Long-term variability in sugarcane bagasse feedstock compositional methods: sources and magnitude of analytical variability.

BACKGROUND: In an effort to find economical, carbon-neutral transportation fuels, biomass feedstock compositional analysis methods are used to monitor, compare, and improve biofuel conversion processes. These methods are empirical, and the analytical variability seen in the feedstock compositional data propagates into variability in the conversion yields, component balances, mass balances, and ultimately the minimum ethanol selling price (MESP). We report the average composition and standard deviations of 119 individually extracted National Institute of Standards and Technology (NIST) bagasse [Reference Material (RM) 8491] run by seven analysts over 7 years. Two additional datasets, using bulk-extracted bagasse (containing 58 and 291 replicates each), were examined to separate out the effects of batch, analyst, sugar recovery standard calculation method, and extractions from the total analytical variability seen in the individually extracted dataset. We believe this is the world's largest NIST bagasse compositional analysis dataset and it provides unique insight into the long-term analytical variability. Understanding the long-term variability of the feedstock analysis will help determine the minimum difference that can be detected in yield, mass balance, and efficiency calculations. RESULTS: The long-term data show consistent bagasse component values through time and by different analysts. This suggests that the standard compositional analysis methods were performed consistently and that the bagasse RM itself remained unchanged during this time period. The long-term variability seen here is generally higher than short-term variabilities. It is worth noting that the effect of short-term or long-term feedstock compositional variability on MESP is small, about $0.03 per gallon. CONCLUSIONS: The long-term analysis variabilities reported here are plausible minimum values for these methods, though not necessarily average or expected variabilities. We must emphasize the importance of training and good analytical procedures needed to generate this data. When combined with a robust QA/QC oversight protocol, these empirical methods can be relied upon to generate high-quality data over a long period of time.

Compositional Analysis of Biomass Reference Materials: Results from an Interlaboratory Study.

Biomass compositional methods are used to compare different lignocellulosic feedstocks, to measure component balances around unit operations and to determine process yields and therefore the economic viability of biomass-to-biofuel processes. Four biomass reference materials (RMs NIST 8491-8494) were prepared and characterized, via an interlaboratory comparison exercise in the early 1990s to evaluate biomass summative compositional methods, analysts, and laboratories. Having common, uniform, and stable biomass reference materials gives the opportunity to assess compositional data compared to other analysts, to other labs, and to a known compositional value. The expiration date for the original characterization of these RMs was reached and an effort to assess their stability and recharacterize the reference values for the remaining material using more current methods of analysis was initiated. We sent samples of the four biomass RMs to 11 academic, industrial, and government laboratories, familiar with sulfuric acid compositional methods, for recharacterization of the component reference values. In this work, we have used an expanded suite of analytical methods that are more appropriate for herbaceous feedstocks, to recharacterize the RMs' compositions. We report the median values and the expanded uncertainty values for the four RMs on a dry-mass, whole-biomass basis. The original characterization data has been recalculated using median statistics to facilitate comparisons with this data. We found improved total component closures for three out of the four RMs compared to the original characterization, and the total component closures were near 100 %, which suggests that most components were accurately measured and little double counting occurred. The major components were not statistically different in the recharacterization which suggests that the biomass materials are stable during storage and that additional components, not seen in the original characterization, were quantified here.

Effect of corn stover compositional variability on minimum ethanol selling price (MESP).

A techno-economic sensitivity analysis was performed using a National Renewable Energy Laboratory (NREL) 2011 biochemical conversion design model varying feedstock compositions. A total of 496 feedstock near infrared (NIR) compositions from 47 locations in eight US Corn Belt states were used as the inputs to calculate minimum ethanol selling price (MESP), ethanol yield (gallons per dry ton biomass feedstock), ethanol annual production, as well as total installed project cost for each composition. From this study, the calculated MESP is $2.20 ± 0.21 (average ± 3 SD) per gallon ethanol.

Separation and quantification of microalgal carbohydrates.

Structural carbohydrates can constitute a large fraction of the dry weight of algal biomass and thus accurate identification and quantification is important for summative mass closure. Two limitations to the accurate characterization of microalgal carbohydrates are the lack of a robust analytical procedure to hydrolyze polymeric carbohydrates to their respective monomers and the subsequent identification and quantification of those monosaccharides. We address the second limitation, chromatographic separation of monosaccharides, here by identifying optimum conditions for the resolution of a synthetic mixture of 13 microalgae-specific monosaccharides, comprised of 8 neutral, 2 amino sugars, 2 uronic acids and 1 alditol (myo-inositol as an internal standard). The synthetic 13-carbohydrate mix showed incomplete resolution across 11 traditional high performance liquid chromatography (HPLC) methods, but showed improved resolution and accurate quantification using anion exchange chromatography (HPAEC) as well as alditol acetate derivatization followed by gas chromatography (for the neutral- and amino-sugars only). We demonstrate the application of monosaccharide quantification using optimized chromatography conditions after sulfuric acid analytical hydrolysis for three model algae strains and compare the quantification and complexity of monosaccharides in analytical hydrolysates relative to a typical terrestrial feedstock, sugarcane bagasse.

