title: Optimization of biomass torrefaction conditions by the gain and loss method and regression model analysis.
abstract: In this study, the optimal conditions for biomass torrefaction were determined by comparing the gain of energy content to the weight loss of biomass from the final products. Torrefaction experiments were performed at temperatures ranging from 220 to 280°C using 20-80min reaction times. Polynomial regression models ranging from the 1st to the 3rd order were used to determine a relationship between the severity factor (SF) and calorific value or weight loss. The intersection of two regression models for calorific value and weight loss was determined and assumed to be the optimized SF. The optimized SFs on each biomass ranged from 6.056 to 6.372. Optimized torrefaction conditions were determined at various reaction times of 15, 30, and 60min. The average optimized temperature was 248.55°C in the studied biomass when torrefaction was performed for 60min.
authors.affiliation: Division of Wood Chemistry and Microbiology, Department of Forest Products, Korea Forest Research Institute, Seoul 130-712, Republic of Korea; Forest and Environment, Center for International Forestry Research, Bogor 16115, Indonesia.
authors.forename: Soo Min
authors.initials: SM
authors.lastname: Lee
authors.affiliation: Department of Forest Products and Technology, College of Agriculture and Life Sciences, Chonnam National University, Gwang-ju 500-757, Republic of Korea. Electronic address: ljw43376@chonnam.ac.kr.
authors.forename: Jae-Won
authors.initials: JW
authors.lastname: Lee
mesh_terms: D000465:Algorithms; D020650:Combinatorial Chemistry Techniques / Q000379:methods*; D003198:Computer Simulation; D006358:Hot Temperature; D015233:Models, Statistical; D010936:Plant Extracts / Q000737:chemistry*; D012044:Regression Analysis; D013818:Thermogravimetry / Q000379:methods*; D014197:Trees / Q000737:chemistry*; D014934:Wood / Q000737:chemistry*
chemical_list: D010936:Plant Extracts
keywords: Biomass; Gain and Loss; Optimization; Regression analysis; Torrefaction