Pretreatment and Posttreatment Approaches for Reducing ...

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Masters Theses Graduate School

12-2017

Pretreatment and Posttreatment Approaches for Reducing Pretreatment and Posttreatment Approaches for Reducing

Biomass Inorganic Impurities during Gasification Biomass Inorganic Impurities during Gasification

Qiaoming Liu University of Tennessee

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Recommended Citation Recommended Citation Liu, Qiaoming, "Pretreatment and Posttreatment Approaches for Reducing Biomass Inorganic Impurities during Gasification. " Master's Thesis, University of Tennessee, 2017. https://trace.tennessee.edu/utk_gradthes/5020

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To the Graduate Council:

I am submitting herewith a thesis written by Qiaoming Liu entitled "Pretreatment and

Posttreatment Approaches for Reducing Biomass Inorganic Impurities during Gasification." I

have examined the final electronic copy of this thesis for form and content and recommend that

it be accepted in partial fulfillment of the requirements for the degree of Master of Science, with

a major in Biosystems Engineering.

Nourredine H. Abdoulmoumine, Stephen C. Chmely, Major Professor

We have read this thesis and recommend its acceptance:

Xiaofei Ye

Accepted for the Council:

Dixie L. Thompson

Vice Provost and Dean of the Graduate School

(Original signatures are on file with official student records.)

Pretreatment and Posttreatment Approaches for Reducing Biomass

Inorganic Impurities during Gasification

A Thesis Presented for the

Master of Science

Degree

The University of Tennessee, Knoxville

Qiaoming Liu

December 2017

ii

Copyright © 2017 by Qiaoming Liu.

All rights reserved.

iii

ACKNOWLEDGEMENTS

I would like to thank my professors, Dr. Nour Abdoulmoumine and Dr. Chmely, for supporting

me, encouraging me, and offering me this great opportunity to participate in the research. I

would like to express my gratitude to my colleagues, Femi Oyedeji and Ross Houston, for being

my support and motivation. I wish to acknowledge Dr. Philip Ye, Dr. Nicole Labbe, and Dr.

Sushil Adhikari, without whose generous help, resources, and insights, the research would not

have been accomplished. I am grateful to the University of Tennessee, Sungrant Southeastern

Regional Center and the Department of Transportation with support for this research.

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ABSTRACT

During gasification, biomass can be thermally decomposed into a mixture of combustible

gases known collectively as syngas to produce heat, power, and liquid fuels in downstream

processes. However, inorganic elements, present in biomass and released into syngas as

impurities, are considered one of the main deterrent to the commercial deployment of biomass

gasification technologies and have recently contributed to the failure of a thermochemical

biorefinery. In conventional gasification installations, a syngas cleanup process area, which

comprises a combination of processes, is used to reduce the concentrations of these inorganic

impurities below tolerable limits.

In recent years, several treatment approaches have been explored to reduce the

concentrations of inorganic impurities in syngas and, ultimately, decrease the cost associated

with syngas cleanup. This project is aligned with these recent advancements and seeks to

develop gasification treatments to mitigate the impact of inorganic species. Specifically, the

project objectives are to i) develop a hot water extraction (HWE) based pretreatment approach to

reduce select inorganic elements (N, S, Na, K, Ca, and Mg) relevant to gasification; ii) develop

and evaluate new sorbents for posttreatment and; iii) evaluate the impact of HWE pretreatment

and sorbent posttreatment on the overall economics of the gasification plant.

In the first objective, HWE was carried out at five temperatures (60, 80, 100, 120 and

140 °C) and three soaking times (15, 30, 45 min) and the effect of these two parameters on the

responses (N, S, Na, K, Ca, and Mg reduction) were investigated by a two factor analysis of

variance of an unbalanced, complete factorial design at the 0.05 significance level. It was

observed that the acidity of the extraction liquor increased with both temperature and time with

lower pH resulting in higher total inorganic reduction.

For posttreatment of gas phase inorganics in syngas, layered double hydroxide based

mixed metal sorbent was synthesized, characterized and evaluated against commercial sorbents

on a model syngas mixture. The sorbents were thermally stable in the hot gas cleanup

temperature range (300 - 700 °C). Further, fixed bed experimental evaluation of hydrogen

chloride (HCl) gas removal was conducted on the sorbents.

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TABLE OF CONTENTS

INTRODUCTION .......................................................................................................................... 1

CHAPTER I Biomass Treatment Strategies for Thermochemical Conversion .............................. 2

1. ABSTRACT ............................................................................................................................ 3

2. INTRODUCTION .................................................................................................................. 4

3. THE ORIGIN, NATURE, AND VARIABILITY OF INORGANICS IN

LIGNOCELLULOSIC BIOMASS ............................................................................................. 5

4. THE EFFECT OF INORGANICS ON BIOMASS THERMOCHEMICAL CONVERSION

PROCESSES .............................................................................................................................. 8

4.1 Pyrolysis ............................................................................................................................ 8

4.2 Gasification ....................................................................................................................... 9

4.3 Combustion ..................................................................................................................... 11

5. PRE-TREATMENTS FOR THERMOCHEMICAL CONVERSION OF BIOMASS ........ 12

5.1 Mechanical pre-treatment ............................................................................................... 13

5.2 Thermal pre-treatment .................................................................................................... 14

5.3 Chemical pre-treatment ................................................................................................... 17

5.3.1 Water leaching ......................................................................................................... 17

5.3.2 Acid washing ............................................................................................................ 22

5.3.3 Base washing ........................................................................................................... 24

6. POST-TREATMENTS FOR THE THERMOCHEMICAL CONVERSION OF BIOMASS

24

6.1 Gas product posttreatments ............................................................................................. 25

6.2 Liquid product posttreatments ........................................................................................ 26

6.3 Solid product posttreatments ........................................................................................... 26

7. CONCLUSIONS .................................................................................................................. 27

8. ACKNOWLEDGMENTS .................................................................................................... 28

9. REFERENCES ..................................................................................................................... 29

CHAPTER II Hot Water Extraction as a Pretreatment for Reducing Syngas Inorganics Impurities

– A Parametric Investigation on Switchgrass and Loblolly Pine Bark ......................................... 37

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1. ABSTRACT ...................................................................................................................... 38

2. INTRODUCTION ............................................................................................................ 39

3. MATERIALS AND METHODS ...................................................................................... 41

3.1 Biomass preparation and characterization ...................................................................... 41

3.2 Hot water extraction ........................................................................................................ 41

3.3 Characterization of hot water extraction products .......................................................... 42

3.4 Statistical analyses .......................................................................................................... 43

4. RESULTS AND DISCUSSION ....................................................................................... 43

4.1 Proximate and ultimate analysis of raw switchgrass and loblolly pine bark samples .... 43

4.2 Effect of hot water extraction ......................................................................................... 45

4.2.1 Effect on nitrogen reduction and its impact on nitrogen contaminants ................... 47

4.2.2 Effect on sulfur reduction and its impact on sulfur contaminants ........................... 48

4.2.3 Effect on alkali metal reduction and its impact on syngas metal contaminants ...... 49

4.2.4 Effect on alkaline earth metals reduction and their impact on syngas metal

contaminants ..................................................................................................................... 50

5. CONCLUSIONS .............................................................................................................. 52

6. ACKNOWLEDGMENTS ................................................................................................ 53

7. REFERENCES ................................................................................................................. 54

8. APPENDIX ....................................................................................................................... 58

8.1 Hot water extraction experimental conditions and severities ......................................... 58

8.2 Summary of two-way analysis of variance results ......................................................... 59

8.3 Illustration of extraction severity .................................................................................... 60

CHAPTER III Synthesis and Evaluation of Sorbents for Reducing the Concentrations of

Hydrogen Chloride in Syngas ....................................................................................................... 61

1. ABSTRACT ...................................................................................................................... 62

2. INTRODUCTION ............................................................................................................ 63


3.1 Sorbent synthesis and preparation .................................................................................. 64

3.2 Sorbent characterization .................................................................................................. 65

3.3 Sorption study, sampling and analysis procedure ........................................................... 65

3.4 Model of HCl Sorption ................................................................................................... 67

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4.1 Characterization of sorbents ........................................................................................... 70

4.1.1 Elemental analysis of synthesized sorbent by ICP-OES .......................................... 70

4.1.2 Thermogravimetric analysis (TGA) ......................................................................... 70

4.1.3 BET analysis ............................................................................................................ 71

4.2 HCl sorption study .......................................................................................................... 72

4.3 Kinetics model fitting of HCl removal reaction ............................................................. 75

5. CONCLUSIONS .............................................................................................................. 75

6. ACKNOWLEDGMENTS ................................................................................................ 76

7. REFERENCES ................................................................................................................. 77

8. APPENDIX ....................................................................................................................... 80

8.1 Reaction temperature ...................................................................................................... 80

8.2 Actual experimental setup ............................................................................................... 80

8.3 MATLAB code for kinetics model fitting of HCl removal reaction at 600 °C .............. 81

CHAPTER IV Techno-Economic Analysis of a Conceptual Biorefinery – Hot Water Extraction

Integrated to a Hybrid Biochemical and Thermochemical Conversion Process for High Ash

Lignocellulosic Biomass to Hydrocarbon Fuels and Succinic Acid ............................................. 87

1. ABSTRACT ...................................................................................................................... 88

2. INTRODUCTION ............................................................................................................ 89


3.1 Feed handling, hot water extraction, and succinic acid production ................................ 90

3.2 Gasification ..................................................................................................................... 93

3.3 Syngas cleanup and compression .................................................................................... 93

3.4 Methanol synthesis .......................................................................................................... 93

3.5 Methanol conditioning .................................................................................................... 94

3.6 High-octane gasoline synthesis ....................................................................................... 94

4. ECONOMIC ANALYSIS ................................................................................................ 95

4.1 Capital cost estimation .................................................................................................... 95

4.2 Production cost estimation .............................................................................................. 96

4.3 Economic analysis .......................................................................................................... 96


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5.1 Process performance of HWE and succinic acid production .......................................... 97

5.2 Total capital investment .................................................................................................. 97

5.3 Operating costs ................................................................................................................ 99

5.4 Minimum fuel selling price ........................................................................................... 100

6. REFERENCES ............................................................................................................... 102

CONCLUSIONS AND FUTURE PERSPECTIVES ................................................................. 103

1. CONCLUSIONS ............................................................................................................ 104

2. RECOMMENDATIONS FOR FUTURE WORK ......................................................... 106

VITA ........................................................................................................................................... 107

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LIST OF TABLES

Table 1 Origin of inorganic matter in lignocellulosic biomassa ..................................................... 6

Table 2 Common nature of inorganic in lignocellulosic biomass .................................................. 6

Table 3 Typical syngas applications and associated cleaning requirements11 .............................. 10

Table 4 Select indices indicative of slagging, fouling, agglomeration, and corrosiona ................ 12

Table 5 Effect of mechanical sieving on ash content for select lignocellulosic feedstocks ......... 14

Table 6 Summary of thermal pretreatment for inorganic removal from biomass ........................ 18

Table 7 Summary of chemical pretreatment for inorganic removal from biomass ...................... 19

Table 8 Proximate and ultimate analyses of raw switchgrass and loblolly pine bark .................. 44

Table 9 Summary of hot water extraction experimental conditions and severities for switchgrass

............................................................................................................................................... 58

Table 10 Summary of hot water extraction experimental conditions and severities for pine bark

............................................................................................................................................... 58

Table 11 Summary of two-way analysis of variance results for switchgrass and pine bark ........ 59

Table 12 Weight loss (%) of the sorbents during TGA ................................................................ 71

Table 13 Summary of BET analysis results of sorbents calcined at 700 °C ................................ 71

Table 14 Comparison of BET analysis results of MgAlO from literature .................................... 72

Table 15 Summary of 1 ppm HCl breakthrough time of sorbents ................................................ 73

Table 16 Summary surface elemental composition of cLDH and cLDH samples after sorption

tests shown in Figure 15 ....................................................................................................... 74

Table 17 Summary of kinetic model results ................................................................................. 76

Table 18 Summary of Nth Plant Assumptions1 ............................................................................. 91

Table 19 Ultimate analysis of woody biomass and switchgrass after HWE ................................ 91

Table 20 Plant workforce and salary per position ........................................................................ 96

Table 21 Feed and product flow rates for high-octane hydrocarbons and succinic acid production

process ................................................................................................................................... 97

Table 22 Capital cost estimates per process area for both scenarios (2017 U.S. dollars) ............ 98

Table 23 Indirect cost factors for both scenarios .......................................................................... 99

Table 24 Summary of the project costs ......................................................................................... 99

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LIST OF FIGURES

Figure 1 Pathways to aerosols: ejection of biomass inorganics during primary aerosol formation30

................................................................................................................................................. 9

Figure 2 Schematic representation of the hot water extraction experimental setup ..................... 42

Figure 3 Effect of temperature and time of hot water extraction on pH (a), ash reduction (b), and

mass loss (c) for switchgrass, and effect of temperature and time of hot water extraction on

pH (d), ash reduction (e), and mass loss (f) for pine bark. Red dots represent response

means for each condition and surface plot represents best fit of experimental data ............. 45

Figure 4 Effect of hot water extraction severity on pH (a and d), ash content reduction (b and e),

and mass loss (c and f) for switchgrass (above) and pine bark (below), respectively .......... 47

Figure 5 The effect of HWE severity on nitrogen (N) content reduction for switchgrass (a) and

pine bark (b ) ......................................................................................................................... 48

Figure 6 The effect of HWE severity on S content reduction for switchgrass (a) and pine bark (b)

............................................................................................................................................... 49

Figure 7 The effect of HWE severity on alkali metals reduction for switchgrass (a) and pine bark

(b) .......................................................................................................................................... 50

Figure 8 The effect of HWE severity on alkaline-earth metals reduction for switchgrass (a) and

pine bark (b) .......................................................................................................................... 51

Figure 9 Illustration of the area under the curve approach used to calculate severity of HWE ... 60

Figure 10 Schematic representation of the fixed bed experimental setup .................................... 66

Figure 11 TGA curves of calcined sorbents ................................................................................. 71

Figure 12 The concentration of in NaOH solution for sorbents at 400, 500, and 600 °C ...... 73

Figure 13 The concentration of outlet HCl gas for sorbents at 400, 500, and 600 °C with grey

line representing 1 ppm breakthrough .................................................................................. 73

Figure 14 SEM micrographs of: (a) cLDH; (b) cLDH after 14 h sorption at 400 °C; (c) cLDH

after 14 h sorption at 500 °C; (d) cLDH after 14 h sorption at 600 °C with 2000 X

magnification, and (e) cLDH; (f) cLDH after 14 h sorption at 400 °C; (g) cLDH after 14 h

sorption at 500 °C; (h) cLDH after 14 h sorption at 600 °C with 500 X magnification ....... 75

Figure 15 PXRD diffractograms of: (a) original LDH sample and references

(((Mg6Al2)(OH)18(H2O)4)0.375, NaNO3, Na2CO3, and Mg36Al61.7), (b) calcined LDH sample

xi

and references (Na3.893(CO3)2, NaNO3, Mg2O(OH)2, and Al2O3), and (c) calcined LDH

sample after 28 h of HCl sorption and references (NaCl, Na2CO3, Al2O3·3H2O, MgO, and

Na6MgCl8) ............................................................................................................................. 75

Figure 16 Kinetics model fitting of HCl removal reaction ........................................................... 76

Figure 17 The reactor temperature of 14 h HCl sorption test at 400 °C, 500 °C, and 600 °C,

respectively ........................................................................................................................... 80

Figure 18 Actual experimental setup ............................................................................................ 80

Figure 19 Biomass gasification and the production of high-octane hydrocarbons diagram ......... 91

Figure 20 Succinic acid production plant flow diagram ............................................................... 92

Figure 21 Simplified methanol to hydrocarbons flow diagram .................................................... 95

Figure 22 Cost contribution details of the base case scenario .................................................... 101

Figure 23 Cost contribution details of the HWE and SA production scenario ........................... 101

1

INTRODUCTION

This thesis presents research conducted to develop and evaluate pre and post gasification

treatments to reduce the levels of inorganics in biomass and syngas during gasification. It is

structured in chapters and comprises of five chapters. Chapter I is a reprint of the paper entitled,

“Biomass Treatment Strategies for Thermochemical Conversion,” published in the Journal of

Energy Fuels in March 2017. The paper summarizes pre-treatment and post-treatment techniques

for controlling the inorganic elements during thermochemical conversion processes (pyrolysis,

gasification, and combustion). The paper comprehensively reviews recent work to elucidate the

fate of inorganics during these processes and summarizes pre-treatment and post-treatment

techniques for controlling the inorganic impurities. Chapter II summarizes our investigation of

switchgrass and loblolly pine bark inorganic removal using hot water extraction as a gasification

pretreatment. The findings of this study have compiled into manuscript currently under review in

Fuel in September 2017. Chapter III summarizes our investigation on post gasification treatment

of inorganics using hydrogen chloride as model compound. The findings of this chapter will be

compiled into a manuscript for submission to Applied Catalysis A: General. In Chapter IV, we

carried out a techno-economic analysis of conceptual biorefinery that integrates hot water

extraction to remove inorganics, gasification to produce hydrocarbon fuels and biochemical

conversion to produce succinic acid (SA) from high ash switchgrass. The findings of this chapter

will be compiled into a manuscript for submission to Biofuels, Bioproducts & Biorefining.

Finally, Chapter V presents concluding remarks based on the outcomes of this project and

recommendations for future work.

2

CHAPTER I BIOMASS TREATMENT STRATEGIES FOR THERMOCHEMICAL

CONVERSION

3

Qiaoming Liua, Stephen C. Chmelyb and Nourredine Abdoulmouminea,b

aBiosystems Engineering and Soil Science Department, University of Tennessee bCenter for Renewable Carbon, University of Tennessee

Copyright © 2017 by authors and American Chemical Society

How to cite this paper: Qiaoming Liu, Stephen C. Chmely, and Nourredine Abdoulmoumine.

"Biomass treatment strategies for thermochemical conversion." Energy & Fuels 31.4 (2017):

3525-3536. DOI: 10.1021/acs.energyfuels.7b00258

1. ABSTRACT

Biomass is among the most promising renewable resources to provide a sustainable

solution to meet the world’s increasing usage of it in biochemical and thermochemical

conversion technologies. Thermochemical conversion processes (pyrolysis, gasification, and

combustion) thermally convert biomass into energy-dense intermediates that can be, in turn,

converted to power, liquid fuels, and chemicals. The performance of the processes and quality of

the intermediates are strongly affected by endogenic and technogenic inorganics. This review

highlights investigations on the effect and the fate of inorganics during pyrolysis, gasification,

and combustion of lignocellulosic biomass and critically and comprehensively presents

pretreatment and post-treatment approaches for inorganic removal. During pyrolysis process, the

inorganic contents can have significant catalytic effects and change the thermal degradation rate,

chemical pathway, and bio-oil yield. During combustion process, the inorganic contents can

bring various technological problems, environmental risks, and health concerns. During

gasification process, the inorganic contents cause diversified downstream hazards. In recent

years, several pre-treatment (mechanical, thermal, and chemical pre-treatment) and post-

treatment (gas product and liquid product post-treatment) approaches have been employed to

control and diminish the impact of inorganics during thermochemical conversion. Effective pre-

treatment technologies exist to remove inorganic contaminants to lower concentration limits.

However, the main drawbacks of these pre-treatments are that they (i) reduce the overall

4

efficiency due to the need of further drying process of wet biomass after pre-treatment and (ii)

increase chemicals, facilities, and drying costs. Post-treatment technologies are utilized to meet

the strict levels of cleanup demands for the downstream applications. A great number of

technologies exist to purify the raw synthesis gas stream that is produced by thermochemical

conversion of biomass.

2. INTRODUCTION

The excessive consumption, finite reserves, and established contribution to the

greenhouse effect of fossil fuels is motivating the development of renewable technologies as

sustainable long-term solutions. These technologies rely on biomass, solar, wind, water or

geothermal resources as their primary energy source. Among all these renewable resources,

biomass is the only resource that produces power, liquid fuels, and chemicals, thus making it an

attractive option for countries with abundant biomass resources.1 Biomass can be converted to

intermediates that can be used to produce power, liquid fuels, and chemicals through

biochemical (enzymatic hydrolysis, sugar fermentation) or thermochemical (combustion,

pyrolysis, gasification) routes. The biochemical route seeks to convert carbohydrates in

lignocellulosic biomass to energy carriers for power,2 ethanol and butanol as liquid fuels,3 and

other platform chemicals.4-6 In the thermochemical platform, biomass is converted thermally to

energy-dense intermediates that can be, in turn, converted to power, liquid fuels, and chemicals.7

Specifically, biomass can be converted to thermal energy during direct combustion; into thermal

energy and a mixture of flammable gas known as syngas during gasification; and into mostly an

energy-rich liquid known as bio-oil, as well as a small amount of syngas and solid biochar during

pyrolysis.7 The presence of biomass inorganics is detrimental to processes in both routes. For

example, the presence of inorganic compounds during biochemical conversion has been

associated with many issues that resulted in the inhibition of biological growth or productivity

through the biochemical conversion route.8-10 Issues related to inorganics during thermochemical

conversion include equipment corrosion, fouling of surfaces, catalysts deactivation, and bed

agglomeration in reactors.11-12

In recent years, recognizing the challenges associated with inorganics during biomass

conversion, several review papers attempted to organize the growing body of knowledge on the

fate of inorganics during conversion, their effects on the processes, and pre-treatment and post-

5

treatment strategies to mitigate those effects.13-14 However, past reviews focused on pre-

treatment techniques in the context of biochemical conversion technologies15 and post-treatment

reviews focused solely on gasification.11-12 This review focuses only on the main

thermochemical conversion processes namely, pyrolysis, gasification, and combustion and

comprehensively reviews recent work to elucidate the fate of inorganics during these processes

and summarizes pre-treatment and post-treatment techniques for controlling these elements.

3. THE ORIGIN, NATURE, AND VARIABILITY OF INORGANICS IN LIGNOCELLULOSIC BIOMASS

Besides the structural carbohydrates and lignin, lignocellulosic biomass also contains a

small amount of extraneous components that do not serve structural functions. These extraneous

components are present inside and outside the cell wall but are generally not bound to it.16-18

Extraneous components are grouped into extractives and inorganics, the latter being of interest in

this review. Inorganic elements in lignocellulosic biomass have different origins: authigenic,

which is formed in the biomass; detrital, which is formed outside the biomass, but fixed inside or

on the biomass; and technogenic, which is formed outside the biomass (see Table 1).19-20

The type and proportions of inorganics are highly variable and are dependent on several

environmental conditions. For example, plants grown on contaminated groundwater absorbed

more metal contaminants than their counterparts.21 The same species of Syncarpia laurifolia,

commonly known as the turpentine tree, had 0.6% and 0.09% physiological silicon when grown

in Australia and Hawaii, respectively.18 Agricultural crops were reported to have a higher

nitrogen content for a higher total nitrogen supply via fertilizer nitrogen applications.22-23

Natural or physiological inorganics originate from proteins and alkaloids for nitrogen,

sulfate salts of minerals for sulfur and soil nutrients taken up during plant growth for nitrogen,

sulfur, and all other metals, respectively.18 Anthropogenic inorganics are a result of harvest

operations (i.e., type of equipment, harvest techniques) and seasons that result in increases in

inorganic content.

Physiological inorganics are present in lignocellulosic biomass in numerous forms, as

illustrated in Table 2. These elements can be in their organic form when covalently bonded to

organic structures (e.g., proteins) or in their inorganic simplest form as a free ion (e.g., Na+ )

dissolved inside the fluid matter of the plant or as salts (e.g., NaCl).21 The alkali metals (Na and

6

Table 1 Origin of inorganic matter in lignocellulosic biomassa origin time of formation formation mechanism

Natural Process authigenic

syngenetic inorganics that are the result of biogenic processes during plant growth (e.g., photosynthesis, diffusion, adsorption, osmosis, pinocytosis, exocytosis, endocytosis, hydrolysis, precipitation, etc.)

epigenetic inorganics generated from natural processes after plants died (evaporation, precipitation)

detrital

pre-syngenetic fine (~ 1μm) inorganic particulates suspended in water and transported into the plant during syngenesis (endocytosis)

syngenetic, pre-syngenetic or epigenetic

small (<10–100 μm) inorganic particulates deposited on plant surfaces by water and wind, and fixed in voids and cracks over time during plant growth

Anthropogenic Process technogenic

post-epigenetic

none physiological inorganics resulting from harvest (collection, handling, transportation) and preprocessing (comminution, separation, etc.) operations

aSyngenetic = during plant growth; epigenetic = after plant death; pre-syngenetic = before plant growth, post-epigenetic = during and after plant collection.

