WEF Residuals and Biosolids Conference 2017

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1 Pilot-scale Evaluation of for Digestate Treatment Blair Wisdom 1 *, Brad Van Anderson 1, Isaac Avila 1, Troy Gottschalk 1, Kurt Carson 1, Liam Cavanaugh 1 1 Metro Wastewater Reclamation District, Denver, Colorado * BWisdom@mwrd.dst.co.us ABSTRACT Waste sludge from biological phosphorus removal systems has been associated with negative impacts to anaerobic solids digestion and dewatering processes. Ahead of instituting a largescale full plant biological phosphorus removal process, Metro Wastewater Reclamation District staff conducted an in-depth pilot-scale investigation of (CNP-Technology Water and Biosolids Corp., Kenosha, WI) as a possible approach to mitigate undesirable effects of Bio-P on the facility s solids treatment and handling processes. Results from the evaluation concluded that pretreatment of digestate by an type technology to promote in-vessel struvite formation was effective at sequestering phosphorus from the dewatering recycle stream and reducing struvite formation potential in downstream equipment. In addition, this pretreatment resulted in a 15 to 20 percent reduction in polymer required for dewatering and a notable increase in dry cake solids leading to an overall 7 to 10 percent reduction in biosolids hauling requirements depending on the degree to which struvite is recovered as a separate fertilizer stream or commingled with the biosolids. KEYWORDS: Phosphorus, struvite, dewaterability, resource recovery INTRODUCTION The Metro Wastewater Reclamation District s (District) 220 MGD (833 MLD) Robert W. Hite Treatment Facility (RWHTF) currently serves 1.8 million population. This large-scale facility with anaerobic digestion is transitioning to enhanced biological phosphorus removal (Bio-P) to address nutrient over-enrichment of the South Platte River watershed. Waste Bio-P sludge has been associated with negative impacts on anaerobic solids digestion and dewatering processes (Shimp, Barnard, & Bott, 2013). It is also well known that Bio-P can exacerbate struvite formation in anaerobic digesters and downstream processes. The District conducted an in-depth pilot-scale investigation of (CNP-Technology Water and Biosolids Corp., Kenosha, WI) as a possible approach to mitigate undesirable effects of Bio-P on the RWHTF s solids treatment and handling processes. (and other similar digestate treatment processes) imparts a slight aeration velocity to the digestate inside a dedicated reactor to strip some of the carbon dioxide (CO2) and elevate the ph. Under elevated ph conditions magnesium (Mg) is added to the reactor to precipitate with phosphate (PO4 3- ) in order to predominately form struvite (NH4MgPO4 6H2O). The resulting change in chemistry of the digestate has been associated with reduced polymer demand and increased biosolids cake dryness. Several theoretical explanations are proposed to help describe these observations (Higgins & Novak, 1997) (Bergmans, Veltman, van Loosdrecht, van Lier, & Rietveld, 2014). 119

2 The District used five drivers to help define an effective overall approach for management of phosphorus once removed from wastewater. These drivers are to (i) break the phosphorus recycle loop that otherwise occurs during dewatering of anaerobically digested sludge (ii) to counter the impact that Bio-P can have on dewatering performance and biosolids hauling costs, (iii) reduce or eliminate problematic struvite scaling in piping and equipment and accumulation inside the digesters (Cavanaugh, Khunjar, Atwater, Carson, & McQuarrie, 2016), (iv) reduce the phosphorus relative to nitrogen in the biosolids product to create a more balanced product for nitrogen-intensive wheat and corn crops and (v) recover phosphorus in a form that is valued as a fertilizer product. MATERIALS AND METHODS The pilot system is a stand-alone mobile treatment process. The main setup for the pilot-scale evaluation included a 40 foot (12.2 meters) tall reactor with struvite recovery system, magnesium chloride (MgCl2) chemical feed, and a 10-inch (25.4 centimeter) diameter dewatering centrifuge (Centrysis CS10-4) as shown in Figure 1. Figure 1: Reactor (left) and Centrysis Centrifuge Dewatering (right) A turbo blower and air compressor each supply air to two sparging rings installed at different heights within the reactor. Air sparging circulates and mixes the reactor contents and strips some CO 2 from the digestate increasing the ph to around 7.9. As magnesium concentration is typically limiting the struvite precipitation reaction, a liquid solution of 30 percent MgCl2 was fed to create the desired molar ratio of Mg 2+ to phosphorus (Mg:P) entering the reactor with the digestate. Once precipitated, the struvite crystals (specific gravity 1.7) increase in size with a fraction settling in the conical section of the reactor. The remaining struvite crystal fraction that did not settle remained within the biosolids matrix and discharged with the reactor effluent. The settled struvite was harvested from the reactor by periodically opening a discharge valve at the bottom of the cone with the flow routed to a grit classifier. The classifier used plant water to clean the struvite. The harvested struvite was discharged from the classifier into a collection container. 120

