4.4 Article

Characterizing Aggregate Pore Structure by X-Ray Micro-Computed Tomography and a Network Model

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SOIL SCIENCE SOCIETY OF AMERICA JOURNAL
卷 82, 期 4, 页码 744-756

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SOIL SCI SOC AMER
DOI: 10.2136/sssaj2017.11.0385

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资金

  1. National Key R & D Program of China [2016YFD0200302]
  2. National Natural Science Foundation of China [41701242]

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Information about the influence of intra-aggregate pore structure on functions and properties of soil aggregates is not fully available or predictable. In this study, the microscale intra-aggregate pore structure of four soils (Mollisol, Alfisol, Ultisol, and Vertisol) was studied by a synergistic use of synchrotron-based X-ray micro-computed tomography (SR-mCT) and advanced analytical data methods. Detailed characteristics of the connected and isolated pores of four soils were investigated by a pore network model, a network analysis, and a pore map analysis, respectively. Results indicated that total porosity and the connected/isolated porosity ratio (C/I) could describe the possible function of the soil aggregates. The aggregates with larger total porosity and C/I ratio (such as Mollisol and Alfisol) tend to have better air, water, and nutrient exchangeability as well as balance of water retention and physical C protection; whereas the aggregates with smaller total porosity and C/I ratio (such as Ultisol and Vertisol) tend to reduce air and weer exchange but have relatively better water retention ability. The pore map analysis revealed the spatial variations of isolated pores within the aggregates and depending on soil types, may influence greatly water retention and C physical protection in aggregates. The pore network model and the network analysis revealed that Ultisol and Vertisol have a smaller average throat area, an average channel length, a larger network diameter, and an average path length, which could have limited the exchangeability of air, water, and nutrient. Our results indicated that the total porosity and the C/I ratio were effective proxy indicators, which could be used to predict the functions and properties of an aggregate.

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