1. Introduction

Data from monitoring studies have routinely confirmed the occurrence of thousands of organic micropollutants in surface water resources around the world [1–3]. The main targets of these monitoring studies have been pharmaceuticals [4], personal care products [5], illicit drugs [6], pesticides [7], industrial chemicals [8], or other anthropogenic chemicals [9] that have known or putative toxic effects on aquatic ecosystems or exposed human populations [10–15]. The potential sources of these chemicals are varied, with much attention focused on sewage treatment plant (STP)

outfalls [5], combined sewer overflows [16], industrial discharges [17], stormwater outfalls [18], and diffuse runoff from agricultural and urban landscapes [2], though many other potential sources have not yet been fully explored.

new AC [24]. New adsorbents that address these deficiencies of ACs will lead to more efficient removal of micropollutants during water and wastewater treatment. We have recently discovered a promising alternative adsorbent that removes organic molecules from water with unprecedented speed and high capacity and can be regenerated by washing with benign solvents at room temperature [25]. This material is the first mesoporous, high-surface area polymer containing β-cyclodex-

Water Quality in the Twenty-First Century: New Tools for the Characterization…

DOI: http://dx.doi.org/10.5772/intechopen.90099

trin (β-CD), which is a macrocycle comprised of seven glucose molecules (Figure 1). β-CD's cuplike shape provides a distinct hydrophobic interior cavity, which forms host-guest complexes with thousands of organic molecules. This property suggests that CDs would make ideal adsorbents for water purification, though CDs must first be rendered insoluble by incorporating them into a polymer network. Several CD-containing polymers have been previously described, though none have had the required porosity or surface area to perform as well as AC as an adsorbent [26–29]. Our new β-CD polymer combines the molecular recognition

Map of the Hudson River Estuary and select tributary watersheds. The sampling locations are represented with

Figure 2.

29

circles and site ID.

Improved understanding of the sources of micropollutants that are present in surface water resources is essential for risk assessment and for developing mitigation strategies. Recently, long-term monitoring data characterizing micropollutant occurrence at the watershed scale has been used to identify the relative contributions of various sources within particular watersheds. Mass balance and multivariate analyses revealed three distinct sources of micropollutants in the Minnesota River including upstream diffuse runoff, mixed pathways, and sewage outfalls [19]. High-resolution temporal sampling was used to identify an industrial source that was emitting pollutants to a river in Germany at randomly spaced temporal intervals [17]. Long-term longitudinal sampling along the Rhine River was used to identify several previously unknown sources of micropollutants, particularly from tributaries and industrial sources [3]. In each of these examples, the identification of micropollutant sources was predicated on two major features of the studies. First, each of these studies examined a diverse set of micropollutants; the selected micropollutants contained chemicals that might be expected to originate from a variety of sources including agriculture, wastewater treatment plants, or industrial discharges. Second, each of these studies employed high-frequency sampling within the watersheds, investigating either a large number of samples from a single location or a large number of samples distributed spatially throughout the watershed. Data has shown that evaluating the spatial and temporal variability of micropollutant occurrence can lead to key insights on sources of micropollutants.

In addition to micropollutant monitoring, there is a clear need for solutions to remove micropollutants during drinking water production. Adsorption processes are widely employed to remove organic chemicals from water and wastewater. Activated carbons (ACs) are the most widespread adsorbents used to remove micropollutants; their efficacy derives primarily from their high surface areas, nanostructured pores, and hydrophobicity [20]. However, AC adsorption is relatively slow [21], performs poorly for many polar and semipolar micropollutants [22], and can be fouled by natural organic matter (NOM) [23]. Further, activation and regeneration of AC are energy-intensive and slowly degrade its performance relative to the

#### Figure 1.

Schematic of the β-CD polymer. β-CD is a macrocycle of glucose (blue) and is cross-linked with tetrafluoroterephthalonitrile (red) to generate the first mesoporous, high-surface area β-CD polymer.

#### Water Quality in the Twenty-First Century: New Tools for the Characterization… DOI: http://dx.doi.org/10.5772/intechopen.90099

new AC [24]. New adsorbents that address these deficiencies of ACs will lead to more efficient removal of micropollutants during water and wastewater treatment.

