Abstract
Lignocellulosic agricultural side products like wheat straw are widely seen as an important contribution to a sustainable future economy. However, the optimization of biorefinery processes, especially the pretreatment step, is crucial for an economically viable biorefinery. The monitoring of this pretreatment process in terms of delignification and the generation of the fermentation inhibitors acetic acid, furfural, and hydroxymethylfurfural (HMF) is essential in order to adapt the process parameters for a desired outcome and an economical operation. However, traditional wet chemistry methods are time-consuming and not suitable for on-line process monitoring. Therefore, UV-Vis spectroscopy in combination with partial least-squares regression was used for the determination of the concentrations of lignin, acetic acid, furfural, and HMF. Five different data blocks with increasing amounts of impurities were investigated to evaluate the influence of the inevitable impurities on the calibration models. Lignin showed a good prediction accuracy with 95% tolerance intervals between ±0.46 to ±1.6 mg/L for concentrations up to 30 mg/L. Also, the other components could be predicted with a sufficient accuracy for on-line process monitoring. A satisfactory calibration can be obtained with 10 to 20 reference samples valid at process temperatures between 160 °C and 180 °C.
Highlights
Many petrochemicals are produced from conventional crude oil-fed refineries, whereas it is anticipated that in the future, many products and chemicals will be produced from biorefineries fed with lignocellulosic biomass such as agricultural residuals [1]
Lignin, as one of the three main components of lignocellulosic biomass, is currently underutilized and mainly used as an energy source, whereas it is anticipated to improve the economics of a biorefinery [3]
partial least-squares (PLS) models have been developed for the estimation of the concentrations of lignin, acetic acid, HMF, and furfural from UV-Vis data
Summary
Many petrochemicals are produced from conventional crude oil-fed refineries, whereas it is anticipated that in the future, many products and chemicals will be produced from biorefineries fed with lignocellulosic biomass such as agricultural residuals [1]. A biorefinery approach involves multi-step processes in which the first step, subsequent to the feedstock selection, typically involves treating the biomass to pre-separate the main components and to make it more amenable for further processing [4] This step is conventionally referred to as pretreatment. Compared to other pretreatment technologies, the organosolv process, used in this work, extracts relatively pure, low-molecular-weight lignin from biomass. This lignin shows a minimum of carbohydrate and mineral impurities and facilitates lignin applications with a higher value than heat and power generation [5]. PLS models have been developed for the estimation of the concentrations of lignin, acetic acid, HMF, and furfural from UV-Vis data. The main focus of this work is, on monitoring the pretreatment process at nearly constant process parameters
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