Impacts of channel morphology on residues and ecological risks of polychlorinated biphenyls in water and sediment in Chahe River

Zhen-hua Zhao*,Jie Sun,Xiao-kun Fang,Li-ling Xia,Javi Hussain

aDepartment of Plant,Soil,and Microbial Sciences,Michigan State University,East Lansing,MI 48824,USA

bKey Laboratory of Integrated Regulation and Resource Development on Shallow Lakes of Ministry of Education,Hohai University,Nanjing 210098,China

cCollege of Environment,Hohai University,Nanjing 210098,China

dNanjing Institute of Industry Technology,Nanjing 210016,China

Impacts of channel morphology on residues and ecological risks of polychlorinated biphenyls in water and sediment in Chahe River

Zhen-hua Zhaoa,b,c,*,Jie Sunb,c,Xiao-kun Fangb,c,Li-ling Xiad,Javid Hussainb,c

aDepartment of Plant,Soil,and Microbial Sciences,Michigan State University,East Lansing,MI 48824,USA

bKey Laboratory of Integrated Regulation and Resource Development on Shallow Lakes of Ministry of Education,Hohai University,Nanjing 210098,China

cCollege of Environment,Hohai University,Nanjing 210098,China

dNanjing Institute of Industry Technology,Nanjing 210016,China

The impacts of channel morphology on the residues and ecological risks of 14 polychlorinated biphenyl(PCB)congeners in water and sediment were investigated in summer(July)and autumn(September)in the Chahe River,in Nanjing,China.The residual concentrations of trichlorobiphenyls(tri-CBs,PCB 18)and tetra-CBs(PCB 52)in water were significantly higher than those of penta-CBs to deca-CBs,and the average residual concentration of∑PCBs(sum of 14 PCB congeners)in summer was about six times higher than in autumn.However,the residues in sediment did not change significantly.Redundancy analysis(RDA)indicated that channel morphology and the corresponding environmental indices had significant impacts on PCB residues and their composition profiles in water and sediment.The overfl ow weir and lake-type watercourse may remarkably reduce the residual concentration and ecological risks of PCBs in water.The highest reduction percentages of the residualconcentration and ecological risks of∑PCBs induced by an overflow weir were 78%and 67%,respectively,and those induced by a lake-type watercourse were 36%and 70%,respectively.The watercourses with different channel morphologies were ranked by residual∑PCBs concentrations in the following descending order:the natural ecological watercourse,vertical concrete watercourse,and vegetation-type riprap watercourse.However,they were ranked by residual∑PCBs concentrations in sediment in the following descending order:the vertical concrete watercourse,vegetation-type riprap watercourse,and natural ecological watercourse.

PCBs;Channel morphology;RDA;Ecological risk;Toxic equivalent concentration

1.Introduction

Polychlorinated biphenyls(PCBs)are one set of semivolatile organic compounds,which have been used widely as electric insulators in transformers,hydraulic fl uids,and paint additives since they began being produced commercially in 1929(Wang et al.,2011).A great deal of concern has been expressed overthe presence of PCBs in differentenvironmental matrices,due to their high toxicity,persistence,bioaccumulation,biomagnification,and long-range transportation (Zhang et al.,2002;Wan et al.,2005).Once released into the aquatic environment,PCBs are usually bound to suspendedparticles or absorbed by aquatic organisms.They can be biomagnifi ed to about200-70000 times along the food chain and cause potential risks to organisms and humans(Ashley et al., 2000;Fontenot et al.,2000;Pruell et al.,2000;UNEP,2004; Dodoo et al.,2012).It is now common knowledge that PCBs pose a major threat to humans and the environment even at very low concentrations(Baars et al.,2004;Dodoo et al., 2012).Exposure to PCBs can cause a series of health impacts,including reproductive disorders and immune suppression of various organisms,and even result in cancer, teratogenesis,and mutations(Van den Berg et al.,2006;Zhao et al.,2014).

China produced a total of approximately 10000 tons of PCBs from 1965 to 1974,including 9000 tons of tri-CBs and 1000 tons of penta-CBs(Wu et al.,2011,2015).Although PCBs are notproduced any more,some of them remain in the environment.Many studies have already analyzed and reported the distribution,level,and fate of PCBs in air,water, soil(Zhang et al.,2007;Wang et al.,2008,2010),sediment, organisms,and the human body(Zhang et al.,2003;Nakata et al.,2005;Li et al.,2008;Weijs et al.,2009;Wu et al., 2009,2011;Hu et al.,2010;Bao et al.,2012;Consonni et al.,2012;Dodoo et al.,2012).The levels of PCBs in the Haihe and Huaihe rivers are 311-3110 ng/L(∑PCB12,sum of 12 PCB congeners)and 46.8-194 ng/L(∑PCB57,sum of 57 PCB congeners),respectively,which are higher than those in the Yangtze River(with a∑PCB18concentration ranging from 0.92 to 5.11 ng/L,sum of 18 PCB congeners)and the Pearl River(with a∑PCB20concentration ranging from 0.12 to 1.47 ng/L,sum of 20 PCB congeners)(Bao et al.,2012).

