Cadmium adsorption capacity of selected Ontario soils

1996 ◽  
Vol 76 (2) ◽  
pp. 183-189 ◽  
Author(s):  
K. A. Bolton ◽  
L. J. Evans
Keyword(s):  
Soil Properties ◽  
Linear Regression Analysis ◽  
Surface Complexation ◽  
Solution Concentration ◽  
Multiple Linear Regression Analysis ◽  
Batch Adsorption ◽  
Surface Complexation Modeling ◽  
Ph Values ◽  
Cadmium Adsorption ◽  
Cd Adsorption

The retention of Cd by selected Ontario soils with a range of soil properties was investigated. Batch adsorption experiments were carried out at the actual (unadjusted) PH of the soil and at a range of PH values adjusted by the addition of acid or base. For all soils, Cd adsorption increased with increasing pH and with increasing Cd solution concentration. The adsorption data was fitted, by a linear least squares technique, to the Langmuir adsorption isotherm. Maximum adsorption, qmax, at unadjusted soil pH values ranged from less than 8 mmol kg−1 for the Fox sandy soil to 64.8 mmol kg−1 for the Hanbury heavy clay soil. Calculated Cd adsorption maxima were regressed against measured soil properties to determine the most important properties involved in the adsorption of Cd. Multiple linear regression analysis revealed the best model to be qmax = 8.33 + 0.67 (organic carbon) + 4.37 (inorganic – poorly crystalline Fe, Fepc). Surface complexation modeling indicates that humic surfaces account for adsorption at pH values beginning at approximately 3.5 and that hydrous ferric oxide surfaces account for Cd adsorption at pH values greater than 7. Key words: Cadmium adsorption, Langmuir isotherm, surface complexation, soil contamination

Arsenic removal by ferric-chloride coagulation – effect of phosphate, bicarbonate and silicate

2011 ◽  
Vol 64 (5) ◽  
pp. 1046-1055 ◽  
Author(s):  
Dóra Laky ◽  
István Licskó
Keyword(s):  
Adverse Effect ◽  
Arsenic Removal ◽  
Linear Regression Analysis ◽  
Arsenic Concentration ◽  
Ferric Hydroxide ◽  
Multiple Linear Regression Analysis ◽  
Ph Values ◽  
Robust Model ◽  
Coagulant Dosage ◽  
Negative Effect

Jar tests with synthetic water were carried out in order to investigate the effect of phosphate, bicarbonate and silicate on arsenic removal efficiency by in-situ formed ferric hydroxide. Above 12 mg C/L inorganic carbon concentration, the adverse effect of bicarbonate was definite, and resulted in higher remaining arsenic concentration. At all pH values (7.5–7.8) and coagulant dosages (0.84–3.00 mg/L Fe) tested, the negative effect of phosphate on arsenic removal was also evident. In the presence of silicate small ferric-hydroxide colloids were formed, which were able to go through the 0.45 μm pore-size membrane. Compared to silicate-free systems, 2.5–3.5 times higher coagulant dose was needed to achieve the target arsenic concentration in the presence of 14–23 mg/L Si. At higher pH values the adverse effect of silicate was even more significant. All data were merged and multiple linear regression analysis was carried out in order to build up a robust model to predict the residual arsenic concentration if the raw water contains 50–60 μg/L initial arsenic concentration. The estimation was based on the following variables: PO4-P concentration, final pH, Si concentration, Fe(III) dose. The most important influencing factors proved to be the silicate concentration and applied coagulant dosage.

scholarly journals Proton release by tea plant (Camellia sinensis L.) roots as affected by nutrient solution concentration and pH

2012 ◽  
Vol 58 (No. 9) ◽  
pp. 429-434 ◽  
Author(s):  
Q. Wan ◽  
R.K. Xu ◽  
X.H. Li
Keyword(s):  
Linear Regression Analysis ◽  
Solution Concentration ◽  
Multiple Linear Regression Analysis ◽  
Solution Culture ◽  
Tea Plant ◽  
Charge Balance ◽  
Proton Release ◽  
Factors Affecting ◽  
Plant Body ◽  
Titration System

