Controlling trace organic contaminants with GAC adsorption

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Corwin & Summers | http://dx.doi.org/10.5942/jawwa.2012.104.0004 Journal - American Water Works Association Peer-Reviewed

Controlling trace organic contaminants with GAC adsorption C hr i s t o p he r J. Co rw in 1 and R. Sc ott Summers 2 1Jacobs

Engineering, Denver, Colo. University of Colorado, Boulder, Colo.

2Professor,

The adsorption of trace organic contaminants by granular activated carbon (GAC) was assessed relative to the control of taste and odor (T&O) compounds and disinfection by-product (DBP) precursor removal. Adsorbers operated for the control of T&O and DBP precursors were shown to yield good to excellent removal of 17 trace organic contaminant probe compounds. Increasing influent concentration of the trace organic contaminant in the parts-per-billion level was shown not to affect compound breakthrough on a normalized basis;

however, higher influent concentrations did lead to earlier breakthrough on a mass concentration basis. Increasing background dissolved organic matter concentration increased competition for a fixed number of adsorption sites and led to earlier breakthrough. Optimal empty bed contact time depended on the specific treatment objectives and the contaminant removal level needed to meet those objectives. Series and parallel adsorber operation was calculated to yield a twofold decrease in the GAC use rate.

Keywords: disinfection by-products, granular activated carbon, micropollutants, optimization, taste and odor Public concern has increased about trace levels of pesticides, pharmaceuticals, and personal care products (some of which are suspected endocrine-disrupting compounds) in drinking water sources since the presence of these compounds was reported by Kolpin and colleagues (2002). These compounds, collectively termed trace organic contaminants, are typically not well removed during conventional drinking water treatment (Westerhoff et al, 2005). To maintain consumer confidence, some utilities are considering additional treatment to remove these contaminants, regardless of their regulatory status.

Background Granular activated carbon (GAC) adsorption is an effective barrier against a wide array of dissolved organic contaminants. In surface waters, GAC is most commonly applied for control of taste and odor (T&O) compounds, often the algal metabolites 2-methylisoborneol (MIB) and geosmin. MIB and geosmin usually occur in episodes lasting from two weeks to two months with concentrations between 30 and 100 ng/L (Graham et al, 2000a). GAC use for control of disinfection by-product (DBP) formation by removal of dissolved organic matter (DOM) has increased. In groundwaters, GAC is typically used to control specific organic contaminants. GAC can be applied as the media in a filter, termed a filter adsorber (FA), or in a separate adsorber placed after the filter, termed a postfilter adsorber (PFA). FAs typically are operA full report of this project, Cost-Effective Regulatory Compliance With GAC Biofilters (4155), is available for free to Water Research Foundation subscribers by logging on to www.waterrf.org.

ated with empty bed contact times (EBCTs) of 5 to 10 min, whereas PFAs use longer EBCTs, typically 10 to 20 min (Summers et al, 2010). GAC adsorption is a nonsteady-state process that involves time- and resource-intensive pilot studies for optimized designs. Bench-scale tools have the potential to reduce the time and expense associated with pilot studies, resulting in a more informed process selection. Estimating the cost of GAC requires consideration of three primary variables: capital cost, GAC use rate, and the adsorber operational cost. Capital cost is mostly driven by adsorber size and can be highly variable, depending on space availability, hydraulics, influent water quality, location, reactivation approach, and operation strategy. The use rate is a measure of the GAC mass needed to treat a given volume of water. The bed life is the frequency of how often the GAC must be replaced, which may be a significant portion of the operational cost for some systems. In this study, use rate and bed life were used as an indicator of cost, because capital and operating costs of GAC adsorbers are site-specific. The use rate for a single adsorber to a specific treatment objective is calculated in Eq 1: GAC  Use rate = BVTO (1)

in which rGAC is the apparent bed density of the GAC media, BVTO is the throughput in bed volumes (BV) to the treatment objective (TO); BV = volume treated/volume of empty GAC bed or BV = operation time/EBCT.

2012 © American Water Works Association

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The bed life is calculated in Eq 2: Bed life = BVTO × EBCT

(2)

The rapid small-scale column test (RSSCT) can be used to estimate use rate and bed life on the bench scale early in the process planning stage. The RSSCT uses the principle of similitude to scale down the fixed-bed adsorption process. Because the RSSCT uses GAC particles crushed to a smaller size, breakthrough curves can be obtained in a much shorter time and using less water than is required by pilot studies (Crittenden et al, 1991). The RSSCT design is based on proportional diffusivity (PD) and has been shown to match DOM breakthrough curves (Crittenden et al, 1991). Historically, less success has been found in matching RSSCT breakthrough curves for target compounds to full-scale results when background DOM is present. Corwin and Summers (2010) determined that fouling by DOM was dependent on GAC particle size because crushing the GAC to a smaller particle size opens more of the surface area to the bulk flow and makes the smaller GAC less susceptible to pore blockage by DOM. Thus RSSCTs indicate more adsorption capacity for trace organic contaminants than is observed in full-size GAC. A mathematical procedure for projecting PD–RSSCT breakthrough curves to full scale has been presented and requires data at two GAC particle sizes (Corwin & Summers, 2010). However, breakthrough curves from the PD–RSSCT may not match fullscale results because intraparticle diffusivity may not be perfectly simulated. The objective of the current study was to assess GAC control of trace organic contaminants relative to GAC control of T&O compounds and DBP formation. A series of RSSCTs was performed to assess the effects of influent contaminant concentration, influent DOM concentration, EBCT, and operational strategies. These results were then projected to full-scale use rate and bed life for typical scenarios. MIB was selected to represent T&O removal because earlier work has shown MIB to be more weakly adsorbed than geosmin (Kim & Summers, 2006). Because bed life is a function of EBCT, comparisons were made at a 10-min EBCT, which is typical for both FAs and PFAs.