In addition,some studies show that increased amounts of aquatic plants and phytoplankton productivity can reduce the concentrations of persistent organic pollutants(POPs)in aquatic ecosystems,and the species and biomass of aquatic plants and phytoplankton can affect the bioaccumulation and distribution of PCBs(Taylor et al.,1991;Cailleaud et al., 2007;Nizzetto et al.,2012;Frouin et al.,2013;Galbˊan-Malagˊon et al.,2013;Zhao et al.,2014).The physical and biogeochemical characteristics of the aquatic environment such as light,temperature,eutrophication,and nutrient stress can affect the bioaccumulation of PCBs in aquatic ecosystems (Magnusson and Tiselius,2010;Berrojalbiz et al.,2011;Zhao et al.,2014).However,few researchers have investigated the impact of channel morphology on the residual characteristics of PCBs.Recently,China has embarked on a pilot national monitoring program to assess ecological integrities of major watersheds since 2010.The components used in this monitoring program included hydrology,channel morphology, physico-chemical parameters,residues of pollutants(e.g., heavy metals,nutrients,and POPs),ecotoxicological aspects, types and numbers of biota and age,and growth of fi sh(Wang etal.,2014).The change of channelmorphology can affectthe fl ow rate,physico-chemical indices,such as pH and dissolved oxygen(DO),and the deposition of suspended particles, leading to a change in residualcharacteristics of POPs in water and sediment(Ko and Baker,2004;Wurl and Obbard,2006; Yan et al.,2008;Sandy,2010).

The objectives of this study were to describe the impact of channel morphology on the residues and ecological risks of PCBs based on the investigation and redundancy analysis (RDA)of residual PCBs and environmentalindices atdifferent sampling sites.

2.Materials and methods

2.1.Study area

The Chahe Watershed,a typical small agricultural watershed consisting mainly of small patches of uplands and paddy fields,is located in Baima Town(ata latitude of 31°34′N and a longitude of 119°10′E)in Nanjing,China(Fig.1).The study area is located in a subtropical monsoon climate zone with an average annualtemperature of 15.4°C and an annual rainfallof 1087.4 mm(Zhu etal.,2013).The totalarea is about4.087 km2and mostof the land is used for farming,of which paddy fi elds account for 50%and uplands account for 30%.The river mainly undertakes the functions of irrigation and drainage.In addition,most of the watercourses show a natural formation with small cross-sections and large curvature.For the purposes of irrigation and impoundment,a large number of sluices, dams,and other impounding buildings were built along the watercourses.Overfl ow weir 1 and Overfl ow weir 2 are located near Bridge 1 and Bridge 2,respectively.These structures affect the transportation of pollutants and sediment.There are mainly two kinds of pollution sources(mainly containing high concentrations of nitrogen,phosphorous,and trace POPs)along the river:(1)a large amount of field water,with agricultural non-point source pollutants,directly draining into the upper reaches of the Chahe River,especially at sampling site#1;and (2)a point source sewage outfall located between sampling sites#4 and#5.In addition,a paintfactory and a waste plastics recovery plant located near the Chahe River are also possible pollution sources(Bao et al.,2012).The Chahe River has been heavily polluted by the agricultural non-pointsource pollutants and sewage.In order to improve its water quality,some ecological engineering measures,such as overfl ow weirs, aquatic plants,and ecological riverbanks and watercourses, have been applied to the river since 2009.

2.2.Sample collection

The samples of water and sediment were collected according to the channel morphology along the Chahe River in the summer(on July 7,2013)and autumn(on September 30, 2013)(Fig.1).In July,the rainy season of this region,there is a lot of surface runoff fl owing into the river.Rice in July is at its tillering stage,and it needs plenty of pesticides and extensive irrigation.Therefore,fi eld water easily drained into the river and increased the pollution load of the river.Meanwhile,in September,rice is at its milk stage,and the climatic characteristics are entirely different from those in July.The sampling sites were set according to the channel morphology of the Chahe River from north to south:the#1,#2,#3,#4,#5, and#6 sites(Fig.1 and Table 1).Sites#1 and#2 were locatedin a watercourse with a natural ecological riverbank,and#1 was the representative site.Sites#3 and#4 were located in a watercourse with vegetation-type rock revetment,and#4 was the representative site.Sites#5 and#6 were located in an area with a vertical concrete riverbank,and#6 was the representative site.

