Environ Sci Pollut Res DOI 10.1007/s11356-015-4954-0
RESEARCH ARTICLE
Characterization of the precursors of trihalomethanes and haloacetic acids in the Yuqiao Reservoir in China Zhi-Guang Niu 1 & Xiao-Ting Wei 1 & Ying Zhang 2
Received: 7 March 2015 / Accepted: 23 June 2015 # Springer-Verlag Berlin Heidelberg 2015
Abstract To identify the primary precursors of trihalomethanes and haloacetic acids in the Yuqiao Reservoir in China, dissolved organic matters in the source water were isolated and fractionated into five different fractions (with XAD resin), and both trihalomethane and haloacetic acid formation potentials in each fraction were analysed by liquid-liquid extraction and GC-ECD. The primary precursors of trihalomethanes and haloacetic acids were identified using the index of disinfection by-product formation potential and specific disinfection byproduct formation potential. In addition, the relationship between the specific ultraviolet absorbance and the specific disinfection by-product formation potential was studied using correlation analysis. The results indicated that during the sampling period, the hydrophobic acids and hydrophilic matter are the primary organic fractions in the Yuqiao Reservoir, accounting for 27.6–40.9 % and 21.2–32.5%, respectively. Among the five fractions, the hydrophobic acids had the highest disinfection by-product formation potential and specific disinfection by-product formation potential, indicating that the hydrophobic acids were the primary precursors of the disinfection by-products in the Yuqiao Reservoir. A Responsible editor: Ester Heath * Ying Zhang [email protected] Zhi-Guang Niu [email protected] Xiao-Ting Wei [email protected] 1
School of Environmental Science and Engineering, Tianjin University, Tianjin 300072, China
2
College of Environmental Science and Engineering, Nankai University, Tianjin 300071, China
correlation analysis indicates that the specific ultraviolet absorbance had a moderately positive correlation with the specific disinfection by-product formation potential; therefore, the specific ultraviolet absorbance can be a reference index to analyse the ability of organic matter to generate disinfection by-products. Keywords Yuqiao Reservoir . Trihalomethanes . Haloacetic acids . Precursor identification . Organic fraction
Introduction In recent years, disinfection by-products (DBPs) in drinking water have become the focus of public attention. DBPs generate from the reaction between organic and chlorine, being carcinogenic to humans and may cause reproductive, developmental or other adverse effects (Nieuwenhuijsen et al. 2000; Villanueva et al. 2004; Tardiff et al. 2006). Due to long-term chlorination disinfection, DBPs have widely existed in the source water. Now, DBPs were already detected in many source waters in China (Liu 2007; Hong et al. 2013). At present, the main measures to control the DBPs are reducing the organic matter and decreasing the chlorine dosage. In recent years, to control DBPs in drinking water, many researchers have studied the primary precursors of DBPs in source water. For example, Reckhow et al. (1990) analysed the abilities of humic acids and fulvic acids to generate DBPs in five source waters, determining that fulvic acids produced more chloroform, while humic acids produced more dichloroacetic acid and trichloroacetic acid. Marhaba and Van (2000) observed that hydrophilic acids (HiA) and hydrophobic neutral fractions (HoN) were the primary precursors of trihalomethanes (THMs) and haloacetic acids (HAAs), respectively, in surface water in northern New Jersey. Croué
Environ Sci Pollut Res
et al. (2000) discovered that the more hydrophobic and more acidic fractions provide the most active precursor sites. Kitis et al. (2004) used five physicochemical separation processes, such as activated carbon and XAD-8 batch adsorption, alum coagulation, ultrafiltration, and XAD-8 column fractionation to fractionate dissolved organic matter, observing a strong correlation between the specific ultraviolet absorbance (SUVA) values of DOM fractions and their THM and HAA9 formations. In recent years, many reservoirs or rivers in China have been studied to find the primary precursors of DBPs based on analysing both disinfection by-product formation potential (DBPFP) and specific disinfection by-product formation potential (SDBPFP) of physical or chemical fractions (Yin et al. 2011; Zhao et al. 2011; Huang et al. 2013; Yuan 2012; Qiao et al. 2006). To date, the primary precursors of DBPs have been determined to be different in different waters, and the ability of organic fractions to generate DBPs is still disputed. Yuqiao Reservoir is the major water resource of Tianjin in North China with a volume of 15.59 billion cubic meters, supplying drinking water for 12.94 million people in Tianjin. The water quality of the Yuqiao Reservoir has a direct impact on the drinking water safety of Tianjin (Zhang et al. 2013a). In recent years, many studies focused on the water quality of the reservoir by analysing the content of chlorophyll, pH, nitrogen, phosphorus, heavy metals, phytoplankton, macrozoobenthos and other parameters (Liu et al. 2014; Chen et al. 2011, 2012; Guang et al. 2011; Zhang et al. 2013c; Ma et al. 2012). However, few studies on DBPs and their precursors have been published to date.
In this study, organic fractions of water from the Yuqiao Reservoir and their DBPFPs were studied. The correlation degree between SUVA and SDBPFP was also analysed. The aim of this paper is to identify the primary precursors of THMs and HAAs in Yuqiao Reservoir, thereby providing support for controlling the DBPs.
Materials and methods Sample collection The water sampling points of the Yuqiao Reservoir were evenly distributed, with the grid size being defined as 10 km× 10 km (shown in Fig. 1). There were a total of 10 sampling points, in which point 1 was set at the inlet of the Lin River into the Yuqiao Reservoir, point 2 was set at the inlet of the confluence of the Li River and the Sha River into the Yuqiao Reservoir, point 10 was set at the outlet of the Yuqiao Reservoir into the Zhou River, and the rest of the points were evenly distributed around the reservoir. The water feeds into the reservoir at point 1 from the Lin River and 2 from the Sha River and Li River, flows past each point from east to west, and eventually flows out at point 10 to the Zhou River. The water was sampled five times from May to September in 2014. The sampling point was 0.5 m under the surface layer, and the samples were preserved in brown glass bottles at 4 °C and analysed within 24 h.
Fig. 1 Sampling points for water quality in the Yuqiao Reservoir
Tianjin
China Tianjin
Downtown
Yuqiao
Reservoir
Yuqiao Reservoir
Environ Sci Pollut Res Table 1
Computational formula of each DOC fraction in water sample
DOC fraction
Content (mg/L)
Percentage account in raw water
HoA HoN HoB WHoA HiM
DOC2 −DOC4 DOC1 −DOC2 −(DOC3 −DOCB)/3.5 (DOC3 −DOCB)/3.5 DOC4 −DOC5 DOC5
(DOC2 −DOC4)/DOC1 ×100 % [DOC1 −DOC2 −(DOC3 −DOCB)/3.5]/DOC1 ×100 % [(DOC3 −DOCB)/3.5]/DOC1 ×100 % (DOC4 −DOC5)/DOC1 ×100 % DOC5 /DOC1 ×100 %
DOC1 is the DOC value of raw water. DOC2 is the DOC value of water sample passed through the XAD-8 column at the first time. DOC3 is the DOC value of phosphoric acid passed through the XAD-8 column. DOC4 is the DOC value of water sample passed through the XAD-8 column at the second time. DOC5 is the DOC value of water sample passed through the XAD-4 column. DOCB is the DOC value of phosphoric acid.
As for dissolved organic carbon (DOC), DBPs and DBPFP, samples of 10 points were analysed, and the average value was used to discuss, while the isolation and fractionation of the DBP precursors were only conducted with the sample of point 6.
immediately run through the XAD-4 resin. WHoA was adsorbed by the XAD-4 resin, and HiM was left in the sample. DOC of five organic fractions in water sample is calculated by the computational formula shown in Table 1.
