Comparison of Struvite and K-Struvite for Pb and Cr Immobilisation in Contaminated Soil

Abstract

Struvite is a value-added product recovered from the phosphorus-rich wastewater treatment by adding magnesium. Struvite is mainly used as slow-release fertilisers containing phosphate that can form insoluble salts with certain heavy metals. Hence, struvite may have potential application as a phosphate remediation agent for immobilisation of heavy metals in contaminated soil, while the related study is limited. Similarly, an analogue compound of struvite, K-struvite, may also have this value but has not been reported elsewhere. This study investigated the effect of struvite and K-struvite on the remediation of Cr-spiked and Pb-spiked soil. To evaluate the feasibility, the agent dosage and two quality parameters (particle size and purity) of struvite and K-struvite were considered for the experimental design and statically analysed by PCA and PLS. The results show that the dosage significantly impacts the immobilisation process, while the effect of particle size and purity are negligible. Struvite and K-struvite have similar performance on heavy metals immobilisation, and both are significant in Pb immobilisation (up to 96% of F5, stable fraction) and are beneficial for reducing the most mobilised fractions (F1 and F2) of Cr to lesser than 3%. Struvite and K-struvite share similar performance due to their similar atomic radius, and the different performance between Cr and Pb immobilisation can be explained by the strong hydrolysis trend of chromium ion, which may inhibit the binding of the phosphate and chromium. The kinetic study finds that all three variables positively impact the free chromium ion, and the immobilisation process is a fast reaction so unlikely to be kinetically limited. These findings of this project will provide insight into how the immobilisation process changes in response to the dosage and quality of struvite compounds.

Keywords: Struvite, K- Struvite, Soil remediation, Heavy metals immobilisation, Multivariate data analysis