Pharmaceuticals included carbamazepine (CBZ), caffeine, diclofenac, diphenhydramine, erythromycin (ERY), gemfibrozil, and sulfamethoxazole (SMX). Daidzein and genistein are plant estrogens. Bisphenol A (BPA) is a plasticizer, MIB is an algal metabolite, tris(2chloroethyl)phosphate is a flame retardant, and N,N-diethyl-metatoluamide is an insect repellant. Probe compounds were selected to be representative of an array of trace organic contaminants based on physical properties known to affect adsorption, i.e., molecular weight, ionic state, and hydrophobicity. Molecular weights ranged from 168.3 to 733.9 D, and hydrophobicity ranged from –0.70 to 4.47, measured as log Kow (octanal–water partition coefficient) values. Eight compounds were nonionic, and the remaining compounds had pKa values ranging from 0.67 to 10.5. Probe compound analysis. Radiolabeled probe compounds were obtained from a supplier.1 To yield detection limits below 10 ng/L, 14C BPA, 14C MIB, 3H 2,4-D, and 3H ERY were adjusted to a specific activity by adding a measured mass of unlabeled carrier stock. Samples were prepared by placing 4 mL of sample and 16 mL of scintillation cocktail into a 20-mL polyethylene vial. Samples were analyzed on a liquid scintillation analyzer for 40 min of counting time. A series of dual-labeled quenched standards was prepared and analyzed to determine scintillation counting efficiencies.

TABLE 1

Molecular properties of probe compounds MW

log Kow

pKa

2,4-D

Probe Compound

221.0

2.81

2.73

Atrazine

215.7

2.65

1.7

BPA

228.3

3.32

10.5

Caffeine

194.2

-0.07

10.4

CBZ

236.3

2.45

0.37

Daidzein

254.2

2.55

7.1

DEET

191.3

2.18

0.67

Deethylatrazine

187.6

1.51

NA

Deisopropylatrazine

173.5

1.15

NA

Diclofenac

296.2

0.70

4.51

MATERIALS AND METHODS

DPH

255.4

3.27

8.98

Adsorbents. Fresh bituminous and lignite GACs were handcrushed with a mortar and pestle and separated with US standard sieves on a sieve shaker. The fraction between the 100 and 200 sieves (particle diameter = 0.11 mm) was collected for bench-scale experiments. The crushed GAC was rinsed in laboratory reagent water to separate fines and then dried in an oven at 105°C to a constant weight. The GAC was stored in a capped bottle in a desiccator until use. For one experiment, the prepared GAC was preloaded with DOM by performing an RSSCT with unspiked influent water. Adsorbates. Table 1 summarizes the molecular properties of the 20 probe compounds used in this research. The compounds included the following seven pesticide/herbicides or degradates: 2,4-dichlorophenoxyacetic acid (2,4-D), atrazine, flutolanil, prometon, simazine, deethylatrazine, and deisopropylatrazine.

ERY

733.9

3.06

8.88

Flutolanil

323.3

3.7

NA

Gemfibrozil

250.3

4.77

4.42

Genistein

270.2

2.84

7.2

MIB

168.3

3.31

n/a

Prometon

225.3

2.99

4.3

Simazine

201.7

2.18

1.62

SMX

253.3

0.89

5.5

TCEP

285.5

1.44

NA

Compiled from National Library of Medicine (2011), Snyder et al (2007), and Westerhoff et al (2005) 2,4-D—2,4-dichlorophenoxyacetic acid, BPA—bisphenol A, CBZ—carbamazepine, DEET— N,N-diethyl-meta-toluamide, DPH—diphenhydramine, ERY—erythromycin, MIB—2-methylisoborneol, MW—molecular weight, NA—not applicable, SMX— sulfamethoxazole, TCEP—tris(2-chloroethyl)phosphate


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trihalomethanes maximum contaminant level (MCL), 64 µg/L, under simulated distribution system conditions. These treatment objectives were met at bed replacement frequencies of 5,700 BV for MIB control and 9,500 BV for DBP control. At 10,000 BV, 16 of the 17 probe compounds exhibited less than 10% breakthrough, whereas SMX exhibited ~ 20% breakthrough. As detailed in the following section, at these low concentrations, the

FIGURE 1 RSSCT breakthrough curves for MIB, DOC, and 15 probe compounds (divided into two parts for clarity)

0.9 T&O bed life

0.8 0.7 0.6 0.5 0.4 0.3 0.2 0.1 0.0

0

5,000

10,000

15,000

20,000

25,000

30,000

25,000

30,000

Throughput—BV

B

1.0 0.9

T&O bed life

0.8

C/C0

0.7 0.6 0.5

Gemfibrozil Daidzein Deethylatrazine DPH

DOC Prometon MIB Caffeine TCEP DBP bed life

RESULTS AND DISCUSSION Results from the 17 RSSCTs indicated SMX, ERY, and BPA were the first of the 20 compounds to break through; as such, they were chosen as probes to represent weakly adsorbing trace organic contaminants. GAC performance for removing these three conservative probe compounds was then compared with removal of MIB (representing T&O compounds) and DOC (representing DBP precursors). Adsorption of trace organic contaminants relative to MIB and DBP precursors. An RSSCT was performed with reservoir water with the following influent properties: influent DOC (DOC0) of 2.4 mg/L and a specific UVA (SUVA) of 1.5 L/mg-m, 17 trace organic contaminant probe compounds at 500 ng/L each, and MIB at 100 ng/L. The RSSCT was designed to simulate an FA with fresh 8 × 20 bituminous GAC with a bed density of 0.5 g/cm3 and an EBCT of 7.1 min. Figure 1 shows the RSSCT breakthrough curves for DOC, MIB, and 15 of the 17 trace organic contaminants on a throughput basis in BV, which normalizes performance per mass of GAC. Genistein and deisopropylatrazine were not detected in the effluent. The data in Figure 1 show that DOC broke through first, followed by MIB, and then the 17 probe compounds. The treatment objective for MIB was assumed to be an odor threshold of 10 ng/L. DBP formation testing on this water indicated a DOC treatment objective of 1.4 mg/L was required to meet 80% of the total