Analysis methods Isolation and fractionation In this study, DOC was divided into five fractions, which were categorized as hydrophobic bases (HoB), hydrophobic acids (HoA), hydrophobic neutral fractions (HoN), weakly hydrophobic acids (WHoA) and hydrophilic matter (HiM), through resin adsorption using XAD-8 resin and XAD-4 resin. The specific steps of isolation and fractionation of DOC referred to Wei et al. (2006). The XAD-8 resin and XAD-4 resin need be pretreated first to ensure that the organic matter will not be soluble from the resin. Keeping the speed of the liquids at 15 times the bed volume per hour for the whole process, the filtered sample passed through the XAD-8 column directly. After sampling, 10 times the bed volume of 0.1 mol/L phosphoric acid passed through the XAD-8 column. HoB was desorbed by phosphoric acid, while HoN was adsorbed by the XAD-8 resin column. Then, the sample effluent from the XAD-8 column was acidified to pH 2 and recycled through the XAD-8 column, and HoA was adsorbed by the XAD-8 resin. At last, the sample, which now contained only WHoA and HiM, was
Table 2
The quality of raw water
Water quality index
Range
Average value
Temperature, °C pH Turbidity, NTU Ammonia nitrogen, mg/L UV254, cm−1 DOC, mg/L
23.8–32.3 8.15–8.88 1.22–6.93 0.09–0.32 0.052–0.063 2.969–3.539
29.2 8.66 3.89 0.19 0.059 3.350
DOC, trihalomethane formation potential (THMFP), haloacetic acid formation potential (HAAFP) and SUVA were analysed in this study. Before analysis, all water samples were filtered with 0.45 μm microfiltration membrane. Four THMs and five HAAs were detected in the experiment. The four THMs are chloroform (TCM), bromodichloromethane (BDCM), dibromochloromethane (DBCM) and tribromethane (TBM). The five HAAs consisted of monochloroacetic acid (MCAA), dichloroacetic acid (DCAA), trichloroacetic acid (TCAA), bromoacetic acid (MBAA) and dibromoacetic acid (DBAA). The DOC was analysed through a total organic carbon analyser (Shimadzu TOC-VCPH). Chlorination of samples was necessary in the process of analysing both the THMFP and HAAFP. Firstly, water samples with the volume of 200 mL were put into the abrasive glass bottles respectively, and all samples were adjusted to a pH of 7.0±0.2 using 1 mol/L hydrochloric acid. Four milliliters of 0.1 mol/L phosphate, consisting of 17.025 g of potassium dihydrogen phosphate and 2.925 g of sodium hydroxide mixed in 250 mL ultrapure water, was then used to buffer the solution at pH 7. To provide a residual-free chlorine of 3– 5 mg/L to ensure the chlorination condition (Liu et al. 2009, 2011; Qiao et al. 2006), the samples was chlorinated by sodium hypochlorite (20 mg/L of available chlorine). At last, the
Table 3
DOC concentrations of raw water in the Yuqiao Reservoir
Sampling date May30 June30 July30 August 25 September 12 DOC, mg/L
2.969
3.287
3.539
3.523
3.431
Environ Sci Pollut Res 1.6
Table 5
1.4
HoB
Concentraon
1.2
The DOC concentrations in different water sources
Water source
DOC, mg/L 2.969–3.539 2.51–2.71
Reference
1.0
HoN
0.8
HoA
0.6
WHoA
Yuqiao Reservoir Reservoir water from Yellow River
HiM
Shenzhen Reservoir
1.2–2.1
Qiao et al. 2007
A typical river-type water source in the Yangtze River Delta Three reservoirs in Northern China
4.4–4.7
Huang et al. 2013
26.6–34.5
Yin et al. 2011
0.4 0.2 0.0 30 May
30 Jun
30 Jul
25 Aug
12 Sep
date
Zhang et al. 2013a, b, c
Fig. 2 The concentrations of organic fractions
samples were put into a biochemical incubator at 25±0.5 °C for 7 days in the dark (Liu 1999; Wang et al. 2001; Liu et al. 2009). The samples were analysed by liquid-liquid extraction and gas chromatography using an Agilent 6890N system and an electron capture detector equipped with an HP-5 capillary column (30.0 m×320 μm×0.25 μm) and an automatic sampler (Agilent 7683B). The specific analyses of THMs and HAAs were conducted according to optimized USEPA standard methods 551.1 (USEPA 1995a) and 552.3 (USEPA 1995b), respectively. Residual chlorine in each sample was analysed by DPD photometry after constant temperature cultivation. If residual chlorine was in the range of 3–5 mg/L, 1 g ascorbic acid was added to the water sample to terminate chlorination reaction, and 25 mL surface water was transferred to a 50-mL brown screw cap glass vial. For THMs, the sample was extracted with 12 g anhydrous sodium sulfate and 3 mL methyl tert-butyl ether (MTBE); after oscillating for 4 min and settling for 2 min, 1 mL surface organic solution was extracted to a 2-mL brown screw cap glass vial for analysis. The temperatures for the inlet and detector were 150 and 300 °C, respectively, and the oven temperature gradient began at 30 °C for 2 min and rose to 70 °C at a rate of 5 °C/min. For HAAs, the sample was extracted with 1.5 mL concentrated sulfuric acid, 12 g anhydrous sodium sulfate and 3mL MTBE. After oscillating for 3 min and settling for 3 min, 1 mL surface organic solution was extracted to a 15-mL brown screw cap glass vial, and 2 mL 10 % sulfuric acid methanol solution was added to the same vial. Then, thermostatic water bath was conducted for 1 h under 50 °C. After the water sample cooling down, adding 5 mL 10 % sodium sulfate solution and 1 mL MTBE, then oscillating for 2 min and settling for 2 min, finally 1 mL surface organic solution was extracted to a 2-mL brown screw cap glass vial for analysis. The temperatures for the injector Table 4 The monthly average temperature of Tianjin from May to September, 2014 Month
May June July August September
Average highest temperature, °C 28 Average lowest temperature, °C 17
31 22
33 25
31 23
26 18
and detector were 220 and 280 °C, respectively. The oven temperature gradient began at 40 °C for 7 min, rose to 70 °C at a rate of 5 °C/min and then rose to 250 °C at a rate of 30 °C/min (holding for 5 min). SUVA is the ultraviolet absorbance of a unit DOC concentration under 254 nm irradiation (Lee et al. 2001), calculated by the UV254/DOC ratio multiplied by 100. UV254 is analysed by ultraviolet spectrophotometer with 254 nm irradiation. Statistical analysis The results of DOC fractions, DBP precursors and UV254 were processed by EXCEL2003, and the correlation between DBPFP and SUVA was calculated by SPSS 19.0. Quality assurance All the samples and blanks were analysed in duplicates for quality assurance control of laboratory analyses in this study. Only the relative standard deviation (RSD) values below 10 % were accepted, while other samples outside this range were reanalysed. A standard reference material (SRM) GSB 071982-2005 from Institution for Environmental Reference Material Ministry of Environmental Protection was applied for calibration and analytical control. Table 6
THMs and THMFP in the Yuqiao Reservoir May 30 June 30 July 30
THMs, μg/L
TCM 4.559 BDCM 2.155
DBCM TBM Total THMFP, TCM μg/L BDCM DBCM TBM Total
0.000 0.000 6.714 133.667 13.300 5.077 0.000 152.044
August 25
September 12
9.189 2.773
17.164 2.540
16.116 2.102
15.049 1.845
2.037 0.000 13.998 246.049 124.099 9.142 0.000 379.291
0.000 0.000 19.704 266.359 156.562 12.378 0.000 435.299
1.058 0.000 19.277 261.342 154.889 8.971 0.000 425.202
2.040 0.000 18.935 195.835 39.178 7.985 0.000 242.998
Environ Sci Pollut Res Table 7
The THMFP in different water sources
Table 8 fraction
Source water
THMFP, μg/L
Reference
Yuqiao Reservoir A typical river-type water source in the Yangtze River Delta The raw water from Nanjing Water Treatment Plant The Sacramento River, California
152.0–435.3 130–182
Huang et al. 2013
90
Shang et al. 2005
156–196
Chow et al. 2007
The San Joaquin River, California
392–490
Chow et al. 2007
Australian source waters
199–522
Fabris et al. 2008
Southeast of Norwegian source waters Buyukcekmece Lake
846
Fabris et al. 2008
126–1535
Aydin et al. 2012
THMs and HAAs were identified relative to external standards. Recoveries of SRM and external stands varied from 91.2 to 94.5 %. In addition, SRM was continuously diluted and analysed until the peak is a signal-to-noise ratio (S/N) of 3, and the corresponding concentration was regarded as the detection limit, which was 0.01 μg/L for the four kinds of THMs and the five kinds of HAAs. Chemicals The chemicals were all purchased from chemical network management platform of Tianjin University (http://219.243. 47.181/chem).
Results and discussion The quality of raw water in Yuqiao Reservoir during the sampling period was shown in Table 2. Classification results of DOC in the Yuqiao Reservoir The DOC concentrations in the Yuqiao Reservoir during the sampling period are shown in Table 3, and the isolation results of DOC are shown in Fig. 2. The results showed that DOC
The concentration of four kinds of THMs in each DOC TCM, μg/L
BDCM, μg/L
DBCM, μg/L
TBM, μg/L
HoB HoN HoA WHoA
0.872–3.314 0.991–3.464 1.143–3.511 0.416~3.399
0.34–0.55 0.351–0.561 0.388–0.579 0.376~0.52
0–0.312 0–0.316 0–0.373 0~0.498
0 0 0 0
HiM
1.137~3.487
0.39~0.563
0~0.687
0
concentrations of raw water in the Yuqiao Reservoir fluctuated temporally. The average value was 3.350 mg/L. The maximum value appeared in July 30, and the lowest value appeared in May 30, which is consistent with the temperature variation (Table 4). Compared to other source waters (Table 5), DOC in the Yuqiao Reservoir was at medium level. The results indicate that HoA and HiM, with percentages of 27.6–40.9 and 21.2–32.5 %, respectively, were the primary organic fractions. Our results are consistent with Huang (2013) and Qiao et al. (2006), but different from Yin et al. (2011) and Marhaba and Van (2000). The HoN concentration was close to the WHoA concentration, while the HoB concentration was the lowest of the five fractions, with a contribution of less than 10 %. In May, June and September, the order of the concentration levels was HoA > HiM > HoN > WHoA > HoB, while in July and August, the order turned into HiM > HoA > WHoA > HoN > HoB, which showed that the HiM concentration increased in July and August. Identification of THM precursors in Yuqiao Reservoir The THMs of raw water and corresponding THMFP in Yuqiao Reservoir during the sampling period were shown in Table 6. The THMs in raw water during sampling period were between 6.714 and 19.704 μg/L, in which TCM concentration was the highest, BDCM concentration was the second highest, DBCM concentration was the lowest, and TBM was not
250
180 160
200
140
HoB
HoN
120
HoN
100
HoA 100
WHoA HiM
50
STHMFP
THMFP
150
HoB
HoA
80 60
WHoA
40
HiM
20 0
0 30 May
30 Jun
30 Jul
25 Aug
date
Fig. 3 THMFPs of the five organic fractions
12 Sep
30 May
30 Jun
30 Jul date
Fig. 4 STHMFP of organic fractions
25 Aug
12 Sep
Environ Sci Pollut Res 180
35%
160
(%
25% 20%
140
HoB
HoN
120
HoN
HoA
15%
WHoA
10% STHMFP
HoB
100 HAAFP
30%
HiM
5%
HoA
80 60
WHoA
40
HiM
20 0
0% 30 May
30 Jun
30 Jul
25 Aug
30 May
12 Sep
30 Jun
30 Jul
25 Aug
12 Sep
date
date
Fig. 5 STHMFP percentage of organic fractions
Fig. 6 HAAFPs of organic fractions
detected. The corresponding THMFP concentrations were ranged from 152.044 to 435.299 μg/L. Both THMs and THMFP were all changed temporally, the highest values of which occurred in July and August, while the lowest values appeared in May. Compared with other source waters (Table 7), THMFP in Yuqiao Reservoir was at a medium level. The THMFP of the five organic fractions during the sampling period are shown in Fig. 3 and Table 8. HoA had the highest THMFP (69.9–196.5 μg/L), accounting for 35.8– 51.8 % of the total THMFP of the five organic fractions. Next was HiM, whose THMFP contribution was between 19.6 and 32 %. Because of their high THMFP, HoA and HiM were the primary precursors of THMs in the Yuqiao Reservoir, comprising approximately 70 % of the total. The THMFP of WHoA, HoN and HoB decreased orderly, and the lowest contribution was only 1–1.7 %. Moreover, the THMFP of the five organic fractions were usually higher in July and August, indicating that the Yuqiao Reservoir had a higher concentration of THM precursors in July and August. The ability to generate THMs of different organic fractions was evaluated by the specific trihalomethane formation potential (STHMFP) (the ratio of THMFP to DOC). The STHMFP of the organic fractions and their percentages are shown in Fig. 4 and Fig. 5, respectively. Figure 4 shows that the STHM
FP varied with the sampling date, and the higher values appeared from June to August. By contrast, the STHMFP percentages of the different organic fractions (shown in Fig. 5) were relatively stable during the sampling period. Among the five organic fractions, HoA had the highest STHMFP, with values ranging from 64.8 to 159.5 μg/mg, 29.7 to 30.9 % of the total, meaning that HoA was the primary THM precursor. This conclusion was consistent with the findings of Huang et al. (2013) and Yuan (2012), but different from Yin et al. (2011). If the organics were only classified by hydrophilicity and hydrophobicity, the STHMFP of HoM would be between 108.6 and 265.9 μg/mg, 49.7–51.9 % of the total STHMFP. The above results illustrate that HoM was the primary THM precursors, which is consistent with most studies (Yin et al. 2011; Huang et al. 2013; Yuan 2012; Qiao et al. 2006). The STHMFP of WHoA was lower than that of HoM, and the STHMFP of HiM was the lowest.
