Chemosphere 84 (2011) 1506–1511

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Derivation of aquatic predicted no-effect concentration (PNEC) for2,4-dichlorophenol: Comparing native species data with non-native species data

Xiaowei Jin a, Jinmiao Zha a, Yiping Xu a, Zijian Wang a,⇑, Satyanarayanan Senthil Kumaran b

a State Key Laboratory of Environmental Aquatic Chemistry, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, P.O. Box 2871, Beijing 100085, Chinab Unit of Toxicology, Bharathiar University, Coimbatore 641 046, India

a r t i c l e i n f o a b s t r a c t

Article history:Received 12 October 2010Received in revised form 24 March 2011Accepted 7 April 2011Available online 4 May 2011

Keywords:2,4-DichlorophenolChronic toxicityNative speciesPredicted no-effect concentrationSpecies sensitivity distribution

0045-6535/$ - see front matter � 2011 Elsevier Ltd. Adoi:10.1016/j.chemosphere.2011.04.033

Abbreviations: 2,4-DCP, 2,4-dichlorophenol; PNECtration; SSD, species sensitivity distribution; NOEC, ntion; LOEC, lowest observed effect concentration;toxicant concentration; CCC, criterion continuous cochronic ratios; AF, application factor.⇑ Corresponding author. Address: State Key Laborat

Chemistry, Research Center for Eco-Environmental SHaidian District, Beijing 100085, China. Tel.: +86 10 63543.

E-mail address: wangzj@rcees.ac.cn (Z. Wang).

2,4-Dichlorophenol (2,4-DCP) is known as an important chemical intermediate and an environmentalendocrine disruptor. There is no paper dealing with the predicted no-effect concentration (PNEC) of2,4-DCP, mainly due to shortage of chronic and site-specific toxicity data. In the present study, toxicitydata was obtained from the tests using six Chinese native aquatic species. The HC5 (hazardous concen-tration for 5% of species) was derived based on the constructed species sensitivity distribution (SSD),which was compared with that derived from literature toxicity data of non-native species. For inverte-brates, the survival no-observed effect concentrations (NOECs) were 0.05 and 1.00 mg L�1 for Macrob-rachium superbum and Corbicula fluminea, respectively. NOECs based on fishes’ growth were 0.10, 0.20and 0.40 mg L�1 for Mylopharyngodon piceus, Plagiognathops microlepis and Erythroculter ilishaeformis,respectively. For aquatic plant Soirodela polyrhiza, NOEC based on concentration of chlorophyll was1.00 mg L�1. A final PNEC calculated using the SSD approach with a 50% certainty based on different taxaranged between 0.008 and 0.045 mg L�1. There is no significant difference between HC5 derived fromnative and that from non-native taxa.

� 2011 Elsevier Ltd. All rights reserved.

1. Introduction

Chlorophenols are widely used synthetic organic compoundseither used as synthesis intermediates in dyestuffs and pesticidesor as biocides themselves. Chlorophenols commonly occur inindustrial wastes and as direct pollutants in the water environ-ment, which have been frequently detected (Czaplicka, 2004; Gaoet al., 2008). Among them, 2,4-dichlorophenol (2,4-DCP) is themost abundant chlorophenol in aquatic environment (Houseet al., 1997). 2,4-DCP is usually used as a mothproofing agent, ger-micide, antiseptic and precursor in the production of herbicide 2,4-dichlorophenoxyacetate (Zhang et al., 2008). Although 2,4-DCPpresently has no direct commercial application, it is used as animportant chemical intermediate, it is also synthesized from dilute