We have recently discovered a promising alternative adsorbent that removes organic molecules from water with unprecedented speed and high capacity and can be regenerated by washing with benign solvents at room temperature [25]. This material is the first mesoporous, high-surface area polymer containing β-cyclodextrin (β-CD), which is a macrocycle comprised of seven glucose molecules (Figure 1). β-CD's cuplike shape provides a distinct hydrophobic interior cavity, which forms host-guest complexes with thousands of organic molecules. This property suggests that CDs would make ideal adsorbents for water purification, though CDs must first be rendered insoluble by incorporating them into a polymer network. Several CD-containing polymers have been previously described, though none have had the required porosity or surface area to perform as well as AC as an adsorbent [26–29]. Our new β-CD polymer combines the molecular recognition

Map of the Hudson River Estuary and select tributary watersheds. The sampling locations are represented with circles and site ID.

outfalls [5], combined sewer overflows [16], industrial discharges [17], stormwater outfalls [18], and diffuse runoff from agricultural and urban landscapes [2], though

Improved understanding of the sources of micropollutants that are present in surface water resources is essential for risk assessment and for developing mitigation strategies. Recently, long-term monitoring data characterizing micropollutant occurrence at the watershed scale has been used to identify the relative contributions of various sources within particular watersheds. Mass balance and multivariate analyses revealed three distinct sources of micropollutants in the Minnesota River including upstream diffuse runoff, mixed pathways, and sewage outfalls [19]. High-resolution temporal sampling was used to identify an industrial source that was emitting pollutants to a river in Germany at randomly spaced temporal intervals [17]. Long-term longitudinal sampling along the Rhine River was used to identify several previously unknown sources of micropollutants, particularly from tributaries and industrial sources [3]. In each of these examples, the identification of micropollutant sources was predicated on two major features of the studies. First, each of these studies examined a diverse set of micropollutants; the selected micropollutants contained chemicals that might be expected to originate from a variety of sources including agriculture, wastewater treatment plants, or industrial discharges. Second, each of these studies employed high-frequency sampling within the watersheds, investigating either a large number of samples from a single location or a large number of samples distributed spatially throughout the watershed. Data has shown that evaluating the spatial and temporal variability of micropollutant occurrence can lead to key insights on sources of micropollutants. In addition to micropollutant monitoring, there is a clear need for solutions to remove micropollutants during drinking water production. Adsorption processes are widely employed to remove organic chemicals from water and wastewater. Acti-

many other potential sources have not yet been fully explored.

Technology, Science and Culture - A Global Vision, Volume II

vated carbons (ACs) are the most widespread adsorbents used to remove

Schematic of the β-CD polymer. β-CD is a macrocycle of glucose (blue) and is cross-linked with tetrafluoroterephthalonitrile (red) to generate the first mesoporous, high-surface area β-CD polymer.

Figure 1.

28

micropollutants; their efficacy derives primarily from their high surface areas, nanostructured pores, and hydrophobicity [20]. However, AC adsorption is relatively slow [21], performs poorly for many polar and semipolar micropollutants [22], and can be fouled by natural organic matter (NOM) [23]. Further, activation and regeneration of AC are energy-intensive and slowly degrade its performance relative to the properties of CDs with the porosity and high surface area of ACs to yield an adsorbent with superior adsorption kinetics and an adsorption capacity on the order of AC. However, we have not yet tested our β-CD polymer against diverse groups of micropollutants and under environmentally relevant conditions.

2.2 Micropollutant adsorption

DOI: http://dx.doi.org/10.5772/intechopen.90099

2.3 Batch experiments

adsorbent dose of 10 mg L<sup>1</sup>

2.4 Flow-through experiments

25 mL min<sup>1</sup>

mix (1 μg L<sup>1</sup>

3. Results

31

of each micropollutant.

