Characteristics of disinfection by-products precursors removal from micro-polluted water by constructed wetlands

Characteristics of disinfection by-products precursors removal from micro-polluted water by constructed wetlands

Ecological Engineering 93 (2016) 262–268 Contents lists available at ScienceDirect Ecological Engineering journal homepage: www.elsevier.com/locate/...

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Ecological Engineering 93 (2016) 262–268

Contents lists available at ScienceDirect

Ecological Engineering journal homepage: www.elsevier.com/locate/ecoleng

Characteristics of disinfection by-products precursors removal from micro-polluted water by constructed wetlands Yuli Yang a,1 , Jilai Lu b,∗,1 , Haikuan Yu c , Xiaoli Yang b a b c

College of Civil Engineering, Southeast University, Nanjing 210096, China Jiangsu Provincial Academy of Environmental Science, Nanjing 210036, China Department of Environmental Engineering, Hohai University, Nanjing 210098, China

a r t i c l e

i n f o

Article history: Received 2 January 2016 Received in revised form 9 March 2016 Accepted 7 May 2016 Keywords: Constructed wetlands Disinfection by-products formation potential Micro-polluted water Interval of molecular weight Yangtze river

a b s t r a c t The goal of this research was to investigate the performance of constructed wetlands (CWs) for the removal of dissolved organic carbon (DOC) and access the possible, formation of disinfection by-products (DBPS ) after CWs treatment. A mixture of raw water from Yangtze River was spiked directly into pilotscale CWs to assess impacts on various factors, including the removal of DOC, ultraviolet absorbance at 254 nm (UV254 ), specific ultraviolet Absorbance (SUVA), disinfection by-products formation potential (DBPFP), trihalomethane formation potential (THMFP), and haloacetic formation potential (HAAFP). The average removal of CODMn , NH4 + -N, TN, DOC, UV254 , THMs, and HAAs were 38.40%, 41.70%, 25.90%, 30.96%, 47.58%, −20.52%, and 25.22% respectively. CWs could degrade complicated organic matter into those with lower molecular weight, but could not further change to carbon dioxide and water. The average molecular weight of THMs in effluent flow declined to the level below, and high molecular weight organic compounds were more likely to form HAAs. The SUVA had no obvious relationships with the removal of specific trihalomethane formation potential (STHMFP), but had apparent relationship with the removal of specific haloacetic formation potential (SHAAFP) in CWs (p < 0.5), suggesting that aromatic moieties had a higher apparent propensity to form HAAs than THMs. © 2016 Elsevier B.V. All rights reserved.

1. Introduction Constructed wetland (CWs) is an effective method to decline pollutants for drinking source water. However, it can also increase secondary pollutants such as disinfection by-products precursors. Yangtze River is the third longest River in the world, which supply about 40.00% of drinking water for China. So it is very important to investigate the Characteristics of pretreatment of drinking water for Yangtze River. Dissolved organic carbon (DOC) is ubiquitous in micro polluted water, which contains chemical oxygen demand CODMn below 10 mg L−1 (Sagbo et al., 2008), and is categorized into two main origins: natural organic matter (NOM) and synthetic organic contaminants (SOCs). The presence of DOC, especially for SOCs, in source water for drinking purpose can cause the formation of disinfection by-products (DBPs) and increase chlorine demand in the disinfection process (Hua and Reckhow, 2007; Wang et al., 2013). DBPs, including trihalomethanes (THMs) and

∗ Corresponding author. E-mail address: [email protected] (J. Lu). 1 These authors contribute equally to this work. http://dx.doi.org/10.1016/j.ecoleng.2016.05.022 0925-8574/© 2016 Elsevier B.V. All rights reserved.

haloacetic acids (HAAs) are potentially toxic and may cause severe health effects (Gan et al., 2015; Grellier et al., 2015). Previous studies have demonstrated that numerous DBPs can be controlled in drinking water systems through physical and chemical treatment processes and biodegradation such as enhanced coagulation, filtration and certain disinfection processes (Bond et al., 2011; Chu et al., 2011; Roccaro et al., 2014; Chu et al., 2015). Furthermore, due to the size of precursors affects the formation of DBPs, molecular weight (MW) of DOM are important properties in drinking water treatment processes (Nissinen et al., 2001). Many different techniques have been used to measure the MW of DOM. High-performance size-exclusion chromatography (HPSEC), which provides a rapid analysis of the water samples at different stages of treatment, is one of those techniques (Bolea et al., 2006; Nissinen et al., 2001). However, no consistent trend has been observed with respect to DBP formation from individual MW fractions (Hua and Reckhow, 2007). Therefore, in order to best control the formation of potentially hazardous DBPs. A better understanding of characteristic of source water, including the molecular weight (MW) of DOM, DBPs formation, and its relationship could assist in the utilities to minimize the DBP concentrations.