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, predicted no-effect concen-o-observed effect concentra-MATC, maximum allowablencentration; ACRs, acute to

ory of Environmental Aquaticciences, Shuangqing Rd. 18,284 9140; fax: +86 10 6292

aqueous solutions, and released into the environment as anintermediate compound from paper mills and chemical industries.2,4-DCP is recognized as a priority pollutant in the aquatic environ-ment in the USA as well as in China due to their high toxicity toaquatic life, resistance to degradation, and potential to be bioaccu-mulated (USEPA, 1979; Yin et al., 2003). It is also been reportedthat 2,4-DCP is an endocrine disruptor (Zhang et al., 2008). In addi-tion, permanent impairment of vision or blindness of the eyes andsevere injury of the upper respiratory tract were observed whilehuman and animals were exposed to 2,4-DCP (USEPA, 2000). Theconcentrations of 2,4-DCP in rivers were less than 1 lg L�1 in Uni-ted Kingdom (House et al., 1997) and ranged from 1.1 to19 960 ng L�1 in China (Gao et al., 2008). Therefore, the deleteriouseffects and ecological risk of 2,4-DCP on estuarine and coastal eco-systems have raised considerable concern.

An important step in ecological risk assessment of chemicals isthe determination of the maximum concentration at which theecosystem is protected, i.e., the predicted no-effect concentration(PNEC). PNECs are usually derived from laboratory-based toxicitytest (especially for chronic) using well-defined protocols on a lim-ited number of species. Despite the numerous toxicity data of 2,4-DCP available on fish, Daphnia and algae, few have been tested forits adverse effects on the environment on the basis of chronic testsowing to the high financial investment required, especially for lo-cal species in China (Yin et al., 2003). So no final decision was made

X. Jin et al. / Chemosphere 84 (2011) 1506–1511 1507

regarding PNEC derivation for 2,4-DCP. Yin et al. (2003) have de-rived a criterion continuous concentration (CCC) of 0.212 mg L�1

for protection of aquatic life in China using acute to chronic ratios(ACRs) (also called application factors, AFs). However, the use ofACRs has been criticized (Chapman et al., 1998; Crane and New-man, 2000; Roex et al., 2000; Isnard et al., 2001). In some cases,average ACRs may be inadequate to extrapolate accurately fromacute to chronic value (Brix et al., 2001; Besser et al., 2005).

The present paper focuses on the derivation of PNECs using thespecies sensitivity distribution (SSD) method (Garay et al., 2000;Hampel et al., 2007; Caldwell et al., 2008; Amorim et al., 2010).Usually a point estimate known as the HC5 (hazardous concentra-tion for 5% of species) is calculated. This is a concentration that willexceed no more than 5% of species effect levels. For this purpose,SSDs are generally constructed by fitting cumulative probabilitydistributions to a plot of species toxicity data against rank-assigned percentile (Van Straalen and Denneman, 1989; Aldenbergand Slob, 1993; Wheeler et al., 2002). The SSD method may resultin more robust PNECs, but only a substantial amount of chronicdata for several taxonomic groups is available, for most new andexisting substances, this type data is lacking (Sijm et al., 2001). Fur-thermore, in most countries, SSD curves and HC5 values are beingused to derive PNECs for toxicants based on local species data orsite-specific data (USEPA, 1985; ANZECC&ARMCANZ, 2000; Yinet al., 2003). The potential use of non-native toxicity data fordescription of local problems is controversial, and leaves one toquestion whether criteria based on species from one geographicalregion provide appropriate protection for species in a differentregion (Davies et al., 1994). However, this argument could not beresolved previously in large part due to the paucity of toxicity dataapplicable for local species.

In the current study, chronic toxicity tests were conducted forsix Chinese native species, including three fish species, two inver-tebrate species and one hygrophyte species. Then, the experimen-tal chronic toxicity data for 2,4-DCP combined with data reportedon native species in the literature were compared with non-nativetaxa using HC5 and values which was calculated by fitting SSDcurves. The aims to this study are (1) a supplement to 2,4-DCPchronic toxicity database, (2) derivation of PNEC for 2,4-DCP, and(3) comparison of the difference between native species and non-native species exposure to 2,4-DCP and discussion of the necessityof native species for the establishment of PNECs for site-specificecological risk assessment.