Fig.1.Chahe Watershed and locations of sampling sites.

Three parallel water samples at a water depth of 0.5 m at each site were collected in brown glass bottles with a polytetrafl uoroethylene stopple.They were used for the determination of PCB concentrations(Zhao et al.,2014).These glass bottles were cleaned with K2Cr2O7-H2SO4solution and distilled water before being used.The samples were kept in a refrigerator at4°C afterthey were broughtto the laboratory.At each site,aboutten random plant samples in a 20 cm×20 cm area were collected.The fresh plant samples were washed, weighed,and used to assess the biomass of aquatic plants(Li et al.,2002).Sedimentsamples were collected with a stainless Peterson grab.After the sedimentsamples were dried in a cool and well-ventilated place,grinded,treated to remove impurities,and sieved through 100 meshes,they were mixed thoroughly for detection.Then,the samples were stored in brown glass bottles.

2.3.Analysis of environmental parameters

After the portable electrochemical meters were precalibrated,the temperature,DO concentration,pH,oxidationreduction potential(ORP),and conductivity were measured in situ using SX751-series portable electrochemical meters (San-Xin Instrumentation Inc.,Shanghai,China)(Zhao et al., 2014).The river flow rate was measured using a LSH10-1A portable ultrasonic wave Doppler flowmeter(Boyida Instrumentation Inc.,Xiamen,China).The turbidity was measured with a 2100Q portable turbidimeter(Hach Company,Loveland, Colorado,USA)(Zhao et al.,2013).

2.4.Chemicals and materials

In this study,the acetone,hexane,methanol,methylene chloride,anhydrous sodium sulfate,neutral alumina and copper powder,C18-bonded silica gel,and non-bonded silica gel were used.Their detailed information is the same as in Zhao et al.(2014).

Fourteen PCBs were purchased from Dr.Ehrenstorfer GmbH(Augsburg,Germany),including tri-CBs(PCB 18, PCB 28,and PCB 31),tetra-CBs(PCB 44 and PCB 52),penta-CBs(PCB 101 and PCB 118),hexa-CBs(PCB 138,PCB 149, and PCB 153),hepta-CBs(PCB 170 and PCB 180),octa-CBs (PCB 194),and deca-CBs(PCB 209).These PCBs were diluted with n-hexane into standard solutions for experimental work(Zhao et al.,2014).

2.5.Extraction of PCBs from water samples

A 10-L water sample was enriched with a C18 solid-phase extraction column ateach site.The eluent was concentrated to approximately 1 mL with a vacuum rotary evaporator,and blown to near dry with N2.After the concentrated solution was adjusted to 1 mL with n-hexane,the PCBs were determined by a gas chromatograph/ion trap mass spectrometer(GC-IT/MS, Thermo Fisher Scientifi c Inc.,Billerica,MA,USA).The detailed extraction method of PCBs from water was described by Zhao et al.(2014).

2.6.Extraction of PCBs from sediment samples

5.0 g of sediment sample and 2.0 g of anhydrous sodium sulfate were weighed,put into a 50-mL glass centrifuge tube, and mixed.After the sediment was soaked in a 15-mL methylene chloride and hexane mixture(with a volumetric ratio of 2:1)for 1 h,the ultrasonic extraction lasted for 10 min.Then,the supernatantwas transferred into a pear-shaped bottle.After the processes above were repeated twice,the extraction liquid was concentrated to about 1 mL at40°C with a vacuum rotary evaporator.The solid-phase purification column(SPPC)was obtained by fi lling the upper layer with 0.5 g of copper powder and 1 g of anhydrous sodium sulfate,the middle layer with 1 g of silica gel,and the bottom layer with 1 g of alumina in a 6-mL empty column(Zhao et al.,2014).After the SPPC was rinsed and activated with 5 mL of hexane,concentrated extracting liquor was transferred into the SPPC.Then,the SPPC was eluted with a 25-mL mixture of hexane and methylene chloride(with a volumetric ratio of 3:1),and concentrated to about 1 mL.Finally,the volume was adjusted to 1 mL with n-hexane for determination.

Table 1 Division of different channel morphologies for Chahe Watershed.