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However, using coagulation, sedimentation or filtration has high cost and biotransformation during biodegradation treatment produces new DBP precursors in the form of soluble microbial products (SMPs) (Wei et al., 2013). Therefore, effective removal of DOC and the precursor of DBPs, is one of the major challenges during drinking water pretreatment. There is no single parameter which can provide a complete characterization of NOM. Instead, several surrogate parameters, including DOC, ultraviolet absorbance at 254 nm (UV254 ), specific ultraviolet absorbance (SUVA) and DBP Formation Potential (DBPFP), are used to describe properties of DBP precursors (Uyak et al., 2008). In recent years, CWs including biological, chemical, and physical processes have been introduced as a cost-efficient approach to treat wastewater (Braeckevelt et al., 2008; Huang et al., 2012). Enhanced microbial activity in the plant’s rhizosphere of CWs can provide an effective contaminant degradation zone to deal with DBPs in drinking water (Truu et al., 2009), which because microorganisms play a critical role in decomposition (Wu et al., 2015; Wu et al., 2013; Zeng, 2015). However, the majority of previous studies have only focused on treating DBPs and there are a few reports about removal of precursor of DBPs treated by CWs. Previous studies have showed the typical 13.00–49.00% DOC reduction in the CWs, depending on season (Kraus et al., 2008). In addition, Tian et al. reported that MBR could only remove 19.40% of DOC and 16.40% of UV254 when used for drinking water treatment (Tian et al., 2008). It was thus significantly seen that the CWs had a better removal efficiency for precursor of DBPs. This study was conducted mainly to quantitatively investigate the effect of CWs on the formation of DBPs-precursor, and the relationship between SUVA and SDBPFP, STHMFP, SHAAFP among different interval of molecular weight was investigated to reach perfect DBPs-precursor removal.

2. Materials and methods 2.1. Constructed wetlands A pilot scale CWs was set up along the riverbank of Yangtze River, which is an important drinking water source, located in the southeast of China, approximately 50 km from the estuary (Fig. 1). This system combined vertical flow CWs (VFCWs) with surface flow CWs (SFCWs) in series. The VFCWs was 6 m long, 3 m wide and 0.45 m high. This unit consisted of a filter medium which generally had a coal cinder transition layer and a gravel drainage layer, separated into four cells in parallel. To better understand characteristics of DBP precursors removal by CWs, hydraulic retention time (HRT) of 1.07 m3 m−2 d−1 and water sampled in summer time, which contributed to improving the removal of DBP precursors, was used from our pervious researches. Moreover, with the same reason, Acorus calamus, which could get from local markets, was chosen as the emergent plants of CWs with a density of two plants per square meter. These plants were harvested once a year, and the rotting plant were used to compost. The SFCWs were 6 m long, 3 m wide and 0.45 m high (Fig. 2). The raw surface water was collected from Yangtze River (Table 1).

2.2. Analytical techniques The water was sampled in June to July under normal operating conditions. NH4 + -N, TN, and CODMn were measured according to Chinese State Environmental Protection Agency (SEPA) Standard Methods. UV254 was measured with a UV 2550 spectrophotometer (Shimadzu, Japan) in a quartz cell with 1 cm optical path length. DOC was determined by a TOC analyzer (TOC-VCPH, Shimadzu, Japan).

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Table 1 characteristics of raw water. Water quality parameters

range

Temperature (◦ C) pH CODMn (mg L−1 ) NH3 N (mg L−1 ) TN (mg L−1 ) TP (mg L−1 ) UV254 (cm−1 ) TOC (mg L−1 ) SUVA(mg L−1 m−1 )

20.8–31.6 7.63–8.04 3.15–6.25 0.26–1.42 0.27–1.20 0.01–0.08 0.06–0.14 4.01–7.38 1.67–2.43

Table 2 Concentration of water quality indicators in CWs (mean, n = 6).