Table 9 HAAs and HAAFP in the Yuqiao Reservoir HAAs, μg/L
HAAFP, μg/L
MCAA DCAA TCAA MBAA DBAA Total MCAA DCAA TCAA MBAA DBAA Total
Identification of HAA precursors in the Yuqiao Reservoir The HAAs of raw water and corresponding HAAFP in Yuqiao Reservoir during the sampling period were shown in Table 9. The five components were all detected, in which DCAA and TCAA were the major matter. Generally, brominated HAAs
May 30
June 30
July 30
August 25
September 12
3.430 6.357 5.863 1.067 1.463 18.18 44.761 81.217 79.776 3.881 12.210 221.844
4.942 9.709 8.645 0.726 1.643 25.666 63.059 113.448 102.650 3.687 12.657 295.502
6.319 9.955 8.837 1.154 1.023 27.288 68.980 177.890 114.588 4.233 15.313 381.004
6.112 9.803 8.251 0.714 1.036 25.916 64.729 173.594 112.284 3.901 14.641 369.149
5.142 9.235 7.060 0.633 1.688 23.758 58.186 115.692 103.945 3.765 14.331 295.919
Environ Sci Pollut Res Table 10 The concentration of five kinds of HAAs in each DOC fraction HoB HoN HoA WHoA HiM
MCAA, μg/L
DCAA, μg/L
TCAA, μg/L
MBAA, μg/L
DBAA, μg/L
0.680–1.157 0.45–1.128 0.96–1.486 0.61–1.209 0.73–1.416
1.168–1.762 1.147–1.729 1.457–2.608 1.136–1.876 1.449–2.485
1.035–1.528 1.198–1.739 1.261–2.042 1.132–1.598 1.237–2.28
0.094–0.227 0.129–0.225 0.112–0.217 0.107–0.199 0.163–0.305
0.182–0.316 0.174–0.306 0.191–0.335 0.144–0.297 0.311–0.499
were less than chlorinated HAAs. During sampling period, the HAAs were always higher than THMs in the raw water, while the temporal variations of HAAs and HAAFP were the same as THMs and THMFP. The HAAFPs of the five organic fractions in Yuqiao Reservoir during the sampling period are shown in Fig. 6 and Table 10. The results show that HAAFP was detected in all organic fractions. The HAAFP of HoA was from 113.1 to 164.3 μg/L, representing 41.4–55.6 % of the total, indicating that approximately half of the HAAs in the Yuqiao Reservoir are generated by HoA. HiM was the second-highest fraction of the HAAFP, accounting for 21.7–34.1 % of the total. Consequently, HoA and HiM are the two primary precursors of HAAs in the Yuqiao Reservoir. The HAAFPs of WHoA and HoN were very close, and the maximum difference between them was only 3.6 % during the sampling period. HoB had the lowest HAAFP, representing less than 1 %, illustrating that HoB had little impact on HAAs. These results are similar to Wu (2006). In addition, Fig. 6 shows that the HAAFPs were higher in most organic fractions in July and August, which was slightly different from the THMFP distributions of the five organic fractions. The specific haloacetic acid formation potential (SHAAFP) of the five organic fractions in the Yuqiao Reservoir during the sampling period are shown in Fig. 7, and their percentages are shown in Fig. 8. The SHAAFPs fluctuated temporally, but their percentages were stable. The SHAAFP of HoA was the highest, and its percentage was between 35.1 and 37.3 %, indicating that HoA was the primary HAAs precursor. This conclusion is consistent with Huang et al. (2013) and Lu et al.
(2009). The SHAAFP percentage of HiM was approximately 10 % lower than that of HoA, showing that the ability of HiM to generate HAAs was slightly lower than that of HoA. The SHAAFPs of WHoA and HoN were close, as were the SHAA FP percentages. HoB had the lowest SHAAFP, indicating that the ability of HoB to generate HAAs was weak. The THMs and HAAs were added together to analyse the primary precursors of DBPs, and the results showed that the order of DBPFP of the five organic fractions was HoA > HiM > WHoA > HoN > HoB, as was the SDBPFP. This suggests that HoA is the primary precursor of DBPs among the five organic fractions. The ability of an organic fraction to generate DBPs can be changed. Although the DOC in water was already classified by the resin adsorption method, the composition of each organic fraction was still complex. The functional groups contained in each organic fraction change with water quality, so the ability of an organic fraction to generate DBPs may vary. Correlation analysis between SUVA and SDBPFP SUVA is the ultraviolet absorbance of a unit DOC concentration under 254 nm irradiation (Lee et al. 2001), calculated by the UV/DOC ratio multiplied by 100. SUVA can reflect some characteristics of organic matter in water, such as humification degree and the relative content of unsaturated double bonds or aromatic organic compounds (Imai et al. 2001). Some studies have indicated that SUVA is significantly correlated
180
40%
160 120
HoN
25%
HoN
HoA
20%
HoA
60
WHoA
15%
WHoA
40
HiM
20
SHAAFP
80
(%
HoB
100 SHAAFP
35%
140
HoB
30%
10%
HiM
5% 0%
0 30 May
30 Jun
30 Jul date
Fig. 7 SHAAFPs of organic fractions
25 Aug
12 Sep
30 May
30 Jun
30 Jul
25 Aug
date
Fig. 8 SHAAFP percentages of organic fractions
12 Sep
Environ Sci Pollut Res Table 11
SUVA of raw water during the sampling period
Sampling date
Results of correlation analysis between SUVA and SHAAFP
Table 14
May30 June30 July30 August 25 September 12
SUVA, L/(m·mg) 1.75
1.76
1.75
1.79
SUVA
1.72
SHAAFP 2.5 2.0
HoB HoN
1.5 SUVA
HoA 1.0
30 May
30 Jun
30 Jul
25 Aug
12 Sep
date
Fig. 9 SUVA of organic fractions
STHMFP
1
.765** .000 496.864 20.703 25 1
8.730 .364 25 .765** .000 496.864 20.703 25
48,297.695 2012.404 25
**Correlation is significant at the 0.01 level (two-tailed)
HiM
0.0
SUVA
SHAAFP
WHoA
0.5
Table 12 STHMFP
Pearson correlation Sig. (two-tailed) Sum of squares and cross-products Covariance N Pearson correlation Sig. (two-tailed) Sum of squares and cross-products Covariance N
SUVA
Results of the correlation analysis between SUVA and SUVA
STHMFP
Pearson correlation Sig. (two-tailed) Sum of squares and cross-products Covariance N Pearson correlation Sig. (two-tailed)
1
.766** .000 523.172 21.799 25 1
Sum of squares and cross-products Covariance N
523.172 21.799 25
8.730 .364 25 .766** .000
53,424.523 2226.022 25
**Correlation is significant at the 0.01 level (two-tailed)
Table 13 The function between SUVA and STHMFP
Equation
with the ability of organic matter to generate DBPs (Kitis et al. 2002). Table 11 shows the SUVA of raw water during the sampling period, and Fig. 9 shows the SUVA of each organic fraction. The SUVA of raw water and those of the five organic fractions were stable during the sampling period. In the Yuqiao Reservoir, the organic acids had the highest value of SUVA, indicating that the organic acids not only had the highest humification degree but were also a major source of unsaturated double bonds or aromatic organic compounds. A correlation analysis by IBM SPSS statistics 19 was conducted to investigate the correlation degree between SUVA and DBPFP. The results (Table 12 and Table 13) show that SUVA and STHMFP have a moderately positive correlation (the Pearson coefficient was between 0.5 and 0.8), with a significant correlation at the 0.01 level (the two-tailed significant value was less than 0.01). The results of the correlation analysis between SUVA and SHAAFP are shown in Table 14 and Table 15. The SUVA and SHAAFP had a moderately positive correlation as well (the Pearson coefficient was between 0.5 and 0.8), which was also significant at the 0.01 level (the two-tailed significant value was less than 0.01). The above results illustrate that SUVA has some correlation with SDBPFP, but the two parameters were not precisely
Model summary R2
F
Parameter estimation Sig.
Constant
STHMFP coefficient
Value
t
Sig.
Value
t
Sig.
