Adsorption of mixtures of nutrients and heavy metals in simulated urban stormwater by different filter materials.

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Journal of Environmental Science and Health, Part A: Toxic/Hazardous Substances and Environmental Engineering Publication details, including instructions for authors and subscription information: http://www.tandfonline.com/loi/lesa20

Adsorption of mixtures of nutrients and heavy metals in simulated urban stormwater by different filter materials a

a

Krishna R. Reddy , Tao Xie & Sara Dastgheibi

a

a

Department of Civil and Materials Engineering , University of Illinois at Chicago , Chicago , Illinois , USA Published online: 10 Jan 2014.

To cite this article: Krishna R. Reddy , Tao Xie & Sara Dastgheibi (2014) Adsorption of mixtures of nutrients and heavy metals in simulated urban stormwater by different filter materials, Journal of Environmental Science and Health, Part A: Toxic/ Hazardous Substances and Environmental Engineering, 49:5, 524-539, DOI: 10.1080/10934529.2014.859030 To link to this article: http://dx.doi.org/10.1080/10934529.2014.859030

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Journal of Environmental Science and Health, Part A (2014) 49, 524–539 C Taylor & Francis Group, LLC Copyright ISSN: 1093-4529 (Print); 1532-4117 (Online) DOI: 10.1080/10934529.2014.859030

Adsorption of mixtures of nutrients and heavy metals in simulated urban stormwater by different filter materials KRISHNA R. REDDY, TAO XIE and SARA DASTGHEIBI

Downloaded by [University of Tasmania] at 04:36 01 September 2014

Department of Civil and Materials Engineering, University of Illinois at Chicago, Chicago, Illinois, USA

In recent years, several best management practices have been developed for the removal of different types of pollutants from stormwater runoff that lead to effective stormwater management. Filter materials that remove a wide range of contaminants have great potential for extensive use in filtration systems. In this study, four filter materials (calcite, zeolite, sand, and iron filings) were investigated for their adsorption and efficiency in the removal of nutrients and heavy metals when they exist individually versus when they co-exist. Laboratory batch experiments were conducted separately under individual and mixed contaminants conditions at different initial concentrations. Adsorption capacities varied under the individual and mixed contaminant conditions due to different removal mechanisms. Most filter materials showed lower removal efficiency under mixed contaminant conditions. In general, iron filings were found effective in the removal of nutrients and heavy metals simultaneously to the maximum levels. Freundlich and Langmuir isotherms were used to model the batch adsorption results and the former better fitted the experimental results. Overall, the results indicate that the filter materials used in this study have the potential to be effective media for the treatment of nutrients and heavy metals commonly found in urban stormwater runoff. Keywords: Nutrients, nitrate, phosphate, heavy metals, filter materials, adsorption, stormwater, treatment.

Introduction Urban stormwater runoff is contaminated by salts on roadways, oils and other organic liquids from parking or docking areas, fertilizers and other chemicals from parking lots that wash into the stormwater.[1–3] These contaminants can include high levels of nutrients (nitrate and phosphate),[4–7] and heavy metals (e.g., Cd, Cu and Pb),[8–11] as well as dirt and trash. If the contaminated urban stormwater is discharged directly into surface water bodies such as rivers, ponds and lakes, this can adversely impact the environment and public health.[12–14] One such example is found at lake or ocean beach locations, where the urban surface runoff can directly enter the water, negatively impacting the beaches and beachgoers.[15,16] Urban stormwater runoff is considered one of the major sources that contribute to the adverse water quality at beaches. For effective stormwater management, several best management practices have been developed for the removal of different types of pollutants and particulates from the stormwater.[1,17–20] However, these practices are not feasible Address correspondence to Krishna R. Reddy, University of Illinois at Chicago, Department of Civil and Materials Engineering, 842 West Taylor Street, Chicago, IL 60607, USA; E-mail: [email protected] Received June 12, 2013.

in urban setting and cannot handle the full range of contaminants present in urban stormwater runoff. To address this problem, a limited number of studies have focused on integrating detention systems with filtration.[21–25] The use of filtration systems alone has also received greater attention as a means to remove particulate matter and other contaminants from this runoff.[26] The use of different filter media in such systems to help promote the removal of nutrients and heavy metals is an appealing engineering approach to dealing with an increasing trend of higher concentrations of contaminants. Largescale implementation of systems using different filter media to remove contaminants has been recognized as a promising future strategy for stormwater treatment.[21–23] Such a filter system should allow adequate water flow while it removes contaminants; it requires the use of permeable materials as the filter materials. These materials should be readily available, easily replaceable and inexpensive, and the filter materials should also be proven applicable for the removal of a wide range of contaminants from urban stormwater.[27–30] The main purpose of this research is to examine the sorption capacity and model the isolated filtration kinetics of selected filter materials. This research looks at the removal of individual and mixed contaminants using the Langmuir and Freundlich isotherms. Pollutants of concern mainly include two nutrients (nitrate and total phosphorus [TP]) and six heavy metals (Cd, Cu, Pb, Ni, Cr, and Zn). The filter

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media selected for this study are calcite, zeolite, sand, and iron filings. The objectives of this study are to: (1) compare specific functionalized filter media for contaminant removal via batch experiments, (2) examine the adsorption and ion exchange capacity for contaminant removal in both individual and mixed contaminant conditions, separately, and (3) understand the isolated adsorption isotherm of each filter media in the physicochemical process. These efforts collectively demonstrate the potential applicability of permeable adsorptive media for filtration, leading to the promotion of sustainable water infrastructure systems for use in urban settings, particularly along the shores of lakes, ponds and the ocean.

Materials and methods Filter materials Based on the review of published literature on wastewater filtration systems and permeable reactive barriers for groundwater treatment as well as preliminary assessment and column screening experimental results for various materials, four promising filter materials were selected for this investigation of the removal of nutrients and heavy metals. These materials are calcite (C), zeolite (Z), sand (S), and iron filings (IF). Calcite is sedimentary limestone rock composed mostly of mineral calcite that consists of different crystal forms of calcium carbonate (CaCO3 ). The calcite used for this research was obtained from DuPage Water Conditioning (West Chicago, IL, USA). Natural zeolites are formed in basaltic lava, in specific rocks that are subjected to moderate geologic temperature and pressure. They consist of hydrous aluminosilicate minerals, and the zeolite used for this study was obtained from Bear River Zeolite Co., Inc. (Preston, ID, USA). The white Ottawa silica sand used in this study is primarily composed of silicon dioxide (SiO2 ) and was obtained from U.S. Silica Company (Ottawa, IL, USA). Iron filings are mostly a by-product of the grinding, filing or milling of finished iron products, and those used here were obtained from Connelly-GPM, Inc. (Chicago, IL, USA). All four filter materials, as received from the suppliers, were first air-dried and then washed on Sieve #200 (0.075 mm) with deionized water to remove the very fine fraction that could otherwise increase the total suspended solids in the treated stormwater. Washed materials were then dried in an oven overnight to dry completely. The washed filter materials were tested to characterize the physical, chemical and hydraulic properties based on the American Society of Testing and Materials (ASTM) standard testing procedures. Particle-size distribution of materials was determined by mechanical sieve analysis and hydrometer analysis (ASTM D422). The density of the filter materials was determined by compacting the material in a Harvard Miniature Compaction mold. Loss-on-ignition at

440◦ C was used to determine the organic content of filter materials (ASTM D2974). Hydraulic conductivity of the materials was analyzed using the constant-head permeability method (ASTM D4972). Standard methods were used to determine the pH of the filter materials, oxidation-redox potential (ORP) and electrical conductivity (EC) using a slurry mixed for 1 h that contained 10 mL of deionized water and 5 g of filter material (ASTM D1293). Scanning electron micrographs were also made to assess the structure and morphology of each filter material.

