solvents. To our knowledge, this is the most extensive exploration of process variables in HTL where

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different feedstocks can be directly compared and it provides insight to both the independent effects of process

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variables but also the interactions governing product distribution. The distribution of carbon, nitrogen, and oxygen

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to the bio-crude allows identification of process conditions where nitrogen and oxygen can be minimized and

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carbon recovery maximized.

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2. Materials and methods


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2.1 Chemicals and reagents

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Spirulina platensis was purchased from Inner Mongolia Rejuve Biotech Co. Ltd. (Otog Inner Mongolia, China) as

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a dry powder and used as received. Miscanthus was obtained from Department of Agroecology, Denmark

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(harvested in January 2018). Stems and leaves were chopped into coarse pieces and subsequently extruded.

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Afterwards it was dried at 105 ˚C overnight. Primary sewage sludge was obtained from Marselisborg water

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filtration, Denmark at approximately 5 wt.%. The sludge was dried at 105 ˚C until constant weight to avoid

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digestion. Acetone (SigmaAldrich) and dichloromethane (Merck) were HPLC grade. The proximate and ultimate

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analyses of the feedstocks are presented in Table 1.

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Table 1. Proximate and ultimate analysis of feedstocks Sample

C (wt.%, db)

H (wt.%, db)

N (wt.%, db)

S (wt.%, db)

O (wt.%, db)*

Spirulina

50.6

7.0

11.8

0.8

23.3

Moisture (wt.%) 7.4

Ash (wt.%) 6.5

Miscanthus

49.1

3.8

0.7

0.2

42.0

12.1

4.2

Primary sludge

46.5

6.1

3.3

0.4

5.8

3.7

37.9

79 80 81

* determined by difference db is dry basis

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2.2 Experimental design

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The aim of the study was to explore the most important variables of the product distribution from HTL. The key

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factors for product distribution and composition are biomass type, reaction temperature, reaction time, and solid

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loading, of which biomass type is the most important variable.19 The three different biomasses were chosen to

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represent the diversity of feedstocks used in HTL and to span the elemental composition (carbon: 46.5 – 50.6%,

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hydrogen: 3.8 – 7.0%, nitrogen: 0.7 – 11.8%, sulphur: 0.2 – 0.8%, oxygen: 5.8 – 42.0%). To explore the effect of

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temperature, reaction time, and solid loading a circumscribed central composite design (CCD) was employed

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(Table 2). The range of temperature was 250-350˚C, reaction time was 5-31 min, and solid loading was 5-25 wt.%.

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The settings for the process variables were chosen based on optimal values obtained for other batch studies of

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microalgae and lignocellulosics.11,

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achieved for continuous HTL even for lignocellulosics and has a significant effect on the minimum fuel selling

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price.21, 22

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Table 2. Factor levels for the experimental design Parameter Temperature - ˚C Reaction time – min Solid loading – wt.%

-1.633 250 5 5

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Solid loading was increased up to 25 wt.%, which has previously been

-1 270 10 9

0 300 18 15

1 330 26 21

1.633 350 31 25

95 96 97

Data for the CCD of each feedstock was fitted to the following quadratic model using the factor levels: 𝑌 = 𝑋0 + 𝑋1𝐴 + 𝑋2𝐵 + 𝑋3𝐶 + 𝑋12𝐴𝐵 + 𝑋13𝐴𝐶 + 𝑋23𝐵𝐶 + 𝑋11𝐴2 + 𝑋22𝐵2 + 𝑋33𝐶2



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The model takes into account the linear terms, interactions, and quadratic effects of reaction temperature (A),

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reaction time (B), and solid loading (C). Each model was evaluated based on R2, p-value, F-value, and relative

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squared error (RSE). The significance of each parameter was evaluated based on p-values. Response surface

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methodology was used to evaluate the effect of each parameter based on only statistically significant coefficients.

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Center point experiments were performed six times, while all other experiments were performed in duplicates. The

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experimental error of the HTL process and product separation was evaluated based on the six replicates of the

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center point. The standard deviations were; gas ≤ 0.7-1.4%, bio-crude ≤ 1.8-2.6%, SR ≤ 0.3-2.0%, and AqP ≤ 1.3-

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2.7%. However, this does not represent the experimental error for the remaining batches as the difficulty of product

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separation varies significantly. The models are presented in tables throughout the result section and can be used

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to estimate product yields if the process parameters are converted to factor levels. Determining bio-crude yields

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is illustrated in supplementary information (A.1).

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2.3 Hydrothermal liquefaction

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The HTL experiments were conducted with 20 ml batch reactors. Reactors were loaded with biomass according

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to the CCD, filled with demineralized water to 10 g and mixed in the reactors. The reactors were sealed and

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lowered into an Omega Engineering FSB-4 fluidized sand bath preheated to the designated temperature. The

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highest reaction temperature of 350 ˚C was reached within 4 min. The reaction time included both the heating

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period and the residence time at the designated reaction temperature. Afterwards the reactors were cooled to

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ambient temperature in a water bath. In order to compare results despite the variation in feedstock type and

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reaction parameters, the product separation was standardized without extraction of the AqP. However, at low

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temperature, short reaction time, and high solid loading it is often difficult to obtain a clearly separated AqP as the

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biomass conversion may be limited, especially for lignocellulosics. The reactors were weighed, vented, and

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weighed again to determine the amount of gas produced. The AqP was decanted into a centrifuge tube. If the

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obtained AqP amounted to > 90% of the original water content no further collection of AqP was done. If the

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obtained AqP amounted to < 90% of the original water content the walls of the reactor were scraped to the bottom

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of the reactor to reledase pockets of water and the contents were squeezed with a spatula to release water from

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unconverted biomass. If the obtained AqP was still not satisfactory, the solid content of the reactor was retrieved

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with a spatula and placed in the same centrifuge tube as the AqP. Subsequently the AqP was centrifuged two

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times at 6000 rpm for 5 min where the AqP was transferred with a pipette to a 12 mL glass vial after each

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centrifugation. The headspace of the vial was flushed with argon and stored at 5 ˚C until further analysis. After

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separation of the AqP the reactor was extracted with small amounts of dichloromethane and acetone (additions of

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1 mL). Extraction with one solvent was performed until the recovered solvent appeared clear followed by the

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second solvent and scraping of the reactor walls (total between 5 and 15 mL). Bio-crudes from Spirulina and

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sewage sludge were first extracted with dichloromethane while acetone was first used for Miscanthus. The organic

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phases were combined and was vacuum filtrated through a filter paper. The precipitate from recovery of the AqP

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was centrifuged again and the AqP hereof (small amounts) was discarded while the remaining solid matter was


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added to the filter paper. We chose to discard the AqP from the second round of centrifugation, since the

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previously collected AqP had already been flushed with argon and sealed to avoid changes to AqP composition

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upon re-opening of the vials (which we have previously observed). The filter paper was thoroughly washed with

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dichloromethane and acetone. The solvents were evaporated under a stream of nitrogen to obtain the bio-crude.

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The solid residue (SR) was obtained by drying the filter paper overnight at 105 ˚C. The yields of the different

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fractions were determined based on dry and ash free (daf) basis of the biomass according to the following

139

equations. 𝑔𝑎𝑠𝑚𝑎𝑠𝑠

140

𝑌𝑖𝑒𝑙𝑑𝑔𝑎𝑠 =

141

𝑌𝑖𝑒𝑙𝑑𝑏𝑖𝑜 ― 𝑐𝑟𝑢𝑑𝑒 =

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𝑌𝑖𝑒𝑙𝑑𝑠𝑜𝑙𝑖𝑑 𝑟𝑒𝑠𝑖𝑑𝑢𝑒 =

143

𝑌𝑖𝑒𝑙𝑑𝐴𝑞𝑃 𝑎𝑛𝑑 𝑙𝑜𝑠𝑠 =

𝑓𝑒𝑒𝑑𝑠𝑡𝑜𝑐𝑘𝑚𝑎𝑠𝑠,

× 100 𝑑𝑎𝑓

𝑏𝑖𝑜 ― 𝑐𝑟𝑢𝑑𝑒𝑚𝑎𝑠𝑠 𝑓𝑒𝑒𝑑𝑠𝑡𝑜𝑐𝑘𝑚𝑎𝑠𝑠,

𝑠𝑜𝑙𝑖𝑑 𝑟𝑒𝑠𝑖𝑑𝑢𝑒𝑚𝑎𝑠𝑠 𝑓𝑒𝑒𝑑𝑠𝑡𝑜𝑐𝑘𝑚𝑎𝑠𝑠,

× 100

𝑑𝑎𝑓

× 100

𝑑𝑎𝑓

𝑓𝑒𝑒𝑑𝑠𝑡𝑜𝑐𝑘𝑚𝑎𝑠𝑠,𝑑𝑎𝑓 ― 𝑔𝑎𝑠𝑚𝑎𝑠𝑠 ― 𝑏𝑖𝑜 ― 𝑐𝑟𝑢𝑑𝑒𝑚𝑎𝑠𝑠 ― 𝑠𝑜𝑙𝑖𝑑 𝑟𝑒𝑠𝑖𝑑𝑢𝑒𝑚𝑎𝑠𝑠 𝑓𝑒𝑒𝑑𝑠𝑡𝑜𝑐𝑘𝑚𝑎𝑠𝑠,

× 100

𝑑𝑎𝑓

144

Throughout the text, the AqP yield is defined as the percentage of feedstock retained in the AqP (also including

145

mass lost during work-up). We calculated AqP yield by difference (as the second round of AqP from centrifugation

146

was discarded), which introduces uncertainty to the mass balance. Interpretation of the coefficient from AqP yield

147

modelling should be made with caution as experiments from low reaction temperature, short reaction time, and

148

high solid loading may lead to overestimation. The moisture content of the biomasses was determined by loss on

149

drying at 105 ˚C until constant weight. The ash content was determined by incineration at 550 ˚C for 5 hours. The

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elemental composition of the biomasses and the bio-crude was determined using a CHNS-O Elementar Vario

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MACRO cube analyzer (Elementar Analysensysteme). Oxygen contents were determined by difference. The

152

higher heating value (HHV) was calculated according to the Boie equation.

