Date of Award
5-2010
Document Type
Thesis
Degree Name
Master of Science (MS)
Legacy Department
Environmental Engineering and Science
Committee Chair/Advisor
Schlautman, Mark A
Committee Member
Molz, III , Fred J
Abstract
Eroded sediment and the pollutants it transports are problems in water bodies in South Carolina (SC) and the United States as a whole. Current regulations and engineering practice attempt to remedy this problem by trapping sediment according to settling velocity, and thus, particle size. However, relatively little is known about most eroded soils. In most cases, little experimental data are available to describe a soil's ability to adsorb a pollutant of interest. More-effective design tools are necessary if design engineers and regulators are to be successful in reducing the amount of sediment and sediment-bound pollutants in water bodies. This study will attempt to develop such a tool for phosphate adsorption, since phosphate is the dominant form of phosphorus found in the environment.
Eroded particle size distributions have been developed by previous researchers for thirty-four soils from across South Carolina (Price, 1994). Soil characterizations relating to phosphate adsorption were conducted for these soils, including phosphate adsorption isotherms. These isotherms were developed in the current study using the Langmuir isotherm equation, which fits adsorption data using parameters Qmax and kl. Three different approaches for determining previously-adsorbed phosphate (Q0) were evaluated and used to create Langmuir isotherms. One approach involved a least squares linear regression among the lowest aqueous phosphate concentrations as endorsed by the Southern Cooperative Series (Graetz and Nair, 2009). The other two approaches involved direct fitting of a superposition term for Q0 using the least squares nonlinear regression tool in Microcal Origin and user-defined functions for the one- and two-surface Langmuir isotherms.
Isotherm parameters developed for the modified one-surface Langmuir were compared geographically and correlated with soil properties in order to provide a predictive model of phosphate adsorption. These properties include specific surface area (SSA), iron content and aluminum content, as well as properties which were already available in the literature, such as clay content, and properties that were accessible at relatively low cost, such as organic matter content and standard soil tests. Alternate adsorption normalizations demonstrated that across most of SC, surface area-related measurements SSA and clay content were the most important factors driving phosphate adsorption. Geographic groupings of adsorption data and isotherm parameters were also evaluated for predictive power.
Langmuir parameter Qmax was strongly related (p < 0.05) to SSA, clay content, organic matter (OM) content, and dithionite-citrate-bicarbonate extracted iron (FeDCB). Multilinear regressions involving SSA and either OM or FeDCB provided the strongest estimates of Qmax (R2adj = 0.87) for the soils analyzed in this study. An equation involving the clay-OM product is suggested for use (R2adj= 0.80), as both clay and OM analysis are economical and readily-available.
Langmuir parameter kl was not strongly related to soil characteristics other than clay, although inclusion of OM and FeDCB (p < 0.10) improved fit (R2adj = 0.24-0.25). An estimate of FeDCB (p < 0.10) based on OM and carbon (Cb) content also improved fit (R2adj = 0.23); an equation involving clay and estimated FeDCB is recommended, as clay, OM, and Cb analyses are economical and readily-available. Also, as kl was not normally distributed, descriptive statistics for topsoil and subsoil kl were developed. The arithmetic mean of kl for topsoils was 0.33, and the trimmed mean of kl for subsoils was 0.91. These estimates of kl were nearly as strong as for the regression equation, so they may be used in the absence of site-specific soil characterization data.
Geographic groupings of adsorption data and isotherm parameters did not provide particularly strong estimates of site-specific phosphate adsorption. Due to subsoil enrichment of Fe and clay caused by leaching through the soil column, geography-based estimates must differentiate between top- and subsoils. Even so, they are not recommended over estimates based on site-specific soil characterization data.
Standard soil test data developed using the Mehlich-1 procedure were not related to phosphate adsorption. Also, soil texture data from the literature were compared to site-specific data as determined by sieve and hydrometer analysis. Literature values were not strongly related to site-specific data; use of these values should be avoided.
Recommended Citation
Cannon, Jesse, "Modeling Phosphate Adsorption for South Carolina Soils" (2010). All Theses. 829.
https://tigerprints.clemson.edu/all_theses/829