Predicting moisture and bark content of woody biomass using visible light spectroscopy

Two of the most important characteristics of woody biomass to consider when evaluating their suitability for use in bio-energy applications are moisture content and ash content. The industry has long been seeking a technology capable of rapidly and economically characterizing feedstock, however such asolution is currently not available. This project will lay the groundwork for a potential solution that predicts these important characteristics based on the color of the feedstock. Using spectrophotometry, the study of how an object absorbs the visible region of the electromagnetic spectrum, this project will attempt to uncover any relationships between the color of woody feedstock and its moisture and bark content. Industry sponsor Cogent Industrial Technologies is a consulting service provider who has recently decided to expand its reach to the emerging bio-energy market. Through its involvement in the project, Cogent will gain valuable insight to the ways various feedstock characteristics affect each step of the energy pathway and to the development of this new technology.

Faculty Supervisor:

Dr. Shahab Sokhansanj

Student:

Asa Parker

Partner:

Cogent Industrial Technologies

Discipline:

Engineering - chemical / biological

Sector:

Environmental industry

University:

University of British Columbia