153

𝐻𝐻𝑉𝐵𝑜𝑖𝑒 (𝑀𝐽 𝑘𝑔 ―1) = 0.3516𝐶 + 1.16225𝐻 ― 0.1109𝑂 + 0.0628𝑁 + 0.10465𝑆

154

The energy recovery (ER) and carbon recovery (Crec) of the bio-crude were calculated according to the following

155

equations.

156

𝐸𝑅 = 100 𝑥

157

𝐻𝐻𝑉𝑏𝑖𝑜 ― 𝑐𝑟𝑢𝑑𝑒 𝐻𝐻𝑉𝑓𝑒𝑒𝑑𝑠𝑡𝑜𝑐𝑘

𝐶𝑟𝑒𝑐 = 100 𝑥

𝐶𝑏𝑖𝑜 ― 𝑐𝑟𝑢𝑑𝑒 𝐶𝑓𝑒𝑒𝑑𝑠𝑡𝑜𝑐𝑘

𝑥 𝑌𝑖𝑒𝑙𝑑𝑏𝑖𝑜 ― 𝑐𝑟𝑢𝑑𝑒

𝑥 𝑌𝑖𝑒𝑙𝑑𝑏𝑖𝑜 ― 𝑐𝑟𝑢𝑑𝑒

158

Average values of all product yields, CHNS-O, carbon recovery, HHV, and ER are presented in supplementary

159

information for reference (average values were not used for model fitting).

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3. Results and discussion



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We focus on the effects of process parameters on yields of gas, bio-crude, SR, and AqP as well as migration of

162

heteroatoms to the bio-crude and its carbon recovery and ER in order to identify optimal conditions. Data of key

163

variables are presented as response surface (RS) plots including only statistically significant coefficients where

164

the remaining variable is kept constant at factor level zero. The RS plots are used to identify a potential optimum,

165

which would ideally mean lowest yield of gas, SR, AqP, and the highest yield of bio-crude along with low

166

contents of heteroatoms and high carbon recovery and ER of the bio-crude. Note that the coefficients of

167

variables are not directly comparable as the absolute values are different (e.g. temperature is 10 times larger

168

than solid loading).

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3.1 Spirulina

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3.1.1 Gas yield

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The gas yield range for Spirulina was 6.8 – 17.8 wt.%. The gas yields are within the range of previous results for

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protein rich microalgae at these conditions.23-25 The lowest yield was obtained at 250 ˚C, 18 min, and 15 wt.%

173

while the highest yield was obtained at 330 ˚C, 26 min, and 21 wt.%. The gas model was found to be statistically

174

significant (R2 = 0.95, p = 5.09 x 10-13, F = 46.47, RSE = 0.8916) as seen in Table 3.

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Table 3. Coefficients and figure of merit for the quadratic models of gas, bio-crude, and solid residue from HTL of

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Spirulina Gas

Coefficient

X0 X1 X2 X3 X12 X13 X23 X11 X22 X33 R2 p F RSE

11.6546 2.9769 1.2862 0.5215 0.9014 1.0382 -02797 0.0838 -0.5320 0.7074 0.9457 5.09 x 10-13 46.47 0.8916

p-value

7.09 x 10-15 1.41 x 10-7 0.0066 0.0006 0.0001 0.2340 0.6681 0.0110 0.0012

Biocrude X0 X1 X2 X3 X12 X13 X23 X11 X22 X33 R2 P F RSE

Coefficient 38.5940 1.2985 0.8464 3.0406 -1.6491 2.5819 1.9181 -2.7687 -3.3736 -1.9336 0.8474 8.75 x 10-8 14.81 2.503

p-value

0.0133 0.0984 1.80 x 10-6 0.0158 0.0005 0.0059 2.64 x 10-5 1.60 x 10-6 0.0014

Solid residue X0 X1 X2 X3 X12 X13 X23 X11 X22 X33 R2 P F RSE

Coefficient 3.9976 -2.2388 -1.6757 0.3879 1.3938 -0.3716 0.1619 0.2554 0.1105 -0.9385 0.917 7.51 x 10-11 29.47 1.028

p-value

3.68 x 10-11 1.01 x 10-8 0.0602 1.42 x 10-5 0.1610 0.5345 0.2496 0.6143 0.0002

AqP

Coefficient

X0 X1 X2 X3 X12 X13 X23 X11 X22 X33 R2 P F RSE

46.7449 -2.0366 -0.4568 -3.9500 -0.6460 -3.2284 -1.8004 2.0912 3.4567 1.8259 0.8152 7.70 x 10-7 11.76 3.189

p-value

0.0027 0.4613 1.08 x 10-6 0.4257 0.0005 0.0333 0.0047 2.86 x 10-5 0.0120

177 178

The linear effects of temperature, reaction time, and solid loading on gas yield were all significant with positive

179

coefficients. Temperature had the largest linear effect as higher temperature promotes degradation of biomass

180

and its products. Carbon dioxide is the major gas phase component with decarboxylation being the main mode

181

of gas formation for microalgae up until 350 ˚C after which cracking starts to increase.26 The large effect of

182

temperature on gas formation from protein rich microalgae was previously shown with a linear effect for

183

Chlorella27 and for Spirulina26 with higher lipid contents, however, gas yields can be constant at temperatures

184

above 260 ˚C for Chlorella with negligible lipid content.25 Extended reaction times show a less pronounced linear

185

effect on gas yield, somewhat similar to other studies processing microalgae with higher lipid contents.26, 28 The

186

extended reaction times may simply lead to further decarboxylation of degraded biomass. A smaller though


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187

positive linear effect is seen from increased solid loading. Furthermore, there are significant positive interactions

188

from temperature with reaction time and solid loading meaning that with simultaneous small or large parameter

189

values the gas yield is further increased. Reaction time had a negative quadratic effect, i.e. with long reaction

190

times the gas formation increases less. At high temperatures this could mean that extensive decarboxylation has

191

occurred and further gas formation is from slower cracking of biomass product. At lower temperatures it may be

192

indicative of extensive decarboxylation of initially free carboxylic acids, while further decarboxylation relies on the

193

degradation of biomass to release free carboxylic acids. However, the linear effects and the strong positive

194

interaction with temperature dominates the RS plot of temperature and reaction time (Fig. 1, row 1 left). Minima

195

are obtained with low temperature and either short or long reaction times due to the positive interaction.

196

However, higher temperatures are desirable for improving bio-crude yields. When high temperatures (≥ 300 ˚C)

197

are employed, the reaction time should be kept to a minimum because at these temperatures, increased reaction

198

time leads to a rapid increase in gas production. Solid loading gave a positive quadratic effect, which provides a

199

minimum value while gas formation is increased at lower or higher solid loadings. However, the positive

200

interaction with temperature means that it is desirable to maintain the temperature at ≤ 300 ˚C with high loadings

201

(> 15 wt.%) while it could be preferable to increase the temperature (> 300 ˚C) with lower loadings (< 15 wt.%)

202

as seen from Fig 1 (row 1 middle). The positive linear effect and the negative quadratic effect from reaction time

203

is easily observed from the RS plot (Fig. 1, row 1 right) with solid loading where the increasing gas yield levels

204

off at higher reaction times. Gas formation is lowest at short reaction times and solid loading around 12 wt.%.

205

Maintaining the solid loading at 12 wt.% leads to the smallest increase in gas formation with increasing reaction

206

time providing a local minimum at 26 min from where solid loading can be increased to 20 wt.% without affecting

207

gas yields.