Table 2 Common nature of inorganic in lignocellulosic biomass (adapted from ref 21)

group examples of organic forms

examples of inorganic forms dominant forms

alkali metals oxalate Na+ and K+ in fluid matter; KCl, NaCl; NaNO3, KNO3

mostly in ionic salts forms

alkaline earth metals

oxalate; carbonate

Mg2+ and Ca2+ in fluid matter; CaCl2, MgCl2, Ca3(PO4)2 and Mg3(PO4)2

form with organic counter ions to large extent complexes

transition metals

Fe-Chelates; Mn-

Carbohydrate

Fe2+, Mn2+ and Cr3+ in fluid matter; Metallic form; Iron oxide

often in small (< 2 μm) crystal structures

other metals (Al, Pb etc.)

– aluminum hydroxide (Al(OH)3);Kaolinite

mostly in inorganic forms

non-metals (P, S etc.)

covalently bound to proteins, amino acids

sulfate (SO42−), sulfite (SO3

2−) and phosphate (PO4

3 −) anions varies with types of feedstocks

7

K) are mostly not metabolized by the plant and remain in the form of ionic salts in

lignocellulosic biomass materials.24 They are often dissolved in the fluid matter are trapped

within the biomass cell structure in free ion form (Na+ , K+ ) with counterions such as chloride

(Cl−) or malate (C4H4O5 2−).21 Alkali metals also appear in solid salt structures fixed on the

biomass cell wall.21 A small amount of Na and K are attached to functional groups in the organic

matrix as carboxylates and phenoxides.25 Alkaline-earth metals (Mg and Ca) exist in different

chemical statuses than alkali metals. In the plants, Mg and Ca are required for plant growth and,

to a large extent, have a tendency to form complexes with organic counterions.25 As such,

alkaline-earth metals do not usually occur in free ionic form.

Besides alkali and alkaline-earth metals, other metals commonly present in

lignocellulosic biomass are Fe, Cu, Ni, Cd, Cr, Co, Mn, Zn, Al, and Pb. When present in

biomass, the concentrations of the transition metals are usually very low. Transition metals

present in biomass can be from the natural environment (for example, when mineral-rich water

or contaminated groundwater is taken up by the roots and transported via the stems to upper

branches and leaves18). The sources of these elements are largely technogenic. For example,

harvesting equipment can transfer metal traces to the biomass material due to natural wear and

tear that occurs as a result of these operations.19 These metals have various forms. They can bond

with organic matter and impurities in the amorphous or crystalline cellulose or defects in the salt

crystal structure.26 In addition, they can exist in ionic form and as impurities in sulfates, nitrates,

etc.26 Cohen and Dunn27 reported these metals to be often included in small (<2 μm) crystal

structures. Fe, Cu, Ni, Cr, Mn, Zn, and Pb were shown to associate primarily with the water-

insoluble portion of the lignocellulosic biomass, while Cd, Co, and Al showed positive

associations with the water-soluble fraction.26 Except for Fe, Cu, and Al, all transition elements

showed a positive association with cellulose. Elements that did not show a positive association

with cellulose (Fe, Cu, and Al) are frequently used as construction metals in processing

equipment, which suggests that these elements may be rather more technogenic than natural.19

Nonmetals such as phosphorus (P) and sulfur (S) can be found in both organic and

inorganic components. The ratio between organic and inorganic sulfur-containing molecules is

largely dependent on the type of biomass, as well as the location. While phosphorus and sulfur

can exist in proteins and amino acids and as sulfate and phosphate anions,21 phosphorus is

predominantly found in its inorganic form. Chlorine is also present in most biomass materials as

8

chlorides, chlorites, and chlorates. Chlorides identified in biomass can be formed in biomass and

from outside resources in origin.19 Elemental nitrogen (N) exists as nitrates, nitrites, and

alkaloids.18

4. THE EFFECT OF INORGANICS ON BIOMASS THERMOCHEMICAL CONVERSION PROCESSES

Thermochemical conversion technologies (combustion, gasification, and pyrolysis) are

very sensitive to feedstock inorganic content with recommended ash contents of <1 wt %.20 In

the next sections, we discuss the effect and fate of inorganics on pyrolysis, gasification, and

combustion.

4.1 Pyrolysis Inorganic elements of biomass have been known for some time to have significant and

often undesired consequences on the pyrolysis process.28-29 The presence of these elements in the

pyrolysis vapors occurs by ejection of biomass inorganics during primary aerosol formation, as

illustrated in Figure 1.30 Although biomass inorganics remain predominantly in the biochar, the

fraction ejected as well as fine biochar particles entrained can have drastic impacts on the biooil

properties and product yields.21, 29 Studies have shown negative effects of higher bulk ash content

on the pyrolysis yields with a negative correlation between total ash content and bio-oil yield.31-

32 Biomass feedstocks with low ash content generally result in higher organic bio-oil, compared

to high ash feedstocks. It was reported that bio-oil yields increased by 1%− 5% for each 1% of

ash removed from native biomass.31, 33-34 Silica is relatively inert and typically accumulates in the

product char fraction. However, even trace levels (<0.1%) of catalytically active ash components

can change the thermal degradation rate and chemical pathways during pyrolysis. Alkali metals

(K and Na) and, to a lesser extent, the alkaline-earth metals (Ca and Mg) are known to catalyze

the thermal degradation of biomass. In the case of alkali metals at a lower concentration in

biomass, the extent of transfer from biomass to bio-oil varies, depending on the species: for

sodium, the transfer is high and averages 25% of the original content in biomass, whereas for

potassium, the transfer was moderate and 2.6%.21 For alkaline-earth metals, the concentration

of Ca and Mg in the pyrolysis oil was reported to be within the range of 1%−5% of the original

content in the biomass.21 In addition, a higher water content was observed in the bio-oil with

higher content of alkaline-earth metals.35 For nonmetals, the degree of sulfur transfer varied

9

based on the biomass type. In the woody biomass materials, the extent of sulfur transfer was 36%

or greater, while it was 32%−96% in the agricultural residues. Phosphorus had a low transfer to

pyrolysis oil, with an average of 2%.21 Meanwhile, gas-phase emissions during pyrolysis

contain a certain degree of nitrogenous species (NH3, HNCO, and HCN), chlorine species (HCl

and Cl2), and sulfur species (COS, H2S, and SO2).36 The formation pathways of NH3 are that (i)

proteins and amino acids may release in the form of NH3 in the temperature range of

300−500 °C, (ii) thermal cracking reactions of tar and char can form NH3 by undergoing

secondary reactions, and (iii) hydrogenation and hydrolysis of HCN can introduce NH3 on the

surface of the char.37 As for HCN and HNCO, cracking of the cyclic amides is considered to be

the main reaction leading to their formation.38 NH3, HNCO, and HCN are the precursors of

nitrogen oxides (NOX and N2O), which can cause environmental concerns. Chloric species could

be released to the flue gas as HCl and much lower content of Cl2, which could subsequently

bring corrosion problems.36 For sulfur species, COS and H2S are released from the

decomposition of organically bound sulfur with a lower stability, and SO2 comes from the

evaporation or transformation of inorganic sulfate.36 The SO2 content from the sulfur is also

considered to be an important factor in the corrosion processes.36

Figure 1 Pathways to aerosols: ejection of biomass inorganics during primary aerosol

formation30

4.2 Gasification Inorganic impurities in gasification producer gas include sulfur compounds, nitrogen

compounds, alkali metals (primarily potassium and sodium), and hydrogen chloride (HCl).12, 39-40

Depending on the downstream applications, each contaminant creates specific challenges

ranging from corrosion and fouling of surfaces to rapid and permanent deactivation of

10

catalysts.39, 41 In the producer gas, the concentrations of contaminants based on biomass-bound

inorganic impurities vary greatly and are positively correlated to inorganic content in the starting

solid feedstocks.42-43 Thus, the cleaning process for syngas is of great importance. The level of

required cleaning varies, depending on the downstream technology and/or emission standards

(see Table 3).11

Table 3 Typical syngas applications and associated cleaning requirements11 application sulfur nitrogen alkali halides

gas turbine <20 μL L−1 <50 μL L−1 <0.024 μL L−1 1 μL L−1 methanol synthesis <1 mg m−3 <0.1 mg m−3 <0.1 mg m−3 FT synthesis <0.01 μL L−1 <0.02 μL L−1 <0.01 μL L−1 <0.01 μL L−1

During gasification, the major nonmetal biomass inorganics are nitrogen, sulfur, and

chlorine, because contaminants derived from these species have been tied to specific challenges

in downstream applications (see Table 3). Typical syngas applications and associated cleaning

requirements are also given in Table 3.11-12, 39, 41 Biomass-bound nitrogen is predominantly

transformed to ammonia (NH3), with smaller amounts of hydrogen cyanide (HCN), in producer

gas. The nitrogen-based contaminants can also be further oxidized to nitrogen oxide (NO) and/or

dioxide (NO2), both of which are environmental pollutants subjected to control under the U.S.

Environmental Protection Agency (USEPA) regulations. Biomass sulfur is converted

predominantly to hydrogen sulfide (H2S), carbonyl sulfide (COS), and other minor sulfur

containing compounds.12, 44 Organically associated S is released during the decomposition of the

organic fuel matrix during devolatilization.45 Through this pathway, the release of S proceeds

through the formation of SH radicals, which come from the thermal decomposition of S-bound

organic compounds.46 These SH radicals, which are highly reactive, could extract H, C, or O

from the char, forming H2S, COS, or SO2.45-46

Their proportions in producer gas are dependent on the sulfur content of the starting

feedstocks, as well as the operating conditions: higher physiological sulfur in biomass results in

higher sulfur-based contaminants in producer gas, while lower equivalence ratios (i.e., lower O2)

result in more reduced forms of sulfur contaminants.39-40 Chloride, which is the most abundant of

the halide-based contaminants in producer gas, is present at relatively lower concentrations in the

form of HCl with concentrations of <100 ppmv for woody biomass.39-40 Despite their low

concentrations, chlorine-based contaminants can cause serious challenges, including fouling and

11

deposition as the producer gas is cooled downstream, as well as corrosion, as a result of the

deposition and catalyst poisoning.47 Moreover, chloride in the producer gas can react with other

contaminants in the gas phase to produce other contaminants such as ammonium chloride

(NH4Cl) and sodium chloride (NaCl). Besides sulfur, nitrogen, and chlorine, trace metals are

important to track throughout the process. Especially, alkali and, to a lesser extent, alkaline-earth

metals are of interest, because they have been associated with hot corrosion of the gasifier.48 In

addition, catalysts are known to be extremely sensitive to alkali metals and can easily be

poisoned by levels found in biomass during in situ catalytic gasification.11 However, since alkali

compounds can leave the reactor as aerosols and vapors and are transported out of the reactor,

normally in the form of hydroxides, chlorides, and sulfates, they still present a challenge for ex-

situ conditioning of syngas or downstream catalytic applications and can cause substantially

fouling and corrosion in downstream processes.48-49

4.3 Combustion About 95%−97% of the world’s bioenergy is currently produced by direct combustion of

biomass.50 As a result, 480 million tons of biomass ash could be generated worldwide annually

if the burned biomass is assumed to be 7 billion tons.50 The challenges of managing biomass-ash-

derived inorganics during combustion is welldocumented.12, 51-53 Generally, issues related to

these inorganics during combustion are agglomeration,50 alkali deposits,53 slagging,51 fouling, 51-

52 and corrosion.52, 54 The propensity for inorganics to lead to the aforementioned issues are

measured by various indices, as shown in Table 4.

Slagging and fouling propensity are typically determined by similar feedstock

properties.52, 55-56 Slagging is defined as the formation of sintered and molten deposits on

surfaces and refractory lining in the main furnace cavity in regions directly exposed to flame

radiation, while fouling is defined as the formation of sintered, but not molten, deposits on

surfaces in the convective pass of the boiler not directly exposed to flame radiation with flue gas

temperature below the melting temperature of the bulk fuel ash.57 Slagging and fouling deposits

are of great concern to biomass or biomass-coal fired plants. Its primary mechanism consists of

the condensation of devolatilized inorganic species on the refractory lining, heat exchangers,

superheaters, reheaters, and other surfaces in the furnace and on the path of hot flue gases.58 The

transformation of inorganic components with chemical reactions occurring could cause the

formation of chemical compounds and complexes with extremely low melting point and/or very

12

Table 4 Select indices indicative of slagging, fouling, agglomeration, and corrosiona indicesb empirical formula indicator of propensity

Low Medium High base/Acid Ratio

slagging fouling

< 0.4 0.4 - 0.7 >0.7

fouling Index fouling < 0.6 0.6 - 40 > 40

slagging factor

slagging <0.6 0.6 - 2.0 > 2.0

alkali index (kg/GJ)

fouling slagging

< 0.17 0.17 - 0.34 > 0.34

Cl content (wt.% dry)

corrosion < 0.1 > 0.1

S content (wt.% dry)

corrosion < 0.1 > 0.1

bed agglomeration

agglomeration > 2.5 0.1 - 2.5 < 0.1

aData taken from ref 55-58. bIndices for which units are not specified are unitless. high adhesion force.55 For example, Na2S2O7 melts by 401 °C, K2S2O7 melts by 325 °C,

Na3K3Fe2(SO4)6 melts by 552 °C, Na2SO4−NaCl melts by 625 °C, Na2S−FeS melts by 640 °C,

and eutectic mixture CaSO4−CaS melts by 850 °C.55 The low melting points can be expected by

combustion of fuels with high sodium and potassium contents.55 The mechanism typically begins

with the condensation of alkali salt vapors on exposed surfaces, thus creating sticky anchors that

assist in binding other inorganics and particulates.59 The result of this process is the formation of

a hard and fused glassy layered deposit structure on these surfaces and the loss of functional

purpose (i.e., loss heat transfer potential, loss of integrity, etc.).50-51 Among the inorganic

elements, K, Na, Cl, and S are thought to be the root causes of slagging/fouling, agglomeration,

and corrosion during the combustion of biomass-based fuels.60-61

5. PRE-TREATMENTS FOR THERMOCHEMICAL CONVERSION OF BIOMASS

Pre-treatment is the first and most important step in biomass processing. It is the key

process to modify the undesirable properties of lignocellulosic biomass in order to improve its

conversion efficiency and reduce its production cost.62 In the context of the thermochemical

conversion platform, pretreatment has been traditionally used to facilitate material handling.

However, in recent years, pre-treatment techniques commonly used in biochemical conversion

13

are beginning to be explored for the targeted amelioration of specific biomass properties.33, 63

This section narrowly focuses on the impact of these advancements on reducing the content of

inorganics in lignocellulosic biomass dedicated to thermochemical conversion. We grouped pre-

treatment techniques into four categories: (1) mechanical (e.g., comminution and mechanical

sieving); (2) thermal (e.g., torrefaction, steam explosion/liquid hot water pre-treatment, and

ultrasound/microwave irradiation); (3) chemical (e.g., treatment with acids, bases, and ionic

liquids); and (4) biological (e.g., fungal, microbial consortium, and enzymatic). Biological pre-

treatment has not yet been employed in the context of thermochemical conversion, based on our

survey. Therefore, no discussion is presented.

5.1 Mechanical pre-treatment Mechanical pre-treatment encapsulates all of the techniques that primarily employ

mechanical energy to affect changes in biomass properties and includes comminution to reduce

particle and sieving to fractionate material based on particle size. The latter, mechanical sieving,

has been shown to significantly affect ash content of biomass by varying biomass particle sizes

and disproportionately segregating inorganic elements in different fractions.64-67 Liu et al. studied

the effect of size fractionation for switchgrass and pine bark and reported that ash content varied

greatly by different size fractions.65 Furthermore, their results showed that size fractionation

could potentially remove more than 20% of the inorganic constituents from the switchgrass and

up to 30% of inorganic constituents from raw pine bark. The fine fractions of ground switchgrass

and pine bark have larger ash content than the coarser fractions. In particular, for a sample that

varied from 0 to 0.95 mm in particle size, the fraction of biomass between 0.4−0.95 mm had the

lowest ash content, highlighting the disproportionate distribution of ash in fines. Bridgeman et al.

reported similar trends for switchgrass and reed canary grass and observed that the ash content

nearly doubled in fines (<90 μm) from 3.62 wt % to 6.0 wt % (dry basis) for reed canary grass

and 3.12 wt % to 6.88 wt % (dry basis) for switchgrass, respectively.64 Pattiya and co-workers

studied the effects of biomass size reduction on cassava stalk and rhizome.68 They found that, for

both cassava stalk and rhizome, the particle size of 0.250 mm showed much lower ash contents.

The differences among the ash contents of the biomass with a particle size of >0.250 mm were

very small. Arvelakis et al. investigated the effect of size fractionation of three different agro-

residues.69 The results showed that the total ash content in the coarse fraction samples (particle

size of >1 mm) is reduced by almost 35% from the original sample, but most of the main

14

troublesome elements (such as K, Cl, and S), which are considered to be responsible for

problematic ash thermal behavior, remained in it. For the fine fraction samples (particle sizes of

<1 mm), their ash content was significantly larger than the course samples.

While ash content increased in fines upon fractionation (see Table 5), the concentration

of individual elements in fines might vary depending on the feedstock, the definition of what

constitutes “fines” and representativeness of the samples characterization is carried on. Miranda

and colleagues reported that the concentration of elements such as nitrogen (N), phosphor (P),

sodium (Na), and potassium (K) increased in the fine fraction (<180 μm) of Norway spruce

(Picea abies (L.) Karst.) and Scots Pine (Pinus sylvestris L.) barks. However, the content of

magnesium (Mg) decreased in the fines and increased in the coarser fraction for both

feedstocks.66 However, Bridgeman and co-workers showed that all 11 elements measured in their

study (Al, Ca, K, Na, Mg, Mn, Ni, P, S, Zn, and Fe) increased in the fine fraction (<90 μm).64

5.2 Thermal pre-treatment Thermal pre-treatment includes the techniques that primarily rely on thermal energy to

affect changes in biomass properties. While it is understood that, with increasing temperature,

several chemical reactions would occur, thermal pre-treatment techniques are primarily driven by

thermal energy delivered through a gaseous or liquid carrier. Because of the change of properties

during thermal pretreatment, the ash content of the biomass would also be changed. Pre-

treatments such as steam explosion, hot water extraction, and hydrothermal carbonization have

shown their effect on the change in ash content of several biomass materials.

Table 5 Effect of mechanical sieving on ash content for select lignocellulosic feedstocks Ash Content (wt % dry basis)

Refs fraction, μm < 180 180 - 250 250 - 450 450 - 850 850 – 2000 > 2000 birch 3.4 4.5 2.5 2.6 2.1 2.2 66 eucalyptus 23.1 14.7 15.9 7.9 6.7 4.3 66 Douglas fir 1.5 1.1 0.8 0.8 1.2 0.4 67 switchgrass† 10.53 8.07 7.21 5.54 4.31 -- 65 pine barka 4.93 4.04 2.79 2.40 2.38 -- 65

aFractions for these two feedstocks are as follow: < 150, 150 – 300, 300 – 400, 400 – 950 and > 950 μm, respectively

The typical process of commercial steam explosion involves filling a vessel with wood

chips and then pressurizing it with saturated steam at a pressure of 7000 kPa.33 The pressurized

15

steam permeates the chips, and introducing the rapid decompression defibrates the wood chips

when the vessel is suddenly opened.33 During steam explosion, lignin depolymerizes into low-

molecular-weight products (400−8000 units) and condenses with other degradation products,

which results in an increase in lignin content. Steam explosion also partially breaks down

hemicelluloses, which become predominantly soluble in water. The loss of hydroxyl groups

causes a reduction in the hygroscopicity of the biomass material, since hydroxyl groups provide

hydrogen bonding sites for water molecules in the hemicellulose and cellulose. Steam explosion

also showed effectiveness in the change of ash content for different raw biomass materials. Jeoh

and Agblevor studied the effect of steam explosion on cotton gin waste with 10.5 (±3.4) wt %

ash content.70 Results showed the effectiveness of steam explosion to reduce the ash content of

cotton gin waste to between 6.1 (±2.1) wt % and 0.0 (±0.0) wt %, depending on increasing

severities. Lam investigated the effect of steam explosion on Douglas Fir wood chips.71-72 The

study showed a slight increase (0.27% to 0.32% by weight) of the ash content for the 200 °C

treated wood pellet and a further increase (0.27% to 0.52% by weight) of the ash content of the

220 °C treated wood pellet. Tooyserkani et al. studied the steam treatment of three white

softwood species (pin, spruce, and Douglas fir) and one sample of bark at 220 °C for a residence

time of 5 min.73 Their study showed an increase in the relative ash content values for the four

samples, which, as stated in the study, cannot directly show the increase in the inorganic content

of samples; it could indicate the relative loss of other components in the samples. Wang and

Chen utilized steam explosion technology on cornstalk at 185−190 °C for a residence time of 5

min.74 The steam-exploded cornstalk showed lower ash content (1.24 wt %), compared to the

original cornstalk sample (1.59 wt %). Kemppainen et al. studied steam explosion for industrial

spruce bark at 205 °C/16.3 bar for 5 min.75 Ash content of spruce bark was reduced to 3.2 wt %

dry basis from 3.6 wt %. Biswas et al. studied the influence of steam explosion on Salix wood

chips.76 Their study resulted in the reduction of ash content in steamtreated residue (from 2.4%

to 1.8%, dry basis), especially of alkali metals (both Na and K achieved 50% of reduction).

Hot water extraction (HWE) pre-treatment is one of the leading pre-treatment methods

for improving cellulose digestibility of lignocellulosic biomass.77 The acidic liquor of HWE,

usually conducted at elevated temperatures (120−260 °C) with no added chemicals, is regarded

as an environmentally friendly pre-treatment process. Several studies have reported a noticeable

reduction of ash content upon hot water extraction with notably high removal efficiency for

16

alkali metals.78-79 The efficiency of HWE in removing alkali species can be due to the fact that

most alkali elements in biomass are present in watersoluble forms.80 Mante et al. analyzed the

hot-water treated (at 160 °C for 2 h) sugar maple samples.79 Results showed that HWE decreased

the ash contents from 0.81 wt % to 0.38 wt % dry basis. Das et al. carried out hot water treatment

on the Douglas fir and the hybrid poplar (H. pop) for 30 min at 121 °C.32 The hot-water-treated

Douglas fir sample had an ash content of 0.1 wt %, compared to the original 0.3 wt % dry basis;

the hot-water-treated hybrid poplar sample had an ash content of 5.4 wt %, compared to the

original 7.0 wt % dry basis. Their results also showed that, for both the biomass samples, hot

water extraction effectively reduced the content of Ca, Mg, Na, and K. Kemppainen et al. studied

hot water extraction as pre-treatments for industrial spruce bark at 80 °C for 120 min. The ash

content of spruce bark was reduced to 3.3 wt % dry basis, from 3.6 wt %.75

Hydrothermal carbonization (HTC) or wet torrefaction is another thermal pre-treatment

method that has been used to pretreat biomass prior to thermochemical conversion.81-82 The

objectives of hydrothermal carbonization are to produce a material with increased stability, as

well as increased carbon and energy contents.33 HTC results in three products: gases, aqueous

chemicals, and solid fuels. Temperatures for HTC are usually between 160−300 °C and pressures

below 5000 kPa.33, 81-82 The production rate of HTC is higher than that of torrefaction and,

because initial moisture content is not critical, HTC may be compatible with a broader range of

feedstocks. However, commercial-scale HTC is expected to be more expensive than dry thermal

pre-treatments such as torrefaction, because of the need for pressure vessels, which are more

expensive.33 The economics of combining HTC with fast pyrolysis have not been thoroughly

assessed in the literature. Determining whether a dry, wet, or no thermal/chemical pretreatment is

preferred prior to thermochemical conversions requires consideration of the costs and

technologies available for grinding, drying, transporting, storing, handling, and upgrading.33

HTC has the capability to reduce the ash content of pretreated biomass. According to Chen et al.,

the wet torrefaction of sugar cane bagasse was conducted at 180 °C for 5−30 min with sulfuric

acid (concentrations of 0 and 0.1 M).83 Results showed a reduction from 3.55 wt % to 1.70 wt %

of the ash content in bagasse under water torrefaction. Wet torrefaction with acid solution can

also remove ash; however, more solid was also consumed. Bach et al. investigated the effect of

wet torrefaction on Norway spruce and birch under different conditions (temperatures of 175,

200, and 225 °C; holding times of 10, 30, and 60 min; and pressures of 15.54, 70, and 160 bar).84

17

According to their results, the ash content of Norway spruce can be reduced from 0.23 wt % to

0.09 wt %, and the ash content of birch can be reduced from 0.28 wt % to 0.08 wt %. Zhang et

al. studied the effect of wet torrefaction on the ash content of duckweed samples with an ash

content of 9.7 wt %. As the wet torrefaction temperature increased from 130 °C to 250 °C, the

ash content increased from 7.6% to 19.9%.85 Table 6 summarizes studies that were focused on

thermal pretreatment and their effectiveness in ash content reduction.