Linear Index
0.587 0.582
32.672 31.994
.000 .000
0.529 0.008
3.290 5.656
.003 .000
0.010 0.609
5.716 7.397
.000 .000
Logistic
0.582
31.994
.000
1.641
7.397
.000
0.992
694.154
0.000
Environ Sci Pollut Res Table 15 The function between SUVA and SHAAFP
Equation
Model summary R2
F
Parameter estimation Sig.
Constant
STHMFP coefficient
Value
t
Sig.
Value
t
Sig.
Linear Index
0.586 0.562
32.491 29.568
.000 .000
0.570 0.637
3.680 7.517
.001 .000
0.010 0.008
5.700 5.438
.000 .000
Logistic
0.562
29.568
.000
1.570
7.517
.000
0.992
645.288
0.000
aligned. Therefore, SUVA can be used as a reference index to analyse the ability of organic matter to generate DBPs but cannot completely replace SDBPFP.
Conclusions The DOC, DBPs and DBPFP were all detected in water from Yuqiao Reservoir during the sampling period, and the results show that (1) except for TBM, nine kinds of DBPs and corresponding DBPFP were all detected. TCM, DCAA and TCAA have higher concentration and formation potentials; (2) compared with other surface water sources, DOC, THMFP and HAAFP in water from Yuqiao Reservoir are at a medium level; (3) the concentration of DOC, THMFP and HAAFP were relatively higher from June to September. The primary precursors of both THMs and HAAs in the Yuqiao Reservoir were identified, and the results indicate that (1) HoA and HiM are the primary organic fractions in Yuqiao Reservoir, accounting for 27.6–40.9 and 21.2–32.5 % of the total DOC, respectively; (2) HoA is the primary precursor of THMs and HAAs in Yuqiao Reservoir; and (3) SUVA and SDBPFP have a moderately positive correlation. Based on this study, the further research should focus on the influence factors of organic fractions and the control methods of the DBPFP in the source water. Acknowledgments This project was supported by the National Science Foundation of China (51308305), the Major Projects of the National Water Pollution Control and Treatment Technology of China (2014ZX07203-009), and the Program for New Century Excellent Talents in University of China.
References Aydin E, Yaman FB, Genceli EA, Topuz E, Erdim E, Gurel M, Ipek M, Pehlivanoglu-Mantas E (2012) Occurrence of THM and NDMA precursors in a watershed: effect of seasons and anthropogenic pollution. J Hazard Mater 221–222:86–91 Chen SR, Wu GH, Su RX (2011) Change characteristics of water quality and its impact factor at the Yuqiao Reservoir in Tianjin. Water Resour Prot 27(27–30):34
Chen YY, Zhang C, Gao XP, Wang LY (2012) Long-term variations of water quality in a reservoir in China. Water Sci Technol 65:1454– 1460 Chow AT, Dahlgren RA, Harrison JA (2007) Watershed sources of disinfection byproduct precursors in the Sacramento and San Joaquin Rivers, California. Environ Sci Technol 41: 7645–7652 Croué JP, Violleau D, Labouyrie L (2000) Disinfection by-product formation potentials of hydrophobic and hydrophilic natural organic matter fractions: a comparison between a low- and a high-humic water. American Chemical Society, Washington, DC Fabris R, Chow CWK, Drikas M, Eikebrokk B (2008) Comparison of NOM character in selected Australian and Norwegian drinking waters. Water Res 42:4188–4196 Guang HW, Shan SC, Shui RC, Fang TC (2011) Accumulation and remobilization of metals in superficial sediments in Tianjin, China. Environ Monit Assess 173:917–928 Hong HC, Xiong YJ, Ruan MY, Liao FL, Lin HJ, Liang Y (2013) Factors affecting THMs, HAAs and HNMs formation of Jin Lan Reservoir water exposed to chlorine and monochloramine. Sci Total Environ 444:196–204 Huang H, Cheng ZP, Lin F, Li Q, Fei XQ, Jiang GC, Xu JM (2013) Species distribution characteristic of organic matters in the rivertype water source and its relationship with disinfection by-products. Resour Environ Yangtze Basin 22:1602–1607 Imai A, Fukushima T, Matsushige K, Kim YH (2001) Fractionation and characterization of dissolved organic matter in a shallow eutrophic lake, its inflowing rivers, and other organic matter sources. Water Res 35:4019–4028 Kitis M, Karanfil T, Wigton A, Kilduff JE (2002) Probing reactivity of dissolved organic matter for disinfection by-product formation using XAD-8 resin adsorption and ultrafiltration fractionation. Water Res 36:3834–3848 Kitis M, Karanfil T, Kilduff JE (2004) The reactivity of dissolved organic matter for disinfection by-product formation. Turkish J Eng Env Sci 28:167–179 Lee KJ, Kim BH, Hong JE, Pyo HS, Park SJ, Lee DW (2001) A study on the distribution of chlorination by-products (CBPs) in treated water in Korea. Water Res 35:2861–2872 Liu WJ (1999) Study on characteristics of biodegradable organic matter and disinfection by-products in drinking water. Dissertation of Tsinghua University, China Liu WL (2007) Analysis of correlation between coneentration of trihalomethanes and genetietoxieity in drinking water. Environ Sci Manag 32(45–46):53 Liu J, Chen C, Zhang XJ (2009) Disinfection by-products reduction of combined disinfection by chlorine and monochloramines in distribution system. Environ Sci 30:2538–2542 Liu YF, Wang QS, Yue SC, Li SS, Zhang YR, Lu JF (2011) Analysis of disinfection by-product precursors based on hydrophobicity and molecular weight. Water Wastewater Eng 37:128-132
Environ Sci Pollut Res Liu XB, Dong F, He GJ, Liu JL (2014) Use of PCA-RBF model for prediction of chlorophyll-a in Yuqiao Reservoir in the Haihe River Basin, China. Water Sci Technol-Water Supply 14:73–80 Lu JF, Zhang T, Ma J, Chen ZL (2009) Evaluation of disinfection byproducts formation during chlorination and chloramination of dissolved natural organic matter fractions isolated from a filtered river water. J Hazard Mater 162:140–145 Ma XJ, Shen JZ, Sun JH, Wang HS, Zhang K (2012) Macrozoobenthos community structure and water quality evaluation of Yuqiao Reservoir in Tianjin, North China. Chinese J Ecol 31:2356–2364 Marhaba TF, Van D (2000) The variation of mass and disinfection byproduct formation potential of dissolved organic matter fractions along a conventional surface water treatment plant. J Hazard Mater 74:133–147 Nieuwenhuijsen MJ, Toledano MB, Elliott P (2000) Uptake of chlorination disinfec-tion by-products: a review and a discussion of its implications for exposureassessment in epidemiological studies. J Expo Anal Environ Epidemiol 10:586–599 Qiao CG, Wei QS, Wang DS, Liu LJ, Huang XD, Zhang JS, Wei Q, Li MJ (2006) Fractionation and characterization of DOM and the THMFP feature in the South-China source water. Acta Scien Circum 26:944–948 Qiao CG, Wei QS, Wang DS, Yang M, Wei Q, Li MJ (2007) Molecular weight distribution and removal characters of DOM in the typical source water in south of China. Acta Scien Circum 27:195–200 Reckhow DA, Singer PC, Malcolm RL (1990) Chlorination of humic materials: by-product formation and chemical interpretations. Environ Sci Technol 24:1655–1664 Shang DH, Wang ZP, Zhang ZS (2005) Study on influence factor of trihalomethanes formation in drinking water. J East China Shipbuild Institute (Natural Science Edition) 19:91–93 Tardiff RG, Carson ML, Ginevan ME (2006) Updated weight of evidence for an association between adverse reproductive and developmental effects and exposureto disinfection by-products. Regul Toxicol Pharm 45:185–205
USEPA (1995a) Determination of chlorination disinfection by-products, chlorinated solvents, and halogenated pesticides/herbicides in drinking water by liquid-liquid extraction and gas chromatograph with electron-capture detection (Method 551.1) USEPA (1995b) Determination of haloacetic acids and dalapon in drinking water by liquid-liquid microextraction, derivatization, and gas chromatography with electron-capture detection (Method 552.3) Villanueva CM, Cantor KP, Cordier S, Jaakkola JJ, King WD, Lynch CF, Porru S, Kogevinas M (2004) Disinfection byproducts and bladder cancer: a pooledanalysis. Epidemiology 15:357–367 Wang LH, Zhou H, Zhang XJ, Wang ZS (2001) Characteristics and chlorination activity of dissolved organic matter fractions in surface source water. Acta Scien Circum 21:573–576 Wei QS, Wang DS, Yu JF, Liu HL, Han HD, He WJ (2006) Mechanism and method for chemical fractionation of dissolved organic matter in water. Techniques Equip Environ Poll Control 7(17–21):82 Wu HH (2006) Study on formation characteristics and removal mechanism of disinfection by-products during prechlorination. Dissertation of Tongji University, China Yin J, Zhou X, Lin YZ, Wang X (2011) Chemical fractionation of organic matters and THMFP characterization in north reservoir water. China Water Wastewater 27:83–86 Yuan XH (2012) Study on the chlorinated disinfection by-products of the raw water from water plants in Fuzhou. Master Dissertation of Fujian Normal University, China Zhang Y, Zhai RC, Wang CC (2013a) Study on vulnerability assessment of reservoir-type water source. J Water Resour Water Eng 24:5–9 Zhang YH, Wang M, Yu J, Xing LZ, Liu JG (2013b) Study on characteristics of dissolved organic carbon in reservoir water from Yellow River. J Shandong Jianzhu University 28:27–30 Zhang Z, Bian SW, Mei PY, Wu D, Wang HY, Wang M (2013c) Correlation between phytoplankton abundance and environmental factors in Yuqiao Reservoir. Ecol Sci 32:594–598 Zhao SJ, Gao NY, Jiang FC, Li Q, Chu WH (2011) Influence of the characterstics of organic matter in reservior water on the formation of DBPs. Water Wastewater Eng 37:119–124
