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Biological mineral range effects on biomass conversion to aromatic hydrocarbons via catalytic fast pyrolysis over HZSM-5 Charles A Mullen, Akwasi A Boateng, Robert B Dadson, and Fawzy M. Hashem Energy Fuels, Just Accepted Manuscript • DOI: 10.1021/ef502010t • Publication Date (Web): 20 Oct 2014 Downloaded from http://pubs.acs.org on October 29, 2014
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Biological mineral range effects on biomass conversion to aromatic hydrocarbons via catalytic fast pyrolysis over HZSM-5 Charles A. Mullena*, Akwasi A. Boatenga, Robert B. Dadsonb, Fawzy M. Hashemb a
b
USDA-ARS, Eastern Regional Research Center, 600 E. Mermaid Lane, Wyndmoor, PA 19038
Department of Agriculture, University of Maryland –Eastern Shore, Princess Anne, MD 21853
* To whom corresponding should be addressed. E-mail:
[email protected] (C.A. Mullen). Mention of trade names or commercial products in this publication is solely for the purpose of providing specific information and does not imply recommendation or endorsement by the U.S. Department of Agriculture. USDA is an equal opportunity provider and employer.
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Abstract
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A set of 20 biomass samples, comprising 10 genotypes of switchgrass, sorghum and miscanthus
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grown in two different soils with high and low poultry manure input conditions, and having a
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wide biological range of mineral content, were subjected to catalytic fast pyrolysis (CFP) over
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HZMS-5 using py-GC/MS. The resulting products including BTEX (benzene, toluene, ethyl
6
benzene and xylenes), naphthalenes and gases including carbon oxides, methane and olefins
7
were quantified in terms of product carbon yield and chemical selectivity. The effects of total ash
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content as well as the individual mineral components were compared to evaluate the effect of the
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natural range of these components on the product distribution. While there was considerable
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variation in the data due to the biological influence, a positive correlation was found between ash
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content and carbon conversion to aromatic hydrocarbons, which was particularly strong when
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considering only the switchgrass samples. This large degree of variation may be characteristic
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only of this sample set. Among individual mineral elements in the biomass, potassium, an
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essential mineral for plant growth, was found to have a strong negative influence on the carbon
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conversion to aromatic hydrocarbons, but iron was found to have a positive influence on the
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conversion to aromatics. Correlations between mineral content, the chemical intermediates from
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the incipient pyrolysis process and the final CFP products suggest that potassium’s main
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influence is on the initial pyrolysis reactions while iron may affect the catalytic reactions over
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HZSM-5.
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21
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Introduction
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Lignocellulosic biomass is the most abundant renewable resource available for the production of
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biofuels and bio-based chemicals and materials.1 However, biorefining industries based on
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lignocellulosic materials have been slow to develop because economically feasible conversion
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methods have not yet been fully developed. Thermochemical conversion technologies, and
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specifically fast pyrolysis methods have shown promise as inexpensive routes to liquefy and
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densify biomass; however, the unfavorable properties exhibited because of the high
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concentration of oxygenated compounds in pyrolysis oils (bio-oil) have hindered its utilization as
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a fuel, refinery feed or chemical feedstock.2-3 In order to utilize traditional fast pyrolysis oils as a
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refinery blendstock most of the oxygen must be removed via hydrotreating over an expensive
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metal catalyst at high pressures of hydrogen and high temperatures.4-5 Even with the state of the
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art technologies for this upgrading step, active catalyst lifetimes are not long enough to make the
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process economically efficient.6 Therefore, large research efforts have focused on producing
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deoxygenated pyrolysis oils as starting materials. Using bio-oil with low oxygen content from
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the onset may ease the burden on hydrogen use in the post production refining steps and decrease
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the difficulties encountered by virtue of its higher level of thermal stability. Among the most
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effective methods for production of deoxygenated bio-oils is applying catalytic fast pyrolysis
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(CFP) over zeolite-based catalysts (particularly HZSM-5) that leads to aromatic hydrocarbons
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and olefins.7-16
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In any process, the composition of the input feedstock will have a large influence on the
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yield and composition of the products. In the area of non-catalytic pyrolysis, many studies have
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determined the effects of varying biomass composition on the pyrolysis product yield and
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distribution. Pyrolysis oil, bio-char and gaseous products have been shown to respond to the
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ratios of the major biomass components such as, cellulose, hemicellulose and lignin17-18 as well
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as lipids19, proteins20 and inorganic elements.17,21-25 The effects of inorganic components
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(collectively known as ash) of the biomass have been especially well studied for non-catalytic
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pyrolysis. Their main influence is found to be associated with the breakdown of the
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carbohydrate fraction of biomass. For example in cellulose pyrolysis, overall ash content has
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been shown to cause a change in the chemical mechanisms of thermal decomposition towards
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increases in fragmentation reactions23 that enrich the production of permanent gases, acetol and
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hydroxyacetaldehyde and lead to a lesser formation of the dehydrated cellulose monomer,
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levoglucosan. Specifically, alkali metal salts have been determined to be the main catalyst
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leading to this effect.23 There has been little work on extending these studies to the effects
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inorganic salts have on catalytic pyrolysis. Recently our group demonstrated that some inorganic
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elements accumulate rapidly on HZSM-5 during CFP thereby affecting the performance of the
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catalyst over time.18 However, the effects of the presence of the salts on the incipient CFP
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chemistry have not been elucidated either via biomass doping or comparing results over a wide
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biological range of the essential minerals of biomass rather than biomass components.
