Identification and quantification of titanium nanoparticles in surface water: A case study in Lake Taihu, China

Identification and quantification of titanium nanoparticles in surface water: A case study in Lake Taihu, China

Journal of Hazardous Materials 382 (2020) 121045 Contents lists available at ScienceDirect Journal of Hazardous Materials journal homepage: www.else...

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Journal of Hazardous Materials 382 (2020) 121045

Contents lists available at ScienceDirect

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Identification and quantification of titanium nanoparticles in surface water: A case study in Lake Taihu, China Shengmin Wua,b,c, Shenghu Zhangb, Yang Gongb, Lili Shib, Bingsheng Zhoua,



State Key Laboratory of Freshwater Ecology and Biotechnology, Institute of Hydrobiology, Chinese Academy of Science, Wuhan 430072, China Nanjing Institute of Environmental Sciences, Ministry of Ecology and Environment, Nanjing 210042, China c University of Chinese Academy of Sciences, Beijing 100049, China b




Editor: D. Aga

The accurate detection and quantification of nanoparticles (NPs) in aquatic environments are essential for toxicological and ecological risk assessment. Herein, we used single particle inductively coupled mass spectroscopy (SP-ICP-MS) to quantify titanium nanoparticles (Ti-NPs) in the extraction fractions of surface waters, and transmission electron microscopy coupled with an energy dispersive X-ray spectrometer (TEM-EDS) to specifically identify the nanoparticles. By using gold-NPs as reference standard, this approach achieved a Ti-NPs size detection limit in water of 25 nm with a particle number concentration limit of 102 particles/ml. We measured Ti-NPs concentrations in surface waters from Lake Taihu, China. The results revealed that the particles concentration was 2.78 × 105 particles/ml with the mean size of 67 nm in October 2016, and the particles concentration of 2.28 × 105 particles/ml with the mean size of 65 nm in April 2018, respectively. Based on TEMEDS observation, various shapes of Ti-NPs were further identified, including regular cubes, long rods and flaky. We further measured the total organic carbon (TOC), and found that there was a positive correlation between TiNPs and TOC. This method enabled accurate detection and quantification of Ti-NPs concentration in environmental surface waters, which could be hugely useful for environmental risk assessment in aquatic systems.

Keywords: Titanium nanoparticles Identification and quantification Surface water Lake Taihu

Corresponding author. E-mail address: [email protected] (B. Zhou). Received 28 March 2019; Received in revised form 7 August 2019; Accepted 19 August 2019 Available online 20 August 2019 0304-3894/ © 2019 Elsevier B.V. All rights reserved.

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1. Introduction

spectrometry (SP-ICP-MS) has been developed for the detection of nanoparticles in natural systems at environmentally relevant (ng/L˜μg/L) concentrations (Chang et al., 2017; Dan et al., 2015b; Donovan et al., 2016). This approach can rapidly characterize a large number of particles, particle size and size distribution, the particle number concentration in a sample, and the element mass concentration of particulate species (Laborda et al., 2016; Pace et al., 2011; Peters et al., 2014; Montaño et al., 2016; Vidmar et al., 2017). Indeed, SP-ICP-MS has been successfully applied to determine and analyze silver and gold nanoparticles in environmental water (Yang et al., 2016; Merrifield et al., 2017), as well as gold nanoparticles in plants (Dan et al., 2015b). The objectives of the present study were (i) to develop and validate an approach for quantifying the size and form of Ti-NPs in water; (ii) measure the environmental concentration of Ti-NPs; and finally (iii) to examine the NP distribution and TOC relationship in Taihu Lake surface water in China.

