Effect of Clay Minerals and Organic Matter on the Cation Exchange Capacity of Silt Fractions

Peinemann, N.; Amiotti, Nilda Mabel; Zalba, Patricia Eugenia; Villamil, María B.

doi:10.1002/(sici)1522-2624(200002)163:1<47::aid-jpln47>3.0.co;2-a

Cited by 39 publications

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“…Each of OC and clay content explained 19% of the variation in CEC for PTF 2 . Contribution of organic matter (Peinemann et al, 2000) and clay (MacDonald, 1998) in the soil CEC has been reported by some authors. However, the relationship between clay and CEC can be highly variable.…”

Section: T a B L E 2 Correlation Coefficients (R) Between Input And mentioning

confidence: 99%

Prediction of CEC Using Fractal Parameters by Artificial Neural Networks

Bayat¹,

Davatgar²,

Jalali³

2014

International Agrophysics

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A b s t r a c t. The prediction of cation exchange capacity from readily available soil properties remains a challenge. In this study, firstly, we extended the entire particle size distribution curve from limited soil texture data and, at the second step, calculated the fractal parameters from the particle size distribution curve. Three pedotransfer functions were developed based on soil properties, parameters of particle size distribution curve model and fractal parameters of particle size distribution curve fractal model using the artificial neural networks technique. 1 662 soil samples were collected and separated into eight groups. Particle size distribution curve model parameters were estimated from limited soil texture data by the Skaggs method and fractal parameters were calculated by Bird model. Using particle size distribution curve model parameters and fractal parameters in the pedotransfer functions resulted in improvements of cation exchange capacity predictions. The pedotransfer functions that used fractal parameters as predictors performed better than the those which used particle size distribution curve model parameters. This can be related to the non-linear relationship between cation exchange capacity and fractal parameters. Partitioning the soil samples significantly increased the accuracy and reliability of the pedotransfer functions. Substantial improvement was achieved by utilising fractal parameters in the clusters.K e y w o r d s: cation exchange capacity, fractal theory, particle size distribution, pedotransfer functions

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Section: T a B L E 2 Correlation Coefficients (R) Between Input And mentioning

confidence: 99%

Prediction of CEC Using Fractal Parameters by Artificial Neural Networks

Bayat¹,

Davatgar²,

Jalali³

2014

International Agrophysics

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“…TOC in soil depends largely on the input of plant litter and fertilizers. As the rice plants had been harvested one month before sampling, the organic matter left in the soil was decomposed by microorganisms, resulting in low TOC and hence CEC (Peinemann et al 2000;Yang et al 2005).…”

Section: Chemical Properties and Trace Elements In Stream Water And Smentioning

confidence: 81%

“…TOC decreased with depth from 1.76% to 0.70%(Figure 2b), probably because the amount of root debris also decreased with depth (personal observation during the sieving process). CEC is expected to increase with TOC(Peinemann et al 2000), but there was no significant correlation between CEC and depth (Figure 2c). The reason remains unknown but it could be due to higher clay content in the deeper soil(Yang et al 2005), offsetting the reduced TOC with depth.…”

mentioning

confidence: 99%

Contamination and vertical distribution of As, Cd, Cr, Cu, Pb, Tl, and Zn in paddy soil irrigated with untreated leachate from tailings retention ponds

Leung

Pérez

et al. 2015

Toxicological & Environmental Chemistry

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The contamination and vertical distribution of As, Cd, Cr, Cu, Pb, Tl and Zn in paddy soil irrigated with untreated leachate from the tailings retention pond were investigated. As, Cr, Cu and Zn were slightly contaminated in the surface soil and hence their vertical distribution was not obvious. However, Cd and Pb were highly contaminated in the surface soil, while their concentrations decreased with depth, being negatively correlated with pH and positively with total organic matter. Tl was Downloaded by [FU Berlin] at 04:37 04 July 2015A c c e p t e d M a n u s c r i p t 2 considerably contaminated in the surface soil and a V-shaped vertical distribution was observed where the concentration increased to a maximum at about 30 cm depth and decreased thereafter. The findings revealed that regular irrigation with untreated leachate from the tailings retention ponds could cause considerable contamination of Cd, Pb and Tl, and thus tailings should be stringently treated before disposal to minimize their potential environmental impacts on the surroundings.

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“…The silt fraction was positively correlated while the clay and sand fractions showed a negative correlation with soil CEC. This can be explained by the association of organic matter content with the silt fraction as studied by Peinemmann et al (2000).…”

Section: Resultsmentioning

confidence: 99%

Seasonal Changes in Arsenic Concentrations and Hydrogeochemistry of Canadian Creek, Ballarat (Victoria, Australia)

Sultan

Dowling

2006

Water Air Soil Pollut

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A 10-month study of surface waters in Canadian Creek (Ballarat, Victoria, Australia) showed the significant influence of historic gold mining waste material. The investigation focussed on the hydrogeochemistry of the surface waters and soils in order to: (1) document the levels and seasonal trends in major, minor and trace elements in the creek, (2) identify the process by which As is released from the soil/waste mining material to surface waters. For most dissolved major and trace elements (Na, Ca, Mg, K, and As) in surface waters, the concentrations decreased with the increasing rainfall and flow conditions except for Al and Fe. Two sites selected along the creek (<1 km apart) allowed evaluation of the possibility that mining waste material is contributing to the elevated As concentrations (up to 145 µg/l) in downstream surface water. Arsenic concentration varied more than 28 fold seasonally and was highest in autumn and lowest in spring. Elevated concentrations of As (up to 1946 mg/kg) at the downstream site indicated the presence of a source of As concentration in both surface and subsurface soils. Oxidation of arsenic sulphides under aerobic conditions with redox fluctuations (7 to 201 mV) could cause elevated As levels in the creek. Significant statistical correlations among the major cations (Ca, Na and Mg) point to a common source(s) resulting in neutral to slightly alkaline (pH ∼ 6.5 to 7.8) surface water. Fe and Al secondary phases under oxidising conditions are a significant controlling mechanism for the mobilization of As in highly contaminated soils (>1500 mg/kg) in the study area. The large As adsorption capacity of Fe and Al could be limiting extreme mobilization into the water. Rainfall with relatively low pH is possibly causing mobilisation of Al, Fe and As from highly alkaline soils (pH ≈ 9.0) into the nearby creek.

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Effect of Clay Minerals and Organic Matter on the Cation Exchange Capacity of Silt Fractions

Cited by 39 publications

References 0 publications

Prediction of CEC Using Fractal Parameters by Artificial Neural Networks

Prediction of CEC Using Fractal Parameters by Artificial Neural Networks

Contamination and vertical distribution of As, Cd, Cr, Cu, Pb, Tl, and Zn in paddy soil irrigated with untreated leachate from tailings retention ponds

Seasonal Changes in Arsenic Concentrations and Hydrogeochemistry of Canadian Creek, Ballarat (Victoria, Australia)

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