5.3 Chemical pre-treatment Chemical pre-treatment includes techniques that primarily rely on the action of chemical

agents applied at or near room temperature to affect changes in biomass properties. The

techniques reviewed here include water leaching and acid, alkali, and salt washing. Table 7

summarizes the main outcomes of studies that investigated various chemical pre-treatment

techniques for inorganic reduction.

5.3.1 Water leaching Washing the biomass with water have been shown to be effective in removing the

majority of alkali metals (e.g., K and Na), as well as some of the chlorine contaminants.49, 86, 88

Liaw and Wu reported that an acidic leachate was produced during the batch leaching of organic

matter from biomass, resulting in the leaching of some waterinsoluble inorganic species.98 Baxter

et al. reported that 80%− 90% of the alkali metals in biomass exist in water-soluble or

ionexchangeable species form.53 Meantime, water washing is more suitable for feedstock with a

high inorganics content.53 Biomass with a low inorganics content (e.g., woody biomass) has a

higher concentration of alkali metals bound to the organic structure and thus has limits with

regard to the effectiveness of water washing, although agitation can enhance the efficiency.53

Jenkins et al. carried out experiments on inorganic removal from rice and wheat straws by water

leaching at room temperature for 24 h.86 Their results showed that 90% of K, 98% of Cl, 55% of

S, 68% of Na, 72% of P. and 68% of Mg were removed. Also, total ash concentrations were

reduced by 10% in rice straw, and by 68% for wheat straw for well-washed samples.86

Davidsson et al. studied wheat straw and wood waste (mainly pine and birch), with respect to

alkali-metal release.88 Their study found out that washing with water at room temperature for 4 h

reduced the alkali emission by 5%−30% from wood waste and wheat straw. Yu and co-workers

18

Table 6 Summary of thermal pretreatment for inorganic removal from biomass Feedstock Experimental conditions Original ash content

(wt%, dry basis) Final ash content (wt%, dry basis)

Refs

Steam Explosion cotton gin waste

At 185, 211.5, and 238 °C for 20, 510, and 265 s

10.5 6.1-0.0 70

cornstalk At 185 to 190 °C for 5 min

1.59 1.24 74

spruce bark

At 205 °C/16.3 bar for 5 min

3.6 3.2 75

salix wood chips

At 220 and 228 °C for 6 and 12 min

2.4 1.8 76

Douglas fir

At 200 and 220 °C for 5 and 10 min

0.27 0.32-0.52 71-72

pine At 220 °C for 5 min 0.07 0.34 73 spruce At 220 °C for 5 min 0.22 0.94 73 Douglas fir

At 220 °C for 5 min 0.14 0.28 73

Douglas fir bark

At 220 °C for 5 min 2.11 4.13 73

Hot Water Extraction sugar maple

At 160 °C for 2 h 0.81 0.38 79

Douglas fir

At 121 °C for 30 min 0.3 0.1 32

hybrid poplar

At 121 °C for 30 min 7 5.4 32

spruce bark

At 80 °C for 2h 3.6 3.3 75

Hydrothermal Carbonization sugarcane bagasse

At 180 °C for 5 to 30 min with sulfuric acid

3.55 1.7 83

Norway spruce

At 175, 200, 225 °C for 10, 30, 60 min, pressure at 15.54, 70, 160 bar

0.23 0.09 84

birch At 175, 200, 225 °C for 10, 30, 60 min, pressure at 15.54, 70, 160 bar

0.28 0.08 84

duckweed At 130 to 250 °C for 60 min

9.7 7.6 - 19.9 85

19

Table 7 Summary of chemical pretreatment for inorganic removal from biomass Pretreatment Feedstocks Experimental conditions Outcomes Refs Biomass particle

size (mm) Liquid to solid ratio

Time (hour) Temp (°C)

Ash reduction (%)

Mass loss (%)

Water leaching D.I. water Rice straw 70:1 24 20-25 10 86

Wheat straw 70:1 24 20-25 68 86 Miscanthus 0.25–2.00 20:1 4 (300 rpm) 25 48 5 (carbon

reduction) 87

Wheat straw 0.50–2.00 50:1 4 25 47 88 Wood waste 0.50–2.00 50:1 4 25 36 88 Miscanthus 2.00 20:1 6 22 15 89 Switchgrass 2.00 20:1 6 22 24 89 Wheatgrass 2.00 20:1 6 22 53 89 Rice straw 2.00 20:1 6 22 24 89 Wheat straw 2.00 20:1 6 22 39 89 Corn stover 2.00 20:1 6 22 47 89 Douglas fir 2.00 20:1 6 22 40 89 Switchgrass 0.40-0.95 40:1 48 20 40 65 Sugarcane bagasse

0.25 12:1 1 25 31 18-20 32

Empty fruit bunchs

0.31 20:1 1, 3, 5, 10, 30, 60, and 120 min

25, 40, 55

52 90

Palm kernel shells

0.72 20:1 1, 3, 5, 10, 30, 60, and 120 min

25, 40, 55

10 90

Rice straw 0.84 40:1 24 25 14 56

Wheat straw 0.84 120:1 24 25 50 56

Switchgrass 0.84 120:1 24 25 14 56

Wood fuel 0.84 120:1 24 25 10 56

Acid washing 10 g/l CH3COOH Switchgrass 0.42 20:1 0.33 85 62.8 6.1 78

20

Table 7 Continued Pretreatment Feedstocks Experimental conditions Outcomes Refs 10 g/l C6H8O7 Switchgrass 0.42 20:1 0.33 85 52.5 6.8 78 10 g/l H2SO4 59.7 32.9

H2SO4 Douglas fir 0.42-0.85 2.5:1 3 25 47 91 Hybrid poplar

0.42-0.85 2.5:1 3 25 46 91

1.00% HCl Miscanthus 0.25–2.00 20:1 4 (300 rpm) 25 4 87 HCl Seaweed 5.00 40:1 24 (200

rpm) 25 15 92

H2SO4 Seaweed 5.00 40:1 24 (200 rpm)

25 16 92

HNO3 Seaweed 5.00 40:1 24 (200 rpm)

25 17 92

0.1 M HCl Cotton residue

0.25 20:1 4 25 68 93

Waste wood 0.25 20:1 4 25 24 93 1 M CH3COOH

Cotton residue

0.25 20:1 4 25 58 93

Waste wood 0.25 20:1 4 25 18 93 1 M CH3COOH

Wheat straw 0.50–2.00 50:1 4 25 83 88

1 M CH3COOH

Wood waste 0.50–2.00 50:1 4 25 73 88

0.1 M HCl Switchgrass 0.40-0.95 20:1 48 20 72 65 5 M CH3COOH

Switchgrass 0.40-0.95 20:1 48 20 48 65

0.01 M HNO3 Switchgrass 0.40-0.95 20:1 48 20 35 65 5 M HCl Sugarcane

bagasse 0.25 12:1 1 25 -16 50 32

CH3COOH and HNO3

Beech wood 20:1 2 & 4 25 & 50

4–15 94

21

Table 7 Continued Pretreatment Feedstocks Experimental conditions Outcomes Refs 0.1% HNO3 Mallee

wood 0.18-0.43 10:1 2 25 100 (Na, K, &

Mg removal); 96 (Ca removal)

95

5% HCl Rice straw 0.15-0.45 25:1 24 105 95 (K removal), 99 (Na removal)

96

Alkali washing NaOH Seaweed 5.00 40:1 24 (200

rpm) 25 51 (Cr

removal) 47 92

NH4OH Seaweed 5.00 40:1 24 (200 rpm)

25 52 (Cr removal)

35 92

NaOH Barley straw 25-30 4:1 10 min 100 86 97

Salt washing NH4H2PO4 Douglas fir 0.42-0.85 2.5:1 3 25 -13 91

Hybrid poplar

0.42-0.85 2.5:1 3 25 46 91

Chelating agent EDTA Switchgrass 0.42 20:1 0.33 85 87.3 8.0 78

22

investigated the effect of water leaching on ash contents of wheat and rice straws, Jose tall

wheatgrass, switchgrass, miscanthus, Douglas fir, and corn stover at room temperature for 6 h.89

Their results showed that the ash contents of all feedstock samples were significantly reduced.

Leaching reduced the ash concentration in rice straw by 15% of dry matter, in wheat straw by

24%, in corn stover by 53%, in switchgrass by 24%, in miscanthus by 39%, in Jose tall

wheatgrass by 47%, and in Douglas fir by 40%. Liu and Bi reported ash removal for water

leaching of switchgrass up to 40% when leaching for 48 h at room temperature when the biomass

particle size was reduced to 0.4−0.95 mm.65 Their study showed that a combination of size

fractionation and water leaching could potentially remove more than 60% of inorganic

contaminants from the switchgrass. Lam et al. studied the effect of leaching on oil palm residues

and reported three leaching stages of empty fruit bunches achieved ash reduction from 5.47% to

2.63%, with the greatest potassium reduction being from 2.42% to 0.36%.90 Also, Das et al.

carried out water leaching for sugar cane bagasse at room temperature for 1 h.32 The results

showed that leaching reduced ash contents in sugar cane bagasse by 31% of dry matter, with a

mass loss of 18%−20%.

5.3.2 Acid washing It has been suggested that acid washing facilitates mass transfer and higher levels of ash

removal, compared with normal water leaching.68 Scott et al. suggested that inorganics in

biomass are present in water-soluble salts and cations that are bound to reactive sites,

respectively.99 Treatment with water at room temperature is adequate for the removal of the

water-soluble part, but the cations bound to reactive sites require ion exchange. Because of the

existence of some water-insoluble inorganic elements in biomass, washing with dilute acid

(hydrochloric acid (HCl), acetic acid (CH3COOH), sulfuric acid (H2SO4), hydrofluoric acid

(HF), and nitric acid (HNO3)) has been developed for higher levels of ash removal from

biomass.65 Stylianos and co-workers94 studied the ash reduction from beech wood by acid

washing (HNO3 and CH3COOH) and found that washing with acidic solutions achieved an

inorganics removal of >90%. The los of biomass in this study varied in the range of 4%−15%.

Shi’s group96 investigated 5% HCl acid washing for rice straw at room temperature for 3 h and

reported that almost all alkali and alkaline-earth metals (AAEMs) were removed by this method.

Mourant and co-workers95 used dilute HNO3 acid (0.1 wt %) at room temperature for 2 h and

reported complete removal of all AAEM species, with the exception of calcium, for which only

23

4% of the initial content remained. Das et al. employed H2SO4 acid (0.3 wt %) on Douglas fir

(softwood) and hybrid poplar (hardwood) for 3 h at room temperature and achieved an ash

reduction of 47%.91 Banks et al. used HCl acid (1 wt %) to pretreat miscanthus at room

temperature, which resulted in 48% of ash reduction.87 However, partial hydrolysis of

hemicellulose was shown by TGA analysis in their study. Vamvuka et al. determined the extent

to which various inorganics could be removed by different acids (HCl and CH3COOH) and the

effect of acid pre-treatments on biomass ash composition.93 Their study found that ash removal

was accomplished by acid-washing of waste wood and cotton samples at room temperature,

which resulted in ash removals of 15%−24% and 57%−68%, respectively. Davidsson et al.

investigated the effect of acid washing on the release of alkali compounds.88 With 4 h of acetic

acid washing at room temperature, the study attained 73% and 83% reduction in alkali release of

wood waste and wheat straw, respectively. Liu et al. investigated several acid washing pre-

treatments (HCl, HNO3, H2SO4, and CH3COOH) to remove inorganic components from pine

bark and switchgrass.65 Their results showed that acid treatment improved inorganics removal

efficiency significantly. Acidity is the key paramount factor that affects the removal, with more

ash being removed as the pH decreased. Furthermore, the washing time and acid type were less

significant than the acidity of the liquor. In contrast with water leaching, acid washing can lead

to a large mass loss, because polysaccharides (i.e., cellulose and hemicellulose) can be partially

hydrolyzed, with 20% weight loss of coarse samples (0.4−0.95 mm) after 8 h of soaking into

0.5 M HNO3 at room temperature. Park and others also found that acid treatment of seaweed

resulted in mass losses; with HNO3, H2SO4, and HCl causing mass losses of 17%, 16%, and

15%, respectively.92

In summary, these studies clearly show that acid washing is effective in removing

inorganics from biomass and can achieve complete removal of all alkali and alkaline-earth

metals, given enough time and acidity. The main drawbacks of mineral acid washing are the

added cost associated with recovery and disposal of spent acidic liquor; the introduction of

inorganic elements that the washing process is seeking to remove in the first place; and the

resulting mass loss, in some cases, that reduces carbon availability for thermochemical

conversion. Large quantities of wastewater generated in this process are especially problematic

and lead to excessive wastewater generation. Often, mineral acid washed biomass must be

rewashed multiple times with deionized water to remove remaining mineral acid ions, such as

24

chloride (Cl−) when HCl is used or nitrate (NO3−) when nitric acid (HNO3) is used during

washing. Those drawbacks restrict the large-scale applications of acid washing in

thermochemical conversion were these residual species have undesirable consequences

downstream.

5.3.3 Base washing Besides acid washing, base washing is investigated as another approach to avoid the

negative effects of inorganics. Park et al. explored seaweed washing with sodium hydroxide

(NaOH) and ammonium hydroxide (NH4OH) at a concentration of 1 M for 24 h and observed

51%−52% removal in Cr(VI), which is the target of their study.92 Furthermore, they reported

mass losses of 47% and 35% for NaOH and NH4OH, respectively. Kazi et al. investigated the

effectiveness of NaOH impregnation on barley straw at different levels and three temperatures

(25, 60, and 100 °C) for 10 min.97 Their results showed that a considerable amount of ash is

removed (up to 86 wt % of the initial ash), along with extractives. Few studies have explored

basic salts as a pre-treatment agent for reducing inorganic content. Das et al. investigated the

effect of salt washing on Douglas fir and hybrid poplar at room temperature for 3 h.91 They

found salt doping pre-treatment was effective in removing 46% of ash from hybrid poplar

samples. Salt pre-treatment increased the activation energies of Douglas fir, which increased the

thermal decomposition stability. Similar to that observed for acid washing, base washing of

biomass suffers from similar drawbacks related to wastewater generation due to rinsing

requirements to remove residual ions, which restricts its large-scale applications.

6. POST-TREATMENTS FOR THE THERMOCHEMICAL CONVERSION OF BIOMASS

After thermochemical conversion, inorganics in biomass become volatile, carrying

chlorine, sulfur, alkali, and other harmful elements either in the gas or liquid products.100

Depending on the level of these inorganic species, posttreatment processes might be necessary to

reduce their potential impact on the downstream applications. In the context of gasification and

combustion, post-treatment techniques for remediating inorganic and organic gaseous

undesirable species have thus far been referenced as hot or warm gas cleanup. The application of

post-treatment application in pyrolysis is relatively new and emerged in the early 1990s, when

research suggested that biochar inorganics enhanced bio-oil polymerization during storage.28-29

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The following section discusses only post-treatment processes applicable to pyrolysis,

gasification, and combustion products in gaseous or liquid forms.

6.1 Gas product posttreatments Gas-phase processes, which have been evaluated to decrease inorganics and improve

product quality, employ physical methods, as well as catalysts and/or sorbents. In the context of

pyrolysis, hot gas filtration (HGF), as a physical post-treatment method, has been extensively

evaluated to explore its impact on inorganic associated with biochar, which provide nucleation

sites for polymerization or catalyze reactions.12, 29, 101-102 Hot vapor filtration was evaluated by

researchers at the U.S. National Renewable Laboratory (NREL) to assess the effect of biochar

filtration on bio-oil stability.101 They reported a significant viscosity reduction (by a factor of

≥10), as well as low alkali and alkaline-earth metals, iron, and overall total solid content

reduction when using ceramic candle filter elements. However, the same effect on viscosity was

not observed when sintered stainless steel candle filter elements were evaluated. Instead,

increasing the iron content in bio-oil filtered through the stainless steel elements upon

condensation, which suggested that elements were chemically attacked and reduced their

effectiveness by the corrosive bio-oil.29, 101 While sintered filters are the most common means of

HGF, a moving-bed granular filter was applied in HGF with noticeable ash reduction from 0.82

wt % in fresh bio-oil to 0.01 wt % after filtration in the best-case scenario.103 One adverse effect

of HGF is the resulting weight loss.101, 104 It was estimated that 10%−30% (by weight) is lost as a

result of HGF.101

In gasification and combustion, warm or hot cleanup have thus far been the primary

methods employed to remediate gas phase inorganics. Gas-phase cleanup of ammonia includes

selective catalytic oxidation or thermal catalytic decomposition.105 In both of these cases, the

catalytic reactor benefits from the high reaction temperature at the exit of the gasifier. However,

the catalyst must be tolerant to other contaminants, especially sulfur impurities (e.g., H2S, COS)

which deactivate catalysts after short operation period.106-107 Catalyst deactivation by sulfur

poisoning can be exacerbated when operating reactors at higher pressure.106 Common industrial

Ni-based reforming catalysts as well as other nickel catalyst formulations with Zn, Ce, Co, Mo,

Fe, and Ru are very effective in NH3 removal at 800−950 °C.106-109

Gas-phase sulfur species removal is achieved with the help of a sorbent, commonly a

metal oxide, through desulfurization reaction or physical adsorption. A wide range of studies

26

have explored and reported on various sorbents including CaO, CaCO3 and dolomite,110 zinc

ferrite promoted with V2O5 111 and various mixed metal oxides of La, Co, Zn, Fe, Cu.112-113 The

effective temperature varies widely, based on the sorbents, but generally ranges from 500 °C to

700 °C.112-114 Alkalimetal sorbents (e.g., Na2CO3, NaAlO2, or NaHCO3) have been shown to be

very effective in removing halides.115-116 These alkali-metal sorbents have a tendency to combine

with halides to form salts (NaCl, KCl, etc.) during thermochemical conversion. Similarly,

alkaline-earth metals (e.g., BaO, SrO, CaO, MgO) could be effective in the removal of halides,

based on thermodynamic modeling.12 In addition, inexpensive minerals (e.g., such as fly ash,

bentonite, kaoline, and bauxite) were reported to be effective for capturing trace metals during

biomass combustion.117 Besides sorbents, barriers filtration unit operations (cyclones, candle

filter, bag filters) after the gasifier have been shown to significantly reduced the concentration of

fine particules, and thus inorganics, in the gas stream.11

6.2 Liquid product posttreatments Upon cooling, inorganics in the pyrolysis vapors are condensed into the biooil. The

multiphase nature of freshly obtained bio-oil suggested that biochar, and thus its related

inorganic elements, will predominantly reside in the aqueous phase.118-119 Liquid bio-oil filtration

has been shown to effectively reduce the alkali and alkali-earth metal content.120 Bio-oil filtration

is physical challenging to achieve and will likely require pressure filtration, because of its high

viscosity and the complex interaction between char and bio-oil to form a gelatinous substrate that

rapidly clogs the filter.121 However, the impedance to filtration can be decreased by partially or

completely dissolving the biochar−bio-oil gel, using common solvents, such as methanol or

ethanol.121

6.3 Solid product posttreatments Biochar is a solid carbon-rich residue yielded from the thermochemical decomposition of

lignocellulosic biomass in the partial or total absence of oxygen.122 The solid char has a great

variety of applications.123 It can be used as an excellent fuel for cofiring in coal-fired power

stations,124 applied as a soil amendment,123 and mixed with bio-oil to produce a bioslurry fuel for

bioenergy plants.124 However, biochar may have high inorganic contents (alkali and alkaline

earth metals, in combination with other inorganic elements) that are undesirable in power plant

fuels.125 Thus, demineralization of biochar is of great importance. Two-step water leaching has

27

been shown to leach 27%−35% of K and Na from biochar for the first 30 min, with the effect of

leaching varying for biochar from different agricultural residues.125 Water leaching could also

release nearly all chlorine within a few minutes during biochar washes.126

7. CONCLUSIONS

Biomass, with the potential to be converted to power, liquid fuels, and chemicals through

thermochemical conversion, is a promising and attractive option for global energy resources.

Biomass can be converted to energy-dense intermediates through thermochemical conversion

technologies, including combustion, gasification, and pyrolysis. However, the inorganic content

(ash) of biomass has been known for some time have significant effects on the thermochemical

conversion process and create specific downstream hazards with diversified downstream

applications:

• During pyrolysis process, the inorganic contents can have significant catalytic effects and

change the thermal degradation rate, chemical pathway, and bio-oil yield.

• During combustion process, the inorganic contents can bring various technological

problems (agglomeration, corrosion, abrasion−erosion, slagging, fouling), environmental

risks, and health concerns.

• During gasification process, the inorganic contents create diversified downstream

hazards, including minor process inefficiencies, such as corrosion and pipe blockages, as

well as catastrophic failures, such as rapid and permanent deactivation of catalysts.

Economically friendly and effective remediation technology of inorganic contaminants

challenges the commercial deployment of large-scale biomass thermochemical conversion.

Pretreatment is the first and most important step in biomass processing to improve the efficiency

of biomass handling, processing, and conversion. Effective pre-treatment technologies exist to

remove inorganic contaminants to lower concentration limits:

• Mechanical sieving changes the ash content of biomass by varying biomass particle sizes.

• Washing biomass with water, acid, alkali, or salt has been shown to be effective in

removing inorganic contents, especially the alkali and alkaline-earth metals.

• Hot water extraction has been shown to be efficient in removing the majority of alkali

metals.

28

• Some other pre-treatments, such as steam explosion and hydrothermal carbonization,

have been shown to improve lignocellulosic biomass materials. However, their effects on

inorganics removal have not been investigated.

However, the main drawbacks of these pre-treatments are that they (i) reduce the overall

efficiency due to the need of further drying process of wet biomass after pre-treatment and (ii)

increase chemicals, facilities, and drying costs. As such, activities in this area should aim to

develop pre-treatment technologies that will improve efficiency and decrease cost.

Post-treatment technologies are utilized after the thermochemical conversion to meet the

strict levels of cleanup demands for the downstream applications. A great number of

technologies exist to purify the raw synthesis gas stream that is produced by the thermochemical

conversion of biomass.

8. ACKNOWLEDGMENTS

This research was supported by Southeastern Sun Grant Center and the U.S. Department

of Transportation, Research and Innovative Technology Administration, Grant No. DTO559- 07-

G-00050. S.C.C. wishes to acknowledge the Southeastern Partnership for Integrated Biomass

Supply Systems (IBSS), which is supported by AFRI No. 2011-68005-30410 from USDA NIFA.

