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The importance of soluble microbial products (SMPs) in biological drinking water treatment
PII: S0043-1354(99)00269-9
Wat. Res. Vol. 34, No. 4, pp. 1386±1396, 2000 # 2000 Elsevier Science Ltd. All rights reserved Printed in Great Britain 0043-1354/00/$ - see front matter
www.elsevier.com/locate/watres
THE IMPORTANCE OF SOLUBLE MICROBIAL PRODUCTS (SMPS) IN BIOLOGICAL DRINKING WATER TREATMENT KENNETH H. CARLSON1*M and GARY L. AMY2M 1
Department of Civil Engineering, Colorado State University, Fort Collins, CO 80523-1372, USA and 2 Department of Civil Engineering, University of Colorado-Boulder, Boulder, CO 80309, USA (First received 1 August 1996; accepted in revised form 1 June 1999)
AbstractÐThe formation of soluble microbial products (SMPs) during a drinking water ozonebio®ltration process was estimated using two approaches. First, a model was developed that related the assimilation of biodegradable organic matter (BOM) to the accumulation of biomass on ®lter media. The model was calibrated with data from a regularly backwashed, pilot scale bio®lter that approximated a steady-state plug ¯ow reactor. The second approach was a direct measurement of SMP concentrations, accomplished by applying a synthetic water comprised of known compounds to a bioacclimated ®lter. The SMP concentration was estimated by determining the dierence between knowncompound removal (on a carbon basis) and dissolved organic carbon (DOC) removal. Comparable results were obtained from both approaches. SMPs were found to be important relative to the carbon removal that is typically measured (DOC), indicating that this measurement can signi®cantly underestimate the actual BOM removal (17±33% in this research). The concentration of SMPs was negligible relative to the ®lter euent DOC pool. # 2000 Elsevier Science Ltd. All rights reserved Key wordsÐsoluble microbial products, drinking water, bio®ltration, ozone, model, biodegradable organic matter
NOMENCLATURE
acells b BAP BOM DOC DOCin¯uent DOCeuent kBAP kUAP K KBAP KUAP n NBOM OBP rBAP rUAP qm qBAP qUAP SMP UAP
biomass removal rate from media during backwash (minÿ1) biomass endogenous decay coecient (minÿ1) biomass associated products (mg lÿ1) biodegradable organic matter (mg lÿ1) dissolved organic carbon (mg lÿ1) bio®lter in¯uent DOC concentration (mg lÿ1) bio®lter euent DOC concentration (mg lÿ1) BAP formation rate constant (mgBAP mgÿ1 BOM) UAP formation rate constant (mgUAP ÿ1 mgBOM) half-maximum rate concentration for BOM degradation (mg lÿ1) half-maximum rate concentration for BAP degradation (mg lÿ1) half-maximum rate concentration for UAP degradation (mg lÿ1) hydraulic loading rate, HLR (m hÿ1) non-biodegradable organic matter (mg lÿ1) ozone by-products BAP degradation (mg lÿ1) UAP degradation (mg lÿ1) maximum rate of BOM degradation (mg ÿ1 mgÿ1 cells min ) maximum rate of BAP degradation (mg ÿ1 mgÿ1 cells min ) maximum rate of UAP degradation (mg ÿ1 mgÿ1 cells min ) soluble microbial products (mg lÿ1) utilization associated products (mg lÿ1)
*Author to whom all correspondence should be addressed.
X Y YSMP z
biomass (mg Ccells lÿ1) growth yield associated with BOM growth yield associated with SMP ®lter depth (m)
INTRODUCTION
Biological processes have not traditionally been used intentionally in drinking water treatment in North America. The increased use of ozone for disinfection and the recognition that ozone can transform a signi®cant portion of natural organic matter (NOM) into BOM (biodegradable organic matter) has precipitated interest in the design and operation of biological ®ltration processes (Langlais et al., 1991; Westerho et al., 1996). The presence of BOM in a drinking water treatment plant's ®nished water is undesirable because it can lead to bacterial regrowth within the distribution system (Servais et al., 1993) and potentially a loss of residual disinfectant and other operational problems. BOM removal is also desirable because the concentration of NOM (BOM is a fraction of NOM) is directly related to the formation of regulated disinfection by-products (DBPs) when chlorine is applied as the primary disinfectant (Amy et al., 1987). The removal of BOM decreases the NOM concentration and therefore the DBP formation potential.
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SMPs in biological drinking water
When bio®lms are employed as part of a water or wastewater treatment strategy, soluble microbial products (SMPs) will be released. Various researchers have shown that these SMPs can comprise a signi®cant fraction of the DOC pool in batch, suspended cell bioreactors (Chudoba, 1967; Grady and Williams, 1975; Saunders and Dick, 1981; Noguera et al., 1994). Namkung and Rittman (1986) suggested the formation of two types of SMPs; growth related utilization associated products (UAPs) and non-growth related biomass associated products (BAPs). The formation of UAPs is directly related to the cell growth rate, which is proportional to the substrate utilization rate. The formation of BAPs is related to the endogenous respiration of the cells and therefore is proportional to the biomass concentration. In a number of wastewater studies, SMPs have been shown to be larger in molecular weight and less biodegradable than the original BOM substrate (Namkung and Rittman, 1986; Boero et al., 1990). Grady et al. (1984) reported that 52% of the organic matter leaving a batch biological reactor had a molecular weight of greater than 10,000 daltons indicating that the majority of the SMPs were complex biochemicals, perhaps polymeric in nature. Rittman (1987) postulated that bioreactor euent organic matter consisted of humic and fulvic acids, polysaccharides, proteins, nucleic acids, amino acids and steroids. All of these compounds, except the humic and fulvic acids, can be generated within the bioreactor and therefore are considered potential SMPs. Limited research has been conducted regarding the formation and removal of SMPs in a drinking water treatment context. Woolschlager and Rittman (1995a) modeled the formation of UAPs and BAPs in a batch bioreactor and showed that the presence of SMPs can cause the BOM concentration to be underestimated by 30±40% when DOC removal is used to estimate BOM. The modeling approach used by these authors has been applied in this
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research to a pilot scale bio®lter to assess the importance of SMPs in this application. The research discussed in this paper had two objectives: 1. determine the magnitude of SMP production relative to the bio-removal of DOC in a typical drinking water bio®ltration process; 2. determine the signi®cance of SMPs in the DOC pool of the bio®lter euent water. The ®rst objective will allow a comparison of the measured DOC removal during bio®ltration and the actual BOM removed. The second objective will assess the need to characterize SMPs in terms of chlorine reactivity and distribution system biodegradability. If SMPs are a signi®cant fraction of the NOM that is released from a bio®lter, the potential for DBP formation and bacterial regrowth should be studied further. Two approaches were used to accomplish these objectives. First, a model was developed for the pilot scale bio®lter, simulated as a ¯ow-through, plug ¯ow reactor. The data collected during bio®ltration characterization experiments were used as inputs to this model and the presence of SMPs was calculated. Additionally, experiments were conducted to measure the SMP concentrations directly and these values are compared with the model predictions. MATERIALS AND METHODS
SMP formation model development A model describing a ¯ow-through, plug ¯ow, steady state bioreactor was developed using materials balances for biomass, BOM, UAPs and BAPs. Total SMP (UAP+BAP) concentration was de®ned as the dierence between the actual BOM removed and the measured DOC removal across a bio®lter (SMP generation within the ®lter reduces the DOC removal). The ®ve materials balance equations that make up the model are shown in Table 1. The water source that was used in the pilot scale bio®lter to collect the model calibration data consisted mostly of snowmelt with negligible (<0.1 mg
Table 1. Steady-state materials balance equations for a plug ¯ow bio®lter that is regularly backwasheda Biomass BOM UAP BAP qBAP X Ysmp qUAP X bX kBAP X acells X Yqm K BOM KUAP UAP KBAP BAP
(1)
BOM u
d BOM BOM ÿqm X dz K BOM
(2)
UAPs u
d UAP BOM UAP X kUAP qm X ÿ qUAP dz K BOM KUAP UAP
(3)
BAPs u
d BAP BAP X kBAP X ÿ qBAP dz KBAP BAP
DOC Removal DOC Removal DOCinfluent ÿ DOCeffluent BOM Removal ÿ UAP ÿ BAP a
See nomenclature summary for de®nitions and units of parameters.
