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Science of the Total Environment 441 (2012) 125–131
Contents lists available at SciVerse ScienceDirect
Science of the Total Environment
journal homepage: www.elsevier.com/locate/scitotenv
pH-dependent aquatic criteria for 2,4-dichlorophenol, 2,4,6-trichlorophenol
and pentachlorophenol
Liqun Xing a, Hongling Liu a,⁎, John P. Giesy a, b, c, Hongxia Yu a,⁎
a
b
c
State Key Laboratory of Pollution Control and Resource Reuse, School of the Environment, Nanjing University, Nanjing 20046, China
Department of Veterinary Biomedical Sciences and Toxicology Centre, University of Saskatchewan, Saskatoon, Saskatchewan, Canada
Department of Biology & Chemistry and State Key Laboratory for Marine Pollution, City University of Hong Kong, Kowloon, Hong Kong
H I G H L I G H T S
► The effects of pH on toxicity of CPs to Daphnia magna and Scenedesmus obliquus were studied.
► There were strong correlations between the logarithmic EC50s and pH values for both D. magna and S. obliquus.
► The manipulation of data (intra-species variation or/and proportions of taxonomic groups) is important to the result of WQC.
a r t i c l e
i n f o
Article history:
Received 26 June 2012
Received in revised form 18 September 2012
Accepted 24 September 2012
Available online xxxx
Keywords:
Chlorophenol
Species sensitivity weighted distribution
(SSWD)
Intra-species variation
Taxonomic groups
Water quality criteria
Pesticides
a b s t r a c t
Due to their agricultural as well as industrial uses, 2,4-dichlorophenol (2,4-DCP), 2,4,6-trichlorophenol
(2,4,6-TCP), and pentachlorophenol (PCP) are ubiquitous in the environment and recognized as priority pollutants in many countries. In this study, effects of pH on toxicity to the crustacean Daphnia magna and the
alga Scenedesmus obliquus were investigated. Combined published toxicity data of the three chlorophenols
along with; relationships between toxicity and pH reported here were used to establish pH-dependent
water quality criteria (WQC). The WQC expressed as a function of pH, also considered intra-species variation
and proportions of taxonomic groups. At pH 7.8, the recommended acute exposure water quality criteria
(WQC) were 286.2 μg 2,4-DCP/l, 341.5 μg 2,4,6-TCP/l and 11.4 μg PCP/l. The recommended chronic exposure
WQC were 16.3 μg 2,4-DCP/l, 54.6 μg 2,4,6-TCP/land 3.9 μg PCP/l.
Crown Copyright © 2012 Published by Elsevier B.V. All rights reserved.
1. Introduction
In China water quality criteria (WQC) refer to concentrations of
individual pollutants that are developed for specified uses of surface
waters, including drinking water, recreation, production of fish, propagation of other aquatic life, and industry and agriculture. WQC are
used in environmental management and pollution control. Several
methods have been developed for derivation of WQC (ANZECC and
ARMCANZ, 2000; CCME, 2007; EU, 2003; Stephan et al., 1985). In
China, WQC have been established for some chemicals; but they are
mainly derived from environmental quality standards or criteria of
more developed countries, which may be over- or under-protected
aquatic organisms due to differences between hydrographic conditions and species in China and those in other countries (Wu et al.,
2010; Yan et al., 2012). The Major State Basic Research Development
Program and the National Major Project of Science & Technology Ministry of China on the Development of China were initiated in 2008.
⁎ Corresponding authors. Tel./fax: +86 25 89680356.
E-mail addresses: hlliu@nju.edu.cn (H. Liu), yuhx@nju.edu.cn (H. Yu).