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In this contribution we have studied a set of 10 biomass samples, varying genotypes of
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switchgrass, sorghum and miscanthus grown in soils treated with two amounts of poultry manure
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fertilizer. The use of the different genotypes and growing conditions has provided a set of 20
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samples with a wide enough range of inorganic compositions to advise this effort. We have
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performed CFP over HZSM-5 using pyrolysis-gas chromatography with mass spectrometry (py-
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GC/MS) to correlate the carbon conversion and selectivities to aromatic hydrocarbons with
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compositional traits. Unlike studies that used model components or washed biomass samples to
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study the effect of added salts, in this contribution we have studied untreated biomass samples so
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mineral content is biologically incorporated and present in natural ranges and relationships with
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the organic material. Therefore, competing effects of various natural components are observed.
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Furthermore, we have related the observations on the effects of mineral contents, specifically
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potassium and iron, to their influence on the chemical pathways of aromatic hydrocarbon
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production via CFP over HZSM-5.
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Materials and Methods
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Biomass Characterization. Compositional data on the biomass samples used in this study are
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provided in Table 1. CHNS elemental analysis was determined using a Thermo Falsh EA1112
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elemental analyzer. Water content was determined by drying at 105 °C for 4h and total ash was
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determined by heating in a muffle furnace in air at 650 °C for 6h. Oxygen content was then
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determined by difference accounting for C,H,N,S, ash and water. Mineral components were
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determined by Inductive Coupled Plasma (ICP) using a Thermo Scientific iCAP6300 Duo ICP
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Spectrometer. Standards for ICP atomic emission spectroscopy measurements of Ca, Cu, Fe, K,
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Mg, Na and P were purchased as from Inorganic Ventures, Inc. as 1000 ppm solution in dilute
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HNO3. The standards were diluted using DI water further purified by a Barnstead International
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E-Pure water purification, model #D4641 to make four-point calibrations for each element.
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Biomass samples for ICP analysis were ashed for 4 h at 800 °C in a muffle furnace in an air
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atmosphere. After cooling in a desiccator, ash samples were dissolved in concentrated HCl (4
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mL/200 mg sample) by overnight stirring. Samples were then diluted to 100 mL using DI water
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purified as above. Calibrations were quality checked after every 10 samples run on the
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instrument. Recovery fractions of individual metals (Xm) were determined as Xm=([M]p*Xp
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)/([M]sg*Xsg) where [M]p and [M]sg are the concentration of that metal in the biomass and Xp
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and Xsg are the biomass.
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Pyrolysis Experiments. Micropyrolysis was performed by a Frontier Lab Double-Shot micro
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pyrolyzer PY-3030iD with a Frontier Lab Auto-Shot Sampler AS-1020E attached to a gas
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chromatograph, Shimadzu GC-2010. Detection of products was achieved using a Shimadzu
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GCMS-QP2010S mass spectrometer. The interface temperature of the micropyrolyzer was set to
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300°C and the furnace was set to 500°C. A 1:5 ratio biomass to catalyst ratio was used for
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catalytic pyrolysis. Catalyst used in this analysis was HZSM-5, activated from NH4ZSM-5
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(CBV-2314; 23 SiO2:Al2O3) purchased from Zeolyst International (Conshohocken, PA).