208



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210

211 212

Figure 1. Response surface plots of gas (row 1), bio-crude (row 2), solid residue (row 3), and AqP (row 4) for

213

HTL of Spirulina. Left) temperature and reaction time, Middle) temperature and solid loading, Right) reaction time

214

and solid loading

215 216

3.1.2 Bio-crude yield

217

The bio-crude yields were in the range of 19.8 – 39.2 wt.%, in agreement with previous studies on Spirulina23, 29

218

while they are in some cases slightly lower than yields obtained for microalgae with higher lipid contents.28 The

219

lowest yield was obtained at 330 ˚C, 26 min, and 9 wt.% while the highest yield was obtained at 300 ˚C, 18 min,

220

and 15 wt.%. The bio-crude model was found to perform satisfactorily (R2 = 0.85, p = 8.75 x 10-8, F = 14.81, RSE

221

= 2.503, Table 3). The linear effects of temperature, reaction time, and especially solid loading were all

222

significantly positive. Previous studies of HTL of protein-rich microalgae have found that bio-crude yields

223

increase until approximately 300 ˚C after which it either stabilizes or decreases.26, 28, 30 Reaction time may be


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224

important at certain time intervals, most likely at low temperature and high loading.26 Only few studies have

225

investigated the effect of solid loading for HTL of microalgae. Valdez 28 found that the bio-crude yields increased

226

with solid loading while Jena, et al. 31 found that it did not change. In both cases process conditions of 350 ˚C

227

and 60 min were used, making the present results comparable only at these extreme conditions. The increased

228

bio-crude yields from high solid loading is likely due to shift in the partitioning of compounds with low solubility in

229

water, such as fatty acids and some phenolics. As less water is available more of these compounds will dissolve

230

in the bio-crude. At the same time the pH value was found to increase by approximately 0.5 when solid loading

231

was doubled, which to some extent may enhance biomass degradation or decrease SR formation.

232

A negative interaction between temperature and reaction time was observed. This interaction was observed to

233

be positive for gas and SR formation, which may indicate that at high temperature and long reaction time bio-

234

crude components begin to undergo cracking and coke and char formation as competing reactions. At low

235

temperature and short reaction time the biomass is first stripped of volatile components while the conditions are

236

insufficient for biomass degradation. On the other hand, positive interactions were observed for solid loading

237

with temperature and reaction time. These positive interactions may be due to a more rapid increase of pH

238

allowing for improved biomass degradation and reduced coke and char formation. Another possible explanation

239

could be that the increased solid loading leads to a more rapid saturation of the water with degradation products,

240

which has been proposed to be the reason for improved bio-crude yields during water recirculation.32, 33

241

All quadratic terms were found to be significant and negative resulting in global maxima for all RS plots. The RS

242

plot of temperature and reaction time has a wide plateau maximum at 300 ˚C and 18 min (Fig. 1, row 2 left).

243

Similarly, Valdez 28 studied HTL of protein rich microalgae (250–400 ˚C, 0-90 min) and found that bio-crude

244

yields were highest at 300 ˚C and 20 min. The RS plot of temperature and solid loading shows that severe

245

reaction parameters provides the highest yield at 325 ˚C and 22 wt.% (Fig. 1, row 2 middle). Similarly, the RS

246

plot of reaction time and solid loading shows that a reaction time around 18-20 min provides the highest bio-

247

crude yields if processing approximately 20 wt.% Spirulina (Fig. 1, row 2 right). Wei and Jie 34 also studied HTL

248

of Spirulina using a CCD, and many similarities are observed, even though they applied higher temperature

249

(315-375 ˚C), longer reaction times (20-60 min), a 2 L parr reactor with 2 C/min heating, and chloroform

250

extraction of the AqP. Their linear and quadratic effects were very similar to the current study, while no

251

interactions were observed and the optimum process parameters were different, which is likely due to the

252

differences in reactor types and extraction method. In a study of Chlorella pyrenoidosa by Gai, et al. 20 solid

253

loading was found to be almost insignificant and temperature was the most important parameter, however, only

254

the toluene-dissolved fraction of the raw oil was considered as bio-crude.

255

3.1.3 Solid residue yield

256

No SR was formed at 300 ˚C, 18 min, and 5 wt.% solid loading while up to 10.8 wt.% SR was obtained at 270

257

˚C, 10 min, and 21 wt.% solid loading. The quadratic model for SR performed well (R2 = 0.92, p = 7.51 x 10-11, F

258

= 29.47, RSE = 1.028, Table 3). The linear effects of the three variables were all significant with temperature and



Page 10 of 31

259

reaction time being the most important and negative. The quadratic effects of temperature and reaction time

260

were non-significant indicating that limited char formation occurs, and SR is mostly from non-degraded biomass

261

as observed from the RS plot (Fig. 1, row 3 left). However, interaction of temperature and reaction time was

262

significant and positive, meaning that the decrease in SR yield levels off at high temperature and long reaction

263

time as the biomass is fully degraded. On the other hand, the linear effect of solid loading was significantly

264

positive, while the quadratic effect was negative. This leads to a ridge of maximum SR yield for solid loadings of

265

15-18 wt.%, which decreases at higher and lower solid loadings as observed for the RS plots with temperature

266

(Fig. 1, row 3 middle) and reaction time (Fig. 1, row 3 right). Hence, with the max bio-crude yield obtained with

267

solid loadings > 18 wt.% it seems highly beneficial for large scale HTL to maintain high solid loadings for protein-

268

rich microalgae.

269

3.1.4 Aqueous phase yield

270

The yield of products in the AqP was as high as 46.4 - 63.9 wt.%. Multiple experiments gave low yields, but

271

common to these were temperatures ≥ 300 ˚C and solid loadings ≥ 15 wt.%, while the highest yield was at 330

272

˚C, 26 min, and 9 wt.%. The quadratic model was significant but only with a decent fit (R2 = 0.82, p = 7.7 x 10-7,

273

F = 11.76, RSE = 3.189, Table 3). The linear effects were significantly negative for temperature and especially

274

solid loading, while a strong negative interaction between the two was also found. The linear effect of reaction

275

time was non-significant, but a negative interaction was found with solid loading. Instead, the quadratic effect of

276

reaction time was stronger than for temperature and solid loading while being positive for all three.

277

The RS plot of temperature and reaction time shows a minimum yield at 315 ˚C and 18 min while the yield

278

increases slowly with differences of ± 15 ˚C and ± 4 min (Fig. 1, row 4 left). The RS plots of solid loading with

279

temperature and reaction time, respectively, show that minimum AqP yield is obtained by increasing the solid

280

loading to 20-25 wt.% while maintaining > 330 ˚C and 18-22 min reaction time (Fig. 1, row 4 middle and right).

281

The negative interactions of solid loading with both temperature and reaction time significantly lowers the yield at

282

high parameter settings.

283

Kinetic models have been proposed that consider AqP products to be in equilibrium with bio-crude.35, 36 The

284

initially decreasing AqP yield from increasing temperature is accompanied by decreasing SR yields, while bio-

285

crude and especially gas yields increase. The high-protein content is simply depolymerized to amino acids

286

(decreasing SR), which are further decarboxylated to amines (increasing gas). Amines and ammonium are

287

nucleophilic and will form imines with ketones and aldehydes, which we have previously proposed to be

288

precursors of N-heterocyclic compounds present in bio-crude (increasing bio-crude).37 They may also form

289

amides with fatty acids. As the temperature is raised above 300 ˚C, deamination becomes more prevalent, which

290

forms water soluble carboxylic acids and ammonium and increases the AqP yield. Additionally, the bio-crude

291

constituents may begin to crack, which will further increase gas yield, while decreasing bio-crude yield. The

292

decreasing AqP yield from increasing solid loading is almost solely offset by increasing bio-crude yield, which is

293

the case not only for the linear and quadratic effects but also for the interactions with temperature and reaction


Page 11 of 31 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


294

time. Hence, increased loading seems to facilitate reactions towards less polar compounds from ring-forming

295

reactions or increased decarboxylation, while the AqP is also gradually saturated leading to increasing bio-crude

296

yields.32

297

3.1.5 Elemental composition

298

Elemental composition of the bio-crude is important, as it directly affects the higher heating value, and if diesel

299

fuel specifications are desired, the vast majority of heteroatoms will have to be removed via catalytic

300

hydrotreatment, where the hydrogen demand is directly related to the heteroatom content. The HTL process

301

significantly reduces the nitrogen and oxygen content compared to the biomass, but further upgrading is

302

required through catalytic hydrotreatment where particularly nitrogen may prove troublesome.38, 39 The ultimate

303

goal of HTL is to recover as much carbon as possible in the form of a combustible fuel with HHV similar to fossil

304

fuel. Modelling of the content of nitrogen and oxygen as well as recovery of carbon and energy was therefore

305

performed to identify ideal process conditions (Table 4). For Spirulina the model for ER was nearly identical to

306

carbon recovery and is therefore not displayed with RSM.