3.1 Micropollutant monitoring

concentration of each adsorbate of 1 μg L<sup>1</sup>

P-CDP was synthesized as previously described [25], and the CCAC is commercially available (AquaCarb 1230C, Westates Carbon, Siemens, Roseville, MN). To increase the similarity in particle size between the P-CDP and CCAC, the CCAC was pulverized with a mortar and pestle until >95% (mass) passed a 74 μm sieve (200 US mesh). The P-CDP and the pulverized CCAC were dried under a vacuum in a

desiccator for 1 week and stored in a refrigerator at 4°C. We selected 90

Water Quality in the Twenty-First Century: New Tools for the Characterization…

concentration of 10 mg L<sup>1</sup> using nanopure water.

micropollutants based on their environmental relevance and previous reports of their adsorption onto AC. Stock solutions of each compound were prepared at a concentration of 1 g L<sup>1</sup> using 100% HPLC-grade methanol. The stock solutions were used to prepare an analytical mix containing all 90 micropollutants at a

Batch experiments were performed in 125 mL glass Erlenmeyer flasks with magnetic stir bars on a multi-position stirrer (VWR) with a stirring rate of 400 revolutions per minute (rpm) at 23°C. Batch experiments were performed at an

umes at predetermined sampling times (0, 0.05, 0.17, 0.5, 1, 5, 10, 30, 60, 90, 120 min) and filtered through a 0.22 μm PVDF syringe filter (Restek). Control experiments to account for other micropollutant losses were performed under the same conditions with no addition of adsorbent. All samples were analyzed by means

Flow-through experiments were performed with a 10 mL Luer Lock glass syringe and Restek 0.22 μm PVDF syringe filters at 23°C with a constant flow rate of

water or nanopure water amended with humic acid (HA) as a surrogate for NOM and NaCl as a surrogate for inorganic matrix constituents. Syringe filters were loaded with adsorbent by passing 1 mL of the adsorbent suspension through the inorganic syringe filter to form a thin layer of 1 mg of adsorbent on the filter surface. Following the loading of the filters with adsorbent, 8 mL of the analytical

pressure over 20 s. Control experiments were performed in the same way with no adsorbent on the filter to account for losses through the filter. The filtrates were analyzed by means of HPLC-MS/MS to determine the aqueous phase concentration

To complement the micropollutant data analysis and to enable a more comprehensive study of micropollutant sources, we first collected geospatial data for the Hudson River Estuary catchment area. We used ArcGIS and publically available data to develop maps of the Hudson River Estuary catchment area that include

. Flow-through experiments were performed with either nanopure

) was pushed through the adsorbent-loaded filter with constant

of HPLC-MS/MS to determine the aqueous phase concentration of each micropollutant as a function of contact time with the adsorbent.

. The micropollutants were spiked to generate an initial

. Samples were collected in 8 mL vol-

The objectives of this research were twofold. First, we aimed to assess the relative contributions of various sources to micropollutant occurrence in the Hudson River Estuary, a major freshwater system in New York. We collected grab samples at 17 sites along the Hudson River Estuary between the Mohawk River and the Tappan Zee Bridge. Samples were collected in May, July, and September of 2016. A map of the 17 sampling sites is provided in Figure 2 along with a delineation of the watersheds for each of the tributaries. The sites include three sewage treatment plant outfalls, five sites at the mouth of tributaries of the Hudson River, seven sites inside the tributaries of the Hudson River, and two control sites in the midchannel of the Hudson River at the northern and southern ends of the study boundaries. The samples were analyzed using a target screening analysis to quantify the occurrence of up to 200 micropollutants commonly identified in surface waters around the world. Second, we aimed to evaluate the performance of porous β-CD polymers (P-CDPs) as adsorbents of micropollutants in aquatic matrices. Adsorption kinetics and micropollutant removal were measured in batch and flow-through experiments for a mixture of 90 micropollutants at environmentally relevant concentrations (1 μg L<sup>1</sup> ) and in the presence and absence of natural organic matter (NOM). The performance was benchmarked against a coconut shell activated carbon (CCAC). Data reveal slower and nonselective uptake on CCAC and faster and selective uptake on P-CDP. The presence of NOM had a negative effect on the adsorption of micropollutants to CCAC but had almost no effect on adsorption of micropollutants to P-CDP. These data highlight advantages of P-CDP adsorbents relevant to micropollutant removal during water and wastewater treatment.