2.7.Chromatographic conditions

The qualitative detection of PCBs in samples was based on the chromatographic conditions described in Zacharis et al. (2012).A thermo GC-IT/MS system consisting of a TRACE GC Ultra gas chromatograph and a Polaris-Q ion-trap mass spectrometer(Thermo Fisher Scientifi c Inc.,Billerica,MA, USA)was used.The flow rate of the carrier gas(helium,with a purity of 99.999%)was 2.0 mL/min in constantflow,and the non-splitmode was selected.The column temperature and ion source temperature were 290°C and 220°C,respectively.The injection volume was 2μL.The mass spectrometer was operated in the electron impact(EI)mode at 70 eV.The detection was achieved in the selected ion monitoring(SIM) mode.Full-scan mass spectrometer(MS)data were acquired over the range of mass to charge ratios of 50-500 to obtain the fragmentation spectra of the analytes.Also,the U.S.NIST v.2.0g mass spectral database was used for the MS data interpretation.Qualitative detection of the relative retention time and peak were performed according to an internal standard(2,4,5,6-tetrachloro-m-xylene,TMX)(Zacharis et al., 2012).

2.8.Quality control

To verify the accuracy of the experimental data,a field blank and a laboratory blank for each batch of samples were set up.TMX was used as the internal standard to monitor the sample-preparation process.The recovery of the internal standard was 78.6%-104.4%.Each sample was analyzed six times,the relative standard deviation(RSD)was 2.1%-5.3%, and the standard error was between 0.14%and 13.52%(Zhao et al.,2014).Calibration was performed by extracting the spiked water-methanol samples at seven calibration levels (0.1,0.5,2.5,5,10,50,and 100 ng/L).The detection limitwas defi ned as the concentration,giving a signal-to-noise ratio of 3.Linearity was investigated within the range between the detection limit and 100 ng/L,and the values of the coeffi cient of determination(R2)were between 0.9950 and 0.9999.The detection limitof the target compounds(including the internal standard)was 0.25-1.0 ng/L(Popp et al.,2005).

2.9.Data analysis

The residual level and component characteristics of PCBs in water and sedimentwere graphed using GraphPad Prism 6.0 (Windows software package).Redundancy analysis(RDA)of residual quantities of PCBs,environmental indices,and samples were performed using the Canoco 5.0 software package. Values for residual PCBs and environmental indices were normalized by lg(x+1)transformation.Through comparisonof the RDA ordination results,we identifi ed the dominant environmental indices,which affected the residues of PCBs at different sampling sites(Zhao et al.,2014).

3.Results and discussion

3.1.Analysis of physicochemical indices

Physicochemical indices of water samples showed the water environmental characteristics at each sampling site. Through comparison of physicochemical indices,we can identify the key factors affecting the residual characteristics of PCBs in the river(Table 2).

The spatial varieties of each physicochemical index in the river were not significant within the same season.However, most of the environmental indices in summer were significantly higher than in autumn at each sampling site.The minimum DO concentration appeared at site#4 in both summer and autumn.This may be related to the poor reoxygenation ability of water due to the low velocity at this site,which was located in a typicallake-type watercourse.Along the fl ow direction of the river,the value of conductivity gradually decreased in summer.The change of turbidity is closely related to the fl ow rate of water,which implies that the fl ow rate affected the sedimentation of suspended particulate matter (SPM).The slightly acidic pH values at sites#2 and#3 in autumn may be related to the decrease of aquatic plant biomass,which leads to weakened photosynthesis and a high concentration of CO2in water.

3.2.Residualleveland componentcharacteristics ofPCBs

3.2.1.Residues of PCBs in water

The residual concentrations of PCBs in water in summer and autumn at each sampling site are shown in Fig.2.The∑PCBs(sum of 14 PCB congeners)concentration in summer and autumn ranged from 5.81 to 276.82 ng/L(with an average of 108.73 ng/L)and from 6.65 to 30.60 ng/L(with an average of 18.13 ng/L),respectively.The average of∑PCBs concentration in summer was about six times higher than in autumn.The highest∑PCBs concentrations in water in both summer and autumn were found at site#5,which might be related to the presence of a point source sewage outfall upstream of this sampling site.The decrease of the∑PCBs concentration in autumn(the highest∑PCBs concentration was only 30.60 ng/L)may be due to the abundant absorption of PCBs by rice in paddy fi elds in the late growth stage of rice and aquatic plants in the river.The absorption of PCBs by rice may decrease the residualconcentration of PCBs in field water and indirectly reduce the runoff output of PCBs into the river. The absorption of PCBs by a large number of aquatic plants may also lead to a decrease of the PCB concentration in rivers (Richard et al.,1997;Huesemann et al.,2009).

Fig.2.Distribution characteristics of PCBs in water in summer and autumn.

As for the profile of PCB congeners,the concentrations of low-chlorinated PCBs,including tri-CBs and tetra-CBs in water(accounting for 40.47%-96.39%,with an average of 74.65%,mainly including PCB 18,PCB 44,and PCB 52), were significantly higher than those of highly chlorinated PCBs including penta-CBs to deca-CBs(accounting for 3.61%-59.53%,mainly including PCB 149,PCB 170,and PCB 194).In general,the dominant PCBs were tetra-CBs, followed by tri-CBs,penta-CBs,and hexa-CBs in different seasons at all sites except at site#3.The concentrations of other PCB congeners were much lower.