Influence(mg L−1 ) Effluence(mg L−1 ) Removal (%)

CODMn

NH3 -N

5.45 ± 0.24 3.33 ± 0.14 38.39 ± 2.50

0.55 ± 0.04 0.29 ± 0.11 41.67 ± 2.56

TN 0.48 ± 0.09 0.36 ± 0.05 25.94 ± 1.87

THMs and HAAs were determined following USEPA method 551.1 with gas chromatography-electron capture detector (GCECD) (Agilent 6890N, USA) equipped with a capillary column. Residual chlorine was determined according to DPD/FAS titration method (Anipsitakis et al., 2008). For the measurement of volatile DBPs, experiments were conducted in duplicate under heads pacefree conditions in 50 mL glass screw-cap vials. For the experiments of DBP formation as a function of pH, triplicate samples were performed to ensure the data quality in this study. A chlorine dose of 1 mg L−1 under the temperature of 298 K was added into a bensulfuron-methyl solution (0.09 mol L−1 ), which was buffered at pH 7 using 10 mM monopotassium phosphate. Molecular weight (MW) distribution was measured in ultrafiltration with different size. The separated compounds were detected by UV absorbance at 254 nm. The MW distribution pattern was derived by calibration with poly-styrene sulphonate MW standards of 14, 7.5, 4.3, 1.4, 0.7, 0.5 and 0.21 kDa. Statistical tests were calculated by SPSS software; p < 0.05 was considered statistically significant. Samples were treated as replicates for examination of differences using oneway ANOVA, performed in Sigmaplot (San Jose CA, USA). 3. Results and discussion 3.1. Pollutants removal As the concentration of pollutant in the influent varied, the removal rates of pollutants in the CWs showed certain fluctuations. The average removal rates of CODMn , NH4 + , and total N were 38.40%, 41.70%, and 25.90%, respectively (Table 2). In addition to total P, the system was adaptable to fluctuation in water quality and had acceptable removal ability. According to the Chinese National Standards for Drinking Water Quality (CNSDWQ, GB5749-2006), which regulated a maximum contamination level of 3.0 mg L−1 for CODMn and 0.5 mg L−1 for NH4 + , the effluent with acceptable concentration NH4 + could be achieved. The previous studies showed that the removal of CODMn in CWs generally ranged in 80.00%–90.00% (Doherty et al., 2015; Silveira et al., 2015; Zhang et al., 2015), but own to the low concentration of organic matter in raw water, the amount of available organic carbon to microorganisms was relatively low, and the purification of organic matter was adopted by aerobic bacteria with poor nutrition, where heterotrophic bacteria played an important role in CODMn removal (Huang et al., 2012). Thus, the CODMn removal was not significant. As dissolved oxygen (DO) in the system was consumed quickly, the process of ammonia oxidation was limited. Moreover, nitrogen removal in CWs was affected by the temperature

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Fig. 1. The location of pilot test.

Fig. 2. A schematic diagram showing two different types of constructed wetlands, including vertical flow (left side), surface flow (right side).

(Akratos and Tsihrintzis, 2007). The optimum temperature for nitrification in the CWs usually ranged from 15 ◦ C to 25 ◦ C, Ammonia volatilization increased 1.3–3.5 times with each 10 ◦ C rising in temperature from 0 ◦ C to 30 ◦ C (Truu et al., 2009; Zhang et al., 2015). However, due to the onset of summer, which caused enhanced surface temperature up to 40 ◦ C, microbial diversity was consequently damaged. Due to low-level organic matter, the number of denitrification bacteria, which were heterotrophic anaerobic bacteria, was inhibited and the removal of total N was limited (Ovez et al., 2006). 3.2. Characteristics of MW distribution of DOC fractions The difference of chemicals and structures of MW distribution of DOC fractions could cause the different ability to generate DBPs.