Until now, studies on WQC in China have been based on effects of
chemicals on several native species, but the methods used to derive
WQC were those of more developed countries, such as those of the
United States Environmental Protection Agency (USEPA) (USEPA-FAV
method), or Canada, Australia and New Zealand (mainly species
sensitivity distributions (SSDs) method). SSDs have some advantages
compared to USEPA approaches. The SSD approach considers all
available toxicity data and uses the entire species distribution to
calculate the protection level with a graphical component that allows
visualization of the SSD. Another criticism of the EPA-FAV method is
that the procedure can give poor extrapolations from small datasets
or with datasets with severe outliers in toxicity values (Stephan
et al., 1985). SSD methods are increasingly used in derivation of
water quality criteria by many countries including China. In China,
historically WQC had not considered intra-species variation or/and
proportions of taxonomic groups, and/or physical–chemical properties
of water.
Due to their use in agriculture and industry as pesticides, wood
preservatives, personal care formulations, and in the production of
other products chlorophenols (CPs) are ubiquitous globally in
0048-9697/$ – see front matter. Crown Copyright © 2012 Published by Elsevier B.V. All rights reserved.
http://dx.doi.org/10.1016/j.scitotenv.2012.09.060
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L. Xing et al. / Science of the Total Environment 441 (2012) 125–131
surface waters, groundwater, wastewater, sludge and drinking waters (Czaplicka, 2004; Davì and Gnudi, 1999; Gao et al., 2008;
Olaniran and Igbinosa, 2011; Zheng et al., 2011). CPs have received
worldwide attention due to their toxicity to aquatic life, persistence,
and potential to bioaccumulate (Ge et al., 2007; Olaniran and
Igbinosa, 2011; Xing et al., 2012a; Zheng et al., 2011; Zheng et al.,
2012). In China among CPs, 2,4-dichlorophenol (2,4-DCP), 2,4,6trichlorophenol (2,4,6-TCP), and pentachlorophenol (PCP) are ubiquitous at concentrations of as much as 103.70 μg/l (Gao et al., 2008;
Zheng et al., 2012; Zhong et al., 2010). Such concentrations pose
risks to humans and aquatic organisms (Cooper and Jones, 2008;
Ma et al., 2011; Ruder and Yiin, 2011; Xing et al., 2012a). For these
reasons, CPs are classified as priority pollutants in the United States
(USEPA, 1991) and China (Zhou et al., 1990).
Recently, WQC for 2,4-DCP, 2,4,6-TCP and PCP for protection of
aquatic life based on resident aquatic biota have been derived in
China (Jin et al., 2012a; Jin et al., 2012b; Jin et al., 2011; Yin et al.,
2003a; Yin et al., 2003b). However, these WQC did not consider
effects of water characteristics such as pH on toxicity of CPs. Because
chlorophenols have an OH functional group depending on pH they
can exist as protonated or ionic forms (Kishino and Kobayashi,
1995). The proportion of the CPs in each form is governed by their
pKa (Erickson et al., 2006a,b). The degree of dissociation of weak
acids, such as phenols and specifically CPs is thus a function of pH.
The fraction of weakly acidic organic compounds is directly proportional to acidity and thus inversely proportional to pH (Kishino and
Kobayashi, 1995; Saarikoski and Viluksela, 1981). Unionized molecules are more soluble in lipids and can diffuse more easily across
membranes to exert their effects. This effect is important because
the toxicity of some compounds is affected by the degree of dissociation (USEPA, 1991). In the case of CPs, the protonated form, which is
unionized, is more accumulated and thus more toxic than the unionized form. For this reason, in 1995, the USEPA developed criteria for
protection of aquatic life from the effects of CPs in ambient water
that were dependent on pH. WQC for PCP are expressed as functions
of pH (http://www.epa.gov/ost/criteria/wqctable/).
