Microwave vacuum pyrolysis rapidly transforms bamboo into solid biofuel: Predicting fuel performances by response surface methodology

被引:1
|
作者
Gao, Qi [1 ,2 ]
Ni, Liangmeng [1 ,2 ]
Ren, Hao [1 ,2 ]
Su, Mengfu [1 ,2 ]
Rong, Shaowen [1 ,2 ]
Liu, Zhijia [1 ,2 ]
机构
[1] Int Ctr Bamboo & Rattan, Beijing 100102, Peoples R China
[2] Key Lab NFGA Beijing Bamboo & Rattan Sci & Technol, Beijing 100102, Peoples R China
关键词
Bamboo charcoal; Microwave pyrolysis; Fuel performances; Response surface methodology; WASTE BIOMASS; CARBONIZATION; BIOCHAR;
D O I
10.1016/j.renene.2024.121346
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Microwave vacuum pyrolysis presents significant advantages in biochar refining and industrial upgrading. In this study, bamboo charcoal (BC) was produced rapidly by microwave vacuum pyrolysis, the microwave pyrolysis and conventional pyrolysis characteristics of bamboo were compared, and the potential of response surface methodology (RSM) to predict the fuel performances was investigated. The results indicated that microwave pyrolysis significantly reduced the heating time, and also effectively lowered the threshold of thermal decomposition reaction. Besides, as the microwave power and radiation time rose, the fixed carbon, ash, higher heating value, energy density, and fuel ratio of BCs increased, while the yield, H/C, O/C, volatile, and energy yield decreased. The quadratic models have high correlation coefficients for these characteristics, which can be used for the prediction of subsequent BCs production. When the microwave power was 1666 W and the radiation time was 13.3 min, the prepared BC exhibited the highest yield while maintaining a fixed carbon content of over 85%. This research provided a green way for the transformation and upgrading of BCs industry, and also showed that the most cost-effective production strategy can be formulated through RSM.
引用
收藏
页数:11
相关论文
共 50 条
  • [41] Microwave-assisted In-situ catalytic co-pyrolysis of polypropylene and polystyrene mixtures: Response surface methodology analysis using machine learning
    Kamireddi, Dinesh
    Terapalli, Avinash
    Sridevi, Veluru
    Bai, M. Tukaram
    Surya, Dadi Venkata
    Rao, Chinta Sankar
    Jeeru, Lakshmana Rao
    JOURNAL OF ANALYTICAL AND APPLIED PYROLYSIS, 2023, 172
  • [42] Response Surface Methodology-Central Composite Design Optimization Sugarcane Bagasse Activated Carbon under Varying Microwave-Assisted Pyrolysis Conditions
    Chen, Xuexue
    Pei, Yunji
    Wang, Xinran
    Zhou, Wenlin
    Jiang, Li
    PROCESSES, 2024, 12 (03)
  • [43] Optimization of bio-oil production from microwave co-pyrolysis of food waste and low-density polyethylene with response surface methodology
    Neha, Shukla
    Remya, Neelancherry
    JOURNAL OF ENVIRONMENTAL MANAGEMENT, 2021, 297
  • [44] Modeling and Optimization of Microwave-Based Bio-Jet Fuel from Coconut Oil: Investigation of Response Surface Methodology (RSM) and Artificial Neural Network Methodology (ANN)
    Ong, Mei Yin
    Nomanbhay, Saifuddin
    Kusumo, Fitranto
    Raja Shahruzzaman, Raja Mohamad Hafriz
    Shamsuddin, Abd Halim
    ENERGIES, 2021, 14 (02)
  • [45] Response surface methodology (RSM)-based pyrolysis process parameter optimization for char generation from municipal solid waste (MSW) in a fixed bed reactor
    Saikia, Silvia
    Kalamdhad, Ajay S.
    SUSTAINABLE ENERGY TECHNOLOGIES AND ASSESSMENTS, 2023, 60
  • [46] Pilot-scale production of gasoline and diesel-like fuel from natural rubber scrap: Fractional condensation of pyrolysis vapors and optimization of pyrolysis parameters by using response surface methodology (RSM)
    Suiuay, Chokchai
    Katekaew, Somporn
    Senawong, Kritsadang
    Junsiri, Chaiyan
    Srichat, Aphichat
    Laloon, Kittipong
    FUEL, 2024, 364
  • [47] A new insight into high quality syngas production from co-pyrolysis of light bio-oil leached bamboo and heavy bio-oil using response surface methodology
    Zhuang, Xiaozhuang
    Gan, Ziyu
    Chen, Dengyu
    Cen, Kehui
    Ba, Yuping
    Jia, Dongxia
    FUEL, 2022, 324
  • [48] Multi-objective optimization of diesel engine performances and exhaust emissions characteristics of Hermetia illucens larvae oil-diesel fuel blends using response surface methodology
    Kamarulzaman, Mohd Kamal
    Abdullah, Adam
    ENERGY SOURCES PART A-RECOVERY UTILIZATION AND ENVIRONMENTAL EFFECTS, 2025, 47 (01) : 2952 - 2965
  • [49] Optimization of process parameters of Lagerstroemia speciosa seed hull pyrolysis using a combined approach of Response Surface Methodology (RSM) and Artificial Neural Network (ANN) for renewable fuel production
    Nawaz, Ahmad
    Kumar, Pradeep
    BIORESOURCE TECHNOLOGY REPORTS, 2022, 18
  • [50] Raw and processed data set for optimization of bio-oil production from microwave co-pyrolysis of food waste and low-density polyethylene with response surface methodology
    Neha, Shukla
    Remya, Neelancherry
    DATA IN BRIEF, 2022, 42