当前位置: 首页 > 文章 > NaOH预处理甘蔗叶与猪粪-牛粪混合厌氧消化工艺参数优化 农业工程学报 2019 (5) 212-218
Position: Home > Articles > Parameter optimization in anaerobic co-digestion of NaOH pretreated sugarcane leaves and pig manure-dairy manure Transactions of the Chinese Society of Agricultural Engineering 2019 (5) 212-218

NaOH预处理甘蔗叶与猪粪-牛粪混合厌氧消化工艺参数优化

作  者:
罗娟;赵立欣;姚宗路;孟海波;李秀金;冯晶;袁海荣;于佳动;黄开明
单  位:
北京化工大学化学工程学院;农业农村部规划设计研究院农业农村部农业废弃物能源化利用重点实验室
关键词:
沼气;粪;甘蔗叶;猪粪;牛粪;混合厌氧消化
摘  要:
为探究Na OH预处理甘蔗叶与猪粪、牛粪混合厌氧消化性能,该文在研究甘蔗叶分别与猪粪、牛粪不同配比厌氧消化性能及动力学特性的基础上,采用Box-Behnken试验设计方法开展3种物料混合厌氧消化试验,并运用响应曲面法模拟和优化温度、混配比、C/N 3个工艺参数。结果表明,甘蔗叶与动物粪便混合厌氧消化时产生了协同作用,累积沼气产量比假设未产生协同作用的理论计算值提高了8.13%~15.01%;修正的Gompertz模型可以较好地模拟2种物料混合厌氧消化的动力学过程,相关度系数大于0.998;甘蔗叶与猪粪/牛粪(1:1)混合(甘蔗叶与粪比为1)厌氧消化的最优工艺条件为:温度36.5℃,C/N比27∶1,该条件下混合物料的单位干物质产沼气量实测值为337.5m L/g,与预测值(331.92 mL/g)非常接近。
译  名:
Parameter optimization in anaerobic co-digestion of NaOH pretreated sugarcane leaves and pig manure-dairy manure
作  者:
Luo Juan;Zhao Lixin;Yao Zonglu;Meng Haibo;Li Xiujin;Feng Jing;Yuan Hairong;Yu Jiadong;Huang Kaiming;Chinese Academy of Agricultural Engineering Planning & Design, Key Laboratory of Energy Resource Utilization from Agricultural Residues;College of Chemical Engineering, Beijing University of Chemical Technology;
单  位:
Luo Juan%Zhao Lixin%Yao Zonglu%Meng Haibo%Li Xiujin%Feng Jing%Yuan Hairong%Yu Jiadong%Huang Kaiming%Chinese Academy of Agricultural Engineering Planning & Design, Key Laboratory of Energy Resource Utilization from Agricultural Residues%College of Chemical Engineering, Beijing University of Chemical Technology
关键词:
biogas;;manures;;sugarcane leaves;;pig manures;;dairy manures;;anaerobic co-digestion
摘  要:
Tropical agriculture in south of China produces a large amount of tropical agricultural wastes every year including sugarcane leaves(SL). According to statistics, the annual output of SL in China is as high as 36 million tons, while the utilization rate is less than 20%. Lots of SL is discarded or even incinerated, causing environmental pollution. At the same time, South China is traditional dominant area for pig and herbivore due to rich and cheap feed. A great amount of animal manure(AM) is produced every year, which causes ecological and environmental pressure. Anaerobic digestion(AD) technology is considered to be an effective way to deal with wastes from planting and breeding. However, the low efficiency and biogas production resulting from large amount of lignocellulose limits large-scale application of SL. The biodegradability of SL can be effectively improved by pretreatment, and the anaerobic co-digestion can improve the biogas production performance of SL and AM. In this paper, the anaerobic co-digestion performance of AM and SL pretreated by NaOH was studied. The AD performance of pretreated SL with pig manure(dairy manure) at different mixing ratios(2∶1, 1∶1, 1∶2, 1∶0, 0∶1) was investigated. After that, the effects of temperature(30, 35, 40 ℃) and C/N(20∶1, 25∶1, 30∶1) of modified SL, pig manures and dairy manures were determined with Central Composite design method. The results of the tests indicated that the cumulative gas production of the mixed materials was significantly higher than that with single material and the best mixing ratio was 1:1, with which the values reached 6 075.57 and 5 903.61 mL respectively and were 8.13%-15.01% higher than that without pretreated SL or AM. The modified Gompertz model could simulate the kinetics of anaerobic co-digestion of SL and AM, and the correlation coefficient was more than 0.998. The synergistic effect was found in anaerobic co-digestion and resulted in nutrients balance and promotion of organic matter. Regression model analysis showed that the temperature and C/N had significant effects on AD. The optimal process conditions were determined by response surface methodology, that the temperature was 36.5 and C/N was 27. The measured values of biogas production of the mixture of SL and AM was 337.5 mL/g under the optimized conditions above, which was very close to the predicted value(331.92 mL/g). The model verification results showed that RSM could be used to optimize the AD process parameters of mixture.

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