Understanding and Predicting the Influence of Water Quality on Contaminant Removal During Coagulation

EPA Grant Number: FP916406
Title: Understanding and Predicting the Influence of Water Quality on Contaminant Removal During Coagulation
Investigators: Davis, Christina C.
Institution: Virginia Polytechnic Institute and State University
EPA Project Officer: Jones, Brandon
Project Period: January 1, 2004 through December 31, 2006
Project Amount: $108,016
RFA: STAR Graduate Fellowships (2004) RFA Text |  Recipients Lists
Research Category: Academic Fellowships , Fellowship - Environmental Engineering , Engineering and Environmental Chemistry


Coagulation processes are key to successful treatment at most surface water treatment plants, facilitating effective reductions in turbidity, pathogens, and inorganic and organic contaminants. Existing coagulation processes often can be optimized to achieve new goals, such as improved removal of natural organic matter (e.g., disinfection byproduct precursors) and arsenic, but existing knowledge is not always sufficient to meet new challenges while maintaining effective particle removal. Design and operation of coagulation processes are currently based almost exclusively on trial-and-error testing at bench-, pilot-, or full-scale. The results cannot be applied with confidence to other water sources or even to the same water source at a different time of the year. This fundamental study will seek to bridge the knowledge gap between current practice and our existing models of coagulation and contaminant sorption. The objective is to develop the ability to quantitatively predict the most effective combination of coagulant type, dose, and pH adjustment (e.g., caustic, lime, or acid) to achieve specified regulatory or water quality targets.


In this research, surface complexation modeling (SCM) will be applied to develop fundamental models of contaminant removal for both iron and aluminum coagulant salts. Prediction of floc surface charge will be a primary goal, given its direct influence on coagulation and filtration effectiveness. Special emphasis also will be given to differentiating between contaminant removal attributable to co-precipitation and surface adsorption. The general approach for developing each SCM includes two phases. In the first phase, laboratory experiments will be conducted to form representative solids by varying pH and concentrations of silica, carbonate, natural organic matter, and sulfate. Experiments will be designed to approximate conditions typical of coagulation, including in situ formation of metal hydroxide solids in aquatic environments representative of natural waters. Sorbent properties, including surface area, site density, and binding strength, will be characterized in each test and attempts will be made to predict sorbent characteristics as a function of source water quality. The second phase of this work will utilize extensive data collected in the American Water Works Association’s National Enhanced Coagulation and Softening Database and other sources. These databases contain thousands of jar test results for source waters from around the United States, with data generated on the effectiveness of particle destabilization and organic matter removal. Iterative feedback will be implemented to determine potential knowledge gaps between model predictions based on the fundamental laboratory studies and actual performance data, and this information will be used to plan a final phase of research to attempt to reconcile theory and practice.

Supplemental Keywords:

fellowship, water quality, water treatment, coagulation, contaminant removal, surface complexation modeling, iron salts, aluminum salts, organic matter removal,, Scientific Discipline, Water, Environmental Chemistry, Engineering, Chemistry, & Physics, Environmental Engineering, coagulant dose control, contaminated waters, arsenic removal, iron, water quality, contaminant removal, aluminum coagulant salts