Phosphorus Sequestration and Recovery with Calcium: Validating Chemical Equilibrium and Process Models with Case Studies

Novelty and Relevance: This study applies a chemical equilibrium model for brushite precipitation in AD effluent and compares the results with BioWin and XRD analysis. Based on literature review, this is the first paper that investigates the applicability of Visual MINTEQ (V MINTEQ) for calcium phosphate precipitation in wastewater and a side-by-side comparison of V MINTEQ with a wastewater simulator such as BioWin. To date, technology provider inputs have been used for estimating the calcium dose to sidestreams for brushite recovery. This study attempts at verifying results from BioWin and V MINTEQ as additional tools to estimate Ca dosing and brushite recovery using full scale data. Methodology and Materials: Samples and XRD Analysis: Four AD samples for City of Longmont and two Post Aerobic Digester (PAD) samples from City of Boulder WRRF and Metro Water Recovery NTP were obtained for analytical measurements and XRD analysis. The chemical characteristics of the sludge samples are shown in Table 1. Sample 2 was used for bench scale testing at Ca/P molar ratios of 1.5, 2.5, and 3.5 with addition of 20% CaCl2. V MINTEQ Set up : V MINTEQ v3.1 (KTH Vetenskap Och Konst, Stockholm, Sweden) was used to predict the precipitates formed in samples using a constant pH approach at 35 degrees C. Details of model set-up and revisions are described in full paper. Experimental Set up: Bench scale experiments were performed using a sample of AD (City of Longmont WRRF) at room temperature. CaCl2 was added, samples were stirred at 200r/min using a magnetic stirrer, and pH was measured after 45 minutes. Photos 1 and 2 show the samples for Conditions 2 and 5 after mixing has stopped. There was no clear visual sign for precipitants formed. Final pH for sample conditions 3, 4, and 5 were 7.2, 7.05, and 6.9, respectively. Samples were sent for XRD analysis and Ortho-P measurements. BioWin Modeling : A whole plant BioWin model was set up in BioWin 6.2 for Condition 1 for City of Boulder WRRF (Figure 1) and Conditions 2-5 for City of Longmont WRRF (Figure 2 and 3). Results and Discussion: Testing the Validity of Model Results: The quantitative crystalline phase analysis for conditions 1 to 6 is shown in Table 2. The observations made based on XRD analysis are presented in Table 3. Figure 4 shows the XRD pattern for condition 1. XRD results for conditions 2 to 5 are presented in Figures 5 to 8, respectively. Figure 9 shows the XRD pattern for condition 6. V MINTEQ Results: Table 4 shows the model output for major precipitates with positive saturation index which indicates supersaturation as well as the solids in finite state (in equilibrium). The observations made based on V MINTEQ are presented in Table 5. The Ortho-P reduction, as predicted by V MINTEQ, is compared with actual data in Table 6 for Conditions 3 to 5. V MINTEQ underpredicted the Ortho-P removal. V MINTEQ estimated that the Ortho-P reduction was linked to precipitation of calcium phosphate. The % of total phosphate in dissolved form decreased from 56% for condition 2 to 36% with increasing Ca:P ratios from 1.5 to 3.5. BioWin Model Results: Condition 1 : The BioWin model (Figure 1) was calibrated for influent fractionation, effluent quality, and solids production. The model predicts ammonia, pH, and alkalinity well, overpredicts ortho-P concentration and underpredicts metals (Table 7). Figure 10 shows the precipitates and concentrations in AD and PAD. Brushite is formed in PAD, along with small concentrations of ferrous sulfide and vivianite. This is consistent with the findings of XRD analysis, indicating presence of vivianite and amorphous material which most likely includes Amorphous Calcium Phosphate. Conditions 2 to 5 : Dynamic modeling for the existing conditions at City of Longmont WRRF was conducted (Figure 2). The model predicts digester Ortho-P, Ca, and Mg very well (Figure 11). The results of BioWin modeling for Conditions 2 to 5 are presented in Table 8. For Condition 2, BioWin predicted all the key constituents very well, including Ca and Mg in AD. The Ortho-P reduction for Condition 3 at Ca/P ratio of 1.5 is about 11% higher than actual value. The Ortho-P reduction for Conditions 4 and 5 at Ca/P molar ratios of 2.5 and 3.5, respectively are overpredicted by BioWin. At such high metal/P ratios, the Ortho-P reductions predicted by BioWin do not seem unreasonable. The removal rates based on experimental data seem to be relatively low, which may be due to the operational conditions of the bench scale testing. Comparison of Models: Comparison of two models with XRD analysis was conducted for conditions 2 to 5 (Table 9). Mineral species predicted by BioWin and V MINTEQ are generally in agreement. While BioWin predicts some small quantities of struvite formed in Conditions 3 and 4, V MINTEQ does not predict any struvite formation. XRD predicts some amorphous content which is likely calcium phosphate and no struvite. For Condition 5, both models predict increased quantities of calcium phosphate species with no struvite formation, which is consistent with XRD analysis. Summary and Conclusions: The results indicate that while a chemical equilibrium can be helpful in predicting the precipitation of brushite and other phosphate-bearing minerals, BioWin was able to predict precipitates formation and Ortho-P reduction reasonably well. Verification results with XRD demonstrated that BioWin can be reliably used to determine Ca-P precipitates in AD.