29

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72. Lam, P. S.; Sokhansanj, S.; Bi, X.; Lim, C. J.; Melin, S., Energy input and quality of pellets made from steam-exploded Douglas fir (Pseudotsuga menziesii). Energy & Fuels 2011, 25 (4), 1521-1528. 73. Tooyserkani, Z.; Sokhansanj, S.; Bi, X.; Lim, J.; Lau, A.; Saddler, J.; Kumar, L.; Lam, P. S.; Melin, S., Steam treatment of four softwood species and bark to produce torrefied wood. Applied Energy 2013, 103, 514-521. 74. Wang, N.; Chen, H.-Z., Manufacture of dissolving pulps from cornstalk by novel method coupling steam explosion and mechanical carding fractionation. Bioresource technology 2013, 139, 59-65. 75. Kemppainen, K.; Inkinen, J.; Uusitalo, J.; Nakari-Setälä, T.; Siika-aho, M., Hot water extraction and steam explosion as pretreatments for ethanol production from spruce bark. Bioresource technology 2012, 117, 131-139. 76. Biswas, A. K.; Yang, W.; Blasiak, W., Steam pretreatment of Salix to upgrade biomass fuel for wood pellet production. Fuel processing technology 2011, 92 (9), 1711-1717. 77. Mosier, N.; Hendrickson, R.; Ho, N.; Sedlak, M.; Ladisch, M. R., Optimization of pH controlled liquid hot water pretreatment of corn stover. Bioresource Technology 2005, 96 (18), 1986-1993. 78. Edmunds, C. W.; Hamilton, C.; Kim, K.; Chmely, S. C.; Labbé, N., Using a chelating agent to generate low ash bioenergy feedstock. Biomass and Bioenergy 2017, 96, 12-18. 79. Mante, O. D.; Amidon, T. E.; Stipanovic, A.; Babu, S. P., Integration of biomass pretreatment with fast pyrolysis: An evaluation of electron beam (EB) irradiation and hot-water extraction (HWE). Journal of Analytical and Applied Pyrolysis 2014, 110, 44-54. 80. Baxter, L. L.; Miles, T. R.; Miles Jr, T. R.; Jenkins, B. M.; Milne, T.; Dayton, D.; Bryers, R. W.; Oden, L. L., The behavior of inorganic material in biomass-fired power boilers: field and laboratory experiences. Fuel Processing Technology 1998, 54 (1–3), 47-78. 81. Chang, S.; Zhao, Z.; Zheng, A.; Li, X.; Wang, X.; Huang, Z.; He, F.; Li, H., Effect of hydrothermal pretreatment on properties of bio-oil produced from fast pyrolysis of eucalyptus wood in a fluidized bed reactor. Bioresource Technology 2013, 138, 321-328. 82. Hoekman, S. K.; Broch, A.; Robbins, C., Hydrothermal Carbonization (HTC) of Lignocellulosic Biomass. Energy & Fuels 2011, 25 (4), 1802-1810. 83. Chen, W.-H.; Ye, S.-C.; Sheen, H.-K., Hydrothermal carbonization of sugarcane bagasse via wet torrefaction in association with microwave heating. Bioresource technology 2012, 118, 195-203. 84. Bach, Q.-V.; Tran, K.-Q.; Skreiberg, Ø.; Khalil, R. A.; Phan, A. N., Effects of wet torrefaction on reactivity and kinetics of wood under air combustion conditions. Fuel 2014, 137, 375-383. 85. Zhang, S.; Chen, T.; Li, W.; Dong, Q.; Xiong, Y., Physicochemical properties and combustion behavior of duckweed during wet torrefaction. Bioresource Technology 2016, 218, 1157-1162. 86. Jenkins, B.; Bakker, R.; Wei, J., On the properties of washed straw. Biomass and bioenergy 1996, 10 (4), 177-200. 87. Banks, S.; Nowakowski, D.; Bridgwater, A., Fast pyrolysis processing of surfactant washed Miscanthus. Fuel Processing Technology 2014, 128, 94-103. 88. Davidsson, K.; Korsgren, J.; Pettersson, J.; Jäglid, U., The effects of fuel washing techniques on alkali release from biomass. Fuel 2002, 81 (2), 137-142.

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89. Yu, C.; Thy, P.; Wang, L.; Anderson, S.; VanderGheynst, J.; Upadhyaya, S.; Jenkins, B., Influence of leaching pretreatment on fuel properties of biomass. Fuel Processing Technology 2014, 128, 43-53. 90. Lam, P. Y.; Lim, C. J.; Sokhansanj, S.; Lam, P. S.; Stephen, J. D.; Pribowo, A.; Mabee, W. E., Leaching characteristics of inorganic constituents from oil palm residues by water. Industrial & Engineering Chemistry Research 2014, 53 (29), 11822-11827. 91. Das, O.; Sarmah, A. K., Mechanism of waste biomass pyrolysis: Effect of physical and chemical pre-treatments. The Science of the total environment 2015, 537, 323-34. 92. Park, D.; Yun, Y.-S.; Park, J. M., Studies on hexavalent chromium biosorption by chemically-treated biomass of Ecklonia sp. Chemosphere 2005, 60 (10), 1356-1364. 93. Vamvuka, D.; Troulinos, S.; Kastanaki, E., The effect of mineral matter on the physical and chemical activation of low rank coal and biomass materials. Fuel 2006, 85 (12), 1763-1771. 94. Stefanidis, S. D.; Heracleous, E.; Patiaka, D. T.; Kalogiannis, K. G.; Michailof, C. M.; Lappas, A. A., Optimization of bio-oil yields by demineralization of low quality biomass. Biomass and Bioenergy 2015, 83, 105-115. 95. Mourant, D.; Wang, Z.; He, M.; Wang, X. S.; Garcia-Perez, M.; Ling, K.; Li, C.-Z., Mallee wood fast pyrolysis: Effects of alkali and alkaline earth metallic species on the yield and composition of bio-oil. Fuel 2011, 90 (9), 2915-2922. 96. Shi, L.; Yu, S.; Wang, F.-C.; Wang, J., Pyrolytic characteristics of rice straw and its constituents catalyzed by internal alkali and alkali earth metals. Fuel 2012, 96, 586-594. 97. Kazi, K. M. F.; Jollez, P.; Chornet, E., Preimpregnation: an important step for biomass refining processes. Biomass and Bioenergy 1998, 15 (2), 125-141. 98. Liaw, S. B.; Wu, H., Leaching characteristics of organic and inorganic matter from biomass by water: differences between batch and semi-continuous operations. Industrial & Engineering Chemistry Research 2013, 52 (11), 4280-4289. 99. Scott, D. S.; Paterson, L.; Piskorz, J.; Radlein, D., Pretreatment of poplar wood for fast pyrolysis: rate of cation removal. Journal of Analytical and Applied Pyrolysis 2001, 57 (2), 169-176. 100. Froment, K.; Defoort, F.; Bertrand, C.; Seiler, J.; Berjonneau, J.; Poirier, J., Thermodynamic equilibrium calculations of the volatilization and condensation of inorganics during wood gasification. Fuel 2013, 107, 269-281. 101. Baldwin, R. M.; Feik, C. J., Bio-oil Stabilization and Upgrading by Hot Gas Filtration. Energy & Fuels 2013, 27 (6), 3224-3238. 102. Case, P. A.; Wheeler, M. C.; DeSisto, W. J., Effect of Residence Time and Hot Gas Filtration on the Physical and Chemical Properties of Pyrolysis Oil. Energy & Fuels 2014, 28 (6), 3964-3969. 103. Paenpong, C.; Inthidech, S.; Pattiya, A., Effect of filter media size, mass flow rate and filtration stage number in a moving-bed granular filter on the yield and properties of bio-oil from fast pyrolysis of biomass. Bioresource Technology 2013, 139, 34-42. 104. Chen, T.; Wu, C.; Liu, R.; Fei, W.; Liu, S., Effect of hot vapor filtration on the characterization of bio-oil from rice husks with fast pyrolysis in a fluidized-bed reactor. Bioresource Technology 2011, 102 (10), 6178-6185. 105. Torres, W.; Pansare, S. S.; Goodwin, J. G., Hot Gas Removal of Tars, Ammonia, and Hydrogen Sulfide from Biomass Gasification Gas. Catalysis Reviews 2007, 49 (4), 407-456.

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106. Mojtahedi, W.; Ylitalo, M.; Maunula, T.; Abbasian, J., Catalytic decomposition of ammonia in fuel gas produced in pilot-scale pressurized fluidized-bed gasifier. Fuel Processing Technology 1995, 45 (3), 221-236. 107. Ozawa, Y.; Tochihara, Y., Catalytic decomposition of ammonia in simulated coal-derived gas over supported nickel catalysts. Catalysis today 2011, 164 (1), 528-532. 108. Simell, P.; Kurkela, E.; Ståhlberg, P.; Hepola, J., 1st World Conference Environmental Catalysis For a Better World and LifeCatalytic hot gas cleaning of gasification gas. Catalysis Today 1996, 27 (1), 55-62. 109. Park, J. J.; Park, C. G.; Jung, S. Y.; Lee, S. C.; Ragupathy, D.; Kim, J. C., A study on Zn-based catal-sorbents for the simultaneous removal of hydrogen sulfide and ammonia at high temperature. Research on Chemical Intermediates 2011, 37 (9), 1193-1202. 110. Yrjas, P.; Iisa, K.; Hupa, M., Limestone and dolomite as sulfur absorbents under pressurized gasification conditions. Fuel 1996, 75 (1), 89-95. 111. Akyurtlu, J. F.; Akyurtlu, A., Hot gas desulfurization with vanadium-promoted zinc ferrite sorbents. Gas Separation & Purification 1995, 9 (1), 17-25. 112. Cheah, S.; Parent, Y. O.; Jablonski, W. S.; Vinzant, T.; Olstad, J. L., Manganese and ceria sorbents for high temperature sulfur removal from biomass-derived syngas–the impact of steam on capacity and sorption mode. Fuel 2012, 97, 612-620. 113. Liu, B. S.; Wan, Z. Y.; Zhan, Y. P.; Au, C. T., Desulfurization of hot coal gas over high-surface-area LaMeOx/MCM-41 sorbents. Fuel 2012, 98, 95-102. 114. Jung, S. Y.; Lee, S. J.; Park, J. J.; Lee, S. C.; Jun, H. K.; Lee, T. J.; Ryu, C. K.; Kim, J. C., The simultaneous removal of hydrogen sulfide and ammonia over zinc-based dry sorbent supported on alumina. Separation and Purification Technology 2008, 63 (2), 297-302. 115. Ohtsuka, Y.; Tsubouchi, N.; Kikuchi, T.; Hashimoto, H., Recent progress in Japan on hot gas cleanup of hydrogen chloride, hydrogen sulfide and ammonia in coal-derived fuel gas. Powder Technology 2009, 190 (3), 340-347. 116. Duo, W.; Kirkby, N. F.; Seville, J. P. K.; Kiel, J. H. A.; Bos, A.; Den Uil, H., Chemical Reaction Engineering: From Fundamentals to Commercial Plants and ProductsKinetics of HCl reactions with calcium and sodium sorbents for IGCC fuel gas cleaning. Chemical Engineering Science 1996, 51 (11), 2541-2546. 117. Bläsing, M.; Müller, M., Investigation of the effect of alkali metal sorbents on the release and capture of trace elements during combustion of straw. Combustion and Flame 2013, 160 (12), 3015-3020. 118. Garcìa-Pérez, M.; Chaala, A.; Pakdel, H.; Kretschmer, D.; Rodrigue, D.; Roy, C., Multiphase Structure of Bio-oils. Energy & Fuels 2006, 20 (1), 364-375. 119. Fratini, E.; Bonini, M.; Oasmaa, A.; Solantausta, Y.; Teixeira, J.; Baglioni, P., SANS Analysis of the Microstructural Evolution during the Aging of Pyrolysis Oils from Biomass. Langmuir 2006, 22 (1), 306-312. 120. Kang, B.-S.; Lee, K. H.; Park, H. J.; Park, Y.-K.; Kim, J.-S., Fast pyrolysis of radiata pine in a bench scale plant with a fluidized bed: Influence of a char separation system and reaction conditions on the production of bio-oil. Journal of Analytical and Applied Pyrolysis 2006, 76 (1–2), 32-37. 121. Bridgwater, A. V., Review of fast pyrolysis of biomass and product upgrading. Biomass and bioenergy 2012, 38, 68-94.

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122. Sohi, S. P.; Krull, E.; Lopez-Capel, E.; Bol, R., Chapter 2 - A Review of Biochar and Its Use and Function in Soil. In Advances in Agronomy, Academic Press: 2010; Vol. Volume 105, pp 47-82. 123. Brewer, C. E.; Schmidt Rohr, K.; Satrio, J. A.; Brown, R. C., Characterization of biochar from fast pyrolysis and gasification systems. Environmental Progress & Sustainable Energy 2009, 28 (3), 386-396. 124. Wu, H.; Yu, Y.; Yip, K., Bioslurry as a fuel. 1. Viability of a bioslurry-based bioenergy supply chain for mallee biomass in Western Australia. Energy & Fuels 2010, 24 (10), 5652-5659. 125. DEMİRBAŞ, A., Demineralization of agricultural residues by water leaching. Energy sources 2003, 25 (7), 679-687. 126. Jensen, P. A.; Sander, B.; Dam-Johansen, K., Removal of K and Cl by leaching of straw char. Biomass and Bioenergy 2001, 20 (6), 447-457.

37

CHAPTER II HOT WATER EXTRACTION AS A PRETREATMENT FOR REDUCING

SYNGAS INORGANICS IMPURITIES – A PARAMETRIC INVESTIGATION ON SWITCHGRASS AND LOBLOLLY PINE BARK

38

Qiaoming Liua, Nicole Labbéb, Sushil Adhikaric, Stephen C. Chmelyb and Nourredine

Abdoulmouminea,b

aBiosystems Engineering and Soil Science Department, University of Tennessee bCenter for Renewable Carbon, University of Tennessee cBiosystems Engineering, Auburn University, Auburn, AL

This chapter entitled “Hot water extraction as a pretreatment for reducing syngas

inorganics impurities – A parametric investigation on switchgrass and loblolly pine bark”

with the co-authors of Qiaoming Liu, Nicole Labbé, Sushil Adhikari, Stephen C. Chmely, and

Nourredine Abdoulmoumine was submitted to the journal of Fuel on September 26th, 2017.

Qiaoming Liu conducted the experiment, performed the data analysis, and drafted the

manuscript. Dr. Labbé assisted in the supply of raw materials and chemical composition analysis

of samples. Dr. Adhikari participated in the characterization of hot water extraction products. Dr.

Chmely participated in the experiment design and data interpretation. Dr. Abdoulmoumine

designed the experiments and provided help in data analysis and manuscript writing. All authors

revised this manuscript approved the final version.

1. ABSTRACT

The effects of hot water extraction on the removal of inorganic impurities (N, S, Na, K,

Mg and Ca) in biomass that are detrimental to gasification were investigated on switchgrass and

loblolly pine bark. As hot water extraction severity increased from 13 to 141 h °C, the extraction

liquor pH decreased from 6.0 to 4.5 for switchgrass and 3.6 to 3.1 for pine bark, thus resulting in

20.7 to 69.6 % of ash reduction for switchgrass and 57.0 to 73.3 % for pine bark, respectively. In

addition, the nitrogen content which results in ammonia (NH3) formation was reduced by 9.3 to

22.9 % for switchgrass and 1.0 to 6.8 % for pine bark following increment of severity.

Furthermore, sulfur which leads to hydrogen sulfide (H2S) formation was reduced from 48.3 to

62.5 % and 5.6 to 17.3 % for switchgrass and pine bark, respectively.

39

The range of potassium, sodium, magnesium and calcium reductions were 94.9 - 98.8,

47.9 - 72.4, 58.7 - 83.5 and 8.5 - 13.0 for switchgrass and 50.8 - 67.5, 29.2 - 60.1, 9.7 - 50.8 and

3.3 - 33.0 % for pine bark. Finally, statistical analysis was carried out on the statistical

significance of the extraction temperature and time as well as their interaction on the removal of

inorganic impurities. The extraction temperature, time, and the interaction differed in their effect

on liquor pH, ash reduction, mass loss, and reduction of individual inorganics.

2. INTRODUCTION

Energy and fuel produced from renewable biomass is a promising research area today

because of the reduction of greenhouse gases emission from fossil fuels and the environmental

sustainability.1 Notably, the thermochemical conversion of lignocellulosic biomass to biofuel and

energy via gasification process is attractive as it has the potential to produce gasoline through

methanol synthesis, mixed alcohols, gasoline and diesel through Fischer-Tropsch (FT) synthesis,

as well as energy through internal combustion engine, steam and gas turbines.2 Currently, the

presence of contaminants in biomass derived syngas is considered the primary hurdle for the

commercialization of syngas.3 Among the gaseous contaminants, inorganics have been

associated with catalyst poisoning, corrosion, agglomeration, and undesirable emissions during

gasification.4-5 In particular, nitrogen, sulfur, and alkali and alkaline earth metals present in

biomass result in ammonia (NH3), hydrogen sulfide (H2S), and trace metal vapors (K, Na, Ca,

and Mg), respectively at concentrations ranging from few parts per million (ppm) to few

thousands depending on the species, operating conditions, and biomass properties.6-9 Nitrogen in

biomass is mainly linking with proteins in living organic tissues.10-11 During gasification, it is

liberated as predominantly as NH3, hydrogen cyanide (HCN), molecular nitrogen (N2), heavy

tars, with a smaller part retained in solid char.12 Sulfur (S) presents in both inorganic and organic

forms in biomass. The organic forms of S are covalently bound to proteins and amino acids,

while the inorganic forms can exist as sulfate (SO42−) and sulfite (SO3

2−).11 During gasification,

sulfur in the biomass is primarily converted to hydrogen sulfide (H2S), which causes equipment

corrosion and catalyst deactivation in downstream applications.13-15 The alkali metals (Na and K)

in the biomass mainly remained in the form of ionic salts that were not metabolized by the

plant.16 Within the cell structure of biomass, alkali metals often exist in free ion form (Na+ and

K+) with counter ions in the fluid matter, such as chloride (Cl−) or malate (C4H4O52−).17 They can

40

also present in solid salt structures settled on the cell wall of biomass.17 A small amount of alkali

metals present in the organic matrix when attached to functional groups as carboxylates and

phenoxides.18 For in situ gasification, alkali metals can easily poison catalysts; they also pose

challenge to ex situ conditioning of syngas or downstream catalytic applications.4, 19 The

existence of alkali metals can cause corrosion and fouling in downstream processes as well.20

Alkaline-earth metals (Mg and Ca) do not usually exist in free ionic form, which is different

from the chemical status of alkali metals.11 Mg and Ca have a tendency to form complexes with

organic counterio18 These species are regarded as the major inorganic syngas contaminants and

their concentrations are strictly restricted depending of the intended syngas application.21 In fuel

synthesis applications through FT and methanol syntheses, the tolerable limit of nitrogen and

sulfur contaminants are 20 and 0.01 ppm, respectively. As for gas turbine based power

generation applications, concentrations below 50 and 0.02 ppm are desired for nitrogen and

sulfur contaminants, respectively.19 As such, contaminant removal efficiencies greater than 99 %

are typically required to ensure that inorganic contaminants in biomass derived syngas are below

these limits.

Traditionally, syngas inorganic contaminant reduction has been achieved through

downstream gas cleanup.13, 19 While effective commercial gas cleanup technologies exist, recent

technoeconomic analyses show that gas cleanup accounted for the highest share of the total

capital investment in gasification related applications.22 In recent years, pretreatment techniques

have been explored to reduce inorganic content and improve the quality of biomass prior to

pyrolysis conversion.23-30 However, the potential beneficial impact of pretreatment techniques on

reducing inorganics of concerned (N, S and metals) in gasification have drawn less attention.31

The pretreatment methods can be very different for pyrolysis and gasification due to the

downstream processes requirements for their dissimilar conversion products (bio-oil and syngas,

respectively). Consequently, this study aims to explore the impact of hot water extraction (HWE)

as an inorganic reduction pretreatment on biomass nitrogen, sulfur, and select metals (Na, K, Mg

and Ca).

41

3. MATERIALS AND METHODS

3.1 Biomass preparation and characterization Biomass types investigated in this study were switchgrass (Panicum virgatum) obtained

through the University of Tennessee Biofuels Initiative (UTBI) and loblolly pine (Pinus taeda)

bark obtained from Auburn University. The samples were grounded and sieved to particle size

below 40 mesh (425 µm). Proximate analyses of moisture, ash, volatile matter and fixed carbon

were performed on each biomass sample according to standard methods ASTM E871-

82(2013)32, ASTM E1755-01(2015)33 and ASTM E872-82(2013)34, respectively. Ultimate

analysis of C, H, N, and O were conducted using a Perkin Elmer CHN analyzer. Fixed carbon

was determined by difference between the volatile matter and ash values. The inorganic

elemental composition of each biomass was determined by inductively coupled plasma optical

emission spectroscopy (ICP-OES) with an Optima 7300 DV spectrometer (Perkin Elmer). Prior

to ICP-OES analysis, approximately 0.5 g of each biomass sample was microwave digested

using 4 mL of concentrated nitric acid (HNO3, 70 % w/w), 3 mL of concentrated hydrochloric

acid (HCl), and 0.2 mL of hydrofluoric acid HF, 51 %) at temperatures between 160 and 210 °C

for 20 min.35 After digestion, the solution was diluted to 50 mL with Milli-Q H20 and filtered

with 0.45µm PTFE filters prior to ICP-OES analysis. All compositional and elemental analyses

were performed in triplicate.

3.2 Hot water extraction The HWE extraction vessel consists of a 200-mL heavy-wall round bottom flask with a

screw cap fitted with ¼ in. compression fittings for a thermocouple and pressure gauge ports

(Figure 2). The extraction temperature was monitored and controlled by a PID (proportional–

summation–difference) temperature controller with continuous data logging. In this experiment,

the extraction severity (16 to 141 h °C for switchgrass and 13 to 128 h °C for pine bark,

respectively) was determined by computing the time integral of the experimentally measured

temperature recorded by a PID controller using a Matlab script. This approach enabled to capture

the contribution of the overall extraction of ramping from room to extraction set point

temperature as well as to use natural temperature fluctuations observed in experiments (Figure

9).

42

Figure 2 Schematic representation of the hot water extraction experimental setup

For each HWE experiment, approximately 5 g of each biomass sample were thoroughly

mixed with deionized (D.I.) water at 1:20 biomass to water ratio, on weight basis. This ratio was

chosen to ensure that (i) there is ample liquor for further analysis and (ii) that the thermocouple

was fully submerged even during vigorous agitation which led to the formation of a vortex in the

slurry. After reaching the appropriate extraction temperature (60, 80, 100, 120 and 140 °C), the

mixture was held there for a desired extraction time (15, 30 and 45 min). The reactor was then

allowed to cool, and the slurry was filtered to recover the undiluted filtrate for pH measurement.

The residual extracted biomass was thoroughly rinsed with 100 mL of D.I. water to remove any

deposited inorganic elements on the surface and dried at 80 °C overnight. All HWE extraction

and compositional and elemental analyses were performed in triplicate.

3.3 Characterization of hot water extraction products The pH, total dissolved solids (TDS), inorganic elemental composition, and total organic

nitrogen (TN) were measured on the undiluted liquor collected after filtration of the HWE slurry.

ICP-OES analysis of the liquor followed the same approach used in determining biomass

inorganic elemental composition and described in 2.1. TN analysis was performed on a TOC-L

analyzer attached with TNM-L unit (Shimadzu Corp., Japan) after filtration of liquor samples

using 0.2 μm filter to remove the suspended particles. The filtrates were subsequently diluted by

a dilution factor (DF) of 3-7 depending on the extraction severity and kept in an auto-sampler for

measurement. The total mass dissolved in the liquor was determined gravimetrically by drying

43

an aliquot at 60 °C until weight loss ceased. On residual extracted solid, the compositional

changes due to HWE were monitored through proximate and ultimate analyses according to

ASTM standards previously described in 2.1. All product analyses were performed in triplicate.

3.4 Statistical analyses The effects of temperature (60, 80, 100, 120 and 140 °C) and time (15, 30 and 45 min) on the

responses (pH, mass loss, total ash and individual inorganic element - N, S, Na, K, Mg and Ca),

expressed on a dry basis, were investigated by a two-factor analysis of variance of an

unbalanced, complete factorial design with three observations per treatment at the 0.05

significance level. If necessary, Tukey-Kramer HSD (honest significant difference) was used for

multiple comparisons.36 All statistical analyses were performed using the statistical analysis

software of JMP.