2,4-D DEET Atrazine Simazine Flutolanil

DOC SMX MIB CBZ Diclofenac DBP bed life

A

1.0

C/C0

Samples from experiments not using radiolabeled compounds were analyzed using liquid chromatography followed by tandem mass spectrometry with a reporting level of 1 ng/L each. Analysis was conducted at the Center for Environmental Mass Spectrometry at the University of Colorado, Boulder. Dissolved organic carbon (DOC) and ultraviolet absorbance (UVA). DOC samples were analyzed using the ultraviolet irradiation/ persulfate oxidation method in accordance with method 5310C (Standard Methods, 2005). UVA254 was analyzed at a wavelength of 253.7 nm using a spectrophotometer in accordance with method 5910 (Standard Methods, 2005). RSSCTs. RSSCTs were designed according to the PD approach (Crittenden et al, 1991) in order to match DOC breakthrough curves to full scale. All RSSCT results were projected to full scale using the method presented in Corwin and Summers (2010). GAC was packed into a 4.76-mm (inside diameter) PTFE column. A diaphragm pump delivered the influent water to the column at 2 mL/min. All materials in contact with the water were either glass, PTFE, or stainless steel. The influent reservoir was designed with a trap on the air-displacement side to minimize volatilization losses. Influent samples were periodically taken from immediately above the column. In addition to probe compound concentration, samples were analyzed for UVA, pH, and DOC concentration. Seventeen RSSCTs with four different GACs at seven different EBCTs ranging from 5 to 20 min were run. Eleven of the 12 surface waters were coagulated with alum in the sweep floc zone, flocculated, settled, and then filtered through a 0.45-µm filter, resulting in DOC concentrations of 1.3 to 3.8 mg/L and pH of 7.0 to 8.2. One source water was treated solely by low-pressure membrane.

0.4 0.3 0.2 0.1 0.0

0

5,000

10,000

15,000

20,000

Throughput—BV 2,4-D—2,4-dichlorophenoxyacetic acid, BV—bed volume, CBZ—carbamazepine, DEET—N,N-diethyl-meta-toluamide, DBP—disinfection by-product, DOC—dissolved organic carbon, DPH—diphenhydramine, EBCT—empty bed contact time, GAC—granular activated carbon, MIB—2-methylisoborneol, SMX—sulfamethoxazole, TCEP—tris(2-chloroethyl)phosphate, T&O—taste and odor Bituminous GAC, EBCT = 7.1 min, DOC0 = 2.4 mg/L


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influent concentration of the compound does not affect the breakthrough curve when plotted in this manner; therefore, the MIB and trace organic contaminant results are valid for all environmental concentrations typically encountered. For MIB breakthrough at 10 ng/L, the use rate and bed life for a single adsorber with a 10-min EBCT were 0.73 lb GAC/1,000 gal and 40 days, respectively. For DBP control at an effluent DOC of 1.4 mg/L, the use rate and bed life improved to 0.44 lb GAC/1,000 gal and 66 days, respectively. For control of trace organic contaminants, a treatment objective of 80% removal of the most weakly adsorbed probe compound was used as a baseline criteria throughout this study, which resulted in high removal of the total mass of all measured trace organic contaminants. At a treatment objective of 80% SMX removal, the use rate and bed life improved to 0.42 lb GAC/1,000 gal and 70 days, respectively. Thus, under these operating conditions, the 10% breakthrough of MIB at a constant influent concentration of 100 ng/L for 40 days (representing a long T&O episode) controls GAC bed life. As shown in subsequent sections, optimization of the operating conditions significantly improved the use rate and bed life. Although these results were valid only for the conditions tested, it was expected that the breakthrough curves of the probe compounds would occur in the same relative order with other waters and GACs. The breakthroughs remain relative because the factors that change (such as the GAC product, background water, and EBCT) tend not to change the probe compounds’ adsorbability, only the level of competition. To illustrate this, throughput results at 10% breakthrough, BV10%, from Figure 1 were compared with those from Snyder and colleagues (2007) for eight compounds used in both studies. The results were normalized to those for CBZ (BV10% /BV10% CBZ), CBZ being the compound that broke through last. Figure 2

FIGURE 2

Throughputs to 10% breakthrough for data from Figure 1 compared with reported values by Snyder et al (2007) normalized to CBZ

BV10% /BV10% CBZ From Figure 1

1.0

CBZ

R2 = 0.95

Atrazine

Caffeine

DEET 0.5

Gemfibrozil TCEP Diclofenac SMX

0.0

0.0

0.5

1.0

BV10% /BV10% CBZ From Snyder et al 2007 BV—bed volume, CBZ—carbamazepine, DEET—N,N-diethyl-metatoluamide, TCEP—tris(2-chloroethyl)phosphate