RESEARCH ARTICLE
Characterization of the precursors of trihalomethanes and haloacetic acids in the Yuqiao Reservoir in China Zhi-Guang Niu 1 & Xiao-Ting Wei 1 & Ying Zhang 2
Received: 7 March 2015 / Accepted: 23 June 2015 # Springer-Verlag Berlin Heidelberg 2015
Abstract To identify the primary precursors of trihalomethanes and haloacetic acids in the Yuqiao Reservoir in China, dissolved organic matters in the source water were isolated and fractionated into five different fractions (with XAD resin), and both trihalomethane and haloacetic acid formation potentials in each fraction were analysed by liquid-liquid extraction and GC-ECD. The primary precursors of trihalomethanes and haloacetic acids were identified using the index of disinfection by-product formation potential and specific disinfection byproduct formation potential. In addition, the relationship between the specific ultraviolet absorbance and the specific disinfection by-product formation potential was studied using correlation analysis. The results indicated that during the sampling period, the hydrophobic acids and hydrophilic matter are the primary organic fractions in the Yuqiao Reservoir, accounting for 27.6–40.9 % and 21.2–32.5%, respectively. Among the five fractions, the hydrophobic acids had the highest disinfection by-product formation potential and specific disinfection by-product formation potential, indicating that the hydrophobic acids were the primary precursors of the disinfection by-products in the Yuqiao Reservoir. A Responsible editor: Ester Heath * Ying Zhang [email protected] Zhi-Guang Niu [email protected] Xiao-Ting Wei [email protected] 1
School of Environmental Science and Engineering, Tianjin University, Tianjin 300072, China
2
College of Environmental Science and Engineering, Nankai University, Tianjin 300071, China
correlation analysis indicates that the specific ultraviolet absorbance had a moderately positive correlation with the specific disinfection by-product formation potential; therefore, the specific ultraviolet absorbance can be a reference index to analyse the ability of organic matter to generate disinfection by-products. Keywords Yuqiao Reservoir . Trihalomethanes . Haloacetic acids . Precursor identification . Organic fraction
Introduction In recent years, disinfection by-products (DBPs) in drinking water have become the focus of public attention. DBPs generate from the reaction between organic and chlorine, being carcinogenic to humans and may cause reproductive, developmental or other adverse effects (Nieuwenhuijsen et al. 2000; Villanueva et al. 2004; Tardiff et al. 2006). Due to long-term chlorination disinfection, DBPs have widely existed in the source water. Now, DBPs were already detected in many source waters in China (Liu 2007; Hong et al. 2013). At present, the main measures to control the DBPs are reducing the organic matter and decreasing the chlorine dosage. In recent years, to control DBPs in drinking water, many researchers have studied the primary precursors of DBPs in source water. For example, Reckhow et al. (1990) analysed the abilities of humic acids and fulvic acids to generate DBPs in five source waters, determining that fulvic acids produced more chloroform, while humic acids produced more dichloroacetic acid and trichloroacetic acid. Marhaba and Van (2000) observed that hydrophilic acids (HiA) and hydrophobic neutral fractions (HoN) were the primary precursors of trihalomethanes (THMs) and haloacetic acids (HAAs), respectively, in surface water in northern New Jersey. Croué
Environ Sci Pollut Res
et al. (2000) discovered that the more hydrophobic and more acidic fractions provide the most active precursor sites. Kitis et al. (2004) used five physicochemical separation processes, such as activated carbon and XAD-8 batch adsorption, alum coagulation, ultrafiltration, and XAD-8 column fractionation to fractionate dissolved organic matter, observing a strong correlation between the specific ultraviolet absorbance (SUVA) values of DOM fractions and their THM and HAA9 formations. In recent years, many reservoirs or rivers in China have been studied to find the primary precursors of DBPs based on analysing both disinfection by-product formation potential (DBPFP) and specific disinfection by-product formation potential (SDBPFP) of physical or chemical fractions (Yin et al. 2011; Zhao et al. 2011; Huang et al. 2013; Yuan 2012; Qiao et al. 2006). To date, the primary precursors of DBPs have been determined to be different in different waters, and the ability of organic fractions to generate DBPs is still disputed. Yuqiao Reservoir is the major water resource of Tianjin in North China with a volume of 15.59 billion cubic meters, supplying drinking water for 12.94 million people in Tianjin. The water quality of the Yuqiao Reservoir has a direct impact on the drinking water safety of Tianjin (Zhang et al. 2013a). In recent years, many studies focused on the water quality of the reservoir by analysing the content of chlorophyll, pH, nitrogen, phosphorus, heavy metals, phytoplankton, macrozoobenthos and other parameters (Liu et al. 2014; Chen et al. 2011, 2012; Guang et al. 2011; Zhang et al. 2013c; Ma et al. 2012). However, few studies on DBPs and their precursors have been published to date.
In this study, organic fractions of water from the Yuqiao Reservoir and their DBPFPs were studied. The correlation degree between SUVA and SDBPFP was also analysed. The aim of this paper is to identify the primary precursors of THMs and HAAs in Yuqiao Reservoir, thereby providing support for controlling the DBPs.
Materials and methods Sample collection The water sampling points of the Yuqiao Reservoir were evenly distributed, with the grid size being defined as 10 km× 10 km (shown in Fig. 1). There were a total of 10 sampling points, in which point 1 was set at the inlet of the Lin River into the Yuqiao Reservoir, point 2 was set at the inlet of the confluence of the Li River and the Sha River into the Yuqiao Reservoir, point 10 was set at the outlet of the Yuqiao Reservoir into the Zhou River, and the rest of the points were evenly distributed around the reservoir. The water feeds into the reservoir at point 1 from the Lin River and 2 from the Sha River and Li River, flows past each point from east to west, and eventually flows out at point 10 to the Zhou River. The water was sampled five times from May to September in 2014. The sampling point was 0.5 m under the surface layer, and the samples were preserved in brown glass bottles at 4 °C and analysed within 24 h.
Fig. 1 Sampling points for water quality in the Yuqiao Reservoir
Tianjin
China Tianjin
Downtown
Yuqiao
Reservoir
Yuqiao Reservoir
Environ Sci Pollut Res Table 1
Computational formula of each DOC fraction in water sample
DOC fraction
Content (mg/L)
Percentage account in raw water
HoA HoN HoB WHoA HiM
DOC2 −DOC4 DOC1 −DOC2 −(DOC3 −DOCB)/3.5 (DOC3 −DOCB)/3.5 DOC4 −DOC5 DOC5
(DOC2 −DOC4)/DOC1 ×100 % [DOC1 −DOC2 −(DOC3 −DOCB)/3.5]/DOC1 ×100 % [(DOC3 −DOCB)/3.5]/DOC1 ×100 % (DOC4 −DOC5)/DOC1 ×100 % DOC5 /DOC1 ×100 %
DOC1 is the DOC value of raw water. DOC2 is the DOC value of water sample passed through the XAD-8 column at the first time. DOC3 is the DOC value of phosphoric acid passed through the XAD-8 column. DOC4 is the DOC value of water sample passed through the XAD-8 column at the second time. DOC5 is the DOC value of water sample passed through the XAD-4 column. DOCB is the DOC value of phosphoric acid.
As for dissolved organic carbon (DOC), DBPs and DBPFP, samples of 10 points were analysed, and the average value was used to discuss, while the isolation and fractionation of the DBP precursors were only conducted with the sample of point 6.
immediately run through the XAD-4 resin. WHoA was adsorbed by the XAD-4 resin, and HiM was left in the sample. DOC of five organic fractions in water sample is calculated by the computational formula shown in Table 1.
