Baline
Spatial variation,environmental risk and biological hazard asssment of heavy metals in surface diments of the Yangtze River estuary
Haotian Wang,Jiawei Wang,Ruimin Liu ⇑,Wenwen Yu,Zhenyao Shen
cougarState Key Laboratory of Water Environment Simulation,School of Environment,Beijing Normal University,No.19,Xinjiekouwai Street,Beijing 100875,China
a r t i c l e i n f o Article history:
Available online xxxx
Keywords:
Yangtze River estuary
Heavy metal contamination Spatial distribution
Environmental risk asssment Biological hazard asssment
a b s t r a c t
30samples of eight heavy metals were collected in February 2011within Yangtze River estuary (YRE).The mean concentrations met the primary standard criteria bad on Marine Sediments Quality of China.The spatial distribution showed that a gradient concentration decread gradually fr
confirmationom inner-estuary to river mouth.Anthropogenic inputs might be the main contributor,and fine grained diments might also aggravate the heavy metal contamination.The asssment results indicated that the YRE was in low risk of contamination caud by every single heavy metal.However,it was in considerable degree of con-tamination considering combination of all the heavy metals.The toxicities of heavy metals might be elevated when heavy metals were in combination.Arnic should be of primary concern due to its higher asssment values and the potential of adver biological effects.And the concentration of As in the YRE had a trend to increa becau of anthropogenic activities nearby.
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Metallic elements from anthropogenic inputs due to the rapid economic development especially in the vicinity of coastal areas have caud vere environmental cris in marine ecosystem (Gao and Chen,2012;Xu et al.,2014).Heavy metal contamination in aquatic environment has recently drawn particular public atten-tions due to their toxicity,persistence and biological accumulation (Hu et al.,2013c;Li et al.,2013a ).In addition,heavy metals are likely to be conrved and accumulated by aquatic organisms (Sharma and Agrawal,2005).Once enriched by aquatic organisms,heavy metals might be converted to more toxic organic complexes,which might cau potential risk to human healt
h through food web (Jiang et al.,2012;Hu et al.,2013b ).When accumulating to a toxic concen-tration level,heavy metals might lead to biological hazard risk (Yi et al.,2011).So heavy metal contamination might not only po a risk to aquatic organisms,but cau long-term implication on human health,even damage on ecosystem (Ip et al.,2007;Wang and Rainbow,2008;Dou et al.,2013).
Sediments show a great capacity to accumulate heavy metals even from low concentrations in aquatic environment (Nemr et al.,2007;Christophoridis et al.,2009).It has been reported that most heavy metals loaded in aquatic ecosystem are associated with diments,especially the bottom diments (Singh et al.,2005;Kucukzgin et al.,2008;Zahra et al.,2014).Heavy metals fixed by diments which act as both final sink for various chemical pollutants and potential condary source might be relead back into water columns with changed environmental conditions (Hill et al.,2013;Hu et al.,2013a ).
In order to take measures to protect aquatic ecosystem,it is nec-essary to asss the heavy metal contamination in diments,and it is important to differentiate the influence caud by natural source or anthropogenic source (Yu et al.,2008).Besides asssing the heavy metal contamination,evaluating the biological adver risk is equally important.Enrichment factor (EF),index of geoaccumula-tion (I geo ),degree of contamination (DC),diment quality guideli-nes (
SQGs),mean ERM quotient (M-ERM-Q)and hazard quotients (HQ)were indices which widely applied to asss the degree of con-tamination and adver ecological effects respectively (Feng et al.,2011;Sundaray,et al.,2011;Gao and Chen,2012;Lin et al.,2013;Hasan et al.,2013;Li et al.,2013b;Wang et al.,2014).
For small scale regions,mean concentration values are enough to be ud to asss the heavy metal contamination.But the spatial distribution of heavy metals is of primary concern in asssing pol-lution for large scale regions.Many studies have proved that heavy metal contaminants are not uniformly distributed and varied spa-tially and temporally (Zhao et al.,2012a;Gu et al.,2012;Qiao et al.,2013).Generally,geostatistics and geographic information system (GIS)are widely ud to exhibit an overall distribution of heavy metals in study areas (Ho et al.,2013).