Due to unique or novel properties, the usages of nanoparticles (NPs) are of more widely applications and increasing importance. As a consequence, a large number of nanoparticles might entry into the environment (Kaegi et al., 2008; Shi et al., 2016; Tou et al., 2017). This in turn can have adverse effects on aquatic organisms, which represents a significant ecological risk. However, nanoparticle risk assessment is hampered due to detection method limitations, and the dimensions of the nanoscale materials in natural environments remain undefined (Coll et al., 2016). Indeed, most toxic studies in terms of nanoparticles are based on nominal concentrations or predicted environment concentrations. Furthermore, it is well-known that the same kind of composition nanoparticles with different sizes and forms, for instance, differ from toxicity (Hund-Rinke and Simon, 2006). Therefore, it is necessary to develop methods that reliably quantify and characterize nanoparticles in real-environment systems. Titanium nanoparticles (Ti-NPs) are one of the most widely used nanoscale materials. Indeed, Ti-NPs, especially titanium dioxide nanoparticles (TiO2-NPs) can be found in a variety of consumer products such as sunscreen and toothpaste, industrial products like paints, lacquers, and papers, and are applied in photocatalytic processes such as water treatment (Haider et al., 2019; Calle et al., 2018). However, few studies have been conducted that have detected and quantified TiO2NPs in an aquatic environment. A limited number of studies have used probabilistic material flow modeling to predict environmental concentrations of TiO2-NPs, in surface water; for example, previous studies reported that the predicted environmental concentration of TiO2-NPs in surface water was 0.7–16 μg/L in Switzerland in 2008 (Mueller and Nowack, 2008; Gottschalk et al., 2009). Recently, a few studies have been conducted to detect and quantify Ti-NPs in lake waters, effluent from waste water plants (Shi et al., 2016; Gondikas et al., 2014; Reed et al., 2017), showing that the average total TiO2 concentration was less than 1.7 μg/L in Old Danube Recreational lake (Gondikas et al., 2014), and 4 μg/L in a creek in Golden Colorado, USA (Reed et al., 2017), while concentrations from waste water treatment effluents reached 27–43 μg/L (Shi et al., 2016). Although limited literature examples have reported on the number of TiO2-NPs per milliliter in facade runoffs (Kaegi et al., 2008), sludge materials (Tou et al., 2017), sunscreens (Dan et al., 2015a), and construction and demolition landfills (Kaegi et al., 2017), very few studies have reported concentrations of Ti-NPs in aquatic environment. Additionally, Ti-NPs can aggregate or remain in suspension in natural waters, which is significantly influenced by natural organic matter and is related to the total organic carbon (TOC) value (Liu et al., 2011; Ottofuelling et al., 2011). Considering these complex and interactive processes, it is difficult to predict Ti-NPs concentrations accurately in real environments through forecasting models (Gondikas et al., 2014). Thus, the present study was designed to develop a sound analytical approach to quantifying the concentration of Ti-NPs in surface waters, with particle size characterization, to better understand their environmental fate. To date, most methods developed for the detection of NPs and the quantification of particle size and mass are commonly achieved through a combination of direct techniques. For NP size characterization, microscopy- and spectroscopy-based techniques such as scanning electron microscopy (SEM), transmission electron microscopy (TEM), atomic force microscope (AFM), and dynamic light scattering (DLS) are typically employed (Badireddy et al., 2012; Chang et al., 2017; Khlebtsov and Khlebtsov, 2011). To this end, these techniques have been generally applied to study the size, shape, and morphology of individual particles, but are not capable of quantifying the mass concentration of NPs. While techniques such as inductively coupled plasma mass spectrometry (ICP-MS) and UV–vis spectrophotometer can be applied to quantify the mass concentration, they offer little information in terms of size distribution (Zhou et al., 2017). In recent years, single-particle inductively coupled plasma mass

2. Material and methods 2.1. Study area Lake Taihu, one of the five largest freshwater lakes in China, is surrounded by industrial developed cities of Wuxi, Suzhou, Changzhou and Huzhou. It is a typical shallow lake, with a mean depth of 1.9 m and an area of 2338 km2 (Qin et al., 2007). The lake is the main source of drinking water for 27 million residents in the surrounding area and also receives wastewater from the surrounding area. With the rise of the Lake Taihu region in China's economic status, public attention on pollution in the lake has been gradually increasing. Specifically, since the vicious algal bloom in 2007, the water environment in Lake Taihu has received extensive public attention and has become a typical ecosystem for studying migration and transformation of various organic pollutants (Guo, 2007). With this in mind, it is of significant interest and importance to study the occurrence, distribution, and risk assessment of Ti-NPs in Lake Taihu. In the present study, twenty-five water samples from Lake Taihu were used to evaluate the mass concentration of TiNPs in its surface waters (Fig. S1). The latitude and longitude of each sampling point are shown in Table S1. 2.2. Sample collections A total of 25 water samples (1–2 m, one sample per point) were taken from 25 sites (W1–W25) in Lake Taihu and two major tributaries northwest of the lake (coordinate points in google earth, Fig. S1) in October 2016 and April 2018. Three replicate samples were collected in each sampling site. Temperature, pH, and dissolved oxygen (DO) in the samples were analyzed on sites (Table S1 shows the quality parameters of the water samples). Water samples were preserved in 5 L brown glass containers bottles that had been pre-cleaned and transported to the laboratory. Before chemical analysis, all samples were subjected to ultrasonication to facilitate NP dispersion (Branson® Ultrasonic Bath) to attempt to minimize agglomerates (Taurozzi et al., 2011; Mahbubul et al., 2015), and then filtered immediately through 1.0 μm glass fiber filters (Membrane Solution LLC., America). Then the samples were for measurement of Ti-NPs and also TOC concentration. 2.3. Preparation of working solutions The quantification of NPs by SP-ICP-MS is based on the following hypotheses: All of the particles are spherical. Due to the fact that Ti-NPs do not assume a standard spherical form, a standard curve was constructed with Au-NPs, which assume a spherical form (Pace et al., 2012). In this study, the particle number concentration of the standard stock Au-NP suspensions purchased from PerkinElmer (Waltham, USA) was calculated from the known gold concentration and from the nanoparticle diameter, which were 48.17, 51.86, 50.21, and 49.39 μg/ml 2

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Merck KGaA) digestion method for Ti as described by Standard Method 3030 G (EPA, 1998). The digested samples were analyzed by PerkinElmer NexlON®2000 Inductively Coupled Plasma Mass Spectrometry. Titanium Standard for ICP (1000 mg/L, 2% nitric acid containing trace amounts of HF) obtained from Sigma-Aldrich, were used for calibration and diluted in a 2% nitric acid solution to attain a series concentration ranging from 1 μg/L to 100 μg/L.

Au and 30, 60, 80, and 100 nm, respectively. For calibration, standards were prepared by serial dilution of the standard stock suspensions with Milli-Q water to a final nominal concentration of approximately 1 × 105 particles/ml. Spiked samples were prepared by adding standard 100 nm TiO2 (anatase) obtained from Hangzhou Wanjing New Material Co., Ltd. (Hangzhou, China) into Milli-Q water at a concentration of 10 μg/L, to verify the accuracy of the concentration and size of TiO2-NPs. All standards and spiked samples were sonicated for 2 h under sonication (Branson® Ultrasonic Batch) prior to analysis to attempt to minimize agglomerates, and then immediately analyzed by SP-ICP-MS.