3 Hach test kits were used to field monitor the incoming PO4 3- concentration of the digestate and the Mg dose was adjusted accordingly. During the final three weeks of the evaluation the Mg:P ratio was varied to examine the effect that changing this parameter would have on performance. Both the Untreated and Treated digestate feeds were sampled and analyzed each week by a certified laboratory as summarized in Table 1. Table 1 - Sampling Schedule and Analyses 1,2 Parameter Reactor Centrifuge Influent Underflow Effluent Influent Centrate Cake ph Temperature Total Solids (TS) 3 Volatile Solids 3 (TVS) Total Ca, Mg, Fe, K, Na Dissolved Ca, Mg, Fe, K, Na Orthophosphate Total Phosphorus Water Extractable Phosphorus 4 4 Acid-cake Struvite Test 5 Ammonium Conductivity Total Alkalinity CODEPS 1 All analysis conducted once per week unless otherwise noted. 2 All analysis conducted using grab samples. 3 Daily. 4 One time during study. 5 Untreated cake samples collected on 1/21/2016 and 8/29/2016 and treated cake samples collected on 7/29/2016 and 8/3/2016. Throughout the evaluation, both polymer consumption and dewatered cake solids measurements were collected weekly on centrifuge operation for both the Untreated Digestate feed as well as the Treated Digestate. For each feed type the rate of polymer addition progressed through a prescribed dosage range. Machine performance data was collected for each setting. Biosolids dewatering performance was assessed using two criteria; (i) dewatering polymer throughput use and (ii) the ultimate wet tons of biosolids generated from dewatering. Both assessment criteria require that special consideration be given to the influence that struvite mass has on the results as well as the analytical corrections required to fully address struvite mass in a given sample. 121

4 Correction to total solids results for struvite content The ammonium (NH 4 + ) and six water molecules that contribute to struvite have been observed to decompose under thermal heating. Mass loss begins at a temperature of 55 o C and is complete at a temperature of 250 o C (Bhuiyan, 2007). A correction was applied to the laboratory measured dewatered biosolids TS result to account for mass loss when the sample was dried at 104 o C. This study assumed that all of the water and NH4 evaporated during heated drying resulting in a 51.4 percent loss (126 g/mol out of 245 g/mol total) of struvite mass. The TS cake solids laboratory measurements were thus corrected using Equation 1. An intention of the reactor is to generate struvite out of the soluble PO4 3- entering the reactor with the digested solids. Some of this struvite settles in the reactor and leaves with the underflow. However, a majority of the additional struvite generated remains in the biosolids matrix. The struvite retained in the biosolids increases the dry mass of dewatered biosolids produced at the facility. In order to estimate the additional struvite, acid extraction tests (acidcake) were performed to quantify Mg 2+ and PO4 3- released from the cake sample and generate an estimate of the percentage of the overall dewatered biosolids mass that was attributed to struvite. Equation 1 below was used to correct the %TS of the cake solids for untreated biosolids to account for the mass loss due to struvite decomposition during sample drying. Equation 1 %TTTT CCCCCCCCCCCCCCCCCC UUUUCCCCCCUUCCCCCC = %TTTT MMCCUUMMMMCCCCCC (1 + (% SSCCCCMMSSSSCCCC Content 0.514)) Whereas, %TS Corrected Untreated = Lab result %TS corrected for struvite content in untreated biosolids, %TSMeasured = Laboratory result %TS, and %Struvite Content = Estimated mass fraction of struvite in untreated biosolids. Similarly, Equation 2 provides the corrected dry ton production for untreated biosolids to account for struvite mass loss. As described in Discussion of Results, full-scale dry ton data from the RWHTF was used in conjunction with the pilot-scale performance data to project and communicate comparative dewatering performance between the Untreated and Treated feed streams. Equation 2 TTTTTTTTTT DDDD CCCCCCCCCCCCCCCCCC UUUUCCCCCCUUCCCCCC = DDDD MMCCUUMMMMCCCCCC (1 + (% SSCCCCMMSSSSCCCC Content 0.514)) Whereas, DT Corrected Untreated = Measured dry ton result corrected for its struvite content, DTMeasured = From full-scale centrifuge throughput and performance data, and %Struvite Content = Estimated mass fraction of struvite in untreated biosolids. 122