The average concentration of DOC in raw water were 6.22 mg L−1 , and the majority of MW distribution of DOC fractions were low molecular weight (LMW, <1 kDa), which was 42.42% of raw water (Fig. 3). Majority of DOC from Yangtze River was long-chain hydrocarbons, which was caused by human activities (Kim and Yu, 2005; Zhao et al., 2006). Wong found that low molecular weight compounds were strongly hydrophilic (Wong et al., 2002), while more high molecular weight compounds are related to hydrophobicity of DOC fractions, which could form more THMFP than hydrophilic part of DOC fractions (Klymenko et al., 2010). In all 6 samples for each DOC concentration, the effluent had significantly lower value than influent (p < 0.003; ANOVA), and the average removal rate of DOC in effluent was 30.96%, suggesting that CWs had limited abilities to remove the organic

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DOC(mg L-1)

5

60 50

4

40

3

30

2

20

DOC removal(%)

6

the percentage of composition of THMs(%)

70

influent effluent DOC removal

1 10 0 K K K K K C m < 1 tal TO 45 µ 100 ~ 10 0 K ~ 3 3 K ~ 1 > 0. µm ~ 10 0 K 1 To 5 4 0.

0

MWD(Da)

Fig. 3. MW distribution of DOC in raw water and effluent flow (mean value, n = 6).

4.0

influent SUVA effluent SUVA

3.5 3.0 2.5 2.0 1.5 1.0 0.5

0.00 ~ 10

SUVA (L mg-1 m-1)

UV254 (cm-1)

effluent UV254

0.02

µm 0.45

0K 10 K K ~ 3 K K ~ 1 K K~ 3 10 10 0

80

TCM

DCBM

influent THMs

DBCM

TBM

effluent THMs

70

35 30 25

60

20

50

15

40 30

10

20 5

10 0

0

K 0K 3K 0K ~1 ~ 10 0 K ~ 1 10 K ~ 3K m µ 0 1 .45

<1

K

MWD(Da)

Fig. 5. MW distribution of THMs component in raw water and effluent flow (mean, n = 6).

4.5

influent UV254 0.04

90

THMs(ug L` )

7

265

<1

K

MWD(Da)

Fig. 4. MW distribution of UV254 and SUVA in raw water and effluent flow (mean value, n = 6).

compound. The average removal rates of DOC in molecular weight >0.45 ␮m, 0.45 ␮m–100 KDa, 100 K–10 KDa, and 3 K–1 KDa was 61.85%, 59.42%, 42.69%, and 42.65%, which indicated that CWs could change organic matter into those with lower molecular weight. The anaerobic environment contributed to decomposing high molecular weight into low molecular weight (Farnet et al., 2009). The removal rates of DOC in molecular weight 10 K–3 KDa was 25.42%, which was far below molecular weight 3 K–1 KDa. The average removal rates of DOC in molecular weight <1 kDa was 9.91%, which showed that CWs could partly further decomposed organic matters into carbon dioxide and water to realize complete removal (Kraus et al., 2008). 3.3. Characteristics of MW distribution of UV254 and SUVA UV254 is proportional to the aromatic carbon content and has been considered as a good indicator for the amount of DBP precursors in waters. Specific UV254 (SUVA), which was the value of ratio UV254 /DOC, has been found to be a good predictor of the carbon aromaticity content of the DOC and DBP formation in water (Liang and Singer, 2003; Chow et al., 2008). The MW distribution of SUVA ranged of 10 K–3 KDa and 3 K–1 KDa were higher than others (p < 0.004; ANOVA) (Fig. 4), suggesting that middle molecular weight contained more aromatic and unsaturated organic matter (Lamsal et al., 2011). The average concentration of UV254 in raw water was 0.058 mg L−1 , and the average removal rates of UV254 in effluent flow were 47.58%, which was far above average concentration of DOC removal. The MW distribution of UV254 was obviously

declined (p < 0.002; ANOVA), which further indicated that CWs could change type, morphology and distribution of organic matter in water, and reduced its aromaticity and unsaturation (Weishaar et al., 2003).