Table 2 Physicochemical indices of samples in summer and autumn.

3.2.2.Residues of PCBs in sediment

The residualconcentrations of PCBs in surface sedimentin summer and autumn in the study region are shown in Fig.3. The∑PCBs concentration in sedimentin summer and autumn ranged from 12.91 to 65.11 ng/g(with an average of 38.69 ng/g)and from 4.88 to 79.41 ng/g(with an average of 32.10 ng/g),respectively.The∑PCBs concentration did not change significantly in sedimentin summeror autumn,and the principal components were similar to those in water.The highest∑PCBs concentrations in summer and autumn were detected at sites#2 and#6,respectively,which might be related to the relative deposition and accumulation of PCBs in sediments upstream of the overfl ow weir.

The profi le of PCB congeners in sediment was similar to that in water.The sum of average percentages of tri-CBs and tetra-CBs accounted for about 87.70%of the concentration of∑PCBs(mainly including PCB 18,PCB 44,and PCB 52).In general,the dominant congeners were tri-CBs,followed by tetra-CBs,hexa-CBs,and penta-CBs in different seasons.

The production and application of PCBs in China mainly consist of tri-CBs(90%)and penta-CBs(10%)(Que et al., 2006).However,whether in water or in sediment,the concentration of penta-CBs was always lower in this study.In sediment,the concentration of tri-CBs ranged from 1.04 to 58.81 ng/g,accounting for 2.07%-91.18%of the∑PCBs concentration,and the highest concentration of tri-CBs in summer and autumn occurred at site#6.The concentration of penta-CBs was only between 0 and 0.76 ng/g.This may be due to easy degradation dechlorination of penta-CBs in the environment(Sun et al.,2008).

Fig.3.Distribution characteristics of PCBs in sediment in summer and autumn.

3.3.Impact of channel morphology on PCB residues

In the upper reach of the Chahe River(with sites#1 and#2), site#1 was considered to have the typicalchannel morphology of a long and narrow river with natural ecological riverbank. Although there were plenty of floating plants and submerged plants in the watercourse to reduce the PCB residues at site#1, the∑PCBs concentration atthis site was stillthe highestof all the sampling sites except site#5,due to the high flow rate, difficulty ofdeposition of SPM,and receiptof non-pointsource pollution from farmlands atsite#1.Hence,the pollution source and high fl ow rate played a dominant role in the increase of PCB concentrations in water.Ko and Baker(2004)reported that large amounts of suspended particles in the Susquehanna River resulted in elevated levels of hydrophobic organic compounds(HOC)and increased loads of these contaminants flowing to Chesapeake Bay during high flow periods.

When the water flowed to site#2 in a lake-type watercourse, the presence of Overfl ow weir 1 near Bridge 1 and the broadening of river width caused the flow rate to greatly slow down and a large number of PCBs bound to SPM to be deposited easily to the bottom of the river.Therefore,the∑PCBs concentration in surface water decreased atsite#2(the mean value in summer and autumn was 46.00 ng/L).At the same time,the∑PCBs concentration in sediment increased greatly at this site(Fig.3).Hence,the overfl ow weir and low flow rate played a dominant role in the decrease of PCB concentrations in water.The reduction of turbidity also means the sedimentation of particles,and the overflow weir may play a key role in separating the water column into different layers. This phenomenon of vertical distribution profi les of PCBs in the water column has also been reported in the Black Sea and along Singapore's coast(Maldonado and Bayona,2002;Wurl and Obbard,2006).The types and sizes of SPMs in different water layers may affect the distribution and enrichment of contaminants due to the adsorption ability difference of different SPMs in relation to contaminants,and this phenomenon is usually affected by the resuspension processes of contaminated sediments and heavy rainfall events(Wurl and Obbard,2006).