Individual and mixed contaminants Nutrient concentrations in urban stormwater runoff are highly variable and strongly depend on their spatial location. Based on the review of published literature, the typical maximum concentrations of nitrate and total phosphorus in the urban stormwater runoff are 1 mg L−1 and 0.5 mg L−1, respectively.[31] In this study, nutrient concentrations were chosen to represent several orders of magnitude lower and higher than the typical concentrations found in stormwater runoff. The four selected nitrate concentrations were 0.5, 1, 5, and 10 mg L−1, and these solutions were prepared by dissolving required amounts of sodium nitrate (NaNO3 ) in deionized water. The four selected total phosphorus concentrations were 0.25, 0.5, 2.5, and 5 mg L−1 and these solutions were prepared by dissolving required amounts of potassium phosphate (K3 PO4 ) in deionized water. Six heavy metals, specifically Zn, Cu, Pb, Cr, Ni, and Cd, were selected for this study. The concentrations of heavy metals were chosen based on the typical range of heavy metal concentrations found in urban stormwater run-off. [31–33] The typical maximum concentrations for the heavy metals and the source chemicals used to prepare the synthetic stormwater in this study were: Cd (30 mg L−1)-source of chemical (CdSO4 ); Cr (5 mg L−1)-source of chemical (K2 CrO4 ); Cu (5 mg L−1)-source of chemical (Cu(SO)4 ·5H2 O); Pb (50 mg L−1)-source of chemical (PbCl2 ); Ni (100 mg L−1)-source of chemical (NiCl2 ·6H2 O); and Zn (50 mg L−1)-source of chemical (ZnSO4 ·7H2 O). Several orders lower and higher concentration values of these typical concentrations were considered for assessing the adsorption capacity of the filter materials. In addition to the individual contaminant solutions identified here, simulated urban stormwater was prepared using a mix of nutrients and heavy metals at typical maximum concentration levels. The required amount of each source chemical was weighed and added to deionized water to yield the desired concentrations of each contaminant. To investigate adsorption under different concentration levels, three additional simulated stormwater samples were prepared with all contaminant concentrations reduced by one-half, increased by 5 times and increased by 10 times. The simulated stormwater samples were stirred for at least

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24 h on a magnetic stirrer at room temperature to ensure dissolution of the chemicals.


Batch experimental procedure Batch experiments were conducted to evaluate the contaminant removal efficiency of the filter materials. The contaminant removal depends on the amount of contaminants originally present and the exposure time. Batch experiments were performed with different initial concentrations of nutrients and heavy metals, while retaining the same exposure time of 24 h. The 24-h time period was selected to examine if equilibrium conditions are reached within this time period and to allow a test of the comparative performance of different filter materials under the identical exposure time. Batch tests were conducted with nutrients and heavy metals individually and in mixed conditions with the goal of identifying the synergistic effects of co-existent multiple contaminants on the adsorption and removal of each contaminant. These results will aid in identifying filter materials that can be used individually or in combination to remove the mixed pollutants (nutrients and heavy metals) present in urban stormwater runoff. The testing procedures consisted of placing 10 g dry mass of filter materials into a glass bottle containing 100 mL of a selected individual contaminant solution or simulated stormwater solution with known initial concentrations. The filter material and contaminant solution samples were mixed for 24 h in a mechanical tumbler at room temperature to reach equilibrium concentration. The supernatant was separated and the final equilibrium concentration of the contaminant in the solution was determined. The difference in the initial and final solution concentrations at equilibrium condition was used to determine the mass of each contaminant adsorbed per unit dry mass of filter material based on the following equation: V × C0 − C f S= M

(1)

where V = volume of contaminant or simulated stormwater solution; M = dry mass of the filter media used; C0 = initial concentration of the contaminant; and Cf = final concentration of the contaminant in the supernatant. The supernatant was also analyzed for pH, oxidation reduction potential (ORP) and electrical conductivity (EC). All batch tests were performed in duplicate to ensure repeatability. To ensure accuracy, control batch tests were conducted on samples containing 10 g of each filter material in 100 mL of deionized water (with no nutrient or heavy metal). In addition, blank batch tests were conducted with samples containing only 100 mL of individual contaminant solution alone without filter material.

Analytical methods The pH, ORP and EC of filtered samples were measured in accordance with ASTM Standard Test Methods D1293, D1498 and D1125, respectively. The pH was measured using an Orion model 720A pH meter that was calibrated using pH 7 and 10 buffers. The pH probe was inserted into the sample and the pH value was recorded after the electrode stabilized. ORP and EC of the samples were measured in the same manner by using the appropriate electrodes. Nitrate and total phosphorus concentrations in all filtered, control and blank samples were analyzed using second derivative UV spectroscopy in accordance with the American Public Health Association standard test methods (4500-NO3-B for nitrate and 4500-P for total phosphorus). The heavy metals concentrations in all control and filtered samples were analyzed using atomic absorption spectrophotometer (AAS) in accordance with the US EPA method 7130 for Cd, 7190 for Cr, 7210 for Cu, 7420 for Pb, 7520 for Ni, and 7950 for Zn. All samples were analyzed in duplicate to ensure accuracy and repeatability. All of the data obtained through these tests underwent statistical analysis of variance and fitting using SigmaPlot software (Systat Software, Inc., Chicago, IL, USA).

Adsorption isotherm modeling The adsorption isotherm modeling was performed to quantify the amount of contaminant adsorbed to the filter media.[34] The Freundlich and Langmuir models were used to analyze the adsorption data. The Freundlich isotherm model is: N S = K × Ceq

(2)

where S is the sorbed concentration (mass adsorbate/mass adsorbent), Ceq is the aqueous concentration of adsorbate (mass/volume). K and N are constants that can be determined by plotting of logCeq versus logS, which produces a straight line with an intercept of logK and slope of N. K and N are Freundlich constants related to adsorption capacity and adsorption intensity, respectively.[11] The Langmuir isotherm model is given by: S=

αβCeq 1 + αCeq

(3)

where α and β are constants that can be determined by plotting Ceq versus Ceq /S, which results in a straight line with an intercept of 1/αβ and slope of 1/β. α is the measure of affinity of adsorbate for adsorbent, β is the maximum capacity of adsorbent for the adsorbate (mass adsorbate/mass adsorbent).