3.4. Characteristics of MW distribution of DBPs fractions Laboratory formation potentials for THMs and HAAs were measured by accessing the amount of DBPs forming under specified chlorination conditions. The DCBM was the main THMs component, which accounted for 42.95% of all THMs fractions (Fig. 5). The concentration of THMs in raw water was 63.73 ␮g L−1 , and the main component of THMs was in ranged of <1 KDa (54.50%), suggesting that THMFP was generated by organic matter and it was dominated by low-molecular-weight organics compounds. This agreed with previous work that organic compounds with lower molecular weight was characterized as aromatic, which could be easily oxidized to form THMs (Xu et al., 2007). The average concentration of THMs in effluent was 76.80 ␮g L−1 , and the average removal rate of THMs in effluent was −20.52%, which revealed that CWs had limited capabilities/efficiency to remove the THMs. As one of the key components in CWs, plants could improve the removal of volatile organic compounds by phytovolatilization, plant uptake and/or biodegradation (Wang et al., 2004). CWs soil can provide not only a large number of different species of microorganisms, protozoa, and metazoa, but also good conditions for the survival of hydrophytes. The supply of oxygen plays a crucial role in the activity and rate of metabolism performed by microorganisms in the root zone. Plants’ involvement in the input of oxygen into the root zone, uptake of nutrients and direct degradation of pollutants as well as the role of microorganisms were all important factors (Stottmeister et al., 2003). Other researchers showed that scoria with better surface activity and porosity had superior adsorption effect compared to the sands with smooth surface (Cui et al., 2006). The cinder materials was characteristic of developed void space structure and huge surface area, which enhanced its filtration function. Thus, it had also high adsorption performance. Others discovered that the concentration of trace elements in fallen litter were higher than in the living shoots, but lower than the belowground tissues. Those sediments were the primary sinks for the elements removed from the wastewater (Ye et al., 2001). Due to high weight molecular compounds changed into low weight molecular compounds by CWs, the THMs precursor content increased. Thus, the formation of THMs was related with those aspects.

Y. Yang et al. / Ecological Engineering 93 (2016) 262–268

0

60

MBAA

DCAA

influent HAAs

TCAA

DBAA

effluent HAAs

1.4

Table 3 The relationship between SUVA and STHMFP, SHAAFP in CWs (%).

1.2

MW

1.0

40

0.8 0.6 20

0.4

HAAs(ug L-1)

the persentage composition of HAAs(%)

266

0.2 0

0.0

K 0K 0K 3K ~1 ~ 10 0 K ~ 1 10 K ~ 3K µm 10 .45

K <1

MWD(Da)

Fig. 6. MW distribution of HAAs component in raw water and effluent flow (mean, n = 6).

The THMs mainly came from low molecular weight (LMW, <1 kDa), accounting for 78.35% of all THMs component in effluent (Fig. 5). Furthermore, the average concentration of MW distribution in effluent was declined (p < 0.002; ANOVA), despite low molecular weight compounds (LMW, <1 kDa). Wastewater effluent DOC entering a CW underwent biological degradation, resulting in particulate biomass growth and cellular respiration to carbon dioxide. DOC leaching from growing and dead plants could increase DOC levels in wetlands (Pinney et al., 2000). DOC reactivity to form THMs was also reduced on both absolute and per carbon mass basis. Thus, plants and soil in CWs could decompose organic matter into acidic substance, which was bromo-THM precursor, resulting in higher concentration of THMs in low molecular weight. The DCAA and MBAA were the major components of HAAs (Fig. 6), accounting for 44.67%, and 34.42% of all HAAs fractions, respectively. The concentration of HAAs in raw water was 6.19 ␮g L−1 , and lower than the concentration of THMs (p < 0.005; ANOVA), suggested that the number of THMs was greater than HAAs, which could be generating potentially harmful carcinogens. The MW distribution of HAAs in influent was mainly ranged <1 KDa, and 0.45–100 KDa, accounting for 24.99%, and 22.28%, suggesting that HAAFP generated by organic matter in the CWs was dominated by low and high molecular weight organic compounds. That meant that high molecular weight organic compounds reacted with chlorine and were naturally more inclined to form HAAs. Previous study was found similar that controlling low and high molecular weight organic compounds was the dominant way to reduce the formation of HAAs (Hua and Reckhow, 2007). The average concentration of HAAs in effluent flow was 4.63 ␮g L−1 , and the average removal rates of HAAs in effluent was 25.22%, which revealed that CWs had abilities to remove the HAAs. Of all HAAs component in effluent flow, the HAAs mainly came from MW ranged <1 KDa, 3 K–1 KDa, and 10 K–3 KDa, accounting for 39.32%, 19.59%, and 15.17%. Similarly, the formation of HAAs was related to plants and soil conditions. However, high molecular weight organic compounds were more likely to form HAAs and the concentration of DOC in effluent flow was low removed by CWs, the average removal rate of HAAs was higher than THMs (p < 0.001, ANOVA), which could reduce the risk of carcinogenesis (Lee et al., 2009). Some researchers showed that algae and chlorophyll also could be the precursor of THMs and HAAs (Cheng et al., 2010). 3.5. The relationship of DBPs fractions and SUVA The measure of DBPsFP consumed long time, and had high requirement to operating person. Thus, seeking a more simple