307

Table 4. Coefficients and figure of merit for the quadratic models of nitrogen, oxygen, carbon recovery (C rec),

308

and energy recovery (ER) from HTL of Spirulina N X0 X1 X2 X3 X12 X13 X23 X11 X22 X33 R2 P F RSE

Coefficient 6.9972 0.0873 0.1538 0.4771 -0.4550 -0.1313 -0.2463 -0.2012 -0.1596 -0.0845 0.8318 2.65 x 10-7 13.19 0.3283

p-value 0.1773 0.0221 7.80 x 10-8 1.06 x 10-5 0.1229 0.0062 0.0077 0.0299 0.2334

O X0 X1 X2 X3 X12 X13 X23 X11 X22 X33 R2 P F RSE

Coefficient 19.5609 -2.4501 -2.0150 -0.0202 0.7231 -0.0153 0.0601 -0.3383 -0.3610 -1.1039 0.8920 1.62 x 10-9 22.03 1.252

p-value 3.17 x 10-10 1.29 x 10-8 0.9336 0.0298 0.9615 0.8490 0.2117 0.1837 0.0003

C rec X0 X1 X2 X3 X12 X13 X23 X11 X22 X33 R2 p F RSE

Coefficient 49.3369 3.0422 2.1433 3.8573 -2.3573 3.5513 2.6812 -3.1947 -3.9366 -1.7231 0.8384 1.67 x 10-7 13.84 3.631

p-value 0.0002 0.0051 3.17 x 10-10 0.0158 0.0007 0.0069 0.0003 2.86 x 10-5 0.0336

ER X0 X1 X2 X3 X12 X13 X23 X11 X22 X33 R2 p F RSE

Coefficient 48.5636 3.0865 2.2119 3.8736 -2.1568 3.5458 2.6912 -3.1038 -3.9427 -1.7578 0.8326 2.50 x 10-7 13.27 3.705

p-value 0.0002 0.0047 1.29 x 10-5 0.0286 0.0008 0.0078 0.0006 3.64 x 10-5 0.0337

309 310

The nitrogen content was 4.1% - 7.8%. The quadratic fit was significant with a decent fit (R2 = 0.83, Table 4).

311

Solid loading had the largest linear effect (positive), while reaction time also had a smaller positive effect.

312

Reaction time had negative interactions with temperature and solid loading, which lead to lower nitrogen

313

contents when both parameters are either small or large. The quadratic effects were significantly negative for

314

temperature and reaction time. The RS plot of temperature and reaction time shows the combined effect leading

315

to a ridge of maximum nitrogen content from high temperature and short reaction time to low temperature and

316

long reaction time (Fig. 2, row 1 left). Hence, obtaining high bio-crude yields is directly linked to maximum

317

nitrogen content, where increasing or decreasing temperature and reaction time simultaneously will decrease

318

the nitrogen content at the expense of a considerable reduction in bio-crude yield. Even worse is the adjustment

319

of the parameters in opposite directions, which will decrease the bio-crude yield, while maintaining a high

320

nitrogen content. The RS plot of reaction time and solid loading shows a somewhat similar picture, but the



321

smaller negative interaction means that the ridge is less pronounced and only small changes are found at

322

optimal conditions for the bio-crude yield making high solid loading ideal for Spirulina (Fig. 2, row 1 right).

Page 12 of 31

323

324

325 326

Figure 2. Response surface plots of nitrogen (row 1), oxygen (row 2), and carbon recovery (row 3) for HTL of

327

Spirulina. Left) temperature and reaction time, right) reaction time and solid loading

328

The oxygen content was 12.8% - 24.3%, and the quadratic model had a good fit (R2 = 0.89). Temperature and

329

reaction time had significant negative linear effects along with a positive interaction. The positive interaction may

330

be used to combine high temperature and short reaction time for slightly greater decarboxylation or long reaction

331

time with low temperature (Fig. 2, row 2 left). However, this will substantially decrease the bio-crude yield. Solid

332

loading displayed only a negative quadratic effect, and maximum oxygen content is observed with approximately

333

16 wt.%. (Fig. 2, row 2 right). Increasing the solid loading from 16 wt.% to 25 wt.% can decrease the oxygen

334

content by 2 wt.%, while at the same time increasing bio-crude yield. Interestingly, the quadratic model is quite

335

similar to the model for SR. This shows that there is a correlation between the SR yield and the degree of

336

deoxygenation of the biomass as limited coke and char formation seems to occur.


Page 13 of 31 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


337

The carbon recovery was between 28.2% and 52.4%, and the quadratic model had a decent fit (R2 = 0.84, Table

338

4). The effects of the parameters were very similar to those from bio-crude yields. This leads to an RS plot for

339

temperature and reaction time (Fig. 2, row 3 left) that is highly similar to bio-crude yields although the maximum

340

carbon recovery is slightly skewed towards higher temperature (315 ˚C). Solid loading displayed significant

341

positive interactions with temperature and reaction time (Fig 2, row 3 right). The highest carbon recoveries were

342

found with solid loadings of 25 wt.% combined with 350 ˚C and 25 min (only reaction time and solid loading is

343

shown in Fig. 2), which are slightly higher process parameter than for optimum bio-crude yields. A significant

344

increase in carbon recovery is achieved by increasing solid loading from 5 wt.% to 15 wt.% when ≥ 270 ˚C and ≥

345

10 min. The increase in carbon recovery is even higher at > 300 ˚C, > 18 min, and > 15 wt.% solid loading.

346

3.1.6 Conclusion on process conditions for Spirulina

347

Spirulina was easy to process and a maximum bio-crude yield of approximately 40 wt.% can be obtained at 300-

348

325 ˚C, 18-20 min, and 20-22 wt.% solid loading. The maximum bio-crude yield coincides with a minimum yield

349

of AqP, which is still higher than other feedstocks due to its high protein content. The optimum conditions for

350

temperature and reaction time mainly result in decreasing AqP and SR yields while bio-crude and gas yields

351

increase. Applying high solid loading of Spirulina is highly advantageous as the AqP yield decreases while

352

partitioning the products mostly to the bio-crude. Unfortunately, high bio-crude yields are also linked to high

353

nitrogen content of the bio-crude (7.3% – 7.4%) where mainly temperature and reaction time increases the

354

nitrogen content. The oxygen content at these conditions is 15.7% - 22.9% where temperature and reaction time

355

mainly decreases the content while it is increased by solid loading. High carbon recovery (55.9%) was also

356

obtained at the optimum conditions for bio-crude yield but increasing all process variables slightly leads to

357

improved carbon recoveries (59.1%). Hence, processing of Spirulina should be carried out at temperatures

358

slightly lower than those often applied during HTL if high bio-crude yields and low AqP yields are desired.

359

However, carbon recovery benefits from increasing the process conditions beyond the optimal conditions for bio-

360

crude yields. At the same time, it seems highly beneficial to increase the solid loading above the often applied

361

10-15 wt.%.

362

3.2 Miscanthus

363

3.2.1 Gas yield

364

Addition of alkaline reagents are often beneficial for processing of lignocellulosics as bio-crude yields are

365

improved along with lower SR formation.40 However, for the sake of being able to directly compare the different

366

biomasses used in this study we chose to not use alkaline reagents even though this makes comparison with

367

literature values less appropriate. The effect of alkaline reagents on gas formation varies, as some studies find

368

no effect while others find a significant increase.41, 42

369

The lowest gas yield of 4.0 wt.% was obtained at 300 ˚C, 5 min, and 15 wt.% (solid loading), while the highest

370

(22.7 wt.%) was found at 330 ˚C, 26 min, and 21 wt.%. These yields are in agreement with previous studies of

371

lignocellulosics without alkali reagents.43, 44 The quadratic model performed very well (R2 = 0.97, p = 2.00 x 10-15,



Page 14 of 31

372

F = 79.17, RSE = 1.087, Table 5). The gas formation from Miscanthus was found to be far more simple than for

373

Spirulina and was largely linear dependent on temperature, reaction time, and solid loading in decreasing order

374

of effect (positive). The linear dependency on temperature and solid loading has previously been reported for

375

catalytic conversion of sawdust12 while a similar effect was reported from HTL of barley straw.45 However, Hardi,

376

et al. 12 found that solid loading was more important than temperature and that reaction time was insignificant.

377

The effect of temperature and reaction time may simply be due to first decarboxylation of depolymerized

378

biomass at lower temperature accompanied by cracking of larger components at higher temperature, while the

379

effect of solid loading would require analysis of the gas phase.

380


381

Miscanthus Gas

Coefficient


13.5915 4.2025 2.5773 1.8136 0.0394 0.5462 0.3974 0.0196 -1.6763 0.2902 0.9674 2.00 x 10-15 79.17 1.087

p-value

< 2 x 10-16 6.45 x 10-12 6.69 x 10-9 0.8860 0.0559 0.1568 0.9325 1.46 x 10-7 0.2172

Bio-crude

Coefficient


44.5847 4.7896 -0.6575 3.0140 -1.9608 -0.2348 0.3086 -3.5700 -1.3104 -0.5840 0.9115 1.60 x 10-10 27.45 2.246

p-value

5.69 x 10-11 0.1391 2.99 x 10-7 0.0018 0.6795 0.5877 8.72 x 10-8 0.0106 0.2290

Solid residue X0 X1 X2 X3 X12 X13 X23 X11 X22 X33 R2 P F RSE

Coefficient 14.0227 -13.1222 -7.1787 0.0480 5.1549 0.9996 0.1059 5.2122 6.0079 -0.4678 0.9580 2.44 x 10-14 60.84 3.798

p-value

1.79 x 10-15 6.23 x 10-10 0.9480 1.41 x 10-5 0.3030 0.9120 9.69 x 10-7 9.44 x 10-8 0.5640

AqP

Coefficient


27.8011 4.1306 5.2589 -4.8755 -3.2334 -1.3111 -0.8119 -1.6623 -3.0219 0.7617 0.8705 1.33 x 10-8 17.93 3.843

p-value

8.81 x 10-6 2.17 x 10-7 7.40 x 10-7 0.0026 0.1851 0.4065 0.0511 0.0010 0.3561

382 383

The only significant quadratic term was a negative coefficient from reaction time leading to low gas yields at

384

short reaction times with a rapid increase until reaction times of 14 min. This effect is even more pronounced for

385

the combined negative quadratic effect of reaction time and the positive linear effects of reaction time and solid

386

loading, which means that gas yields increase less rapidly at longer reaction times (> 14 min) compared to short

387

reaction times (< 14 min) as observed from Fig. 3.