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Activation was achieved by heating in a muffle furnace in air at 650 °C for 4 h. A sample size of
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~0.2mg biomass and 1.0 mg catalyst (catalyst added on top of biomass) was subjected to a
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single-shot pyrolysis at 500°C for 30 seconds using stainless steel cups (disposable eco-cup LF;
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Frontier Laboratories) followed by separation on the GC. Analysis of condensable gas was
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performed on a RTX-1701 60 m × 0.25 mm GC fused silica capillary column with a 0.25 µm
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film thickness. The oven for the GC column was set at an initial temperature of 45°C for 5 min
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followed by a ramp rate of 3°C min-1 to 280 °C and held for 20 min for a total run time of 102
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min. The injector temperature was at 250 °C with a split ratio of 90:1 and a helium flow rate of
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1 mL min-1. For the analysis of non-condensable gases, identical experiments were performed
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with a different column and GC method. A split ratio of 100 and a CP-PoraBOND Q, 25 m ×
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0.25 mm fused silica capillary column was used (Varian, Palo Alto, CA). The oven for the GC
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column was set at 35 °C for 3 min followed by a ramp rate of 5 °C min-1 up to 150°C then 10 °C
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min-1 to 250 °C and held for 45 min for a total run time of 81 min. Quantitative analysis of
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individual chemical products was done by the external standard method, using authentic samples
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to generate calibration curves.
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All pyrolysis data was collected in triplicate for all analyses in order to provide adequate
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replication for statistical analysis. All data collected was analyzed in SAS ® version 9.3 (SAS
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Institute Inc., Cary, NC) at a critical α level of 0.05. PROC UNIVARIATE was used to check for
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normality of distribution using Kolmogorov D and Shapiro-Wilk’s statistic W and no
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transformation was required. A two-way ANOVA was performed with 10 genotypes and two
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trials (LPM and HPM) using PROC GLM to test for significance by both genotype and trial and
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their interaction. PROC CORR was used for correlations of the averaged data by genotype from
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each trial (n=20) to compare all variables measured. Correlations were also performed on
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switchgrass only (n=10) and sorghum only (n=8).
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Results and Discussion
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Catalytic pyrolysis over HZSM-5 catalysts converts the oxygenated primary pyrolysis
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vapors to a product mixture rich in aromatic hydrocarbons and olefins.7-16 The carbon yields of
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aromatic hydrocarbons produced from the CFP of the biomass samples used in this study are
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provided in Table 2 and the carbon yields of non-condensable gas products including olefins
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(ethylene and propylene) are provided in Table 3. The entire set of data was subjected to
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statistical analysis as described above to compare the yields and selectivities with the
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composition of the biomass (p < 0.05 considered statistically significant). The analysis was
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performed on the whole set and also sub-sets by species, i.e. switchgrass and sorghum samples
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only. The Pearson correlation constants (r) and p values for the entire matrix of compositional
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traits and pyrolysis products are provided in the supporting information, Tables S1-S16.
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Variation in the organic composition of the biomass samples, i.e. cellulose, hemicellulose and lignin content26 had little to no correlation with the yields of the aromatic or gaseous
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products via CFP (Table S1). This is because the effects of the somewhat narrow variations in
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organic content on the chemistry were masked by the larger effects of the inorganic salts present
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in the biomass. This has been previously seen for non-catalytic pyrolysis of feedstocks with high
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ash content, where expected trends with cell wall compositions were overridden by the effects of
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ash components.17 We therefore focused our analysis on the inorganic portion of the biomass
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composition.
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Total ash contents of the samples ranged from 3.3 to 8.6 wt% for the entire set of
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genotypes studied. The sorghum samples tended to have higher concentrations of total ash,
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potassium and phosphorus (elements which were particularly well correlated with product
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yields) than did the switchgrass or miscanthus samples. Selected relevant correlations of ash
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and CFP products are shown graphically in Figure 1. Under the conditions used in these
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experiments, total carbon yields of aromatics (defined for this analysis as BTEX and
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naphthalenes) ranged from 15 to 16% for this sample set while BTEX carbon yields were in the
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9-12% range. For the overall sample set neither the total aromatic hydrocarbon yields nor yields
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of BTEX alone were significantly correlated with total ash content (Figures 1a and 1b, Table
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S2). However, total ash was positively correlated with yields of o-xylene (r = 0.527, p = 0.017)
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and negatively correlated with yields of naphthalene (r = -0.458, p = 0.042) and methyl
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naphthalene (r = -0.485, p = 0.030).