(4) (5)
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Kenneth H. Carlson and Gary L. Amy
lÿ1) concentrations of ammonia. Therefore, it was assumed that the biomass consisted solely of heterotrophs and no nitri®ers. The variables and constants needed to solve the model were determined by experimentation and/or derived from literature sources (Table 2). The SMP biodegradation kinetic constants (YSMP, qUAP, qBAP, KUAP, KBAP), the UAP and BAP formation constants (kUAP, kBAP) and the endogenous decay constant (b ) were adapted from Woolschlager and Rittman, (1995b). The biomass backwash removal rate constant (acells) was determined by measuring the phospholipids in a sample of backwash water and estimating the total mass removed. Backwashing was done as a discreet event every 24 h but the model assumes that the removal is continuous. To solve the model equations, DOC removal and biomass accumulation data as a function of ®lter depth were needed. These model input data (DOC concentration vs depth and X vs depth) were collected with bio®ltration characterization experiments. The experimental set-up and analytical methods for these experiments is brie¯y described below with additional details provided elsewhere (Carlson, 1996). Pilot plant operation The pilot plant consisted of three 30 lpm trains, 1 of which was equipped to ozonate water before or after coagulation/sedimentation. Two declining rate ®lters (15 cm diameter) were established for these experiments. Filter 1 was set up to simulate deep bed ®ltration and consisted of 213 cm of anthracite with seven sample ports allowing the study of EBCTs ranging from 2 to 11 min at a loading rate of 9.7 m hÿ1. Filter 2 consisted of 94 cm of anthracite with a range of EBCTs of 2±10 min at a loading rate of 5.0 m hÿ1. The ®lters were allowed to develop biological activity by acclimating each with ozonated water at dierent loading rates (Filter 1Ð9.7 m hÿ1, Filter 2Ð5.0 m hÿ1) for at least 60 days. The ozonated raw water (0.6± 0.85 mg O3 per mg DOC transferred dose) was applied to each ®lter continuously and each ®lter was backwashed once per day at a loading rate of 50 m hÿ1 for 10 min using ®nished water from the plant that had been dechlorinated with thiosulfate. Typically, the ®lters were backwashed based on run time, usually once every 24 h. A control ®lter was used to verify that DOC removal was due to biodegradation. The loading rate of the control
®lter was approximately 5.0 m hÿ1. The control ®lter consisted of 94 cm (36 in) of anthracite with an approximate loading rate of 5.0 m hÿ1 and a free chlorine residual in the in¯uent water of between 0.5 and 1.0 mg lÿ1. No DOC removal was measured with control ®lter (95% con®dence level) supporting the assumption that DOC removal in the experimental ®lters was due to biodegradation. The pilot plant was supplied with water from Horsetooth Reservoir (Fort Collins, CO). The source water quality during the study period was relatively constant (DOC=3.31 2 0.26 mg lÿ1 range, T = 10.2 2 1.18C range, pH=7.3 2 0.2 range, turbidity=2.6 2 0.4 NTU range). The pilot scale ®lters were operated in a direct ®ltration mode with an alum dose of 4 mg lÿ1 fed after the water had been ozonated in a three cell ozone contactor. DOC measurement Dissolved organic carbon (DOC) concentration measurement was the most critical analytical protocol of the study. To achieve adequate resolution of BOM and BDOC concentrations, all errors with this protocol needed to be minimized. For example, DOC samples were collected in acid washed ®lter housings and immediately ®ltered through 0.45 mm silver ®lters (Poretics, Livermore, CA) that had been mued at 5508C (the silver ®lters were found to contain trace organic contamination). TOC was measured using a UV-persulfate oxidation followed by a CO2 selective membrane which allows quanti®cation by conductivity (Sievers, Boulder, CO). An analysis of variance (ANOVA) experiment was conducted to quantify the components of DOC concentration measurement variability. The measurement variability was broken into three components: run-to-run, sample handling and instrument. Using a 7 5 3 ANOVA matrix, the pooled standard deviation was measured as 0.116 mg lÿ1. Most of this pooled standard deviation was due to sample handling (75.4%) with run-to-run variability accounting for 22.1% of the total. The error due to the TOC analyzer was only 2.5% of the total. The sample handling component included the error due to glassware, ®lter and atmospheric contamination and therefore it is not surprising that this fraction shows the highest variability. The low error attributable to the TOC analyzer indicated that measuring multiple samples would not appreciably capture the true error of analysis.
Table 2. Input data and constants required for model Input data Calculated based Input constants (experimental) on model (literature) u X z DOCn BOM UAP BAP qm K Y YSMP qUAP qBAP KUAP KBAP b acells kUAP kBAP
Hydraulic loading rate (®lter velocity) Biomass c concentration Filter depth Dissolved organic carbon at sample port n Biodegradable organic matter (true amount of carbon biodegraded) Utilization associated products Biomass associated products Maximum rate of BOM degradation Half-maximum rate concentration for BOM zdegradation Growth yield associated with BOM Growth yield associated with SMPu utilization Maximum speci®c rate of UAP degradation Maximum speci®c rate of BAP degradation Half-maximum rate concentration for UAP utilization Half-maximum rate concentration for BAP utilization Biomass endogenous decay coecient Biomass removed due to sloughing UAP formation rate constant BAP formation rate constant
cm minÿ1 mg carbon lÿ1 cm mg lÿ1 mg lÿ1 mg mg mg mg
X X X X
ÿ1
X X X X
l lÿ1 ÿ1 mgÿ1 cell min lÿ1
mgcell mgÿ1 BOM mgcell mgÿ1 SMP ÿ1 mg mgcell minÿ1 ÿ1 mg mgcell minÿ1 mg lÿ1 mg lÿ1 minÿ1 minÿ1 mgUAP mgÿ1 BOM ÿ1 mgBAP mgÿ1 BOM min
X
3.0Eÿ05
0.6 0.6 0.9Eÿ03 1.39Eÿ03 2.1E+04 1.4E+04 6.9Eÿ05 0.1 4.89Eÿ05
SMPs in biological drinking water Table 3. DOC concentration measurement 95% con®dence interval versus number of runs (two samples per run, two replicates per sample) No. of experimental runs 2 3 4 5 6
Table 4. Experimental conditions for model calibration runs Run no.
95% Con®dence interval (2mg lÿ1) 0.082 0.067 0.059 0.052 0.048
The 95% con®dence intervals that are reported in this paper for DOC concentration use a pooled standard deviation and therefore are a function of the number of runs that are done. Based on the pooled variance determined with the ANOVA experiment, the number of runs that would need to be completed to attain a given 95% con®dence interval can be determined. Assuming that two samples are collected per run and two analysis replicates are completed per sample, ®ve runs would be needed to achieve a 95% con®dence interval of 20.05 mg lÿ1 DOC concentration. The 95% con®dence intervals are compiled for dierent numbers of experimental runs in Table 3. Biomass measurement The presence of biomass was quanti®ed by measuring the lipid-bound phosphorous (total lipid phosphate) according to a method described by Findlay et al. (1989). Media was removed from the ®lters at various depths throughout the study using a horizontal coring device that could be inserted into the sample ports in the side of the ®lters. Approximately 3 g of media were removed for each test, an amount that was negligible relative to the total (>40,000 g). The media was removed after a backwash and the interstitial biomass was assumed to be negligible. This protocol resulted in the measurement and correlation
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1 2 3
Transferred ozone dose (mg O3 mg DOCÿ1)
Filter loading rate (m hÿ1)
EBCT (min)
0.60 0.60 0.85
5.0 9.7 9.8
10 11 11
of only the attached biomass. The lipid-bound phosphorous was extracted and then digested to inorganic phosphate followed by colorimetric quanti®cation. The units of per g of dried media measurement are nmoles of POÿ3 4 and therefore these measurements should not be compared between media types of dierent density. The method was found to be repeatable with measurements taken from the same sample but variability between samples was found to be signi®cant. ANOVA results for the total lipid phosphate analysis indicated that 98% of the variance was due to the sampling and only 2% was due to the analytical process after extraction had occurred. This result is not surprising because media, due to its heterogeneous nature, would not be expected to develop bio®lms equivalently. Additionally, regular backwashing will partially restratify the media, further contributing to variability at any point in the ®lter. The model input parameters (DOC concentration depth pro®le and biomass depth pro®le) are described elsewhere (Carlson and Amy, 1998) and only summarized here. With these input parameters, ®ve values from the model equations remain as unknowns. Since there are ®ve equations, these ®ve unknowns can be uniquely determined. Using a ®nite dierence, least squares algorithm, BOM, UAP and BAP were solved versus depth (z ) and the BOM kinetic coecients (qm and K ) were solved as constants throughout the bio®lter depth. Three model calibration data collection experiments
Fig. 1. SMP formation experimental protocol.