388 389

Figure 3. Response surface plots of gas yield for HTL of Miscanthus. Left) temperature and reaction time, Right)

390

reaction time and solid loading


Page 15 of 31 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


391


392

The minimum bio-crude yield obtained for Miscanthus was 28.0 wt.% at 250 ˚C, 18 min, and 15 wt.% solid

393

loading while the highest bio-crude yield was 52.3 wt.% at 330 ˚C, 10 min, and 21 wt.% (solid loading). The bio-

394

crude yields were in agreement with previous studies of Miscanthus43, 46 and other lignocellulosics both catalytic

395

and non-catalytic.8, 11, 47 However, the yields in this study were generally higher despite the lack of alkali

396

reagents, maybe due to use of both acetone and dichloromethane for recovery of bio-crude from the reactor.

397

The quadratic model provided a good fit (R2 = 0.90, p = 5.35 x 10-10, F = 24.50, RSE = 2.17, Table 5). The most

398

important linear effects for bio-crude yield were temperature and solid loading with large positive coefficients,

399

while reaction time had a smaller negative coefficient. A significant negative interaction was found for

400

temperature and reaction time. This interaction may be caused by char formation of especially phenolic species

401

at high temperature and long reaction times, as the coefficient was highly positive for SR. Temperature gave a

402

large negative quadratic coefficient, while reaction time showed a less significant negative term. The RS plot of

403

temperature and reaction time shows that maximum bio-crude yield is obtained at 330 ˚C and < 10 min (Fig. 4,

404

left). The short reaction time also keeps the gas and SR formation low. Additionally, the bio-crude yield

405

decreases slowly at temperatures of 300-330 ˚C with increasing reaction time, and a consistent high yield is

406

maintained with up to 30 min reaction time, which further decreases the SR yield. The increasing bio-crude

407

yields until 300-330 ˚C followed by decreasing yields have previously been observed for both catalytic and non-

408

catalytic HTL of lignocellulosics48, and is caused by enhanced gas formation from cracking and maybe char

409

formation at higher temperatures. The fact that solid loading only showed a positive linear effect means that the

410

bio-crude yield at these reaction conditions may only be limited by the ability to pump such high loadings for a

411

continuous process. The results made for Miscanthus are in agreement with a previous study on catalytic

412

conversion of barley straw by zhu, et al. 11 except they found a small effect of reaction time, probably, due to the

413

potassium carbonate catalyst limiting char formation.

414 415

Figure 4. Response surface plots of yields from bio-crude (left), solid residue (middle), and AqP (right) for HTL of

416

Miscanthus as a function of temperature and reaction time

417


418

The SR yields range from 7.3 wt.% at 330 ˚C, 10 min, and 9 wt.% solid loading up to 51.9 wt.% at 270 ˚C, 10

419

min, and 9 wt.% (solid loading). The quadratic model for SR was highly significant (R2 = 0.96, p = 2.44 x 10-14, F



Page 16 of 31

420

= 60.84, RSE = 3.798, Table 5) and showed that SR formation was solely dependent on temperature and

421

reaction time. The linear effects were highly significant and negative. A positive interaction was also found and

422

the quadrative effects were positive for both parameters and slightly larger for reaction time. The RS plot shows

423

the initial linear effect as SR decreases rapidly at low temperature and short reaction times due to increasing

424

depolymerization of the feedstock (Fig. 4, middle). The positive quadratic effect creates a minimum at

425

approximately 330 ˚C and 18 min. The positive interaction is clear from the RS plot as low temperature and short

426

reaction time are simply insufficient for degradation of Miscanthus, while char formation seems to be less of an

427

issue.

428


429

The lowest yield of AqP was 2.7 wt.% at 300 ˚C, 5 min, and 15 wt.% solid loading and the highest was 38.5 wt.%

430

at 300 ˚C, 18 min, and 5 wt.% (solid loading). The quadratic model was significant although it was the poorest fit

431

of the four models (R2 = 0.87, p = 1.33 x 10-8, F = 17.93, RSE = 3.843, Table 5). Temperature and reaction time

432

were highly significant for linear effects (positive), interactions (negative), and quadratic effects (negative) with

433

reaction time being more important than temperature. The RS plot shows a steep increase in AqP from low

434

temperature and short reaction time due to depolymerization until reaching a maximum at 320 ˚C and 22 min

435

after which it decreases somewhat (Fig. 4, right). Thus, high bio-crude yields seem linked to high AqP yields,

436

and at higher treatment severity, the SR formation increases mostly at the expense of bio-crude. Phenolics are

437

known to be major components of bio-crude from lignocellulosics, while the SR from Miscanthus consists of

438

chemically modified lignin and repolymerized phenolics.49 The most notable feature of the model is the negative

439

linear effect of solid loading, which is equally significant to temperature and reaction time. The effect of solid

440

loading on AqP is accompanied by a significant increase in bio-crude along with a moderate increase in gas

441

formation but without increasing SR meaning that introduction of high solid loadings is even more advantageous

442

as it seems purely directed towards bio-crude.

443


444

Table 6 shows model results for the contents of nitrogen and oxygen as well as carbon recovery and ER of the

445

bio-crude.

446

Table 6. Coefficients and figure of merit for the quadratic models of nitrogen, oxygen, carbon recovery (C rec),

447

and energy recovery (ER) from HTL of Miscanthus N X0 X1 X2 X3 X12 X13 X23 X11 X22 X33 R2

Coefficient 0.9429 -0.0425 -0.0538 -0.0287 0.1050 -0.0063 -0.0138 0.0612 0.0303 -0.0051 0.8762

p-value 0.0002 1.05 x 10-5 0.0069 1.68 x 10-8 0.6263 0.2887 6.53 x 10-6 0.0091 0.6402

O X0 X1 X2 X3 X12 X13 X23 X11 X22 X33 R2

Coefficient 25.8433 -3.8666 -2.9579 1.1269 -0.6610 -2.2566 -0.2890 -0.8575 1.0972 -0.9548 0.8253

p-value 1.41 x 10-7 8.89 x 10-6 0.0429 0.3466 0.0032 0.6784 0.1523 0.0707 0.1123

C rec X0 X1 X2 X3 X12 X13 X23 X11 X22 X33 R2

Coefficient 60.5059 9.5908 1.4331 3.2794 -2.1063 1.5910 0.5067 -3.9561 -2.6828 0.0618 0.8979


p-value 6.37 x 10-12 0.0763 0.0003 0.0480 0.1286 0.6208 0.0001 0.0043 0.9428

ER X0 X1 X2 X3 X12 X13 X23 X11 X22 X33 R2

Coefficient 72.2201 12.3425 2.3817 4.4322 -2.5738 2.3146 0.8970 -4.4774 -3.4375 0.3654 0.9037

p-value 3.38 x 10-12 0.0212 0.0001 0.0526 0.0791 0.4842 0.0003 0.0035 0.7341

Page 17 of 31 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

P F RSE


7.87 x 10-9 18.88 0.0507

P F RSE

4.07 x 10-7 12.6 2.754

p F RSE

8.44 x 10-10 23.46 4.044

p F RSE

4.28 x 10-10 25.03 3.049

448 449

The nitrogen content was 0.82 % - 1.23 % and the quadratic model had a good fit (R2 = 0.88, Table 6). The

450

effects of temperature and reaction time were significant for all coefficients with negative linear effects, positive

451

interaction, and positive quadratic effects. The RS plot of temperature and reaction time most notably shows the

452

strong effect of the positive interaction along with the positive quadratic term as a valley of minimum is obtained

453

from high temperature and short reaction across to low temperature and long reaction time (Fig. 5, left). This is

454

the exact opposite of Spirulina where maximum values were found for these parameter settings. Hence, a

455

change in reaction chemistry seems evident maybe due to differences in pH and biochemical content of the

456

feedstock. Solid loading had a negative linear effect on nitrogen content. We have previously shown that

457

recirculation of the AqP saturates the AqP and forces N-heterocyclic compounds such as pyrazines into the bio-

458

crude. However, the acidic conditions of Miscanthus AqP protonates these compounds making them hydrophilic.