The Yangtze River estuary (YRE)is one of the largest estuaries in China.With the fastest economic development,the YRE has suf-fered heavy metal contamination (Feng et al.,2004).As a very
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⇑Corresponding author.Tel./fax:+861058800829.
E-mail address:liurm@ (R.Liu).
important industrial center,shipyards,petrochemical plants,steel mills and many other plants are built in ambient towns (Du et al.,2013).There were more than 5⁄106tons/d of industrial effluent and domestic wage discharged into the YRE (Zhang et al.,2009).In addition,the construction of the Three Gorges Dam in the upstream of the YRE has influenced some properties of coastal waters and diments of the East China Sea such as nutrient status,salinity and diments regime,which might affect the toxicity and distribution of heavy metals (Christophoridis et al.,2009;Gao and Li,2012;Feng et al.,2014b ).There have been many previous stud-ies dedicated to investigating heavy metals in the YRE (Zhang et al.,2007;Li et al.,2009;Zhao et al,2012a;Feng et al.,2014a;Wang et al.,2014).However,it is also meaningful to carry out continuous
In February 2011,30sampling sites were t in the YRE (121E–122.75E,31.75N–32N (Fig.1).The surface diments were sampled to a depth of 2–5cm.At each site,three surfaces diments were collected and mixed into a composite sample.All the samples were frozen dried and sieved through a 1mm clean plastic net and then ground in an agate mortar.The grained samples were shaken through nylon membrane sieve (0.071mm)to obtain a fine homo-geneous powder.Samples were microwave-digested in acid-cleaned Teflon vesls containing 5mL of nitric acid and 2mL hydrofluori
c acid for 30min at 200°C.After cooling for at least 1h,the vesls were added to 0.9g of boric acid and then micro-wave-digested for another 30min.After cooling for at least 1h again,the digested sample was transferred to a plastic test tube Fig.1.Map of study area and location of sample sites.
2H.Wang et al./Marine Pollution Bulletin xxx (2015)xxx–xxx
predict the values of attributes at unsampled locations,which con-siders the direction of variations and incorporates trends into the interpolation to create better predictions.Ordinary kriging is esti-mated by a linear combination of the obrved values with weights (Wang et al.,2014):
Z Ãðx 0Þ¼
X
n i ¼1
k i Z ðx i Þð1Þ
where Z ⁄(x 0)is the estimated values of Z at the point x 0,Z (x i )is the sampled value at the point x i and k i is the weight placed on Z (x i ).Indices such as enrichment factor (EF),index of geoaccumula-t
ion (I geo )and degree of contamination (DC)were lected to asss the environmental risk.The classification of each index was listed in Table 1.
Enrichment factor (EF)is commonly ud to estimate the poten-tial sources of heavy metals and asss the extent of metal con-tamination compared to the background (Hu et al.,2013c ).Al is lected as a normalizer becau not only it exists in diments at a respective high level,but it is rich in the Earth’s crust assuming that it is free from anthropogenic impact.EF values for each metal in diment are calculated as follows (Buat-Menard and Cheslet,1979):
EF ¼
C =Al ð dim ent Þð2Þ
where C is the concentration of examined element,the ratio of C/Al stands for the ratio of the concentration of element C to Al.The numerator stands for the ratio in diment,the denominator stands for the ratio in background.
Index of geoaccumulation index (I geo )is another classical asssment parameter to evaluate the heavy metal contamination in diments with corresponding natural background level as ref-erence (Muller,1969).The I geo is defined by the following equation:
I geo ¼Log 2ðC n =1:5B n Þ
ð3Þ
where C n is the examined concentration of metal n in the di-ments.The factor 1.5is ud to minimize the effect of possible var-iations in the background values which might be attributed to lithological variations in the diments (Hu et al.,2013b ),and B n is the geochemical background value of metal n .
Degree of contamination (DC)is the index to asss the extent of multi-metal contamination in the diments,which is different from single-metal factors.According to Hakanson (1980),the equa-tion to calculate DC is:
DC ¼
X 8i ¼1
自学韩语C i f ð4Þ
C i f ¼C i 0À1=C i n
ð5Þ
where C i f is the contamination factor of metal i ,C i 0À1is the mean concentration of metals,C i n is the geochemical background values of metal i .
Indices such as numerous diment quality guidelines (SQGs),the mean ERM quotient (M-ERM-Q)and the hazard quotients (HQ)were lected to asss the biological hazard.The classifica-tion of each index was listed in Table 1.