4. RESULTS AND DISCUSSION

4.1 Proximate and ultimate analysis of raw switchgrass and loblolly pine bark samples Table 8 shows proximate and ultimate results for the switchgrass and pine bark raw

samples representing herbaceous and woody biomass which differ in structure and inorganic

components. Compared to raw loblolly pine bark samples, switchgrass has more volatile matter

(VM) and ash content, as well as less fixed carbon (FC) content. Also, switchgrass has more N,

S, alkali metal (Na and K), and alkaline earth metal (Mg and Ca) content when compared to

loblolly pine bark. The proximate and ultimate analysis results of switchgrass and pine bark raw

samples are consistent with values reported by others.37-42

Besides differences in proximate and ultimate analysis components, switchgrass and pine

bark also differ in their structural components (i.e. cellulose, hemicellulose, and lignin). As an

herbaceous feedstock, switchgrass has less lignin as woody species like loblolly pine.

Switchgrass contains 38-40 % of cellulose, 28-39 % of hemicellulose, and 18-26 % of lignin,

whereas pine bark contains 17-32 % of cellulose, 17-19 % of hemicellulose, and 33-34 % of

lignin. 42-46.

44

Table 8 Proximate and ultimate analyses of raw switchgrass and loblolly pine bark Mean (SD) Switchgrass Pine bark

Moisture, wt. % wet basis 6.34 (0.28) 10.16 (0.42) Proximate analysis, wt. % dry basis Volatile matter 81.51 (0.32) 70.11 (0.19) Fixed carbona 14.90 (0.33) 27.62 (0.32) Ash 3.59 (0.23) 2.27 (0.19) Ultimate analysis wt. % dry basis C 44.82 (0.4) 52.45 (1.51) H 5.77 (0.21) 5.91 (0.04) Oa 47.44 (0.17) 40.50 (1.55) N 0.4 (0.03) 0.35(0.04) ppm dry basis Na 141 (13) 24 (1) K 4398 (165) 1166 (19) Mg 1644 (50) 575 (29) Ca 2005 (17) 1835 (62) S 563 (25) 352 (15) Al 35 (4) 869 (25) Fe 39 (0.3) 1169 (162) Mn 60 (1) 78 (1) P 1117 (44) 197 (7) Si 5123 (313) 1268 (28) Zn 20 (1) BDL

aFixed carbon and oxygen were determined by difference; SD stands for standard deviation; BDL stands for below detection limit.

45

4.2 Effect of hot water extraction The effects of hot water extraction on liquor pH, ash content reduction, and mass loss of

switchgrass and pine bark samples are shown as three-dimensional (3D) surface plots in

Figure 3.

The extraction liquor pH decreased from 6.0 to 4.5 for switchgrass and 3.6 to 3.1 for pine

bark following the increase of temperature as a result of extractives separated from biomass

including acetic, uronic and phenolic acids47. The rate of pH reduction increased rapidly during

switchgrass extraction when temperature increased from 100 to 140 C due to increasing

hydrolysis and extraction rate of acids with higher temperature.47-48 As pH decreased, the total

ash reduction increased from 20.7 to 69.6 % for switchgrass and from 57.0 to 73.3 % for pine

bark, respectively. Similar to the trend observed for switchgrass liquor pH, the rate of ash

reduction increased after 100 °C, indicating that the liquor pH is correlated to ash reduction of

switchgrass as previously reported by others.49-50 Furthermore, as liquor pH decreased during the

extraction of both feedstocks, the mass loss also increased from 5.1 to 15.3 % and 2.5 to 15.3 %

(dry basis) for switchgrass and pine bark, respectively.

Figure 3 Effect of temperature and time of hot water extraction on pH (a), ash reduction

(b), and mass loss (c) for switchgrass, and effect of temperature and time of hot water extraction on pH (d), ash reduction (e), and mass loss (f) for pine bark. Red dots represent response means for each condition and surface plot represents best fit of experimental data

46

Of the two main factors (temperature and time), the statistical analysis of variance

indicated that temperature, but not time or the interaction of temperature and time, had a

statistically significant effect on liquor pH [F(4,30) = 210.68; P < 0.0001] and ash reduction for

switchgrass [F(4,30) = 35.87; P < 0.0001]. In contrast, temperature [F(4,30) = 36.17; P <

0.0001], time [F(2,30) = 4.57; P = 0.0185], and their interaction [F(8,30) = 0.99; P = 0.0025] all

had statistically significant effects on the mass loss for switchgrass. For pine bark, temperature

[F(4,30) = 178.08; P < 0.0001], time [F(2,30) = 5.66; P = 0.0082], and their interaction [F(8,30)

= 2.42; P = 0.0377], had statistically significant effects on its liquor pH. The statistical effects of

temperature [F(4,30) = 853.63; P < 0.0001], time [F(2,30) = 25.43; P < 0.0001], and their

interaction [F(8,30) = 3.79; P = 0.0035] were also significant on the extraction mass loss.

Additionally, temperature [F(4,30) = 1.05; P < 0.0001] but not time [F(2,30) = 2.99; P = 0.0655]

or their interaction [F(8,30) = 0.28; P = 0.0486], had statistically significant effect on ash

reduction of pine bark. Compared to switchgrass, only modest reduction in ash content was

achieved for pine bark as temperature increased. Several reasons might explain this insensitivity

to temperature and time on ash reduction for pine bark. Pine bark contains more lignin (water

insoluble) than switchgrass in which most of the structural ash, the physiological-bound ash in

biomass, is located.42, 51-52 This implies that less structural carbohydrates will be hydrolyzed, thus

making physiological bound ash less accessible.52

The extraction severities varied from 16 to 141 h C for switchgrass and 13 to 128 h C

for pine bark based on the time and temperature (See Tables 9 and 10 in the supplemental

materials). The effect of hot water extraction severity is illustrated in Figure 4. Figures 4a and 4b

show the relation between extraction severity and liquor pH for switchgrass and pine bark,

respectively. As the severity is increased, liquor pH is decreased with a noticeably lower

reduction in pH for bark. The lower pH of pine bark liquor is primarily attributed to its higher

content of acidic extractives such as acetic, resin, and fatty acids.53 In parallel, ash reduction

increased with severity as the acidic liquor enhanced the solubility of ash constituents (Figures

4b and 4e). In contrast to switchgrass, only a moderate increase in ash reduction was observed as

severity increased for pine bark. However, relatively high ash reduction (57.0 %) was achieved

at lower severities due to the relatively low liquor pH that was achieved at the beginning of the

extraction. Our findings are consistent with previous reports where liquor pH decreased with

severity and induced ash reduction of sugar maple and switchgrass.49-50 The hydrolysis of acidic

47

moieties from structural and extraction of extractives as well as the removal of ash is followed by

a decrease in mass, as illustrated in figure 4c and 4f, which increased as the extraction severity

increased. The mass loss occurred due to the loss of carbon, nitrogen, sulfur, and trace metals

during hot water extraction. Based on total organic carbon (TOC) analysis of the liquor, we

observed that as severity increased from 16 to 141 h °C for switchgrass and 13 to 128 h °C for

pine bark, the total carbon loss raised from 3.7 to 10.5 wt. % for switchgrass on a dry basis and

from 1.9 to 13.3 wt % for pine bark on a dry basis, respectively. The total carbon loss during the

extraction can come from the reduction of extractives (acetic acids, phenolic acids, aldehydes,

dicarboxylic acids, resin, and fatty acids), xylose, mannose, glucose, arabinose, and galactose

from the biomass.25, 53 Studies have shown feasible approaches to utilized the listed sugars from

hot water extraction, including biochemical production of ethanol, lactic acid, and butanol

through fermentation, as well as production of health food additives.54-57

Figure 4 Effect of hot water extraction severity on pH (a and d), ash content reduction (b and e), and mass loss (c and f) for switchgrass (above) and pine bark (below), respectively

4.2.1 Effect on nitrogen reduction and its impact on nitrogen contaminants Figure 5 shows the effect of hot water extraction severity on reducing nitrogen content of

switchgrass and pine bark, respectively. Biomass nitrogen content was reduced by 9.3 to 22.9 %

for switchgrass and 1.0 to 6.8 % for pine bark, respectively as severity increased from 16 to 141

h °C for switchgrass and 13 to 128 h °C for pine bark. The effect of HWE on pine bark is not as

48

effective as on switchgrass, which can be due to that pine bark has more lignin components, the

physical barriers to protect biomass from extraction, compared to switchgrass. Statistical analysis

of variance indicated that, of the two main factors (temperature and time) as well as the

interaction of temperature and time, only temperature had statistical significance on the reduction

of nitrogen content for switchgrass [F(4,30) = 9.87; P < 0.0001]; whereas for pine bark,

temperature [F(4,30) = 151.05; P < 0.0001], time [F(2,30) = 8.28; P = 0.0017], and the

interaction [F(8,30) = 2.77; P < 0.0233] all exhibited statistical significance on the reduction of

nitrogen content. The reduction in switchgrass and pine bark’s nitrogen content will

proportionally reduce ammonia concentration from 2400 to 1850 ppm and 2100 to 1957 ppm in

syngas, respectively based on 60 % N-fuel to NH3 conversion rate reported by Van der Drift and

coworkers.12

Figure 5 The effect of HWE severity on nitrogen (N) content reduction for switchgrass (a) and pine bark (b )

4.2.2 Effect on sulfur reduction and its impact on sulfur contaminants Figure 6 represents the effect of hot water extraction severity on reducing sulfur content

of switchgrass and pine bark, respectively. As severity increased from 16 to 141 h °C for

switchgrass and 13 to 128 h °C for pine bark, biomass sulfur content of switchgrass and pine

bark was reduced by 48.3 to 62.5 % and 5.6 to 17.3 %, respectively. The lower amount of sulfur

reduction in pine bark implied the relatively larger amount of organic sulfur existing in the

feedstock which is harder to be extracted compared to the inorganic form sulfur. Of the two main

factors (temperature and time) as well as the interaction of temperature and time, the statistical

49

analysis of variance showed that, for switchgrass, only temperature had statistical significance on

the reduction of sulfur content [F(4,30) = 21.05; P < 0.0001]. However, for pine bark,

temperature [F(4,30) = 1539.11; P < 0.0001], time [F(2,30) = 37.58; P < 0.0001], and the

interaction [F(8,30) = 5.96; P = 0.0001] all showed statistically significant effect on the reduction

of sulfur content. Based on sulfur conversion to H2S reported by Aljboura and Kawamotob58, we

predict that H2S concentration will be reduced from 552 to 213 ppm for switchgrass and 345 to

285 ppm for pine bark.

Figure 6 The effect of HWE severity on S content reduction for switchgrass (a) and pine bark (b)

4.2.3 Effect on alkali metal reduction and its impact on syngas metal contaminants Figure 7 shows the effect of hot water extraction severity on reducing K and Na content

for switchgrass and pine bark, respectively. The K removal ranges from 94.9 to 98.8 % for

switchgrass, which indicate K in switchgrass can be easily extracted, and from 50.8 to 67.5 % for

pine bark. The reduction of Na ranges from 47.9 to 72.4 % for switchgrass, and from 29.2 to

60.1 % for pine bark. With increasing severity, higher reduction of Na in both switchgrass and

pine bark is achieved. To achieve a higher reduction of K in pine bark, higher severity is required

for pine bark samples. The statistical analysis of variance indicated that, of the two main factors

(temperature and time) as well as the interaction of temperature and time, only temperature had

statistical significance on the reduction of K content for both switchgrass [F(4,30) = 6.05; P =

0.0011] and pine bark [F(4,30) = 4.58; P = 0.0065]. Moreover, only temperature was statistically

significant on the reduction of Na content for switchgrass [F(4,30) = 4.29; P = 0.0073].

50

However, both temperature [F(4,30) = 2.91; P = 0.0461] and time [F(2,30) = 4.29; P = 0.0274]

showed statistical significance on the reduction of Na content for pine bark.

Figure 7 The effect of HWE severity on alkali metals reduction for switchgrass (a) and pine bark (b)

During gasification, the conversion rate of alkali metal into gas phase can be 12–34%.59 It

can be predicted that the release of gas phase K being reduced from 1495 to 18 ppm (with 34 %

K conversion rate), and gas phase Na being reduced from 48 to 13 ppm (with 34 % Na

conversion rate) for switchgrass. For pine bark, the release of gas phase K can be reduced from

396 to 129 ppm (with 34 % K conversion rate), and gas phase Na can be reduced from 8 to 3

ppm (with 34 % Na conversion rate). Due to the fairly large amount of free ionic form existing in

biomass, alkali metals are relatively easy to be extracted.

4.2.4 Effect on alkaline earth metals reduction and their impact on syngas metal contaminants Figure 8 shows the effect of hot water extraction severity on reducing Mg and Ca content

for switchgrass and pine bark, respectively. The reduction of Mg ranges from 58.7 to 83.5 % for

switchgrass, and from 9.7 to 50.8 % for pine bark. The increase of HWE severity can further

enhance the reduction of Mg. However, the effect of HWE severity did not have significant

impact on the reduction of Ca for switchgrass, with 13.0 % of reduction, which was different

from pine bark, with 3.3 to 33.0 % reduction of Ca following increase of HWE severity. The

difficulty in extraction of Ca can due to the fact that Ca in biomass is able to effectively crosslink

lignin molecules due to its high affinity for lignin.60 It can also be a result of poor solubility of

the Ca in the complexes form. Of the two main factors (temperature and time) as well as the

51

interaction of temperature and time, the statistical analysis of variance showed that, for both

switchgrass and pine bark, temperature (switchgrass: [F(4,30) = 123.84; P < 0.0001], pine bark:

[F(4,30) = 1410.83; P < 0.0001]), time (switchgrass: [F(2,30) = 13.90; P < 0.0001], pine bark:

[F(2,30) = 43.25; P < 0.0001]), and their interaction (switchgrass: [F(8,30) = 3.55; P = 0.0053],

pine bark: [F(8,30) = 3.01; P = 0.0132]) all had statistical significance on the reduction of Mg

content. Also, temperature (switchgrass: [F(4,30) = 15.16; P < 0.0001], pine bark: [F(4,30) =

2435.50; P < 0.0001]), time (switchgrass: [F(2,30) = 5.50; P = 0.0092], pine bark: [F(2,30) =

91.01; P < 0.0001]), and the interaction (switchgrass: [F(8,30) = 4.02; P = 0.0024], pine bark:

[F(8,30) = 7.15; P < 0.0001]) all showed statistically significant effect on the reduction of Ca

content for switchgrass and pine bark, respectively.

Study reported the conversion rate of alkaline earth metal into gas phase can be 12–16 %

during gasification.59 The existence of alkaline-earth metals in syngas can cause catalyst

deactivation and are detrimental to the downstream processes. It can be predicted that the release

of gas phase Mg being reduced from 263 to 43 ppm (with 16 % Mg conversion rate), and gas

phase Ca being reduced from 321 to 279 ppm (with 16 % Ca conversion rate) for switchgrass.

For pine bark, the release of gas phase Mg can be reduced from 92 to 45 ppm (with 16 % Mg

conversion rate), and gas phase Ca can be reduced from 294 to 197 ppm (with 16 % Ca

conversion rate).

Figure 8 The effect of HWE severity on alkaline-earth metals reduction for switchgrass (a) and pine bark (b)

52

5. CONCLUSIONS

In this study, we present the findings of a parametric investigation on the effect of hot

water extraction on the removal of switchgrass and pine bark nitrogen, sulfur and select metals

(Na, K, Mg and Ca) that lead to the formation of ammonia, hydrogen sulfide and trace metal

contaminants in syngas. Our results revealed that this pretreatment can remove up to 23 % of

nitrogen, 63 % of sulfur, 72% of sodium, 99 % of potassium, 83 % of magnesium, and 13 % of

calcium for switchgrass over the range of conditions investigated. In the case of pine bark, it

resulted in the reduction of up to 7 % of nitrogen, 17 % of sulfur, 60 % of sodium, 67 % of

potassium, 51 % of magnesium, and 34 % of calcium. These reductions correspond to the

following equivalent reduction in syngas contaminants for switchgrass and pine bark

respectively: 2400 to 1850 ppm and 2100 to 1957 ppm of NH3, 552 to 213 ppm and 345 to 285

ppm of H2S, 1495 to 18 ppm and 396 to 129 ppm of K, 48 to 13 ppm and 8 to 3 ppm of Na, 263

to 43 ppm and 92 to 45 ppm of Mg, as well as 321 to 279 ppm and 294 to 197 ppm of Ca. Within

the boundary of the experimental conditions investigated, statistical analysis of variance

(ANOVA) indicated that, for switchgrass, only temperature had a statistically significant effect

on ash reduction as well as on N, S, K, and Na removal, whereas both temperature and time had

a statistically significant effect on the removal of Mg and Ca for switchgrass. Furthermore, for

pine bark, only temperature had a statistically significant effect on ash reduction as well as on the

removal of K, while both temperature and time had a statistically significant effect on the

removal of N, S, Na, Mg, and Ca.

This work shows the benefits of hot water extraction as a pretreatment for inorganics

removal. Compared to other commonly used pretreatment reagents (sulfuric acid, nitric acid,

ethylenediaminetetraacetic acid, and sodium hydroxide), hot water extraction avoids introducing

inorganics into biomass which require additional washing (S in sulfuric acid, N in nitric acid and

ethylenediaminetetraacetic acid, as well as Na in sodium hydroxide), reduces capital cost, and is

environmental friendly. However, further post-treatment is needed to achieve syngas cleanliness

requirement for downstream conversion technologies.

53

6. ACKNOWLEDGMENTS

This research was supported by Southeastern Sun Grant Center and the US Department

of Transportation, Research and Innovative Technology Administration, Grant No. DTO559-07-

G-00050.

54

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8. APPENDIX

8.1 Hot water extraction experimental conditions and severities

Table 9 Summary of hot water extraction experimental conditions and severities for switchgrass

Conditions #1 #2 #3 #4 #5 Temperature, ° C 60 80 100 120 140 Time, min 15 15 15 15 15 Severity, h ° C 16 25 37 65 86 Conditions #6 #7 #8 #9 #10 Temperature, ° C 60 80 100 120 140 Time, min 30 30 30 30 30 Severity, h ° C 22 38 55 75 100 Conditions #11 #12 #13 #14 #15 Temperature, ° C 60 80 100 120 140 Time, min 45 45 45 45 45 Severity, h ° C 33 50 78 102 141

Table 10 Summary of hot water extraction experimental conditions and severities for pine

bark

Conditions #1 #2 #3 #4 #5 Temperature, ° C 60 80 100 120 140 Time, min 15 15 15 15 15 Severity, h ° C 13 21 32 55 68 Conditions #6 #7 #8 #9 #10 Temperature, ° C 60 80 100 120 140 Time, min 30 30 30 30 30 Severity, h ° C 23 35 51 80 97 Conditions #11 #12 #13 #14 #15 Temperature, ° C 60 80 100 120 140 Time, min 45 45 45 45 45 Severity, h ° C 33 49 69 95 128

59

8.2 Summary of two-way analysis of variance results

Table 11 Summary of two-way analysis of variance results for switchgrass and pine bark

Switchgrass Pine bark Hydrolysate pH

Temperature Time Interaction Temperature Time Interaction DF 4 2 8 4 2 8 Error 30 30 30 30 30 30 F ratio 210.68 1.24 1.99 178.08 5.66 2.42 P < 0.0001 0.3031 0.0829 < 0.0001 0.0082 0.0377

Ash reduction DF 4 2 8 4 2 8 Error 30 30 30 30 30 30 F ratio 35.87 1.33 2.17 1.05 2.99 0.28 P < 0.0001 0.2793 0.059 < 0.0001 0.0655 0.0486

Mass loss DF 4 2 8 4 2 8 Error 30 30 30 30 30 30 F ratio 36.17 4.57 0.99 853.63 25.43 3.79 P < 0.0001 0.0185 0.0025 < 0.0001 < 0.0001 0.0035

N DF 4 2 8 4 2 8 Error 30 30 30 30 30 30 F ratio 9.87 0.07 0.48 151.05 8.28 2.77 P < 0.0001 0.9329 0.8606 < 0.0001 0.0017 0.0233

S DF 4 2 8 4 2 8 Error 30 30 30 30 30 30 F ratio 21.05 2 1.45 1539.11 37.58 5.96 P < 0.0001 0.1536 0.2181 < 0.0001 < 0.0001 0.0001

K DF 4 2 8 4 2 8 Error 30 30 30 30 30 30 F ratio 6.05 2.19 1.5 4.58 1.03 1.03 P 0.0011 0.1299 0.1977 0.0065 0.3723 0.4434

Na DF 4 2 8 4 2 8 Error 30 30 30 30 30 30 F ratio 4.29 3.05 0.95 2.91 4.29 1.76 P 0.0073 0.0621 0.4899 0.0461 0.0274 0.1423

60

Table 11 Continued Switchgrass Pine bark

Mg Temperature Time Interaction Temperature Time Interaction DF 4 2 8 4 2 8 Error 30 30 30 30 30 30 F ratio 123.84 13.9 3.55 1410.83 43.25 3.01 P < 0.0001 < 0.0001 0.0053 < 0.0001 < 0.0001 0.0132

Ca DF 4 2 8 4 2 8 Error 30 30 30 30 30 30 F ratio 15.16 5.5 4.02 2435.5 91.01 7.15 P < 0.0001 0.0092 0.0024 < 0.0001 < 0.0001 < 0.0001

8.3 Illustration of extraction severity

Figure 9 Illustration of the area under the curve approach used to calculate severity of

HWE

61

CHAPTER III SYNTHESIS AND EVALUATION OF SORBENTS FOR REDUCING THE

CONCENTRATIONS OF HYDROGEN CHLORIDE IN SYNGAS

62

Qiaoming Liua, Stephen C. Chmelyb and Nourredine Abdoulmouminea,b


This chapter entitled “Synthesis and evaluation of sorbents for reducing the

concentrations of hydrogen chloride in syngas” with the co-authors of Qiaoming Liu, Stephen

C. Chmely, and Nourredine Abdoulmoumine is in preparation for submission to the journal of

Applied Catalysis A: General. Qiaoming Liu designed and performed the experiment, conducted

the data analysis, and drafted the manuscript. Dr. Chmely participated in the experiment design,

assisted with sorbents preparation, and data interpretation. Dr. Abdoulmoumine assisted in the

experiment design, provided help in sorbent analysis and manuscript writing.

1. ABSTRACT

The synthesis of NaMgAl-LDH was achieved by a spontaneous self-assembly method,

calcined at 700 °C, and evaluated along with three commercial sorbents (Na2CO3, NaAlO2, and

commercial LDH) as hot gas cleanup sorbents for HCl sorption in a fixed bed reactor at 400 °C

to 600 °C. It has been shown that all sorbents were thermally stable during the hot gas cleanup

temperature range between 300 °C to 700 °C. During fixed bed experiment, calcined LDH

exhibited great effectiveness in capture of HCl at 400 °C to 600 °C with more than 14 h of

breakthrough time. The better performance of calcined LDH compared to calcined commercial

LDH supported the enhancement of incorporation of Na in the LDH framework for HCl

sorption. The Na-based sorbents showed various effectiveness on HCl removal with comparison

of breakthrough time: calcined LDH > calcined NaAlO2 > calcined Na2CO3 at 400 °C; calcined

LDH = calcined NaAlO2 > calcined Na2CO3 at 500 °C; and calcined Na2CO3 = calcined NaAlO2

= calcined LDH at 600 °C.

63

2. INTRODUCTION

During gasification, biomass is converted into raw syngas and deleterious organic (tars)

and inorganic impurities. While treatment techniques enable removal of most inorganic

contaminants in biomass, they are not unable to achieve removal levels necessary to avoid

downstream challenges.1-14 Syngas cleanup strategies are therefore of great importance to get rid

of residual inorganic contaminants after the gasification stage. The removal of gas phase

inorganics is crucial because they create specific downstream hazards such as equipment

corrosion and rapid and permanent deactivation of catalysts in downstream processes.15-17 Over

the years, much research effort has been devoted to cleaning biomass derived syngas.15 The three

types of gas cleaning processes commonly used are cold, intermediate, and hot temperature gas

cleanup methods and can be classified according to their operational temperature of the cleanup

reactors.15, 17 The cold gas cleanup approach, which is most commonly used, requires scrubbing

syngas at room temperature (~25 °C) through a solvent (commonly water) to absorb inorganic

impurities such as ammonia (NH3), hydrogen chloride (HCl) and hydrogen sulfide (H2S). The

main drawback of cold gas cleanup is the loss in efficiency during the process due to syngas

cooling. Warm gas cleanup requires moderate syngas cooling to induce inorganic condensation.