5 Similar to Equation 1, Equation 3 corrects the measured %TS results for struvite mass loss during drying. Equation 3 %TTTT CCCCCCCCCCCCCCCCCC TTCCCCUUCCCCCC = %TTTT MMCCUUMMMMCCCCCC (1 + (% SSCCCCMMSSSSCCCC Content 0.514)) Whereas, %TS Corrected Treated = Lab result %TS corrected for struvite in treated biosolids, %TS Measured = Laboratory result %TS, and %Struvite Content = Estimated mass fraction of struvite in treated biosolids. For the Treated feed stream to the centrifuge, it was also necessary to estimate the additional struvite mass added to the biosolids during treatment. The amount of struvite additionally produced was estimated based on observed PO 4 3- conversion across the reactor. This value was then adjusted based on expected struvite recovery determined from the acid-cake test results. The total dry tons of dewatered biosolids, including struvite, was calculated by adding the unrecovered generated struvite to the struvite-corrected facility dewatered biosolids dry tons (See Equation 4). Equation 4: TTTTTTTTTT DDDD CCCCCCCCCCCCCCCCCC TTCCCCUUCCCCCC = DDDD AAAAAAPPCCCCPP SSCCCCMMSSSSCCCC + DDDD CCCCCCCCCCCCCCCCCC UUUUCCCCCCUUCCCCCC Whereas, Total DT Corrected Treated = Corrected Untreated Total DT plus added struvite, DTAirprex Struvite = Estimated struvite added based on PO4 3- conversion and recovery DTCorrected Untreated = From Equation 2. Finally overall facility wet hauling requirements resulting from either type of biosolids stream were calculated using Equation 5 Equation 5: HHHHHHHHHHHH WWWWWW TTTTTTTT = TTTTTTTTTT DDDD CCCCCCCCCCCCCCCCCC %TTTT CCCCCCCCCCCCCCCCCC Whereas, Total DTCorrected = From Equation 2 or Equation 4, and %TS Corrected = From Equation 1 or Equation

6 Assessment of Struvite Formation Potential Two different models were used to predict struvite formation potential. Struvite Tool (Office of Water Programs, Sacramento, California) was developed to predict struvite formation potential in a fluidized bed precipitation reactor. The model produced comparable results of struvite formation potential when compared with Visual Minteq (Ohlinger & Mahmood, 2003). The reactor, while not technically a fluidized bed reactor, operates similarly. Struvite Tool requires inputs for Mg, NH4, OP, conductivity, ph, temperature, and flow, and outputs struvite production, residual Mg, residual NH4, residual OP, and saturation index. Struvite Tool can generate struvite production and formation potential estimates with simplified inputs and does not incorporate other precipitation reactions, making the tool simple to use. This was the primary tool used to assess struvite formation potential The second tool, Visual Minteq (KTH, Sweden) is a chemical equilibrium model program with a vast database of thermodynamic constants used for modeling precipitation in natural waters. It has been used to model struvite precipitation in complex sludge matrices in various studies (Ali, Schneider, & Hudson, 2003; Celen, Buchanan, Burns, Robinson, & Raman, 2007). A working knowledge of equilibrium chemistry is required to apply the model appropriately for systems with complex chemical and biological dynamics. The procedure outlined by Celen et al, 2007, for using Visual Minteq to model mineral precipitation in anaerobic digester was followed for this study While the above tools are useful in determining struvite formation potential in the Untreated and Treated digestate streams, a calibrated and validated full plant BioWin model (EnviroSim Associates, Hamilton, Ontario) was needed to assess the impacts that breaking the phosphorus recycle loop could have on struvite formation in the digesters. DISCUSSION OF RESULTS The pilot system began operation on June 6, 2016 and ended August 3, With the exception of a few operational interruptions due to scheduled plant maintenance, the reactor operated continuously. Digestate from the full-scale digested sludge holding tank was pumped to the reactor at a constant flow of 11 gallons per minute (gpm) (41.6 lpm). The pilot centrifuge was configured such that it could be fed Untreated Digestate directly from the full-scale holding tank or Treated Digestate from the reactor. The centrifuge was operated for 6 to 8 hours per day during weekdays to generate dewatering performance curves across a set range of polymer doses for each of the two feed types; Untreated Digestate and Treated Digestate. Initial testing was conducted using Praestol K260-FL and K290-FL polymers, however following the polymer optimization, the majority of testing utilized BASF Zetag For most of study, the Mg:P ratio for the reactor was held between 1.1:1 and 1.5:1 with a target PO4 3- conversion of 90 percent. For each centrifuge machine run the polymer dose was adjusted in 5 pound per dry ton increments with accompanying total solids (TS) and volatile solids (VS) measurements. Machine performance data was collected using polymer doses between 1.60 and 6.20 active pounds per hour which equates to a range between 24.8 and 73.7 active pounds per dry ton (12.4 to 36.9 kilograms per metric ton) based on feed solids TS measurements determined using standard drying procedures at 104 o C. The volumetric sludge throughput of the centrifuge was varied between 8 and 20 gpm (30.3 to 75.7 lpm) though the vast 124