459 460

Figure 5. Response surface plots of nitrogen content (left) and carbon recovery (right) for HTL of Miscanthus as

461

a function of temperature and reaction time

462

The carbon recovery was highly diverse with a low of 36.0% and a high of 75.6%. The quadratic model was

463

significant with a good fit (R2 = 0.90, Table 6), and the intercept was significantly higher than for Spirulina. The

464

linear effects were all significantly positive with temperature having by far the largest coefficient. Negative

465

quadratic effects were found for temperature and reaction time, as well as a negative interaction. The RS plot of

466

temperature and reaction time (Fig. 5, right) was very similar to that of bio-crude but maximum recovery is found

467

at slightly higher temperature and reaction time (340 ˚C, 14 min). However, deviations of ± 10 ˚C and ± 4 min

468

lead to only small changes in carbon recovery. Solid loading had only a positive linear effect as was the case for

469

bio-crude. The model for ER was almost identical to carbon recovery but showed an added positive interaction

470

between temperature and solid loading (Table 6). This means that during processing at > 300 ˚C it becomes

471

even more advantageous to use high solid loadings.

472

The oxygen content varied considerably from 15.9 % up to 38.6 %, and the quadratic model had a decent fit (R2

473

= 0.83, Table 6). Miscanthus bio-crude had the highest oxygen content, which is also reflected by the preferred

474

use of acetone for bio-crude recovery from lignocellulosics. As for Spirulina, the linear effects of temperature and



Page 18 of 31

475

reaction time were significant and negative, though reaction time also gave a positive quadratic effect. The RS

476

plot shows that while higher temperature decreases the oxygen content linearly, the decrease slows down with

477

longer reaction times and reaches minimum around 30 min (Fig. 6, left). Solid loading had a less significant

478

negative linear effect but also a strong negative interaction with temperature. We observed that pH of the AqP

479

was similarly correlated to temperature and solid loading with pH of approximately 3.8 for high temperature and

480

small solid loading and 4.0 at high temperature and high solid loading. This affects the protonation of

481

hydroxylated carboxylic acids (e.g. lactic acid pKa 3.86), which are abundant in the AqP and may force some of

482

the protonated acids into the bio-crude. Minimum oxygen is obtained at high temperature (≥ 325 ˚C) and solid

483

loading ≥ 15 wt.% (Fig. 6, middle). The RS plot of reaction time and solid loading shows that with a constant

484

temperature of 300 ˚C, an increased solid loading will result in an increasing oxygen content of up to 4 % (Fig. 6,

485

right). Again, reaction time seems to be the most crucial parameter, as longer reaction times are beneficial for

486

lowering the oxygen content but this occurs at the expense of bio-crude yields. Hence, 20 min reaction time is an

487

ideal compromise for high bio-crude yields and low oxygen contents for Miscanthus.

488 489

Figure 6. Response surface plots of oxygen content for HTL of Miscanthus. Left) temperature and reaction time,

490

Middle) temperature and solid loading, Right) reaction time and solid loading

491

3.2.6 Conclusion on process conditions for Miscanthus

492

The product distribution for HTL of Miscanthus is highly different from Spirulina. Although, maximum bio-crude

493

yields were obtained at 330 ˚C and < 10 min (46.9 wt.%, at 10 min and 15 wt.%), only small differences were

494

observed at 300 ˚C and 30 min. Solid loading linearly increases bio-crude yields solely at the expense of AqP

495

yield, which places further incentive on higher solid loading for lignocellulosics. The high bio-crude yield

496

coincides with maximum AqP yield and low gas and SR yields. The effect of temperature is mainly to increase

497

the yields of gas, bio-crude, and AqP, while decreasing the SR yield. Reaction time mostly decreases the SR

498

yield while increasing the gas yield. Optimum conditions for low nitrogen content of the bio-crude were similar to

499

the bio-crude yield (0.9% at 10 min and 15 wt.%), while high carbon recovery (67.1%, at 10 min and 15 wt.%)

500

was also found. However, improved carbon recovery can be obtained by increasing the process severity slightly

501

to 340 ˚C and 14 min (69.0% at 15 wt.%). Hence, optimum bio-crude yield and carbon recovery seem to be

502

obtained at process conditions slightly less severe than typically applied for HTL of lignocellulosics although


Page 19 of 31 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


503

more severe than for Spirulina. Similar for Miscanthus, the benefits of processing higher solid loading is highly

504

advantageous for increasing bio-crude yield, improving carbon recovery, and reducing the AqP yield.

505

3.3 Primary sludge

506

3.3.1 Gas yield

507

The wet nature and high abundance of primary sludge makes it an ideal feedstock for HTL.

508

The gas yields for primary sludge ranged from 3.8 wt.% to 19.7 wt.% with the lowest obtained at 270 ˚C, 10 min,

509

and 21 wt.% solid loading and the highest at 330 ˚C, 26 min, and 21 wt.% (solid loading). The yields are in

510

agreement with previously published results from HTL of sewage sludge.43, 50 The fit of the quadratic model was

511

significant (R2 = 0.92, p = 8.65 x 10-11, F = 29.08, RSE = 1.486, Table 7). All linear effects were significant and

512

positive with coefficients in decreasing order; temperature, reaction time, and solid loading. No interactions

513

between variables were observed.

514


515

primary sludge Gas

Coefficients


14.3449 3.4589 2.4278 1.0659 -0.1673 0.6347 0.5639 -0.7785 -1.3922 -0.4522 0.916 8.65 x 10-11 29.08 1.486

p-value

9.39 x 10-12 9.75 x 10-9 0.0010 0.6565 0.1004 0.1420 0.0202 0.0002 0.1614

Biocrude X0 X1 X2 X3 X12 X13 X23 X11 X22 X33 R2 p F RSE

Coefficients 41.5316 2.7600 -0.1815 0.4342 -1.1801 -1.1636 0.1702 -2.4789 -1.9365 -0.7597 0.8630 2.54 x 10-8 16.80 1.1695

p-value

1.04 x 10-8 0.5810 0.1932 0.0103 0.0113 0.6916 3.52 x 10-7 1.43 x 10-5 0.0438

Solid residue X0 X1 X2 X3 X12 X13 X23 X11 X22 X33 R2 p F RSE

Coefficients 18.4714 -10.2288 -5.9137 1.3257 4.8043 5.7593 0.3785 5.6002 0.7499 0.7742 0.9374 2.73 x 10-12 39.95 3.902

p-value

7.69 x 10-13 3.77 x 10-8 0.0885 6.47 x 10-6 0.4496 0.4352 4.98 x 10-6 3.02 x 10-7 0.6493

AqP

Coefficients


25.6522 4.0099 3.6674 -2.8258 -4.2528 -0.2210 -1.5083 -1.5468 -2.4306 0.8334 0.8832 4.02 x 10-9 20.17 2.951

p-value

2.43 x 10-7 1.02 x 10-6 4.10 x 10-5 6.08 x 10-6 0.7670 0.0520 0.0201 0.0007 0.1923

516 517

The quadratic terms of temperature and reaction time were both negative, with reaction time having the largest

518

coefficient meaning that initial increases of the reaction parameters lead to rapid increases in gas yield, which

519

level off at more severe conditions as observed from the RS plot (Fig. 7, left). Primary sludge has already

520

undergone some degree of degradation prior to HTL, and it is likely that components amenable to

521

decarboxylation are more readily available meaning that decarboxylation occurs rapidly. At higher temperature

522

and longer reaction time cracking becomes a more important mode of gas formation than seen for Spirulina and

523

Miscanthus. A positive linear effect of solid loading leads to increasing gas formation, which has previously been

524

reported.51 Interestingly, at conditions more severe than 300 ˚C, 18 min, and 15 wt.% the increase in gas yield is

525

small.



Page 20 of 31

526 527

Figure 7. Response surface plots of yields from gas (left), solid residue (middle), and AqP (right) for HTL of

528

sewage sludge as a function of temperature and reaction time.

529


530

The yield of SR ranged from 14.0 wt.% at 300 ˚C, 18 min, and 5 wt.% solid loading to as much as 55.9 wt.% at

531

270 ˚C, 10 min, and 9 wt.% (solid loading). The fit of the quadratic model was very good (R2 = 0.94, p = 2.73 x

532

10-12, F = 39.95, RSE = 3.902, Table 7). The linear effects were highly significant and negative for temperature

533

and reaction time. Lower SR yield for primary sludge with increasing temperature has previously been

534

observed.50 A significant (positive) coefficient for solid loading was also found, although much smaller than the

535

other parameters. Additionally, a significant positive interaction between temperature and reaction time was

536

found along with positive quadratic effects for both parameters with temperature being by far the most

537

significant. The RS plot of temperature and reaction time shows the strong linear effect of temperature at < 300

538

˚C while a plateau of minima is reached at > 300 ˚C due to the quadratic effect (Fig. 7, middle). The interaction of

539

temperature and reaction time means that the plateau can be reached at lower temperatures by increasing the

540

reaction time or at higher temperature by decreasing the reaction time. The plateau also coincides with the

541

maximum bio-crude yield for temperature and reaction time (Fig. 8, left). The mechanism for SR formation is

542

likely that at low temperature and short reaction time the biomass is not fully depolymerized, while higher

543

temperature and longer reaction time leads to char formation. However, at very severe conditions gas formation

544

increases considerably instead of char formation. Previous studies show that SR formation from protein

545

decreases with longer reaction times, while it may in fact increase for carbohydrates.7, 52

546


547

The lowest yield of AqP was 6.4 wt.% at 270 ˚C, 10 min, and 9 wt.% solid loading while the highest yield was

548

36.9 wt.% at 300 ˚C, 18 min, and 5 wt.% (solid loading). The model was statistically significant (R2 = 0.88, p =

549

4.02 x 10-9, F = 20.17, RSE = 2.951, Table 7). The coefficients for temperature and reaction time were very

550

similar with strong positive linear effects, a strong negative interaction, and smaller negative quadratic effects. A

551

highly significant negative linear effect of solid loading was found along with a less significant negative

552

interaction with reaction time. The RS plot of temperature and reaction time has a strong resemblance to the

553

same plots for bio-crude (Fig. 8, left) and SR (Fig. 7, middle) with a plateau of maximum running from low


Page 21 of 31 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


554

temperature and long reaction time to high temperature and short reaction time although it is slightly rotated (Fig.