It can also involve the usage of sorbents such as activated carbon and silica for adsorbing

inorganic constituents.17 Nevertheless, warm gas cleanup leads to loss of efficiency due to

cooling and uncontrolled deposition of inorganic elements on surfaces which lead to corrosion.

In contrast to the previous approaches, hot gas cleanup occurs at high temperature to adsorb or

decompose impurities in gas phase. The advantages of hot gas cleanup include the increased

efficiency and reduced waste streams.17 However, thermal instability and low removal

efficiencies remain significant challenges to enable wide adoption of this approach.15, 17-18

In recent years, research efforts have been focused on tars, NH3 and H2S abatement

through hot gas cleanup.15, 18 Chlorine contaminants have received much less attention partially

due to their small concentration relative to other contaminants (i.e. tars, NH3 and H2S) in

biomass derived syngas. However, the concentration of chlorine contaminants can be as high as

500 ppm in biomass derived syngas.18

Layered double hydroxide (LDH) materials have gained considerable interest and have

been used as catalysts, ion-exchange materials, sorbents, supports, and absorbers lately.19 These

64

materials have a general formula of [ (OH)2]x+[ · yH2O]x−, where MII and MIII

represent divalent and trivalent metal cations, respectively, and An− is an n-valent anion.20 LDH

materials could be engineered for specific purposes since the cations and anions can be chosen

based on their effectiveness for specific applications. MII could be Ni2+, Zn2+, Mg2+, Mn2+, or

Cu2+; MIII could be Fe3+, Al3+, or Cr3+, and could be , , , , or . Few

studies confirmed the potential of HCl adsorption using calcined LDH mixed metal oxides albeit

at lower temperatures.21-22

In this study, a Na-Mg-Al LDH based sorbent was synthesized and benchmarked against

a commercially available Mg–Al LDH, as well as other sorbents (sodium aluminate (NaAlO2)

and sodium carbonate (Na2CO3)), for hot gas cleanup (400 to 600 °C) of HCl at concentrations

observed in biomass derived syngas. We hypothesize that incorporating sodium (Na) into the

magnesium (Mg) and aluminum (Al) LDH framework will improve the HCl removal efficiency

relative to the commercial LDH.


3.1 Sorbent synthesis and preparation Na-Mg-Al LDH was synthesized by a spontaneous self-assembly method which enables

the insertion of guest molecules into a layered host to generate composite materials of layered

structure.19, 23. Na-Mg-Al LDH was synthesized by co-precipitation technique in which the guest

specie is included in the reaction solution, followed by aging (40 h) to form the final

composite.24 The pH value of a 100 ml aqueous solution containing Mg 2 (0.03 mol), and

Al 3 (0.01 mol) was adjusted to about 10 pH with Na2CO3. The obtained slurry was then

filtered and washed with D.I water. By drying the filtrate in the oven at 80 °C, Na-Mg-Al LDH

sample was then obtained. The calcination was carried out in an electric furnace at 700 °C for 4 h

under oxygen atmosphere. The commercial sorbents (Na2CO3, NaAlO2, and commercial LDH)

were acquired from Strem Chemicals Inc. and Sigma-Aldrich Chemistry and calcined in the

electric furnace at 700 °C for 4 h under air prior to testing the sorption reactor. All sorbents were

pelletized and/or size reduced to particle size between 250 and 850 μm.

65

3.2 Sorbent characterization Inductively Coupled Plasma - Optical Emission Spectroscopy (ICP-OES) was conducted

for the elemental composition analysis of synthesized LDH. 0.01 g sample of LDH and calcined

LDH were analyzed by ICP-OES for metal components. The sample was digested using

Multiwave 3000 (Anton Paar, VA, USA) digester with 4 ml concentrated HNO3 (trace metal

grade, 67-70% w/w), 3 ml H2O2, and 0.2 ml HF at 160 - 210 °C for 20 min at 1150 W. After

digestion, the reaction solution was diluted to 50 ml with Milli-Q H20. The samples were then

filtered and analyzed for their elemental composition. Additionally, all sorbents were subjected

thermogravimetric analysis (TGA) to evaluate their thermal stability at hot gas cleanup

temperatures. Sorbents were analyzed under nitrogen (N2) atmosphere from room temperature

30 °C to 105 °C at 15 °C/min. The temperature was held at that set point for 30.0 min to outgas

moisture and other gases adsorbed on the surface and pores. The furnace was then raised to

700 °C at 5 °C /min. The overall mass loss was quantified, and all samples were analyzed in

triplicate.

Furthermore, the specific surface area and pore volume of the fresh, uncalcined sorbents

were measured by N2 adsorption using a Beckman Coulter surface area analyzer. Prior to the

analysis, all samples were outgassed at 120 °C for 60 min. All samples were analyzed in

triplicate.

In addition, Powder X-ray Diffraction (PXRD) was performed using a Panalytical

Empyrean diffractometer with a CuK alpha1 (high resolution) source (λ = 0.15406 nm) using a

voltage of 45 kV and a current of 40 mA. Surface morphology was examined by scanning

electron microscopy (SEM) using a ZEISS EVO MA15 Scanning Microscope. Energy dispersive

X-ray spectroscopy (Bruker xFlash 6130) was used to determine surface elemental composition

of LDH, CLDH, and CLDH after sorption tests. PXRD and SEM-EDS were collected at the Joint

Institute for Advanced Materials (JIAM) at the University of Tennessee, Knoxville.

3.3 Sorption study, sampling and analysis procedure In order to evaluate the performance of the synthesized LDH and commercial sorbents

for HCl removal from a gas stream, adsorption experiments were carried out with a gas mixture

containing 200 ppm of HCl and a balance of nitrogen (N2). Figure 10 depicts the schematics of

the experimental setup which consists of (1) an HCl specialty mixed gas (200 ppm HCl/balance

N2) cylinder; (2) mass flow controller; (3) an electric furnace; (4) a PID temperature controller;

66

(5) a sorbent bed; (6) coarse wool plugs; (7) a ½ ‘’ outside diameter and 15.5 ‘’ length tubular

fixed bed reactor; (8) sodium hydroxide (NaOH, 1 M) filled impinger with a coarse porosity

fritted tip for gas sparging and; (9) NaOH filled Erlenmeyer flask for trapping unremoved HCl.

Figure 10 Schematic representation of the fixed bed experimental setup

The fixed bed reactor was loaded with 0.814 g of calcined Na-Mg-Al-LDH (0.003 mol

Na and 0.003 mol Mg, with weight hourly space velocity (WHSV) of approximately 9 h-1), 0.353

g of calcined commercial LDH (0.003 mol Mg with WHSV of approximately 20 h-1) , 0.637g of

calcined Na2CO3 (0.006 mol Na with WHSV of approximately 11 h-1), and 0.984 g of calcined

NaAlO2 (0.006 mol Na with WHSV of approximately 7 h-1) sandwiched in between two coarse

wool plugs during different experiments. The reactor was then preheated for 20 min under N2

flow before the hydrogen HCl gas was introduced at a flow rate of 100 ml min−1. Sorption

experiments were carried out for 14 hours at 400, 500, and 600 °C (Figure 17) and atmospheric

pressure in duplicate runs. The impinger scrubbing solution was sampled every 120 min for the

first 4 samples and every 69 min for the rest 6 samples, and the aliquots were analyzed using ion

chromatography (IC). The gas phase hydrogen chloride reacts with NaOH in solution according

to the reaction below.

(1)

67

Thus, we analyzed the chlorine ion concentration to determine the gas phase hydrogen

chloride concentration. This is achieved using a Dionex Model ICS-2100 ion chromatograph

(Sunnyvale, CA, USA) fitted with a Dionex ASRS Suppressor detector was employed. The

separation was achieved by a Dionex IonPac AS11-HC-4μm column. The flow-rate of eluent

was 1 ml/min. All separations were conducted at 30 °C. The chromatographic separation was

affected by a gradient program which consisted of KOH gradient eluent from 5 mM to 23 mM.

The outlet concentration of HCl after the reactor was calculated by determining the chlorine

content in solution at each sampling time interval.

(2)

In equation (2), (μmol ) is the number of moles of chlorine dissolved in NaOH

scrubbing solution for a sampling interval time , (μmol /ml) is the change in chlorine

concentration during , and is volume of NaOH initial scrubbing solution (200 ml)

discounted for the volume of the previous aliquot which is typically 4 ml. Thus, we obtain the

outlet molar flow rate of HCl at each sampling time step, , through the following relationship:

(3)

Finally, we obtain the outlet gas phase concentration of HCl through a mass balance by

dividing the outlet molar flow rate of HCl by the total flow rate, Ftotal, determined through

equation 4

(4)

where the total molar flow rate is computed from the mass flow rate, which is controlled

during the experiment.

3.4 Model of HCl Sorption The modeling of the fixed bed experiment is carried out based on the conservative

equation derived from the sorbent and HCl mass balance:25

68

(5)

where is the bed porosity, C is the HCl gas concentration in the bed, V0 is the bed

velocity in the empty bed, is the sorbent mass per unit volume of bed, and q is the HCl

adsorbed based on unit mass of CLDH sorbent.

The correlation of the HCl and the sorbent during sorption test can be obtained when

assuming a constant breakthrough pattern through the bed: 25

(6)

where C0 is the inlet HCl concentration, q0 is the HCl saturated absorbing condition of the

CLDH sorbent, and XB is the conversion extent of the CLDH sorbent.

Take the sorbent particles into consideration, the shrinking core model is used for the

evaluation of the sorption data. The rate controlling steps of the sorption should be the chemical

reaction on the sorbent surface or the product layer diffusion, or both. The first order surface

chemical reaction rate is defined as: 25

(7)

And the diffusion rate of HCl per sorbent particle is: 25

(8)

The amount of HCl absorbed by CLDH during sorption test per unit time is: 25

(9)

can be eliminated by solving equations (7) for and (8) for . Thus, the

combination of the new equation having only C and equation (9) gives:

(10)

69

The shrinking radius r can be replaced by the sorbent conversion XB by r = R(1 - XB) 1/3

and yields:

(11)

where

(12)

By inserting equation (6) into equation (11), the final expression of the sorption kinetics

is obtained:

(13)

(14)

where is the residence time of gas in the empty bed. The value of C/C0 is

given from breakthrough curves. MATLAB R2016a was applied to fit the experimental data

using equation (13).

Also, the root mean square error (RMSE), mean absolute error (MAE), and quality of fit

(FIT) statistical tests were carried out in MATLAB R2016a to evaluate the kinetic modeling

based on equations (15-17).

(15)

(16)

70

(17)

where N is the observation number; are the experimental values for

observation j; are the predicted values for observation j; and is the

maximum value amidst all observations.


4.1 Characterization of sorbents

4.1.1 Elemental analysis of synthesized sorbent by ICP-OES Estimates of the Mg2+/Na+/Al3+ ratio of the synthesized LDH and calcined synthesized-

LDH were calculated by dividing the Mg2+ and Na+ concentrations by the Al3+ concentration as

determined by ICP-OES. Mg/Na/Al in synthesized LDH uncalcined and calcined showed cation

ratios 3.1:3.5:1 and 3.1:2.9:1, respectively. The Mg/Al ratios (3.1:1) in synthesized LDH before

and after calcination both agree with the Mg/Al ratio in commercial LDH which is 3:1.

4.1.2 Thermogravimetric analysis (TGA) The thermogravimetric (TG) analysis results are shown in Figure 11 and depict the

thermal stability of the sorbents. We observe that calcined Na2CO3 exhibited the highest stability

with a maximum of 0.11 wt. % mass loss followed by calcined NaAlO2 and calcined Na-Mg-Al-

LDH with less than 1.84 and 3.33 wt. % mass loss, respectively. The calcined commercial LDH

(cComLDH) had the lowest thermal stability with less than 9.85 wt. % mass loss. Our findings

on the thermal degradation of cComLDH is consistent with reports by others for an LDH

material with similar Mg/Al molar ratio calcined at 550 C for 4h.26

Table 12 presents the weight loss of the four sorbents based on their original weight

during thermogravimetric analysis at 30, 105, 300, 500 and 700 C. From 30 to 105 C, all

sorbents encountered weight losses due to their moisture evaporation (physically adsorbed

water), with 0.11 % for calcined Na2CO3 (cNa2CO3), 1.53 % for calcined NaAlO2 (cNaAlO2),

0.86 % for calcined Na-Mg-Al LDH (cLDH), and 2.98 % for calcined commercial LDH

(cComLDH). From 105 to 300 C, the further weight loss of cLDH and cComLDH occurred

71

mainly due to the dehydroxylation, consistent with other studies27-28, while the weight of

cNa2CO3 and cNaAlO2 stayed stable.

Figure 11 TGA curves of calcined sorbents

Table 12 Weight loss (%) of the sorbents during TGA Percent mass loss, %

Temperature, °C 30 105 300 500 700 cNa2CO3 0.00 0.11 0.11 0.05 0.04 cNaAlO2 0.00 1.53 1.84 1.79 1.78 cLDH 0.00 0.86 2.27 2.85 3.33 cComLDH 0.00 2.98 7.44 9.14 9.85

4.1.3 BET analysis The BET surface area and pore volume of calcined sorbents were listed in Table 13.

Table 13 Summary of BET analysis results of sorbents calcined at 700 °C cLDH cComLDH cNaAlO2 cNa2CO3

Total Pore Volume (ml/g) 0.027 (0.005) 0.116 (0.015) 0.002 (0.000) 0.001 (0.000) BET Surface Area (m2/g) 4.292 (0.196) 55.019 (0.981) 0.545 (0.021) 0.057 (0.012)

† Values in parentheses represent the standard deviation.

The surface area of the samples can be affected by their chemical composition as well as

calcination temperature and time. The surface area of cComLDH created by the calcination

process comes from the formation of pores and channels due to the evaporation of water and the

removal of carbon dioxide.29 Table 14 summarizes the BET analysis results of MgAlO from

72

literature. It is stated that MgAlO mixed oxides calcined at 350 to 450 C have a relatively high

surface area (>200 m2/g) and 0.5-0.8 ml/g of total pore volume.26, 30-33 The MgAlO oxides

calcined at 500 C has a lower surface area of 82.2 m2/g with a pore volume of 0.85 ml/g.34 As

reported, samples calcined at temperatures within the decomposition temperature range exhibit a

maximum value of the surface area, which decreases following the temperature increase

following further calcination35-36, which can explain the lower surface area for cComLDH which

was calcined at a relatively high temperature 700 C for 4 h. The surface area and pore volume of

cLDH are significantly smaller than the cComLDH, which may be explained by the

accumulation of Na in the compounds. The average pore volume and BET surface area of the

calcined sorbents increased in the following order: cComLDH > cLDH > cNaAlO2 > cNa2CO3.

Table 14 Comparison of BET analysis results of MgAlO from literature Sorbents Total Pore

Volume (ml/g) BET Surface Area (m2/g)

Calcined Temperature ( )

Calcined Duration (h)

Refs

MgAlO - 39.9 800 2 37 MgAlO 0.85 82.2 500 8 34 MgAlO - 115 800 6 36 MgAlO - 194 400 6 36 MgAlO 0.8 210 450 15 30

4.2 HCl sorption study Figure 12 shows the concentration of in NaOH solution for sorbents at 400, 500, and

600 °C, respectively. Following increasing of time, the concentration increased for all four

sorbents. At 400 °C to 600 °C, cComLDH had the highest concentration in NaOH solution,

indicating the least effectiveness of cComLDH in the removal of HCl gas. Compared to

cComLDH, the sodium-based sorbents were more effective in capturing HCl. Relatively low

concentration for cNa2CO3 and lower concentrations for cLDH as well as cNaAlO2 occurred at

400 °C. From 400 °C to 600 °C, cLDH, cNa2CO3 and cNaAlO2 had low concentration of in

NaOH solution.

Figure 13 depicts the outlet HCl breakthrough curves of various sorbents. As the least

competent sorbent, cComLDH reached the 1 ppm HCl breakthrough in less than 2 h (Table 15)

at 400 to 600 °C. For cNa2CO3, it is less effective (2.9 h) at 400 °C than 500 °C (13.2 h) and

73

600 °C (> 14 h). The breakthrough time for 0.006 mol cNa2CO3 in this study is consistent with

around 4 h breakthrough time for 0.012 mol Na2CO3 in the literature.38 For cNaAlO2, it less

effective that cLDH at 400 °C (10.3 h for 0.006 mol), which is in consistence with approximately

18 h breakthrough time for 0.012 mol NaAlO2 at same temperature from literature38. At 500 to

600 °C, cNaAlO2 exhibited its effectiveness (> 14 h) in capturing HCl. As the most effective

sorbent, cLDH reached more than 14 h of breakthrough time from 400 °C to 600 °C. The

breakthrough time of cComLDH and cLDH suggests that the Na in the cLDH could sufficiently

participate in the removal of HCl. It is clear that, the incorporation of Na in the LDH framework

enhanced the effectiveness of HCl sorption. Additionally, Na-based sorbents exhibited different

effects following temperature change: with cLDH > cNaAlO2 > cNa2CO3 at 400 °C; cLDH =

cNaAlO2 > cNa2CO3 at 500 °C; and cNa2CO3 = cNaAlO2 = cLDH at 600 °C.

Figure 12 The concentration of in NaOH solution for sorbents at 400, 500, and 600 °C

Figure 13 The concentration of outlet HCl gas for sorbents at 400, 500, and 600 °C with

grey line representing 1 ppm breakthrough

Table 15 Summary of 1 ppm HCl breakthrough time of sorbents Breakthrough time, h

Temperature, °C cComLDH cLDH cNaAlO2 cNa2CO3 400 < 2 > 14 10.3 2.9 500 < 2 > 14 > 14 13.2 600 < 2 > 14 > 14 > 14

74

The surface morphology and surface elemental composition of LDH, CLDH, and CLDH

samples after sorption tests were reported in Figure 14.

The SEM micrographs (Figure 14) and elemental compositions (Table 16) at 500 and

2000 magnification of cLDH exhibited the amorphous surface morphology of the original

calcined LDH sample (Figure 14 a) with 0% Cl on the surface. Moreover, the EDS atom % of

the elements demonstrates that Na and Cl on the cLDH surface have a positive correlation.

Additionally, the SEM micrographs of cLDH after 14 h sorption reveal the formation of NaCl

crystals which result in a cuboidal morphology39 (Figure 14 d).

PXRD patterns of the original LDH sample, calcined LDH sample, calcined LDH sample

after 28 h of HCl sorption, and references are shown in Figure 15.

The PXRD pattern of the original LDH sample (Figure 15 a blue) contains peaks

corresponding to ((Mg6Al2)(OH)18(H2O)4)0.375, NaNO3, Na2CO3, and Mg36Al61.7 resulted from

the co-precipitation synthesis. After calcination at 700 C, peaks corresponding to Na3.893(CO3)2,

NaNO3, Mg2O(OH)2, and Al2O3 are observed in the PXRD pattern of the calcined LDH sample

(Figure 15 b blue). Peaks corresponding to (Mg6Al2)(OH)18(H2O)4)0.375 and Mg36Al61.7 are absent

in the calcined sample. Figure 15 c reveals the generation of NaCl and Na6MgCl8 in the calcined

LDH sample after 28 h of HCl sorption. Peak corresponding to NaNO3 is not observed.

Observations from SEM-EDS and PXRD analysis implied that Na in CLDH existed in

Table 16 Summary surface elemental composition of cLDH and cLDH samples after sorption tests shown in Figure 15

Surface elemental composition, atom % (SD) C N O Na Mg Al Si Cl

500 X Magnification cLDH 7.8

(2.8) 5.0 (3.0)

57.5 (2.0)

17.2 (4.4)

8.0 (4.1)

4.2 (3.7)

0.2 (0.2)

0.0 (0.0)

cLDH after 14 h sorption at 400 °C

6.5 (2.5)

1.4 (0.5)

39.2 (11.1)

13.9 (11.3)

20.4 (8.3)

6.3 (2.8)

0.4 (0.1)

11.9 (8.1)


9.3 (3.1)

1.5 (0.5)

45.0 (17.2)

19.4 (10.7)

9.4 (5.9)

3.8 (2.7)

0.5 (0.5)

11.1 (11.9)


7.3 (0.4)

2.0 (0.1)

30.5 (7.3)

28.7 (3.7)

6.1 (2.1)

1.5 (0.4)

0.2 (0.0)

23.8 (5.5)

2000 X Magnification cLDH 4.8

(1.8) 5.3 (2.5)

55.5 (2.0)

19.2 (3.1)

10.3 (3.6)

4.7 (1.7)

0.3 (0.1)

0.0 (0.0)


6.5 (1.5)

1.3 (0.6)

38.1 (10.2)

16.2 (10.8)

18.4 (7.5)

5.9 (2.6)

0.3 (0.2)

13.2 (8.5)


13.7 (2.5)

2.0 (1.0)

24.2 (23.3)

30.6 (15.7)

7.3 (11.4)

1.7 (1.8)

0.2 (0.2)

20.2 (17.3)


10.2 (3.4)

2.3 (0.1)

5.8 (2.9)

44.8 (2.3)

1.0 (0.2)

0.4 (0.1)

0.1 (0.0)

35.4 (3.3)

75

Figure 14 SEM micrographs of: (a) cLDH; (b) cLDH after 14 h sorption at 400 °C; (c) cLDH after 14 h sorption at 500 °C; (d) cLDH after 14 h sorption at 600 °C with 2000 X

magnification, and (e) cLDH; (f) cLDH after 14 h sorption at 400 °C; (g) cLDH after 14 h sorption at 500 °C; (h) cLDH after 14 h sorption at 600 °C with 500 X magnification

Figure 15 PXRD diffractograms of: (a) original LDH sample and references

(((Mg6Al2)(OH)18(H2O)4)0.375, NaNO3, Na2CO3, and Mg36Al61.7), (b) calcined LDH sample and references (Na3.893(CO3)2, NaNO3, Mg2O(OH)2, and Al2O3), and (c) calcined LDH

sample after 28 h of HCl sorption and references (NaCl, Na2CO3, Al2O3·3H2O, MgO, and Na6MgCl8)

NaNO3 and Na2CO3. During sorption, HCl gas reacted with NaNO3 and Na2CO3, resulting in

NaCl.

4.3 Kinetics model fitting of HCl removal reaction A kinetic model was applied to investigate the HCl removal reaction in the fixed bed

reactor (Figure 16) with modeling results shown in Table 17.

5. CONCLUSIONS

In this study, we present the findings of the synthesis and evaluation of Mg and Na

layered double hydroxide based high temperature sorbents for hydrogen chloride removal.

Sodium-based LDH was successfully synthesized with Mg/Na/Al cation ratios of 3.1:3.5:1 and

same Mg/Al ration with commercial LDH. The results of this experimental study exhibited the

effectiveness, thermal stability, and efficiency of cLDH in capturing HCl gas contaminant at hot

76

gas cleanup temperatures (400 to 600 °C). Sorption of HCl for commercial sorbents (cComLDH,

cNaAlO2, and cNa2CO3) were also conducted for comparison. The better performance of cLDH

compared to cComLDH supported the enhancement of incorporation of Na in the LDH

framework for HCl sorption. At different temperature, Na-based sorbents showed various

effectiveness on HCl removal with the comparison of their breakthrough time: cLDH > cNaAlO2

> cNa2CO3 at 400 °C; cLDH = cNaAlO2 > cNa2CO3 at 500 °C; and cNa2CO3 = cNaAlO2 =

cLDH at 600 °C.

Figure 16 Kinetics model fitting of HCl removal reaction

Table 17 Summary of kinetic model results K1 K2 RMSE MAE FIT

Prediction 0.176 0.031 0.012 0.005 0.001 Upper 95% CI 0.174 0.028 - - - Lower 95% CI 0.178 0.035 - - -

6. ACKNOWLEDGMENTS

This research was supported by Southeastern Sun Grant Center and the US Department

of Transportation, Research and Innovative Technology Administration, Grant No. DTO559-07-

G-00050.