Solution culture experiments were conducted and the protons released were measured with an automatic titration system to determine the main factors affecting proton release by tea roots. Results indicated that the higher were the cation concentrations, the more protons were released from the roots, suggesting that tea roots took up a large amount of cations during growth, and then released protons to maintain charge balance of the plant body. The amount of protons released from tea roots at controlled pH was much higher than that in the treatments with uncontrolled pH. Stepwise multiple linear regression analysis showed that both NH<sub>4</sub><sup>+</sup>&nbsp;and Al(III) played distinct roles in proton release by tea plant roots. The uptake of Al(III) and NH<sub>4</sub><sup>+</sup>&nbsp;and subsequent release of protons may be an important mechanism for soil acidification in tea gardens.

Pickled Egg Production: Effect of Brine Acetic Acid Concentration and Packing Conditions on Acidification Rate

2014 ◽  
Vol 77 (5) ◽  
pp. 788-795 ◽  
Author(s):  
OSCAR ACOSTA ◽  
XIAOFAN GAO ◽  
ELIZABETH K. SULLIVAN ◽  
OLGA I. PADILLA-ZAKOUR
Keyword(s):  
Acetic Acid ◽  
Regression Analysis ◽  
Acid Concentration ◽  
Egg Production ◽  
Ph Value ◽  
Linear Regression Analysis ◽  
Multiple Linear Regression Analysis ◽  
Acetic Acid Concentration ◽  
Ph Values ◽  
Acidified Foods

U.S. federal regulations require that acidified foods must reach a pH of 4.6 or lower within 24 h of packaging or be kept refrigerated until then. Processes and formulations should be designed to satisfy this requirement, unless proper studies demonstrate the safety of other conditions. Our objective was to determine the effect of brine acetic acid concentration and packing conditions on the acidification rate of hard-boiled eggs. Eggs were acidified (60/40 egg-to-brine ratio) at various conditions of brine temperature, heat treatment to filled jars, and postpacking temperature: (i) 25°C/none/25°C (cold fill), (ii) 25°C/none/2°C (cold fill/refrigerated), (iii) 85°C/none/25°C (hot fill), and (iv) 25°C/100°C for 16 min/25°C (water bath). Three brine concentrations were evaluated (7.5, 4.9, and 2.5% acetic acid) and egg pH values (whole, yolk, four points within egg) were measured from 4 to 144 h, with eggs equilibrating at pH 3.8, 4.0, and 4.3, respectively. Experiments were conducted in triplicate, and effects were considered significant when P &lt; 0.05. Multiple linear regression analysis was conducted to evaluate the effect on pH values at the center of the yolk. Regression analysis showed that brine concentration of 2.5% decreased the acidification rate, while packing conditions of the hot fill trial increased it. Inverse prediction was used to determine the time for the center of the yolk and the total yolk to reach a pH value of 4.6. These results demonstrate the importance of conducting acidification studies with proper pH measurements to determine safe conditions to manufacture commercially stable pickled eggs.

scholarly journals Surface complexation modeling of Cd(II) sorption to montmorillonite, bacteria, and their composite

2016 ◽  
Author(s):  
Ning Wang ◽  
Huihui Du ◽  
Qiaoyun Huang ◽  
Peng Cai ◽  
Xingmin Rong ◽  
...  
Keyword(s):  
Surface Complexation ◽  
Bacterial Cells ◽  
Surface Complexation Modeling ◽  
Isothermal Adsorption ◽  
Spectra Analysis ◽  
Potential Measurement ◽  
Gram Positive Bacteria ◽  
Component Systems ◽  
Adsorption Processes ◽  
Cd Adsorption