2. Materials and methods

2.1. Test species and conditions

Six Chinese local species of two benthic invertebrates (Corbiculafluminea and Macrobrachium superbum); three species of fish(Mylopharyngodon piceus, Plagiognathops microlepis and Erythrocul-ter ilishaeformis) and one hygrophyte (Soirodela polyrhiza) were se-lected primarily based on their wide distribution, economicsignificance and adaptability to laboratory conditions. These testspecies were provided by the Huazhong Agricultural University(Wuhan, China), and were acclimated to test conditions(24 ± 1 �C, pH 7.24 ± 0.16) for more than 2 weeks prior to theexperiments.

In the experiment, the lowest average dissolved oxygen concen-tration for all the test species were approximately 80% of satura-tion. The pH ranged from 7.4 to 7.9. Conductivity (mmhos cm�1)and hardness (as mg L�1 CaCO3) averaged 512 and 100, respec-tively during the freshwater tests. Strip chart records of tempera-ture showed that an average temperature of 24 ± 1 �C wasmaintained for all tests.

2.2. Test chemical

Analytical grade 2,4-DCP (CAS RN: 120-83-2) with 99.0% puritywas purchased from Sigma (Deisenhofen, Germany). Tap water,dechlorinated with activated carbon, was used for all tests. Thewater quality parameters were measured as follows: pH: 7.24± 0.16; dissolved oxygen concentration (DO): 8.43 ± 0.24 mg L�1,total organic carbon (TOC) content: 0.017 mg L�1, and total hard-ness: 100 mg L�1.

2.3. Exposure of organisms

Chronic exposures of 2,4-DCP to six native species were con-ducted using daily replaced static-renewal diluters. Test solutionswere maintained by renewal of 90% every 24-h. There were fivetreatments (nominal concentration) of test chemical plus a controland three replicates of each treatment, each beaker containing 10test organisms. Test concentrations were chosen based upon theresults of preliminary acute toxicity tests (data not shown). Dis-solved oxygen, conductivity, temperature, pH, and salinity weremeasured every 2 d with a multiparameter water quality meter(YSI Model 85 m; Yellow Springs, OH).

2.3.1. InvertebratesThree week survival tests using M. superbum (39.63 ± 0.47 mm,

0.87 ± 0.08 g) and C. fluminea (20.80 ± 0.20 mm, 3.66 ± 0.40 g) wereconducted in glass container containing 4000 mL and 1000 mL testsolution, respectively. The nominal concentrations for C. flumineaand M. superbum used in the study were 0, 1.00, 2.00, 4.00, 6.00,8.00 mg L�1 and 0, 0.05, 0.10, 0.20, 0.30, 0.40 mg L�1 2,4-DCP,respectively. Test organisms were fed daily with a solution of mic-roalgae concentrate prepared from instant algae shellfish diet andnannochloropsis concentrate according to standard guidelines forconducting chronic tests with macro invertebrates (ASTM, 1993).During the exposure, beakers were kept in an incubator at24 ± 1 �C with 16 L: 8 d photoperiod. Mortality and abnormalbehavior were monitored daily and dead organisms were removedimmediately. At the end of test, the 21 d no-observed effect con-centrations (NOEC) and the lowest observed effect concentrations(LOEC) were derived by analyzing survival rate and behavioral ef-fects of test organisms.

2.3.2. FishTwenty-eight days chronic growth inhibition toxicity test using

early life stages of M. piceus (17.65 ± 0.40 mm, 3.80 ± 0.22 �10�2 g), P. microlepis (16.40 ± 0.37 mm, 2.67 ± 0.19 � 10�2 g) andE. ilishaeformis (23.59 ± 0.29 mm, 5.50 ± 0.20 � 10�2 g) were donein glass container containing 1000 mL test solution. The nominalconcentrations used in these studies were 0, 0.10, 0.20, 0.40, 0.60and 0.80 mg L�1 2,4-DCP for both P. microlepis and E. ilishaeformis,and 0, 0.10, 0.20, 0.40, 0.80, 1.60 mg L�1 2,4-DCP for M. piceus.During the exposure, beakers were kept in an incubator at24 ± 1 �C with 16 L: 8 d photoperiod, and juvenile fishes were fedwith brine shrimp at a rate of 0.1% body weight twice daily. Atthe end of the test, length and weight of all tested fish weremeasured and survival rate was calculated at each concentration,from which NOEC and LOEC were derived. For fry growth, thespecific growth rate (SGR) was chosen because it is less dependenton the initial size of the fish and on the time between measure-ments than the other endpoint such as relative growth rate(RGR) (Mallett et al., 1997). The SGR was calculated as ((ln(finalmass) � ln(initial mass)) � 100)/d of exposure (Crossland, 1985).At the end of the chronic toxicity test, all animals survived in thecontrol.