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Fig. 2. Model predictions for BOM and DOC removal; loading rate=9.7 m hÿ1, ozone dose=0.6 mg O3 per mg DOC. were conducted at dierent ozonation (BOM formation) or ®lter (BOM removal) conditions (Table 4). The model was solved at three sets of operating conditions using the data from these experiments. SMP formation experiments Directly measuring SMPs in a bio®lter that treats water containing NOM is not possible because the DOC contributions from SMPs cannot be chemically distinguished from the original NOM. Alternatively, if all of the DOC in¯uent to a bio®lter can be accounted for in terms of known compounds, the total SMP concentration can be estimated. The dierence between the removal of known substrates (as carbon) and the removal of DOC should be the soluble microbial products when adjusted for SMP biodegradation using literature kinetic values (Woolschlager and Rittman, 1995b). An approach was developed to experimentally estimate SMP formation by feeding a synthetic water into the pilot scale bio®lter (anthracite media) and measuring both the DOC removal and the known compound removal (as carbon) throughout the ®lter depth (Fig. 1). The synthetic water consisted of de-ionized, NOM-free water (DOC concentration was measured to be approximately 0.1 mg lÿ1) that had been reconstituted to the bulk water quality in terms of ionic strength, hardness, pH and microbial nutrients nitrate and orthophosphate (Fig. 1). The easily biodegradable ozone by-products (OBPs) included various carboxylic acids, aldehydes, and keto-acids: oxalate, formate, glyoxal, methyl glyoxal, pyruvate and glyoxalate. The relative formation of these compounds during ozonation and the fraction of the BOM that they constitute has been described previously (Carlson and Amy, 1997). The SMP pro®le was determined by measuring the DOC concentration at each sample port 30 min after instantaneously switching the ®lter in¯uent from the ozonated water used for acclimation to the synthetic water source. The SMP concentration was calculated as the dierence between the OBP removal (as carbon) and the DOC removal when UAP and BAP biodegradation are
considered (Eqs. (6) and (7)). Eq. (6) can be understood by examining each component. OBP Removal represents the consumption of the in¯uent substrate. This value should equal the DOC Removal if no SMPs are present. If SMPs are present, DOC removal will be reduced by this amount. The measured concentration of SMPs will be reduced by biodegradation and therefore the total concentration needs to be adjusted upwards by this amount. The UAP and BAP biodegradation term (rUAP and rBAP) is determined using the Monod expressions that are part of the model described in Table 2. SMP OBP Removal ÿ DOC Removal SMP biodegradation
6
SMP OBPinfluent ÿ OBPPort n ÿ DOCinfluent ÿ DOCPort n rBAP rUAP
7
where rUAP is the predicted UAP biodegradation (mg lÿ1), rBAPis the predicted BAP biodegradation (mg lÿ1). Ozone by-product measurement Four dominant aldehydes (formaldehyde, acetaldehyde, glyoxal, methyl glyoxal) were determined by gas chromatography (Hewlett-Packard 5890II) using the method described by Sclimenti et al. (1990). The method involves derivatizing the aldehydes to oximes using PFBHA, O(2,3,4,5,6-penta¯uorobenzyl)-hydroxylamine hydrochloride. HgCl2 was added for preservation but all samples were still derivatized within 24 h. Three dominant ketoacids (glyoxylic acid, ketomalonic acid, pyruvic acid) were measured using a method described by Xie and Reckhow (1992). The ketoacids were derivatized to oxime methyl esters using PFBHA and diazomethane and then quanti®ed using gas chromatography. Samples were derivatized within 6 h of collection and not preserved because of results indicating that HgCl2 addition
SMPs in biological drinking water increased the measurement variability. The interference of HgCl2 with ketoacid measurement was also veri®ed experimentally in this study. Ion chromatography (Dionex, Sunnyvale, CA) was used to determine three dominant carboxylic acids (formate, acetate, oxalate). The method (Kuo et al., 1995) utilizes an AS-10 concentrator column, an AG10 guard column and a conductivity detector equipped with an AMMSII micromembrane suppresser. Samples were preserved with HgCl2 immediately after collection and measured within 24 h. RESULTS AND DISCUSSION
Model predictions of SMP formation The model solution using calibration data from run no. 2 is shown in Fig. 2. Carbon removal is expressed two ways, the measured DOC removal and the calculated BOM removal. The error associated with using DOC removal as an estimate of the BOM removal can be represented as the SMP concentration as a percentage of DOC removed (Eq. (8)). This error would be in addition to the measurement variability discussed previously, less than 0.05 mg lÿ1 (95% con®dence level) for these experiments. DOC
SMP 100 percentage Removed
error
8
Several observations can be made from Fig. 2. First, SMPs constitute a large fraction of the biodegradable material; the dierence between the actual BOM and the measured DOC removal is approximately 25% at the euent of a 175 cm deep bio®l-
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ter. The SMP concentration as a percent of DOC removal increases rapidly in the ®rst 10 cm of the ®lter bed and appears to reach a maximum value within the ®lter bed modeled in the example. The predicted concentrations of SMPs across the bio®lter with the run no. 2 calibration data are shown in Fig. 3. Both formation and biodegradation terms are included in the calculations for the net concentration of UAPs and BAPs. Therefore, the divergence between the UAP or BAP net concentration and formation curves represents the predicted biodegradation. Based on the model results shown in Fig. 3, the biodegradation of UAPs is signi®cant relative to UAP formation (033%) but not important with respect to the total BOM biodegradation (02%). BAP biodegradation was less signi®cant than UAP degradation even though the concentration was greater. The model was also used to determine the SMP and BOM concentrations associated with two other ozonation/bio®ltration conditions. A summary of the ozone and bio®ltration conditions and the SMP production for the three runs is presented in Table 5. The bio®ltration conditions include the ®lter HLR, in¯uent DOC concentration and the in¯uent BOM concentration. Changing the ozone dose (substrate concentration) and ®lter loading rate (substrate ¯ux) created dierent biomass and DOC removal pro®les. The in¯uent BOM represents the BOM that was ®lter removable for each experiment as determined with the model for a 175 cm deep bio®lter and this value is impacted by the ozonation
Fig. 3. Model predictions for SMP formation and degradation; HLR=9.7 m hÿ1, ozone dose=0.6 mg O3 per mg DOC.
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Kenneth H. Carlson and Gary L. Amy
Table 5. Summary of predicted SMP production for three bio®lter conditions (Values in parentheses are normalized to the ®rst experiment) Experimental conditions
1 2 3
Biomass at ®lter surface
SMPs at the bottom of the ®lter (empty bed contact time 110 min)
Ozone dose (mg O3 per mg DOC)
Filter HLR (m hÿ1)
In¯. DOC (mg lÿ1)
In¯. BOM (mg lÿ1)
Phospholipids (nmole POÿ3 4 per g media)
UAPs (mg lÿ1)
BAPs (mg lÿ1)
Total as % of DOC removal
Total as % of euent DOC
0.60 0.60 0.85
5.0 9.7 9.8
3450 3370 3310
397 (1.0) 434 (1.1) 565 (1.4)
56 (1.0) 121 (2.2) 314 (5.6)
22 (1.0) 20 (0.9) 18 (0.8)
33 (1.0) 65 (2.0) 119 (3.6)
17% (1.0) 25% (1.5) 33% (2.0)
1.8% (1.0) 2.9% (1.6) 5.0% (2.8)
conditions. The biomass concentration at the surface of the ®lter is also shown for each bio®ltration condition as a relative indicator of the biomass pro®le, which could be roughly described with a ®rst order decay relationship. The calculated SMP concentrations are shown for each set of experiments. The UAP concentrations were equivalent for each experiment even though the in¯uent BOM was greater by a factor of 1.4 for the third experiment. This discrepancy was due to the higher rate of biodegradation predicted for the UAPs in this experiment. BAP production increased as the surface biomass increased but not linearly. The ®rst two experiments, which were run using the same water quality and ozonation conditions, showed equivalent BAP and biomass increases. The third experiment, which was run with dierent water quality and ozonation conditions, did not show equivalent BAP and biomass increases. This result is most likely due to a dierent biomass depth pro®le since the biomass-normalized BAP production rate should be equivalent for
all three experiments (the BAP production rate was modeled using the same rate constants for all three model calibration conditions). The third set of water quality and ozonation conditions that was studied (run no. 3) had a higher transferred ozone dose (0.85 mg O3 per mg DOC versus 0.60 mg O3 per mg DOC). The net eect of the water quality and ozonation changes was an increase in BOM in¯uent to the bio®lter that was operated at a loading rate of approximately 9.8 m hÿ1. The relative SMP production predicted for these bio®ltration conditions was greater than the two previous cases, and roughly 33% of the DOC removal. The SMP concentration was less than 5% for all three experiments when expressed as a fraction of the bio®lter euent DOC concentration. These results indicate that with the relatively low biological activity that is found in drinking water treatment bio®lters, SMPs comprise an almost negligible portion of the post-®lter DOC pool. The high fraction of BAPs shown in Table 5 also indicates that
Fig. 4. The fate of three biodegradability-related DOC fractions through the bio®lter for the run no. 3 model calibration conditions.
