Abstract
Settlement behaviors of high-food-waste-content (HFWC) and low-food-waste-content (LFWC) municipal solid wastes (MSWs) respectively from developing and developed countries were characterized and compared based on a great number of experimental datasets from references. Fresh HFWC-MSW generally has larger primary compression ratio compared to fresh LFWC-MSW, due to the release of a large amount of intra-particle water contained in food waste under additional stresses. The slopes of strain-logarithmic time curves with respect to the three secondary compression phases are characterized as “slight-steep-slight” for LFWC-MSW and “moderate-moderate-slight” for HFWC-MSW. It is difficult to distinguish the first two phases of the secondary compression in strain-logarithmic time curves for HFWC-MSW. The entropy method was built to evaluate the performance and applicability of nine published settlement models based on the settlement datasets of four large-scale experiments. The computational simplicity, the fitting performance, the prediction performance and the parametric stability were taken as the four criterions in the entropy method. Based on the evaluation results, the models proposed by Sowers et al. (1973) and Gourc et al. (2010) are recommended for predicting settlement at LFWC-MSW landfills, while the hyperbolic model and the Chen et al. (2010) model are recommended for HFWC-MSW landfills.
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This work was supported by the National Basic Research Program of China (Grant No. 2012CB719802), the National Natural Science Foundation of China (Grant Nos. 51708508, 41402249), the Zhejiang Provincial Natural Science Foundation of China (Grant Nos. LY17E080021, LY15E080021), and the Science Technology Department of Zhejiang Province (Grant No. 2019C03107). The authors also want to express their deep thanks to Prof. William Powrie and Dr. Richard Beaven from University of Sonthampton for their constructive comments.
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Xu, H., Qiu, H., Zhu, G. et al. Comparison of settlement behaviors of high-food-waste-content (HFWC) and low-food-waste-content (LFWC) MSWs and assessment of their prediction models. Sci. China Technol. Sci. 62, 2271–2292 (2019). https://doi.org/10.1007/s11431-019-1439-2
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DOI: https://doi.org/10.1007/s11431-019-1439-2