Analysis methods Isolation and fractionation In this study, DOC was divided into five fractions, which were categorized as hydrophobic bases (HoB), hydrophobic acids (HoA), hydrophobic neutral fractions (HoN), weakly hydrophobic acids (WHoA) and hydrophilic matter (HiM), through resin adsorption using XAD-8 resin and XAD-4 resin. The specific steps of isolation and fractionation of DOC referred to Wei et al. (2006). The XAD-8 resin and XAD-4 resin need be pretreated first to ensure that the organic matter will not be soluble from the resin. Keeping the speed of the liquids at 15 times the bed volume per hour for the whole process, the filtered sample passed through the XAD-8 column directly. After sampling, 10 times the bed volume of 0.1 mol/L phosphoric acid passed through the XAD-8 column. HoB was desorbed by phosphoric acid, while HoN was adsorbed by the XAD-8 resin column. Then, the sample effluent from the XAD-8 column was acidified to pH 2 and recycled through the XAD-8 column, and HoA was adsorbed by the XAD-8 resin. At last, the sample, which now contained only WHoA and HiM, was
Table 2
The quality of raw water
Water quality index
Range
Average value
Temperature, °C pH Turbidity, NTU Ammonia nitrogen, mg/L UV254, cm−1 DOC, mg/L
23.8–32.3 8.15–8.88 1.22–6.93 0.09–0.32 0.052–0.063 2.969–3.539
29.2 8.66 3.89 0.19 0.059 3.350
DOC, trihalomethane formation potential (THMFP), haloacetic acid formation potential (HAAFP) and SUVA were analysed in this study. Before analysis, all water samples were filtered with 0.45 μm microfiltration membrane. Four THMs and five HAAs were detected in the experiment. The four THMs are chloroform (TCM), bromodichloromethane (BDCM), dibromochloromethane (DBCM) and tribromethane (TBM). The five HAAs consisted of monochloroacetic acid (MCAA), dichloroacetic acid (DCAA), trichloroacetic acid (TCAA), bromoacetic acid (MBAA) and dibromoacetic acid (DBAA). The DOC was analysed through a total organic carbon analyser (Shimadzu TOC-VCPH). Chlorination of samples was necessary in the process of analysing both the THMFP and HAAFP. Firstly, water samples with the volume of 200 mL were put into the abrasive glass bottles respectively, and all samples were adjusted to a pH of 7.0±0.2 using 1 mol/L hydrochloric acid. Four milliliters of 0.1 mol/L phosphate, consisting of 17.025 g of potassium dihydrogen phosphate and 2.925 g of sodium hydroxide mixed in 250 mL ultrapure water, was then used to buffer the solution at pH 7. To provide a residual-free chlorine of 3– 5 mg/L to ensure the chlorination condition (Liu et al. 2009, 2011; Qiao et al. 2006), the samples was chlorinated by sodium hypochlorite (20 mg/L of available chlorine). At last, the
Table 3
DOC concentrations of raw water in the Yuqiao Reservoir
Sampling date May30 June30 July30 August 25 September 12 DOC, mg/L
2.969
3.287
3.539
3.523
3.431
Environ Sci Pollut Res 1.6
Table 5
1.4
HoB
Concentraon
1.2
The DOC concentrations in different water sources
Water source
DOC, mg/L 2.969–3.539 2.51–2.71
Reference
1.0
HoN
0.8
HoA
0.6
WHoA
Yuqiao Reservoir Reservoir water from Yellow River
HiM
Shenzhen Reservoir
1.2–2.1
Qiao et al. 2007
A typical river-type water source in the Yangtze River Delta Three reservoirs in Northern China
4.4–4.7
Huang et al. 2013
26.6–34.5
Yin et al. 2011
0.4 0.2 0.0 30 May
30 Jun
30 Jul
25 Aug
12 Sep
date
Zhang et al. 2013a, b, c
Fig. 2 The concentrations of organic fractions
samples were put into a biochemical incubator at 25±0.5 °C for 7 days in the dark (Liu 1999; Wang et al. 2001; Liu et al. 2009). The samples were analysed by liquid-liquid extraction and gas chromatography using an Agilent 6890N system and an electron capture detector equipped with an HP-5 capillary column (30.0 m×320 μm×0.25 μm) and an automatic sampler (Agilent 7683B). The specific analyses of THMs and HAAs were conducted according to optimized USEPA standard methods 551.1 (USEPA 1995a) and 552.3 (USEPA 1995b), respectively. Residual chlorine in each sample was analysed by DPD photometry after constant temperature cultivation. If residual chlorine was in the range of 3–5 mg/L, 1 g ascorbic acid was added to the water sample to terminate chlorination reaction, and 25 mL surface water was transferred to a 50-mL brown screw cap glass vial. For THMs, the sample was extracted with 12 g anhydrous sodium sulfate and 3 mL methyl tert-butyl ether (MTBE); after oscillating for 4 min and settling for 2 min, 1 mL surface organic solution was extracted to a 2-mL brown screw cap glass vial for analysis. The temperatures for the inlet and detector were 150 and 300 °C, respectively, and the oven temperature gradient began at 30 °C for 2 min and rose to 70 °C at a rate of 5 °C/min. For HAAs, the sample was extracted with 1.5 mL concentrated sulfuric acid, 12 g anhydrous sodium sulfate and 3mL MTBE. After oscillating for 3 min and settling for 3 min, 1 mL surface organic solution was extracted to a 15-mL brown screw cap glass vial, and 2 mL 10 % sulfuric acid methanol solution was added to the same vial. Then, thermostatic water bath was conducted for 1 h under 50 °C. After the water sample cooling down, adding 5 mL 10 % sodium sulfate solution and 1 mL MTBE, then oscillating for 2 min and settling for 2 min, finally 1 mL surface organic solution was extracted to a 2-mL brown screw cap glass vial for analysis. The temperatures for the injector Table 4 The monthly average temperature of Tianjin from May to September, 2014 Month
May June July August September
Average highest temperature, °C 28 Average lowest temperature, °C 17
31 22
33 25
31 23
26 18
and detector were 220 and 280 °C, respectively. The oven temperature gradient began at 40 °C for 7 min, rose to 70 °C at a rate of 5 °C/min and then rose to 250 °C at a rate of 30 °C/min (holding for 5 min). SUVA is the ultraviolet absorbance of a unit DOC concentration under 254 nm irradiation (Lee et al. 2001), calculated by the UV254/DOC ratio multiplied by 100. UV254 is analysed by ultraviolet spectrophotometer with 254 nm irradiation. Statistical analysis The results of DOC fractions, DBP precursors and UV254 were processed by EXCEL2003, and the correlation between DBPFP and SUVA was calculated by SPSS 19.0. Quality assurance All the samples and blanks were analysed in duplicates for quality assurance control of laboratory analyses in this study. Only the relative standard deviation (RSD) values below 10 % were accepted, while other samples outside this range were reanalysed. A standard reference material (SRM) GSB 071982-2005 from Institution for Environmental Reference Material Ministry of Environmental Protection was applied for calibration and analytical control. Table 6
THMs and THMFP in the Yuqiao Reservoir May 30 June 30 July 30
THMs, μg/L
TCM 4.559 BDCM 2.155
DBCM TBM Total THMFP, TCM μg/L BDCM DBCM TBM Total
0.000 0.000 6.714 133.667 13.300 5.077 0.000 152.044
August 25
September 12
9.189 2.773
17.164 2.540
16.116 2.102
15.049 1.845
2.037 0.000 13.998 246.049 124.099 9.142 0.000 379.291
0.000 0.000 19.704 266.359 156.562 12.378 0.000 435.299
1.058 0.000 19.277 261.342 154.889 8.971 0.000 425.202
2.040 0.000 18.935 195.835 39.178 7.985 0.000 242.998
Environ Sci Pollut Res Table 7
The THMFP in different water sources
Table 8 fraction
Source water
THMFP, μg/L
Reference
Yuqiao Reservoir A typical river-type water source in the Yangtze River Delta The raw water from Nanjing Water Treatment Plant The Sacramento River, California
152.0–435.3 130–182
Huang et al. 2013
90
Shang et al. 2005
156–196
Chow et al. 2007
The San Joaquin River, California
392–490
Chow et al. 2007
Australian source waters
199–522
Fabris et al. 2008
Southeast of Norwegian source waters Buyukcekmece Lake
846
Fabris et al. 2008
126–1535
Aydin et al. 2012
THMs and HAAs were identified relative to external standards. Recoveries of SRM and external stands varied from 91.2 to 94.5 %. In addition, SRM was continuously diluted and analysed until the peak is a signal-to-noise ratio (S/N) of 3, and the corresponding concentration was regarded as the detection limit, which was 0.01 μg/L for the four kinds of THMs and the five kinds of HAAs. Chemicals The chemicals were all purchased from chemical network management platform of Tianjin University (http://219.243. 47.181/chem).
Results and discussion The quality of raw water in Yuqiao Reservoir during the sampling period was shown in Table 2. Classification results of DOC in the Yuqiao Reservoir The DOC concentrations in the Yuqiao Reservoir during the sampling period are shown in Table 3, and the isolation results of DOC are shown in Fig. 2. The results showed that DOC
The concentration of four kinds of THMs in each DOC TCM, μg/L
BDCM, μg/L
DBCM, μg/L
TBM, μg/L
HoB HoN HoA WHoA
0.872–3.314 0.991–3.464 1.143–3.511 0.416~3.399
0.34–0.55 0.351–0.561 0.388–0.579 0.376~0.52
0–0.312 0–0.316 0–0.373 0~0.498
0 0 0 0
HiM
1.137~3.487
0.39~0.563
0~0.687
0
concentrations of raw water in the Yuqiao Reservoir fluctuated temporally. The average value was 3.350 mg/L. The maximum value appeared in July 30, and the lowest value appeared in May 30, which is consistent with the temperature variation (Table 4). Compared to other source waters (Table 5), DOC in the Yuqiao Reservoir was at medium level. The results indicate that HoA and HiM, with percentages of 27.6–40.9 and 21.2–32.5 %, respectively, were the primary organic fractions. Our results are consistent with Huang (2013) and Qiao et al. (2006), but different from Yin et al. (2011) and Marhaba and Van (2000). The HoN concentration was close to the WHoA concentration, while the HoB concentration was the lowest of the five fractions, with a contribution of less than 10 %. In May, June and September, the order of the concentration levels was HoA > HiM > HoN > WHoA > HoB, while in July and August, the order turned into HiM > HoA > WHoA > HoN > HoB, which showed that the HiM concentration increased in July and August. Identification of THM precursors in Yuqiao Reservoir The THMs of raw water and corresponding THMFP in Yuqiao Reservoir during the sampling period were shown in Table 6. The THMs in raw water during sampling period were between 6.714 and 19.704 μg/L, in which TCM concentration was the highest, BDCM concentration was the second highest, DBCM concentration was the lowest, and TBM was not
250
180 160
200
140
HoB
HoN
120
HoN
100
HoA 100
WHoA HiM
50
STHMFP
THMFP
150
HoB
HoA
80 60
WHoA
40
HiM
20 0
0 30 May
30 Jun
30 Jul
25 Aug
date
Fig. 3 THMFPs of the five organic fractions
12 Sep
30 May
30 Jun
30 Jul date
Fig. 4 STHMFP of organic fractions
25 Aug
12 Sep
Environ Sci Pollut Res 180
35%
160
(%
25% 20%
140
HoB
HoN
120
HoN
HoA
15%
WHoA
10% STHMFP
HoB
100 HAAFP
30%
HiM
5%
HoA
80 60
WHoA
40
HiM
20 0
0% 30 May
30 Jun
30 Jul
25 Aug
30 May
12 Sep
30 Jun
30 Jul
25 Aug
12 Sep
date
date
Fig. 5 STHMFP percentage of organic fractions
Fig. 6 HAAFPs of organic fractions
detected. The corresponding THMFP concentrations were ranged from 152.044 to 435.299 μg/L. Both THMs and THMFP were all changed temporally, the highest values of which occurred in July and August, while the lowest values appeared in May. Compared with other source waters (Table 7), THMFP in Yuqiao Reservoir was at a medium level. The THMFP of the five organic fractions during the sampling period are shown in Fig. 3 and Table 8. HoA had the highest THMFP (69.9–196.5 μg/L), accounting for 35.8– 51.8 % of the total THMFP of the five organic fractions. Next was HiM, whose THMFP contribution was between 19.6 and 32 %. Because of their high THMFP, HoA and HiM were the primary precursors of THMs in the Yuqiao Reservoir, comprising approximately 70 % of the total. The THMFP of WHoA, HoN and HoB decreased orderly, and the lowest contribution was only 1–1.7 %. Moreover, the THMFP of the five organic fractions were usually higher in July and August, indicating that the Yuqiao Reservoir had a higher concentration of THM precursors in July and August. The ability to generate THMs of different organic fractions was evaluated by the specific trihalomethane formation potential (STHMFP) (the ratio of THMFP to DOC). The STHMFP of the organic fractions and their percentages are shown in Fig. 4 and Fig. 5, respectively. Figure 4 shows that the STHM
FP varied with the sampling date, and the higher values appeared from June to August. By contrast, the STHMFP percentages of the different organic fractions (shown in Fig. 5) were relatively stable during the sampling period. Among the five organic fractions, HoA had the highest STHMFP, with values ranging from 64.8 to 159.5 μg/mg, 29.7 to 30.9 % of the total, meaning that HoA was the primary THM precursor. This conclusion was consistent with the findings of Huang et al. (2013) and Yuan (2012), but different from Yin et al. (2011). If the organics were only classified by hydrophilicity and hydrophobicity, the STHMFP of HoM would be between 108.6 and 265.9 μg/mg, 49.7–51.9 % of the total STHMFP. The above results illustrate that HoM was the primary THM precursors, which is consistent with most studies (Yin et al. 2011; Huang et al. 2013; Yuan 2012; Qiao et al. 2006). The STHMFP of WHoA was lower than that of HoM, and the STHMFP of HiM was the lowest.