Numerous diment quality guidelines (SQGs)have been devel-oped to evaluate the contaminant toxicity or risks to aquatic ecosystem (MacDonald et al.,2000).Two frequently ud metrics are established for evaluating potentially adver effects of con-taminants on ecosystems bad on their concentrations (Feng et al.,2011).The lower 10th percentile of the effects data is the effects range low (ERL)concentration,while the median or 50th percentile of the effects data is referred to as the effects range median (ERM)(Long et al.,1995).In this study,ERL and ERM were chon to evaluate the potential adver biological effects.The val-ues of ERL and ERM were referred from Long et al.(1995).
All the SQGs are applied through evaluating individual heavy metals by comparing the heavy metal c
oncentrations with their corresponding limit concentrations (Gao and Chen,2012).Bad
Table 1
The classification of environmental risk and biological hazard asssment indices.Index Classification Description
References
EF
62Deficiency to minimal enrichment Buat-Menard and Cheslet (1979)
2–5Moderate enrichment 5–20Significant enrichment 20–40Very high enrichment
confident>40Extremely high enrichment
I geo
60Unpolluted
Muller (1969)
花的英文怎么写
starup0–1Unpolluted to moderately polluted 1–2Moderately polluted
四分之三英语
2–3Moderately polluted to strongly polluted 3–4Strongly polluted
4–5Strongly to extremely polluted >5Extremely polluted
DC 66Low degree of contamination
Hakanson (1980)
6–12Moderate degree of contamination 12–24Considerable degree of contamination >24
Very high degree of contamination ERL and ERM guidelines <ERL
Minimal effects range
Long et al.(1995)
Between ERL and ERM Effects would occasionally occur >ERM Effects would frequently occur M-ERM-Q <0.1
9%probability of toxicity Long et al.(2000)
0.11–0.521%probability of toxicity 0.51–1.549%probability of toxicity >1.5176%probability of toxicity HQ <0.1No adver effects Feng et al.(2011)
0.1–1Potential hazards 1–10Moderate hazards >10
High hazards
H.Wang et al./Marine Pollution Bulletin xxx (2015)xxx–xxx
3
on the fact that heavy metals always occur in diments as com-plex mixtures,the mean ERM quotient (M-ERM-Q)method has been applied to determine the possible biological effect of com-bined toxicant groups by calculating mean quotients for a large range of contaminants using the following formula (Long et al.,2006):
M-ERM-Q ¼X
n i ¼1
ðC i =ERM i Þ=n
ð6Þ
where C i is the concentration of metal i ,ERM i is the ERM values for metal i and n is the number of metal i .
The potential toxic risk to aquatic ecosystem can also be evaluated by calculating the hazard quotients (HQ)of the chemical contaminants using the equation (Urban and Cook,1986):
HQ ¼
SCC SQG
ð7Þ
where SCC is the concentration of metals in diments in l g/g,and SQG is the diment quality guideline in l g/g.SQG values were determined at ERL levels according to Long et al.(1995).
Of the eight heavy metals,Mn and Cd were the metals with the highest and lowest mean concentrati
ons respectively (Table 2).The two metals were also of concern due to the large difference between their mean concentrations and the background values (Table 3).According to the backgrounds of eight heavy metals,the mean concentrations of most heavy metals were greater than the corresponding backgrounds,indicating that anthropogenic activities had a direct impact on the concentrations of heavy met-als in diments.Furthermore,bad on Marine Sediment Quality of China (Table 3),the overall mean concentrations of As,Cd,Cr,Cu,Pb and Zn all met the primary standard criteria except Mn and Ni for which there were no criteria.
Compared with other estuaries in the world (Hyun et al.,2007;Gao and Chen,2012;Hu et al.,2013a;Gu et al.,2013),the mean concentrations of eight heavy metals in the YRE were not outstand-ing.The mean concentrations of Cd,Cr,Cu and Zn were higher than tho found in diments of Changhua River estuary in China,but lower than tho found in diments of coastal Bohai Bay in China and Manzala of Nile in Egypt.The mean concentrations of Cr and Ni were higher than tho found in diments of Masan Bay in Korea.The mean concentration of As was clo with that of Changhua River estuary.In general,heavy metal contamination in the YRE
was not the most rious compared with other large estuaries of world.