1508 X. Jin et al. / Chemosphere 84 (2011) 1506–1511

2.3.3. Aquatic plantChronic toxicity of S. polyrhiza was conducted in 90 mm glass

crystallizing dish with 200 mL of test medium for 10 d. The nomi-nal concentrations of 2,4-DCP used in the definitive studies were 0,1.00, 5.00, 10.0, 25.0 and 50.0 mg L�1. At the end of the test, chlo-rophyll was measured using 7550 ultraviolet and visible spectro-photometer (Zhang and Jin, 1997), from which NOEC and LOECwere derived.

2.4. Chemical analysis

During the acute and chronic toxicity exposure, 2,4-DCP treatedaquarium samples were randomly collected during the experi-ments from control, low, medium, and high dosage concentrations.Triplicate samples were taken from one tank of each concentrationlevel. Samples were spiked with surrogate standard (Biphenol A-d16), adjusted to pH < 2 with 6 lM hydrochloride buffer and en-riched with SPE using C18 cartridge. The cartridges were elutedwith 10 mL dichloromethane (DCM). All of the extracts were evap-orated under a gentle stream of nitrogen. Derivatization was per-formed to reduce the polarity of phenols. The dried residueswere derivatized by bis(trimethylsilyl)trifluoroacetamide (BSTFA)with 1% trimethylchlorosilane (TMCS), which were heated in aheating block at 60 �C for 2 h. Samples were maintained at 4 �Cin brown polypropylene bottles in the dark until analysis.

The samples were analyzed using an Agilent 6890 gas chro-matograph equipped with Agilent MSD 5975 mass spectrometer.The capillary column of 30 m � 0.25 mm i.d. 0.25 lm HP-5 wasused. Gas chromatography (GC) oven temperature was pro-grammed from 40 �C to 300 �C via a ramp of 10 �C min�1 and main-tained at 40 �C for 2 min and at 300 �C for 15 min. Then constantpressure model was used in the whole analysis process. Sampleinjection (1 lL) was in splitless mode. Mass spectrum (MS) wasoperated in full-scan mode from m/z 50–700 for qualitative analy-sis, selected ion monitoring (SIM) mode for quantitative analysis.The inlet and MS transfer line temperatures were maintained at250 �C, and the ion source temperature was 300 �C. The data ofGC–MS were analyzed by the techniques of RTL and DRS (softwareprovided by Agilent).

2,4-DCP was not detected in control aquaria and in blanks. Mea-sured 2,4-DCP concentrations in the treated test species collectedduring experiments varied from 88.7% to 107.9% of nominal con-centrations (mean 95.1%, n = 72). Therefore, all subsequent chronictoxicity results were expressed on nominal concentrations of 2,4-DCP.

2.5. Statistical analysis

Data on chronic tests were analyzed using the SPSS Version 17software. The experimental data were checked for homogeneity ofvariance across treatments by using Levene’s test. The data weresubjected to one-way analysis of variance followed by Dunnett’smultiple comparison tests once the assumptions were met. Statis-tical significances were considered to be significant at p 6 0.05. TheNOEC was defined as the highest concentration that did not resultin a significant effect compared with the control. The LOEC was de-fined as the lowest concentration that did result in a significant ef-fect compared with the control, The maximum allowable toxicantconcentration (MATC) was equal to the geometric average of NOECand LOEC (USEPA, 1985).