<0.45 ␮m <100 K <10 K

STHMFP

SHAAFP

r

R2

r

R2

−0.016 0.011 −0.245

0 0 0.06

0.843 0.968 0.966

0.711 0.938 0.933

and efficient measuring method to replace DBPsFP was essential. Normalizing THMFP and HAAFP by DOC concentration to obtain STHMFP and SHAAFP, respectively, provides an indication of how reactive the DOC pool is on a molar basis. The relationship between UV254 , DOC, SUVA and DBPs had been studied in raw water and effluent (Roccaro and Vagliasindi, 2009). However, whether SUVA could replace DBPsFP need more research to investigate (Ates et al., 2007). This section investigated the relationship between SUVA and STHMFP, SHAAFP removal. Specific THMFP (STHMFP), which is equal to the THMFP divided by the DOC concentration, is used as a measurement of the reactivity of DOC in forming THMs and is generally proportional to the SUVA (Chow et al., 2008). There was not a strong correlation between SUVA and STHMFP (Table 3). The results were in contrast to previous studies reporting that aromatic carbon was generally considered as a major reactive moiety in forming THMs and that SUVA correlates strongly with aromatic content (Norwood et al., 1987; Chow et al., 2005). However, SUVA and STHMFP were not always related, particularly among samples from diverse habitats (White et al., 2003; Weishaar et al., 2003). The absence of a link between SUVA and STHMFP suggested that a significant portion of the aromatic structures within DOC were not THM precursors in CWs, which revealed that SUVA could not express the THMFP value (Chow et al., 2008). Some special NOM moieties, which could not be captured by these NOM parameters and were most probably in non-UV254 nm absorbing section, appeared to be responsible for THM formation (Ates et al., 2007). Non-aromatic moieties were known to react with chlorine, but generally do not contribute to SUVA (Kanokkantapong et al., 2006), which may further explain the poor correlation between STHMFP and SUVA. The formation of chlorinated THM species was more favorable compared to brominated species, mainly due to much lower bromide concentration than those of chlorine (Kitis et al., 2010). The fact that the measured parameters had little predictive power for STHMFP, indicated that high THM precursor content was not necessarily associated with a single type of DOM. The variability in SHAAFP was more highly correlated with SUVA than STHMFP (Table 3), suggesting that aromatic moieties had a higher apparent propensity to form HAAs than THMs, this was consistent with pervious researches (Wu et al., 2000; Liang and Singer, 2003b). Others suggested that HAA precursors were characterized by high aromatic content and associated with fulvic and humic acids (Kraus et al., 2008), that DOC derived from soil and degrading plants was an important source of HAA precursors. 4. Conclusions 1. CWs can effictively decrease the pollutants in the raw water for drinking water pretreatment except THMs. The average removal of CODMn , NH4 + , total N, DOC, UV254 , THMs, and HAAs were 38.4%, 41.7%, 25.9%, 30.96%, 47.58%, −20.52%, and 25.22% respectively. 2. The analysis of molecular weight (MW) distribution by measuring DOC and UV254 showed that CWs could effectively remove the high and middle molecular weight hydrophilic fraction of dissolved organic materials present in the raw water. THMs are