SMPs in biological drinking water
the biomass accumulation, not the BOM utilization, relates most strongly to SMP formation. The predicted DOC in the bio®lter was divided into three fractions at each depth: 1. NBOMÐBOM not removable during bio®ltration; 2. BOMÐBOM removable during bio®ltration; 3. SMPsÐSMPs formed during bio®ltration. Using the model solution from run no. 3, these three fractions are plotted versus bio®lter depth in Fig. 4. The ®lter in¯uent water contained two fractions, the non-biodegradable organic matter and the biodegradable organic matter formed as a result of the ozonation process. Initially, the BOM represented 18% of the total DOC. The BOM was reduced to 0% of the total DOC in the ®lter euent by de®nition. In contrast, the SMP concentration only increased to 5% of the total DOC concentration in the ®lter euent water. Based on the results presented here, the concentration of SMPs in the ®lter euent water is insigni®cant relative to the overall pool of DOC. SMP formation experiments An attempt was made to measure the concentration of SMPs directly by feeding the bio®lter a synthetic water with a known pool of DOC, comprised of individual, easily-biodegradable compounds. The SMP concentration was determined with Eq. (7). Two sets of experiments were conducted. The ®rst set of experiments used a synthetic water with
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six known OBPs (Fig. 3) that represent a range of biodegradation rates. The experimentally determined soluble microbial products are compared with the model prediction for these bio®ltration conditions as a function of bio®lter depth in Fig. 5. Experimental SMP values ranged from 58 to 99 mg lÿ1 but the coecient of variation ranged from 45 to 66% due primarily to the magnitude of the SMP concentrations relative to the error associated with DOC concentration measurement. Nevertheless, the 95% con®dence intervals (based on two duplicate measurements of three samples at each port for two runs) of the experimental data overlap with four out of six of the model predicted values. The second SMP production experiment used glyoxal as the sole BOM substrate. Glyoxal was the least biodegradable of the eight ozone by-products used in this study and this experiment was intended to determine if the bio®lter in¯uent substrate aected the production of SMPs. The predicted SMP production is compared with the experimentally measured values in Fig. 6. The SMP pro®le determined with glyoxal as the substrate is similar to that measured with the multiple OBP substrate. Glyoxal is biodegradable but only partially so with the contact time of the ®lter used in this study. The experimental pro®les indicate that SMP formation is greatest at the top of ®lter (this is where the biomass concentration and BOM assimilation are greatest) followed by signi®cant biodegradation. The experimental results could be interpreted as indicating higher biodegradation kinetic coecients than were used.
Fig. 5. Comparison of SMP concentrations determined experimentally and predicted with the model using a multiple-OBP substrate.
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Fig. 6. Comparison of SMP concentrations determined experimentally and predicted with the model using glyoxal as the sole substrate.
Fig. 7 compares the experimental and modeled SMP results with the total DOC concentration pro®le across the ®lter depth. Approximately 14% of the in¯uent DOC was removed through biodegradation in the bio®lter as the concentration was
reduced from 3150 to 2720 mg lÿ1. In contrast, none of the modeled or measured SMP values exceeded 140 mg lÿ1, a value that is less than 5% of the ®lter euent DOC concentration. The dierence between the measured and modeled results is insigni®cant
Fig. 7. Comparison of measured and predicted SMP concentrations with total DOC concentration as a function of ®lter depth (substrate glyoxal).
SMPs in biological drinking water
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Fig. 8. SUVA ®lter depth pro®le for BOM with and without non-biodegradable NOM.
within the context of the background DOC concentration. The results presented in Fig. 8 were also analyzed from a macroscopic perspective. The data in Figs 5 and 6 tends to indicate that the kinetic coecients used for UAP and BAP biodegradation were underestimated. A sensitivity analysis was conducted to determine the impact of these values on the conclusions from this study. The maximum degradation rate constants, qUAP and qBAP, were changed by factors of 0.5 and 2.0. This coecient variation resulted in the SMP concentration as a fraction of the total DOC removed varying only from 31 to 35%. SMP concentration as a fraction of the euent DOC varied from 4.6 to 5.4% for these six scenarios indicating that the conclusions of this study are not very sensitive to the biodegradability of the UAP and BAP species. SMPs appear to be important when compared to the DOC removed in a bio®lter. The data indicates that the SMP concentration can be greater than 32% of the BOM concentration, a signi®cant amount. To further illustrate this point, the speci®c ultra-violet absorbance at 254 nm (SUVA), an indicator of the aromatic character of NOM (Edzwald and Van Benschoten, 1990), was measured during the known multi-substrate, arti®cial water, SMP formation experiments that were described in Fig. 3. SUVA is the UV absorbance at 254 nm (mÿ1) divided by the DOC concentration (mg lÿ1). The SUVA value increases with an increasing fraction of aromatic or double-bond-rich substances that tend to absorb more strongly at 254 nm. Two sets of data are plotted in Fig. 8. The ®rst set of data (without NBOM in Fig. 8) is the
arti®cial water without the dominant non-biodegradable NOM. The second set of data (with NBOM in Fig. 8) is the SUVA measured with the ozonated natural water in the ®lter. The key point here is that an increasing SUVA implies an increasing concentration of larger, more aromatic, doublebond-rich compounds, potentially a result of SMP production. When the background NOM was present, no trend in SUVA values was apparent. These data further support the supposition that SMPs were insigni®cant relative to the non-biodegradable organic matter. CONCLUSIONS
The primary objective of the research described in this paper was to determine if SMPs are important in a typical drinking water bio®ltration process. SMPs were found to be important only if considered relative to the DOC that is removed during bio®ltration. SMPs do not appear to be important if the BOM fraction of the ®lter-in¯uent DOC is small. If the BOM removal during bio®ltration is being determined, the presence of SMPs will result in a 17±33% error if DOC removal is used for the estimate of BOM. The production of SMPs is highly dependent on the bio®ltration conditions including the substrate (BOM) utilization rate and the accumulated biomass. The conclusions presented here are made in the context of what is considered to be typical drinking water process conditions. The formation of SMPs will be directly related to the BOM removal and the biomass concentration. The
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removal of 10±20% of the in¯uent DOC (roughly the range reported in this study) has been reported by other researchers (Servais and Billen, 1991; Huck et al., 1994, Wang and Summers, 1995) and the biomass levels at the top of the ®lter reported in this research compare favorably with other research (Miltner et al., 1995; Wang and Summers, 1995). AcknowledgementsÐThis work was supported by the Fort Collins (CO) Water Utility and the University of ColoradoÐBoulder. Appreciation is expressed to Greg Blais (University of Colorado) and Sarah MacMillan (City of Fort Collins) for their assistance with the analytical and experimental work. The contributions of the manuscript reviewers is also acknowledged. REFERENCES
Amy G. L., Chadik P. A. and Chowdhury Z. K. (1987) Developing models for predicting trihalomethane formation potential and kinetics. J. AWWA 79(7), 89. Boero V. J., Eckenfelder W. W. and Bowers A. R. (1990) Soluble microbial product formation in biological systems. Wat. Sci. Tech. 23, 1067±1080. Carlson K. H. (1996) Integration of the ozone and bio®ltration processes for multiple drinking water treatment objectives. PhD dissertation, University of ColoradoBoulder. Carlson K. H. and Amy G. L. (1997) The formation of ®lter removable BOM during ozonation. Ozone Sci. and Eng. 19(2), 145. Carlson K. H. and Amy G. L. (1998) Assessing the limitations of BOM removal during bio®ltration. J. AWWA 90(12), 78. Chudoba J. (1967) Residual organic matter in activated sludge process euentsÐ1: degradation of saccharides, fatty acids and amino acids under batch conditions. Technol. Wat. 12, 39±75. Edzwald J. K. and Van Benschoten J. E. (1990) Aluminum Coagulation of Natural Organic Matter. Chemical Water and Wastewater Treatment. Springer±Verlag, Berlin. Findlay R. H., King G. M. and Watling L. (1989) Ecacy of phospholipid analysis in determining microbial biomass in sediments. Appl. Environ. Microbiol. 55(11), 2888±2893. Grady C. P. L. and Williams D. R. (1975) Eects of in¯uent substrate concentration on the kinetics of natural microbial populations in continuous culture. Wat. Res. 9, 171±180. Grady C. P. L., Kirsch E. J., Koczwara M. K., Trgovcich B. and Watt R. D. (1984) Molecular weight distributions in activated sludge euents. Wat. Res. 18, 239± 246. Huck P. M., Zhang S and Price M. L. (1994) BOM removal during biological treatment: a ®rst order model. J. AWWA 86(6), 61±71.