7 majority of testing was conducted at machine feed rates of either 10 or 15 gpm (37.9 to 56.8 lpm). The hydraulic pressure in the centrifuge was adjusted by the Centrisys operator to find ideal dewatering operating conditions for each feed type. The centrifuge hydraulic pressure ranged from 41 to 131 bar with an average of 80 bar on the Untreated Digestate runs, and ranged from 39 to 210 bar with an average of 102 bar on the Treated runs. Breaking of the Phosphorus Recycle Loop Figure 2 summarizes the centrate phosphorus results collected during the study. The average Total Phosphorus (TP) concentration of the untreated recycle centrate was 259 mg-p/l. The PO 4 3- concentration was observed to decrease in the centrate as the Mg:P molar dosing ratio increased. Digestate pretreatment in the system using a Mg:P molar dosing ratio of 1.4:1 resulted in greater than 90 percent conversion of PO 4 3- and corresponding removal of TP in the centrate return stream. At a still higher 1.7:1 dose ratio, the PO4 3- concentration further decreased to an average concentration of 8.5 mg/l. However, TP began to increase, possibly indicating a high formation of smaller struvite crystals or fines that are not removed with the biosolids matrix. Higher concentrations of Mg have been shown to affect the size distribution of struvite crystals, as well affecting the purity due to an increase of additional Mg precipitates (Korchef, Saidou, & Amor, 2011). A magnesium chloride feed dose corresponding to a Mg:P molar ratio of 1.4:1 was observed to be the optimal ratio for limiting the TP in the recycle stream. Phosphorus, mg/l Typical Untreated Mg:P 0.7:1 Mg:P 1.4:1 Particulate Phosphorus Orthophosphorus Mg:P 1.7:1 Figure 2: Phosphorus Recycle Load Control Untreated Digestate Centrate (left) and Treated Centrate at Three Different Mg Doses (right) Figure 3 illustrates steady-state BioWin model results which help to show how lowering the recycle phosphorus load helps to reduce the secondary effluent from 0.26 mg/l P to 0.1 mg/l P. 125

8 Seciondary Effluent Soluble P, mg/l No Recovery Digestate Centrate Recycle Soluble P, mg/l Secondary Effluent Soluble P Centrate Recycle Soluble P Figure 3: Phosphorus Recycle Load Control and Resulting Secondary Effluent PO4 3- Concentrations Biosolids Dewatering Equations 1, 2 and 3 defined in the Materials and Methods require an estimation of the struvite content in the dewatered biosolids. Table 2 summarizes the results from the acid-cake tests. On average about 5.3 percent of the untreated biosolids mass was in the form of struvite. In comparison, about 11.7 percent of the treated biosolids mass was in the form of struvite. Given the recovery of the pilot treatment system, the total dry solids production increased by approximately 6 percent. Based on the results of the acid-cake testing on the treated digestate and the calculated struvite production (based on converted PO4 3- in the reactor), it was estimated that the struvite product capture averaged 20 percent during the pilot, resulting in 80 percent of the produced struvite remaining in the biosolids. Table 2: Measured Struvite Concentration in the Dewatered biosolids Sample Date Sample Stream Average Concentration of Struvite in Dewatered Biosolids (% mass struvite per total mass) 1/21/2016 Untreated 5.6% 7/29/2016 Treated 11.1% 8/3/2016 Treated 12.3% 8/29/2016 Untreated 5.0% Table 3 summarizes the results of the dewatering improvements assessment. The TS measurements were corrected as described in the Materials and Methods using Equations 1 and 3. Pilot-scale performance results were projected to full-scale using the average facility dewatered biosolids dry mass generated during the study period. During June and July 2016; the RWHTF generated 84.3 dry tons of biosolids per day. Using Equation 2 to adjust for struvite mass loss during sample drying, the corrected value for Untreated is 86.6 dry tons of biosolids per day. The amount of struvite produced in the reactor was estimated to be 7.4 tons per day if applied at full scale. This is based on 90 percent conversion of the PO 4 3- passing through the reactor with the digestate. Accounting for the observed 20 percent product recovery, the resulting 126