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Adsorption of mixtures of nutrients and heavy metals Table 1. Properties of filter materials. Filter Material Calcite Zeolite Sand Iron Filings

Effective Particle Size, D10 (mm)

Average Particle Size, D50 (mm)

Dry Density (g/cm3)

Organic Content (%)

0.5 0.6 0.5 0.5

0.7 1.2 0.6 0.9

1.6 1.0 1.8 2.3

0.0 6.8 0.3 0.0

Results and discussion

Table 1 summarizes the properties of the filter materials, while Figure 1 shows their particle size distribution. Particle size analysis indicates that all of the materials are uniformly graded, similar to typical uniform sand, with the same effective particle size of 0.5–0.6 mm; the average particle size was the highest for zeolite (1.2 mm) and lowest for sand (0.6 mm). The particle sizes were larger in the filter materials as follows: zeolite > iron filings > calcite > sand. The filter materials were washed through Sieve #200 (0.075 mm) and then dried. As a result, no fines remained in any of the filter materials. The fines were removed so they would not increase the total suspended solids in the effluent passing out of the filter system. The zeolite had dry density of 1 g/cm3, while calcite and sand had similar dry densities of 1.6 to 1.8 g cm−3. Iron filings had very high density of 2.3 g cm−3. Organic content as measured by loss-on-ignition was 6.8% in zeolite and

Electrical Conductivity (mS/cm)

Hydraulic Conductivity K (cm/s)

9.0 7.8 8.4 5.3

−117.1 −58.0 −95.3 87.6

0.01 0.10 0.02 30.5

0.3 0.4 0.3 0.6

0.3% in sand. The other filter materials were free of any organic matter. The pH of iron filing was slightly acidic (pH 5.3), zeolite and sand were slightly alkaline (pH 7.8–8.4), while the calcite was highly alkaline (pH 9.0). EC values for sand, calcite, and zeolite were low (0.024 to 0.1 mS cm−1) as a result of the removal of the fines and was moderate for iron filings (30.5 mS cm−1). The ORP results show that reducing conditions existed in calcite, zeolite and sand, while oxidizing conditions existed in iron filings; these redox conditions may affect the electrochemical reduction of nitrate to ammonia/ammonium or nitrogen gas. The scanning electron micrographs for the filter materials shown in Figure 2 reveal the porous structure of the materials and, specifically, the high porosity of these materials. As a result of high porosity, the hydraulic conductivity of the filter materials was found to be high, ranging from 0.3 to 0.6 cm s−1. The high hydraulic conductivity property is a prerequisite for a material to be used as filter material in order to allow a high flow rate, which may exist in filter systems during storm events.

100 Calcite Zeolite Sand Iron Filings

80

Percent Finer


Filter materials properties

pH

OxidationReduction) Potential (mV)

60

40

20

0 10

1

.1 Particle Size (mm)

Fig. 1. Particle size distribution of filter materials.

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Fig. 2. Scanning electron micrographs of filter materials. (a) Calcite

100 80 60 40

Individual Mixed

120 Removal Efficiency (%)

Removal Efficiency (%)

(b) Zeolite

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120

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20

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0 N

P

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Cu

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Zn

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Contaminants (c) Sand

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Individual Mixed

100 80 60 40

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Cd

Cu

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Contaminants

Fig. 3. Removal of individual and mixed contaminants using different filter materials.

P

Cd

Cu

Pb

Contaminants

Ni

Cr

Zn

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Adsorption of mixtures of nutrients and heavy metals Contaminant removal

30

Nitrate adsorbed (μg/g)

25 20 15 10 Individual Mixed Individual-Freudlich Mixed-Freudlich

5 0 0.0

.5

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20 (b) Zeolite


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2 0 0.0

.5


3.0

35 (d) Iron Filings 30 Nitrate adsorbed (μg/g)


(a) Calcite

Figure 3 compares the percentage of removal of each contaminant when it exists individually with that of mixed contaminant condition in different filter materials. All of the batch tests were conducted for a 24-h exposure time period. For the batch tests with calcite, the removal rate ranges were: 28 to 65% for nitrate, 35 to 98% for phosphate, 88 to 96% for Cd, 86 to 99% for Cu, 98 to 99% for Pb, 0 to 14% for Ni, 15 to 60 for Cr, and 4 to 99% for Zn (Fig. 3a). Removal efficiencies of nitrate, Ni and Zn by calcite were decreased significantly under the mixed contaminants condition as compared to their individual presence. It was also shown that calcite was capable of removing more phosphate and Cr under the mixed contaminants condition. Nitrate tends to be highly soluble, so chemical precipitates are unlikely to form. The nitrate removal in calcite may be attributed to a non-specific adsorption process in which nitrate anions are electrostatically attracted to positively charged oxygen functional group sites that are present on calcite particle surfaces.[35] This might explain the reduced removal efficiency in the mixed contaminants condition, since some other negatively charged ion, such as phosphate, might compete for the binding sites. The reduced conditions present in calcite can also cause nitrate to reduce into ammonia, ammonium-nitrogen or nitrogen, and the presence of other contaminants might also affect this process. Calcite was capable of phosphate removal with a removal efficiency of 80% achieved by a dual porosity filtration system containing calcite.[36] Calcite is a carbonate mineral consisting of stable calcium carbonate (CaCO3 ). The highest pH observed in the calcite batch tests can be attributed to the presence of carbonates. Some amount of dissolved calcium may be present in the calcite batch tests. As a result, the formation of calcium phosphate chemical precipitates may possibly be responsible for the high rate of removal of phosphate. Some additional heavy metal ions may have enhanced the precipitation process and led to the higher removal efficiency found in the mixed contaminants condition. In addition, ligand exchange of phosphate is also possible where there are oxygen functional groups are present on the calcite particle surfaces. The heavy metals removal in calcite may be attributed to the combination of two effects. First, the rough surface of the limestone provides solid contact resulting in chemisorption of metal ions and, second, the presence of dissolved calcium carbonate increased the pH of the solution, which caused the metals to precipitate as metals oxide and, probably, metals carbonate. Also, a small quantity of the metal is likely retained by the ion exchange with calcium, which provides a metal carbonated compound. Various studies showed that Cd, Ni and Zn cations are strongly sorbed by the calcium carbonate surface. Competition for the binding sites might explain the reduced Ni and Zn removal efficiency in mixed contaminants condition. On the other

25 20 15 10 Individual Mixed Individual-Freundlich Mixed-Freundlich

5 0 0.0

.2

.4

.6

.8

1.0

1.2

Equilibrium concentration (mg/L)

Fig. 4. Adsorption of nitrate under individual and mixed contaminant conditions.

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(a) Calcite

18

(a) Calcite

16

Cadmium adsorbed (μg/g)

Total phosphorus adsorbed (μg/g)

20

14 12 10 8 6 Individual Mixed Individual-Freundlich Mixed-Freundlich

4 2

600 400

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0.0

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3.0

0

50 100 150 200 Equilibrium concentration (mg/L) (b) Zeolite

(b) Zeolite Cadmium adsorbed (μg/g)


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0.0

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Cadmium adsorbed (μg/g)



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40 Individual Mixed Individual-Freundlich Mixed-Freundlich

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0 0.0

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0

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50 100 150 200 Equilibrium concentration (mg/L)

250

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(d) Iron Filings

(d) Iron Filings

1800

140 Cadmium adsorbed (μg/g)


250

2500

60 Total phosphorus adsorbed (μg/g)

800

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0



1000

120 100 80 60 40


20

1600 1400 1200 1000 800 600 Individual Mixed Individual-Freundlich Mixed-Freundlich

400 200 0

0 0

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4

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Fig. 5. Adsorption of phosphorus under individual and mixed contaminant conditions.

0

20

40

60

80


Fig. 6. Adsorption of cadmium (Cd) under individual and mixed contaminant conditions.

