| 光谱学与光谱分析 |
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| Influence of the Composition of the Initial Mixtures on the Physicochemical and Biological Properties and Spectral Characteristics of Composts |
| SONG Cai-hong1, 2, LI Ming-xiao2, WEI Zi-min1, XI Bei-dou2*, ZHAO Yue1*, JIA Xuan2, LIU Ya-ru3, LIU Dong-ming1 |
1. College of Life Science, Northeast Agricultural University, Harbin 150030, China
2. State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing 100012, China
3. Zhongtianyuan Architects & Engineers Ltd., Beijing 100142, China |
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Abstract In this work, biogas residues, the remnant of the anaerobic digestion, was used for composting with livestock manure as the co-substrate. It is important for improving the soil quality in China, because the negative influence of biogas residues being utilized directly as organic fertilizer (a mainstream way of disposing biogas residues in China) on the soil could be eliminated or mitigated via composting. The composition of composting substrate has a great influence on the composting process. To explore the influence of the composition of the initial mixtures on the physicochemical properties and spectroscopic characteristics of composts, fifteen co-composting of biogas residue, pig manure and chicken manure, with different material ratios, were carried out. Physicochemical and biological indicators were determined. Meanwhile, spectroscopic methods, such as UV-Vis, synchronous fluorescence and 3D-EEM spectra were used for identifyingcharacteristic spectral parameters companied with FRI and PARAFAC. Therefore, spectroscopic characteristics of composts were characterized. The relationship between physicochemical properties of composts and the composition of the initial mixtures was established using CCA. Similarly, that between spectroscopic characteristics of composts and the composition of the initial mixtures was also established. The results showed that: physicochemical properties of composts exhibits a significant correlation with the composition of the initial mixtures. A significant correlation between spectroscopic characteristics of composts and the composition of the initial mixtures was also observed. In the two CCA, the former four axes account for 83.9% and 97.5% of the total sample variation. The influence of enviro nmental factors on physicochemical properties of composts was in the order of pig manure amount>chicken manure amount>biogas residue amount and that on spectroscopic characteristics of composts was in the order of biogas residue amount>pig manure amount>chicken manure amount. Carbon-rich raw materials favor the maturation of compost. A high proportion of nitrogen-rich raw materials does not lead to the accumulation of ammonia in compost. A low proportion of biogas residue favors the formation of humic substances during the co-composting of biogas residue and livestock manure. In summary, the evaluation of compost fermentation effect should synthetically consider physic-chemical, biological indicators and spectral parameters instead of a single index.
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Received: 2014-06-10
Accepted: 2014-09-26
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Corresponding Authors:
XI Bei-dou, ZHAO Yue1
E-mail: xibeidou@263.net;zhao1970yue@163.com
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[1] Duan G, Zhang H, Liu Y, et al. Soil Science and Plant Nutrition, 2012, 58(5): 637.
[2] SONG Cai-hong, XIA Xun-feng, XI Bei-dou(宋彩红, 夏训峰, 席北斗). Chinese Environmental Science (中国环境科学), 2012, 32(8): 1474.
[3] Ho Y B, Zakaria M P, Latif P A, et al. Bioresource Technology, 2013, 131: 476.
[4] Singh J, Kalamdhad A S. Ecological Engineering, 2013, 52: 59.
[5] Silva M E F, de Lemos L T, Nunes O C, et al. Waste Management, 2014, 34(1): 21.
[6] Nakano K, Matsumura M. Journal of Bioscience and Bioengineering, 2001, 92(6): 532.
[7] He X S, Xi B D, Jiang Y H, et al. Microchemical Journal, 2013, 106: 160.
[8] Wei Z, Zhao X, Zhu C, et al. Chemosphere, 2014, 95: 261.
[9] Hosseini S M, Aziz H A. Bioresource Technology, 2013, 133: 240.
[10] Xi B, He X, Wei Z, et al. Chemosphere, 2012, 88(6): 744.
[11] He X, Xi B, Wei Z, et al. Chemosphere, 2011, 82(6): 541.
[12] LIU Li-xue, CHEN Hai-tao, HAN Yong-jun(刘丽雪, 陈海涛, 韩永俊). Transactions of the Chinese Society of Agricultural Engineering(农业工程学报), 2010, 26(7): 277.
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