Intra-species variation or/and proportions of taxonomic groups
is also an important consideration in the derivation of WQC. The
effects of the species considered in deriving the WQC are more important than the statistical methods employed (Duboudin et al., 2004;
Maltby et al., 2005; Wheeler et al., 2002). WQC for the three CPs
were derived by the use of a log-logistic model, a typical species
sensitivity distribution (SSD) approach (CCME, 2007; Duboudin et
al., 2004; Maltby et al., 2005; Wheeler et al., 2002) and corrected
for the effects of pH. The effects of pH on toxicity of the three CPs, including 2,4-DCP, 2,4,6-TCP and PCP, to the crustacean, Daphnia magna
and green alga, Scenedesmus obliquus were investigated. According to
Duboudin et al. (2004), four cases in SSD analyses should be considered when deriving a criterion (Fig. A.1 of the Supplementary
information): (1) intra-species variation weighted by the use of
geometric means, and unweighted proportions of taxonomic groups;
(2) intra-species variation weighted by each data to give each species
the same weight, and unweighted proportions of taxonomic groups;
(3) intra-species variation weighted by geometric mean, and weighted proportions of taxonomic groups; (4) intra-species variation
weighted by each data to give each species the same weight, and
weighted proportions of taxonomic groups.
2. Materials and methods
2.1. Test chemicals and culture of daphnids and alga
2,4-DCP (CAS No. 120-83-2, 99% purity) and 2,4,6-TCP (CAS No.
88-06-2, 98% purity) were purchased from Acros Organics (Morris
Plains, NJ, USA), and PCP (CAS No. 87-86-5, 98% purity) was purchased
from Sigma-Aldrich (St Louis, MO, USA). All chemicals were used as
supplied and prepared in HPLC-grade dimethyl sulfoxide (DMSO)
and were kept in thoroughly cleaned glass containers and stored at −
20 °C. Final concentrations of DMSO in experimental media were
equal to or less than 0.05% for D. magna and 0.1% for S. obliquus, respectively. S. obliquus was cultured in 250 ml Erlenmeyer flasks containing
150 ml of WC medium (Kilham et al., 1998) under continuous
light conditions (illuminance 5000 lx) in incubator at 25± 1 °C. Cells
during exponential phase were used for experiments. D. magna
were cultured and maintained following previously published methods
(Xing et al., 2012b). Tap water, aerated for more than three days,
was used as culture medium, which had a pH of 8.12± 0.11, dissolved
oxygen concentration of 6.07± 0.24 mg/l, conductivity of 319 ±
9.1 μs/cm, alkalinity of 95.48 ±4.64 mg/l as CaCO3, and hardness of
125.5 ±4.95 mg/l as CaCO3. Neonates (b 24 h) were used for the
experiments.
2.2. Experimental design
Three different pH values adjusted by the use of buffers (MES
(2-(N-morpholino) ethanesulfonic acid, CAS No. 4432-31-9) for pH 6.5,
MOPS (3-(N-morpholino) propanesulfonic acid, CAS No. 1132-61-2)
for pH 7.5 and CHES (2-(cyclohexylamino) ethanesulfonic acid, CAS
No. 103-47-9) for pH 9.0). Buffers with purities of ≥98% and 0.1 mol/l
NaOH were used to maintain constant nominal pH (Neuwoehner and
Escher, 2011). Concentrations of buffers in media were 5 mmol/l for
D. magna, 20 mmol/l for S. obliquus, respectively. Static non-renewal
tests were conducted for all the experiments and the pH values were
measured by pH meter (Thermo Scientific Orion 5-Star Plus) at the
beginning and end of the experiments.
Studies of S. obliquus were initiated with a cell density approximately 10 5 cells/ml in 50 ml Erlenmeyer flasks containing 20 ml sterilized WC medium for 72 h (OECD, 2002; Yeesang and Cheirsilp,
2011). The other conditions were the same as those during cultivation. For each chemical and each pH, algae were exposed to seven
concentrations, one solvent control and one medium control with
three replicates. Algae were pre-cultured in medium at various
designed pH values for at least 3 days before the experiment in
order to allow for adaptation. Algae cell numbers were determined
every 24 h from 0 to 72 h.
Studies of D. magna experiments were conducted in 6-well
Costar® plates with 10 ml medium according to OECD method 202
(OECD, 2004). The observed endpoint, immobilization, was judged
by the inability to move during 10 s after exposure for 24 and 48 h.