531 600 (a) Calcite

Copper adsorbed (μg/g)


100 0 0

5


30

600 (b) Zeolite



100 0 0

2

4

6

8

10

12

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18

Equilibrium concentration (mg/L) 200 (c) Sand

180


hand, Pb adsorbs on to the calcite surface by moving into the calcium sites.[37] In addition, Cu and Cr removal was a result of adsorption and precipitation on the surface of the calcite due to the high pH values. The precipitation process might have been enhanced when Cr was mixed with other contaminants containing more negatively charged ions, such as nitrate and phosphate, leading to the increased removal efficiency of the Cr in the mixed contaminants condition. The results proved that calcite as a filter material was very effective for the removal of Cu and Pb and was moderately effective for removal of Cd and Zn. For zeolite batch tests, the removal of nitrate ranged from 35 to 75%, phosphate from 70 to 73%, Cd from 32 to 99%, Cu from 95 to 98%, Pb from 99 to 100%, Ni from 0 to 74%, Cr from 9 to 70%, and Zn from 98 to 99% (Fig. 3b). Removal efficiencies of nitrate, Cd and Ni by zeolite were decreased significantly under the mixed contaminants condition as compared to their individual presence. Conversely, zeolite was capable of removing more Cr under the mixed contaminants condition. The process responsible for the removal of nitrate and phosphate in the zeolite batch tests is the electrostatic adsorption of nitrate and phosphate anions to positively charged sites on the zeolite particle surfaces.[38,39] The decreased nitrate removal under this mixed contaminants condition is possibly due to competition between nitrate and phosphate for the same binding sites on zeolite surface. The observed removal of heavy metals by zeolite is consistent with several published studies.[40] Zeolite was reported to achieve more than 91% of Cd removal, 74% of Cu, and 67–91% of Zn, individually.[41,42] Similarly, high Cd removal efficiency was also achieved by the porous iron sorbent and its mixture with zeolite and crystal gravel.[43] The process responsible for the removal of metals in zeolite batch tests is ion exchange, precipitation and electrostatic adsorption of metals cations to negatively charged sites on zeolite particle surfaces.[11,41] The structure of zeolite consists of three-dimensional frameworks of SiO4 and AlO4 tetrahedra and the isomorphous replacement of Si4+ by Al3+ that produces a negative charge in the lattice, which is balanced with by the exchangeable cation (sodium, potassium or calcium). These cations are exchangeable with heavy metals (Cd, Cu, Pb, Ni, and Zn).[44] Competition for binding sites among these metals leads to the decreased removal efficiency when contaminants coexist. Zeolites are also weakly acidic in nature and exchangeable cations, such as sodium, have a tendency to be replaced with hydrogen (R-Na + H2 O⇔RH + Na+ + OH−) in an aqueous solution and provide alkaline condition that can then lead to metal precipitation.[45] Increased Cr removal might be explained by the enhanced metal precipitation in the mixed contaminants condition. In the sand batch tests, the removal of nitrate ranged from 25 to 70%, phosphate from 58 to 91%, Cd from 3.5 to 9%, Cu from 33 to 76%, Pb from11 to 100%, Ni from 0 to

160 140 120 100 80


60 40 20 0 0

10


60

600 (d) Iron Filings 500





100 0 0

5

10

15

20

25

30


Fig. 7. Adsorption of copper (Cu) under individual and mixed contaminant conditions.

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1400 (a) Calcite

(a) Calcite Nickel adsorbed (μg/g)

4000 Lead adsorbed (μg/g)

1200


3000

2000


1000 800 600 400

1000

200 0

0 0.0

.1

.2 .3 .4 .5 Equilibrium concentration (mg/L)

.6

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Nickel adsorbed (μg/g)

Lead adsorbed (μg/g)

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3000

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.05

.10

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(d) Iron Filings Nickel adsorbed (μg/g)


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(b) Zeolite Individual Mixed Individual-Freundlich Mixed-Freundlich

0 0.00

1000

3000

(b) Zeolite 4000


3000

2000

1000

4000

3000


1000

0

0 0

5

10

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20


Fig. 8. Adsorption of lead (Pb) under individual and mixed contaminant conditions.

0

200 400 Equilibrium concentration (mg/L)

600

Fig. 9. Adsorption of nickel (Ni) under individual and mixed contaminant conditions.

533

Chromium adsorbed (μg/g)

(a) Calcite 60


40

20

0 0



50

(b) Zeolite

120


100 80 60 40 20 0 0


50

6 (c) Sand Chromium adsorbed (μg/g)

3%, Cr from 9 to 49%, and Zn from 0 to 49%, respectively (Fig. 3c). The mechanism for the removal of both nutrients and heavy metals might be non-specific electrostatic adsorption to positively charged functional group sites on the sand particle surfaces.[46] It is interesting to find that the removal efficiency for all contaminants increased under the mixed contaminants condition compared to the efficiency found under individual presence with the exception of Zn. This might be attributed to the enhanced adsorption and precipitation processes on the sand particle surfaces since nutrients and metals were united, thus providing even more binding sites for the contaminants. The reason for the decreased Zn removal under the mixed condition is unclear and warrants further investigation. Iron filing batch tests show that the removal of nitrate ranged from 91 to 100%, phosphate from 88 to 94%, Cd from 89 to 95%, Cu from 80 to 100%, Pb from 92 to 97%, Ni from 87 to 89%, Cr from 37 to 82%, and Zn from 96 to 99%, respectively (Fig. 3d). Under the mixed contaminants condition, there was a decrease in the removal efficiency for all of the contaminants with the most significant decrease observed for Cr. Several factors and processes influence the removal of nitrate and phosphate using iron filings, which essentially consist of zero-valent iron in the form of iron oxides and hydroxides. Zero-valent iron is known to assist in the electrochemical reduction of NO3 − to NH4 +. If some iron is dissolved, iron oxides and hydroxides may form, which could produce functional group sites where nitrate and phosphate could become attached via ligand exchange.[47] Additionally, sand mixed with 5% iron filings captures an average of 88% phosphate.[48] Inclusion of cast iron in substrate promotes additional phosphate removal and enables further removal after rejuvenation.[49] Iron-phosphate precipitates may also form, removing some phosphate through this process. Competition for the functional group sites might explain the reduced removal efficiency for nitrate and phosphate when these nutrients co-exist. Zero-valent iron removes dissolved heavy metals through several mechanisms, such as reductive transformation, ion exchange and adsorption/co-precipitation processes.[50] Iron is a strong reducer and a low pH environment (pH less than 4) favors higher electrochemical reduction; this explains the reduction of dissolved metal species, especially Cr, to the zero-valent metal on the iron surface.[51] Since the amount of iron particles was constant during these tests, the reduction effect for one metal species was weakened when all of the heavy metals were present together. It might explain the decreased removal efficiency for all metals in mixed contaminants condition. This hypothesis was confirmed by another study [50] in which the most favorably adsorbed cation, Pb, occupied almost all the adsorption sites on the Fe-coated sand media (IOCS) in the adsorption zone of the IOCS column and, thus, other less favorably adsorbed cations, such as Cd and Zn, had more rapid breakthrough.

5 4 3 2 1 0 0

10


60

300 (d) Iron Filings




250 200 150 100 50 0 0


50

Fig. 10. Adsorption of chromium (Cr) under individual and mixed contaminant conditions.