Table 9 HAAs and HAAFP in the Yuqiao Reservoir HAAs, μg/L
HAAFP, μg/L
MCAA DCAA TCAA MBAA DBAA Total MCAA DCAA TCAA MBAA DBAA Total
Identification of HAA precursors in the Yuqiao Reservoir The HAAs of raw water and corresponding HAAFP in Yuqiao Reservoir during the sampling period were shown in Table 9. The five components were all detected, in which DCAA and TCAA were the major matter. Generally, brominated HAAs
May 30
June 30
July 30
August 25
September 12
3.430 6.357 5.863 1.067 1.463 18.18 44.761 81.217 79.776 3.881 12.210 221.844
4.942 9.709 8.645 0.726 1.643 25.666 63.059 113.448 102.650 3.687 12.657 295.502
6.319 9.955 8.837 1.154 1.023 27.288 68.980 177.890 114.588 4.233 15.313 381.004
6.112 9.803 8.251 0.714 1.036 25.916 64.729 173.594 112.284 3.901 14.641 369.149
5.142 9.235 7.060 0.633 1.688 23.758 58.186 115.692 103.945 3.765 14.331 295.919
Environ Sci Pollut Res Table 10 The concentration of five kinds of HAAs in each DOC fraction HoB HoN HoA WHoA HiM
MCAA, μg/L
DCAA, μg/L
TCAA, μg/L
MBAA, μg/L
DBAA, μg/L
0.680–1.157 0.45–1.128 0.96–1.486 0.61–1.209 0.73–1.416
1.168–1.762 1.147–1.729 1.457–2.608 1.136–1.876 1.449–2.485
1.035–1.528 1.198–1.739 1.261–2.042 1.132–1.598 1.237–2.28
0.094–0.227 0.129–0.225 0.112–0.217 0.107–0.199 0.163–0.305
0.182–0.316 0.174–0.306 0.191–0.335 0.144–0.297 0.311–0.499
were less than chlorinated HAAs. During sampling period, the HAAs were always higher than THMs in the raw water, while the temporal variations of HAAs and HAAFP were the same as THMs and THMFP. The HAAFPs of the five organic fractions in Yuqiao Reservoir during the sampling period are shown in Fig. 6 and Table 10. The results show that HAAFP was detected in all organic fractions. The HAAFP of HoA was from 113.1 to 164.3 μg/L, representing 41.4–55.6 % of the total, indicating that approximately half of the HAAs in the Yuqiao Reservoir are generated by HoA. HiM was the second-highest fraction of the HAAFP, accounting for 21.7–34.1 % of the total. Consequently, HoA and HiM are the two primary precursors of HAAs in the Yuqiao Reservoir. The HAAFPs of WHoA and HoN were very close, and the maximum difference between them was only 3.6 % during the sampling period. HoB had the lowest HAAFP, representing less than 1 %, illustrating that HoB had little impact on HAAs. These results are similar to Wu (2006). In addition, Fig. 6 shows that the HAAFPs were higher in most organic fractions in July and August, which was slightly different from the THMFP distributions of the five organic fractions. The specific haloacetic acid formation potential (SHAAFP) of the five organic fractions in the Yuqiao Reservoir during the sampling period are shown in Fig. 7, and their percentages are shown in Fig. 8. The SHAAFPs fluctuated temporally, but their percentages were stable. The SHAAFP of HoA was the highest, and its percentage was between 35.1 and 37.3 %, indicating that HoA was the primary HAAs precursor. This conclusion is consistent with Huang et al. (2013) and Lu et al.
(2009). The SHAAFP percentage of HiM was approximately 10 % lower than that of HoA, showing that the ability of HiM to generate HAAs was slightly lower than that of HoA. The SHAAFPs of WHoA and HoN were close, as were the SHAA FP percentages. HoB had the lowest SHAAFP, indicating that the ability of HoB to generate HAAs was weak. The THMs and HAAs were added together to analyse the primary precursors of DBPs, and the results showed that the order of DBPFP of the five organic fractions was HoA > HiM > WHoA > HoN > HoB, as was the SDBPFP. This suggests that HoA is the primary precursor of DBPs among the five organic fractions. The ability of an organic fraction to generate DBPs can be changed. Although the DOC in water was already classified by the resin adsorption method, the composition of each organic fraction was still complex. The functional groups contained in each organic fraction change with water quality, so the ability of an organic fraction to generate DBPs may vary. Correlation analysis between SUVA and SDBPFP SUVA is the ultraviolet absorbance of a unit DOC concentration under 254 nm irradiation (Lee et al. 2001), calculated by the UV/DOC ratio multiplied by 100. SUVA can reflect some characteristics of organic matter in water, such as humification degree and the relative content of unsaturated double bonds or aromatic organic compounds (Imai et al. 2001). Some studies have indicated that SUVA is significantly correlated
180
40%
160 120
HoN
25%
HoN
HoA
20%
HoA
60
WHoA
15%
WHoA
40
HiM
20
SHAAFP
80
(%
HoB
100 SHAAFP
35%
140
HoB
30%
10%
HiM
5% 0%
0 30 May
30 Jun
30 Jul date
Fig. 7 SHAAFPs of organic fractions
25 Aug
12 Sep
30 May
30 Jun
30 Jul
25 Aug
date
Fig. 8 SHAAFP percentages of organic fractions
12 Sep
Environ Sci Pollut Res Table 11
SUVA of raw water during the sampling period
Sampling date
Results of correlation analysis between SUVA and SHAAFP
Table 14
May30 June30 July30 August 25 September 12
SUVA, L/(m·mg) 1.75
1.76
1.75
1.79
SUVA
1.72
SHAAFP 2.5 2.0
HoB HoN
1.5 SUVA
HoA 1.0
30 May
30 Jun
30 Jul
25 Aug
12 Sep
date
Fig. 9 SUVA of organic fractions
STHMFP
1
.765** .000 496.864 20.703 25 1
8.730 .364 25 .765** .000 496.864 20.703 25
48,297.695 2012.404 25
**Correlation is significant at the 0.01 level (two-tailed)
HiM
0.0
SUVA
SHAAFP
WHoA
0.5
Table 12 STHMFP
Pearson correlation Sig. (two-tailed) Sum of squares and cross-products Covariance N Pearson correlation Sig. (two-tailed) Sum of squares and cross-products Covariance N
SUVA
Results of the correlation analysis between SUVA and SUVA
STHMFP
Pearson correlation Sig. (two-tailed) Sum of squares and cross-products Covariance N Pearson correlation Sig. (two-tailed)
1
.766** .000 523.172 21.799 25 1
Sum of squares and cross-products Covariance N
523.172 21.799 25
8.730 .364 25 .766** .000
53,424.523 2226.022 25
**Correlation is significant at the 0.01 level (two-tailed)
Table 13 The function between SUVA and STHMFP
Equation
with the ability of organic matter to generate DBPs (Kitis et al. 2002). Table 11 shows the SUVA of raw water during the sampling period, and Fig. 9 shows the SUVA of each organic fraction. The SUVA of raw water and those of the five organic fractions were stable during the sampling period. In the Yuqiao Reservoir, the organic acids had the highest value of SUVA, indicating that the organic acids not only had the highest humification degree but were also a major source of unsaturated double bonds or aromatic organic compounds. A correlation analysis by IBM SPSS statistics 19 was conducted to investigate the correlation degree between SUVA and DBPFP. The results (Table 12 and Table 13) show that SUVA and STHMFP have a moderately positive correlation (the Pearson coefficient was between 0.5 and 0.8), with a significant correlation at the 0.01 level (the two-tailed significant value was less than 0.01). The results of the correlation analysis between SUVA and SHAAFP are shown in Table 14 and Table 15. The SUVA and SHAAFP had a moderately positive correlation as well (the Pearson coefficient was between 0.5 and 0.8), which was also significant at the 0.01 level (the two-tailed significant value was less than 0.01). The above results illustrate that SUVA has some correlation with SDBPFP, but the two parameters were not precisely
Model summary R2
F
Parameter estimation Sig.
Constant
STHMFP coefficient
Value
t
Sig.
Value
t
Sig.