show a good linear relationship for this water—even though the studies used different GACs, waters, and RSSCT design approaches—confirming the relative adsorbability of the compounds. Combining results from both studies resulted in a total of 40 probe compounds, and only one compound, iopromide, was more weakly adsorbed than SMX. However, the hundreds of trace organic contaminants that may be present in source waters exhibit a continuum of adsorbabilities, and compounds less adsorbable than SMX could be present. Effect of trace organic contaminant influent concentration. Several researchers have reported a lack of influence of target compound initial concentration on the fraction remaining in batch studies when the initial target compound concentration was low compared with the initial DOM concentration (Westerhoff et al, 2005; Matsui et al, 2003; Graham et al, 2000b; Gillogly et al, 1998; Knappe et al, 1998). The lack of sensitivity is explained by a linear equilibrium isotherm in the parts-per-trillion concentration range, which has been reported theoretically and experimentally by others (Graham et al, 2000b; Kilduff et al, 1998; Knappe et al, 1998). Matsui and colleagues (2002) and Kim and Summers (2006) observed that influent concentration (C0) of the target adsorbate did not affect the breakthrough curve on a concentration-normalized basis (C/C 0) in continuous-flow adsorbers. Matsui et al (2002) tested simazine and asulam at C0 values up to 30 µg/L, and Kim and Summers (2006) tested MIB at C0 values up to 200 ng/L. The threshold concentration at which linearization of the isotherm occurs is not well defined but typically is in the low microgram-per-litre range. The threshold becomes higher as adsorbability of the compound decreases because weakly adsorbing compounds cannot as effectively compete against the background matrix. Figure 3 shows breakthrough curves for 2,4-D at a C0 of 100 ng/L and 1,000 ng/L in a reservoir water with a DOC0 of 2.4 mg/L (SUVA = 1.2 L/mg-m) and a DOM preloaded 8 × 30 (fullsize) lignite GAC. The data in Figure 3, part A, are presented on a mass concentration basis and show that the high C0 run yielded shorter throughput to a given effluent concentration, i.e., earlier breakthrough. However, when effluent concentrations are normalized as in Figure 3, part B, the C/C0 breakthrough curves are similar. When the treatment objective is a mass concentration (like most MCLs), use rate and bed life are dependent on the C0 of the target compound. For example, if the treatment objective is an effluent 2,4-D concentration of 50 ng/L, a single adsorber with a C0 of 1,000 ng/L can operate for only 5,000 BV, whereas the adsorber with the C0 of 100 ng/L can run up to 15,000 BV, yielding use rates of 0.63 and 0.21 lb GAC/1,000 gal, respectively. Conversely, a treatment objective of 80% removal of 2,4-D is met at 9,000 BV and a use rate of 0.35 lb GAC/1,000 gal at any 2,4-D C0 that is low enough to linearize the isotherm. Therefore, when the target compound varies throughout the year, its influent concentration must be carefully considered when adsorber costs are estimated. The data in Figure 3, part B, indicate that 2,4-D reached about 20% breakthrough at 9,000 BV, whereas under the conditions of Figure 1, 2,4-D ran twice as long. The earlier breakthrough


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occurred primarily because GAC preloaded with DOM was used in the run represented by Figure 3. Had SMX been used in the run represented by Figure 3, it would have been expected to have broken through earlier than 2,4-D, as shown in Figure 1. Effect of influent DOC concentration on trace organic contaminant adsorption. It is well established that competition from background DOM reduces the adsorption capacity of the GAC for target compounds (Summers et al, 2010; Sontheimer et al, 1988). Therefore, it may be expected that the breakthrough curves of trace organic contaminants will occur progressively earlier as the DOC0 increases because of increased competition for a fixed number of adsorption sites. Figure 4 shows breakthrough curves for ERY in four different coagulated and filtered

2,4-D breakthrough curves at influent concentrations of 100 and 1,000 ng/L plotted on effluent mass concentration basis (A) and normalized concentration basis (B)

FIGURE 3

A

Effluent 2,4 D Concentration—ng/L

400

C0 = 1,000 ng/L C0 = 100 ng/L

350 300 250 200

surface waters with DOC0 concentrations ranging from 1.5 to 3.0 mg/L. The Zachman and Summers (2010) model was used to verify that the DOC breakthroughs of all the waters were as expected, meaning none of the waters had DOC sufficiently different in character to affect the relative adsorbability of the DOC. All RSSCTs used an 8 × 30 (full-size) bituminous GAC, an 8-min EBCT, and an influent ERY concentration of 100 ng/L. The ERY data displayed systematically earlier breakthrough curves as the DOC0 concentration increased. Similar results were reported for MIB by Kim and Summers (2006) and are used in Table 2 for comparison. Table 2 shows use rate and bed life data for MIB, DOC, and ERY at DOC0 concentrations of 1.5 and 3.0 mg/L for a single adsorber. Under these conditions, the MIB treatment objective of 10 ng/L controls GAC replacement at both DOC0 concentrations with a higher use rate and shorter bed life, compared with DOC removal to 1.4 mg/L for DBP control and 80% ERY removal. MIB may not be present at all times of the year, however, and in that case, ERY would control the use rate at a DOC0 of 1.5 mg/L, and DOC would control the use rate at a DOC0 of 3.0 mg/L. Effect of EBCT on trace organic contaminant adsorption. Data in Figure 5, part A, show DOM breakthrough curves (as measured by UVA254) at EBCTs of 5, 7.5, 10, and 17 min. RSSCTs were performed using river water with a DOC0 of 2.3 mg/L (SUVA = 2.7 L/mg-m) and a 12 × 40 (full-size) bituminous GAC. A good UVA254–DOC relationship (DOC = 38· UVA254 + 0.17, R2 = 0.98, n = 12) was found, so UVA254 was used for this water in lieu of DOC for ease of analysis. As shown in Figure 5, part A, the breakthrough results indicated that as EBCT increased, the DOM

150 100

FIGURE 4

50 0

0

5,000

10,000

15,000

DOC0 = 3.0 mg/L DOC0 = 2.3 mg/L DOC0 = 1.9 mg/L DOC0 = 1.5 mg/L

20,000

Throughput—BV 0.8

B

0.6

0.7

0.5

0.6

ERY C/C0

2,4-D C/C0

0.4 0.3

0.5 0.4 0.3

0.2

0.2

0.1 0.0

Effect of DOC0 concentration on ERY breakthrough

0.1

0

5,000

10,000

15,000

20,000

Throughput—BV 2,4-D—2,4-dichlorophenoxyacetic acid, BV—bed volume, C0—influent concentration, DOC—dissolved organic carbon, DOM—dissolved organic matter, EBCT—empty bed contact time, GAC—granular activated carbon DOM preloaded lignite GAC, EBCT = 6 min, DOC0 = 2.4 mg/L

0.0

0

20,000

40,000

60,000

80,000

Throughput—BV BV—bed volume, DOC—dissolved organic carbon, ERY—erythromycin Bituminous GAC, EBCT = 8 min, C0 = 100 ng/L


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breakthrough curves were delayed, indicating better DOM removal, consistent with previous findings (Zachman & Summers, 2010; Bond & DiGiano, 2004). Figure 5, part B, shows BPA breakthrough curves from the same RSSCT at an influent concentration of 100 ng/L. At early adsorption times, when there was less than 10% breakthrough, the longer EBCTs performed better because early on, the mass transfer zones of DOM and BPA overlapped and a given adsorption site could be occupied by either DOM or BPA. Further into