Abstract. Surface complexation modeling (SCM) has emerged as a powerful tool for simulating heavy metal adsorption processes on the surface of soil solid components under different geochemical conditions. The component additivity (CA) approach is one of the strategies that have been widely used in multi-component systems. In this study, potentiometric titration, isothermal adsorption, zeta potential measurement, and extended X-ray absorption fine structure (EXAFS) spectra analysis were conducted to investigate Cd adsorption on 2 : 1 clay mineral montmorillonite, on Gram-positive bacteria Bacillus subtilis, and their mineral-organic composite. We developed constant capacitance models (CCM) of Cd adsorption on montmorillonite, bacterial cells, and mineral-organic composite. The adsorption behavior of Cd on the surface of the composite was well explained by CA-SCM. Some deviations were observed from the model simulations at pH 

scholarly journals Surface complexation modeling of Cd(II) sorption to montmorillonite, bacteria, and their composite

2016 ◽  
Vol 13 (19) ◽  
pp. 5557-5566 ◽  
Author(s):  
Ning Wang ◽  
Huihui Du ◽  
Qiaoyun Huang ◽  
Peng Cai ◽  
Xingmin Rong ◽  
...  
Keyword(s):  
Heavy Metal ◽  
Surface Complexation ◽  
Bacterial Cells ◽  
Surface Complexation Modeling ◽  
Isothermal Adsorption ◽  
Spectra Analysis ◽  
Composite Surface ◽  
Potential Measurement ◽  
Adsorption Processes ◽  
Cd Adsorption

Abstract. Surface complexation modeling (SCM) has emerged as a powerful tool for simulating heavy metal adsorption processes on the surface of soil solid components under different geochemical conditions. The component additivity (CA) approach is one of the strategies that have been widely used in multicomponent systems. In this study, potentiometric titration, isothermal adsorption, zeta potential measurement, and extended X-ray absorption fine-structure (EXAFS) spectra analysis were conducted to investigate Cd adsorption on 2 : 1 clay mineral montmorillonite, on Gram-positive bacteria Bacillus subtilis, and their mineral–organic composite. We developed constant capacitance models of Cd adsorption on montmorillonite, bacterial cells, and mineral–organic composite. The adsorption behavior of Cd on the surface of the composite was well explained by CA-SCM. Some deviations were observed from the model simulations at pH < 5, where the values predicted by the model were lower than the experimental results. The Cd complexes of X2Cd, SOCd+, R-COOCd+, and R-POCd+ were the predominant species on the composite surface over the pH range of 3 to 8. The distribution ratio of the adsorbed Cd between montmorillonite and bacterial fractions in the composite as predicted by CA-SCM closely coincided with the estimated value of EXAFS at pH 6. The model could be useful for the prediction of heavy metal distribution at the interface of multicomponents and their risk evaluation in soils and associated environments.

scholarly journals Relationship Between Sugarcane Rust Severity and Soil Properties In Louisiana

2007 ◽  
Vol 97 (6) ◽  
pp. 748-755 ◽  
Author(s):  
Richard M. Johnson ◽  
Michael P. Grisham ◽  
Edward P. Richard
Keyword(s):  
Soil Properties ◽  
Soil Phosphorus ◽  
Linear Regression Analysis ◽  
Predictive Ability ◽  
Multiple Linear Regression Analysis ◽  
Spatial And Temporal Variability ◽  
Spatially Correlated ◽  
Contour Plots ◽  
Two Parameters ◽  
Soil Sulfur

The extent of spatial and temporal variability of sugarcane rust (Puccinia melanocephala) infestation was related to variation in soil properties in five commercial fields of sugarcane (interspecific hybrids of Saccharum spp., cv. LCP 85–384) in southern Louisiana. Sugarcane fields were grid-soil sampled at several intensities and rust ratings were collected at each point over 6 to 7 weeks. Soil properties exhibited significant variability (coefficients of variation = 9 to 70.1%) and were spatially correlated in 39 of 40 cases with a range of spatial correlation varying from 39 to 201 m. Rust ratings were spatially correlated in 32 of 33 cases, with a range varying from 29 to 241 m. Rust ratings were correlated with several soil properties, most notably soil phosphorus (r = 0.40 to 0.81) and soil sulfur (r = 0.36 to 0.68). Multiple linear regression analysis resulted in coefficients of determination that ranged from 0.22 to 0.73, and discriminant analysis further improved the overall predictive ability of rust models. Finally, contour plots of soil properties and rust levels clearly suggested a link between these two parameters. These combined data suggest that sugarcane growers that apply fertilizer in excess of plant requirements will increase the incidence and severity of rust infestations in their fields.