Kuo C-Y., Wamg H-C., Krasner S. W. and Davis M. K. (1995) Ion-chromatographic determination of shortchain carboxylic acids in ozonated drinking water. In Proceedings of 69th Annual Meeting, American Chemical Society, Chicago, IL. Langlais B., Reckhow D. A. and Brink D. R. (1991) Ozone in Water Treatment: Applications and Engineering. Lewis Publishers, Chelsea, MI. Miltner R. J., Summers R. S. and Wang J. Z. (1995) Bio®ltration performanceÐpart 2: eect of backwashing. J. AWWA 87(12), 64±72. Namkung E. and Rittman B. E. (1986) Soluble microbial products (smp) formation kinetics by bio®lms. Wat. Res. 20(6), 795±806. Noguera D. R., Araki N. and Rittman B. E. (1994) Soluble microbial products (smp) in anaerobic chemostats. Biotechnol. Bioeng. 44, 1040±1051. Rittman B. E. (1987) A critical evaluation of microbial product formation in biological processes. Wat. Sci. Tech. 19, 517±528. Saunders F. M. and Dick R. I. (1981) Eect of mean-cell residence time on organic composition of activated sludge euents. J. Wat. Pollut. Control Fed. 53, 201± 215. Sclimenti M. J., Krasner S. W., Glaze W. H. and Weinberg H. S. (1990) Ozone disinfection by-products: optimization of the PFBHA derivatization method for the analysis of aldehydes. In Proceedings of 1990 AWWA WQTC, San Diego, CA. Servais P. and Billen G. (1991) Microbial activity in GAC ®lters at the Choisy-le-Roi treatment plant. J. AWWA 83(2), 44±68. Servais P., Laurent P. and Randon G. (1993) Impact of biodegradable dissolved organic carbon (BDOC) on bacterial dynamics in the distribution system. In Proceedings of AWWA Water Quality Technology Conference, Miami, FL. Wang J. Z. and Summers R. S. (1995) Biomass growth and distribution in drinking water bio®lters and its impact on natural organic matter removal. In Proceedings of the 1995 AWWA Annual Conference, Anaheim, CA. Westerho P., Debroux J., Aiken G. and Amy G. (1996) Structural changes in NOM due to ozonation: implications for water treatment. In Proceedings of 1996 AWWA Annual Conference, Research Division, Toronto, ON. Woolschlager J. and Rittman B. E. (1995a) Determining the actual amount of biodegradable organic matter in drinking water supplies. In Proceedings of the 1995 AWWA Annual Conference, Anaheim, CA. Woolschlager J. and Rittman B. E., (1995b) Evaluating what is measured by BDOC and AOC tests. Revue des Sciences de L'eau. Xie Y. and Reckhow D. A. (1992) A new class of ozonation by-products: the ketoacids. In Proceedings of 1992 AWWA Annual Conference, Vancouver, BC.
Wat. Res. Vol. 34, No. 4, pp. 1386±1396, 2000 # 2000 Elsevier Science Ltd. All rights reserved Printed in Great Britain 0043-1354/00/$ - see front matter
www.elsevier.com/locate/watres
THE IMPORTANCE OF SOLUBLE MICROBIAL PRODUCTS (SMPS) IN BIOLOGICAL DRINKING WATER TREATMENT KENNETH H. CARLSON1*M and GARY L. AMY2M 1
Department of Civil Engineering, Colorado State University, Fort Collins, CO 80523-1372, USA and 2 Department of Civil Engineering, University of Colorado-Boulder, Boulder, CO 80309, USA (First received 1 August 1996; accepted in revised form 1 June 1999)
AbstractÐThe formation of soluble microbial products (SMPs) during a drinking water ozonebio®ltration process was estimated using two approaches. First, a model was developed that related the assimilation of biodegradable organic matter (BOM) to the accumulation of biomass on ®lter media. The model was calibrated with data from a regularly backwashed, pilot scale bio®lter that approximated a steady-state plug ¯ow reactor. The second approach was a direct measurement of SMP concentrations, accomplished by applying a synthetic water comprised of known compounds to a bioacclimated ®lter. The SMP concentration was estimated by determining the dierence between knowncompound removal (on a carbon basis) and dissolved organic carbon (DOC) removal. Comparable results were obtained from both approaches. SMPs were found to be important relative to the carbon removal that is typically measured (DOC), indicating that this measurement can signi®cantly underestimate the actual BOM removal (17±33% in this research). The concentration of SMPs was negligible relative to the ®lter euent DOC pool. # 2000 Elsevier Science Ltd. All rights reserved Key wordsÐsoluble microbial products, drinking water, bio®ltration, ozone, model, biodegradable organic matter
NOMENCLATURE
acells b BAP BOM DOC DOCin¯uent DOCeuent kBAP kUAP K KBAP KUAP n NBOM OBP rBAP rUAP qm qBAP qUAP SMP UAP
biomass removal rate from media during backwash (minÿ1) biomass endogenous decay coecient (minÿ1) biomass associated products (mg lÿ1) biodegradable organic matter (mg lÿ1) dissolved organic carbon (mg lÿ1) bio®lter in¯uent DOC concentration (mg lÿ1) bio®lter euent DOC concentration (mg lÿ1) BAP formation rate constant (mgBAP mgÿ1 BOM) UAP formation rate constant (mgUAP ÿ1 mgBOM) half-maximum rate concentration for BOM degradation (mg lÿ1) half-maximum rate concentration for BAP degradation (mg lÿ1) half-maximum rate concentration for UAP degradation (mg lÿ1) hydraulic loading rate, HLR (m hÿ1) non-biodegradable organic matter (mg lÿ1) ozone by-products BAP degradation (mg lÿ1) UAP degradation (mg lÿ1) maximum rate of BOM degradation (mg ÿ1 mgÿ1 cells min ) maximum rate of BAP degradation (mg ÿ1 mgÿ1 cells min ) maximum rate of UAP degradation (mg ÿ1 mgÿ1 cells min ) soluble microbial products (mg lÿ1) utilization associated products (mg lÿ1)
*Author to whom all correspondence should be addressed.
X Y YSMP z
biomass (mg Ccells lÿ1) growth yield associated with BOM growth yield associated with SMP ®lter depth (m)
INTRODUCTION
Biological processes have not traditionally been used intentionally in drinking water treatment in North America. The increased use of ozone for disinfection and the recognition that ozone can transform a signi®cant portion of natural organic matter (NOM) into BOM (biodegradable organic matter) has precipitated interest in the design and operation of biological ®ltration processes (Langlais et al., 1991; Westerho et al., 1996). The presence of BOM in a drinking water treatment plant's ®nished water is undesirable because it can lead to bacterial regrowth within the distribution system (Servais et al., 1993) and potentially a loss of residual disinfectant and other operational problems. BOM removal is also desirable because the concentration of NOM (BOM is a fraction of NOM) is directly related to the formation of regulated disinfection by-products (DBPs) when chlorine is applied as the primary disinfectant (Amy et al., 1987). The removal of BOM decreases the NOM concentration and therefore the DBP formation potential.
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SMPs in biological drinking water
When bio®lms are employed as part of a water or wastewater treatment strategy, soluble microbial products (SMPs) will be released. Various researchers have shown that these SMPs can comprise a signi®cant fraction of the DOC pool in batch, suspended cell bioreactors (Chudoba, 1967; Grady and Williams, 1975; Saunders and Dick, 1981; Noguera et al., 1994). Namkung and Rittman (1986) suggested the formation of two types of SMPs; growth related utilization associated products (UAPs) and non-growth related biomass associated products (BAPs). The formation of UAPs is directly related to the cell growth rate, which is proportional to the substrate utilization rate. The formation of BAPs is related to the endogenous respiration of the cells and therefore is proportional to the biomass concentration. In a number of wastewater studies, SMPs have been shown to be larger in molecular weight and less biodegradable than the original BOM substrate (Namkung and Rittman, 1986; Boero et al., 1990). Grady et al. (1984) reported that 52% of the organic matter leaving a batch biological reactor had a molecular weight of greater than 10,000 daltons indicating that the majority of the SMPs were complex biochemicals, perhaps polymeric in nature. Rittman (1987) postulated that bioreactor euent organic matter consisted of humic and fulvic acids, polysaccharides, proteins, nucleic acids, amino acids and steroids. All of these compounds, except the humic and fulvic acids, can be generated within the bioreactor and therefore are considered potential SMPs. Limited research has been conducted regarding the formation and removal of SMPs in a drinking water treatment context. Woolschlager and Rittman (1995a) modeled the formation of UAPs and BAPs in a batch bioreactor and showed that the presence of SMPs can cause the BOM concentration to be underestimated by 30±40% when DOC removal is used to estimate BOM. The modeling approach used by these authors has been applied in this
1387
research to a pilot scale bio®lter to assess the importance of SMPs in this application. The research discussed in this paper had two objectives: 1. determine the magnitude of SMP production relative to the bio-removal of DOC in a typical drinking water bio®ltration process; 2. determine the signi®cance of SMPs in the DOC pool of the bio®lter euent water. The ®rst objective will allow a comparison of the measured DOC removal during bio®ltration and the actual BOM removed. The second objective will assess the need to characterize SMPs in terms of chlorine reactivity and distribution system biodegradability. If SMPs are a signi®cant fraction of the NOM that is released from a bio®lter, the potential for DBP formation and bacterial regrowth should be studied further. Two approaches were used to accomplish these objectives. First, a model was developed for the pilot scale bio®lter, simulated as a ¯ow-through, plug ¯ow reactor. The data collected during bio®ltration characterization experiments were used as inputs to this model and the presence of SMPs was calculated. Additionally, experiments were conducted to measure the SMP concentrations directly and these values are compared with the model predictions. MATERIALS AND METHODS
SMP formation model development A model describing a ¯ow-through, plug ¯ow, steady state bioreactor was developed using materials balances for biomass, BOM, UAPs and BAPs. Total SMP (UAP+BAP) concentration was de®ned as the dierence between the actual BOM removed and the measured DOC removal across a bio®lter (SMP generation within the ®lter reduces the DOC removal). The ®ve materials balance equations that make up the model are shown in Table 1. The water source that was used in the pilot scale bio®lter to collect the model calibration data consisted mostly of snowmelt with negligible (<0.1 mg
Table 1. Steady-state materials balance equations for a plug ¯ow bio®lter that is regularly backwasheda Biomass BOM UAP BAP qBAP X Ysmp qUAP X bX kBAP X acells X Yqm K BOM KUAP UAP KBAP BAP
(1)
BOM u
d BOM BOM ÿqm X dz K BOM
(2)
UAPs u
d UAP BOM UAP X kUAP qm X ÿ qUAP dz K BOM KUAP UAP
(3)
BAPs u
d BAP BAP X kBAP X ÿ qBAP dz KBAP BAP
DOC Removal DOC Removal DOCinfluent ÿ DOCeffluent BOM Removal ÿ UAP ÿ BAP a
See nomenclature summary for de®nitions and units of parameters.