FIGURE 5

A

1.0

Breakthrough curves for UVA254 (A) and BPA (B) at four EBCTs 17-min EBCT 10-min EBCT 7.5-min EBCT 5.0-min EBCT

0.9 0.8

UVA254 C/C0

0.7 0.6 0.5 0.4 0.3 0.2 0.1 0.0

0

5,000

10,000

15,000

20,000

25,000

30,000

Throughput—BV

B

0.4

BPA C/C0

0.3

the bed, however, the DOM, with a longer mass transfer zone, reached an adsorption site before BPA and thus hindered subsequent BPA adsorption. A significant amount of DOM preloading of the GAC occurred in the adsorber because the mass transfer zone of the DOM was longer than that of the trace organic contaminant. The deeper the location of the GAC in the column, the more it is fouled by DOM by the time the mass transfer zone of the target adsorbate arrives. Similar results were observed for ERY and MIB for this and other GAC runs in the current study. The data in Figure 5, part B, indicate that BPA was very weakly adsorbed, with the breakthrough curve near the DOM breakthrough. However, BPA is of more concern in the food and bottled water industry because of leaching from plastic and plastic-lined containers. Data shown in Figure 6 show the relationship between EBCT and use rate for MIB, DOC, and BPA at treatment objectives of 10 ng/L MIB, 1.4 mg/L DOC, and 80 and 90% BPA removal. The DOC and BPA curves were obtained from Figure 5, and the MIB data were obtained from Kim and Summers (2006). The data were not collected under the same experimental conditions, but they illustrate three different behaviors that may occur. The MIB use rate exhibited little to no dependence on EBCT at any treatment objective for this data set. The use rate for DOC adsorption decreased with increasing EBCT, as expected from Figure 5. An increasing use rate with EBCT was observed for 80% BPA removal, but the use rate at 90% BPA removal indicated no change with EBCT, reflective of the breakthrough curves in Figure 5. Under the conditions shown in Figure 6, the use rate for MIB was 1.16 lb GAC/1,000 gal for any EBCT. However, increasing the EBCT from 5 to 17 min increased the bed life from 12 to 42 days with the additional GAC in the larger EBCT adsorber. For DOC removal, increasing the EBCT from 5 to 17 min decreased the use rate from 0.67 to 0.33 lb GAC/1,000 gal and increased the bed life from 22 to 149 days, so adsorber operation and maintenance costs decrease with increasing adsorber size. When shorter EBCTs yield a favorable use rate, optimization must include economic analysis of the use rate and bed life because longer EBCTs exhibit a longer bed life. For 80% BPA removal, increasing the EBCT from 5 to 17 min increased the use rate from 0.76 to 1.9 lb GAC/1,000 gal but only increased the bed life from 19 to 26 days.

0.2

TABLE 2

0.1

Performance of single adsorber under different DOC0 concentrations with treatment objectives of DOC = 1.4 mg/L, MIB = 10 ng/L, and 80% ERY removal (bituminous GAC, EBCT = 10 min) DOC0 = 1.5 mg/L

0.0

0

2,000

4,000

6,000

8,000

10,000

Throughput—BV BPA—bisphenol A, BV—bed volume, DOC—dissolved organic carbon, EBCT—empty bed contact time, GAC—granular activated carbon, UVA—ultraviolet absorbance Bituminous GAC, DOC0 = 2.3 mg/L, UVA254 = 0.062 cm–1

DOC0 = 3.0 mg/L

Compound

Use Rate lb/1,000 gal

Bed Life days

Use Rate lb/1,000 gal

Bed Life days

MIB

0.32

90

0.70

42

DOC

< 0.07

> 400

0.67

43

ERY

0.08

350

0.60

49

MIB data were obtained from Kim and Summers (2006). DOC—dissolved organic carbon, EBCT—empty bed contact time, ERY—erythromycin, GAC—granular activated carbon, MIB—2-methylisoborneol


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FIGURE 6

Use Rate—lb GAC/1,000 gal

Relationship between EBCT and use rate for DOC, MIB, and BPA for given treatment objectives (different GAC and DOC0) 90% BPA removal 80% BPA removal

4.0

10 ng/L MIB 1.4 mg/L DOC

3.0

2.0

1.0

0.0

0

5

10

15

20

25

EBCT—min MIB data were obtained from Kim and Summers (2006). BPA—bisphenol A, DOC—dissolved organic carbon, EBCT—empty bed contact time, GAC—granular activated carbon, MIB—2-methylisoborneol

FIGURE 7

Use-rate calculation for lead–lag adsorbers in series for MIB 5-min EBCT 10-min EBCT

80 Effluent MIB Concentration—ng/L

For plants with multiple GAC adsorbers, the effect of EBCT can also be used to determine whether to run adsorbers with lower flow (longer EBCTs) or to take adsorbers out of service when plant demand is below maximum. If longer EBCTs have a negative effect on performance (as shown in Figure 6 for 80% BPA removal), plant flow should be distributed to the number of adsorbers that approximates the design EBCT. In addition, shorter EBCTs increase the filter loading rate, which may be favorable to breakthrough by reducing film (external) mass transfer resistance. When longer EBCTs are favorable for adsorber performance, as shown for DOC removal, then plant flow should be distributed evenly to all available adsorbers. Series and parallel operation of adsorbers. Operation strategy can significantly improve use rate and bed life over singleadsorber performance. Operation of adsorbers in series with a lead–lag strategy can improve the GAC use rate when treatment objectives require a high level of removal, which is typical for many target organic contaminants. Lead–lag series operation uses two adsorbers in series until the treatment objective is reached in the second (lag) adsorber to optimize use rate. At that time the GAC media is replaced in the first (lead) adsorber, and flow is switched so that the lag column becomes the lead column and the replaced adsorber becomes the new lag column (Figure 7). Often, a more conservative approach is used, in which the lead adsorber is replaced as soon as the target compound is detected in the lag column effluent, which results in very high levels of removal. The lead–lag strategy may require additional yard piping, which may have a significant effect on the capital construction cost. To illustrate the use-rate estimation for adsorbers in series, Figure 7 shows MIB breakthrough curves for EBCTs of 5 and 10 min. (Although series operation is unlikely to be economical for MIB because of its episodic nature, MIB is used as an example to illustrate the performance improvement of series adsorbers.) The breakthrough curves were obtained from an RSSCT with a water at a DOC0 of 2.8 mg/L (SUVA = 1.37 L/mg-m) and a 12 × 40 (full-size) bituminous GAC. At 45 days, the 10-min column reached the treatment objective of 10 ng/L, and the media in the 5-min column was replaced. To be strictly accurate, the RSSCT should be run to simulate the replacement of the lead adsorber to capture the preloading effects. The use rate is determined by integrating the adsorbed mass on the lead 5-min EBCT column (area A of Figure 7) plus the mass allowed in the effluent from the lag column (area B of the figure) to the point at which the treatment objective is reached. Area C in Figure 7 represents the mass adsorbed on the lag column, where MIB will continue to be adsorbed when it becomes the lead column. The use rate is calculated by Eq 3:

70

1

2

1

50 Area A

40 30 20

Area C

TO

10

Area B 0

0

Use rate (lb GAC/1,000 gal) =

10

20

30

40

50

Operation Time— days

C0 (ng/L) × EBCT (min) × GAC (g/cm3)  1,440 (min/d) × [Area A (ng/L × day) + Area B (ng/L × day)] × 8,345.4 (lb/g × cm3/gal)

(3)

2

60

DOC—dissolved organic carbon, EBCT—empty bed contact time, GAC—granular activated carbon, MIB—2-methylisoborneol, TO—treatment objective Bituminous GAC, DOC0 = 2.8 mg/L, C0 = 80 ng/L


60

E43


For the MIB data in Figure 7, the use rate for a single 10-min EBCT adsorber was 0.66 lb GAC/1,000 gal; for two 5-min EBCT adsorbers in series, the use rate dropped to 0.39 lb GAC/1,000 gal. Thus, for this case, the GAC media was used 70% more efficiently when operated in series. Operating adsorbers in staged parallel mode can also improve GAC use rate and is often used for DOC removal because DOC treatment objectives typically do not require the high levels of removal required for target organics. Staged parallel operation can be visualized with a three-adsorber system (Figure 8). At initial startup, all three adsorbers are put into service. When the treatment objective is reached, the media of one of the adsorbers are replaced, which allows the other adsorbers to operate beyond the treatment objective by blending their effluent with the effluent from the fresh adsorber. Cyclically, each time the blended effluent reaches the treatment objective, the media are replaced in the adsorber that has been in service the longest. The longer bed life of each individual filter allows a more favorable use rate while meeting the treatment objective with blended adsorber effluent. Roberts and Summers (1982) presented an integration model of the single breakthrough curve that is valid for 10 or more adsorbers in staged parallel mode, which would be the best practically attainable use rate. Figure 8 shows DOC breakthrough curves for a single adsorber and the combined adsorber effluent for three and eight adsorbers in staged parallel operation. Figure 8 calculations demonstrated that staged parallel operation maximizes bed life by managing the effluent concentration near the treatment objective. The negative side of staged parallel operation is the presence of the target compound(s) in the effluent, which may be of concern where the total mass of contaminant must be controlled. Table 3 compares the use rate and bed life values for 1, 2, 3, 5, and 10 parallel stages (based on the conditions shown in Figures 7 and 8) with the values for lead–lag operation for MIB, DOC, and SMX. (For comparison purposes, SMX performance based on Figure 1 was estimated for this scenario.)

TABLE 3

For DOC control to a treatment objective of 1.4 mg/L, ten 10-min EBCT adsorbers in parallel yielded a use rate of 0.18 lb GAC/1,000 gal, compared with 0.45 lb GAC/1,000 gal for a single adsorber and 0.30 lb GAC/1,000 gal for two 5-min EBCT adsorbers in series. For MIB control to a treatment objective of 10 ng/L, 10 adsorbers in parallel improved the use rate from 0.66 to 0.43 lb GAC/1,000 gal, compared with a single adsorber, whereas the two adsorbers in series resulted in the lowest use rate of 0.39 lb GAC/1,000 gal. As mentioned previously, series adsorbers are unlikely to be economical for MIB because of its episodic nature; however, the results here indicated that use of adsorbers in series may be favorable when the breakthrough curve is steep and the treatment objective requires a high level of removal. Lead–lag and staged parallel strategies yielded similar use rate improvements for SMX. Additional guidance on determining when series and parallel operation is economical is available elsewhere (Denning & Dvorak, 2009). Projecting performance throughout an annual cycle. Figure 9 shows an example relationship between the single-adsorber use rate and DOC0 concentration for three levels of MIB, DOC, and SMX removal. The use rates for DOC were developed from the Zachman and Summers (2010) model, the MIB performance was calculated from the breakthrough data of Kim and Summers (2006), and the SMX data were from the current study. Figure 9 reflects a 10-min EBCT and a 12 × 40 bituminous GAC. The relationships show that the use rate for MIB, DOC, and SMX increased with increasing DOC0 concentration. Also, the use rate increased with more stringent treatment objectives (higher removals, lower C/C0). Data plotted in the manner of Figure 9 can be used to determine the controlling treatment objective for a given DOC0 concentration, as illustrated with the following example. A DOC0 concentration of 3 mg/L and a DOC treatment objective of 1.5 mg/L (C/C0 = 0.5) result in a use rate of 0.61 lb GAC/1,000 gal. An influent MIB concentration of 60 ng/L and an MIB treatment objective of 10 ng/L (C/C0 = 0.17) result in an MIB use rate of

Calculated performance of adsorbers in series and staged parallel mode based on a 10-min EBCT to treatment objectives of DOC = 1.4 mg/L, MIB = 10 ng/L, and 80% SMX removal (bituminous GAC, DOC0 = 2.8 mg/L, MIB C0 = 80 ng/L)