534

Reddy et al. 5000 (a) Calcite

Zinc adsorbed (μg/g)

4000

3000


1000

0 0

20


120

3500

Adsorption behavior and synergistic effects

(b) Zeolite



500 0 20

40

60

80

100

120

140

160

180

Equilibrium concentration (mg/L) 3000 (c) Sand



500 0 0


250

6000 (d) Iron Filings 5000 Zinc adsorbed (μg/g)


3000

0

4000 3000 2000 1000 0 0

5

In addition, as iron corrodes in water, the protons are consumed and the concentration of hydroxide increases. Therefore, metal hydroxide and hydroxide complexes precipitate when metals react with hydroxide ions. All of the mixed heavy metals competed for hydroxide in the solution, which also led to the decreased removal efficiency, compared with the condition when only an individual metal was present. Replacing metallic atoms with iron ions in iron oxide or hydroxide is another metals removal mechanism process. A certain amount of iron ions, which are capable of exchanging with metallic atoms, was also the reason for the decreased removal efficiency in the mixed metal condition.

10

15

20

25


Fig. 11. Adsorption of zinc (Zn) under individual and mixed contaminant conditions.

The equilibrium concentration versus amount adsorbed for nitrate in four filter materials is shown in Figure 4. Results of both individual contaminant and mixed contaminant conditions are shown. These results indicate an increase in nitrate removal with an increase in the initial nitrate concentration for the mixed contaminants condition. This implies that the filter material did not reach its maximum adsorption capacity and there are still available active sites to adsorb more nitrates. On the other hand, if nitrate was added individually into the solution, the filter materials almost reached their maximum adsorption capacity with regard to the reduction of the difference between the amounts of nitrate adsorbed per gram of each medium for the last two high concentrations. This indicates that material active sites were occupied by nitrate and there is no space left to absorb more nitrates. Interestingly, all of the filter materials reached their maximum adsorption capacity. Iron filings show the maximum adsorption capacity, over the other materials. That might be attributed to the additional iron oxides provided by iron filings, which provide functional group sites for NH4 + formed from NO3 − through the electrochemical reduction effect by zero-valent iron. Adsorption of total phosphorus to the filter materials versus the equilibrium TP concentration for the four different initial concentrations is shown in Figure 5. Not all of the materials reached their adsorption capacity. At a higher concentration, more phosphate appeared to be precipitated. This trend was most significant for calcite in the mixed contaminants condition, since some additional heavy metal ions might enhance the phosphate precipitation process.[53] Results noted in Figure 6 show an increase in Cd removal with an increase in the initial Cd concentration for zeolite and iron filings, occurring when Cd was added individually. This implies that these two filter materials did not reach their maximum adsorption capacity and indicates that they still could adsorb more Cd. On the contrary, sand and calcite reached their maximum removal capacities at the initial Cd concentration of 25 mg/L and then remained almost constant as the Cd concentration increased. This shows that sand and calcite

535

2.66 1.52 0.86 1.07

0.85 0.50 0.65 0.18

N

0.81 0.90 0.95 0.79

0.82 0.97 0.89 1.00

R2

Valid for equilibrium concentrations less than 1 mg L−1.

58.48 5.97 3.95 89.08

Calcite Zeolite Sand Iron Filings

∗

9.1 12.1 10.5 30.3

K (L/Kg)


Filter Material

Freundlich Isotherm

−1.27 −0.41 0.19 −0.94

0.2 2.1 0.9 46.4

R2 K (L/Kg)

−2.63 −5.71 26.32 −60.61 0.56 0.33 0.34 0.06

0.58 12.44 1.30 0.20

(b)Mixed contaminant condition −0.78 0.19 −0.59 −1.23

1.07 0.73 0.78 0.40

N

Freundlich Isotherm

(a) Individual contaminant condition 45.9 0.25 6.30 20.3 0.99 13.43 23.8 0.93 9.68 30.8 1.00 17.58

β (μg/g)

Langmuir Isotherm α (L/mg)

Nitrate

0.25 0.00 0.04 0.79

1.00 1.00 1.00 1.00

R2

−59.88 −1.42 −323.2 49.40

−0.05 5.66 4.07 33.41

α (L/mg)

1.48 −14.97 5.16 6.75

−111.11 12.35 10.45 13.61

β (μg/g)

Langmuir Isotherm

Total Phosphorus∗

Table 2. Freundlich and Langmuir isotherm model constants for adsorption of nitrate and phosphorus in different filter materials.


0.85 0.01 0.30 0.11

0.33 0.77 0.72 0.99

R2

536 0.26 0.77 0.86 0.62

−0.219 0.099 −0.064 0.032

19.9 17.6 1.8 61.2


−0.41 0.44 0.65 0.67

28.8 3.5 −37.5 6.1 (e) Cr

0.01 0.03 0.16 0.85

0.05 −0.21 −0.70 0.46

29.6 18.8 10.7 76.7

Calcite Zeolite Sand Iron Filings Metals

0.117 0.216 0.014 0.032 (c) Pb

0.94 0.93 0.96 0.91

131 32.4 1.8 61.2


0.52 0.12 0.65 0.67

(a) Cd

0.62 0.98 0.425 1.00

Metals

0.68 0.75 0.23 0.10

0.0 0.0 0.6 0.5

1.1 1.3 2.0 178.4


0.80 0.78 0.66 0.93

−1.7 7.0 0.0 0.1 (e) Cr

2.06 −1.93 0.27 0.72

12020 50.8 11.8 393.7

0.1 0.8 0.0 0.1


0.95 0.94 0.83 1.00 (c) Pb

0.16 0.49 0.79 0.26

R2 K (L/Kg)

0.60 0.98 0.99 0.59

0.93 0.97 0.35 1.00

7.4 273.5 4.0 3140.5

2663.8 573.6 11.4 395.6

23 114 −83 1429

87 64 −1 83

1111 61 65 1429

0.42 0.80 0.97 0.84

0.54 0.02 0.99 0.31

0.98 1.00 0.95 0.85

226.8 62.8 0.2 77.1

16.7 139.0 1.0 57.8

45.8 91.5 24.3 26.7

27.7 0.31 507.1 48.5 0.61 438.3 4.2 0.99 29.6 270.3 0.95 2621.2 (b)Mixed contaminant condition

−666.7 142.9 60.2 5000.0

476.2 2000 128.2 2000

−2.06 −0.05 0.92 −0.25

−0.59 0.30 0.00 0.71

0.51 0.52 0.51 0.77

0.44 0.40 0.67 0.10

0.64 0.32 1.09 0.21

1.36 1.06 0.11 0.46

N

Freundlich Isotherm

(a)Individual contaminant condition

β (μg/g)

Langmuir Isotherm α (L/mg)

182.4 389.0 1.0 557.3

R2


N

(a) Cd

K (L/Kg)

Metals

Parameters

Freundlich Isotherm

0.74 0.05 0.33 0.09

0.55 0.88 0.00 0.84

0.99 0.99 0.89 0.85

0.98 0.97 0.85 0.64

0.66 0.98 0.72 1.00

0.85 0.93 0.28 1.00

R2

Table 3. Freundlich and Langmuir isotherm model constants for adsorption of heavy metals in different filter materials.