2.7. TEM-EDS characterization TEM examination was conducted using a Tecnai G2 microscope (FEI Co., Ltd., Tokyo, Japan), coupled with an energy dispersive X-ray spectrometer (EDS, Noran System 7, Thermo Scientific, USA), which were applied to characterize the morphology, composition, and crystal structures of Ti-NPs. The samples were prepared as follows: Firstly, SPM (suspended particulate Matter) samples were collected from water samples through filtration. During filtration, lake water was pumped into a pressurefiltration membrane using a high pressure peristaltic pump. SPM were collected by filtration through cellulose acetate membranes with 0.22 μm pore size (Membrane Solution LLC., America). Secondly, the SPM and ethanol were added into small beakers, respectively, and ultrasound for 30 min. Then the homogeneous mixture solutions were placed onto a carbon-coated copper grid using glass capillary and allowed to rest for 2 min. The excess liquid was removed by filter paper. Finally, the sample was placed onto sample table for TEM observation after about 15 min, the ethanol would evaporate completely.

2.4. SP-ICP-MS determination A PerkinElmer NexlON®2000 ICP-MS equipped with a NexION nano application module was used for NP analysis. The SP-ICP-MS was operated at 1400 W, with a sample uptake rate set to 0.30 ml/min, and reading rate of 100,000 readings/s. The dwell time was set to 50 μs and the scan time to 100 s per measurement. The mass fraction of TiO2-NPs and Au-NPs was set at 60% and 100%, respectively. This method can be applied for obtaining valuable information regarding the size distribution, particle concentration, and mass concentration of NPs in aqueous environments. The size detection limit of this method is largely affected by dwell time; a shorter dwell time can enhance the signal-to-noise ratio and improve the sensitivity of particle size detection (Dan et al., 2015b; Hineman and Stephan, 2014). When a sufficiently large particle is atomized in the SP-ICP-MS plasma, a “pluse” above background is detected for the analysis. The number of pluse events for a given sample can then be related to the particle concentration, and the intensity of the signal is proportional to the particle mass related to its size (Dan et al., 2015b). Data analysis was conducted automatically by plotting raw pulse intensity data against collection time. Background counts were subtracted from the pulse intensity, and Ti-NPs was sized using a density of 4.54 g/cm3 (density of Ti).

2.8. TOC measurement Non-purgeable organic carbon (NPOC) was determined with an Analytikjena multi N/C 3100 TOC analyzer (Germany). The TOC concentration was quantified according to the following conditions. NPOCPurge time: 200 s; maximum integration time: 200 s; Furnace temperature: 800 °C; Injection volume: 200 μl; Catalyst: CeO2. Each lake water sample was acidified before TOC analysis (Loosli et al., 2015). Three replicate experiments were performed (n = 3). Quantification was achieved using a calibration curve against a TOC standard. TOC standard solutions were prepared by dissolving an appropriate amount of potassium acid phthalate into deionised water (Han et al., 2014).

2.5. Data processing and calculation From the linear regression equation obtained from signal intensity, the mass of a spherical Ti-NPs particle can be calculated using Eq. (1) (Dan et al., 2015a; Pace et al., 2011):

4 D MNP = ρ× ( ) × π× ( NP )3 3 2

2.9. Statistical analysis


To define the relationship between the concentration of Ti-NPs and TOC, total Ti and Ti-NPs, the linear regression model based on the least squares method was adopted. P < 0.05 was considered statistically significant with independent sample t-test All data were analyzed by SPSS software (SPSS 19.0).

Where DNP = single particle diameter (nm), MNP = the mass of a spherical particle (ng), and ρ =4.54 g/cm3 (density of Ti). The measured individual particle sizes were used to produce a size distribution graph. If Ti-NPs were assumed to be TiO2-NPs, the mass fractions of the TiO2-NPs and Au-NPs were 60% and 100%, respectively. In this study, the transport efficiency value ηn was determined for each analysis AuNPs based on the method described in Pace et al. (2011). To calculate the mass concentration, the mass of a single particle multiplied with the number of particles per unit volume:


3. Results and discussion 3.1. Validation results of Ti-NPs in water


3.1.1. Specificity At the mass number 46Ti = 45.9526, 47Ti = 46.9518 and 48 Ti = 47.9480, a series of spiked samples with nominal concentrations at 1.00, 5.00, 10.0, 20.0, 50.0, 100 μg/L were measured under the ICPMS conditions mentioned above. The spiked samples were prepared by adding appropriate amount of Ti-element stock solutions to tap water. Based on the test results, the linear regression equation: y = 727.89x +1894.9 with linearity of r2 = 0.92 for 46Ti element, y = 704.94x +2133.7 with linearity of r2 = 0.99 for 47Ti element, and y = 7304.6x +34222 with linearity of r2 = 0.80 for 48Ti element, respectively. The results showed that 47Ti was the most suitable isotope for detection with the highest correlation coefficient, which indicated the minimal interference (Fig. S2).

where CM = the mass concentration (ng/L), MNP = the mass of the single particle (ng), and NNP = the nanoparticle number concentration (particles/L). 2.6. ICP-MS analysis Because TiO2 has very low solubility, Ti in water samples is expected to occur solely in solid phases, not in ionic forms. For the quantification method used in this investigation, these solid phases must be transformed into ionic forms by acid digestion. Water samples were acid digested using the hydrofluoric acid (40% HF purchased from Sigma-Aldrich) and nitric acid (HNO3 65% Chromatographic grade, 3

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Fig. 1. (A) Signal map of blank sample (Milli-Q water); (B) Signal map of 100 nm TiO2-NPs with concentration of 10.0 μg/L; (C) Calibration Curve for the intensity versus the mass of the nanoparticle for Au-NPs; (D) Normal distribution histogram of 60 nm Au-NPs standards, with data came from SP-ICP-MS plotted as a function of frequency for each size fraction.