Staged Parallel Mode (10-min EBCT Adsorbers)—n Compound

Use Rate and Bed Life

MIB

Use rate—lb/1,000 gal

DOC

Use rate—lb/1,000 gal

Bed life—days

Bed life—days SMX

Use rate—lb/1,000 gal Bed life—days

1

2

3

5

> 10

Series (Two 5-min EBCT Adsorbers)

0.66

0.57

0.53

0.49

0.43

0.39

44

51

55

59

67

37

0.45

0.31

0.26

0.23

0.18

0.30

64

93

110

126

165

49

0.39

0.29

0.25

0.24

0.21

0.22

75

101

115

123

140

65

DOC—dissolved organic carbon, EBCT—empty bed contact time, GAC—granular activated carbon, MIB—2-methylisoborneol, SMX—sulfamethoxazole


E44


Calculated adsorber performance in staged parallel mode for DOC removal

FIGURE 8

2.0 1 2

1.6

8 adsorbers in parallel, 141-day bed life

n

1.4 1.2 1.0 Single adsorber 64-day bed life

Effluent DOC Concentration—ng/L

1.8

0.8 0.6 0.4

3 adsorbers in parallel, 110-day bed life

0.2 0.0

0

50

100

150

200

250

300

Operation Time—days DOC—dissolved organic carbon, EBCT—empty bed contact time, GAC—granular activated carbon Bituminous GAC, EBCT = 10 min, DOC0 = 2.8 mg/L

Example plot of single-adsorber use rate versus DOC0 for control of MIB, DOC, and SMX

FIGURE 9

1.50

DOC C/C0 = 0.3 MIB C/C0 = 0.1

Use Rate—lb GAC/1,000 gal

1.25

MIB C/C0 = 0.2

1.00 0.80

DOC C/C0 = 0.5 MIB C/C0 = 0.5

0.75 0.61

SMX C/C0 = 0.1 DOC C/C0 = 0.7

0.50 0.38

SMX C/C0 = 0.2

0.25

0.00

SMX C/C0 = 0.5

1

2

3

4

5

DOC—mg/L Use rates for DOC were developed from the Zachman and Summers (2010) model. DOC—dissolved organic carbon, EBCT—empty bed contact time, GAC—granular activated carbon, MIB—2-methylisoborneol, SMX—sulfamethoxazole Bituminous GAC, EBCT = 10 min

0.80 lb GAC/1,000 gal by interpolating between the MIB C/C0 = 0.1 and 0.2 lines. If the control of trace organic contaminants is set at 80% SMX removal (SMX C/C0 = 0.2), the resulting use rate is 0.38 lb GAC/1,000 gal. The highest use rate—in this case, MIB—controls adsorber operation. However, MIB typically does not occur at all times of the year, and if it is not present, the DOC treatment objective would control adsorber operation under these conditions. Figure 10 highlights areas of typical operation, based on the relationships shown in Figure 9 but expressed as throughput to the treatment objective. In this case, GAC is typically effective when the influent MIB concentration is between 50 and 100 ng/L under episodic occurrences. Below that range, powdered activated carbon can be used effectively; above that range, multiple treatment processes may be needed. For the 50- to 100-ng/L influent range and a treatment objective of 10 ng/L, 80 to 90% MIB removal is needed. For DBP control, DOC effluent concentrations typically are between 1.2 and 2.0 mg/L. A DOC treatment objective of 1.2 mg/L represents waters that are in aggressive DBP formation conditions, such as high temperature, long residence time, or high bromide concentrations. An effluent DOC treatment objective of 2.0 mg/L represents an average upper range for DBP formation condition. For control of trace organic contaminants, a treatment objective of 80% SMX removal is used. The relationships shown in Figure 10 are for an EBCT of 10 min. Similar relationships were developed for an EBCT of 20 min and demonstrated that the throughput for DOC removal to a given treatment objective increased by 10 to 20%. The DOC0 concentration ranges for the controlling objective were affected by the 20-min EBCT and are shown in parentheses in the following discussion. Analysis of Figure 10 indicated that MIB controls the use rate for DOC0 concentrations up to ~ 2.8 mg/L (~ 3.3 mg/L) when it is present on a continuous basis for more than 30 days, or 4,300 BV at 10-min EBCT. For DOC0 concentrations above 4.75 mg/L (> 5.0 mg/L), DOC controls. For DOC0 concentrations between 2.8 and 4.75 mg/L (3.3 and > 5.0 mg/L), either MIB or DOC may control, depending on the MIB and DOC treatment objectives. Whenever MIB is present, 80% SMX removal (or other more strongly adsorbing trace organic contaminants) will not control the use rate. When MIB is not present, DOC controls the use rate for DOC0 concentrations greater than 3.0 mg/L (3.2 mg/L), SMX controls below DOC0 concentrations of 2.1 mg/L (2.3 mg/L), and either DOC or SMX may control for DOC0 concentrations between 2.1 and 3.0 mg/L (2.3 and 3.2 mg/L), depending on treatment objectives. As an example, a 40-mgd (design flow) conventional plant has the monthly DOC, MIB, and SMX adsorber influent concentrations and average monthly plant demand reported in the first five columns of Table 4. The following calculations are based on the data shown in Figure 9, a PFA with an EBCT of 10 min, and a DOC treatment objective of 1.6 mg/L needed to meet DBP regulations. In addition, a staged parallel operation strategy is used, and the media is a 12 × 40 bituminous GAC (rGAC of 0.5 g/cm3). The flow requirement can be met with eight 580 sq ft × 8 ft deep beds with a loading rate of 6.0 gpm/sq ft. Although fewer adsorbers may be more favorable for capital cost, the larger number of