Y. Yang et al. / Ecological Engineering 93 (2016) 262–268

mainly come from LMW (low molecular weight, <1 Ka), so it is reasonable that THMs are increased after CWs treatment. 3. The THMs and HAAs are quite different in the CWs pretreatment, which are discussed as follows: a) The concentration of HAAs in raw water was 6.19 ␮g L−1 , far less than the concentration of THMs (76.80 ␮g L−1 ). The THMs is the main content of DBPs. b) The DCBM in influent was the main THMs component, which accounted for 42.95% of all THMs fractions. And the DCAA and MBAA were the majority of HAAs components, accounting for 24.99%, and 22.28% respectively. c) The LMW (<1 KDa) DOC is the main content of THMs, which accounts for 54.5% THMs. While the MW distribution of HAAs was mainly ranged <1 KDa, and 0.45–100 KDa, accounting for 24.99%, and 22.28%, suggesting that HAAFP generated by organic matter in the CWs was dominated by low and high molecular weight organics. d) The SUVA did not have obvious relationships with the removal of specific trihalomethane formation potential (STHMFP), but had strong relationship with the removal of specific haloacetic formation potential (SHAAFP) in CWs (p < 0.05). Acknowledgements This work was financially supported by a funding from Jiangsu Province Key Laboratory. Yuli Yang was supported by a grant Preponderant Discipline of civil engineering in Southeast University (#CE02-1/2-0×). References Akratos, C.S., Tsihrintzis, V.A., 2007. Effect of temperature HRT, vegetation and porous media on removal efficiency of pilot-scale horizontal subsurface flow constructed wetlands. Ecol. Eng. 29, 173–191. Anipsitakis, G.P., Tufano, T.P., Dionysiou, D.D., 2008. Chemical and microbial decontamination of pool water using activated potassium peroxymonosulfate. Water Res. 42, 2899–2910. Ates, N., Kitis, M., Yetis, U., 2007. Formation of chlorination by-products in waters with low SUVA—correlations with SUVA and differential UV spectroscopy. Water Res. 41, 4139–4148. Bolea, E., Gorriz, M., Bouby, M., Laborda, F., Castillo, J., Geckeis, H., 2006. Multielement characterization of metal-humic substances complexation by size exclusion chromatography, asymmetrical flow field-flow fractionation, ultrafiltration and inductively coupled plasma-mass spectrometry detection: a comparative approach. J. Chromatogr. A 1129, 236–246. Bond, T., Huang, J., Templeton, M.R., 2011. Occurrence and control of nitrogenous disinfection by-products in drinking water—a review. Water Res. 45, 4341–4354. Braeckevelt, M., Mirschel, G., Wiessner, A., 2008. Treatment of chlorobenzene-contaminated groundwater in a pilot-scale constructed wetland. Ecol. Eng. 33, 45–53. Cheng, Y., Juang, Y., Liao, G., 2010. Dispersed ozone flotation of Chlorella vulgaris. Bioresour. Technol. 101, 9092–9096. Chow, A., Dahlgren, R., Gao, S., 2005. Physical and chemical fractionation of dissolved organic matter and trihalomethane precursors: a review. Aqua 54, 475–507. Chow, A., Dahlgren, R., Zhang, Q., 2008. Relationships between specific ultraviolet absorbance and trihalomethane precursors of different carbon sources. J. Water Supply: Res. Technol. 57, 471–480. Chu, W., Gao, N., Templeton, M.R., 2011. Comparison of inclined plate sedimentation and dissolved air flotation for the minimisation of subsequent nitrogenous disinfection by-product formation. Chemosphere 83, 647–651. Chu, W., Li, C., Gao, N., 2015. Terminating preozonation prior to biological activated carbon filtration results in increased formation of nitrogenous disinfection by-products upon subsequent chlorination. Chemosphere 121, 33–38. Cui, Y., Dong, C., Zhao, L., 2006. The performance study on adsorption of the filled material in constructed wetland. J. Jilin Archit. Civil Eng. Inst. 2, 1. Doherty, L., Zhao, Y., Zhao, X., 2015. Nutrient and organics removal from swine slurry with simultaneous electricity generation in an alum sludge-based constructed wetland incorporating microbial fuel cell technology. Chem. Eng. J. 266, 74–81. Farnet, A.M., Prudent, P., Ziarelli, F., 2009. Solid-state 13 C NMR to assess organic matter transformation in a subsurface wetland under cheese-dairy farm effluents. Bioresour. Technol. 100, 4899–4902.

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