Cation-exchange capacity

About: Cation-exchange capacity is a research topic. Over the lifetime, 8179 publications have been published within this topic receiving 238042 citations.

Environmental Soil Chemistry

Abstract: Environmental Soil Chemistry: An Overview: Evolution of Soil Chemistry. The Modern Environmental Movement. Contaminants in Waters and Soils. Case Study of Pollution of Soils and Waters. Soil Decontamination. Inorganic Soil Components: Pauling's Rules. Primary Soil Minerals. Secondary Soil Minerals. Specific Surface of Soil Minerals. Surface Charge of Soil Minerals. Identification of Minerals by X-Ray Diffraction Analyses. Use of Clay Minerals to Retain Organic Contaminants. Chemistry of Soil Organic Matter: Effects of Soil Formation Factors on SOM Contents. Composition of SOM. Fractionation of SOM. SOM Structure. Functional Groups and Charge Characteristics. Humic Substance-Metal Interactions. SOM-Clay Complexes. Retention of Pesticides and Other Organic Substances by Humic Substances. Soil Solution-Solid Phase Equilibria: Measurement of the Soil Solution. Speciation of the Soil Solution. Ion Activity and Activity Coefficients. Dissolution and Solubility Processes. Sorption Phenomena on Soils: Introduction and Terminology. Surface Functional Groups. Surface Complexes. Adsorption Isotherms. Equilibrium-Based Adsorption Models. Surface Precipitation. Sorption of Metal Cations. Sorption of Anions. Points of Zero Charge. Desorption. Use of Spectroscopic and Microscopic Methods in Determining Mechanisms for Sorption-Desorption Phenomena. Ion Exchange Processes: Characteristics of Ion Exchange. Cation Exchange Equilibrium Constants and Selectivity Coefficients. Thermodynamics of Ion Exchange. Relationship between Thermodynamics and Kinetics of Ion Exchange. Kinetics of Soil Chemical Processes: Rate-Limiting Steps and Time Scales of Soil Chemical Reactions. Rate Laws. Determination of Reacti

The Chemistry of Soils

Abstract: 1. The Chemical Composition of Soils 2. Soil Minerals 3. Soil Humus 4. The Soil Solution 5. Mineral Stability and Weathering 6. Oxidation-Reduction Reactions 7. Soil Particle Surface Charge 8. Soil Adsorption Phenomena 9. Exchangeable Ions 10. Colloidal Phenomena 11. Soil Acidity 12. Soil Salinity

SoilGrids250m: Global gridded soil information based on machine learning

Abstract: This paper describes the technical development and accuracy assessment of the most recent and improved version of the SoilGrids system at 250m resolution (June 2016 update). SoilGrids provides global predictions for standard numeric soil properties (organic carbon, bulk density, Cation Exchange Capacity (CEC), pH, soil texture fractions and coarse fragments) at seven standard depths (0, 5, 15, 30, 60, 100 and 200 cm), in addition to predictions of depth to bedrock and distribution of soil classes based on the World Reference Base (WRB) and USDA classification systems (ca. 280 raster layers in total). Predictions were based on ca. 150,000 soil profiles used for training and a stack of 158 remote sensing-based soil covariates (primarily derived from MODIS land products, SRTM DEM derivatives, climatic images and global landform and lithology maps), which were used to fit an ensemble of machine learning methods-random forest and gradient boosting and/or multinomial logistic regression-as implemented in the R packages ranger, xgboost, nnet and caret. The results of 10-fold cross-validation show that the ensemble models explain between 56% (coarse fragments) and 83% (pH) of variation with an overall average of 61%. Improvements in the relative accuracy considering the amount of variation explained, in comparison to the previous version of SoilGrids at 1 km spatial resolution, range from 60 to 230%. Improvements can be attributed to: (1) the use of machine learning instead of linear regression, (2) to considerable investments in preparing finer resolution covariate layers and (3) to insertion of additional soil profiles. Further development of SoilGrids could include refinement of methods to incorporate input uncertainties and derivation of posterior probability distributions (per pixel), and further automation of spatial modeling so that soil maps can be generated for potentially hundreds of soil variables. Another area of future research is the development of methods for multiscale merging of SoilGrids predictions with local and/or national gridded soil products (e.g. up to 50 m spatial resolution) so that increasingly more accurate, complete and consistent global soil information can be produced. SoilGrids are available under the Open Data Base License.

Soil pH and Soil Acidity

Abstract: Soil pH is probably the single most informative measurement that can be made to determine soil characteristics. At a single glance, pH tells much more about a soil than merely indicating whether it is acidic or basic. For example, availability of essential nutrients and toxicity of other elements can be estimated because of their known relationship with pH. The term pH was "invented" by the Swedish scientist Sorensen (1909) in order to obtain more convenient numbers and the idea quickly caught on. Gillespie and Hurst (1918) seem to have been among the earliest to determine pH (or PH, as it was then called) electrometrically using a platinum-palladium blackhydrogen gas electrode, a calomel reference electrode and a fairly cumbersome potentiometer and galvanometer system. At that period, it was still much more common to use colorimetric methods with indicator dyes than the electrometric method. This changed rapidly, however. Sharp and Hoagland (1919) used a similar but less involved method than Gillespie and Hurst (1918) and Healy and Karraker (1922) used a commercially available platinum-hydrogen gas electrode, potentiometer and galvanometer which had been designed by Clark (1920). The decade of the 1920s saw the development of the quinhydrone electrode which was less fragile and much less expensive than the hydrogen-platinum electrode. But, it was the development of the glass electrode in the 1930s that brought the determination of pH very rapidly to its present importance and convenience. The Beckman Model G pH meter (circa 1931) was practically indestructible and could be used as a portable as well as a laboratory instrument. Although it was cumbersome by today's standards, it was virtually foolproof (except for the constantly failing batteries) and many are still capable of operating if not actually operating today. As recently as two decades ago, the use of the small, handheld portable pH meters then available to determine pH in the field was a very imprecise and hazardous undertaking because both electrodes and meters were subject to sudden failures but this has changed rather abruptly in the last few years. Microcircuitry and plastic have contributed to rugged pH meters and electrodes that withstand