Linear Index
0.587 0.582
32.672 31.994
.000 .000
0.529 0.008
3.290 5.656
.003 .000
0.010 0.609
5.716 7.397
.000 .000
Logistic
0.582
31.994
.000
1.641
7.397
.000
0.992
694.154
0.000
Environ Sci Pollut Res Table 15 The function between SUVA and SHAAFP
Equation
Model summary R2
F
Parameter estimation Sig.
Constant
STHMFP coefficient
Value
t
Sig.
Value
t
Sig.
Linear Index
0.586 0.562
32.491 29.568
.000 .000
0.570 0.637
3.680 7.517
.001 .000
0.010 0.008
5.700 5.438
.000 .000
Logistic
0.562
29.568
.000
1.570
7.517
.000
0.992
645.288
0.000
aligned. Therefore, SUVA can be used as a reference index to analyse the ability of organic matter to generate DBPs but cannot completely replace SDBPFP.
Conclusions The DOC, DBPs and DBPFP were all detected in water from Yuqiao Reservoir during the sampling period, and the results show that (1) except for TBM, nine kinds of DBPs and corresponding DBPFP were all detected. TCM, DCAA and TCAA have higher concentration and formation potentials; (2) compared with other surface water sources, DOC, THMFP and HAAFP in water from Yuqiao Reservoir are at a medium level; (3) the concentration of DOC, THMFP and HAAFP were relatively higher from June to September. The primary precursors of both THMs and HAAs in the Yuqiao Reservoir were identified, and the results indicate that (1) HoA and HiM are the primary organic fractions in Yuqiao Reservoir, accounting for 27.6–40.9 and 21.2–32.5 % of the total DOC, respectively; (2) HoA is the primary precursor of THMs and HAAs in Yuqiao Reservoir; and (3) SUVA and SDBPFP have a moderately positive correlation. Based on this study, the further research should focus on the influence factors of organic fractions and the control methods of the DBPFP in the source water. Acknowledgments This project was supported by the National Science Foundation of China (51308305), the Major Projects of the National Water Pollution Control and Treatment Technology of China (2014ZX07203-009), and the Program for New Century Excellent Talents in University of China.
References Aydin E, Yaman FB, Genceli EA, Topuz E, Erdim E, Gurel M, Ipek M, Pehlivanoglu-Mantas E (2012) Occurrence of THM and NDMA precursors in a watershed: effect of seasons and anthropogenic pollution. J Hazard Mater 221–222:86–91 Chen SR, Wu GH, Su RX (2011) Change characteristics of water quality and its impact factor at the Yuqiao Reservoir in Tianjin. Water Resour Prot 27(27–30):34
Chen YY, Zhang C, Gao XP, Wang LY (2012) Long-term variations of water quality in a reservoir in China. Water Sci Technol 65:1454– 1460 Chow AT, Dahlgren RA, Harrison JA (2007) Watershed sources of disinfection byproduct precursors in the Sacramento and San Joaquin Rivers, California. Environ Sci Technol 41: 7645–7652 Croué JP, Violleau D, Labouyrie L (2000) Disinfection by-product formation potentials of hydrophobic and hydrophilic natural organic matter fractions: a comparison between a low- and a high-humic water. American Chemical Society, Washington, DC Fabris R, Chow CWK, Drikas M, Eikebrokk B (2008) Comparison of NOM character in selected Australian and Norwegian drinking waters. Water Res 42:4188–4196 Guang HW, Shan SC, Shui RC, Fang TC (2011) Accumulation and remobilization of metals in superficial sediments in Tianjin, China. Environ Monit Assess 173:917–928 Hong HC, Xiong YJ, Ruan MY, Liao FL, Lin HJ, Liang Y (2013) Factors affecting THMs, HAAs and HNMs formation of Jin Lan Reservoir water exposed to chlorine and monochloramine. Sci Total Environ 444:196–204 Huang H, Cheng ZP, Lin F, Li Q, Fei XQ, Jiang GC, Xu JM (2013) Species distribution characteristic of organic matters in the rivertype water source and its relationship with disinfection by-products. Resour Environ Yangtze Basin 22:1602–1607 Imai A, Fukushima T, Matsushige K, Kim YH (2001) Fractionation and characterization of dissolved organic matter in a shallow eutrophic lake, its inflowing rivers, and other organic matter sources. Water Res 35:4019–4028 Kitis M, Karanfil T, Wigton A, Kilduff JE (2002) Probing reactivity of dissolved organic matter for disinfection by-product formation using XAD-8 resin adsorption and ultrafiltration fractionation. Water Res 36:3834–3848 Kitis M, Karanfil T, Kilduff JE (2004) The reactivity of dissolved organic matter for disinfection by-product formation. Turkish J Eng Env Sci 28:167–179 Lee KJ, Kim BH, Hong JE, Pyo HS, Park SJ, Lee DW (2001) A study on the distribution of chlorination by-products (CBPs) in treated water in Korea. Water Res 35:2861–2872 Liu WJ (1999) Study on characteristics of biodegradable organic matter and disinfection by-products in drinking water. Dissertation of Tsinghua University, China Liu WL (2007) Analysis of correlation between coneentration of trihalomethanes and genetietoxieity in drinking water. Environ Sci Manag 32(45–46):53 Liu J, Chen C, Zhang XJ (2009) Disinfection by-products reduction of combined disinfection by chlorine and monochloramines in distribution system. Environ Sci 30:2538–2542 Liu YF, Wang QS, Yue SC, Li SS, Zhang YR, Lu JF (2011) Analysis of disinfection by-product precursors based on hydrophobicity and molecular weight. Water Wastewater Eng 37:128-132
Environ Sci Pollut Res Liu XB, Dong F, He GJ, Liu JL (2014) Use of PCA-RBF model for prediction of chlorophyll-a in Yuqiao Reservoir in the Haihe River Basin, China. Water Sci Technol-Water Supply 14:73–80 Lu JF, Zhang T, Ma J, Chen ZL (2009) Evaluation of disinfection byproducts formation during chlorination and chloramination of dissolved natural organic matter fractions isolated from a filtered river water. J Hazard Mater 162:140–145 Ma XJ, Shen JZ, Sun JH, Wang HS, Zhang K (2012) Macrozoobenthos community structure and water quality evaluation of Yuqiao Reservoir in Tianjin, North China. Chinese J Ecol 31:2356–2364 Marhaba TF, Van D (2000) The variation of mass and disinfection byproduct formation potential of dissolved organic matter fractions along a conventional surface water treatment plant. J Hazard Mater 74:133–147 Nieuwenhuijsen MJ, Toledano MB, Elliott P (2000) Uptake of chlorination disinfec-tion by-products: a review and a discussion of its implications for exposureassessment in epidemiological studies. J Expo Anal Environ Epidemiol 10:586–599 Qiao CG, Wei QS, Wang DS, Liu LJ, Huang XD, Zhang JS, Wei Q, Li MJ (2006) Fractionation and characterization of DOM and the THMFP feature in the South-China source water. Acta Scien Circum 26:944–948 Qiao CG, Wei QS, Wang DS, Yang M, Wei Q, Li MJ (2007) Molecular weight distribution and removal characters of DOM in the typical source water in south of China. Acta Scien Circum 27:195–200 Reckhow DA, Singer PC, Malcolm RL (1990) Chlorination of humic materials: by-product formation and chemical interpretations. Environ Sci Technol 24:1655–1664 Shang DH, Wang ZP, Zhang ZS (2005) Study on influence factor of trihalomethanes formation in drinking water. J East China Shipbuild Institute (Natural Science Edition) 19:91–93 Tardiff RG, Carson ML, Ginevan ME (2006) Updated weight of evidence for an association between adverse reproductive and developmental effects and exposureto disinfection by-products. Regul Toxicol Pharm 45:185–205
USEPA (1995a) Determination of chlorination disinfection by-products, chlorinated solvents, and halogenated pesticides/herbicides in drinking water by liquid-liquid extraction and gas chromatograph with electron-capture detection (Method 551.1) USEPA (1995b) Determination of haloacetic acids and dalapon in drinking water by liquid-liquid microextraction, derivatization, and gas chromatography with electron-capture detection (Method 552.3) Villanueva CM, Cantor KP, Cordier S, Jaakkola JJ, King WD, Lynch CF, Porru S, Kogevinas M (2004) Disinfection byproducts and bladder cancer: a pooledanalysis. Epidemiology 15:357–367 Wang LH, Zhou H, Zhang XJ, Wang ZS (2001) Characteristics and chlorination activity of dissolved organic matter fractions in surface source water. Acta Scien Circum 21:573–576 Wei QS, Wang DS, Yu JF, Liu HL, Han HD, He WJ (2006) Mechanism and method for chemical fractionation of dissolved organic matter in water. Techniques Equip Environ Poll Control 7(17–21):82 Wu HH (2006) Study on formation characteristics and removal mechanism of disinfection by-products during prechlorination. Dissertation of Tongji University, China Yin J, Zhou X, Lin YZ, Wang X (2011) Chemical fractionation of organic matters and THMFP characterization in north reservoir water. China Water Wastewater 27:83–86 Yuan XH (2012) Study on the chlorinated disinfection by-products of the raw water from water plants in Fuzhou. Master Dissertation of Fujian Normal University, China Zhang Y, Zhai RC, Wang CC (2013a) Study on vulnerability assessment of reservoir-type water source. J Water Resour Water Eng 24:5–9 Zhang YH, Wang M, Yu J, Xing LZ, Liu JG (2013b) Study on characteristics of dissolved organic carbon in reservoir water from Yellow River. J Shandong Jianzhu University 28:27–30 Zhang Z, Bian SW, Mei PY, Wu D, Wang HY, Wang M (2013c) Correlation between phytoplankton abundance and environmental factors in Yuqiao Reservoir. Ecol Sci 32:594–598 Zhao SJ, Gao NY, Jiang FC, Li Q, Chu WH (2011) Influence of the characterstics of organic matter in reservior water on the formation of DBPs. Water Wastewater Eng 37:119–124