2.6. Data collection and SSD generation

Additional chronic toxicity data for 2,4-DCP were collected fromexisting toxicity databases (e.g. ECOTOX database, http://cfpub.epa.gov/ecotox/), published literature, and government documents

following the principles of accuracy, relevance and reliability(Klimisch et al., 1997). NOECs were calculated from the availableliterature. When a NOEC was not available, MATC or LOEC or ECx

was used and noted. If more than one set of data for the same spe-cies was available, toxicity values for the most sensitive end pointwere chosen. In the case of multiple data on the same endpoint andspecies, the geometric mean was used. Toxicity data were consid-ered ‘‘Native’’ if test organisms occurred in natural ecosystems ofChina and if tests were conducted under local conditions. All localspecies data (including the six native species data in this study andother native data obtained from the literature) were combined andcompared with non-native taxa to 2,4-DCP by fitting SSD curves forchronic toxicity data. Sensitivity distributions were comparedusing the two-sample Kolmogorov–Smirnov test using the SPSSVersion 17 software.

We estimated lower (5% confidence), median (50% confidence),and upper (95% confidence) HC5 using ETX software (ETX 2.0,RIVM) based the method of Aldenberg and Jaworska (2000). Alog-normal distribution model was fitted to a minimum of ten datapoints, with model fit being evaluated using the Anderson–Darlinggoodness-of-fit test. The final PNECs were calculated as the derivedHC5 with a 50% certainty divided by a factor 1–5 (ECB, 2003). Thefactor 1–5, is a qualitatively chosen factor depending on theamount of supporting evidence e.g., multispecies data present,field data, etc.

3. Result

3.1. Chronic toxicity

Six test species showed different sensitivities to 2,4-DCP expo-sure (Table 1).

Results of the 21-d chronic toxicity test showed that M. super-bum was more sensitive than C. fluminea to the exposure of 2,4-DCP based on endpoint of survival. The NOEC of the two aquaticorganisms were 0.05 mg L�1 and 1.00 mg L�1; and their LOECswere 0.10 mg L�1 and 2.00 mg L�1, respectively. The calculatedMATC for both species were 0.07 mg L�1 and 1.41 mg L�1,respectively.

In 28-d chronic growth inhibition toxicity test on early lifestages of M. piceus, P. microlepis and E. ilishaeformis, all animals sur-vived at the end of tests, and the juvenile mean specific growthrates were 3.85%, 5.83% and 2.96% per day in the control, respec-tively. For M. piceus, the 0.20 mg L�1 and above treatments weresignificantly reduced the juvenile specific growth rates (p < 0.05;ANOVA; Fig. 1A). For P. microlepis, juvenile specific growth ratesin the 0.40 mg L�1 and above treatments were significantly lowerthan that in the control (Fig. 1B). For E. ilishaeformis, the critical va-lue was 0.60 mg L�1 (Fig. 1C). Based on the statistical analysis,NOECs for growth inhibition were 0.10 mg L�1, 0.20 mg L�1 and0.40 mg L�1, their LOECs were 0.20 mg L�1, 0.40 mg L�1 and0.60 mg L�1, and the calculated MATC were 0.14 mg L�1,0.28 mg L�1 and 0.49 mg L�1 for M. piceus, P. microlepis and E. ilis-haeformis, respectively.

The results of 10-d toxicity test with S. polyrhiza showed thatthe chlorophyll content decreased gradually with increasing 2,4-DCP exposure concentrations (Fig. 2). The chlorophyll content re-duced to 96.3% from the control at exposure concentrations of1.00 mg L�1, and to 30.4% at 50.0 mg L�1. The calculated NOEC,LOEC and MATC were 1.00 mg L�1, 5.00 mg L�1 and 2.50 mg L�1,respectively.

3.2. Comparison of HC5 derived from native and non-native taxa

A total of 12 (six from this study and six gained from literature)chronic toxicity data based on the native species were collected,

Table 1Summary of chronic toxicity data for exposure of native and non-native taxa to 2,4-dichlorophenol.

