| Research Abstract |
The objective of this research is to obtain a better understanding and better be able to predict sorption, transport and fate of environmental chemicals in urban or agricultural soil systems.
We have shown that small soil particles (colloids) adsorbed relative more chemical (pesticide) than the bulk soil, thus giving an increased risk of colloid-facilitated chemical leaching. Both chemicals showed pronounced adsorption-desorption non-singularity (sorption hysteresis) and thus has a tendency to be immobilized in the soil during soil remediation and clean-up. Also, we have developed and tested a new, rapid method ( [HPLC] Micro-column Method) for direct measurement of dissolved organic chemical transport and sorption in soil during natural water flow conditions.
We have described how the vapor sorption relates to soil-air humidity and soil-water content to soil specific surface area and soil texture. The studies concerns both volatile pesticides (diazinon) and other frequently used toxic v
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olatile organic compounds (benzene, toluene, and trichloroethylene). We have further used our Gas Chromatography [GC] Micro-column Method for direct measurement of VOC transport in unsaturated soil and analyzed the results under conditions corresponding to soil vapor extraction based clean-up of a polluted soil site. It was shown that both vapor sorption air and water permeability and gas diffusivity can significantly affect clean-up time.
We have developed a pore-size dependent model for air and gas permeability in undisturbed soil. We have developed new, more accurate models for saturated and unsaturated hydraulic conductivity in undisturbed soils, as functions of soil-water content and pore-size distribution. We have developed the first realistic models for gas diffusion coefficients in undisturbed soil as related to air permeability, pore-size distribution, and soil macro-porosity. All the new models were tested against the data for Japanese, European and American soils and showed to be more accurate than previously existing models. Less
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