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= 0.551, p = 0.012, Figure 1c) were also positively correlated with ash content in CFP over
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HZSM-5 (Table S3). The varying effects on the yields have consequences for the chemical
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selectivity among the aromatic products. Aromatic hydrocarbon selectivities are provided in
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Table 4. The selectivity for the proportion of carbon in BTEX out of all of the carbon in the
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aromatic hydrocarbon products studied ranged from 70.9 to 78.2%, and was positively correlated
The yields of propylene (r = 0.561, p = 0.010), and CO2 (r
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with ash content (Table S4, r = 0.639, p = 0.002) as shown in Figure 2a. BTEX is more desirable
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than naphthalene or other PAHs for most fuels and petrochemical applications. Furthermore, the
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selectivity within the BTEX product is important. For example, alkyl benzenes are more
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desirable fuel components than benzene itself, due to the latter’s toxicity among other factors. It
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is worth noting that for gasoline, benzene concentrations are capped at 0.62 vol%, meaning high
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benzene feeds would need to be alkylated before they are used in gasoline blends.27 The benzene
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selectivity within the BTEX portion of the CFP product ranged from 15.1 to 17.6% for the
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genotypes studied. Ash content correlated negatively with the selectivity for benzene (r = -
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0.598, p = 0.005, Figure 2b), and hence positively correlated with the more desirable alkylated
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benzenes as a group (toluene, xylenes and ethyl benzenes).
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When we restricted the analysis to only the switchgrass samples for which a narrow range
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of ash content was exhibited, the strongest correlations we observed were with the gaseous
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products of CFP over HZSM-5. As illustrated in Figure 1, there are strong positive correlations
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between ash content and conversion to both the carbon oxides ( CO2 [r = 0.681, p = 0.031,
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Figure 1c]), CO [r = 0.810, p = 0.004, Figure 1d] and olefins (C2H4 [r = 0.707, p = 0.022, Figure
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1e] and C3H6 [r = 0.797, p = 0.006, figure 1f ], Table S5). There are also positive correlations
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between ash content and BTEX (r = 0.714, p = 0.020) as well as with most of its individual
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components when only the switchgrass samples are considered (Table S6). However, the
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aromatic selectivity trends that were observed over the entire sample set do not hold true for the
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switchgrass or sorghum subsets samples (Tables S7-S8); likely because the effects are less
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important over the narrower ash ranges of the subsets as compared to the overall sample set. For
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the non-condensable gases, there was a strong positive correlation between ash and methane
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production (r = 0.740, p = 0.036), but not with the yield of other gases when considering only the
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sorghum samples (Table S9).
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These varying correlations with ash on carbon conversion to various products by CFP of
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the biomass samples having dissimilar compositions suggest that there might be points at which
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higher levels of ash have no additional effects, and also that the mineral ash components could
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be exhibiting competing effects. Therefore, the results were analyzed for trends with several
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different inorganic elements that comprise the ash. Our results indicate that the strongest mineral
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effects on CFP products were exhibited by potassium, phosphorous and iron. However,
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potassium and phosphorous levels were highly correlated with each other26, meaning that the
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correlations seen with one could be due to the effect of the other. Given its higher levels and
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previously described effects on thermochemical processes23-25 it is likely that potassium is the
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more active of the two elements. Potassium levels ranged from 1,700 ppm (miscanthus) to
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18,000 ppm (sorghum) in our data pool. The potassium levels were generally higher for
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sorghum (7300 – 18,000 ppm) than for switchgrass (1300 – 7000 ppm). In Figure 3 we present
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selected relevant correlations between CFP yields and biomass K content. The plots are made
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over the entire sample set to take advantage of the wide range of K exhibited. Over the entire
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sample set (Table S2) negative trends were observed between K content and carbon conversion
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to total aromatics (r = -0.560, p = 0.011, Figure 2a) and also to BTEX alone (r = 0.535, p =
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0.015, Figure 2b). Individually, benzene (r = -0.629, p = 0.006) production was also negatively
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correlated to K content but production of ethyl benzene and xylenes were not significantly
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correlated to K. The negative correlation between K and production of naphthalene (r = -0.764,
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p < 0.001, Figure 2d) and 2-methylnapthalene (r = -0.776, p =