9 increase in dewatered biosolids mass from the process would be 5.9 tons per day. From Equation 4, the total dry tons of dewatered biosolids, including struvite, leaving the facility post- would be 92.5 dry tons per day. Dewatering Polymer Consumption Total polymer consumption was based on a mass flow basis (active pounds of polymer per hour) for the purposes of this comparison. The doses in pounds of active polymer per hour were averaged for each dataset for the digestate and the treated digestate centrifuge runs, and the variation in total polymer use between them was compared on a percent change basis. Four datasets were generated from the study period for the examination of impacts on biosolids dewaterability. Variables in the centrifuge operation were systematically removed as the datasets progressed in order to perform more refined calculations on the anticipated full-scale impacts of an system at the RWHTF. The four datasets that were refined for further examination are: Dataset 1 (n=297) - All valid study period centrifuge dewatering data was included in this dataset. Only data points with obvious data errors (such as zero polymer flow) were eliminated to develop this dataset. Dataset 2 (n=197) - The data points in Dataset 1 were sorted to remove variability in centrifuge sludge throughput rates and polymer types. Only data points with 10 gpm and 15 gpm centrifuge sludge feed throughputs were accepted due to the fact that the majority of centrifuge runs were conducted at those two throughputs to simulate anticipated scaleup throughputs. Additionally, only data points where the BASF Zetag 8849 polymer was used for the centrifuge dewatering were accepted due to that polymer being solely used during the majority of the study. Dataset 3 (n=61) - The data points in Dataset 2 were evaluated to further remove variability in centrifuge sludge throughput rates, and to eliminate the variability in Mg dosing rates for different OP removal targets. Only data points with a 10 gpm centrifuge sludge feed throughput were accepted based on the 10 gpm having the largest number of data points to simulate the design point for future full-scale centrifuge dewatering facilities. Additionally, only data points with a 90% OP removal target were accepted (correlating to an approximate 1.4:1 Mg:P dosing ratio) in order to match the anticipated design point for a full-scale system that would remove the maximum amount of TP (as described in the analysis of the effectiveness of at breaking the recycle phosphorus loop). Dataset 4 (n=20) - The data points in Dataset 3 were assessed to further remove variability in the centrifuge operational settings, and to remove variability in digestate characteristics. Data pairs of one digestate data point and one treated digestate data point were pulled from Dataset 3. The pairs had to meet the criteria of both being within three days of each other in order to ensure consistent digestate OP concentrations, and to have centrifuge hydraulic pressures within 20 bar of each other in order to eliminate the biasing effect of the centrifuge to achieve better dewatering results at higher hydraulic pressure settings. Once a data point was pulled into a pair, it was not used again in another pair. Ultimately, Dataset 4 contained 20 data points (10 pairs) that met the evaluation criteria. Two pairs were three days apart, four pairs were one day apart, and four pairs were on the same day. The average hydraulic pressure of the data points was 127

10 93.5 bar, and the average difference in the hydraulic pressures of the data pairs was 7.1 bar, with a maximum of 16 bar and a minimum of 1 bar. Four data pairs had a higher hydraulic pressure for the data point, one pair had a higher hydraulic pressure for the digestate data point, and five data pairs had a hydraulic pressure difference of 5 bar or less. The data pairs in Dataset 4 were evaluated both by averaging all digestate and data points when each were lumped together, and by generating the dewatered biosolids TS and polymer dose differences for each pair and then averaging those individual results. Table 3 provides the results of the dewatering analysis for the four data sets including raw measurements and corrections as described in the Materials and Methods section. Curves showing the polymer consumption and uncorrected dewatered biosolids TS concentrations are displayed in Figure 4a, b, c and d for each of the data sets. 128

11 Table 3 - Summary of Biosolids Dewaterability Impacts Column Data Set # Untreated Dewatered biosolids Mass Dry Tons per Day 1 Untreated Dewatered biosolids %TS 2 Untreated Dewatered biosolids %TS (Corrected) 3 Untreated Corrected Dewatered Biosolids Wet Tons per Day 4 Untreated Polymer Dose Active lbs/hr 5 Dewatered biosolids Mass Dry Tons per Day 6 Dewatered biosolids %TS 7 Dewatered biosolids %TS (Corrected) 8 Treated Polymer Dose Active lbs/hr 9 Corrected Dewatered biosolids Wet Tons per Day 10 Wet Tons Reduction 11 Polymer Reduction % 21.23% % 24.90% % -0.86% % 21.72% % 25.15% % -1.45% % 21.73% % 26.52% % 0.67% % 21.89% % 25.62% % 17.61% Footnotes 1. Measured from full-scale dewatered biosolids production during the pilot study period. 2. Average measured total solids of untreated digestate dewatered biosolids from the pilot centrifuge. 3. Corrected total solids concentrations of untreated digestate dewatered biosolids from Equation 1 in Materials and Methods. 4. Average wet tons production of untreated digestate from Equation 5 in Materials and Methods. 5. Polymer consumption for dewatering untreated digestate expressed on a mass flow basis. 6. Estimated dewatered biosolids production of treated digestate based on observed pilot OP conversion, 20% product recovery, and full-scale biosolids flows and loads. 7. Average measured total solids of treated digestate dewatered biosolids from the pilot centrifuge. 8. Corrected total solids concentrations of Airprex treated digesatate dewatered biosolids from Equation 2 in Materials and Methods. 9. Polymer consumption for dewatering treated digestate expressed on a mass flow basis. 10. Average wet tons production of treated digestate from Equation 5 in Materials and Methods. 11. Percent difference between the wet tons of untreated and treated dewatered biosolids. 12. Percent difference between the untreated and treated polymer dose. 129