77

7. REFERENCES 1. Liu, X.; Bi, X. T., Removal of inorganic constituents from pine barks and switchgrass. Fuel Processing Technology 2011, 92 (7), 1273-1279. 2. Pattiya, A.; Chaow-u-Thai, A.; Rittidech, S., The influence of pretreatment techniques on ash content of cassava residues. International journal of green energy 2013, 10 (5), 544-552. 3. Bridgeman, T.; Darvell, L.; Jones, J.; Williams, P.; Fahmi, R.; Bridgwater, A.; Barraclough, T.; Shield, I.; Yates, N.; Thain, S., Influence of particle size on the analytical and chemical properties of two energy crops. Fuel 2007, 86 (1), 60-72. 4. Miranda, I.; Gominho, J.; Mirra, I.; Pereira, H., Chemical characterization of barks from Picea abies and Pinus sylvestris after fractioning into different particle sizes. Industrial Crops and Products 2012, 36 (1), 395-400. 5. Mante, O. D.; Amidon, T. E.; Stipanovic, A.; Babu, S. P., Integration of biomass pretreatment with fast pyrolysis: An evaluation of electron beam (EB) irradiation and hot-water extraction (HWE). Journal of Analytical and Applied Pyrolysis 2014, 110, 44-54. 6. Das, P.; Ganesh, A.; Wangikar, P., Influence of pretreatment for deashing of sugarcane bagasse on pyrolysis products. Biomass and Bioenergy 2004, 27 (5), 445-457. 7. Kemppainen, K.; Inkinen, J.; Uusitalo, J.; Nakari-Setälä, T.; Siika-aho, M., Hot water extraction and steam explosion as pretreatments for ethanol production from spruce bark. Bioresource technology 2012, 117, 131-139. 8. Chen, W.-H.; Ye, S.-C.; Sheen, H.-K., Hydrothermal carbonization of sugarcane bagasse via wet torrefaction in association with microwave heating. Bioresource technology 2012, 118, 195-203. 9. Bach, Q.-V.; Tran, K.-Q.; Skreiberg, Ø.; Khalil, R. A.; Phan, A. N., Effects of wet torrefaction on reactivity and kinetics of wood under air combustion conditions. Fuel 2014, 137, 375-383. 10. Jenkins, B.; Bakker, R.; Wei, J., On the properties of washed straw. Biomass and bioenergy 1996, 10 (4), 177-200. 11. Banks, S.; Nowakowski, D.; Bridgwater, A., Fast pyrolysis processing of surfactant washed Miscanthus. Fuel Processing Technology 2014, 128, 94-103. 12. Edmunds, C. W.; Hamilton, C.; Kim, K.; Chmely, S. C.; Labbé, N., Using a chelating agent to generate low ash bioenergy feedstock. Biomass and Bioenergy 2017, 96, 12-18. 13. Das, O.; Sarmah, A. K., Mechanism of waste biomass pyrolysis: effect of physical and chemical pre-treatments. Science of the Total Environment 2015, 537, 323-334. 14. Kazi, K.; Jollez, P.; Chornet, E., Preimpregnation: an important step for biomass refining processes. Biomass and Bioenergy 1998, 15 (2), 125-141. 15. Abdoulmoumine, N.; Adhikari, S.; Kulkarni, A.; Chattanathan, S., A review on biomass gasification syngas cleanup. Applied Energy 2015, 155, 294-307. 16. Xiao, Y.; Li, Z.; Wang, B.; Zhao, L.; Chi, J., Thermodynamic performance assessment of IGCC power plants with various syngas cleanup processes. Journal of Thermal Science 2012, 21 (5), 391-403. 17. Woolcock, P. J.; Brown, R. C., A review of cleaning technologies for biomass-derived syngas. Biomass and Bioenergy 2013, 52, 54-84. 18. Xu, C. C.; Donald, J.; Byambajav, E.; Ohtsuka, Y., Recent advances in catalysts for hot-gas removal of tar and NH 3 from biomass gasification. Fuel 2010, 89 (8), 1784-1795.

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19. Zhang, M.; Gao, B.; Yao, Y.; Inyang, M., Phosphate removal ability of biochar/MgAl-LDH ultra-fine composites prepared by liquid-phase deposition. Chemosphere 2013, 92 (8), 1042-1047. 20. Zümreoglu-Karan, B.; Ay, A. N., Layered double hydroxides — multifunctional nanomaterials. Chemical Papers 2011, 66 (1), 1-10. 21. Ram Reddy, M.; Xu, Z.; Lu, G.; Diniz da Costa, J., Layered double hydroxides for CO2 capture: structure evolution and regeneration. Industrial & engineering chemistry research 2006, 45 (22), 7504-7509. 22. Kameda, T.; Uchiyama, N.; Yoshioka, T., Treatment of gaseous hydrogen chloride using Mg− Al layered double hydroxide intercalated with carbonate ion. Chemosphere 2010, 81 (5), 658-662. 23. Chen, W.; Qu, B., LLDPE/ZnAl LDH-exfoliated nanocomposites: effects of nanolayers on thermal and mechanical properties. Journal of Materials Chemistry 2004, 14 (11), 1705-1710. 24. Hussein, M. Z. B.; Zainal, Z.; Ming, C. Y., Microwave-assisted synthesis of Zn-Al-layered double hydroxide-sodium dodecyl sulfate nanocomposite. Journal of Materials Science Letters 19 (10), 879-883. 25. Wang, W.; Ye, Z.; Bjerle, I., The kinetics of the reaction of hydrogen chloride with fresh and spent Ca-based desulfurization sorbents. Fuel 1996, 75 (2), 207-212. 26. Pfeiffer, H.; Lima, E.; Lara, V.; Valente, J. S., Thermokinetic Study of the Rehydration Process of a Calcined MgAl-Layered Double Hydroxide. Langmuir 2010, 26 (6), 4074-4079. 27. Islam, M.; Patel, R., Physicochemical characterization and adsorption behavior of Ca/Al chloride hydrotalcite-like compound towards removal of nitrate. Journal of hazardous materials 2011, 190 (1), 659-668. 28. Lwin, Y.; Yarmo, M. A.; Yaakob, Z.; Mohamad, A. B.; Daud, W. R. W., Synthesis and characterization of Cu–Al layered double hydroxides. Materials research bulletin 2001, 36 (1), 193-198. 29. Yang, L.; Shahrivari, Z.; Liu, P. K.; Sahimi, M.; Tsotsis, T. T., Removal of trace levels of arsenic and selenium from aqueous solutions by calcined and uncalcined layered double hydroxides (LDH). Industrial & Engineering Chemistry Research 2005, 44 (17), 6804-6815. 30. Abelló, S.; Medina, F.; Tichit, D.; Pérez-Ramírez, J.; Sueiras, J.; Salagre, P.; Cesteros, Y., Aldol condensation of campholenic aldehyde and MEK over activated hydrotalcites. Applied Catalysis B: Environmental 2007, 70 (1), 577-584. 31. Chimentao, R.; Abelló, S.; Medina, F.; Llorca, J.; Sueiras, J.; Cesteros, Y.; Salagre, P., Defect-induced strategies for the creation of highly active hydrotalcites in base-catalyzed reactions. Journal of Catalysis 2007, 252 (2), 249-257. 32. Valente, J. S.; Figueras, F.; Gravelle, M.; Kumbhar, P.; Lopez, J.; Besse, J.-P., Basic properties of the mixed oxides obtained by thermal decomposition of hydrotalcites containing different metallic compositions. Journal of Catalysis 2000, 189 (2), 370-381. 33. Pérez-Ramı́rez, J.; Overeijnder, J.; Kapteijn, F.; Moulijn, J. A., Structural promotion and stabilizing effect of Mg in the catalytic decomposition of nitrous oxide over calcined hydrotalcite-like compounds. Applied Catalysis B: Environmental 1999, 23 (1), 59-72. 34. Sun, J.; Yang, J.; Li, S.; Xu, X., Basicity–FAME yield correlations in metal cation modified MgAl mixed oxides for biodiesel synthesis. Catalysis Communications 2014, 52, 1-4. 35. Romero, A.; Jobbágy, M.; Laborde, M.; Baronetti, G.; Amadeo, N., Ni (II)–Mg (II)–Al (III) catalysts for hydrogen production from ethanol steam reforming: influence of the activation treatments. Catalysis Today 2010, 149 (3), 407-412.

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36. Shen, J.; Tu, M.; Hu, C., Structural and surface acid/base properties of hydrotalcite-derived MgAlO oxides calcined at varying temperatures. Journal of Solid State Chemistry 1998, 137 (2), 295-301. 37. Lv, L.; He, J.; Wei, M.; Evans, D.; Duan, X., Factors influencing the removal of fluoride from aqueous solution by calcined Mg–Al–CO 3 layered double hydroxides. Journal of Hazardous Materials 2006, 133 (1), 119-128. 38. Ohtsuka, Y.; Tsubouchi, N.; Kikuchi, T.; Hashimoto, H., Recent progress in Japan on hot gas cleanup of hydrogen chloride, hydrogen sulfide and ammonia in coal-derived fuel gas. Powder Technology 2009, 190 (3), 340-347. 39. Tran, R. T.; Naseri, E.; Kolasnikov, A.; Bai, X.; Yang, J., A new generation of sodium chloride porogen for tissue engineering. Biotechnology and applied biochemistry 2011, 58 (5), 335-344.

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8. APPENDIX

8.1 Reaction temperature

Figure 17 The reactor temperature of 14 h HCl sorption test at 400 °C, 500 °C, and 600 °C,

respectively

8.2 Actual experimental setup

Figure 18 Actual experimental setup

81

8.3 MATLAB code for kinetics model fitting of HCl removal reaction at 600 °C function kineticmodelfit % NOTES: % 1. The ‘thetas’represent unknown parameters % 2. c represents c/co function C=kinetics(theta,t) c0=0.000001; [T,Cv]=ode45(@DifEq,t,c0); % function dC=DifEq(t,c) dcdt=zeros(1,1); dcdt(1)=c(1)/(((1-c(1))^(-2/3)/theta(1))+(((1-c(1))^(-1/3)-1)/theta(2))); dC=dcdt; end C=Cv; end t=[0 2 4 6 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 48

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62 74 76 78 80 90 92 94]; c=[0 0.00455 0.000617731 0.00441703 0.002012437 0.000878427 0.000338951 0 0 0 0.000506478 0.004128482 0.003874334 0 0.00016041 0.001960343 0.002738948 0 0.004897379 0 0.00087644 0.003785403 0.003525883 0.001053385 0.001153267 0.015925802 0.102857634 0.23240775 0.297805814 0.330752707 0.362009257 0.671808318 0.72731774 0.777737679]; theta0=[0.17572;0.03136];

83

[theta,Rsdnrm,Rsd,ExFlg,OptmInfo,Lmda,Jmat]=lsqcurvefit(@kinetics,theta0,t,c); fprintf(1,'\tRate Constants:\n') for k1 = 1:length(theta) fprintf(1, '\t\tTheta(%d) = %8.5f\n', k1, theta(k1)) end % Find the specific cv at certain t time index = find(t == 0);[cv_point]= Cv (index);fprintf(1, '\t\t %8.5f\n', [cv_point]); index = find(t == 2);cv_point1= Cv (index);fprintf(1, '\t\t %8.5f\n', cv_point1);[cv_point]=[cv_point cv_point1]; index = find(t == 4);cv_point2= Cv (index);fprintf(1, '\t\t %8.5f\n', cv_point2);[cv_point]=[cv_point cv_point2]; index = find(t == 6);cv_point3= Cv (index);fprintf(1, '\t\t %8.5f\n', cv_point3);[cv_point]=[cv_point cv_point3]; index = find(t == 8);cv_point4= Cv (index);fprintf(1, '\t\t %8.5f\n', cv_point4);[cv_point]=[cv_point cv_point4]; index = find(t == 9);cv_point5= Cv (index);fprintf(1, '\t\t %8.5f\n', cv_point5);[cv_point]=[cv_point cv_point5]; index = find(t == 10);cv_point6= Cv (index);fprintf(1, '\t\t %8.5f\n', cv_point6);[cv_point]=[cv_point cv_point6]; index = find(t == 11);cv_point7= Cv (index);fprintf(1, '\t\t %8.5f\n', cv_point7);[cv_point]=[cv_point cv_point7]; index = find(t == 12);cv_point8= Cv (index);fprintf(1, '\t\t %8.5f\n', cv_point8);[cv_point]=[cv_point cv_point8]; index = find(t == 13);cv_point9= Cv (index);fprintf(1, '\t\t %8.5f\n', cv_point9);[cv_point]=[cv_point cv_point9]; index = find(t == 14);cv_point10= Cv (index);fprintf(1, '\t\t %8.5f\n', cv_point10);[cv_point]=[cv_point cv_point10]; index = find(t == 15);cv_point11= Cv (index);fprintf(1, '\t\t %8.5f\n', cv_point11);[cv_point]=[cv_point cv_point11]; index = find(t == 16);cv_point12= Cv (index);fprintf(1, '\t\t %8.5f\n', cv_point12);[cv_point]=[cv_point cv_point12]; index = find(t == 17);cv_point13= Cv (index);fprintf(1, '\t\t %8.5f\n', cv_point13);[cv_point]=[cv_point cv_point13]; index = find(t == 18);cv_point14= Cv (index);fprintf(1, '\t\t %8.5f\n', cv_point14);[cv_point]=[cv_point cv_point14]; index = find(t == 19);cv_point15= Cv (index);fprintf(1, '\t\t %8.5f\n', cv_point15);[cv_point]=[cv_point cv_point15]; index = find(t == 20);cv_point16= Cv (index);fprintf(1, '\t\t %8.5f\n', cv_point16);[cv_point]=[cv_point cv_point16]; index = find(t == 21);cv_point17= Cv (index);fprintf(1, '\t\t %8.5f\n', cv_point17);[cv_point]=[cv_point cv_point17]; index = find(t == 22);cv_point18= Cv (index);fprintf(1, '\t\t %8.5f\n', cv_point18);[cv_point]=[cv_point cv_point18];

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index = find(t == 23);cv_point19= Cv (index);fprintf(1, '\t\t %8.5f\n', cv_point19);[cv_point]=[cv_point cv_point19]; index = find(t == 24);cv_point20= Cv (index);fprintf(1, '\t\t %8.5f\n', cv_point20);[cv_point]=[cv_point cv_point20]; index = find(t == 25);cv_point21= Cv (index);fprintf(1, '\t\t %8.5f\n', cv_point21);[cv_point]=[cv_point cv_point21]; index = find(t == 26);cv_point22= Cv (index);fprintf(1, '\t\t %8.5f\n', cv_point22);[cv_point]=[cv_point cv_point22]; index = find(t == 27);cv_point23= Cv (index);fprintf(1, '\t\t %8.5f\n', cv_point23);[cv_point]=[cv_point cv_point23]; index = find(t == 28);cv_point24= Cv (index);fprintf(1, '\t\t %8.5f\n', cv_point24);[cv_point]=[cv_point cv_point24]; index = find(t == 48);cv_point25= Cv (index);fprintf(1, '\t\t %8.5f\n', cv_point25);[cv_point]=[cv_point cv_point25]; index = find(t == 62);cv_point26= Cv (index);fprintf(1, '\t\t %8.5f\n', cv_point26);[cv_point]=[cv_point cv_point26]; index = find(t == 74);cv_point27= Cv (index);fprintf(1, '\t\t %8.5f\n', cv_point27);[cv_point]=[cv_point cv_point27]; index = find(t == 76);cv_point28= Cv (index);fprintf(1, '\t\t %8.5f\n', cv_point28);[cv_point]=[cv_point cv_point28]; index = find(t == 78);cv_point29= Cv (index);fprintf(1, '\t\t %8.5f\n', cv_point29);[cv_point]=[cv_point cv_point29]; index = find(t == 80);cv_point30= Cv (index);fprintf(1, '\t\t %8.5f\n', cv_point30);[cv_point]=[cv_point cv_point30]; index = find(t == 90);cv_point31= Cv (index);fprintf(1, '\t\t %8.5f\n', cv_point31);[cv_point]=[cv_point cv_point31]; index = find(t == 92);cv_point32= Cv (index);fprintf(1, '\t\t %8.5f\n', cv_point32);[cv_point]=[cv_point cv_point32]; index = find(t == 94);cv_point33= Cv (index);fprintf(1, '\t\t %8.5f\n', cv_point33);[cv_point]=[cv_point cv_point33]; cv_point=cv_point'; % Use the built in MAE Mean Absolute Error function and pass in % the "error" part. builtInMAE = mae(c-cv_point) % Built FIT equation builtFIT = 100*(sum((c - cv_point).^2)/(34^2))/0.777737679; % Built Confidence interval 95% of theta CI = nlparci(theta,Rsd,'jacobian',Jmat) theta1=[0.1738;0.0278]; theta2=[0.1776;0.0350]; tv = linspace(min(t), max(t));

85

Cfit = kinetics(theta, tv); Cfit1 = kinetics(theta1, tv); Cfit2 = kinetics(theta2, tv); figure(1) plot(t, c, 'p') hold on hlp = plot(tv, Cfit); hlp = plot(tv, Cfit1); hlp = plot(tv, Cfit2); hold off grid xlabel('Time') ylabel('C/Co') legend(hlp, 'C_1(t)','Location','N') % Plot Confidence interval 95% hold on % Data output fprintf(1,'\tCv:\n') fprintf(1, '\t\t %8.5f\n', Cv) fprintf(1,'\tSize of t:\n') size(t) fprintf(1,'\tSize of c:\n') size(c) fprintf(1,'\tSize of Cv:\n') size(Cv) fprintf(1,'\tSize of cv_point:\n') fprintf(1, '\t\t %8.5f\n', cv_point) size(cv_point) RMSE = sqrt(mean((c - cv_point).^2)); fprintf(1,'\tRMSE:\n') fprintf(1, '\t\t %8.5f\n',RMSE) fprintf(1,'\tMAE:\n') fprintf(1, '\t\t %8.5f\n',builtInMAE) fprintf(1,'\tFIT:\n') fprintf(1, '\t\t %8.5f\n',builtFIT) Int = trapz(t,c) fprintf(1,'\tArea under the curve:\n')

86

fprintf(1, '\t\t %8.5f\n',Int) end

87

CHAPTER IV TECHNO-ECONOMIC ANALYSIS OF A CONCEPTUAL BIOREFINERY

– HOT WATER EXTRACTION INTEGRATED TO A HYBRID BIOCHEMICAL AND THERMOCHEMICAL CONVERSION PROCESS FOR HIGH ASH LIGNOCELLULOSIC BIOMASS TO HYDROCARBON

FUELS AND SUCCINIC ACID

88

Qiaoming Liua, Nicole Labbéb and Nourredine Abdoulmouminea,b


The manuscript of this chapter entitled “Techno-economic analysis of a conceptual

biorefinery – Hot water extraction integrated to a hybrid biochemical and thermochemical

conversion process for high ash lignocellulosic biomass to hydrocarbon fuels and succinic

acid” with the co-authors of Qiaoming Liu, Nicole Labbé, and Nourredine Abdoulmoumine is in

preparation for submission to the journal of Biofuels, Bioproducts & Biorefining. Qiaoming Liu

performed the techno-economic analysis and drafted the manuscript. Dr. Labbé contributed to

the revision of the manuscript. Dr. Abdoulmoumine assisted in the experiment design, techno-

economic analysis, and manuscript writing.

1. ABSTRACT

This work investigates in detail of the techno-economic impact of hot water extraction

(HWE) and subsequent succinic acid (SA) production on the thermochemical conversion of high

ash content biomass. This study models two scenarios for procuring high octane hydrocarbons: i)

without HWE and the biorefinery process of the extracts to succinic acid and ii) with the

pretreatment and biorefinery process. As a result of the HWE and SA production scenario, 3753

kg/h of succinic acid crystal can be produced for a production of 34,916 US gal/h of gasoline.

Total installed equipment cost is estimated to be $231.91 million for the base case scenario. For

the HWE and SA production scenario, the total installed equipment cost is estimated to be

$280.54 million. The 2017 base case scenario calculates a minimum fuel selling price (MFSP) of

$4.26 per gallon of gasoline. Moreover, the present analysis calculates am MFSP of $4.73 for a

gallon of gasoline blendstock for the HWE scenario. The analysis shows that HWE of high ash

content biomass for high-octane gasoline production has the potential to be a supplement of

gasoline with environmental sustainability. The fermentative succinic acid production from

HWE biomass is feasible. Also, this pathway can be important for attracting industrialization

89

interest on the thermochemical conversion of high ash content biomass. The results of TEA in

this study can be a base case for future exploration and a basis for with other similar scenarios.

2. INTRODUCTION

With the increasing demand for energy, the depletion of crude oil reservation, and the

growing concern of greenhouse gas emission, the biofuel derived from renewable biomass

resources has substantial economic, environmental, and social effects. Under such circumstances,

the development of biomass-derived energy, especially of liquid fuels such as gasoline used in

transportation, is particularly attractive and draws much attention. Efforts have been made to

enable the production of infrastructure-compatible and cost-competitive liquid fuels from

biomass. Among the various possibilities of fuel synthesis, the production of gasification-derived

synthesis gas or syngas (a mixture of CO and H2) followed by high-octane hydrocarbons

synthesis is promising for comprehensive future implementation.

The conversion process is based on a conceptual technology from NREL for obtaining

methanol from syngas, the conversion of methanol to dimethyl ether (DME), and DME

conversion into high-octane, gasoline-range hydrocarbons.1 At lower temperature synthesis

process condition compared to conventional methanol-to-gasoline (MTG) process, the proposed

conversion method produced a low-aromatic, branched-paraffin product with an expected

average octane number of more than 93, greater than the expected average octane number of

hydrocarbon compounds derived from the conventional MTG process.1

Currently, one of the primary obstacles for the commercialization of biomass-derived

syngas is the existence of contaminants during biomass gasification.2 Among the contaminants,

inorganic vapor has been associated with catalyst deactivation, corrosion, agglomeration, and

undesirable emissions during the conversion process.3, 4 Hot water extraction (HWE), as an

environmentally friendly and promising inorganic reduction pretreatment proven in our former

study, results in the removal of alkali and alkaline earth metals, as well as a certain portion of

sulfur and nitrogen from biomass, thus from biomass-derived syngas. Besides inorganic

contaminants, the switchgrass extracts derived from the HWE process consist of approximately

24% of free sugars, 9% of oligomeric sugars, 3% of alditols, and acetic acid.5, 6 This offers an

opportunity for the biorefinery scheme considering the use of crude sugars from the HWE

process for the production of succinic acid through fermentation, which can then be used as ion

90

chelator, surfactant, additive in the pharmaceutical and food industries7, as well as raw material

for biodegradable polymers8.

This study models two scenarios for procuring high octane hydrocarbons using NREL1

model as a base case: i) without HWE and the biorefinery process of the extracts to succinic acid

and ii) with the pretreatment and biorefinery process. Each of the scenarios is modeled in detail,

and economic analysis is performed assuming a “Nth” plant design (Table 18), which assumes a

successfully established industry with mature technology and several operating plants. It

eliminated any first-of-a-kind costs when building the pioneer facilities and provided a standard

basis for comparison between different conversion technologies. Consequently, the aim of this

study is to evaluate the economic potential the HWE pretreatment used by extracting inorganic

contaminants from biomass prior to gasification process. In particular, this study will seek to

address the impact of HWE as well as the biorefinery process of the extracts to succinic acid on

the indirect liquefaction (IDL) platform overall plant economic performance.


The design capacity of biomass gasification plants assumed here process 2000 dry

tonnes/day of switchgrass for gasification with an anticipated 7,884 h/year operating time. Major

processing steps include feed handling, HWE pretreatment, succinic acid production, feedstock

gasification, syngas cleanup, syngas conversion to methanol, the dehydration conversion of

methanol to dimethyl ether (DME), and DME to high-octane hydrocarbons conversion. A

schematic of the biomass indirect liquefaction process to produce high-octane, gasoline-range

hydrocarbons is shown in Figure 19.

