Previous attempts to use fly ash as a soil amendment have had limited success because of its low nutrient value, low cation exchange capacity (CEC), and elevated levels of toxic trace elements. However, treating fly ash with NaOH or KOH at an elevated temperature converts the ash into zeolite minerals and solubilizes the toxic trace elements, which are removed in the base solution. The CEC of the untreated fly ash was <100 mmolC kg-1 but increased to over 3000 mmolC kg-1 when heated for 3 days at 100 °C in 3 M NaOH. The dominant zeolites formed at 100 °C in NaOH were zeolite Na-Pl and zeolite P-C, and at temperatures of 150−250 °C, the mineralogy changed to zeolite X and pectolite. In KOH at 100 °C, zeolite K-G (potassium chabazite) was formed. The fly ash zeolites had a high affinity for K+, Ca2+, and NH4 +, although attempts to use the treated ash to remove NH4 + and heavy metals from wastewater and electroplating wastes were only partially successful. Potential uses of the treated ash were limited due to the high pH that resulted from the dissolution of the zeolite minerals. At pH 4 and pH 5, the rate of fly ash zeolite dissolution was 1000 times faster than most aluminosilicate minerals. Attempts to produce a zeolitic material with NH4OH or fluorides were not successful.

No abstract

No abstract

Digital soil mapping has been introduced as a viable alternative to the traditional mapping methods due to being fast and cost-effective. The objective of the present study was to investigate the capability of the vegetation features and spectral indices as auxiliary variables in digital soil mapping models to predict soil properties. A region with an area of 1225 ha located in Bajgiran rangelands, Khorasan Razavi province, northeastern Iran, was chosen. A total of 137 sampling sites, each containing 3-5 plots with 10-m interval distance along a transect established based on randomized-systematic method, were investigated. In each plot, plant species names and numbers as well as vegetation cover percentage (VCP) were recorded, and finally one composite soil sample was taken from each transect at each site (137 soil samples in total). Terrain attributes were derived from a digital elevation model, different bands and spectral indices were obtained from the Landsat7 ETM+ images, and vegetation features were calculated in the plots, all of which were used as auxiliary variables to predict soil properties using artificial neural network, gene expression programming, and multivariate linear regression models. According to R RMSE and MBE values, artificial neutral network was obtained as the most accurate soil properties prediction function used in scorpan model. Vegetation features and indices were more effective than remotely sensed data and terrain attributes in predicting soil properties including calcium carbonate equivalent, clay, bulk density, total nitrogen, carbon, sand, silt, and saturated moisture capacity. It was also shown that vegetation indices including NDVI, SAVI, MSAVI, SARVI, RDVI, and DVI were more effective in estimating the majority of soil properties compared to separate bands and even some soil spectral indices.

Alfalfa (Medicago sativa L.) was grown in greenhouse sand culture to examine the effect of salinity composition and concentration on Se accumulation by plants. In a 2 • 2 x 4 factorial experiment, salinity was added as either C1-or SO~-salts to the irrigating solution to achieve an electrical conductivity of 0.5, 1.5, 3.0, or 6.0dSm -t Selenium was added to the nutrient solution at a concentration of 0.25 or 1.0 mg Se(VI) 1-t. Following the third cutting, the roots were washed and all plant material analyzed for dry weight and Se. Plant biomass production decreased with additions of either Se or salinity, regardless of composition. In the presence of Se, the yield reduction was greater with C1-salinity than with SO~4-salinity. Plant Se accumulation was reduced from 948 mg Se kg-I to 6 mg Se kg -1 in the presence of SO42-salts (0.5mmol SO 2-1 -l vs. 40mmol SO42-1 -t) due to an apparent Se(VI) -SO42-antagonism. This Se-SO 2-antagonism prevented accumulation of Se and reduced Se-induced toxicity. A lesser antagonistic effect on Se accumulation was observed between C1-and Se. A synergistic interaction between SO 2-and Se(VI) increased plant S concentrations in the presence of the relatively low basal SO~-concentrations but not at the higher solution SO 2-concentrations. In many areas, soil and water containing high Se concentrations also contain large amounts of SO~-. The occurrence of SO~-with Se reduces plant accumulation of Se(VI) and may lower the risk of Se overexposure to animals feeding on forage material grown in high Se-SO 2-regions.