In the middle reach of the Chahe River(with sites#3 and #4),after Overfl ow weir 1,the flow rate increased sharply at site#3.The narrow watercourse and high flow rate caused the∑PCBs concentration to further decrease in water and sediment,which mainly comes from the overlying water upstream, due to the quick volatilization of low-chlorinated PCBs.Allthe possible reasons caused the∑PCBs concentration at this site to reach the lowest value(the mean value in summer and autumn was 10.24 ng/L).Although there is no evidence that high fl ow rate can accelerate the volatilization of lowchlorinated PCBs,several reports have shown that high wind speed and high temperature can accelerate the volatilization of PCBs(Jeremiason etal.,1994;Agrelletal.,2002;Dachs etal., 2002;Meijeretal.,2006,2009;Rowe and Perlinger,2012).For large water bodies,gas exchange with the atmosphere is a dominantprocess in the mass balance for relatively volatile and water-insoluble chemicals such as PCBs and mercury(Jeremiason et al.,1994;Rowe and Perlinger,2012).In the Hudson River,as well as many other water bodies,mass balances indicate that the major process for the removal of PCBs is volatilization,which accounted for about 60%of all PCB losses for congeners 2 through 6.Mono-CBs through tri-CBs congeners accounted for about half of the∑PCBs fl ux,with tetra-CBs through hexa-CBs congeners accounting forthe other half.Fluxes of congeners with more than six chlorines were not calculated.The average daily∑PCBs flux was 4μg/(m2·d), and the mass transfer velocity of PCBs was primarily under the control of water phase(Yan et al.,2008;Sandy,2010).

Site#4 was considered to have the typical channel morphology of a lake-type watercourse with vegetation-type rock revetment.The absorption of vegetation near the watercourse and plenty of aquatic plants in the river could reduce the residual∑PCBs concentrations(Larsson et al.,2000; Berglund et al.,2001;Sobek et al.,2004;Nizzetto et al., 2012).In addition,the wider watercourse and lower fl ow rate were beneficial to the deposition of PCBs on SPM to the bottom of the river.The change of turbidity and the residual PCB concentrations in water and sediment also proved our hypothesis(Table 2 and Figs.2 and 3).Several studies have also shown that the interaction between eutrophication and uptake of POPs in aquatic biota can resultin reduced uptake of POPs in primary producers(growth dilution),and the increase of the downward fl ux of pollutants to the bottom.Therefore, lower amounts of pollutants are transported in the food chain(Larsson et al.,2000).Nizzetto et al.(2012)reported that the compounds with lg Kow＞6.5(where Kowis the octanol-water partition coefficient)in the lake were mainly associated with the biomass of the primary producer,and the phytoplankton biologicalpump was a major driverof exportof POPs from the epilimnion,causing the decline of dissolvedphase concentrations.Sobek et al.(2004)suggested that partitioning of PCBs to particulate organic carbon in surface water was equilibrated and not kinetically limited by factors such as high growth rate of phytoplankton or large cell size. Berglund et al.(2001)showed that more PCBs were accumulated and buried in the sediment of eutrophic lakes than in oligotrophic lakes,where a greater fraction of∑PCBs load was dissolved in water(Berglund etal.,2001).Our research in the Qinhuai River indicated that the bioaccumulation of PCBs was significantly correlated to the composition of phytoplankton.Moreover,Chlorophyta,Bacillariophyta,and Euglenophyta had strong capacities to take up PCBs(Zhao et al.,2014).

However,the presence of a sewage outfallbetween sites#4 and#5 and the effect of Overflow weir 2 near Bridge 2 resulted in higher∑PCBs concentration in water and sediment at site#4(the mean value in summer and autumn was 40.26 ng/L in water)than atsite#3.Moreover,this also led to the highest∑PCBs concentration at site#5 in water(the average was 153.71 ng/L).However,the∑PCBs concentration in sediment remained at a lower level,which may mean that the pollution sources contain fewer suspended particles.

Site#6 was considered to have the typical channel morphology of a river with a vertical concrete riverbank with very few plants and poor permeability.Although the presence of Overfl ow weir 2 upstream of site#6(near Bridge 2)and the high fl ow rate can decrease the∑PCBs concentration in water due to the pre-sedimentation at site#5,the high flow rate and the aerobic water environmentnear the overfl ow weir were not conducive to the deposition and degradation of PCBs in sediment and water.Therefore,the residual∑PCBs concentration in water and sediment was higher at site#6(the mean value in water in summer and autumn was 59.02 ng/L)than at other sites.

In general,the∑PCBs concentrations in water at different sites were ranked in the following descending order:site#5 (153.71 ng/L),site#1(71.36 ng/L),site#6(59.02 ng/L),site #2(46.00 ng/L),site#4(40.26 ng/L),and site#3(10.24 ng/L). The highest reduction percentages of the residual∑PCBs concentrations induced by the overflow weir and lake-type watercourse were 78%and 36%,respectively.However,the residual∑PCBs concentrations in sediment were ranked in the following descending order:verticalconcrete watercourse, vegetation-type riprap watercourse,and natural ecological watercourse.

Through the analysis of the characteristics of PCB residuals,we find thatthe overflow weir may remarkably reduce the∑PCBs concentration in surface water,which implies that PCBs bound to SPM may be a dominant factor affecting the∑PCBs concentration in surface water.The sedimentation of SPM is advantageous to the reduction of the∑PCBs concentration in water due to the low flow rate upstream of the overflow weir.Downstream of the overfl ow weir,the higher volatilization rate of PCBs is also an important contribution to the decrease of the residual∑PCBs concentration in water because of the high fl ow rate.In addition,the absorption of plentiful aquatic plants and the degradation in a lake-type watercourse are also important reasons for the decrease of the residual∑PCBs concentration in water.

