基于生物化学性质的固体废物厌氧降解特征参数 |
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引用本文: | 郑 苇 Khamphe Phoungthong 吕 凡 邵立明 何品晶. 基于生物化学性质的固体废物厌氧降解特征参数[J]. 中国环境科学, 2014, 34(4): 983-988 |
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作者姓名: | 郑 苇 Khamphe Phoungthong 吕 凡 邵立明 何品晶 |
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作者单位: | 同济大学固体废物处理与资源化研究所;住房和城乡建设部村镇建设司农村生活垃圾处理技术研究与培训中心; |
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基金项目: | 国家“973”项目(2012CB719801);国家自然科学基金项目(21177096;51178327) |
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摘 要: | 为了更简便有效地预测固体废物的厌氧降解参数,通过代表性单组份废物的生物化学甲烷潜力实验,研究了甲烷产生潜力,降解速率和碳贮藏因子这3种厌氧降解参数与生物化学性质的关系.结果表明,通过因子分析,可用多糖、蛋白质、脂肪和木质素4种成分替代C、H、N、多糖、蛋白质、脂肪、半纤维素、纤维素和木质素9种成分;再通过偏最小二乘回归数值分析,在厌氧降解参数与多糖、蛋白、脂肪、木质纤维素之间建立线性关系.结果表明,脂肪和多糖含量越高,甲烷产生潜力和降解速率就越大;木质素含量越高,则碳贮藏因子越大.蛋白质含量的增加会导致甲烷产生潜力的减小.研究建立的线性方程可为预测固体废物厌氧降解参数提供一种新的方法.
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关 键 词: | 生物化学性质 因子分析 厌氧降解参数 偏最小二乘分析 预测 线性方程 |
收稿时间: | 2013-08-06 |
Biochemical characterization of solid wastes for the anaerobic degradation parameters |
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Abstract: | In an attempt to predict landfill anaerobic degradation parameters (L0, methane generation potential, k, decay rate and CSF, carbon sequestration factor) more conveniently, the linkage between biochemical characteristics of degradable solid wastes and anaerobic degradation parameters was established. The biochemical characteristics of twenty-eight kinds of degradable solid wastes including C, H, N, polysaccharide, protein, lipid, hemicellulose, cellulose, and lignin, were measured. Four kinds of biochemical characteristics including polysaccharide, protein, lipid, and lignin were determined to substitute for the original nine kinds of biochemical characteristics through factor analysis. Biochemical methane potential (BMP) tests were conducted at mesophilic temperature to investigate anaerobic degradation parameters. Partial least squares regression analysis (PLS) was applied and the results revealed that a linear relation between biochemical characteristics and anaerobic degradation parameters could be implemented. The higher L0 and k value could be attributed to higher lipid and polysaccharide content, however, the higher CSF value could be due to higher lignin content. The higher protein content may lead to lower L0 value. The linear equations can afford a new computation method for predicting anaerobic degradation parameters. |
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Keywords: | biochemical characteristics factor analysis anaerobic degradation parameters partial least squares regression analysis prediction linear equation |
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