(4) (5)
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Kenneth H. Carlson and Gary L. Amy
lÿ1) concentrations of ammonia. Therefore, it was assumed that the biomass consisted solely of heterotrophs and no nitri®ers. The variables and constants needed to solve the model were determined by experimentation and/or derived from literature sources (Table 2). The SMP biodegradation kinetic constants (YSMP, qUAP, qBAP, KUAP, KBAP), the UAP and BAP formation constants (kUAP, kBAP) and the endogenous decay constant (b ) were adapted from Woolschlager and Rittman, (1995b). The biomass backwash removal rate constant (acells) was determined by measuring the phospholipids in a sample of backwash water and estimating the total mass removed. Backwashing was done as a discreet event every 24 h but the model assumes that the removal is continuous. To solve the model equations, DOC removal and biomass accumulation data as a function of ®lter depth were needed. These model input data (DOC concentration vs depth and X vs depth) were collected with bio®ltration characterization experiments. The experimental set-up and analytical methods for these experiments is brie¯y described below with additional details provided elsewhere (Carlson, 1996). Pilot plant operation The pilot plant consisted of three 30 lpm trains, 1 of which was equipped to ozonate water before or after coagulation/sedimentation. Two declining rate ®lters (15 cm diameter) were established for these experiments. Filter 1 was set up to simulate deep bed ®ltration and consisted of 213 cm of anthracite with seven sample ports allowing the study of EBCTs ranging from 2 to 11 min at a loading rate of 9.7 m hÿ1. Filter 2 consisted of 94 cm of anthracite with a range of EBCTs of 2±10 min at a loading rate of 5.0 m hÿ1. The ®lters were allowed to develop biological activity by acclimating each with ozonated water at dierent loading rates (Filter 1Ð9.7 m hÿ1, Filter 2Ð5.0 m hÿ1) for at least 60 days. The ozonated raw water (0.6± 0.85 mg O3 per mg DOC transferred dose) was applied to each ®lter continuously and each ®lter was backwashed once per day at a loading rate of 50 m hÿ1 for 10 min using ®nished water from the plant that had been dechlorinated with thiosulfate. Typically, the ®lters were backwashed based on run time, usually once every 24 h. A control ®lter was used to verify that DOC removal was due to biodegradation. The loading rate of the control
®lter was approximately 5.0 m hÿ1. The control ®lter consisted of 94 cm (36 in) of anthracite with an approximate loading rate of 5.0 m hÿ1 and a free chlorine residual in the in¯uent water of between 0.5 and 1.0 mg lÿ1. No DOC removal was measured with control ®lter (95% con®dence level) supporting the assumption that DOC removal in the experimental ®lters was due to biodegradation. The pilot plant was supplied with water from Horsetooth Reservoir (Fort Collins, CO). The source water quality during the study period was relatively constant (DOC=3.31 2 0.26 mg lÿ1 range, T = 10.2 2 1.18C range, pH=7.3 2 0.2 range, turbidity=2.6 2 0.4 NTU range). The pilot scale ®lters were operated in a direct ®ltration mode with an alum dose of 4 mg lÿ1 fed after the water had been ozonated in a three cell ozone contactor. DOC measurement Dissolved organic carbon (DOC) concentration measurement was the most critical analytical protocol of the study. To achieve adequate resolution of BOM and BDOC concentrations, all errors with this protocol needed to be minimized. For example, DOC samples were collected in acid washed ®lter housings and immediately ®ltered through 0.45 mm silver ®lters (Poretics, Livermore, CA) that had been mued at 5508C (the silver ®lters were found to contain trace organic contamination). TOC was measured using a UV-persulfate oxidation followed by a CO2 selective membrane which allows quanti®cation by conductivity (Sievers, Boulder, CO). An analysis of variance (ANOVA) experiment was conducted to quantify the components of DOC concentration measurement variability. The measurement variability was broken into three components: run-to-run, sample handling and instrument. Using a 7 5 3 ANOVA matrix, the pooled standard deviation was measured as 0.116 mg lÿ1. Most of this pooled standard deviation was due to sample handling (75.4%) with run-to-run variability accounting for 22.1% of the total. The error due to the TOC analyzer was only 2.5% of the total. The sample handling component included the error due to glassware, ®lter and atmospheric contamination and therefore it is not surprising that this fraction shows the highest variability. The low error attributable to the TOC analyzer indicated that measuring multiple samples would not appreciably capture the true error of analysis.
Table 2. Input data and constants required for model Input data Calculated based Input constants (experimental) on model (literature) u X z DOCn BOM UAP BAP qm K Y YSMP qUAP qBAP KUAP KBAP b acells kUAP kBAP
Hydraulic loading rate (®lter velocity) Biomass c concentration Filter depth Dissolved organic carbon at sample port n Biodegradable organic matter (true amount of carbon biodegraded) Utilization associated products Biomass associated products Maximum rate of BOM degradation Half-maximum rate concentration for BOM zdegradation Growth yield associated with BOM Growth yield associated with SMPu utilization Maximum speci®c rate of UAP degradation Maximum speci®c rate of BAP degradation Half-maximum rate concentration for UAP utilization Half-maximum rate concentration for BAP utilization Biomass endogenous decay coecient Biomass removed due to sloughing UAP formation rate constant BAP formation rate constant
cm minÿ1 mg carbon lÿ1 cm mg lÿ1 mg lÿ1 mg mg mg mg
X X X X
ÿ1
X X X X
l lÿ1 ÿ1 mgÿ1 cell min lÿ1
mgcell mgÿ1 BOM mgcell mgÿ1 SMP ÿ1 mg mgcell minÿ1 ÿ1 mg mgcell minÿ1 mg lÿ1 mg lÿ1 minÿ1 minÿ1 mgUAP mgÿ1 BOM ÿ1 mgBAP mgÿ1 BOM min
X
3.0Eÿ05
0.6 0.6 0.9Eÿ03 1.39Eÿ03 2.1E+04 1.4E+04 6.9Eÿ05 0.1 4.89Eÿ05
SMPs in biological drinking water Table 3. DOC concentration measurement 95% con®dence interval versus number of runs (two samples per run, two replicates per sample) No. of experimental runs 2 3 4 5 6
Table 4. Experimental conditions for model calibration runs Run no.
