Struvite Scale Potential Determination Using a Computer Model

A computer model was developed and tested to predict struvite precipitation mass potential. The model validity was tested using results from a fluidized bed precipitation reactor processing wastewater treatment plant sludge liquor. Increasing interest in controlled struvite precipitation to protect wastewater treatment infrastructure and to harvest nitrogen and phosphorus from wastewater will make the model useful to engineering and plant operation practitioners. Introduction Struvite (MgNH4PO4·6 H2O) scaling in post-digestion wastewater treatment processes can cause costly operation and maintenance problems. Cost impacts result from reduced capacity, equipment damage, and system downtime. One significant problem for designers and operators faced with struvite scaling problems is quantification of the struvite scaling potential for a particular waste stream. Although recent work has enabled investigators to determine the presence or absence of struvite scaling potential, designers need to quantify that scaling potential to design remediation or preventative systems or processes (Miles and Ellis, 2001; Ohlinger et al., 1998). Accurate quantification of struvite scaling potential for a particular waste stream has historically been a complex calculation process. The literature contains much of the information needed to determine scaling potential but no commonly accepted standard calculation methodology. Therefore, it has been up to the designer to extract components of the calculation process from different literature sources and piece them together into a method to complete a laborious calculation process. The complexity of the calculation process has been a deterrent to the use of struvite precipitation potential quantification as a process planning and operation tool. Calculation of struvite equilibrium is an iterative process involving solution of a series of non-linear algebraic equations containing multiple variables, any of which can have a significant impact on the accuracy of the result. Many of the parameters are interdependent, making accurate determination of a correct solution dependent upon a thorough understanding of and an accounting for those interdependencies. This is not intended to imply that the process described cannot be readily handled by individuals with a thorough understanding of struvite chemistry and use of chemical equilibrium software. It can. Those individuals, however, are not generally the ones who need the information to make routine design and process decisions regarding struvite precipitation. The objective of the current work is to provide a robust tool for designers and process controllers to efficiently and accurately quantify struvite precipitation potential using input parameters from the user’s process. In assessing struvite precipitation potential, it is often desirable to vary the values of process variables in the calculations to determine the impacts of process changes. Such “what if” Presented June 23-26, 2003, to World Water & Environmental Resources Congress in Philadephia, PA.