555

7, right). Hence, the degradation of sewage sludge seems to end in products for bio-crude and AqP without

556

much equilibrium between the different product fractions, as observed from kinetic studies of microalgae.36

557

Increased solid loading lead to continuously decreasing AqP yields, which is faster at longer reaction times due

558

to the negative interaction with reaction time (plots not shown). The decreasing AqP yields are mainly

559

counteracted by increased gas and SR yields while bio-crude yields reaches a maximum at solid loading of 15

560

wt.%.

561

Hence, in contrast to Miscanthus, processing sludge at higher solid loadings is only beneficial from the viewpoint

562

of processing more biomass in a shorter period of time and for less energy input.

563


564

The bio-crude yields of primary sludge showed the smallest spread of all the experiments. The lowest bio-crude

565

yield was 29.2 wt.% at 270 ˚C, 10 min, and 9 wt.% solid loading while the highest yield was 43.4 wt.% at 330 ˚C,

566

10 min, and 9 wt.% (solid loading). The yields were generally higher than previously published results, which

567

may be due to differences in feedstock composition, process parameters, and work-up procedure.50, 51 Biller, et

568

al. 43 found a bio-crude yield of 42.6 wt.% from HTL of primary sludge from the same water treatment plant. The

569

quadratic model was significant (R2 = 0.86, p = 2.54 x 10-8, F = 16.8, RSE = 1.1695, Table 7). Only temperature

570

was found to have a significant linear effect, which was positive, but negative interactions were found for

571

temperature with both reaction time and solid loading, meaning that simultaneously high or low level of the

572

parameters will decrease bio-crude yield and opposite levels will increase the yield. The quadratic terms of all

573

three parameters were all significant and negative with temperature and reaction time having the largest

574

coefficients. The RS plot of temperature and reaction time shows a maximum bio-crude yield at 320 ˚C and 16

575

min (Fig. 8, left), and a change of ± 30 ˚C or ± 8 min only leads to a decrease of 2 wt.% yield if the other

576

parameters are fixed. The RS plot of temperature and solid loading shows a maximum at 320 ˚C and 12 wt.%

577

(Fig. 8, middle). The effects of changing solid loading is highly dependent on the temperature. More specifically,

578

at 300 ˚C the solid loading can be increased to 25 wt.% with a bio-crude loss of only 1.9 wt.% but larger losses

579

are inflicted at 320 ˚C (loss of 3.5 wt.%), which further escalates at higher temperature. The RS plot of reaction

580

time and solid loading shows a maximum at 18 min and 15 wt.% with minor decreases in yield with changes of ±

581

8 min and ± 8 wt.% (Fig. 8, right).

582

Hence, primary sludge resembles Spirulina although maximum bio-crude yields for primary sludge are obtained

583

at higher temperature, shorter reaction time, and smaller solid loading. The GC-amenable composition of bio-

584

crude from sludge is known to consist of primarily fatty acids and fatty alcohols from hydrolysis of glycerides and

585

waxes.53 Glycerides are readily hydrolyzed at > 280 ˚C54 while bio-crude components from protein are formed at

586

> 250 ˚C55, which could explain the need for higher temperatures. Fatty alcohols and fatty acids are known to be

587

thermally stable at high temperatures but extended reaction times may lead to decarboxylation of fatty acids or



Page 22 of 31

588

cracking of the long carbon chains, which could explain the decreasing yields at longer reaction times compared

589

to Spirulina.

590 591

Figure 8. Response surface plots of bio-crude yield for HTL of primary sludge. A) temperature and reaction time,

592

B) temperature and solid loading, C) reaction time and solid loading

593


594

Primary sewage sludge has previously shown potential for high bio-crude yields along with high carbon content

595

and low oxygen and nitrogen contents.43 The models for sewage sludge were all statistically significant but the

596

figures of merits for oxygen content and ER were poor.

597 598 599

Table 8. Coefficients and figures of merit for the quadratic models of nitrogen, oxygen, carbon recovery (C rec),

600

and energy recovery (ER) from HTL of primary sludge N X0 X1 X2 X3 X12 X13 X23 X11 X22 X33 R2 P F RSE

Coefficient 2.4590 0.0552 -0.0396 0.3431 0.2413 -0.0063 0.0163 0.0464 0.0730 -0.1551 0.8883 2.41 x 10-9 21.2 0.1663

p-value 0.1001 0.2254 1.11 x 10-10 5.57 x 10-6 0.8818 0.6994 0.1974 0.0481 0.0002

O X0 X1 X2 X3 X12 X13 X23 X11 X22 X33 R2 p F RSE

Coefficient 14.0882 -1.1091 -2.7065 0.3139 0.9994 0.2681 0.3528 -0.3246 1.5904 -0.7422 0.7046 0.0001 6.359 2.493

p-value 0.0246 4.04 x 10-5 0.4014 0.2552 0.9379 0.4070 0.6297 0.0081 0.2324

C rec X0 X1 X2 X3 X12 X13 X23 X11 X22 X33 R2 P F RSE

Coefficient 64.9151 5.2439 1.7013 0.2696 -2.5559 -1.9101 0.2466 -3.6465 -4.2353 -0.4524 0.8656 2.04 x 10-8 17.17 3.207

p-value 9.63 x 10-9 0.0106 0.6643 0.0040 0.0255 0.7610 1.52 x 10-5 1.76 x 10-6 0.5093

ER X0 X1 X2 X3 X12 X13 X23 X11 X22 X33 R2 p F RSE

Coefficient 46.5910 0.5098 1.7633 -0.5340 -0.9180 -0.2244 -0.3790 0.1739 -1.1033 0.6055 0.7089 0.0001 6.494 1.693

p-value 0.1285 1.35 x 10-5 0.1122 0.0402 0.6008 0.3793 0.6301 0.0049 0.1023

601 602

The nitrogen content of bio-crude was 1.2% - 3.1% and the fit of the model was good (R2 = 0.89). The effect of

603

temperature and reaction time was peculiar, as a significant positive interaction was found along with a small

604

negative quadratic effect for reaction time. This leads to a near opposite effect to the AqP yields. The RS plot

605

shows a saddle where low nitrogen yields is obtained from high temperature and short reaction time to low

606

temperature and long reaction times (Fig. 9 left). The same was observed for Miscanthus and the opposite for


Page 23 of 31 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


607

Spirulina indicating that a certain amount of nitrogen in the feedstock determines the displacement of nitrogen to

608

the bio-crude. Solid loading had the greatest effect on the nitrogen content with a positive linear effect and a

609

negative quadratic effect, so the nitrogen content increases significantly until approximately 20 wt.% solid

610

loading (Fig. 9 right). The RS plot of reaction time and solid loading also shows that minimum nitrogen is

611

obtained with approximately 18 min. Hence, low nitrogen content and high bio-crude yield are obtained at almost

612

similar temperature and reaction time. Solid loading has a small effect on bio-crude yields but can increase the

613

nitrogen content by up to 1% and a compromise is necessary.

614 615

Figure 9. Left: Nitrogen as a function of temperature and reaction time, Middle) Nitrogen as a function of reaction

616

time and solid loading, Right) Oxygen as a function of temperature and reaction time

617

The oxygen content was 10.2% - 27.4%. The model was found to be significant but the fit was poor (R2 = 0.66).

618

The linear effects were significant and negative for temperature and reaction time, and reaction time also had a

619

positive quadratic effect. Therefore the RS plot of temperature and reaction time shows a slow and steady linear

620

decrease of oxygen content with increasing temperature, while increasing reaction time initially leads to rapidly

621

decreasing oxygen contents reaching a minimum at 26 min (Fig. 9, right).

622

The carbon recovery of sludge was generally the highest on average of the three feedstocks with a low of 42.7%

623

and a high of 70.2%, which is arguably due to the dominant presence of fatty alcohols and fatty acids.53 The fit of

624

the model was good (R2 = 0.87, Table 8). Temperature and reaction time were the most significant parameters

625

with positive linear effects and negative quadratic effects with temperature having the largest coefficients.

626

Additionally, a negative interaction between the two was found. The RS plots of temperature with reaction time

627

and solid loading were almost identical to those from bio-crude but maximum carbon recovery is obtained at

628

slightly higher process parameters (Fig 10, left and right).