3.1.3. Precision The nominal 100 nm size of Au-NPs standards at 1.00 μg/L (approximately 1 × 105 particles/ml) were analysed for 6 times, and continuously for 3 days. The results were shown in Table S2. The results showed that the RSD of repeatability on the particle size, particle number and mass concentration of these determinations were not more than 10% for each day. In addition, the intermediate precision suggested that the developed method gave repeatable results for three consecutive days.

In addition, to characterize the Ti background of the system and reagents, a blank solution without any TiO2 (Milli-Q water) was analyzed, with the resulting signal is shown in Fig. 1 A. There were a few signal spikes, most of which below 2 counts, which indicated the cleanliness of the system. The signals for the spiked sample of 10 μg/L TiO2-NPs with 100 nm is shown in Fig. 1B, which obviously more signal spikes than the blank solution.

3.1.2. Calibration curve Fig. 1C showed the plot of the mean intensity versus the mass of the different sizes (30, 60, 80, 100 nm) of Au-NPs. Fig. 1D showed the normal distribution histogram of 60 nm Au-NPs standards. Based on the test result, a linear regression equation was obtained: y =13.681x512.74, with good linearity of r2 = 0.87, where y represents intensity (counts), and x is diameters of Au-NPs (nm). The results showed that linearity for nanoparticles sizes range from 30 nm to 100 nm is good.

3.1.4. Accuracy The spiked samples were prepared by adding 100 nm TiO2 into Milli-Q water at a concentration of 10.0 μg/L. The results showed that the average recovery rate was 70.4%, ranging from 68.1% to 73.5%, the relative standard deviation was 3.98%.


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Fig. 2. (A) Measured total Ti and Ti-NPs concentrations (μg/L) of water samples from Lake Taihu in October 2016. (B) Measured total Ti and Ti-NPs concentrations (μg/L) of water samples from Lake Taihu in April 2018.

TiO2-NPs was 27˜29 nm, which was similar to the results of this study. The particle number detection limit (LODN) was related to number of reading counts, which affect the frequency of events (Pace et al., 2012; Laborda et al., 2011). By measuring series dilution of TiO2-NPs solution, the 102 Particles/ml was always obtained in the lowest dilution to produce a defined size distribution, which indicated that the LODN for the developed method was approximately 102 Particles/ml. In this study, the reading per second was 100,000, which is significantly more than that in most literatures (1000˜10,000 readings per second). Therefore, the result was one order of magnitude less than previous studies reported the particle concentration limits (103 Particles/ml), which indicated the TiO2-NPs can be detected in trace concentration (Pace et al., 2012; Laborda et al., 2011).

3.1.5. Limit of detection (LOD) The detection limits of SP-ICP-MS (LOD) include particle size detection limit (LODs) and particle number detection limit (LODN), respectively. The limit of detection (LODs) can be determined by finding the value three standard deviations above the average background intensity and calculating the corresponding particle size for that intensity. In the present study, with ultrapure water and dwell times of 50 μs, the background signal of the TiO2-NPs was typically near blank levels (mean of 1 count). This allowed pulses as small as 3 counts to be distinguished above the background signal. Under the same condition, a pulse of 3 counts was measured to a particle diameter of 25 nm. The LODs depends on the instrument sensitivity as well as the signal-tonoise ratio, which is largely affected by dwell time, and a shorter dwell time can enhance the signal-to-noise ratio (Dan et al., 2015a; Pace et al., 2012). The dwell time of 50 μs was set in the study, which is significantly shorter than that in most publications (usually several milliseconds), and size limit measured is significantly smaller than that reported in these literatures (Laborda et al., 2011; Lee et al., 2014). And with the dwell time of 100 μs, Dan et al. (2015b) detected size limit of

3.2. Total Ti, and Ti-NPs concentration in Lake Taihu The measured concentration of total Ti, and Ti-NPs in water samples taken from 25 sampling sites in October 2016 and April 2018, respectively are shown in Fig. 2A, and B, Table S3 and Table S4. In October 5

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Fig. 2. (continued)

