Showing papers by "C. Annette Johnson published in 2010"
TL;DR: The presence of a solid solution between SO4- and CrO4-ettringite results in a stabilization of the solids compared to the pure ettringites and thus in an increased uptake of CrO 4(2−) in cementitious systems.
Abstract: Chromate is a toxic contaminant of potential concern, as it is quite soluble in the alkaline pH range and could be released to the environment. In cementitous systems, CrO42− is thought to be incorporated as a solid solution with SO42− in ettringite. The formation of a solid solution (SS) could lower the soluble CrO42− concentrations. Ettringite containing SO42− or CrO42− and mixtures thereof have been synthesized. The resulting solids and their solubility after an equilibration time of 3 months have been characterized. For CrO4-ettringite at 25 °C, a solubility product log KS0 of −40.2 ± 0.4 was calculated: log KCrO4−ettringite = 6log{Ca2+} + 2log{Al(OH)4−} + 3log{CrO42−} + 4log{OH−} + 26log{H2O}. X-ray diffraction and the analysis of the solution indicated the formation of a regular solid solution between SO4- and CrO4-ettringite with a miscibility gap between 0.4 ≤ XCrO4 ≤ 0.6. The miscibility gap of the SO4- and CrO4-ettringite solid solution could be reproduced with a dimensionless Guggenheim fitting...
49 citations
TL;DR: In this article, the authors investigated the uptake of antimony (Sb) by sunflower (Helianthus annuus L. cv. Iregi), and maize (Zea mays L.cv. Magister) in two different soils, a potting mix and an agricultural soil.
Abstract: Using pot experiments, we investigated the uptake of antimony (Sb) by sunflower (Helianthus annuus L. cv. Iregi), and maize (Zea mays L. cv. Magister) in two different soils, a potting mix and an agricultural soil. In one treatment Sb was added to the experimental soils as KSb(OH)6 (“SbV-treatment”) and in the other as Sb2O3 (“SbIII-treatment”). Soluble soil Sb concentrations were linearly related to the applied Sb rates, ranging from 0.02 (controls) to 175 mg L−1 soil solution. Accumulation of Sb tended to be slightly higher in the SbV treatment in sunflower, while no difference in Sb uptake between the two Sb treatments was found in maize. The half maximal effective concentration (EC50) values derived from the dose-response curves were higher for the SbV than for the SbIII treatment when they were related to soluble soil Sb concentrations, but differences became insignificant when they were related to shoot Sb concentrations. Maize was substantially more sensitive to Sb toxicity than sunflower, indicating physiological differences in Sb tolerance between the two plant species. Our results show that on soils with high Sb contamination, as often found in shooting ranges, plants may suffer from Sb toxicity.
45 citations
TL;DR: A global database of fluoride measurements, as well as global-scale information relevant to soil, geology, elevation, climate, and hydrology, indicated that combination of classification techniques and nonlinear predictive method (ANFIS and LR) were more reliable than others and provided a better prediction capability.
Abstract: There is an increasing interest in modeling groundwater contamination, particularly geogenic contaminant, on a large scale both from the researcher's as well as policy maker's point of view. However, modeling large scale groundwater contamination is very challenging due to the incomplete understanding of geochemical and hydrological processes in the aquifer. Despite the incomplete understanding, existing knowledge provides sufficient hints to develop predictive models of geogenic contamination. In this study we used a global database of fluoride measurements (>60,000 entities), as well as global-scale information relevant to soil, geology, elevation, climate, and hydrology to evaluate several hybrid methods. The hybrid methods were developed by combining two classification techniques including classification and regression tree (CART) and ''knowledge based clustering'' (KBC) and three predictive techniques including multiple linear regression (MLR), adoptive neuro-fuzzy inference system (ANFIS) and logistic regression (LR). The results indicated that combination of classification techniques and nonlinear predictive method (ANFIS and LR) were more reliable than others and provided a better prediction capability. Among the different hybrid procedures, combination of KBC-ANFIS and also CART-ANFIS resulted in larger true positive rates and smaller false negative rates for both training and test data sets. However, as the CART classifier is very unstable and very sensitive to resampling, the combination of KBC and ANFIS is preferred as it not only is more robust but also is flexible enough to account for geohydrological conditions.
19 citations