12 Cake % Total Solids (Uncorrected for Struvite) 29% 27% 25% 23% 21% 19% 17% 15% Effluent Digestate Polymer Dose (Active Pounds per Hour) Figure 4. a) Dewatered Biosolids Total Solids Concentration Versus Polymer Dose for Dataset 1 29% Cake % Total Solids (Uncorrected for Struvite) 27% 25% 23% 21% 19% Effluent 17% 15% Digestate Polymer Dose (Active Pounds per Hour) Figure 4. b) Dewatered Biosolids Total Solids Concentration Versus Polymer Dose for Dataset 2 130

13 29% Cake % Total Solids (Uncorrected for Struvite) 27% 25% 23% 21% 19% Effluent Digestate 17% 15% Polymer Dose (Active Pounds per Hour) Figure 4. c) Dewatered Biosolids Total Solids Concentration Versus Polymer Dose for Dataset 3 29% Cake % Total Solids (Uncorrected for Struvite) 27% 25% 23% 21% 19% 17% Effluent Digestate 15% Polymer Dose (Active Pounds per Hour) Figure 4. d) Dewatered Biosolids Total Solids Concentration Versus Polymer Dose for Dataset 4 131

14 There is similarity in polymer doses when averaging the large amount of data in Datasets 1-3 because both the untreated digestate and treated digestate centrifuge tests were prescriptively run through the same range of polymer doses to generate the necessary detailed dewatering information. When specific pairs of dewatering points were identified for Dataset 4 by eliminating all other factors, there was a decrease of 17.6 percent polymer consumption for the effluent centrifuge runs over the untreated digestate. Additionally, when polymer differences were calculated for each data pair, and then averaged, the calculated decrease in polymer consumption for Dataset 4 was 16.5 percent for the effluent. There were no instances in the data pairs where the untreated digestate polymer dose was lower than the treated digestate polymer dose. Additional analyses of the decrease in total wet tons from treatment were performed on Dataset 4 to evaluate the sensitivity of the reduction in total wet tons of either dewatered biosolids produced when the assumed struvite recovery in the reactor varied, or when the struvite mass evaporated was modified. When the struvite recovery amount in the pilot reactor was varied from 0 percent to 35 percent of the generated struvite, the wet tons reduction ranged from 7.26 percent to 9.82 percent. Table 4 presents the results of the struvite recovery variations. Full-scale recovery amounts would not necessarily significantly change these wet tons projections, because the calculations are based on the pilot-scale study data for the dewaterability improvements. Table 4 - Sensitivity of Total Biosolids Mass Reduction to Pilot-Scale Struvite Recovery Assumption Struvite Recovery Efficiency 0% 10% 20% 35% Wet Tons Reduction 7.3% 8.0% 8.7% 9.8% To check the assumptions made about struvite evaporation occurring during the TS test, the assumed mass of struvite evaporation was modified from 51.4 percent (which assumed that the NH4 and six water molecules evaporate during the test) to 29.4 percent (which equates to the evaporation of NH4 and three water molecules). When examining the impact on the total wet tons reduction from treatment using Dataset 4, the total wet tons reduction changed from 8.7 percent at 51.4 percent struvite evaporation to a reduction of 7.4 percent at 29.4 percent struvite evaporation. This difference in the assumption of struvite evaporation is significant, because it equates to a difference of approximately 1,930 wet tons of biosolids being hauled annually. The results from the analysis of all four datasets show two significant benefits from the process. First, throughout all four datasets, the total wet tons hauled showed a decrease of at least 7.7 percent with the potential for further improvement. When the increased hydraulic pressure bias for the treated digestate centrifuge runs was eliminated from the data, the wet tons decrease was still 8.7 percent, which reduces any concern that centrifuge operating set points were the driver behind the improved dewatering performance. Second, when the data is paired to 132