2016, the mean concentration for total Ti was 14.5 μg/L, ranging from 2.71 to 53.2 μg/L, and the mean concentration for Ti-NPs was 1.52 μg/ L, ranging from 0.09 to 10.2 μg/L, respectively. In April 2018, the mean concentration was 5.54 μg/L, ranging from 1.46 to 23.0 μg/L for total Ti, and 0.73 μg/L, ranging from 0.11 to 4.16 μg/L for the Ti-NPs, respectively. By using SP-ICP/MS, for the first time, we were able to measure the concentrations of Ti-NPs in Lake Taihu. However, this method is based on the generation of discrete pulses of ions that arise from single particles sequentially introduced into the ICP-MS. Hence, SP-ICP-MS can only be applied to the determination of metallic nanoparticles, but not applicable for determination of non-metallic nanoparticles, such as carbonaceous nanoparticles. It was found that the concentration decreased significantly from 2016 to 2018 without considering natural and anthropogenic Ti-NPs. The reason may be that in recent years, the provinces and cities around the Lake Taihu Basin have promoted the adjustment and upgrading of industrial structure, and implemented wastewater discharge standards of key industries higher than other parts of China. Since 2007, the bottom sediments have been dredged gradually and the Yangtze River

has been introduced into Lake Taihu, which has promoted the improvement of water quality (Zhu et al., 2016). Additionally, distributions of these Ti-NPs are dramatically different in all sampling sites which could be contributed to the point sources nearby. With comparison, the concentrations of total Ti and Ti-NPs in W3 were obviously higher than those measured from the other sampling sites, which may be caused by two reasons. On the one hand, the sampling location of W3 was near the interchange of Lake Taihu as well as its tributaries (canal across Lake Taihu and Lake Gehu). The rapid flow of water and disturbance urged the nanoparticles entering from lake-bottom sediment into aqueous phases (Tou et al., 2017). On the other hand, the Ti-NPs produced in paint, chemical fiber and cosmetics went into the environment from the industries near the canal. For example, titanium oxides were widely used as photocatalyst and important ingredient in sunscreens to block UV light, and there is high chance that they flow into the lake and increase the concentration of the Ti-NPs in water.


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Fig. 3. The particle size distribution of some water samples was plotted as a frequency plot with a Gaussian fit size fraction using data from SP-ICP-MS. (A) W15 in 2016 (B) W20 in 2016 (C) W8 in 2016 (D) W1 in 2016 (E) W2 in 2018 (F)W19 in 2018.

the nanoparticles (< 30 nm) and submicron particles (> 300 nm) contributed a low percentage to the frequency. Kaegi et al. reported that between roughly 20 and 300 nm dimension Ti-NPs were present in the runoff from urban applications into aquatic their study environment (Kaegi et al., 2008). Gondikas et al. reported a number concentration of approximately Ti-NPs 106 particles/ml, assuming 60 nm diameter in the Old Danube Lake (Gondikas et al., 2014). These results indicate that TiNPs particle sizes vary regionally. NP particle sizes are regulated by TiNPs stability, which is in turn related to agglomeration (Ottofuelling et al., 2011; Zhang et al., 2008; Wang et al., 2018). Some literatures have reported that the mechanism of particle agglomeration is dependent on a number of factors including surface potential, interaction forces, various contaminants and so on (Mylon and Chen, 2004;

3.3. Particle analysis in Lake Taihu Some water sample particle size distribution from SP-ICP-MS analysis plotted as a diagram of frequency for size fraction is detailed in Fig. 3. The mean particle concentration of Ti-NPs was determined to be 2.78 × 105 particles/ml, ranging from 1.48 × 104 to 1.08 × 106 particles/ml, the mean size of Ti-NPs in the water samples was about 67 nm in October 2016. And the mean particle concentration of Ti-NPs was 2.28 × 105 particles/ml, ranging from 1.66 × 104 to 1.20 × 106 particles/ml, the mean size of Ti-NPs in the water samples was about 65 nm in April 2018, respectively. From Table S3 and Table S4, it is obvious that the particles (30 ˜ 100 nm), more than 95% abundance, were the dominant fraction, while 7

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Fig. 4. Characterization of Ti-NPs in SPM from the sampling sites. Representative TEM images showing detected Ti-NPs with different shapes. A, B, C represent anatase TiO2-NPs, D represents rutile TiO2-NPs, and E indicates that it may be barium titanate nanoparticle. A1, B1, C1, D1, E1 are the corresponding energy spectrums showing that the particles observed are Ti-NPs. A2, B2, C2, D2 are the corresponding SAED images for A, B, C and D.


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Fig. 4. (continued)

products with a diameter generally between 100 and a few hundreds of nanometers (Kaegi et al., 2017). On the other hand, the titaniumbarium bound nanoparticles were observed in SPM samples with irregular shapes and rough surfaces (Fig. 4E), which maybe natural Ti-NPs formed intricate assemblages with minerals and organic compounds, or artificial nanoparticles (barium titanate nanoparticle) that have been mineralized for a long time (Real et al., 2018).

Guzman et al., 2006). The majority of particles in an aqueous suspension carry a surface charge, rendering the particles unstable and prone to agglomeration. Thus, inter-adsorption of nanoparticles results from electrostatic, Van der Waals, and hydrogen bond forceshile interactions between nanoparticles and contaminants or sediment grains can be ascribed to hydrophobicity, ionic strength, hydration forces, and ligand exchange, and so forth (Ottofuelling et al., 2011; Wang et al., 2018; Fang et al., 2013). Therefore, the determination of nanoparticle size should account for the factors that cause agglomeration in water. Some micrographs of Ti-NPs from SPM samples in Lake Taihu characterized by TEM-EDS were shown in Fig. 4. Rutile and anatase, a pair of typical TiO2, can be identified in SAED (selected area electron diffraction). Fig. 4 shows examples of anatase (Fig. 4A–C) and rutile (Fig. 4D), with different sizes, ranging from 50 to 300 nm. The observed d-spacings of 0.325 and 0.353 nm in different crystals matched the (110) lattice plane of rutile and (101) lattice plane of anatase, respectively. It is possible to help to discriminate natural vs. anthropogenic TiNPs with the morphology of the Ti-NPs particles observed by TEM-EDS. Some particles are diverse in shapes, with regular cubes (Fig. 4A), long rods (Fig. 4B, C) and flaky shape (Fig. 4D), which are typical of TiO2 pigments and raw materials (rutile and anatase) used in consumer