0.1 0.1 0.0 0.3

−0.173 −1.342 0.054 −3.506

−0.006 0.870 0.002 0.017 (f) Zn

(d)Ni

0.226 0.491 0.097 0.063

(b) Cu

(f)Zn

0.0 0.0 0.0 0.0

−1.5 −0.1 0.4 10.0 (d) Ni

(b)Cu

α (L/mg)

0.3 38.6 −8.0 32.1

1 500 −286 2000

263 385 189 417

5000 3333 2500 5000

1250 2500 −2000 5000

−500.0 −5000 17.9 500.0

β (μg/g)

Langmuir Isotherm

0.50 0.94 0.01 0.34

0.54 0.99 0.72 0.52

0.97 0.99 0.65 0.62

0.97 0.98 0.97 1.00

0.08 0.93 0.01 1.00

0.18 0.01 0.95 0.94

R2

537


Adsorption of mixtures of nutrients and heavy metals active sites were occupied by Cd completely and they had reached their saturation condition. However, it seems that none of the materials reached their maximum adsorption capacity when Cd was mixed with the other contaminants. Of this, zeolite and iron filings showed better adsorption capacity since they both provided exchanging sites for Cd due to the existence of Al3+ and iron ions on their surfaces, separately. Adsorption of Cd reduced in all media except calcite when mixed conditions existed. Adsorption of Cu to the filter materials versus equilibrium Cu concentration for the four different initial concentrations is shown in Figure 7. Sand was the only filter material that reached its maximum adsorption capacity when Cu was the only contaminant in the solution. In contrast, removal of the Cu by calcite, zeolite and iron filings increased as the initial concentration of Cu increased and there were still more available active sites to adsorb Cu. However, almost totally opposite results were found when Cu was mixed with the other contaminants in the solution. Calcite, zeolite and iron filings did not appear to be capable of adsorbing more Cu when it was found in the mixed condition. This result might be due to the fact that the mechanism for the Cu removal by the filter materials was its connection with binding sites on the media surfaces.[54] Having mixed contaminants led to competition for binding sites between Cu and the other metals. Adsorption of Pb to the filter materials versus equilibrium Pb concentration for four different initial concentrations is shown in Figure 8. Only sand reached its maximum adsorption capacity when individual Pb was added into the solution. For all other materials, Pb adsorption capacity still increased for both individual and mixed contaminants conditions. Adsorption of Pb was approximately the same or reduced under the multiple contaminants condition for all filter media except sand where a higher adsorption of Pb was found when mixed contaminants existed. Pb seemed to be more easily removed when compared with other metals.[28,36,55] Stronger Pb removal might be in accordance with the lower solubility of Pb carbonates or other Pb crystals.[56] None of the tested filter materials reached their maximum adsorption capacity for Ni as shown in Figure 9. Zeolite adsorbed Ni at a higher rate than did calcite or sand, and the adsorption rate increased with the increase of the concentration of Ni in the solution. The highest adsorption was observed for iron filings, which is mainly attributed to the iron reduction mechanism. Iron is a strong reducer, which explains the reduction of dissolved metal species to the zero-valent metal onto the iron surface. Removal of Ni by zeolite and iron filings was also confirmed in another study.[9] In general, the multiple contaminants condition resulted in a lower adsorption in all filter materials that were tested except sand. The Cr adsorption and removal was not effective with calcite, zeolite, and sand as shown by the low adsorption capacity values in Figure 10. Some studies reported that

calcite could remove more than 98% of Cr, and zeolite sand could remove Cr as well.[57,58] However, the Cr adsorption was found to be low in this study, and only iron filings were effective for electrochemical reduction, adsorption, and removal of Cr. Mixed contaminant conditions led to a higher Cr adsorption in calcite and zeolite, but lower adsorption is observed in when the filter materials were iron filings or sand. Calcite, zeolite and sand adsorbed considerable amounts of Zn and still had more available active sites to adsorb more, as seen in Figure 11. Adsorption of Zn by iron filings was remarkably more than that of the other filter materials. This is consistent with other reported studies that show calcite and zeolite as good materials for Zn removal. In general, however, mixed contaminants led to a lower removal of Zn. Adsorption isotherms models The constants of Freundlich and Langmuir isotherm models were determined based on the adsorption test results. These constants were calculated for each contaminant in each filter media under individual and mixed contaminant conditions, and the results are summarized in Tables 2 and 3 for nutrients and heavy metals, respectively. Different constants in the Freundlich and Langmuir models have different meaning for the contaminants adsorption affinity and capacity.[52] Constant N reflects the affinity of filter media for the different adsorbate. A relatively small value of α indicates that the correlations between S and Ceq for all four media are significant. The maximal capacity of adsorbent for adsorbate is also shown by β. In addition, the values of R2, when Freundlich modeling is applied, are close to one (the exception is phosphorus and Zn adsorption in mixed contaminant condition), which suggests a good fit across the data points. The maximum contaminants adsorption capacities of the contaminants are revealed in the constant β in Langmuir equation. Nitrate adsorption capacities are relatively higher than phosphorus for all media with higher values of β, which is also consistent with their removal efficiencies. As an inert media, sand showed negligible heavy metal adsorption capacity (approximately 100 µg g−1). Calcite and zeolite exhibited improved adsorption capacities for different metals. Iron filings demonstrated the best adsorption capacity for almost all metals, which is approximately 10 to 100 times the value of sand.

Conclusions This study proved that the four selected filter media (calcite, zeolite, sand, and iron filings) exhibit different removal efficiencies depending on the type of the contaminant and whether multiple contaminants co-exist.

538 Electrochemical reduction, adsorption and ion exchange processes are considered the main mechanisms of contaminant removal. Most filter materials showed lower removal efficiency when multiple contaminants exist as compared to that when the contaminant exists alone. The Freundlich and Langmuir isotherms can be used to model the batch adsorption results, but the former better fitted the experimental results. Iron filings were found to be effective filter material as compared to the other materials tested in this study for the removal of both nutrients and heavy metals simultaneously from the simulated urban stormwater runoff to the maximum levels.


Acknowledgment The assistance of Giridhar Prabukumar, Krishna Pagilla, Preethi Chinchoud, Poupak Yaghoubi, Alexander Hardaway, and Hanumanth Kulkarni is gratefully acknowledged.

Funding Financial support for this project is provided by the U.S. Environmental Protection Agency Great Lakes National Program Office (under Grant Number GL00E00526). The support for the second author is provided by the China Scholarship Council.