Experimental conditions were the same as those used during culture.
For each chemical and each pH, seven concentration groups, solvent
control and medium control with five repeats containing five neonates were carried out. Simultaneously, tests with the reference
chemical K2Cr2O7 were conducted to ensure that the test organisms
exhibited constant sensitivities to this reference toxicant as an indicator of the physiological status of the organisms. D. magna were
pre-cultured in medium at designed pHs for at least 2 weeks before
the experiment in order to allow for adaptation.
2.3. Collection and selection of toxicity data
Values for toxicities to fish, amphibians, molluscs, crustaceans,
algae for the three CPs considered here were collected from the
ECOTOX database (http://cfpub.epa.gov/ecotox/) or published literature. The acceptability of toxicity data was assessed according to the
principles of aquatic life criteria with accuracy, relevance and reliability (CCME, 2007; Klimisch et al., 1997; Stephan et al., 1985). If endpoints were extrapolated beyond the range of concentrations tested
or greater than the limit of solubility, the studies were not included
in the database. Briefly, only toxicity data for species existing broadly
or cultivated widely in freshwaters of China were considered and
characterized by a specific endpoint, duration time and pH value. In
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L. Xing et al. / Science of the Total Environment 441 (2012) 125–131
addition, median effective concentration (EC50) or half lethal concentration (LC50) was chosen as measurement endpoints of acute toxicity. Since derivation of no observed effect concentrations (NOECs) or
lowest observed effect concentrations (LOECs) is dependent on experimental design and hypothesis testing; while the maximum acceptable
toxicant concentration (MATC) or 10% effective concentration (EC10)
are more invariability and preferred (CCME, 2007) either the MATC or
EC10 was selected as the measurement endpoint chronic toxicity. Only
when MATC and EC10 are not available, values of NOECs or LOECs
were used as substitutes in deriving WQC (See Table A.1–A.6 of the
Supplementary information).
2.4. Data analysis
The algae cell density was determined by measurement of optical
density (OD) by the use of a Synergy H4 Hybrid Microplate Reader
(excitation/emission: 485 nm/685 nm) (BioTek Instruments Inc.,
Winooski, VT). Two aliquants of 100-μl media from each Erlenmeyer
flask were added wells of a 96-well plate and read by Synergy H4
Hybrid Microplate Reader. A linear standard curve (r 2 = 0.9996,
p b 0.01) between fluorometric measurements and cell density was
developed. Percent inhibition of growth rate was calculated from
(Eqs. (1) and (2)) according to OECD (OECD, 2002).
μi ¼
lnðN i =N0 Þ
ti
ð1Þ
Ii ¼
μ C −μ T
μC
ð2Þ
Where: μi is the average growth rate from the initial to time i (i= 24,
48, 72 h); Ni, N0 are the biomass concentrations at the initial and time i,
respectively; ti is the exposure period; Ii is the percent inhibition on
average growth rate at ti; μC, μT are the growth rates in the control and
treatment, respectively.
Values for EC50 and EC10 with 95% confidence intervals (CI) for
S. obliquus were calculated by the use of a four-parameter log-logistic
regression model (Chalifour and Juneau, 2011). EC50 values with 95%
CI for D. magna were calculated through three-parameter log-logistic
regression model (Syberg et al., 2008; Xing et al., 2012b).
WQC with 95% CI were derived by use of previously published
methods (Duboudin et al., 2004), in which three taxonomic groups,
algae, invertebrates and vertebrates, were divided and corresponding
proportions were 64%, 26% and 10% (taking a value of 2.5 for the
factor change in species number between trophic levels), respectively
(Forbes and Calow, 2002). Final values of WQC were calculated by
taking the geometric mean of two weighted taxonomic groups
(cases (3) and (4) in introduction section intra-species variation
weighted by geometric mean, and weighted proportions of taxonomic groups; intra-species variation weighted by each data to give each
species the same weight, and weighted proportions of taxonomic
groups). Regression analyses were performed by the use of the statistical computing software R (R version 2.10.1, R Development Core
Team, http://www.r-project.org/).