3.4. Relationship between TOC and Ti-NPs, total Ti and Ti-NPs As shown in Fig. 5, we observed that higher concentrations of TiNPs were measured in three sampling sites (W3, W15, and W21), which aligned with higher TOC content in the same sites. In the present study, the correlation between Ti-NPs and TOC were investigated. A positive correlation (Fig. 6A, r2 = 0.51, p < 0.05; B, r2 = 0.59, p < 0.05) between Ti-NPs and TOC from the water samples in October 2016 and April 2018, respectively, was observed, suggesting that the spatial distribution of Ti-NPs maybe influenced by the TOC content in the water samples. Ti-NPs are highly insoluble and have a large surface area to volume ratio, suggesting that they are likely to interact with other substances in water. TOC is an important indicator of NOM, which is ubiquitous in organic matter and likely to have a significant 9

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Fig. 6. Correlations between the measured concentrations of Ti-NPs and TOC in the sampling sites from Lake Taihu (A) in October 2016 and (B) in April 2018. The linear regression analysis was used to determine the relationships between concentrations of Ti-NPs and TOC. A P < 0.05 was considered statistical significant.

Fig. 5. Measured total Ti, Ti-NPs and TOC concentrations of water samples from Lake Taihu. The value is the mean of three replicates. (A) Sampling in October 2016. (B) Sampling in April 2018.

impact upon the surface potential of nanoparticles (Loosli et al., 2015; Mylon and Chen, 2004). It has been reported that the aqueous stability of nanoparticles in the presence of NOM tends to impart a negative surface charge to suspended particulates and that this increased surface charge results in an increase in the stability of nanoparticle suspensions (Liu et al., 2011; Mylon and Chen, 2004). Overall, nanoparticles have a large surface area to mass ratio and favorable potential NOM adsorption, which increases nanoparticle hydrophilicity, steric hindrance, and electrostatic repulsion between the particles, thereby suppressing agglomeration of the particles and promoting suspension in water (Wang et al., 2018; Fan et al., 2016). NOM influences Ti-NPs aggregation or dispersion and determines the magnitude of toxicity and the mechanism of their environmental and biological effects. Thus, it is necessary to consider the role of NOM in the study of Ti-NPs toxicity on aquatic organisms. Furthermore, a positive linear-correlation between total Ti and Ti-NPs from the water samples in October 2016 (Fig. S3A, r2 = 0.80, p < 0.05) and April 2018 (Fig. S3B, r2 = 0.87, p < 0.05), was also observed, respectively, indicating that Ti-NPs constitute a significant proportion of the total Ti.

useful for quantitative risk assessment of Ti-NPs and toxicological research to aquatic organisms in real-scenario environments. Moreover, the results incite that different environmental stressors may influence the fate of Ti-NPs in real environmental scenarios, particularly NOM, hence, it is also very important to consider the interaction between TiNPs and TOC, because the interactions between them may modify the toxicity of Ti-NPs to aquatic organisms. Furthermore, many types of organic toxicants have been detected in surface waters and the sediments in the lake, and interactions between Ti-NPs and other chemical stressors may also occur. Thus, future investigations will focus on evaluating the interactions between Ti-NPs and other toxicants as well as potential toxic effects on aquatic organisms. Further work on the sediment accumulation of Ti-NPs should also be performed to understand the environmental behavior and fate of this abundant NP.

4. Conclusions


In the present study, we used SP-ICP-MS coupled with TEM-EDS to determine concentrations as well different shapes of Ti-containing nanoparticles in Lake Taihu, China. Furthermore, we found a positive correlation between Ti-NPs and total organic carbon (TOC). For the first time, we were able to systematically analyze the concentration of TiNPs in surface lake waters in China. The measured concentrations are

This work was supported by the National Natural Science Foundation of China [grant number 21577168], and the State Key Laboratory of Freshwater Ecology and Biotechnology [grant number 2019FBZ03]. We would like to thank Wenhui Guo for her assistance with ICP-MS analysis. We also thank Min Zhu at PerkinElmer for his help with SP-ICP-MS analysis.

Declaration of Competing Interest The authors declare that they have no known competing financial interests.


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Appendix A. Supplementary data