3.4.Redundancy analysis between environmental indices and residual∑PCBs

Redundancy analysis(RDA)was conducted to study the relationship between the residual∑PCBs and environmental indices.When the residual PCBs data and environmental indices data acted as the species matrix and environmental matrix,respectively,the eigenvalues of the fi rst two species axes were 0.194 and 0.165(Table 3),and the total eigenvalue was 0.875.The correlation coeffi cients between the fi rst two species axes and the first two environmental axes were 0.729 and 0.614,respectively(Zhao et al.,2014).Due to the factthat corresponding data are compositional data and have a gradient length of 1.3 standard deviation(SD)units,the linear method, RDA,is recommended.The ordination diagram of PCB residues,environmental indices,and sampling sites in water and sediment in summer and autumn are provided in Fig.4.In Fig.4,“sampling site name”and“sampling site name+*”refer to the water samples in summer and autumn,respectively (e.g.,#1 and#1*),and“sampling site name+S”and“sampling site name+*S”refer to the sediment samples in summer andautumn,respectively(e.g.,#1S and#1*S).RDA results show that the first two variable axes can explain 92.1%of the total fi tting cumulative variable,indicating that these results are credible.

Table 3 Eigenvalues of axes and correlation coefficients of environmental axis and species axis.

From the length of the arrows in Fig.4,we can see that the impacts of water environmentalindices including conductivity, ORP,pH,temperature,river width,flow rate,and DO concentration on the residual concentration and distribution of PCBs were greater than those of turbidity and biomass at the corresponding sampling sites in both summer and autumn.In particular,temperature and environmental media(water and sediment)caused the samples in the two seasons to be divided into Group 1,Group 2,and Group 3(Fig.4 and Table 4).Tetra-CBs and hexa-CBs in water showed a signifi cant positive correlation with the environmental indices of ORP,pH,temperature,DO,biomass,and river width in Group 1.This implies thatthe environmentalcharacteristics of high temperature, ORP,and DO concentration in summer were propitious to the generation of tetra-CBs through the degradation of highly chlorinated congeners.Therefore,Group 1 represents the effects of environmental indices on low-chlorinated PCBs in water samples.The sediment samples were divided into Group 2 and Group 3.In Group 3,the highly chlorinated congeners,including penta-CBs to deca-CBs,showed a negative correlation with environmental indices in autumn.This suggests that low temperature was not propitious to the degradation of highly chlorinated congeners,so the percentage of highly chlorinated PCBs notably increased(Laietal.,2015). In Group 2,the sedimentsamples are the summer samples,due to the degradation of highly chlorinated PCBs and the deposition of tri-CBs from the overlying water,and the tri-CBs become the dominant type of residual∑PCBs in sediment(Fig.3).

The relationship between the samples and environmental factors indicated that the samples#1,#1*,#1S,#1*S,#3,#3*, #3S,#3*S,#6,#6*,#6S,and#6*S,taken from a long and narrow watercourse with a high fl ow rate,were symmetrically distributed near the three environmental indices of flow rate, conductivity,and turbidity.The samples#2,#2*,#2S,#2*S, #4,#4*,#4S,#4*S,#5,#5*,#5S,and#5*S,taken from a laketype watercourse with plentiful plants,were all located near the two index arrows of river width and biomass,and in the reverse direction of fl ow rate index.

Therefore,channel morphology and environmental indices had a significant impact on PCB residues and their composition in the water.The high temperature,ORP,DO concentration,pH,fl ow rate,and narrow watercourse were propitious to the generation of low-chlorinated PCBs through the degradation of highly chlorinated congeners and their diffusion into the overlying water.The low temperature,laketype watercourse,and overflow weir accelerated the deposition of suspended particles and PCBs adsorbed by the particles into sediment(Table 4).

3.5.Effect of channelmorphology on ecological risks of PCBs in water and sediment

The toxic equivalency factor(TEF)method was employed to assess the effect of channel morphology on the potential ecological risks of PCBs in water of the study area.The 2,3,7,8-tetrachlorodibenzo-p-dioxin(TCDD)is the mostpotent congener within these groups of compounds,and several PCBs have been found to have toxic responses similarto those caused by TCDD(Giesy and Kannan,1998).As a result,the TEF method established by the World Health Organization(WHO) was used to evaluate the effects of these compounds on human and environmental health.The concentrations of these dioxinlike compounds can be converted into 2,3,7,8-TCDD toxic equivalent concentrations(TEQ)(Van den Berg et al.,1998; Wang et al.,2008).Then,the toxicity of the sample equals the summation of TEQ of each congener.The calculation was carried out as in Eq.(1):

where Fiis the toxic equivalency factor of the i th PCB congener,and Ciis the content of the i th PCB congener in water(Zhao et al.,2010).

