Department of Biological and Environmental Sciences, Federal University of Technology - Parana, Avenida Brasil 4232, Medianeira, Brazil; Research Group on Water Resources and Environmental Sanitation, Western Parana State University, Agricultural Engineering Graduate Program, Rua Universitária, 2069 Jardim Universitário, 85.819-110 Cascavel, Paraná, Brazil.
Department of Biological and Environmental Sciences, Federal University of Technology - Parana, Avenida Brasil 4232, Medianeira, Brazil.
Waste Manag. 2018 Jan;71:618-625. doi: 10.1016/j.wasman.2017.05.030. Epub 2017 May 26.
This study investigates the influence of chemical composition on the biochemical methane potential (BMP) of twelve different batches of fruit and vegetable waste (FVW) with different compositions collected over one year. BMP ranged from 288 to 516LCHkgVS, with significant statistical differences between means, which was explained by variations in the chemical composition over time. BMP was most strongly correlated to lipid content and high calorific values. Multiple linear regression was performed to develop statistical models to more rapidly predict methane potential. Models were analysed that considered chemical compounds and that considered only high calorific value as a single parameter. The best BMP prediction was obtained using the statistical model that included lipid, protein, cellulose, lignin, and high calorific value (HCV), with R of 92.5%; lignin was negatively correlated to methane production. Because HCV and lipids are strongly correlated, and because HCV can be determined more rapidly than overall chemical composition, HCV may be useful for predicting BMP.
本研究调查了化学成分对 12 批不同组成的水果和蔬菜废物(FVW)生化甲烷潜力(BMP)的影响,这些 FVW 是在一年中收集的。BMP 范围为 288 至 516LCHkgVS,平均值之间存在显著的统计学差异,这是由于化学成分随时间的变化而变化。BMP 与脂质含量和高热值高度相关。进行了多元线性回归分析,以开发更快速预测甲烷潜力的统计模型。分析了考虑化学化合物的模型和仅考虑高热值作为单个参数的模型。使用包含脂质、蛋白质、纤维素、木质素和高热值(HCV)的统计模型获得了最佳的 BMP 预测,R 为 92.5%;木质素与甲烷生成呈负相关。由于 HCV 和脂质高度相关,并且由于 HCV 可以比整体化学成分更快地确定,因此 HCV 可能有助于预测 BMP。