Page 24 of 31

629 630

Figure 10. Response surface plots of carbon recovery for HTL of Sludge. Left) temperature and reaction time,

631

Right) temperature and solid loading

632

3.3.6 Conclusion on process conditions for sewage sludge

633

The maximum bio-crude yield from sewage sludge (42.3 wt.%) could be obtained at approximately 320 ˚C, 18

634

min, 15 wt.% solid loading but only a small decrease is found with changes of ± 30 ˚C, ± 8 min, and ± 8 wt.%.

635

Similar to Miscanthus, the high bio-crude yields coincide with high AqP yield and low SR yield. Increasing the

636

solid loading had a similar decreasing effect on the AqP yield as the other feedstocks but the products were

637

predominantly displaced to the gas and SR fractions. Hence, high solid loading does not have the same

638

advantageous effect as for Miscanthus and Spirulina. Instead, the effect of solid loading is highly dependent on

639

the chosen temperature as a negative interaction is present and temperatures < 320 ˚C are preferred at high

640

solid loading. A particular disadvantage for sludge is the fact that the nitrogen content of bio-crude increases

641

with solid loading. However, the optimal values for temperature and reaction time do coincide with low nitrogen

642

content. The carbon recovery at maximum bio-crude yield was 69.7% and only small increases in carbon

643

recovery can be made by changing process conditions.

644

3.4 General discussion of results across biomasses

645

Gas formation was predominantly governed by reaction temperature for all three biomasses and only reached a

646

maximum for sludge. Reaction time was also important for gas formation from HTL of all biomasses but it also

647

reached a maximum for all biomasses, indicating that HTL of the three types of biomasses reaches a point

648

where degradation into smaller components stops and repolymerization may be the only further reaction. Solid

649

loading was the least important factor for gas formation. Positive interactions were only observed for Spirulina,

650

which may occur from increased pH with enhanced decarboxylation. The magnitude of the coefficients follows

651

the order of Miscanthus > sludge > Spirulina. Thus, gas formation seems highly linked to increasing

652

carbohydrate and lignin content as especially carbohydrates are degraded to monosaccharides that degrade to

653

smaller volatile components.

654

Temperature is highly important for bio-crude yield as well, and for all three biomasses a maximum is reached.

655

The linear term again seems to depend on the content of carbohydrate and lignin, but the maximum is also

656

reached the fastest for Miscanthus, which may be due to a faster onset of repolymerization from these


Page 25 of 31 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


657

degradation products. The opposite trend is observed for reaction time, as the maximum occurs in the order

658

Spirulina > sludge > Miscanthus.

659

The most notable observation for bio-crude yield is that increased solid loading improves bio-crude yields for all

660

biomasses. Bio-crudes of Spirulina and Miscanthus have previously been shown to contain several small

661

alcohols and acids, while bio-crude from sludge contains long chain fatty acids and alcohols. As solid loading

662

increases the small alcohols and acids are dispersed to the bio-crude from the AqP as seen in studies with

663

recirculation of the AqP 31-32 while the long chain alcohols and fatty acids form emulsions in water and may end

664

up adsorbing to the SR.

665

Increasing solid loading also increases SR, although it is the least important factor for SR. Especially for sludge it

666

is strictly a linear dependency, supporting the hypothesis that fatty alcohols and fatty acids do end up in the SR

667

from bio-crude. Instead temperature and reaction time determine the SR for especially Miscanthus and sludge

668

owing to their lignin contents. However, they also both reach a minimum where the degradation products may

669

start to repolymerize. The same minimum is reached for Miscanthus with extended reaction time but not for

670

sludge. This could be caused by degradation products from carbohydrates in Miscanthus starting to

671

repolymerize whereas in many cases they can react with nitrogen species in sludge as seen when mixing

672

biomasses.

673

The AqP yield is highly dependent on solid loading (negative coefficient) for all biomasses meaning that the

674

biochemical content is not linked to the effect of solid loading. However, protein content dictates the overall AqP

675

yield mostly from a large diversity of small organic acids. The effect of reaction temperature and time are very

676

similar for Miscanthus and sludge with positive linear coefficients and negative quadratic coefficients and

677

interactions. Hence, carbohydrates and lignin increasingly degrade into AqP soluble components but with

678

combined high temperature and long reaction time the large number of small organic acids decrease the pH and

679

lignin derived monomers start to polymerize as observed from the SR. The protein content of Spirulina

680

seemingly means that protein-derived bio-crude components start to degrade into AqP soluble components at

681

elevated temperatures and long reaction times.

682

The nitrogen content of the bio-crude is predominantly determined by the protein content and solid loading.

683

Increasing the solid loading increases the nitrogen content significantly for both Spirulina and sludge as the AqP

684

is being increasingly saturated with N-containing compounds as seen from recirculation of AqP. 31-32 However,

685

the interaction of temperature and reaction time is negative for Spirulina and positive for sludge, which may be

686

related to a greater extent of Maillard type reactions during HTL of sludge where more carbohydrates are

687

present. The oxygen content of biocrude is in all cases almost linearly dependent on temperature and reaction

688

time and it therefore seems irrespective of biochemical content. However, the coefficient for temperature is much

689

lower for sludge due to the high content of waxes and fatty acids, which are more difficult to deoxygenate. The

690

increasing difficulty of product separation for Miscanthus when high solid loading is used also means that

691

pockets of AqP may remain in the bio-crude, increasing its oxygen content.



Page 26 of 31

692

4. Conclusion

693

This study investigated the effects of the three most important process variables for HTL on three widely applied

694

feedstocks; Spirulina, Miscanthus, and sewage sludge. A systematic approach was used with a circumscribed

695

central composite design, fitting to a quadratic model, and response surface methodology to account for effects

696

on product distribution of gas, bio-crude, SR, and AqP as well as contents of heteroatoms and carbon recovery

697

of the bio-crude. Results from the different feedstocks were directly comparable as a standardized procedure for

698

product separation was applied.

699

Maximum bio-crude yields of approximately 40 wt.% were found for Spirulina at 300-320 ˚C, 16-18 min, and 20-

700

22 wt.%. The effect of temperature and reaction time is mainly to enhance the yields of bio-crude and gas at the

701

expense of AqP and SR. Particularly, the AqP reaches a minimum at these conditions. High nitrogen content (>

702

7%) and carbon recovery (55.9%) follows the high bio-crude yield mainly affected by temperature and reaction

703

time, which at the same time decreased the oxygen content (15.7% - 22.9%).

704

The model of Miscanthus estimated the highest bio-crude yield of all feedstocks with 46.9 wt.% at 330 ˚C, 10

705

min, and 15 wt.% solid loading. High bio-crude yield for Miscanthus is inevitably linked to high AqP yield and low

706

SR yield, which is mainly the effect of temperature. Increasing the reaction time also lowers the SR yield but

707

products that are more volatile are formed instead of bio-crude. Minimum nitrogen content (0.9%) and high

708

carbon recovery (67.1%) followed the optimal conditions for bio-crude yield.

709

High bio-crude yields were most stable for sewage sludge where changes of ± 30 ˚C, ± 8 min, and ± 8 wt.%

710

inflicted only minor changes. The maximum bio-crude yield was 42.3 wt.% at 320 ˚C, 18 min, and 15 wt.% solid

711

loading. Similar to Miscanthus, high bio-crude yield for sewage sludge is inevitably linked to high AqP yield and

712

low SR yield. The effects of solid loading on HTL of sewage sludge are subtle but important. At low solid loading

713

(< 15 wt.%) high temperature is preferred (≥ 320 ˚C) for high bio-crude yields while at high solid loading (> 15

714

wt.%) lower temperature is preferred (< 320 ˚C). Additionally the nitrogen content of bio-crude increases

715

continuously with higher solid loading while it has limited effect on carbon recovery. The optimum temperature

716

and reaction time were also linked to maximum carbon recovery and minimum nitrogen in the bio-crude (2.5%

717

and 69.7%, respectively, at 15 wt.%).

718

Solid loading had a general effect of decreasing the AqP yield for all feedstocks. The lower AqP yields were

719

displaced to bio-crude and gas for Spirulina and Miscanthus, which also resulted in a higher oxygen content of

720

the bio-crude. For sewage sludge it ended up as SR and gas. It was also common to Spirulina and Miscanthus

721

that the carbon recovery improved with slightly more severe conditions than for maximum bio-crude yield (59.1%

722

and 69.0%, respectively).

723

Acknowledgements

724

The authors would like to acknowledge Professor Bo B. Iversen for providing facilities to conduct experiments

725

and elemental analysis. We would also like to thank Assist. Prof. Patrick Biller and Dr. Konstantinos Anastasakis

726

for helpful discussions. This research was funded by the European Union’s Horizon 2020 research and


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727

innovation programme under grant agreement No. 764734 (HyFlexFuel – Hydrothermal liquefaction: Enhanced

728

performance and feedstock flexibility for efficient biofuel production).

729

Conflicts of interest

730

The authors declare no conflict of interest

731

Supporting Information

732

Prediction of bio-crude yield, experimental yields of gas, bio-crude, SR, and AqP, and experimental results of

733

CHNS-O, carbon recovery, HHV, and energy recovery of bio-crude.

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How do hydrothermal liquefaction conditions and feedstock type

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