E45


adsorbers will improve the use rate, which must be considered in the economic analysis. High loading rates are favorable for better mass transfer but must be balanced against the higher head loss. The mass of GAC in each adsorber is 72.4 tons, which yields a total GAC mass of 580 tons in service at maximum plant flow. GAC performance is estimated throughout the year on a monthly basis as shown in Table 4. For example, in June this utility experiences near-maximum plant demand and DOC0 concentration. The adsorbers will be operating near their design EBCT of 10 min, and the controlling treatment objective from Figure 9 is 1.6 mg/L DOC for DBP control and a resulting singleadsorber use rate of 0.92 lb GAC/1,000 gal and bed life of 4,530 BV. Eight adsorbers in staged parallel mode drop the use rate to 0.41 lb GAC/1,000 gal and increase the bed life to 10,180 BV. The monthly plant demand (volume of water requiring treatment) of 1,140 mil gal and this use rate yield a required total mass of 234 tons of GAC for the month. In September, a seasonal 30-day T&O episode occurs with an MIB concentration of 50 ng/L, and performance is controlled to the treatment objective of 10 ng/L. The use rate calculated from the relationships with DOC0, EBCT, and C0, and using eight adsorbers in parallel is 0.50 lb GAC/1,000 gal, and the monthly GAC use is 210 tons. However, if the T&O episode is shorter than 30 days and the GAC media lasts through the episode without exceeding the MIB treatment objective, the GAC consumed may be based on the DOC treatment objective because it determines bed replacement. In November, the plant is operating near minimum flow, and wastewater-derived contaminants (such as pharmaceuticals and

TABLE 4

personal care products) are near their peak. DBP formation and T&O episodes are not as much of a concern at this time of year, so the controlling treatment objective is 80% SMX removal. Plant flow is met with only four PFAs. The use rate estimated from the relationships with DOC0, EBCT, C0, and the operational strategy is 0.16 lb GAC/1,000 gal, yielding a monthly GAC use of only 38 tons, nearly the lowest for the year. These calculations are repeated every month, and the total required mass of GAC is summed as shown in Table 4. The total annual required mass of GAC is 1,460 tons, which is also the yearly mass requiring reactivation. The mass requiring reactivation can be spread out evenly over the year at 121 tons per month to minimize the size of the reactivation furnace. Assuming 10% GAC loss during reactivation and transport, the plant needs an additional 146 tons, which can be ordered during peak use times to minimize the amount of media storage required on site. The total annual volume of water treated by the adsorbers is 9,360 mil gal. The average annual GAC use rate of 0.31 lb GAC/1,000 gal is calculated by dividing the total annual GAC mass by the total plant production. The required mass of GAC (1,460 tons) divided by the mass of GAC in the adsorbers (580 tons) is 2.5, which is the average number of bed replacements throughout the year. The average bed life can then be calculated by dividing 365 days by the number of replacements (about 150 days). The bed life is only an average, however, because more frequent bed replacements will occur at times of the year when the use rate is higher and because replacement of beds is staggered. For the same case but considering only DOC and MIB treatment objectives, the annual GAC use rate only drops from 0.31

Example calculations of GAC use rate throughout an annual cycle for a water with an annual average DOC0 of 2.9 mg/L, an influent SMX of 50 ng/L, and two annual T&O episodes GAC Influent Concentration

Time of Year January

DOC0 mg/L

MIB ng/L

SMX ng/L

Plant Demand mgd

Number of Adsorbers in Service

Use Rate lb GAC/ 1,000 gal

Treated Volume mil gal

GAC Used tons

2.2

0

40

16

4

0.15

496

37

February

2.5

0

30

17

4

0.16

476

38

March

2.7

0

30

22

8

0.19

682

65

April

2.9

0

40

27

8

0.22

810

89

May

3.3

50

50

32

8

0.55

992

273

June

3.7

0

60

38

8

0.41

1,140

234

July

3.5

0

60

40

8

0.36

1,240

223

August

3.2

0

60

35

8

0.29

1,085

157

September

2.8

50

60

28

8

0.50

840

210

October

2.6

0

60

20

8

0.17

620

53

November

2.5

0

60

16

4

0.16

480

38

December

2.3

0

50

16

4

0.15

496

37

Annual average

2.9

50

26

9,360

1,460

0.31

Total annual DOC—dissolved organic carbon, GAC—granular activated carbon, MIB—2-methylisoborneol, SMX—sulfamethoxazole, T&O—taste and odor Shaded areas indicate controlling treatment objective.


E46


FIGURE 10 Example of single-adsorber control regions for MIB, DOC, and SMX

18 16 Throughput to TO— BV × 1,000

DOCTO = 2.0 mg/L DOCTO = 1.2 mg/L

80% SMX removal 80% MIB removal 90% MIB removal SMX

SMX or DOC

DOC

control

control

control

MIB not present

14

ACKNOWLEDGMENT

12 10 8 6 4 2

MIB

MIB

present control 0

potential cost savings and operations optimization associated with developing an operational strategy based on balancing multiple treatment objectives. It may not be practical with every project to collect the data needed to develop the use-rate-versus-DOC relationships used here. However, an understanding of the use-rate-versus-DOC relationships can lead to better design process planning studies and estimation of the GAC costs, resulting in better comparisons to alternative unit processes.

1

2

DOC or MIB

DOC

control

control

3

4

5

DOC0—mg/L BV—bed volume, DOC—dissolved organic carbon, EBCT—empty bed contact time, GAC—granular activated carbon, MIB—2-methylisoborneol, SMX—sulfamethoxazole, TO—treatment objective Bituminous GAC, EBCT = 10 min

to 0.30 lb GAC/1,000 gal. Thus, for this example, controlling for SMX adds less than 5% to the use rate. If only the DOC and SMX treatment objectives are considered, the annual use rate drops to 0.26 lb GAC/1,000 gal, the same as when only the DOC treatment objective is considered.

CONCLUSIONS This study found the GAC use rate for control of 17 representative trace organic contaminants to be lower than that for T&O or DBP control under typical conditions. This may not always be the case, however, given the wide range of compound adsorbability and treatment objectives for the compounds present in some surface waters. The influent concentration of trace organic contaminants was shown not to affect breakthrough on a normalized concentration basis, but mass concentration breakthrough to a set MCL occurred earlier at higher influent concentrations. Higher influent DOC concentrations also resulted in shorter bed life for trace organic contaminants. The effect of EBCT on breakthrough of trace organic contaminants was found to be specific to the level of treatment required. For stringent treatment objectives (> 90% removal), longer EBCTs led to slightly favorable performance. However, for less stringent treatment objectives (