Family Species Time (d) Endpoint Measurement Con. (mg L�1) Reference

Native taxaBufonidae Bufo bufo gargarizans 30 NOEC Growth 0.50 Yin et al. (2003)Corbiculidae Corbicula fluminea 21 NOEC Survival 1.00 In this studyDaphnidae Daphnia magna 14 NOEC Reproduction 0.40 Yin et al. (2003)Palaemonidae Macrobrachium superbum 21 NOEC Survival 0.05 In this studyCyprinidae Mylopharyngodon piceus 28 NOEC Growth 0.10 In this study

Plagiognathops microlepis 28 NOEC Growth 0.20 In this studyErythroculter ilishaeformis 28 NOEC Growth 0.40 In this studyCarassius auratus 30 NOEC Survival 0.25 Yin et al. (2003)Ctenopharyngodon idellus 60 NOEC Survival 0.50 Yin et al. (2003)Gobiocypris rarus 21 NOEC Reproduction 0.10 Zhang et al. (2008)

Lemnaceae Soirodela polyrhiza 10 NOEC Chlorophyll 1.00 In this studyScenedesmaceae Scendesmus obliquus 4 NOEC Growth 5.00 Yin et al. (2003)

Non-native taxaAstacoidea Cambarus robustus 10 NOEC Glucose 0.10 ECOTOXCambaridae Cambaridaea 10 NOEC Survival 1.00 ECOTOXCambaridae Orconectes propinquus 10 NOEC Glucose 0.10 ECOTOXCalanoida Calanoidaa 26 NOEC Development 0.30 ECOTOXDogielinotidae Allorchestes compressa 4 NOEC Survival 0.075 ECOTOXUnionidae Unio tumidus 3 LOEC Enzymes 0.10 ECOTOXAdrianichthyidae Oryzias latipes 40 NOEC Survival 0.32 ECOTOXCyprinidae Pimephales promelas 32 NOEC Survival 0.29 ECOTOXSalmonidae Oncorhynchus mykiss 85 NOEC Growth 0.18 ECOTOXLemnoideae Lemna gibba 10 NOEC Growth 1.50 ECOTOX

a Species names of these two organisms were not specified in ECOTOX database. Because of most of species in the family distribute in North America and the test conductedunder non-local conditions, toxicity data of these two species defined as non-native.

X. Jin et al. / Chemosphere 84 (2011) 1506–1511 1509

including six fishes, four invertebrates, one planktonic algae andone hygrophyte. Ten chronic NOEC (or LOEC) values were foundfrom database and literature that based on non-native taxa, amongthem three data points were from fish taxa, six from invertebrates,and one from hygrophyte, respectively (showed in Table 1). Log-normal distribution was fitted to both native and non-nativechronic datasets. The calculated results are given in Table 2. Themedian HC5 of chronic data for native and non-native taxa are verysimilar, and the differences of sensitivity distribution for nativeand non-native species were not statistically significant(Kolmogorov–Smirnov test: ks = 0.895, n1 = 12, n2 = 10, p = 0.399)(Fig. 3). Combined native species toxicity data for 2,4-DCP withthose of non-native, a median HC5 of 0.045 (0.021–0.077) mg L�1

was calculated. This result was approximately equaled to medianHC5 derived from toxicity data of native or non-native taxa sepa-rately. The differences of sensitivity distribution for native taxa(ks = 0.486, n1 = 22, n2 = 12, p = 0.972) and non-native taxa(ks = 0.548, n1 = 22, n2 = 10, p = 0.925) were also not statisticallysignificant (Fig. 3).

Results of the calculations of PNECs can be seen in Table 2.