J. Anal. Atom. Spectrom. 26, 1362–1371. Lee, S., Bi, X., Reed, R.B., Ranville, J.F., Herckes, P., Westerhoff, P., 2014. Nanoparticle size detection limits by single particle ICP-MS for 40 elements. Environ. Sci. Technol. 48, 10291–10300. Liu, W., Zhou, Q.F., Liu, J.Y., Fu, J.J., Liu, S.J., Jiang, G.B., 2011. Environmental and biological influences on the stability of silver nanoparticles. Chin. Sci. Bull. 56, 2009–2015. Loosli, F., Vitirazi, L., Berret, J.F., Stoll, S., 2015. Towards a better understanding on agglomeration mechanisms and thermodynamic properties of TiO2 nanoparticles interacting with natural organic matter. Water Res. 80, 139–148. Mahbubul, I.M., Saidur, R., Amalina, M.A., 2015. Effective ultrasonication process for better colloidal dispersion of nanofluid. Ultrason. Sonochem. 26, 361–369. Merrifield, R.C., Stephan, C., Lead, J., 2017. Determining the concentration dependent transformations of Ag nanoparticles in complex media: using SP-ICP-MS and [email protected] core-shell nanoparticles as tracers. Environ. Sci. Technol. 51, 3206–3213. Montaño, M.D., Olesik, J.W., Barber, A.G., Challis, K., Ranville, J.F., 2016. Single particle ICP-MS: advances toward routine analysis of nanomaterials. Anal. Bioanal. Chem. 408, 5047–5053. Mueller, N.C., Nowack, B., 2008. Exposure modeling of engineered nanoparticles in the environment. Environ. Sci. Technol. 42, 4447–4453. Mylon, S.E., Chen, K.L., 2004. Elimelech, M. influence of natural organic matter and ionic composition on the kinetics and structure of hematite colloid aggregation: implications to iron depletion in estuaries. Lanqmuir 20, 9000–9006. Ottofuelling, S., Von der Kammer, F., Hofmann, T., 2011. Commercial titanium dioxide nanoparticles in both natural and synthetic water: comprehensive multidimensional testing and prediction of aggregation behavior. Environ. Sci. Technol. 45, 10045–10052. Pace, H.E., Rogers, N.J., Jarolimek, C., Coleman, V.A., Higgins, C.P., Ranville, J.F., 2011. Determining transport efficiency for the purpose of counting and sizing nanoparticles via single particle inductively coupled plasma mass spectrometry. Anal. Chem. 83, 9361–9369. Pace, H.E., Rogers, N., Jarolimek, C., Coleman, V.A., Gray, E.P., Higgins, C.P., Ranville, J.F., 2012. Single particle inductively coupled plasma-mass spectrometry: a performance evaluation and method comparison in the determination of nanoparticle size. Environ. Sci. Technol. 46, 12272–12280. Peters, R.J., Rivera, Z.H., Van Bemmel, G., Marvin, H.J., Weigel, S., Bouwmeester, H., 2014. Development and validation of single particle ICP-MS for sizing and quantitative determination of nano-silver in chicken meat. Anal. Bioanal. Chem. 406, 3875–3885. Qin, B., Xu, P., Wu, Q., Luo, L., Zhang, Y., 2007. Environmental issues of Lake Taihu, China. Hydrobiologia 581, 3–14. Real, A., Castillo-Michel, H., Kaegi, R., Larue, C., Nolf, W., Reyes-Herrera, J., Tucoulou, R., Findling, N., Salas-Colera, E., Sarret, G., 2018. Searching for relevant criteria to distinguish natural vs. anthropogenic TiO2 nanoparticles in soils. Environ. Sci. Nano 5, 2853–2863. Reed, R.B., Martin, D.P., Bednar, A.J., Montano, M.D., Westerhoff, P., Ranville, J.F., 2017. Multi-day diurnal measurements of Ti-containing nanoparticle and organic sunscreen chemical release during recreational use of a natural surface water. Environ. Sci. Nano 4, 69–77. Shi, X., Li, Z., Chen, W., Li, Q., Xia, J., Chen, M., Zhu, L., Alvarez, P., 2016. Fate of TiO2 nanoparticles entering sewage treatment plants and bioaccumulation in fish in the receiving streams. NanoImpact 3–4, 96–103. Taurozzi, J.S., Hackley, V.A., Wiesner, M.R., 2011. Ultrasonic dispersion of nanoparticles for environmental, health and safety assessment–issues and recommendations. Nanotoxicology 5, 711–729. Tou, F., Yang, Y., Feng, J., Niu, Z., Pan, H., Qin, Y., Guo, X., Meng, X., Liu, M., Hochella, M.F., 2017. Environmental risk implications of metals in sludges from waste water treatment plants: the discovery of vast stores of metal containing nanoparticles. Environ. Sci. Technol. 51, 4831–4840. Vidmar, J., Milačič, R., Ščančar, J., 2017. Sizing and simultaneous quantification of nanoscale titaniumdioxide and a dissolved titanium form by single particle inductively coupled plasma mass spectrometry. Microchem. J. 132, 391–400. Wang, X., Adeleye, A.S., Wang, H., Zhang, M., Liu, M., Wang, Y., Li, Y., Keller, A.A., 2018. Interactions between polybrominated diphenyl ethers (PBDEs) and Ti O2 nanoparticle in artificial and natural waters. Water Res. 146, 98–108. Yang, Y., Long, C.L., Li, H.P., Wang, Q., Yang, Z.G., 2016. Analysis of silver and gold nanoparticles in environmental water using single particle-inductively coupled plasma-mass spectrometry. Sci. Total Environ. 563–564, 996–1007. Zhang, Y., Chen, Y., Westerhoff, P., Hristovski, K., Crittenden, J.C., 2008. Stability of commercial metal oxide nanoparticles in water. Water Res. 42, 2204–2212. Zhou, X.X., Liu, J.F., Jiang, G.B., 2017. Elemental mass size distribution for characterization, quantification and identification of trace nanoparticles in serum and environmental waters. Environ. Sci. Technol. 51, 3892–3901. Zhu, W., Zhou, X., Cai, J., 2016. Lesson from comprehensive management of water environment in Taihu Basin. J. Water Resources Protect. 32, 149–152.

