Multifractal Description of Nitrogen Adsorption Isotherms

Paz‐Ferreiro, Jorge; Wilson, Marcelo Germán; Vázquez, Eva Vidal

doi:10.2136/vzj2008.0007

Cited by 51 publications

(79 citation statements)

References 34 publications

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“…Also, the scaling properties of NAIs from soils (Paz-Ferreiro et al, 2009, Vidal-Vazquez and Paz-Ferreiro, 2012) and artifitial organoclays ) have been reasonably well described by multifractal models. More recently, Paz-Ferreiro et al, 2013 performed multiscale analysis of both NAIs and NDIs.…”

mentioning

confidence: 79%

“…This procedure has been frequently used for multifractal evaluation of various soil properties, including pore size distributions (Posadas et al, 2003;Tarquis et al, 2006), Particle size distributions (Miranda et al, 2006) surface roughness (Vidal Vázquez et al, 2008) etc. Also, more recently it has been employed for assessing multifractal property of either the adsorption branch (Paz-Ferreiro et al, 2009Vidal-Vázquez and PazFerreiro, 2012;Lado et al, 2013) or both, the adsorption and desorption branches (Paz-Ferreiro et al, 2013) of nitrogen 35 isotherms. Therefore multifractal concepts and method of analysis will be here only briefly described.…”

Section: Multifractal Analysismentioning

confidence: 99%

“…Therefore, the distributions of N 2 was taken as the measure, µ i , and the relative pressure, p/p 0 , itself, as the support. To evaluate the scaling behavior of the measure, µ i , the support p/p 0 was next divided into successive segments with a unit length, δ, following dyadic downscaling 2009 Thereafter, the data sets consisting of distributions of N 2 during absorption or desorption are normalized, meaning that a new 5 variable, the probability mass function, p i (δ) or µ i (δ), is defined as:…”

Section: Multifractal Analysismentioning

confidence: 99%

“…15 (Petersen et al, 1996;Hajnos et al, 2000;Jozefaciuck et al, 2006;Bartoli et al, 2007;Paz-Ferreiro et al, 2009Lado et al, 2009). To estimate SSA, classical, non-fractal models are employed, from which the most conventional is the Brunnauer-Emmett-Teller (BET) model (Brunauer et al, 1938).…”

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confidence: 99%

“…First, the BET model, 25 estimates the total surface area from adsorption isotherms in a limited range of relative pressure, (i.e., 0.05<p/p 0 < 0.35), while fractal and multifractal approaches use the information contained in the entire adsorption or desorption curve. Second, the BET method assumes that the soil pore-solid interface is not a fractal (Paz-Ferreiro et al, 2009). Nevertheless, it has been claimed that SSA and scaling analysis of N 2 isotherms yield complementary information that may be useful for a better understanding of the geometry of soil surfaces and porous systems (Paz-Ferreiro et al, 2013).…”

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confidence: 99%

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Multiscale analysis of nitrogen adsorption and desorption isotherms in soils with contrasting pedogenesis and texture

Paz‐Ferreiro

Marinho

Abreu

et al. 2016

Preprint

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Abstract. The specific surface area (SSA) of a soil is commonly estimated from adsorption isotherms determined in a limited range of relative pressures (p/p 0 ), admitting a non fractal model. Nitrogen adsorption (NAI) and desorption (NDI) isotherms determined over the full range of p/p 0 have been described using the multifractal approach. This study aimed to assess effects of soil texture on the multifractality of NAIs and NDIs, and to analyze the association between multifractal parameters and soil properties. Six soil profiles were taken to get two groups of samples with contrasting pedogenetic origin, 15 texture (medium or clayey), susceptibility to water erosion and quality for agricultural uses. These two soil groups also were significant differences in SSA and cation exchange capacity (CEC), but not in organic matter content (OMC). Consistent with previous studies, the scaling properties of both NAIs and NDIs from all the soil horizons studied could be fitted reasonably well with multifractal models. Values of parameters D -5 , D 1 , D 2 and D 5 , extracted from the generalized dimension function, D q , were higher for clayey soils during adsorption, but during desorption all of them were higher for medium 20 textured soils. Therefore, the measure was more evenly distributed for clayey soils during adsorption and for medium textured soils during desorption. Width of D q function given by parameter (D -5 -D 5 ) was significantly higher clayey soils for NAIs, but not significant differences were detected for NDIs; subsequently scaling heterogeneity of NAIs was higher for clayey than for medium textured soil. Differences in multifractal behaviour of NAIs and NDIs were consistent with a wider hysteresis loop of the medium texture soils compared to that of the clayey soils. Linear correlations were found between 25 parameters D -5 and (D -5 -D 5 ) and clay content or SSA, which were positive and negative for NAIs and NDIs, respectively.Agronomical and environmental characterization of these soil groups with contrasting properties be enhanced by evaluating SSA and by inspecting NAIs and NDIs for multifractality.

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mentioning

confidence: 79%

Section: Multifractal Analysismentioning

confidence: 99%

Section: Multifractal Analysismentioning

confidence: 99%

mentioning

confidence: 99%

mentioning

confidence: 99%

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Multiscale analysis of nitrogen adsorption and desorption isotherms in soils with contrasting pedogenesis and texture

Paz‐Ferreiro

Marinho

Abreu

et al. 2016

Preprint

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Estimation of spatial covariance of log conductivity from particle size data

Riva

Sánchez-Vila²,

Guadagnini

2014

Water Resources Research

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We derive analytical relationships between the spatial covariance of the (natural) logarithm of hydraulic conductivity (K) and that of representative soil particle sizes and porosity. The latter quantities can be directly measured during routine sedimentological analyses of soil samples and provide a way of incorporating K estimates into groundwater flow models at a relatively modest experimental cost. Here we rely on widely used empirical formulations requiring measurements of representative particle diameters and, in some cases, of medium porosity. We derive exact formulations relating the spatial covariance of these quantities and K and present workable approximations on the basis of perturbation methods. Our formulations provide a direct link between key geostatistical descriptors of sedimentological and hydraulic parameters of heterogeneous aquifers which can be employed in classical estimation and simulation procedures. The approach and theoretical results are tested on an extensive data set comprising 411 particle size curves collected at 12 boreholes in a small-scale alluvial aquifer.

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