References [1] Deng, Z.Q.; Sun, S.W.; Gang, D.D. Modeling nitrate-nitrogen removal process in first-flush reactor for stormwater treatment. Bioproc. Biosyst. Eng. 2012, 35(6), 865–874. [2] Parker, J.K.; Mcintyre, D.; Noble, R.T. Characterizing fecal contamination in stormwater runoff in coastal North Carolina, USA. Water Res. 2010, 44(14), 4186–4194. [3] Bannerman, R.T.; Owens, D.W.; Dodds, R.B.; Hornewer, N.J. Sources of pollutants in Wisconsin stormwater. Water Sci. Technol. 1993, 28(3–5), 241–259. [4] Lapointe, B.E.; Bedford, B.J. Stormwater nutrient inputs favor growth of non-native macroalgae (Rhodophyta) on O’ahu, Hawaiian Islands. Harmful Algae 2011, 10(3), 310–318. [5] Sample, D.J.; Grizzard, T.J.; Sansalone, J.; Davis, A.P.; Roseen, R.M.; Walker, J. Assessing performance of manufactured treatment devices for the removal of phosphorus from urban stormwater. J. Environ. Manage. 2012, 113, 279–291. [6] Thompson, M.; Milbrandt, E.; Bartleson, R.; Rybak, A. Evaluation of bacteriological and nutrient concerns in nearshore waters of a barrier island community in SW Florida. Mar. Pollut. Bull. 2012, 64(7), 1425–1434. [7] Smith, D.P. Sorptive media biofiltration for inorganic nitrogen removal from storm water. J. Irrig. Drain. E.-ASCE. 2008, 134(5), 624–629. [8] Walker, D.J.; Hurl, S. The reduction of heavy metals in a stormwater wetland. Ecol. Eng. 2002, 18(4), 407–414. [9] Wium-Andersen, T.; Nielsen, A.H.; Hvitved-Jacobsen, T.; Kristensen, N.K.; Brix, H.; Arias, C.; Vollertsen, J. Sorption media for stormwater treatment—A laboratory evaluation of five low-cost media for their ability to remove metals and phosphorus from artificial stormwater. Water Environ. Res. 2012, 84(7), 605–616.

Reddy et al. [10] Birch, G.F.; Rochford, L. Stormwater metal loading to a wellmixed/stratified estuary (Sydney Estuary, Australia) and management implications. Environ. Monit. Assess. 2010, 169(1–4), 531–551. [11] Seelsaen, N.; McLaughlan, R.; Moore, S.; Ball, J.E.; Stuetz, R.M. Pollutant removal efficiency of alternative filtration media in stormwater treatment. Water Sci. Technol. 2006, 54(6–7), 299–305. [12] Bratieres, K.; Schang, C.; Deletic, A.; McCarthy, D.T. Performance of envissTM stormwater filters: results of a laboratory trial. Water Sci. Technol. 2012, 66(4), 719–727. [13] Hatt, B.E.; Fletcher, T.D.; Deletic, A. Hydraulic and pollutant removal performance of fine media stormwater filtration systems. Environ. Sci. Technol. 2008, 42(7), 2535–2541. [14] Hubbard, R.K.; Sheridan, J.M. Nitrate movement to groundwater in the southeastern coastal-plain. J. Soil Water Conserv. 1989, 44(1), 20–27. [15] Loehr, R.C. Characteristics and comparative magnitude of nonpoint sources. J. Water Poll. Contr. Feder. 1974, 46(8), 1849–1872. [16] Mclellan, S.L.; Hollis, E.J.; Depas, M.M.; Van Dyke, M.; Harris, J.; Scopel, C.O. Distribution and fate of Escherichia coli in Lake Michigan following contamination with urban stormwater and combined sewer overflows. J. Great Lakes Res. 2007, 33(3), 566–580. [17] Hogan, D.M.; Walbridge, M.R. Best management practices for nutrient and sediment retention in urban stormwater runoff. J. Environ. Qual. 2007, 36(2), 386–395. [18] Kumar, S.; Kamra, S.K.; Yadav, R.K.; Sharma, J.P. Evaluation of sand-based stormwater filtration system for groundwater recharge wells. Curr. Sci. India 2012, 103(4), 395–404. [19] Lloyd, S. D.; Wong, T.; Porter, B. The planning and construction of an urban stormwater management scheme. Water Sci. Technol. 2002, 45(7), 1–10. [20] Lynch, J.A.; Corbett, E.S. Evaluation of best management-practices for controlling nonpoint pollution from silvicultural operations. Water Resour. Bull. 1990, 26(1), 41–52. [21] Singhal, N.; Elefsiniotis, T.; Weeraratne, N.; Johnson, A. Sediment retention by alternative filtration media configurations in stormwater treatment. Water Air Soil Poll. 2008, 187(1–4), 173–180. [22] Siriwardene, N.R.; Deletic, A.; Fletcher, T.D. Modeling of sediment transport through stormwater gravel filters over their lifespan. Environ. Sci. Technol. 2007, 41(23), 8099–8103. [23] Vezzaro, L.; Eriksson, E.; Ledin, A.; Mikkelsen, P.S. Quantification of uncertainty in modelled partitioning and removal of heavy metals (Cu, Zn) in a stormwater retention pond and a biofilter. Water Res. 2012, 46(20SI), 6891–6903. [24] Hatt, B.E.; Siriwardene, N.; Deletic, A.; Fletcher, T.D. Filter media for stormwater treatment and recycling: the influence of hydraulic properties of flow on pollutant removal. Water Sci. Technol. 2006, 54(6–7), 263–271. [25] Feng, W.; Hatt, B.E.; McCarthy, D.T.; Fletcher, T.D.; Deletic, A. Biofilters for stormwater harvesting: Understanding the treatment performance of key metals that pose a risk for water use. Environ. Sci. Technol. 2012, 46(9), 5100–5108. [26] Bratieres, K.; Fletcher, T.D.; Deletic, A.; Zinger, Y. Nutrient and sediment removal by stormwater biofilters: A large-scale design optimisation study. Water Res. 2008, 42(14), 3930–3940. [27] Dierberg, F.E.; Debusk, T.A. Particulate phosphorus transformations in south Florida stormwater treatment areas used for Everglades protection. Ecol. Eng. 2008, 34(2), 100–15. [28] Birch, G.F.; Fazeli, M.S.; Niatthai, C. Efficiency of an infiltration basin in removing contaminants from urban stormwater. Environ. Monit. Assess. 2005, 101(1–3), 23–38. [29] Hipp, J.A.; Ogunseitan, O.; Lejano, R.; Smith, C.S. Optimization of stormwater filtration at the urban/watershed interface. Environ. Sci. Technol. 2006, 40(15), 4794–4801. [30] Beecham, S.; Pezzaniti, D.; Kandasamy, J. Stormwater treatment using permeable pavements. Proc. Institut. Civil Eng.-Water Manage. 2012, 165(3), 161–170.