4. Discussion

Results of the present study indicate that 2,4-DCP is highly toxicto native freshwater aquatic organisms. Among different species,the fishes were more sensitive than aquatic macro invertebrates,the hygrophytes were the least sensitive. For individual species,C. fluminea is less sensitive than M. superbum that may be due tothe presence of protective shell. The three juvenile fish have simi-lar sensitivities during chronic exposure mainly because they be-long to the same family (Cyprinidae). Comparing the presentresults with previous studies, it reveals that NOEC value of 2,4-DCP for three tested fishes (0.10–0.40 mg L�1) were close to theNOEC value (0.10–0.50 mg L�1) to other members in Cyprinidae(Yin et al., 2003; Zhang et al., 2008). The chronic toxicity of theshrimp, bivalve and aquatic plant cannot be compared with previ-ous studies due to lack of chronic toxicity data for other local spe-

cies in China. Similar comparisons were conducted for results ofchronic tests based on native and non-native species. For fish,the results showed that the NOECs derived from the native species(Table 1) ranged from 0.10 mg L�1 to 0.40 mg L�1 that were consis-tent with those from non-native species including Oryzias latipes,Pimephales promelas and Oncorhynchus mykiss, whose NOECs are0.32 mg L�1, 0.29 mg L�1 and 0.18 mg L�1, respectively (USEPA,2002). The native shrimp, M. superbum was more sensitive thannon-native shrimp with NOECs ranged from 0.10 mg L�1 to1.00 mg L�1 (Table 1). For aquatic plant, it is reported that 10-dNOEC for Lemna gibba was 1.50 mg L�1 based on reduction in fronddensity, which is similar to that observed in present work(1.00 mg L�1). In general, there is no significant difference for NOE-Cs derived from native species from that of non-native species ex-cept for the shrimp.

In general, European or North American species are being pri-marily used for environmental hazard assessment of freshwaterenvironments due to standardized testing protocol. Fewer toxicitydata is available for native species. The relevance of using one geo-graphical region to assess the hazard posed to species in a differentregion has been questioned (Davies et al., 1994), and differences inthe sensitivity of cold-water, temperate, and tropical fish specieshave been reported previously (Dyer et al., 1997). From the resultsof this study, there were no significant differences betweenChinese native freshwater organisms and non-native species forchronic 2,4-DCP exposure. From a global perspective, studies haveshown similar sensitivities between Australian and non-Australianorganisms exposed to endosulfan based on calculated HC5 (Hoseand Van den Brink, 2004). Dyer et al. (1997) and Maltby et al.(2002) showed similar sensitivities among North American andEuropean taxa with different geographic distributions. Maltbyet al. (2005) also noted that the habitat and geographical distribu-tion of the species used to construct the SSD do not have a signif-icant influence on the assessment of hazard, but the taxonomiccomposition of the species assemblage does.

The derivation of PNEC in EU risk assessment usually uses eitherthe application of an assessment factor of 10–1000 on the lowestNOEC or the HC5 (based in the SSD approach) divided by a factor

2,4-dichlorophenol Concentrations (mg L -1)

Spec

ific

Gro

wth

Rat

e (%

/day

)

0

1

2

3

4

5

Control 0.10 0.20 0.40 0.80 1.60

Control 0.10 0.20 0.40 0.60 0.80

Control 0.10 0.20 0.40 0.60 0.80

**

**

* *

0

1

2

3

4

5

6

7

* * *

0.0

.5

1.0

1.5

2.0

2.5

3.0

3.5

*

*

A

B

C

Fig. 1. Effect of 28-d exposure to 2,4-dichlorophenol on early life stages of M. piceus(A), P. microlepis (B) and E. ilishaeformis (C) specific growth rate. Data are presentedas means ± standard deviation (SD). ⁄ and ⁄⁄ significant differences from the valuesof the control at p < 0.05 and p < 0.01, respectively.

2,4-dichlorophenol Concentrations (mg L-1)

Chl

orop

hyll

Con

tent

(m

g g-1

)

0.0

.2

.4

.6

.8

1.0

Control 1.00 5.00 10.0 25.0 50.0

**

****

Fig. 2. Effect of 10-d exposure to 2,4-dichlorophenol on chlorophyll content inSoirodela polyrhiza. Data are presented as means ± standard deviation (SD). ⁄ and ⁄⁄significant differences from the values of the control at p < 0.05 and p < 0.01,respectively.

