期刊
WASTE MANAGEMENT
卷 83, 期 -, 页码 33-45出版社
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.wasman.2018.10.043
关键词
Waste non-homogeneity; Vertical wells; Landfill gas recovery; Analytical techniques; Dimensionless analysis
资金
- National Natural Science Foundation of China [41572265, 41661130153]
- National Program for Support of Top-Notch Young Professionals
- Newton Advanced Fellowship of the Royal Society [NA150466]
- China Scholarship Council
- Canada Research Chairs program
A two-dimensional axisymmetric and normalized analytical model for landfill gas (LFG) migration around a vertical well is developed. The vertical gas permeability and LFG generation rate of waste are assumed to be subject to exponential decreases with depth. Using a general analytical solution, over 500,000 scenarios involving a combination of typical control variables (viz: cover properties, waste properties, vacuum pressure, well radius and spacing) are modelled. A quantitative analysis of the coupled effects of these control variables on LFG recovery rate indicates that the recovery response could be captured by: (a) three dimensionless variables (denoted as cover resistance, pump capacity, and well spacing parameters), and (b) two constants defining the decreases in gas permeability and LFG generation of waste with depth. For example, if the LFG generation rate of the waste at the top is doubled, a two times increase in the vacuum pressure with other parameters being equal would give a same gas recovery rate, as well as simultaneously doubling the thickness and gas permeability of the cover. The recovery efficiency of a vertical well with a low permeability cover is examined as a function of cover resistance and pump capacity, and design charts are presented that may be used to optimize gas recovery by adjusting cover properties and vacuum pressure. The proposed model makes it possible to consider the waste non-homogeneity in the design process, and the results contribute to a preliminary design of a cover and vertical LFG collection systems. (C) 2018 Elsevier Ltd. All rights reserved.
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