Adsorption of mixtures of nutrients and heavy metals [31] Lee, J.H.; Bang, K.W. Characterization of urban stormwater runoff. Water Res. 2000, 34(6), 1773–1780. [32] Davis, A.P.; Shokouhian, M.; Ni, S.B. Loading estimates of lead, copper, cadmium, and zinc in urban runoff from specific sources. Chemosphere 2001, 44(5), 997–1009. [33] Walker, W.J.; Mcnutt, R.P.; Maslanka, C.K. The potential contribution of urban runoff to surface sediments of the Passaic River: Sources and chemical characteristics. Chemosphere 1999, 38(2), 363–377. [34] Hossain, F.; Chang, N.B.; Wanielista, M. Modeling kinetics and isotherms of functionalized filter media for nutrient removal from stormwater dry ponds. Environ. Progr. Sustain. Ener. 2010, 29(3), 319–333. [35] Ferree, M.A.; Shannon, R.D. Evaluation of a second derivative UV/Visible spectroscopy technique for nitrate and total nitrogen analysis of wastewater samples. Water Res. 2001, 35(1), 327–332. [36] Jensen, M.B.; Cederkvist, K.; Bjerager, P.E.; Holm, P.E. Dual porosity filtration for treatment of stormwater runoff: first proof of concept from Copenhagen pilot plant. Water Sci. Technol. 2011, 64(7), 1547–1557. [37] Davis, A.P.; Burns, M. Evaluation of lead concentration in runoff from painted structures. Water Res. 1999, 33(13), 2949–2958. [38] Chang, N.B.; Wanielista, M.P.; Henderson, D. Temperature effects on functionalized filter media for nutrient removal in stormwater treatment. Environ. Progr. Sustain. Ener. 2011, 30(3), 309–317. [39] Karwacki, L.; Kox, M.; De Winter, D., et al. Morphologydependent zeolite intergrowth structures leading to distinct internal and outer-surface molecular diffusion barriers. Nat. Mater. 2009, 8(12), 959–965. [40] Ma, J.; Lenhart, J.H.; Tracy, K. Orthophosphate adsorption equilibrium and breakthrough on filtration media for storm-water runoff treatment. J. Irrig. Drain. E.-ASCE 2011, 137(4), 244–250. [41] Pitcher, S.K.; Slade, R.; Ward, N.I. Heavy metal removal from motorway stormwater using zeolites. Sci. Total Environ. 2004, 334(SI), 161–166. [42] Kim, L.H.; Kang, H.M.; Bae, W. Treatment of particulates and metals from highway stormwater runoff using zeolite filtration. Desal. Water Treat. 2010, 19(1–3), 97–104. [43] Wu, P.; Zhou, Y.S. Simultaneous removal of coexistent heavy metals from simulated urban stormwater using four sorbents: A porous iron sorbent and its mixtures with zeolite and crystal gravel. J. Hazard. Mater. 2009, 168(2–3), 674–680. [44] Erdem, E.; Karapinar, N.; Donat, R. The removal of heavy metal cations by natural zeolites. J. Coll. Interf. Sci. 2004, 280(2), 309– 314.

539 [45] Gallagher, D.L.; Johnston, K.M.; Dietrich, A.M. Fate and transport of copper-based crop protectants in plasticulture runoff and the impact of sedimentation as a best management practice. Water Res. 2001, 35(12), 2984–2994. [46] Arias, C.A.; Del Bubba, M.; Brix, H. Phosphorus removal by sands for use as media in subsurface flow constructed reed beds. Water Res. 2001, 35(5), 1159–1168. [47] Westerhoff, P.; James, J. Nitrate removal in zero-valent iron packed columns. Water Res. 2003, 37(8), 1818–1830. [48] Erickson, A.J.; Gulliver, J.S.; Weiss, P.T. Capturing phosphates with iron enhanced sand filtration. Water Res. 2012, 46(9), 3032–3042. [49] Rosenquist, S.E.; Hession, W.C.; Eick, M.J.; Vaughan, D.H. Field application of a renewable constructed wetland substrate for phosphorus removal. J. Am. Water Resour. As. 2011, 47(4), 800–812. [50] Liu, D.F.; Sansalone, J.J.; Cartledge, F.K. Comparison of sorptive filter media for treatment of metals in runoff. J. Environ. Eng.—ASCE. 2005, 131(8), 1178–1186. [51] Ranysivek, R.; Jekel, M.R. Removal of dissolved metals by zerovalent iron (ZVI): Kinetics, equilibria, processes and implications for stormwater runoff treatment (Vol 39, Pg 4153, 2005). Water Res. 2006, 40(3), 640. [52] Ho, Y.S.; Huang, C.T.; Huang, H.W. Equilibrium sorption isotherm for metal ions on tree fern. Proc. Biochem. 2002, 37(12), 1421–1430. [53] Cucarella, V.; Renman, G. Phosphorus sorption capacity of filter materials used for on-site wastewater treatment determined in batch experiments—A comparative study. J. Environ. Qual. 2009, 38(2), 381–392. [54] Aziz, H.A.; Othman, N.; Yusuff, M.S.; Basri, D.R.; Ashaari, F.A; Adlan, M.N.; Othman, F., Johari, M.; Perwira, M. Removal of copper from water using limestone filtration technique - Determination of mechanism of removal. Environ. Int. 2001, 26(5–6SI), 395–399. [55] Rios, C.A.; Williams, C.D.; Roberts, C.L. Removal of heavy metals from acid mine drainage (AMD) using coal fly ash, natural clinker and synthetic zeolites. J. Hazard. Mater. 2008, 156(1–3), 23–35. [56] Lassabatere, L.; Spadini, L.; Delolme, C.; Fevrier, L.; GalvezCloutier, R.; Winiarski, T. Concomitant Zn-Cd and Pb retention in a carbonated fluvio-glacial deposit under both static and dynamic conditions. Chemosphere 2007, 69(9), 1499–1508. [57] Cederkvist, K.; Holm, P.E.; Jensen, M.B. Full-scale removal of arsenate and chromate from water using a limestone and ochreous sludge mixture as a low-cost sorbent material. Water Environ. Res. 2010, 82(5), 401–408. [58] Genc-Fuhrman, H.; Mikkelsen, P. S.; Ledin, A. Simultaneous removal of As, Cd, Cr, Cu, Ni and Zn from stormwater: Experimental comparison of 11 different sorbents. Water Res. 2007, 41(3), 591–602.

Treatment of suspended solids and heavy metals from urban stormwater runoff by a tree box filter.

Comparison of filter media materials for heavy metal removal from urban stormwater runoff using biofiltration systems.

Heavy metal contamination of vegetables irrigated by urban stormwater: a matter of time?

Contamination, toxicity and speciation of heavy metals in an industrialized urban river: Implications for the dispersal of heavy metals.

Titanium Pyrophosphate for Removal of Trivalent Heavy Metals and Actinides Simulated by Retention of Europium.

Evaluation of single and multilayered reactive zones for heavy metals removal from stormwater.

Potential of biological materials for removing heavy metals from wastewater.

talc nanocomposite and optimization study using response surface methodology.

Removal of E. coli from urban stormwater using antimicrobial-modified filter media.

Pollution of intensively managed greenhouse soils by nutrients and heavy metals in the Yellow River Irrigation Region, Northwest China.

Distribution of PAHs and trace metals in urban stormwater sediments: combination of density fractionation, mineralogy and microanalysis.

A field study on phytoremediation of dredged sediment contaminated by heavy metals and nutrients: the impacts of sediment aeration.

Toxicity assessment due to sub-chronic exposure to individual and mixtures of four toxic heavy metals.

Bioremoval of heavy metals by bacterial biomass.

Removal Efficiency of Faecal Indicator Organisms, Nutrients and Heavy Metals from a Peri-Urban Wastewater Treatment Plant in Thohoyandou, Limpopo Province, South Africa.

Transport of heavy metals by the kidney.

Levels of heavy metals in liver and kidney of dogs from urban environment.

Characterizing heavy metal build-up on urban road surfaces: implication for stormwater reuse.

Competitive Adsorption and Oxidation Behavior of Heavy Metals on nZVI Coated with TEOS.

Coupled electrokinetics-adsorption technique for simultaneous removal of heavy metals and organics from saline-sodic soil.

Thermodynamic parameters for adsorption equilibrium of heavy metals and dyes from wastewaters.

Heavy metals in particulate and colloidal matter from atmospheric deposition of urban Guangzhou, South China.

Adsorption of insulin by infusion materials.

Competitive adsorption and selectivity sequence of heavy metals by chicken bone-derived biochar: Batch and column experiment.