3.1 Feed handling, hot water extraction, and succinic acid production The modeled switchgrass has a moisture content of 6.3%, with an ash content of 3.6%

and field chopped size of 20 to 40 mm. After hot water extraction, the field chopped switchgrass

with 80% moisture content is dried to 10% moisture. The delivered cost (including grower

payment/access cost, harvest and collection, landing preprocessing, transportation,

preprocessing, storage, and handling) of switchgrass, as determined from the Idaho National

Laboratory (INL), is $66.68/dry U.S. ton (in 2011 dollars).9 The ultimate analysis results of

woody biomass and switchgrass after HWE are shown in Table 19. Upon delivery, the

switchgrass is then blended in heated water in a batch reactor at 140 °C for 45 min under

91

Table 18 Summary of Nth Plant Assumptions Assumption Value of assumptionInternal rate of return 10% Plant financing by equity 40% of total capital investment Plant financing by debt 60% of total capital investment Plant life 30 years Income tax rate 35% Interest rate for debt financing 8.0% annually Term for debt financing 10 years Working capital cost 5.0% of fixed capital investment

(excluding the cost of land purchase) Depreciation schedulea 7-year MACRS schedule Construction period (spending schedule)

3 years (8% Y1, 60% Y2, 32% Y3)

Plant salvage value No value Start-up time 6 months

Revenue and costs during startup Revenue = 50% of normal Variable costs = 75% of normal Fixed costs = 100% of normal

On-stream percentage after startup 90% (7,884 operating hours per year) aCapital depreciation is computed based on the IRS Modified Accelerated Cost Recovery

System (MACRS).

Figure 19 Biomass gasification and the production of high-octane hydrocarbons diagram

Table 19 Ultimate analysis of woody biomass and switchgrass after HWE Component Weight % (Dry Basis)

Woody biomass After HWE Carbon 44.82 46.50 Hydrogen 5.77 6.14 Nitrogen 0.4 0.24 Sulfur 0.06 0.02 Oxygen 47.44 46.86 Ash 3.59 1.02

92

autogenous pressure. After the HWE process, the product is then filtered into solid switchgrass

extract for gasification and liquid extract which is then transferred to a fermenter for succinic

acid production.10 The modeled production plant of succinic acid crystals is composed of two

main sections: upstream section of succinic acid fermentation and downstream section of

concentration as well as purification, as depicted in Figure 20. The fermentation section starts

with the sterilization of feed(E-102-104) where Anaerobiospirillum succiniciproducens (AS)

with nutrient mixture and recycled Na2Succinate is heated to 121 °C and cooled to 37 °C for the

fermenter. The fermentation product is then centrifuged (F-102) to cell mass removal. The

centrifuged cells are recycled to the fermenter (V-102) while the cell-free product is sent to the

adsorption columns and desorption columns (C-106). The adsorption is carried out through

zeolite columns while succinic acid desorption being conducted by hot water at 150 °C. The

desorption columns are exposed to hot air to remove fouling components every three cycles.

After desorption, the effluent is fed to a flash drum (V-103) for excess heat removal and to an

evaporator for further concentration (E-105). The product is then transferred to a crystallizer (V-

105) where the crystals are produced and filtered by rotary vacuum filter (F-103). The wet

crystals are fed to a rotary dryer for final dying (E-106).

Figure 20 Succinic acid production plant flow diagram

On the other side, the extracted switchgrass is dried by a cross-flow dryer to 10%

moisture and pre-heated prior to feeding into the gasifier, using process waste heat.

93

3.2 Gasification During gasification, the extracted switchgrass is indirectly gasified at 870°C using the

heat supplied by a char combustor heated circulating synthetic olivine sand. The gasifier is

operated at low-pressure (0.124 MPa) with injected steam for the stabilization of the biomass and

olivine flow. Syngas is thus produced with tars and solid char. The char and olivine are separated

from the syngas through the cyclones. The former is fed to the combustor for char combustion,

leading to the temperature increase of olivine to greater than 982 °C. After then, the olivine and

residual ash flow to a pair of cyclones where olivine is captured, separated with the fines of ash

and olivine, and fed back to the gasifier. The left fines of ash and olivine are cooled, moistened,

and removed to waste.

3.3 Syngas cleanup and compression During syngas cleanup process, the reformation of tars, methane, and other hydrocarbons

to additional CO and H2 happens, while the particulates being removed through scrubbing. The

compression is conducted for the cleaned syngas. Specifically, the syngas after gasification is fed

into the catalytic tar reformer at 910 °C (temperature at the reactor outlet) where the conversion

of methane, tars, other hydrocarbons, and NH3 happened. The catalyst regenerator burns coke

deposits from the catalyst (Ni/Mg/K supported on alumina) particles and gains supplemental

combustion gases to provided heat for the tar reforming process. After exiting the tar reformer,

syngas is cooled to 60 °C via heat exchangers and scrubbed for removal of particulates,

ammonia, halides, and residual tars. The syngas after scrubbing is then compressed by a three-

stage centrifugal compressor to 2.96 MPa.

3.4 Methanol synthesis The compressed syngas after cleanup and compression process is sent to an amine-based

acid gas removal (AGR) unit to remove the CO2 and H2S before entering the reactor for

methanol synthesis. The recovered H2S-rich acid gas stream is converted to elemental sulfur for

disposal through the Merichem LO-CAT sulfur recovery unit while CO2 is sent to the feed

sterilization.

After AGR, the cleaned syngas is separated into two parts: i) one part (about 6% of the

syngas) for H2 separation in a pressure swing adsorption (PSA) system, and ii) the rest for

exothermic methanol synthesis within a fixed-bed reactor which has a copper/zinc oxide/alumina

catalyst with associated reactions shown below:

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(18)

(19)

(20)

The heat removal and temperature control of the reactor depend on the steam production.

The methanol product and unconverted syngas are cooled by heat-exchange and followed by

methanol condensation and the recycling of unconverted syngas.

3.5 Methanol conditioning The crude liquid methanol from the synthesis reactor is fed to a distillation column that

removes dissolved gases (mainly CO2) to the tar reformer. The methanol stream is then cooled to

43 °C and fed to a distillation column for methanol de-gassing. The de-gassed methanol is

subsequently transferred to a storage tank for high-octane gasoline synthesis.

3.6 High-octane gasoline synthesis Methanol from storage is converted into DME on commercial catalyst gamma alumina

(γ-Al2O3) at 250°C and 0.965 MPa in an adiabatic packed bed reactor with the reaction shown

below:

(21)

DME is then fed to the bed reactors which have metal modified beta-zeolite (H-BEA)

catalyst for the production of high-octane gasoline. The conversion of DME is at a maximum

temperature of 232°C with the overall conversion of 92.5%. The C4 products as well as

unconverted DME are recycled for additional reactions in the reactors. Heat removal and

temperature control of the synthesis is conducted with the use of the adiabatic reactors.

Moreover, water is supplied by process water as well as the reformer steam. The regeneration of

the catalyst is achieved by the catalyst regenerator that burns off the coke deposits of the catalyst

particles. The simplified methanol to hydrocarbons flow diagram is shown in Figure 21.

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4. ECONOMIC ANALYSIS

4.1 Capital cost estimation The capital costs were estimated for each area. The equipment cost was determined using

literature sources which were adjusted to match our design scale and corrected to the design year

according to equations (15) and (16), respectively.

Figure 21 Simplified methanol to hydrocarbons flow diagram

(22)

(23)

Where n varied for individual equipment in each area and cost indexes (i.e., Index2017) were

taken from Chemical Engineering’s (CE) Plant Cost Index.1 The total purchased equipment cost

(TPEC) and the total installed cost (TIC) of the area were then calculated using the individual

equipment and installed equipment cost for each area. The total direct cost (TDC) was

determined using the total cost of the total installed and site development costs. The site

development cost was calculated as 4% of the inside battery limits (ISBL: A100-500, A1400,

and A1500) total installed cost. The indirect cost was determined from the total direct cost and

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included the prorated expenses, home office and construction fees, field expenses, project

contingency, and other costs (start-up and permits) estimated at 10, 20, 10, 10 and 10% of the

total direct cost. Finally, the working capital was determined as 5% of the total fixed capital

investment (FCI), the summation of the total direct and indirect costs, excluding the land cost.

4.2 Production cost estimation The annual operating cost was determined based a plant processing capacity, the mass

and energy balance of the process analysis and 7884 h/year operation with delivered switchgrass

at $66.68/dry U.S. ton (in 2011 dollars). The fixed capital includes the labor, direct overhead,

maintenance, overhead expenses and interest financing. The labor requirement for this integrated

plant is shown in Table 20.

Table 20 Plant workforce and salary per position Position Title Salary (2017) Number of Positions $MM/yr Plant manager $161,362 1 $0.161 Plant engineer $76,839 1 $0.077 Maintenance supervisor $62,569 1 $0.063 Laboratory manager $61,471 1 $0.061 Shift supervisor $52,690 5 $0.263 Lab technician $43,908 2 $0.088 Maintenance technician $43,908 16 $0.703 Shift operators $43,908 20 $0.878 Yard employees $30,736 12 $0.369 Clerks and secretaries $39,517 3 $0.119 Business manager $56,000 1 $0.056 Procurement manager $80,523 1 $0.081 Total Salaries (2017) $2.92

The maintenance cost is taken as 3 % of FCI cost. Finally, the overhead expenses are

estimated as the combined costs of plant overhead, taken as 65% of labor and maintenance costs,

and tax and insurance costs, taken as 1% of the total FCI cost.

4.3 Economic analysis The minimum fuel selling price (MFSP) of our product, high-octane hydrocarbons is

determined based on a net zero present value at the end of the project lifetime (30 years). Also,

the sensitivity analysis is conducted for the determination of the impact of the uncertainties in

our assumptions on the minimum selling price (MSFP) of the high-octane hydrocarbons.

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5.1 Process performance of HWE and succinic acid production The flow rates of simulated feed and products are modeled and shown in Table 21. For a

production of 34,916 US gal/h of gasoline, 3753 kg/h of succinic acid crystal can be produced.

The process also generate sulfur as by-product, and the amount of its production is reduced in

scenario II due to the HWE process. The annual production of succinic acid crystal is 29,592

metric tons, which could be utilized as a precursor of many essential chemicals in chemical,

pharmaceutical, and food industries.8 It also stands out with its sustainability impacts when

compare with petrochemical counterpart due to the consumption of greenhouse gas CO2 by the

bacteria during succinic acid fermentation.11

Table 21 Feed and product flow rates for high-octane hydrocarbons and succinic acid production process

Scenario I Flow rates (lb/h) Without HWE & SA production Raw materials Woody biomass (dry) 138,718 Product and wastewater stream Gasoline 34,916 (US gal/h) Sulfur 119 Wastewater 11,337 Scenario II With HWE & SA production Raw materials Switchgrass (dry) 216,904 Product and wastewater stream Gasoline 34,916 (US gal/h) Succinic acid crystal 3753 (kg/h) Sulfur 45 Wastewater 951,873

5.2 Total capital investment Table 22 is total purchased equipment costs, installation factors, and total installed costs

by process area. The capital costs for each process area are based on data NREL design reports,

industry equipment suppliers, and published literature. Total installed equipment cost is

estimated to be $231.91 million for the base case scenario. The most expensive process area of

the base case scenario is Area 300 of syngas cleanup and compression which takes up 28.15% of

total installed equipment cost. For the HWE and SA production scenario, the total installed

equipment cost is estimated to be $280.54 million. Area 300 is still the most expensive process

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Table 22 Capital cost estimates per process area for both scenarios (2017 U.S. dollars) Process areas Total purchased

equipment cost (TPEC)

Installation factor finstallation

Total installed cost (TIC)

Scenario I MM$ % A100: Raw material handling 0.09 2.00 0.18 0.08 A200: Gasification 20.08 2.32 46.50 20.05 A300: Syngas cleanup 33.59 1.94 65.27 28.15 A400: Methanol synthesis & acid gas removal 15.12 2.28 34.41 14.84 A500: Methanol conditioning 1.19 2.65 3.15 1.36 A600: Power generation & steam system 16.61 2.15 35.76 15.42 A700: Cooling water & other utilities 2.24 2.23 5.00 2.16 A1400: High octane hydrocarbons Synthesis 21.01 1.68 35.20 15.18 A1500: Product recovery 2.86 2.25 6.44 2.78 Total 112.78 2.06 231.91 100.00 Scenario II A100: Raw material handling, HWE, SA production

28.40 1.72 48.82 17.40

A200: Gasification 20.08 2.32 46.50 16.58 A300: Syngas cleanup 33.59 1.94 65.27 23.27 A400: Methanol synthesis & acid gas removal 15.12 2.28 34.41 12.26 A500: Methanol conditioning 1.19 2.65 3.15 1.12 A600: Power generation & steam system 16.61 2.15 35.76 12.75 A700: Cooling water & other utilities 2.24 2.23 5.00 1.78 A1400: High octane hydrocarbons Synthesis 21.01 1.68 35.20 12.55 A1500: Product recovery 2.86 2.25 6.44 2.30 Total 141.09 1.99 280.54 100.00

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area, with 23.27% share of total installed equipment cost. The indirect costs of the plant

including prorated expenses, the fees for home office and construction, field expenses, project

contingency, and other costs (start-up and permits) are estimated by applying factors rest on the

total direct cost (TDC). The chosen factors are the same with both scenarios and are summarized

in Table 23. The summary of the project costs for the base case scenario and the HWE scenario

is presented in Table 24.

Table 23 Indirect cost factors for both scenarios Indirect Costs % of TPEC % of TDC* % of FCI* Prorated expenses 21.2 10 6.3 Home office and construction fees 42.5 20 12.5 Field expenses 21.2 10 6.3 Project contingency 21.2 10 6.3 Other costs (start-up and permits) 21.2 10 6.3 Total indirect costs 127.4 60 37.5 Working capital 5

*Land purchase cost is excluded here.

Table 24 Summary of the project costs Scenario I Scenario II Total purchased equipment cost (TPEC) $112,776,248 $141,086,415 Installation factor 2.056 1.988 Total installed cost (TIC) $231,905,233 $280,543,265 Other direct costs Site development 4.0% of ISBL $7,610,727 $9,556,249 Total direct costs (TDC) $239,515,961 $290,099,514 Indirect costs % of TDC (ex Land) Prorated expenses 10.00% $23,951,596 $29,009,951 Home office &construction fees 20.00% $47,903,192 $58,019,903 Field expenses 10.00% $23,951,596 $29,009,951 Project contingency 10.00% $23,951,596 $29,009,951 Other costs (start-up and permits) 10.00% $23,951,596 $29,009,951 Total indirect costs 60.00% $143,709,576 $174,059,708 Fixed capital investment (FCI) $383,225,537 $464,159,222 Land (not depreciated) $1,610,000 $1,610,000 Working capital 5.0% of FCI (ex

Land) $19,161,277 $23,207,961

Total capital investment (TCI) $403,996,814 $488,977,183

5.3 Operating costs The operating costs of both scenarios are evaluated based on 7,884 operating hours per

year. The operating costs are determined based on variable and fixed operating costs. By-

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products, raw materials, consumables, and utilities together contribute to the total variable

operating cost which is $74.99 million per year for the base case scenario and $72.33 million per

year for the HWE scenario, respectively. The total fixed operating cost, including labor,

maintenance, overhead expense, and interest on debt financing, is $57.13 million per year for the

base case scenario and $68.17 million per year for the HWE scenario, respectively.

5.4 Minimum fuel selling price The NREL study 1 quantified the economic feasibility of its 2011 model by fixing the 30-year

plant life, 40% equity set with 10% internal rate of return, the remaining 60% debt set at 8%

interest, and calculating the high-octane gasoline MFSP. The present analysis evaluates

economic feasibility in the same manner, in order for a straightforward comparison between two

scenarios. The 2017 base case scenario calculates an MFSP of $4.26 per gallon of gasoline. The

present analysis calculates an MFSP of $4.73 for a 2000 gallon of gasoline blendstock. The cost

contribution details of two scenarios for high-octane hydrocarbons from each process area are

shown in Figure 22 and Figure 23. The economic viability is one of the most crucial factors to

the success of the biofuels industry; the sustainability is another very crucial factor. The analysis

shows that HWE of high ash content biomass for high-octane gasoline production has the

potential to be supplement of gasoline with environmental sustainability. The fermentative

succinic acid production from HWE biomass is feasible. Moreover, this pathway can be

important for attracting industrialization interest on the thermochemical conversion of high ash

content biomass. TEA results in this study can be a base case for future exploration and a basis

for with other similar scenarios.

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Figure 22 Cost contribution details of the base case scenario

Figure 23 Cost contribution details of the HWE and SA production scenario

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6. REFERENCES 1. E. C. D. Tan, M. Talmadge, A. Dutta, J. Hensley, L. J. Snowden-Swan, D. Humbird, J.

Schaidle and M. Biddy, Biofuels, Bioproducts and Biorefining, 2016, 10, 17-35. 2. M. M. Yung, W. S. Jablonski and K. A. Magrini-Bair, Energy & Fuels, 2009, 23, 1874-

1887. 3. S. Q. Turn, C. M. Kinoshita, D. M. Ishimura and J. Zhou, Fuel, 1998, 77, 135-146. 4. Å. Kling, C. Andersson, Å. Myringer, D. Eskilsson and S. G. Järås, Applied Catalysis B:

Environmental, 2007, 69, 240-251. 5. S.-F. Chen, R. A. Mowery, R. S. Sevcik, C. J. Scarlata and C. K. Chambliss, Journal of

Agricultural and Food Chemistry, 2010, 58, 3251-3258. 6. S. Liu, Biotechnology advances, 2010, 28, 563-582. 7. J. G. Zeikus, M. K. Jain and P. Elankovan, Applied Microbiology and Biotechnology,

1999, 51, 545-552. 8. H. Song and S. Y. Lee, Enzyme and Microbial Technology, 2006, 39, 352-361. 9. J. Jacobson, K. Cafferty, M. Roni, P. Lamers and K. Kenney, Idaho National Laboratory,

Idaho Falls, ID, 2014. 10. Ç. Efe, L. A. M. van der Wielen and A. J. J. Straathof, Biomass and Bioenergy, 2013, 56,

479-492. 11. B. C. Klein, J. F. L. Silva, T. L. Junqueira, S. C. Rabelo, P. V. Arruda, J. L. Ienczak, P. E.

Mantelatto, J. G. C. Pradella, S. V. Junior and A. Bonomi, Biofuels, Bioproducts and Biorefining, DOI: 10.1002/bbb.1813, n/a-n/a.

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CONCLUSIONS AND FUTURE PERSPECTIVES

104

1. CONCLUSIONS

Biomass, one of the most promising renewable resources, can be used to produce power,

liquid fuels, and chemicals through thermochemical and biochemical conversions. However, the

presence of biomass inorganics is detrimental to processes in both routes, making high ash

lignocellulosic biomass less valuable for further usage. This research explored the treatment

approaches for reducing biomass inorganic impurities during gasification. The effects of hot

water extraction on the removal of inorganic impurities (N, S, Na, K, Mg and Ca) in biomass as a

pretreatment were revealed. A NaMgAl-LDH sorbent was evaluated to be efficient and stable for

hot gas clean-up of HCl gas, with better performances than three commercial sorbents (Na2CO3,

NaAlO2, and commercial LDH). The techno-economic analysis of a conceptual biorefinery with

HWE integrated to a hybrid biochemical and thermochemical conversion process for high ash

lignocellulosic biomass to hydrocarbon fuels and succinic acid resulted in a minimum fuel

selling price of $4.73 per gallon of gasoline with 3753 kg/h of succinic acid crystal production.

In the first section, HWE was applied to the high ash content switchgrass and loblolly

pine bark samples with 13 to 141 h °C extraction severity as pretreatment. The extraction liquor

pH decreased from 6.0 to 4.5 for switchgrass and 3.6 to 3.1 for pine bark following the increase

of HWE severity as a result of extractives including acetic, uronic, and phenolic acids separated

from biomass. As a result of the decreasing pH, the total ash reduction of switchgrass and pine

bark increased from 20.7 to 69.6 % and from 57.0 to 73.3 %, respectively. The mass loss also

increased from 5.1 to 15.3 % and 2.5 to 15.3 % (dry basis) following the decrease of the pH for

switchgrass and pine bark, respectively. This mass loss included the loss of carbon, nitrogen,

sulfur, and trace metals during HWE. The two-way analysis of variance revealed that, of the two

main factors (temperature and time), only temperature, but not time or the interaction of

temperature and time, had a statistically significant effect on the total ash reduction for both

switchgrass and pine bark. The study on HWE also revealed the removal of individual inorganics

achieved including up to 23 % of nitrogen, 63 % of sulfur, 72% of sodium, 99 % of potassium,

83 % of magnesium, and 13 % of calcium for switchgrass, as well as 7 % of nitrogen, 17 % of

sulfur, 60 % of sodium, 67 % of potassium, 51 % of magnesium, and 34 % of calcium for pine

bark. These reductions correspond to the equivalent reduction in syngas contaminants for both

switchgrass and pine bark.

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In the next section, the effectiveness for HCl gas sorption of NaMgAl-LDH along with

three commercial sorbents (Na2CO3, NaAlO2, and commercial LDH) were evaluated for post-

gasification treatment. The NaMgAl-LDH sorbent was synthesized by a spontaneous self-

assembly method and characterized with Na2CO3, NaAlO2, and commercial LDH. The Sodium-

based LDH was successfully synthesized with the same Mg/Al ration (3 : 1) of commercial

LDH. The result revealed that all sorbents were thermally stable during the hot gas cleanup

temperature range between 300 °C to 700 °C. For HCl sorption study, cLDH exhibited better

performance compared to cComLDH, which supported the enhancement of incorporation of Na

in the LDH framework for HCl sorption. Moreover, calcined LDH exhibited great effectiveness

in the capture of HCl at 400 °C to 600 °C with more than 14 h of breakthrough time during fixed

bed experiment, the most effective among all chosen sorbent. The results indicated a promising

application of cLDH in HCl sorption for post-gasification treatment.

In the third section, two scenarios for procuring high octane hydrocarbons using NREL

model as a base case was studied to evaluate the feasibility of a conceptual biorefinery – Hot

water extraction integrated to a hybrid biochemical and thermochemical conversion process for

high ash lignocellulosic biomass to high-octane hydrocarbons and succinic acid. A design

capacity of 2000 (dry) tonnes/day of switchgrass for gasification with an anticipated 7,884 h/year

operating time was assumed. As a result of modeling, 3753 kg/h of the succinic acid crystal can

be produced for a production of 34,916 US gal/h of gasoline. The annual production of succinic

acid crystal thus is 29,592 metric tons. The techno-economic analyses of two scenarios of

thermochemical conversion process: i) with and ii) without HWE and biochemical conversion

were conducted in 2017 U.S. dollars. The present analysis calculates an MFSP of $4.73 for a

gallon of gasoline blendstock under the conversion without HWE and biochemical conversion

scenario. The MFSP for the conversion without HWE and biochemical conversion was

calculated as $4.26 per gallon of gasoline. The environmental sustainability offered by the hybrid

biochemical and thermochemical conversion process suggested the potential of its product to be

a supplement of gasoline derived from petroleum industry.

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2. RECOMMENDATIONS FOR FUTURE WORK Future work recommended based on this study includes:

(1) Investigate the effect of HWE on more a diversified group of high ash lignocellulosic

biomass since the result of chapter 2 showed the impact of HWE on total ash reduction and

individual inorganics differed between switchgrass and pine bark.

(2) A broaden time length of HWE can be evaluated on biomass.

(3) The regeneration ability and economic feasibility of NaMgAl-LDH can be investigated and

compared with other commercial sorbents.

(4) More data points can be added to investigate the HCl removal reaction in the fixed bed

reactor at 600 °C. And the sorption experiment of cLDH can be conducted at 400 and 500 °C for

kinetics study and modeling.

(5) The performance of cLDH to remove HCl as well as other gas phase contaminants from

syngas can be evaluated.

(6) The environmental sustainability of HWE on high ash content biomass for high-octane

gasoline production with SA production can be investigated and compared with the base case

scenario in detail.

(7) Sensitivity analysis can be performed to examine the impact of changes in different process

parameters, material costs, by-product selling price, and financial assumptions on the MFSP of

high-octane hydrocarbons.

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VITA Qiaoming Liu was born in Meishan, China and got a bachelor of science in Agricultural

Engineering from the China Agricultural University, in Beijing, China. She continued to study

Biosystems Engineering at the University of Tennessee, Knoxville.

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