TY - JOUR
T1 - Prediction of pyrolyzate yields by response surface methodology
T2 - A case study of cellulose and polyethylene co-pyrolysis
AU - Xie, Shengyu
AU - Kumagai, Shogo
AU - Kameda, Tomohito
AU - Saito, Yuko
AU - Yoshioka, Toshiaki
N1 - Funding Information:
This work was supported by JSPS KAKENHI grant number 19H04306 and JST FOREST Program grant number JPMJFR206U. Shengyu Xie was supported by the Chinese Scholarship Council (CSC). Authorship contribution statement. Shengyu Xie: Pyrolysis experiments, product analysis, evaluation of the results by RSM, and drafting of the manuscript. Shogo Kumagai: Conceptualization, supervision, and drafting of the manuscript. Tomohito Kameda, Yuko Saito, and Toshiaki Yoshioka: Drafting of the introduction. All authors reviewed the manuscript.
Funding Information:
This work was supported by JSPS KAKENHI grant number 19H04306 and JST FOREST Program grant number JPMJFR206U. Shengyu Xie was supported by the Chinese Scholarship Council (CSC).
Publisher Copyright:
© 2021 Elsevier Ltd
PY - 2021/10
Y1 - 2021/10
N2 - There are numerous combinations of biomass, plastic, and co-pyrolysis conditions. The presence of synergies, which make pyrolyzate distribution more complex, has been supported by research. In this study, the potential of response surface methodology (RSM) to predict the pyrolyzate yields affected by synergies during co-pyrolysis (500–700 °C) of cellulose and polyethylene was investigated, beyond gas, oil, and char yields. The results indicated that co-pyrolysis promoted liquid and C5–28 hydrocarbon production with increasing temperature. The quadratic model could predict the total gas, CO, CO2, and liquid yields, including the synergy. The cubic model could predict the levoglucosan and C5–28 hydrocarbon yields due to various synergies under different conditions. The linear model was suitable for the char yield distribution without interaction. Thus, this study reveals that RSM has a significant potential to predict pyrolyzate yields, enabling co-pyrolysis condition setting to maximize the desired product recovery with the fewest experiments.
AB - There are numerous combinations of biomass, plastic, and co-pyrolysis conditions. The presence of synergies, which make pyrolyzate distribution more complex, has been supported by research. In this study, the potential of response surface methodology (RSM) to predict the pyrolyzate yields affected by synergies during co-pyrolysis (500–700 °C) of cellulose and polyethylene was investigated, beyond gas, oil, and char yields. The results indicated that co-pyrolysis promoted liquid and C5–28 hydrocarbon production with increasing temperature. The quadratic model could predict the total gas, CO, CO2, and liquid yields, including the synergy. The cubic model could predict the levoglucosan and C5–28 hydrocarbon yields due to various synergies under different conditions. The linear model was suitable for the char yield distribution without interaction. Thus, this study reveals that RSM has a significant potential to predict pyrolyzate yields, enabling co-pyrolysis condition setting to maximize the desired product recovery with the fewest experiments.
KW - Cellulose
KW - Co-pyrolysis
KW - Polyethylene
KW - Pyrolyzate prediction
KW - Response surface methodology
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U2 - 10.1016/j.biortech.2021.125435
DO - 10.1016/j.biortech.2021.125435
M3 - Article
C2 - 34175770
AN - SCOPUS:85108568862
SN - 0960-8524
VL - 337
JO - Bioresource Technology
JF - Bioresource Technology
M1 - 125435
ER -