The spatial distributions of eight heavy metals in the diments of whole estuary all exhibited a gradient trend:the concentrations decread from inner-estuary to river mouth (Fig.2).The gradient concentrations of heavy metals might result from the dilution effect caud by complicated tidal cycles and oceanic currents (Zhao et al.,2012b ).
Furthermore,higher concentrations of eight heavy metals were always found in the South Branch of inner-estuary (site-4).The phenomenon was worthy to be of great environmental concern,suggesting that anthropogenic influences nearby might be respon-sible for the higher concentrations.The industrial effluents and municipal wage discharged by local plants might be the main contribution.It was reported that over 30km 3wage including considerable industrial effluents was discharged into the YRE each year (Gu et al.,2013).Moreover,the inner estuary contained many main shipping channels,the spilling of oil,the combustion of pet-roleum and the emissions of automobiles might be important con-tributors for the higher concentrations (Zhao et al.,2012b ).
Besides anthropogenic inputs,grain size of inner-estuary might also have influence on the higher concentrations.Heavy metal con-centrations might be affected by grain size (Zhang et al.,2008;Xu et al.,2014).Heavy metal concentrations were positively and high-ly correlated with fine-grained diments contents,especially silt and clay contents (Owen and Sandhu,2000;Zhang et al.,2009;Gan
et al.,2013).Furthermore,it has been reported that organic matter played an important role in controlling heavy metal con-centrations (Schmitt et al.,2002;Lin et al.,2002).The fine grained diments also controlled total organic carbon concentration and its spatial distribution in surface diments (Gao and Li,2012).As expected,clay and silt the fine-grained diments abundant in the inner-estuary (Chen,et al.,2004;Zhang et al.,2013),higher concentrations of heavy metals exhibited in the inner-estuary might be reasonable.
In addition,lower concentrations of all the heavy metals were always found near the mouth of Huangpu River.The diluting effect caud by Huangpu River might reduce heavy metal concentra-tions of downstream resulting in a sudden change of spatial distri-bution.Huangpu River received large amount industrial and domestic wage considering the city Shanghai with high level economic activities (An et al.,2009).However,compared to Yangtze River,heavy metal pollution was not rious in the Huang-pu River (Zhang,2007).The less polluted water of Huangpu River might have contribution on diluting the higher concentrations of heavy metal in the surroundings of site-4.
The mean EF values for Cd,Cu,Mn,Ni,Pb and Zn were all lower than 1.5,while the mean EF value of Cr was nearly 1.5(Fig.3a).Generally,an EF value of about 1suggested that a given metal may be entirely from crustal materials or natural weathering pro-cess,and EF value greater than 1.5indicat
ed that a significant portion of trace metal was delivered from non-crustal materials or non-natural weathering process (Zhang and Liu,2002;Zhang et al.,2009).Although some sites of mean EF values for Cd,Cr and Mn were greater than 1.5,most metals showed respective low EF values (<1.5),indicating that the metals were scarcely influenced by anthropogenic impact and almost entirely came
Table 2
Heavy metal concentrations (l g g À1)in surface diments of the Yangtze River estuary.
Mean
Min Max As 9.1 5.0316.88Cd 0.190.070.71Cr 79.150.35123.1Cu 24.79.6749.21Mn 772.7395.991417.32Ni 31.919.9242.19Pb 23.814.845.09Zn
82.9
46.52
126.74
Table 3
The heavy metal guideline values (l g g À1)of Marine Sediment Quality of China and background values (l g g À1)in surface diments of the Yangtze River estuary.Criteria
吉的堡少儿英语教材As Cd Cr Cu Mn Ni Pb Zn References
Sediment Quality I 200.580.035.0na na 60.0150.0AQSIQ (2002)Sediment Quality II 65.0 1.5150.0100.0na na 130.0350.0AQSIQ (2002)
Background
8.9
0.09
13
23
542
34.9eversion
19
87
Gu et al.(2013)and Fang et al.(2013)
4H.Wang et al./Marine Pollution Bulletin xxx (2015)
xxx–xxx
Fig.2.The spatial distributions of eight heavy metals in surface diments of the Yangtze River estuary.
from natural weathering process or crustal materials.However,the mean EF value of As was more than 1.5,suggesting that the anthro-pogenic inputs might have influence on the higher enrichment of As.Generally the heavy metal contamination was not of primary environmental concern becau almost entire estuary had defi-ciency to minimal enrichment for each heavy metal except As,although a few regions had moderate enrichment for specific met-als.However,the YRE had moderate enrichment for As.
