Quantitative Evaluation of Wastewater Feed Quality for Struvite Crystallization

摘要

Phosphorus recovery via struvite crystallization is a promising technology for closing the loop in the phosphorus life cycle. However, the spatial and temporal variation of wastewater composition has a detrimental effect on the produced struvite purity, thus reducing its economic value. To address this challenge, this paper investigates the effect of the wastewater composition on struvite purity using response surface models and an artificial neural network. Further principal component analysis indicated that high phosphorus removal efficiency and high struvite purity depend heavily on the wastewater composition and can be improved through magnesium addition in most cases. However, when the wastewater is simultaneously rich in calcium and low in phosphorus, struvite crystallization becomes economically unfeasible, even with supplementary magnesium. The model developed can be used as a preliminary tool to check whether the desired product is attainable and if, and how much, magnesium would need to be used to compensate for low product quality in various wastewater streams.