15 ensure consistent digestate composition and centrifuge operations between the untreated digestate and treated digestate, the data showed at least a 16.5 percent reduction in total polymer use on a strictly active pounds consumed basis. Struvite Reduction Table 5 summarizes the average analyte concentrations and water quality parameters as determined through the weekly pilot sampling and analyses; these parameters were used as inputs in the models. Struvite formation potential was modeled downstream of the reactor to reflect potential nuisance struvite formation in the dewatering process. Digester effluent acted as the control stream. Struvite formation potential was estimated to determine the impact that the system would have on the nuisance struvite production in the dewatering complex and centrate piping and holding tanks. The reactor contents were determined via mass balance of the inputs, digester effluent, and MgCl2 dose. Centrate was modeled for both control streams and test streams to determine struvite formation potential occurring in pipes and equipment downstream of dewatering. Table 5 - Average Composition of Modeled Streams Parameter Digester Effluent Reactor Untreated Centrate Treated Centrate Dissolved Calcium, mg/l Dissolved Iron, mg/l Dissolved Potassium, mg/l Dissolved Magnesium, mg/l Dissolved Sodium, mg/l Ammonium, mg/l 1,593 1,598 1,243 1,165 Orthophosphate, mg/l ph, S.U Temperature, C Conductivity, uhmo/cm 8, ,660 10,250 Alkalinity, mg CaCO3/L 4,723 4,723 3,943 3,140 Figure 8 shows a comparison between the model outputs of both Visual Minteq and Struvite Tool looking at three different streams; within the reactor (Top), treated centrate (bottom left), and untreated centrate (bottom right). Looking at the treated centrate stream, there is some degree of variability in the outputs between the two models. For example, Visual Minteq predicts the precipitation of significant quantities of magnesite alongside the struvite precipitation, hence the discrepancy between the two. However, when looking at untreated streams, the two models are closer in agreement with each other. This is due to the fact that the propensity for struvite to precipitate is greater in the untreated streams, and Visual Minteq predicts that struvite precipitation will dominate over the other minerals. The rest of the thermodynamic modeling results presented are from Struvite Tool. 133

16 Figure 8: Comparison of Struvite Formation Potential Between Struvite Tool with Visual Minteq. This reduced return of phosphorus to the secondary treatment process would reduce phosphorus uptake in the biological sludge, reducing phosphorus and Mg loading to the anaerobic digestion process, thus mitigating the impacts of nuisance struvite formation. A full plant BioWin model was used to determine the effect that reduced phosphorus recycle would have on struvite formation in the digesters. Figure 9 illustrates how the operation of an system would be anticipated to reduce the struvite formation in the digesters by 28 percent. Struvite Production in Digesters, ppd P 20,000 15,000 10,000 5,000 0 No Recovery Digestate Figure 9: Struvite Formation in Gas Phase Digesters Figure 10 summarizes the model estimates of struvite saturation index for the untreated digestate, treated digestate, and the treated centrate. Saturation index is an indicator for the propensity of struvite to precipitate, the higher the saturation index, the greater the potential. The 134

17 results from this analysis show that can significantly reduce the propensity of struvite to form in downstream equipment. Saturation Index % Avg OP Removal 79% OP Removal 67% OP Removal Digester Effluent Airprex Effluent Treated Centrate Figure 10: Struvite Formation Potential in Digesters and Downstream Equipment at Different OP Removals in Figure 11 summarizes the model estimates of the magnitude of struvite formation in the digester effluent (left axis), treated and untreated centrate (left axis), and the reactor (right axis) throughout the course of the pilot. The first data points collected were during startup, and the optimum recovery had yet to be optimized; hence, the predicted struvite production of the treated digestate on June 15 did not differ much from the untreated digestate. The next four data points were collected during targeted 90 percent OP conversion. At the targeted 90 percent OP conversion, the struvite estimates illustrate the benefit of intentional struvite precipitation to help with downstream nuisance struvite issues. Starting on July 19, lower Mg:P dosing ratios were fed to the reactor, resulting in increased struvite production estimates for locations downstream of the system. 135