Table 2Parameters of species sensitivity distributions for 2,4-dichlorophenol based on nativeand non-native species toxicity data.

Toxicitydata

n Mean(mg L�1)

Standarddeviation

Median HC5 PNEC(mg L�1)

Native data 12 0.79 1.36 0.044 (0.012–0.097) 0.009–0.044Non-native

data10 0.40 0.47 0.042 (0.012–0.084) 0.008–0.042

All data 22 0.61 1.05 0.045 (0.021–0.077) 0.009–0.045

2,4-dichlorophenol Concentrations (mg L-1)101.1.01

Pot

enti

ally

Aff

ecte

d P

erce

ntag

e (%

)

0

10

20

30

40

50

60

70

80

90

100

Native taxaNon-native taxaAll taxa

Fig. 3. Species sensitivity distribution of chronic toxicity data for 2,4-dichlorophenol.

1510 X. Jin et al. / Chemosphere 84 (2011) 1506–1511

of 1–5, depending upon the additional data present such as multi-species test and field test (ECB, 2003). Assessment factors are rec-ognized as a conservative approach for dealing with uncertainty inassessing risks posed by chemicals (Chapman et al., 1998). It hasbeen also noted that current applications of safety factors arebased on policy rather than on empirical science and that they re-sult in values that are protective, but not predictive. Specificallyaddressing ACRs, Chapman et al. (1998) cited studies showing thatmeasured ACRs can vary from 1 to 20 000. In view of this, it isunreasonable to apply a generic factor (whether of 10 or someother magnitude) across species and across substances. In the pres-

ent study, a CCC of 0.212 mg L�1 derived based on ACRs (Yin et al.,2003) could not provide enough protection to native M. superbum,M. piceus and P. microlepis, their NOEC being 0.05 mg L�1,0.10 mg L�1, 0.20 mg L�1, respectively. In this study, the PNEC ran-ged from 0.008 to 0.045 mg L�1 using the SSD approach with a 50%certainty based on different taxa. In spite of violations of someassumptions (OECD, 1995) and disadvantages (Posthuma et al.,2002), SSD methods still have many advantages over AF methodsin criteria derivation. Of particular importance to risk managersis the ability to select appropriate percentile levels and confidence

X. Jin et al. / Chemosphere 84 (2011) 1506–1511 1511

levels, which is not possible by the AF method. So far, PNECs de-rived from SSDs have proven to be protective for ecosystems. How-ever, a major limitation is the scarcity of suitable toxicity data,particular for site-specific chronic data. It is recommended thatat least 10–15 toxicity data (depending on the toxicant) are neces-sary to improve precision (Wheeler et al., 2002). From the result ofthis study, there were no significant difference between native andnon-native taxa for HC5 and sensitivity distributions of freshwaterorganisms to chronic 2,4-DCP exposure. Therefore, PNECs can bederived using SSD methods with combined data from native site-specific toxicity data and non-native toxicity data in hazard assess-ment of 2,4-DCP.

5. Conclusion

This study is a contribution in the assessment of the effect of2,4-dichlorophenol in the aquatic environment, where limitedsite-specific chronic data existed. 2,4-DCP caused different levelsof toxicity to various organisms, in which fishes and macro inver-tebrates were more sensitive than hygrophytes. Comparing thesensitivity distributions and HC5s, there were no significant differ-ence between native species and non-native species. It indicatesthat data for organisms from different geographic region can beused in estimating PNEC for ecological risk assessment of 2,4-DCP. Furthermore, the PNEC derived using SSD method is moreprecise and stable than AF method when the amount of chronictoxicity data increases.

Acknowledgements

This research was financially supported by Chinese Academy ofScience (KZCX2-YW-Q02-06), Ministry of Environmental Protec-tion of the People’s Republic of China (201009032) and Natural Sci-ence Foundation of China (20737003).

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