95% Con®dence interval (2mg lÿ1) 0.082 0.067 0.059 0.052 0.048
The 95% con®dence intervals that are reported in this paper for DOC concentration use a pooled standard deviation and therefore are a function of the number of runs that are done. Based on the pooled variance determined with the ANOVA experiment, the number of runs that would need to be completed to attain a given 95% con®dence interval can be determined. Assuming that two samples are collected per run and two analysis replicates are completed per sample, ®ve runs would be needed to achieve a 95% con®dence interval of 20.05 mg lÿ1 DOC concentration. The 95% con®dence intervals are compiled for dierent numbers of experimental runs in Table 3. Biomass measurement The presence of biomass was quanti®ed by measuring the lipid-bound phosphorous (total lipid phosphate) according to a method described by Findlay et al. (1989). Media was removed from the ®lters at various depths throughout the study using a horizontal coring device that could be inserted into the sample ports in the side of the ®lters. Approximately 3 g of media were removed for each test, an amount that was negligible relative to the total (>40,000 g). The media was removed after a backwash and the interstitial biomass was assumed to be negligible. This protocol resulted in the measurement and correlation
1389
1 2 3
Transferred ozone dose (mg O3 mg DOCÿ1)
Filter loading rate (m hÿ1)
EBCT (min)
0.60 0.60 0.85
5.0 9.7 9.8
10 11 11
of only the attached biomass. The lipid-bound phosphorous was extracted and then digested to inorganic phosphate followed by colorimetric quanti®cation. The units of per g of dried media measurement are nmoles of POÿ3 4 and therefore these measurements should not be compared between media types of dierent density. The method was found to be repeatable with measurements taken from the same sample but variability between samples was found to be signi®cant. ANOVA results for the total lipid phosphate analysis indicated that 98% of the variance was due to the sampling and only 2% was due to the analytical process after extraction had occurred. This result is not surprising because media, due to its heterogeneous nature, would not be expected to develop bio®lms equivalently. Additionally, regular backwashing will partially restratify the media, further contributing to variability at any point in the ®lter. The model input parameters (DOC concentration depth pro®le and biomass depth pro®le) are described elsewhere (Carlson and Amy, 1998) and only summarized here. With these input parameters, ®ve values from the model equations remain as unknowns. Since there are ®ve equations, these ®ve unknowns can be uniquely determined. Using a ®nite dierence, least squares algorithm, BOM, UAP and BAP were solved versus depth (z ) and the BOM kinetic coecients (qm and K ) were solved as constants throughout the bio®lter depth. Three model calibration data collection experiments
Fig. 1. SMP formation experimental protocol.
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Kenneth H. Carlson and Gary L. Amy
Fig. 2. Model predictions for BOM and DOC removal; loading rate=9.7 m hÿ1, ozone dose=0.6 mg O3 per mg DOC. were conducted at dierent ozonation (BOM formation) or ®lter (BOM removal) conditions (Table 4). The model was solved at three sets of operating conditions using the data from these experiments. SMP formation experiments Directly measuring SMPs in a bio®lter that treats water containing NOM is not possible because the DOC contributions from SMPs cannot be chemically distinguished from the original NOM. Alternatively, if all of the DOC in¯uent to a bio®lter can be accounted for in terms of known compounds, the total SMP concentration can be estimated. The dierence between the removal of known substrates (as carbon) and the removal of DOC should be the soluble microbial products when adjusted for SMP biodegradation using literature kinetic values (Woolschlager and Rittman, 1995b). An approach was developed to experimentally estimate SMP formation by feeding a synthetic water into the pilot scale bio®lter (anthracite media) and measuring both the DOC removal and the known compound removal (as carbon) throughout the ®lter depth (Fig. 1). The synthetic water consisted of de-ionized, NOM-free water (DOC concentration was measured to be approximately 0.1 mg lÿ1) that had been reconstituted to the bulk water quality in terms of ionic strength, hardness, pH and microbial nutrients nitrate and orthophosphate (Fig. 1). The easily biodegradable ozone by-products (OBPs) included various carboxylic acids, aldehydes, and keto-acids: oxalate, formate, glyoxal, methyl glyoxal, pyruvate and glyoxalate. The relative formation of these compounds during ozonation and the fraction of the BOM that they constitute has been described previously (Carlson and Amy, 1997). The SMP pro®le was determined by measuring the DOC concentration at each sample port 30 min after instantaneously switching the ®lter in¯uent from the ozonated water used for acclimation to the synthetic water source. The SMP concentration was calculated as the dierence between the OBP removal (as carbon) and the DOC removal when UAP and BAP biodegradation are
considered (Eqs. (6) and (7)). Eq. (6) can be understood by examining each component. OBP Removal represents the consumption of the in¯uent substrate. This value should equal the DOC Removal if no SMPs are present. If SMPs are present, DOC removal will be reduced by this amount. The measured concentration of SMPs will be reduced by biodegradation and therefore the total concentration needs to be adjusted upwards by this amount. The UAP and BAP biodegradation term (rUAP and rBAP) is determined using the Monod expressions that are part of the model described in Table 2. SMP OBP Removal ÿ DOC Removal SMP biodegradation
6
SMP OBPinfluent ÿ OBPPort n ÿ DOCinfluent ÿ DOCPort n rBAP rUAP
7
where rUAP is the predicted UAP biodegradation (mg lÿ1), rBAPis the predicted BAP biodegradation (mg lÿ1). Ozone by-product measurement Four dominant aldehydes (formaldehyde, acetaldehyde, glyoxal, methyl glyoxal) were determined by gas chromatography (Hewlett-Packard 5890II) using the method described by Sclimenti et al. (1990). The method involves derivatizing the aldehydes to oximes using PFBHA, O(2,3,4,5,6-penta¯uorobenzyl)-hydroxylamine hydrochloride. HgCl2 was added for preservation but all samples were still derivatized within 24 h. Three dominant ketoacids (glyoxylic acid, ketomalonic acid, pyruvic acid) were measured using a method described by Xie and Reckhow (1992). The ketoacids were derivatized to oxime methyl esters using PFBHA and diazomethane and then quanti®ed using gas chromatography. Samples were derivatized within 6 h of collection and not preserved because of results indicating that HgCl2 addition
SMPs in biological drinking water increased the measurement variability. The interference of HgCl2 with ketoacid measurement was also veri®ed experimentally in this study. Ion chromatography (Dionex, Sunnyvale, CA) was used to determine three dominant carboxylic acids (formate, acetate, oxalate). The method (Kuo et al., 1995) utilizes an AS-10 concentrator column, an AG10 guard column and a conductivity detector equipped with an AMMSII micromembrane suppresser. Samples were preserved with HgCl2 immediately after collection and measured within 24 h. RESULTS AND DISCUSSION
Model predictions of SMP formation The model solution using calibration data from run no. 2 is shown in Fig. 2. Carbon removal is expressed two ways, the measured DOC removal and the calculated BOM removal. The error associated with using DOC removal as an estimate of the BOM removal can be represented as the SMP concentration as a percentage of DOC removed (Eq. (8)). This error would be in addition to the measurement variability discussed previously, less than 0.05 mg lÿ1 (95% con®dence level) for these experiments. DOC
SMP 100 percentage Removed
error
8
Several observations can be made from Fig. 2. First, SMPs constitute a large fraction of the biodegradable material; the dierence between the actual BOM and the measured DOC removal is approximately 25% at the euent of a 175 cm deep bio®l-
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ter. The SMP concentration as a percent of DOC removal increases rapidly in the ®rst 10 cm of the ®lter bed and appears to reach a maximum value within the ®lter bed modeled in the example. The predicted concentrations of SMPs across the bio®lter with the run no. 2 calibration data are shown in Fig. 3. Both formation and biodegradation terms are included in the calculations for the net concentration of UAPs and BAPs. Therefore, the divergence between the UAP or BAP net concentration and formation curves represents the predicted biodegradation. Based on the model results shown in Fig. 3, the biodegradation of UAPs is signi®cant relative to UAP formation (033%) but not important with respect to the total BOM biodegradation (02%). BAP biodegradation was less signi®cant than UAP degradation even though the concentration was greater. The model was also used to determine the SMP and BOM concentrations associated with two other ozonation/bio®ltration conditions. A summary of the ozone and bio®ltration conditions and the SMP production for the three runs is presented in Table 5. The bio®ltration conditions include the ®lter HLR, in¯uent DOC concentration and the in¯uent BOM concentration. Changing the ozone dose (substrate concentration) and ®lter loading rate (substrate ¯ux) created dierent biomass and DOC removal pro®les. The in¯uent BOM represents the BOM that was ®lter removable for each experiment as determined with the model for a 175 cm deep bio®lter and this value is impacted by the ozonation
Fig. 3. Model predictions for SMP formation and degradation; HLR=9.7 m hÿ1, ozone dose=0.6 mg O3 per mg DOC.
