Key Laboratory of Energy Thermal Conversion and Control of Ministry of Education, School of Energy and Environment, Southeast University, Nanjing, 210096, People's Republic of China.
College of Mechanical and Electrical Engineering, Henan Agricultural University, Nongye Road 63, Zhengzhou, Henan, 450002, People's Republic of China.
Environ Sci Pollut Res Int. 2021 May;28(20):25808-25818. doi: 10.1007/s11356-020-12262-1. Epub 2021 Jan 21.
In the present study, the simplex lattice mixture design method was adopted to design the artificial biomass with different ratios of three major components (cellulose, hemicellulose, lignin). The methane yield from the co-digestion of the artificial/ natural biomass (corn stover, wheat stover, rice straw, and peanut stalk) samples with the mixed sludge at the mixture ratio of 1:1 based on total solid (TS) content was recorded for 50 days. The original mathematical prediction models for estimating the cumulative methane production, maximum methane production rate, and lag phase time were established based on the experimental results from the co-digestion of artificial biomass with sludge. To investigate the influence of the structural features of biomass and interactions among the components of biomass which contributing to the inhibition of methane production, the macroscopic factor (MF) was proposed. The mathematical models which revealed the relationship between MF and the methane production parameters were developed by the combination of the prediction results from the original mathematical prediction model and experimental results from the co-digestion of natural biomass with sludge. Modification of the original mathematical prediction models was carried out by considering MF. After modification, the relative error (RE) and root mean square error (RMSE) of the prediction model for cumulative methane production were declined from 19.00 to 30.18% and 42.38 mL/g VS to that of - 1.93~7.14% and 4.36 mL/g VS, respectively.
在本研究中,采用单纯形格子混合设计方法设计了三种主要成分(纤维素、半纤维素、木质素)不同比例的人工生物质。基于总固体(TS)含量,以 1:1 的混合比例将人工/天然生物质(玉米秸秆、小麦秸秆、水稻秸秆和花生秸秆)与混合污泥共消化,记录 50 天的甲烷产量。根据人工生物质与污泥共消化的实验结果,建立了原始的数学预测模型,用于估算累积甲烷产量、最大甲烷产率和迟滞期时间。为了研究生物质结构特征和生物质各成分之间相互作用对甲烷生成的抑制影响,提出了宏观因子(MF)。通过原始数学预测模型的预测结果与污泥共消化天然生物质的实验结果相结合,建立了揭示 MF 与甲烷生产参数之间关系的数学模型。通过考虑 MF 对原始数学预测模型进行了修正。修正后,累积甲烷产量预测模型的相对误差(RE)和均方根误差(RMSE)从 19.00%降至 30.18%,从 42.38 mL/g VS 降至-1.93%至 7.14%和 4.36 mL/g VS。