18 Pre Airprex, Post Airprex, and Centrate Struvite Production, ppd Jun 19-Jun 29-Jun 9-Jul 19-Jul 29-Jul 8-Aug Untreated Digestate Untreated Centrate Airprex Treated Digestate Treated Centrate Figure 11: Struvite Production in Digesters, Reactor, and Recycle Streams throughout the Entirety of Pilot Study Phosphorus Index Phosphorus concentrations in the biosolids directly affect the loading rates of land application sites and therefore hauling and dispersal operating costs. Accumulating phosphorus in the biosolids due to tightening treated effluent limits can be detrimental to land application unless recovery of phosphorus as a separate biosolids stream with a separate management scheme is implemented. The mass of phosphorus recovered from the reactor was difficult to determine during the pilot due to periodic removal of the reactor struvite product but as presented in the dewatering section, recovery was estimated at around 20 percent with the potential to be higher for full-scale operation depending on reactor configurations and operation. This recovery results in an average of 80 percent of the produced struvite remaining within the biosolids. Recovery will directly affect TP in the biosolids (and thus land application of dewatered biosolids). From analyses on the dewatered biosolids, the untreated dewatered biosolids had a TP concentration of 2.7 on average while the treated dewatered biosolids had an average TP concentration of 3.4 percent. This concentration was consistent with TP concentrations obtained from BioWin modeling of the treatment process. As a comparison, ferric sequestration of phosphorus in the biosolids would result in a TP concentration of 3.8 percent. Phosphorus Recovery Metals analysis and pathogen counts were performed on the recovered struvite product. The results of the metals analysis are summarized in Table 6. Metals concentrations were all within the High Quality pollution limits set by the EPA. Fecal coliform testing was run for samples collected on three occasions to determine whether the recovered product was anticipated to require additional treatment in order to be classified as a Class A material per EPA 503 regulations. The fecal coliform counts are summarized in Table 7. The initial test resulted in a concentration above the cut-off level for Class A designation while the subsequent tests were well within the limits. While preliminary results indicate that it may be possible to meet Class A 136

19 criteria without further treatment, supplemental treatment technologies such as solar drying may be required to further deactivate pathogens as required. Table 6: Struvite Product Metals Analysis "High Quality" Pollutant Pollutant Concentration Limits** (mg/kg) Pilot Struvite Results Lab Analysis from Previous Pilot Arsenic 41 BDL 2 Cadmium 39 BDL BDL Copper Lead Mercury Molybdenum 1 < Nickel 420 BDL BDL Selenium 100 BDL Zinc There is currently no limit for Molybdenum for High Quality while rules are awaiting EPA investigation. Ceiling limit is 75 ppm. 2 Levels were below detection limit Table 7: Struvite Product Pathogen Analysis Fecal Date Coliforms MPN/g-TS 7/19/ /2/ /12/2016 <0.31 CONCLUDING REMARKS The pilot data allowed for a quantitative analysis of the treatment system against each of the five established drivers and will ultimately be used to compare the system against other potential technology solutions. This data will feed into economic models, imparting confidence in the operational costs and cost-benefit analysis for this system. Although extensive piloting of technologies is time consuming and expensive, the process can provide system specific information that is not readily available for technologies with limited full-scale installation experience. Findings from this study showed that would be an effective technology for reducing the impacts of centrate phosphorus recycle on effluent quality and struvite generation in the digesters. Findings from the study also indicated that the technology would reduce dewatering polymer consumption by 15 to 20 percent along with a 7 to 10 percent reduction in wet ton hauling requirements. The initial quality of the recovered and cleaned struvite also made it conceivable that the material could be managed such that it could meet 503 Class A requirements and be distributed as a fertilizer. 137

20 REFERENCES Ali, M. I., Schneider, P. A., & Hudson, N. (2003). Assessing nutrient recovery from piggery effluents. International Congress on Modelling and Simulation (MODSIM03). New Zealand. Bergmans, B., Veltman, A., van Loosdrecht, M., van Lier, J., & Rietveld, L. (2014). Struvite formation for enhanced dewaterability of digested wastewater sludge. Environmental Technology, Bhuiyan, I. H. (2007, October). Investigation into Struvite Solubility, Growth, and Dissolution Kinetics in the Context of Phosphorus Recovery from Wastewater. The University of British Columbia. Cavanaugh, L., Khunjar, W., Atwater, A., Carson, K., & McQuarrie, J. (2016). Making the Case for Phosphorus Recovery: Theoretical and Full-Scale Business Case Evaluations at an 830-MLD Wastewater Treatment Facility. WEF/IWA Nutrient Removal and Recovery. Denver. Celen, I., Buchanan, J. R., Burns, R. T., Robinson, R. B., & Raman, D. R. (2007). Using a chemical equilibrium model to predict amendments required to precipitate phosphorus as struvtie in liquid swine manure. Water Research, 41(8), Higgins, M., & Novak, J. T. (1997). The effect of cations ont he settling and dewatering of activated sludges. Water Environment Research, Korchef, A. Saidou, H. & Amor, M.B. (2011). Phosphate recovery through struvite precipitation by CO2 removal: Effect of magnesium, phosphate, and ammonium concentrations. Journal of Hazardous Materials, Ohlinger, K. N., & Mahmood, R. J. (2003). Struvite scale potential determination using a computer model. World Water & Environment Resources Congress. Shimp, G. F., Barnard, J. L., & Bott, C. B. (2013). Seeking to Understand and Address the Impacts of Biological Phosphorus Removal on Biosolids Dewatering. WEFTEC 2013, (pp ). 138