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Table 5. Summary of predicted SMP production for three bio®lter conditions (Values in parentheses are normalized to the ®rst experiment) Experimental conditions
1 2 3
Biomass at ®lter surface
SMPs at the bottom of the ®lter (empty bed contact time 110 min)
Ozone dose (mg O3 per mg DOC)
Filter HLR (m hÿ1)
In¯. DOC (mg lÿ1)
In¯. BOM (mg lÿ1)
Phospholipids (nmole POÿ3 4 per g media)
UAPs (mg lÿ1)
BAPs (mg lÿ1)
Total as % of DOC removal
Total as % of euent DOC
0.60 0.60 0.85
5.0 9.7 9.8
3450 3370 3310
397 (1.0) 434 (1.1) 565 (1.4)
56 (1.0) 121 (2.2) 314 (5.6)
22 (1.0) 20 (0.9) 18 (0.8)
33 (1.0) 65 (2.0) 119 (3.6)
17% (1.0) 25% (1.5) 33% (2.0)
1.8% (1.0) 2.9% (1.6) 5.0% (2.8)
conditions. The biomass concentration at the surface of the ®lter is also shown for each bio®ltration condition as a relative indicator of the biomass pro®le, which could be roughly described with a ®rst order decay relationship. The calculated SMP concentrations are shown for each set of experiments. The UAP concentrations were equivalent for each experiment even though the in¯uent BOM was greater by a factor of 1.4 for the third experiment. This discrepancy was due to the higher rate of biodegradation predicted for the UAPs in this experiment. BAP production increased as the surface biomass increased but not linearly. The ®rst two experiments, which were run using the same water quality and ozonation conditions, showed equivalent BAP and biomass increases. The third experiment, which was run with dierent water quality and ozonation conditions, did not show equivalent BAP and biomass increases. This result is most likely due to a dierent biomass depth pro®le since the biomass-normalized BAP production rate should be equivalent for
all three experiments (the BAP production rate was modeled using the same rate constants for all three model calibration conditions). The third set of water quality and ozonation conditions that was studied (run no. 3) had a higher transferred ozone dose (0.85 mg O3 per mg DOC versus 0.60 mg O3 per mg DOC). The net eect of the water quality and ozonation changes was an increase in BOM in¯uent to the bio®lter that was operated at a loading rate of approximately 9.8 m hÿ1. The relative SMP production predicted for these bio®ltration conditions was greater than the two previous cases, and roughly 33% of the DOC removal. The SMP concentration was less than 5% for all three experiments when expressed as a fraction of the bio®lter euent DOC concentration. These results indicate that with the relatively low biological activity that is found in drinking water treatment bio®lters, SMPs comprise an almost negligible portion of the post-®lter DOC pool. The high fraction of BAPs shown in Table 5 also indicates that
Fig. 4. The fate of three biodegradability-related DOC fractions through the bio®lter for the run no. 3 model calibration conditions.
SMPs in biological drinking water
the biomass accumulation, not the BOM utilization, relates most strongly to SMP formation. The predicted DOC in the bio®lter was divided into three fractions at each depth: 1. NBOMÐBOM not removable during bio®ltration; 2. BOMÐBOM removable during bio®ltration; 3. SMPsÐSMPs formed during bio®ltration. Using the model solution from run no. 3, these three fractions are plotted versus bio®lter depth in Fig. 4. The ®lter in¯uent water contained two fractions, the non-biodegradable organic matter and the biodegradable organic matter formed as a result of the ozonation process. Initially, the BOM represented 18% of the total DOC. The BOM was reduced to 0% of the total DOC in the ®lter euent by de®nition. In contrast, the SMP concentration only increased to 5% of the total DOC concentration in the ®lter euent water. Based on the results presented here, the concentration of SMPs in the ®lter euent water is insigni®cant relative to the overall pool of DOC. SMP formation experiments An attempt was made to measure the concentration of SMPs directly by feeding the bio®lter a synthetic water with a known pool of DOC, comprised of individual, easily-biodegradable compounds. The SMP concentration was determined with Eq. (7). Two sets of experiments were conducted. The ®rst set of experiments used a synthetic water with
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six known OBPs (Fig. 3) that represent a range of biodegradation rates. The experimentally determined soluble microbial products are compared with the model prediction for these bio®ltration conditions as a function of bio®lter depth in Fig. 5. Experimental SMP values ranged from 58 to 99 mg lÿ1 but the coecient of variation ranged from 45 to 66% due primarily to the magnitude of the SMP concentrations relative to the error associated with DOC concentration measurement. Nevertheless, the 95% con®dence intervals (based on two duplicate measurements of three samples at each port for two runs) of the experimental data overlap with four out of six of the model predicted values. The second SMP production experiment used glyoxal as the sole BOM substrate. Glyoxal was the least biodegradable of the eight ozone by-products used in this study and this experiment was intended to determine if the bio®lter in¯uent substrate aected the production of SMPs. The predicted SMP production is compared with the experimentally measured values in Fig. 6. The SMP pro®le determined with glyoxal as the substrate is similar to that measured with the multiple OBP substrate. Glyoxal is biodegradable but only partially so with the contact time of the ®lter used in this study. The experimental pro®les indicate that SMP formation is greatest at the top of ®lter (this is where the biomass concentration and BOM assimilation are greatest) followed by signi®cant biodegradation. The experimental results could be interpreted as indicating higher biodegradation kinetic coecients than were used.
Fig. 5. Comparison of SMP concentrations determined experimentally and predicted with the model using a multiple-OBP substrate.
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Fig. 6. Comparison of SMP concentrations determined experimentally and predicted with the model using glyoxal as the sole substrate.
Fig. 7 compares the experimental and modeled SMP results with the total DOC concentration pro®le across the ®lter depth. Approximately 14% of the in¯uent DOC was removed through biodegradation in the bio®lter as the concentration was
reduced from 3150 to 2720 mg lÿ1. In contrast, none of the modeled or measured SMP values exceeded 140 mg lÿ1, a value that is less than 5% of the ®lter euent DOC concentration. The dierence between the measured and modeled results is insigni®cant
Fig. 7. Comparison of measured and predicted SMP concentrations with total DOC concentration as a function of ®lter depth (substrate glyoxal).
SMPs in biological drinking water
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Fig. 8. SUVA ®lter depth pro®le for BOM with and without non-biodegradable NOM.
within the context of the background DOC concentration. The results presented in Fig. 8 were also analyzed from a macroscopic perspective. The data in Figs 5 and 6 tends to indicate that the kinetic coecients used for UAP and BAP biodegradation were underestimated. A sensitivity analysis was conducted to determine the impact of these values on the conclusions from this study. The maximum degradation rate constants, qUAP and qBAP, were changed by factors of 0.5 and 2.0. This coecient variation resulted in the SMP concentration as a fraction of the total DOC removed varying only from 31 to 35%. SMP concentration as a fraction of the euent DOC varied from 4.6 to 5.4% for these six scenarios indicating that the conclusions of this study are not very sensitive to the biodegradability of the UAP and BAP species. SMPs appear to be important when compared to the DOC removed in a bio®lter. The data indicates that the SMP concentration can be greater than 32% of the BOM concentration, a signi®cant amount. To further illustrate this point, the speci®c ultra-violet absorbance at 254 nm (SUVA), an indicator of the aromatic character of NOM (Edzwald and Van Benschoten, 1990), was measured during the known multi-substrate, arti®cial water, SMP formation experiments that were described in Fig. 3. SUVA is the UV absorbance at 254 nm (mÿ1) divided by the DOC concentration (mg lÿ1). The SUVA value increases with an increasing fraction of aromatic or double-bond-rich substances that tend to absorb more strongly at 254 nm. Two sets of data are plotted in Fig. 8. The ®rst set of data (without NBOM in Fig. 8) is the
arti®cial water without the dominant non-biodegradable NOM. The second set of data (with NBOM in Fig. 8) is the SUVA measured with the ozonated natural water in the ®lter. The key point here is that an increasing SUVA implies an increasing concentration of larger, more aromatic, doublebond-rich compounds, potentially a result of SMP production. When the background NOM was present, no trend in SUVA values was apparent. These data further support the supposition that SMPs were insigni®cant relative to the non-biodegradable organic matter. CONCLUSIONS
The primary objective of the research described in this paper was to determine if SMPs are important in a typical drinking water bio®ltration process. SMPs were found to be important only if considered relative to the DOC that is removed during bio®ltration. SMPs do not appear to be important if the BOM fraction of the ®lter-in¯uent DOC is small. If the BOM removal during bio®ltration is being determined, the presence of SMPs will result in a 17±33% error if DOC removal is used for the estimate of BOM. The production of SMPs is highly dependent on the bio®ltration conditions including the substrate (BOM) utilization rate and the accumulated biomass. The conclusions presented here are made in the context of what is considered to be typical drinking water process conditions. The formation of SMPs will be directly related to the BOM removal and the biomass concentration. The
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Kenneth H. Carlson and Gary L. Amy
removal of 10±20% of the in¯uent DOC (roughly the range reported in this study) has been reported by other researchers (Servais and Billen, 1991; Huck et al., 1994, Wang and Summers, 1995) and the biomass levels at the top of the ®lter reported in this research compare favorably with other research (Miltner et al., 1995; Wang and Summers, 1995). AcknowledgementsÐThis work was supported by the Fort Collins (CO) Water Utility and the University of ColoradoÐBoulder. Appreciation is expressed to Greg Blais (University of Colorado) and Sarah MacMillan (City of Fort Collins) for their assistance with the analytical and experimental work. The contributions of the manuscript reviewers is also acknowledged. REFERENCES
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