Supplementary material related to this article can be found, in the online version, at doi: References Badireddy, A.R., Wiesner, M.R., Liu, J., 2012. Detection, characterization, and abundance of engineered nanoparticles in complex waters by hyperspectral imagery with enhanced Darkfield microscopy. Environ. Sci. Technol. 46, 10081–10088. Calle, I.D.L., Menta, M., Klein, M., Maxit, B., Seby, F., 2018. Towards routine analysis of TiO2 (nano-) particle size in consumer products- Evaluation of potential techniques. Spectrochim. Acta Part B 147, 28–42. Chang, Y.J., Shih, Y.H., Su, C.H., Ho, H.C., 2017. Comparison of three analytical methods to measure the size of silver nanoparticles in real environmental water and wastewater samples. J. Hazard. Mater. 322, 95–104. Coll, C., Notter, D., Gottschalk, F., Sun, T., Som, C., Nowack, B., 2016. Probabilistic environmental risk assessment of five nanomaterials (nano-TiO2, nano-Ag, nano-ZnO, CNT, and fullerences). Nanotoxicology 10, 436–444. Dan, Y.B., Shi, H.L., Stephan, C., Liang, X.H., 2015a. Rapid analysis of titanium dioxide nanoparticles in sunscreens using single particle inductively coupled plasma–mass spectrometry. Microchem. J. 122, 119–126. Dan, Y.B., Zhang, W.L., Xue, R.M., Ma, X.M., Stephan, C., Shi, H.L., 2015b. Characterization of gold nanoparticles uptake by tomato plants using enzymatic extraction followed by single particle inductively coupled plasma-mass spectrometry analysis. Environ. Sci. Technol. 49, 3007–3014. Donovan, A.R., Adams, C.D., Ma, Y., Stephan, C., Eichholz, T., Shi, H., 2016. Single particle ICP-MS characterization of titanium dioxide, silver, and gold nanoparticles during drinking water treatment. Chemosphere 144, 148–153. EPA, 1998. Nitric Acid-Sulfuric Acid Digestion. EPA Method 3030G. EPA, Washington, DC. Fan, W., Peng, R., Li, X., Ren, J., Liu, T., Wang, X., 2016. Effect of titanium dioxide nanoparticles on copper toxicity to Daphnia magna in water: role of organic matter. Water Res. 105, 129–137. Fang, J., Xu, M.J., Wang, D.J., Wen, B., Han, J.Y., 2013. Modeling the transport of TiO2 nanoparticle aggregates in saturated and unsaturated granular med: effects of ionic strength and pH. Water Res. 47, 1399–1408. Gondikas, A.P., Von der kammer, F., Reed, R.B., Wagner, S., Ranville, J.F., Hofmann, T., 2014. Release of TiO2 nanoparticles from sunscreens into surface waters: a one-year survey at the old Danube Recreational Lake. Environ. Sci. Technol. 48, 5415–5422. Gottschalk, F., Sonderer, T., Scholz, R.W., Nowack, B., 2009. Modeled environmental concentrations of engineered nanomaterials (TiO2, ZnO, Ag, CNT, fullerenes) for different regions. Environ. Sci. Technol. 43, 9216–9222. Guo, L., 2007. Doing battle with the green monster of Lake Taihu. Science 317 (5842), 1166. Guzman, K.A., Finneqan, M.P., Banfield, J.F., 2006. Influence of surface potential on aggregation and transport of titania nanoparticles. Environ. Sci. Technol. 40, 7688–7693. Haider, A.J., Jameel, Z.N., Al-Hussaini, I.H., 2019. Review on: titanium dioxide applications. Energy Procedia 157, 17–29. Han, B., Jiang, X., Hou, X., Zheng, C., 2014. Miniaturized dielectric barrier discharge carbon atomic emission spectrometry with online microwave-assisted oxidation for determination of total organic carbon. Anal. Chem. 86, 6214–6219. Hineman, A., Stephan, C., 2014. Effect of dwell time on single particle inductively coupled plasma mass spectrometry data acquisition quality. J. Anal. Atom. Spectrom. 29, 1252–1257. Hund-Rinke, K., Simon, M., 2006. Ecotoxic effect of photocatalytic active nanoparticles (TiO2) on algae and daphnids. Environ. Sci. Pollut. Res. 13, 225–232. Kaegi, R., Ulrich, A., Sinnet, B., Vonbank, R., Wichser, A., Zuleeg, S., Simmler, H., Brunner, S., Vonmont, H., Burkhardt, M., Boller, M., 2008. Synthetic TiO2 nanoparticle emission from exterior facades into the aquatic environment. Environ. Pollut. 156, 233–239. Kaegi, R., Englert, A., Gondikas, A., Sinnet, B., von der Kammer, F., Burkhardt, M., 2017. Release of TiO2 – (Nano) particles from construction and demolition landfills. NanoImpact 8, 73–79. Khlebtsov, B.N., Khlebtsov, N.G., 2011. On the measurement of gold nanoparticle sizes by the dynamic light scattering method. Colloid J. 73, 118–127. Laborda, F., Bolea, E., Cepriá, G., Gómez, M.T., Jiménez, M.S., Pérez-Arantegui, J., Castillo, J.R., 2016. Detection, characterization and quantification of inorganic engineered nanomaterials: a review of techniques and methodological approaches for the analysis of complex samples. Anal. Chim. Acta 904, 10–32. Laborda, F., Jiménezlamana, J., Bolea, E., Castillo, J.R., 2011. Selective identification, characterization and determination of dissolved silver (I) and silver nanoparticles based on single particle detection by inductively coupled plasma mass spectrometry.