Characterization of fast pyrolysis bio-oil properties by near-infrared spectroscopic data

• Pyrolysis transforms bulky and heterogeneous lignocellulosic biomass into more easily-handled oils that can be upgraded into bio-based transportation fuels. Existing systems for monitoring pyrolysis processes and characterizing their products rely on slow and time-consuming wet chemical analyses. On-line near-infrared (NIR) spectroscopy could potentially replace such analyses, providing real-time data and reducing costs. To test the usefulness of NIR methods in characterizing pyrolysis oils and processes, biomass from conifers, Salix, and reed canary grass was milled and pyrolyzed at 675, 750, and 775 °C. Two separate pyrolytic fractions (aerosol and condensed) were produced in each experiment, and NIR spectra were collected for each fraction. Multivariate modelling of the resulting data clearly showed that the samples’ NIR spectra could be used to accurately predict important properties of the pyrolysis oils such as their energy values, main organic element (C, H and O) contents, and water content. The spectra also contained predictive information on the samples’ origins, fraction, and temperature treatment, demonstrating the potential of on-line NIR techniques for monitoring pyrolytic production processes and characterizing important properties of pyrolytic oils from lignocellulosic biomass.

Subject headings

NATURVETENSKAP  -- Kemi -- Fysikalisk kemi (hsv//swe)

NATURAL SCIENCES  -- Chemical Sciences -- Physical Chemistry (hsv//eng)

TEKNIK OCH TEKNOLOGIER  -- Industriell bioteknik -- Bioenergi (hsv//swe)

ENGINEERING AND TECHNOLOGY  -- Industrial Biotechnology -- Bioenergy (hsv//eng)

Keyword

OPLS-DA

PCA

Prediction

Pyrolysis cyclone

Reed canary grass

Wood-based biomass

Biomass

Chemical analysis

Cracking (chemical)

Forecasting

Water content

Fast pyrolysis bio-oil

Lignocellulosic biomass

Predictive information

Temperature treatments

Transportation fuels

Wet chemical analysis

Infrared devices

Publication and Content Type

ref (subject category)

art (subject category)