Uncertainty in techno-economic estimates of cellulosic ethanol production due to experimental measurement uncertainty

Abstract

BackgroundCost-effective production of lignocellulosic biofuels remains a major financial and technical challenge at the industrial scale. A critical tool in biofuels process development is the techno-economic (TE) model, which calculates biofuel production costs using a process model and an economic model. The process model solves mass and energy balances for each unit, and the economic model estimates capital and operating costs from the process model based on economic assumptions. The process model inputs include experimental data on the feedstock composition and intermediate product yields for each unit. These experimental yield data are calculated from primary measurements. Uncertainty in these primary measurements is propagated to the calculated yields, to the process model, and ultimately to the economic model. Thus, outputs of the TE model have a minimum uncertainty associated with the uncertainty in the primary measurements.ResultsWe calculate the uncertainty in the Minimum Ethanol Selling Price (MESP) estimate for lignocellulosic ethanol production via a biochemical conversion process: dilute sulfuric acid pretreatment of corn stover followed by enzymatic hydrolysis and co-fermentation of the resulting sugars to ethanol. We perform a sensitivity analysis on the TE model and identify the feedstock composition and conversion yields from three unit operations (xylose from pretreatment, glucose from enzymatic hydrolysis, and ethanol from fermentation) as the most important variables. The uncertainty in the pretreatment xylose yield arises from multiple measurements, whereas the glucose and ethanol yields from enzymatic hydrolysis and fermentation, respectively, are dominated by a single measurement: the fraction of insoluble solids (fIS) in the biomass slurries.ConclusionsWe calculate a $0.15/gal uncertainty in MESP from the TE model due to uncertainties in primary measurements. This result sets a lower bound on the error bars of the TE model predictions. This analysis highlights the primary measurements that merit further development to reduce the uncertainty associated with their use in TE models. While we develop and apply this mathematical framework to a specific biorefinery scenario here, this analysis can be readily adapted to other types of biorefining processes and provides a general framework for propagating uncertainty due to analytical measurements through a TE model.

Bio-jet fuel conversion technologies

“…The technoeconomic analysis of both biochemical and thermochemical processes [82,83] for ethanol production(from starch or cellulosic feedstocks) has been studied extensively [10,[82][83][84][85][86][87][88][89][90]. Most reports calculate a minimum selling price of the fuel based on a number of economic assumptions.…”

Diverse lignocellulosic feedstocks can achieve high field‐scale ethanol yields while providing flexibility for the biorefinery and landscape‐level environmental benefits

“…Although field‐scale ethanol yield is important for growers and breeders of lignocellulosic crops, process ethanol yield is more important for the biorefinery as it is a key factor affecting the minimum ethanol selling price (MESP), the main metric of biorefinery economic sustainability (Vicari et al, ). From our results, the range and variability in the process ethanol yield were highly dependent on the microbe used for fermentation.…”

“…Evaluation of the 2014 feedstocks showed that corn stover from that year had significant inhibition of xylose consumption that resulted in process yield losses for that feedstock. In another study, process ethanol yields from glucose and xylose contributed ~25% of the uncertainty in MESP calculations (Vicari et al, ). Efficient microbial utilization of both glucose and xylose will be important to achieve high process ethanol yields and low MESP.…”

Pre-senescence Harvest of Switchgrass Inhibits Xylose Utilization by Engineered Yeast

“…However, biomass yields and nutrient resorption are not the only factors that may influence choice of harvest date. Harvest date can influence process ethanol yields, which is important due to the potential influence on the minimum ethanol selling price and biorefinery economics (Vicari et al, 2012). Although previous studies have shown an effect of switchgrass harvest date on FIGURE 5 | Enzymatic hydrolysis conversions vary inconsistently with switchgrass harvest date, tend to be higher for high severity AFEX pretreatment, and contain a large proportion of oligomers.…”