According to relevant literature(Van den Berg et al.,1998, 2006;Yang et al.,2010),we selected seven indicative dioxinlike PCBs to calculate the TEQ values of water and sediment samples.The Fivalues were provided by the WHO:0.000002, 0.000005,0.000030,0.000030,0.000010,0.000100,and 0.000010 for PCB 28,PCB 52,PCB 101,PCB 118,PCB 153, PCB 170,and PCB 180,respectively.

As shown in Fig.5,the average TEQ values of dioxin-like PCBs in water samples ranged from 0.04 to 0.39 pg/L,with an average of 0.22 pg/L.The largest reduction percentages of TEQ induced by the overfl ow weir and lake-type watercourse were 67%and 70%,respectively.The variation tendency of TEQ in water with different channel morphologies in summer and autumn was basically consistent.The average TEQ values firstdecreased upstream of site#4,reached the highestvalue at site#5,and then decreased again at site#6.

Fig.4.Ordination diagram of PCB residues,environmental indices,and samples.

Table 4 Relationship between residual PCBs and environmental indices in RDA analysis.

The variation tendency of TEQ values in sediment was signifi cantly different from that in water,and sites#2 and#4 were the inflection points of a trend line.The overfl ow weir and lake-type watercourse play an important role in sediment precipitation and the reduction of TEQ.Based on the comprehensive analysis of the two kinds of change trends of TEQ values in water and sediment,we find that there are two kinds of sources of pollution in the river.The first pollution source,which is mainly field water,has a higher percentage of low-risk PCBs and large amounts of particulate matters,and suffers from more deposition of suspended particles(Figs.2 and 5).The second pollution source,located between sites #4 and#5,has a high content of PCB 52 and PCB 153,with larger Fivalues and less suspended particle content.Therefore, the TEQ value at site#5 reached the highest risk value (0.39 pg/L)in water and maintained a lower levelin sediment. At site#4,the TEQ value decreased mainly because of the degradation and absorption ofshoreside vegetation and aquatic plants in a lake-type watercourse on PCBs.Therefore,the lake-type watercourse is propitious to the decrease of ecological risks induced by PCBs.

Fig.5.TEQ values in water and sediment under different channel morphologies.

4.Conclusions

The overfl ow weir,channelmorphology,and corresponding environmentalfactors had significanteffects on PCB residues. They affected the spatio-temporal distribution characteristics and the composition profile of PCBs in water and sediment. The high temperature,ORP,DO concentration,pH,flow rate, and narrow watercourse were propitious to the generation of low-chlorinated PCBs through the degradation of highly chlorinated congeners and their diffusion into the overlying water.The low temperature,lake-type watercourse,and overflow weir accelerated the deposition of suspended particles and PCBs adsorbed by the particles into sediment. Therefore,the residual∑PCBs concentrations in water were ranked in the following descending order:natural ecological watercourse,vertical concrete watercourse,and vegetationtype riprap watercourse.However,the residual∑PCBs concentrations in sediment were ranked in the following descending order:vertical concrete watercourse,vegetationtype riprap watercourse,and natural ecological watercourse. The highest∑PCBs concentrations in water and sediment samples appeared at sites#5 and#6,respectively.The concentration of low-chlorinated PCBs,including tri-CBs and tetra-CBs,was signifi cantly higher than the concentration of highly chlorinated PCBs including penta-CBs to deca-CBs. Moreover,the TEF method shows that the overflow weir and lake-type watercourse can remarkably reduce the residual concentration and ecological risks of PCBs.These study results can aid in the comprehensive management and pollution control of similar rivers.

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Received 1 August 2016;accepted 3 October 2016

Available online 7 January 2017

This work was supported by the National Natural Science Foundation of China(Grants No.41371307 and 51509129),the Open Foundation of State Key Laboratory of Pollution Control and Resource Reuse(Grant No. PCRRF12010),the State Key Laboratory of Soil and Sustainable Agriculture (Institute of Soil Science,Chinese Academy of Sciences)foundation(Grant No.0812201228),a project funded by the Priority Academic Program Development of Jiangsu Higher Education Institutions,and the Top-notch Academic Programs Project(TAPP)of Jiangsu Higher Education Institutions.

*Corresponding author.

E-mail address:zzh4000@126.com(Zhen-hua Zhao).

Peer review under responsibility of Hohai University.

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