127
16.87 mg PCP/l, respectively. Lesser values of pH resulted in lesser
values for the EC50 (more toxic potency). Values for the 72 h EC10
were 9.76 to 50.45 mg 2,4-DCP/l, 2.00 to 14.20 mg 2,4,6-TCP/l, 0.17
to 12.44 mg PCP/l. The 24-h EC50 values were used as acute toxicity
and the 72-h EC10 values were used as chronic toxicity due to rapid
cell division rate of algae (CCME, 2007). The 24-h EC50 for the reference, positive control chemical K2Cr2O7 indicated that the physiological
condition and thus sensitivity of D. magna were consistent among
experiments. Mean values of the measured final pH values were 7.13,
8.05, 8.81, with ranges of 6.86–7.39, 7.82–8.27, and 8.71–8.90, for
2,4-DCP, 2,4,6-TCP and PCP, respectively. There were some deviations
between the measured pH values and the desired pH values, but the
effects of pH values on the toxicity were still demonstrable (Table 2).
Similarly, the 48-h EC50 values were directly proportional to pH with
lesser toxic potencies observed at greater pHs, which increased (lesser
toxicity) from 0.76 to 1.83 mg 2,4-DCP/l, 1.17 to 6.62 mg 2,4,6-TCP/l,
0.062 to 1.23 mg PCP/l, at 7.13 to 8.81 pHs, respectively. The measured
pH values were used in establishing relationships between toxicity
and pH.
3.2. Relationships between toxicity and pH values for three chlorophenols
The experimental results presented here as well as the data from
published literature were used to develop statistically significant
predictive relationships between pH and toxicity for the three CPs
to aquatic organisms. Acute toxicity values were log-transformed
(lnEC50/LC50) and regressed as a function of pH (-log of concentration
of hydrogen ion) (Eqs. (3)–(4); Fig. 1). In the linear regression analyses, data were available for three species for 2,4-DCP, four species for
2,4,6-TCP, and nine species for PCP. The taxa for which data were
available included algae, crustaceans, and fish (Tables A.1, A.3, A.5 of
the Supplementary information for details). The regression results
indicated significant corrections between log-transformed acute toxicity data (lnEC50/LC50) and pH (Fig. 1):
2
For 2; 4−DCP : lnEC50 ¼ 0:6274 pH−2:6567 r ¼ 0:42; p ¼ 0:02364
ð3Þ
2
For 2; 4; 6−TCP : lnEC50 ¼ 0:8937 pH−5:3075 r ¼ 0:86; p < 0:00001
ð4Þ
2
For PCP : lnEC50 ¼ 0:7330 pH−6:3261 r ¼ 0:33; p ¼ 0:00020 ð5Þ
There were few studies on effects of pH on chronic toxicity to
aquatic organisms such that there was insufficient information from
which to develop relationships between chronic toxicity data and
pHs. In this study, the chronic toxicity related to pH use the same
slope of acute toxicity. In one study (Chèvre et al., 2006), the theory
that slopes of the acute and chronic species sensitivity distribution
(SSD) are parallel has been espoused. Also, the use of acute to chronic
ratios to develop criteria that is used by USEPA is based on the slopes
being equal.
