Analysis of Levulinic Acid

The DIBANET process chain, as a result of its patented pre-treatment stage, has significantly increased the yields of levulinic acid, formic acid, and furfural beyond what was considered to be the state of the art. By fractionating lignocellulosic biomass into its three main polymers (cellulose, hemicellulose, lignin) it has also allowed for lignin to be recovered and sold as a higher-value product. These developments have meant that the amount of acid hydrolysis residues (AHRs) that have been produced are significantly (up to 88%) less than in the Biofine process. These AHRs are required to provide process heat for DIBANET. Direct combustion is the most efficient means for doing this. If such combustion does not occur and the AHRs are instead used in other processes, e.g. pyrolysis and gasification, then more biomass will need to be purchased to fuel the core DIBANET process. The AHRs have not been proven to be superior to virgin biomass when put through these thermochemical processes. Indeed, many of the results from DIBANET Work Package 4 indicate the opposite. Hence, given that DIBANET, and the modelling of its optimal configuration, is designed on the basis of an integrated process, centred on the core element of the acid hydrolysis of biomass, then combustion is the only viable end use for the AHRs. Given that realisation, the focus of this modelling Deliverable is on what the optimal configuration of the process chain would be regarding the three core stages (pretreatment, hydrolysis, and the esterification of levulinic acid with ethanol). It has been demonstrated that a scenario incorporating only the first stage can be profitable in its own right and allow for commercial development at much lower capital costs. In this instance bagasse is a much more attractive feedstock, compared with Miscanthus, due to its higher pentose content.

Integrating the second stage increases capital costs but improves the net present value. The esterification step is somewhat capital intensive but an integrated DIBANET biorefinery that incorporates all three stages can still be highly profitable providing the furfural is sold at its current market price and the lignin is sold rather than used as a fuel for process needs. Indeed, the DIBANET process should not be considered only in the context of biofuels but as a true biorefinery that produces lower value fuels (e.g. ethyl-levulinate) in addition to high value chemicals and bio-products (e.g. furfural and lignin).

The energy and carbon balances of the various DIBANET scenarios have been investigated and are highly positive with values significantly superior to those for the energy-intensive Biofine process. A socioeconomic survey has also been carried out and has shown that there can be a positive effect on employment, both direct and indirect, particularly when Miscanthus is used as the feedstock. The DIBANET integrated process also holds up well when its environmental and social performances are ranked for a range of important parameters.

The development of the core DIBANET IP towards commercial deployment appears to be warranted, based on data provided from the models developed. Indeed, these models present possible scenarios whereby even demonstration-scale DIBANET facilities could operate at significant profits and provide healthy returns on the capital invested.

The processing of lignocellulosic materials in modern biorefineries will allow for the production of transport fuels and platform chemicals that could replace petroleum-derived products. However, there is a critical lack of relevant detailed compositional information regarding feedstocks relevant to Ireland and Irish conditions. This research has involved the collection, preparation, and the analysis, with a high level of precision and accuracy, of a large number of biomass samples from the waste and agricultural sectors. Not all of the waste materials analysed are considered suitable for biorefining; for example the total sugar contents of spent mushroom composts are too low. However, the waste paper/cardboard that is currently exported from Ireland has a chemical composition that could result in high biorefinery yields and so could make a significant contribution to Ireland’s biofuel demands.

Miscanthus was focussed on as a major agricultural feedstock. A large number of plants have been sampled over the course of the harvest window (October to April) from several sites. These have been separated into their anatomical fractions and analysed. This has allowed observations to be made regarding the compositional trends observed within plants, between plants, and between harvest dates. Projections are made regarding the extents to which potential chemical yields may vary. For the DIBANET hydrolysis process that is being developed at the University of Limerick, per hectare yields of levulinic acid from Miscanthus could be 20% greater when harvested early compared with a late harvest.

The wet-chemical analysis of biomass is time-consuming. Near infrared spectroscopy (NIRS) has been developed as a rapid primary analytical tool with separate quantitative models developed for the important constituents of Miscanthus, peat, and (Australian) sugarcane bagasse. The work has demonstrated that accurate models are possible, not only for dry homogenous samples, but also for wet heterogeneous samples. For glucose (cellulose) the root mean square error of prediction (RMSEP) for wet samples is 1.24% and the R2 for the validation set ( ) is 0.931. High accuracies are even possible for minor analytes; e.g. for the rhamnose content of wet Miscanthus samples the RMSEP is 0.03% and the is 0.845. Accurate models have also been developed for pre-treated Miscanthus samples and are discussed. In addition, qualitative models have been developed. These allow for samples to be discriminated for on the basis of plant fraction, plant variety (giganteus/non-giganteus), harvest-period (early/late), and stand-age (one-year/older).

Quantitative NIRS models have also been developed for peat, although the heterogeneity of this feedstock means that the accuracies tend to be lower than for Miscanthus. The development of models for sugarcane bagasse has been hindered, in some cases, by the limited chemical variability between the samples in the calibration set. Good models are possible for the glucose and total sugars content, but the accuracy of other models is poorer. NIRS spectra of Brazilian bagasse samples have been projected onto these models, and onto those developed for Miscanthus, and the Miscanthus models appear to provide a better fit than the Australian bagasse models.