scholarly journals Surface Complexation Modeling in Variable Charge Soils: Prediction of Cadmium Adsorption

2015 ◽  
Vol 39 (5) ◽  
pp. 1395-1405 ◽  
Author(s):  
Giuliano Marchi ◽  
Cesar Crispim Vilar ◽  
George O’Connor ◽  
Letuzia Maria de Oliveira ◽  
Adriana Reatto ◽  
...  
Keyword(s):  
Environmental Conditions ◽  
Equilibrium Constants ◽  
Surface Complexation ◽  
Surface Complexation Modeling ◽  
Adsorption Experiment ◽  
Output Data ◽  
Visual Minteq ◽  
Hand Calculation ◽  
Cadmium Adsorption ◽  
Predicted Values

ABSTRACT Intrinsic equilibrium constants for 22 representative Brazilian Oxisols were estimated from a cadmium adsorption experiment. Equilibrium constants were fitted to two surface complexation models: diffuse layer and constant capacitance. Intrinsic equilibrium constants were optimized by FITEQL and by hand calculation using Visual MINTEQ in sweep mode, and Excel spreadsheets. Data from both models were incorporated into Visual MINTEQ. Constants estimated by FITEQL and incorporated in Visual MINTEQ software failed to predict observed data accurately. However, FITEQL raw output data rendered good results when predicted values were directly compared with observed values, instead of incorporating the estimated constants into Visual MINTEQ. Intrinsic equilibrium constants optimized by hand calculation and incorporated in Visual MINTEQ reliably predicted Cd adsorption reactions on soil surfaces under changing environmental conditions.

scholarly journals Antimony (V) Adsorption at the Hematite–Water Interface: A Macroscopic and In Situ ATR-FTIR Study

Soil Systems ◽  
2021 ◽  
Vol 5 (1) ◽  
pp. 20
Author(s):  
Jerzy Mierzwa ◽  
Rose Mumbi ◽  
Avedananda Ray ◽  
Sudipta Rakshit ◽  
Michael E. Essington ◽  
...  
Keyword(s):  
Iron Oxide ◽  
Adsorption Mechanism ◽  
Surface Complexation ◽  
Outer Sphere ◽  
Surface Complexation Modeling ◽  
Surface Complexes ◽  
Ph Values ◽  
Oxide Minerals ◽  
Complexation Mechanism

The environmental mobility of antimony (Sb) is largely unexplored in geochemical environments. Iron oxide minerals are considered major sinks for Sb. Among the different oxidation states of Sb, (+) V is found more commonly in a wide redox range. Despite many adsorption studies of Sb (V) with various iron oxide minerals, detailed research on the adsorption mechanism of Sb (V) on hematite using macroscopic, spectroscopic, and surface complexation modeling is rare. Thus, the main objective of our study is to evaluate the surface complexation mechanism of Sb (V) on hematite under a range of solution properties using macroscopic, in situ attenuated total reflectance Fourier transform infrared (ATR-FTIR) spectroscopic, and surface complexation modeling. The results indicate that the Sb (V) adsorption on hematite was highest at pH 4–6. After pH 6, the adsorption decreased sharply and became negligible above pH 9. The effect of ionic strength was negligible from pH 4 to 6. The spectroscopic results confirmed the presence of inner- and outer-sphere surface complexes at lower pH values, and only outer-sphere-type surface complex at pH 8. Surface complexation models successfully predicted the Sb (V) adsorption envelope. Our research will improve the understanding of Sb (V) mobility in iron-oxide-rich environments.

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