Accurate and reliable quantification of total microalgal fuel potential as fatty acid methyl esters by in situ transesterification.

In the context of algal biofuels, lipids, or better aliphatic chains of the fatty acids, are perhaps the most important constituents of algal biomass. Accurate quantification of lipids and their respective fuel yield is crucial for comparison of algal strains and growth conditions and for process monitoring. As an alternative to traditional solvent-based lipid extraction procedures, we have developed a robust whole-biomass in situ transesterification procedure for quantification of algal lipids (as fatty acid methyl esters, FAMEs) that (a) can be carried out on a small scale (using 4-7 mg of biomass), (b) is applicable to a range of different species, (c) consists of a single-step reaction, (d) is robust over a range of different temperature and time combinations, and (e) tolerant to at least 50% water in the biomass. Unlike gravimetric lipid quantification, which can over- or underestimate the lipid content, whole biomass transesterification reflects the true potential fuel yield of algal biomass. We report here on the comparison of the yield of FAMEs by using different catalysts and catalyst combinations, with the acid catalyst HCl providing a consistently high level of conversion of fatty acids with a precision of 1.9% relative standard deviation. We investigate the influence of reaction time, temperature, and biomass water content on the measured FAME content and profile for 4 different samples of algae (replete and deplete Chlorella vulgaris, replete Phaeodactylum tricornutum, and replete Nannochloropsis sp.). We conclude by demonstrating a full mass balance closure of all fatty acids around a traditional lipid extraction process.

Compositional analysis of lignocellulosic feedstocks. 1. Review and description of methods.

As interest in lignocellulosic biomass feedstocks for conversion into transportation fuels grows, the summative compositional analysis of biomass, or plant-derived material, becomes ever more important. The sulfuric acid hydrolysis of biomass has been used to measure lignin and structural carbohydrate content for more than 100 years. Researchers have applied these methods to measure the lignin and structural carbohydrate contents of woody materials, estimate the nutritional value of animal feed, analyze the dietary fiber content of human food, compare potential biofuels feedstocks, and measure the efficiency of biomass-to-biofuels processes. The purpose of this paper is to review the history and lineage of biomass compositional analysis methods based on a sulfuric acid hydrolysis. These methods have become the de facto procedure for biomass compositional analysis. The paper traces changes to the biomass compositional analysis methods through time to the biomass methods currently used at the National Renewable Energy Laboratory (NREL). The current suite of laboratory analytical procedures (LAPs) offered by NREL is described, including an overview of the procedures and methodologies and some common pitfalls. Suggestions are made for continuing improvement to the suite of analyses.

Compositional analysis of lignocellulosic feedstocks. 2. Method uncertainties.

The most common procedures for characterizing the chemical components of lignocellulosic feedstocks use a two-stage sulfuric acid hydrolysis to fractionate biomass for gravimetric and instrumental analyses. The uncertainty (i.e., dispersion of values from repeated measurement) in the primary data is of general interest to those with technical or financial interests in biomass conversion technology. The composition of a homogenized corn stover feedstock (154 replicate samples in 13 batches, by 7 analysts in 2 laboratories) was measured along with a National Institute of Standards and Technology (NIST) reference sugar cane bagasse, as a control, using this laboratory's suite of laboratory analytical procedures (LAPs). The uncertainty was evaluated by the statistical analysis of these data and is reported as the standard deviation of each component measurement. Censored and uncensored versions of these data sets are reported, as evidence was found for intermittent instrumental and equipment problems. The censored data are believed to represent the "best case" results of these analyses, whereas the uncensored data show how small method changes can strongly affect the uncertainties of these empirical methods. Relative standard deviations (RSD) of 1-3% are reported for glucan, xylan, lignin, extractives, and total component closure with the other minor components showing 4-10% RSD. The standard deviations seen with the corn stover and NIST bagasse materials were similar, which suggests that the uncertainties reported here are due more to the analytical method used than to the specific feedstock type being analyzed.

Rapid biomass analysis: new tools for compositional analysis of corn stover feedstocks and process intermediates from ethanol production.

New, rapid, and inexpensive methods that monitor the chemical composition of corn stover and corn stover-derived samples are a key element to enabling the commercialization of processes that convert stover to fuels and chemicals. These new techniques combine near infrared (NIR) spectroscopy and projection to latent structures (PLS) multivariate analysis to allow the compositional analysis of hundreds of samples in 1 d at a cost of about $10 each. The new NIR/PLS rapid analysis methods can also be used to support a variety of research projects that would have been too costly to pursue by traditional methods.