Though a few specific sites had values greater than 0,almost all the mean values of I geo for Cu,Mn,Pb and Zn were lower than 0,
indicating that no pollution caud by the metals (Fig.3b).Almost all the mean I geo values for Cd,Cr and Ni were greater than 0,suggesting that the YRE was unpolluted to moderately polluted by the metals respectively.With all the I geo values of As greater than 1,the whole estuary was moderately polluted to strongly pol-luted by As.The South branch and North branch as well as part of coastline near the city Shanghai exhibited the higher I geo values of As,where were moderately to he
avily polluted.Similar with As,Ni also exhibited a gradient distribution of I geo values:moderately contaminated regions changed gradually to uncontaminated regions from inner-estuary to river mouth.
The mean value of DC was 16.5,and the spatial distribution of DC showed that the whole estuary was in considerable degree of contamination (Fig.3c).The result indicated that the level of pollu-tion in the YRE assd by DC was more rious than that evaluat-ed by EF and I geo independently.The reason might be explained that diments accumulated by multiple heavy metal elements would show higher toxicities and aggravate the contamination due to the interaction of heavy metals with each other (Fu et al.,2013).
Among all the heavy metals,Arnic could be verified the main pollutant in comparison with other heavy metals.However,the concentration of As fluctuated around the background level and indicated lower ecological risk in diments from the main-stream,tributaries,and the lakes of the Yangtze River catchment of Wuhan,China (Yang et al.,2009).It indicated that the higher concentration of As in the inner-estuary was not from the flow of upstream.Anthropogenic inputs might be the main contributor causing higher concentration of As in the YRE.The main anthro-pogenic inputs of As included mining by-product,metal refining process,metal smelting,fossil fuels combustion,agricultur
al u such as herbicides,pesticides and phytocide,pigment produc-tion and leaded petroleum manufacture (Smedley and Kinniburgh,2002;Paul et al.,2009;Ren et al.,2010).Higher concentration of As exhibited in the YRE might be attribute to high level economic activities in the inner estuary and along the coastline.
It was also worthy to pay attention that the surroundings of site-4with higher concentration of As were in the vicinity of salt marsh abundant in S.alterniflora (Wang et al.,2012).It has been reported that the concentration of As was influenced with the a-sonal variation which affected the asonal changes of plant growth causing the periodical oxic and anoxic diments,and the concentration of As was highest in August (Wang et al.,2012).Arnic tended to be accumulated in diments under oxic condi-tion,whereas relead back into water under the occurrence of hypoxia (Li et al.,2014).The oxygen would not deplete considering that the samples were collected in February when most plants did not bloom.Furthermore,the fine-grained diments,especially the clay which containing Fe oxides with the capacity of absorbing large amounts of As on their surface,controlled the concentration and distribution of As (Wang et al.,2010).Organic matters and oxi-des of Fe and Mn also had influence on the concentration and dis-tribution of As (Paikaray et al.,2005;Ren et al.,2010).
In addition,over last one hundred years from 1900s,the con-centration of As in the YRE had a trend to increa in general ascribed to the rapid industrialization with the aggravation of anthropogenic activities (Duan et al.,2013).Another phenomenon should be paid attention that the significant positive correlations existed between As and total nitrogen (Yi et al.,2011),which had been significantly increasing during the last three decades (Chen et al.,2012).This obrvation might further prove the increasing trend for the As concentration in the YRE.
The Cd,Pb and Zn results showed that no sites in the study area exceeded the ERL guideline (Table 4).For other metals,the sites which bellowed the ERL guideline ranged from 6.7%to 93.3%,and the remaining samples all fell in the range between ERL and
(a) enrichment factors (EF)
(b) index of geoaccumulation (I geo )
(c) Degree of contamination (DC)
I g e o
3.The spatial distributions of environmental risk asssment indices:enrichment factors (EF);(b)index
of geoaccumulation (I geo );and (c)degree contamination (DC).
6H.Wang et al./Marine Pollution Bulletin xxx (2015)
xxx–xxx