3. Results
3.3. Distribution of selected toxicity data
3.1. Effect of pH on toxicity of chlorophenols
According to the relationships between toxic potency of
chlorophenols and pH (Eqs. (3)–(5)), the toxicity data were normalized to a pH of 7.8 (Supporting information Table A.1–A.6), and
plotted concurrently (Fig. 2). Based on the distribution of the toxicity
data (Fig. 2), PCP (lesser EC/LC50 or EC10/MATC) was more potently
toxic than were 2,4-DCP or 2,4,6-TCP; while the toxic potencies
of 2,4-DCP and 2,4,6-TCP were nearly the same. When normalized
to a pH of 7.8 acute toxic potency ranged from 1770.5 (D. magna)
to 321,024.5 μg/l (Lemna minor) with a median 7902.1 μg/l for
Algae grew well in all media at various pHs with or without 0.1%
DMSO. The measured final values for pH were 6.47–6.54, 7.46–7.53,
8.78–9.05 for 2,4-DCP, 2,4,6-TCP and PCP, respectively. Relationships
between concentrations–responses were observed in all experiments
with exposure concentrations causing 0–100% effects (Table 1). Values
of 48-h EC50 were directly proportional pH with values ranging from
13.81 to 71.81 mg 2,4-DCP/l, 2.71 to 25.83 mg 2,4,6-TCP/l, 0.29 to
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L. Xing et al. / Science of the Total Environment 441 (2012) 125–131
Table 1
Toxicity (mg/l) of three chlorophenols to S. obliquus at various pH.
Chemicals
2,4-DCP
Endpoints
pH = 9.0
72 h
24 h
48 h
72 h
24 h
48 h
72 h
8.72
(7.76–9.67)
13.81
(13.06–14.57)
2.38
9.76
(8.91–10.61)
14.14
(13.42–14.86)
2.00
2.71
2.46
15.08
(12.84–17.32)
19.61
(18.97–20.25)
2.45
(1.66–3.25)
3.47
(2.79–4.16)
0.30
65.92
(41.02–90.82)
71.81
(58.36–85.26)
18.82
(11.11–26.53)
25.83
(18.76–32.91)
14.87
EC50
0.26
0.17
(0–0.35)
0.28
(0.20–0.35)
15.69
(12.39–18.99)
19.53
(18.90–20.15)
2.84
(2.19–3.5)
3.43
(2.23–4.63)
0.19
50.45
(45.04–55.86)
54.26
(35.43–73.1)
14.2
(2.86–25.55)
34.76
0.24
(0.09–0.39)
0.29
29.35
(21.33–37.38)
32.08
(20.86–43.29)
3.59
(0.230–56.06)
3.76
(0.25–57.11)
0.12
114.03
(109.21–118.85)
137.48
(130.45–144.52)
28.13
EC10
21.61
(18.55–24.68)
30.16
(28.98–31.33)
1.56
(0.18–2.94)
4.37
(2.65–6.08)
0.26
0.93
(0.09–1.77)
0.89
(0.31–1.47)
1.23
(0.47–1.99)
16.87
18.07
(7.57–28.58)
EC10
EC10
EC50
PCP
pH= 7.5
48 h
EC50
2,4,6-TCP
pH= 6.5
24 h
30.69
(22.5–38.87)
15.03
(5.805–24.26)
24.06
(13.40–34.73)
12.440
Note: numerical values in brackets represent 95% confidence intervals.
2,4-DCP, from 591.5 (Lepomis macrochirus) to 69,114.0 μg/l
(Corbicula fluminea) with a median 5712.8 μg/l for 2,4,6-TCP,
from 85.9 (L. macrochirus) to 34,376.7 μg/l (Rhabditis sp.) with a
median 277.7 μg/l for PCP, respectively. Chronic toxic potencies at
pH 7.8 ranged from 99.5 (Macrobrachium superbum) to 21,211.3 μg/l
(S. obliquus) with a median 918.2 μg/l for 2,4-DCP, from 115.5
(Mylopharyngodon piceus) to 4668.0 μg/l (C. fluminea) with a median
578.5 μg/l for 2,4,6-TCP, from 18.1 (M. superbum) to 7470.0 μg/l
(Chlorella kessleri) with a median of 85.8 μg/l for PCP.
by functions of pH (Eqs. (6)–(11)):WQC for chronic exposure (μg/l):
WQC2;4−DCP ¼ expð0:6274 pH þ 0:7630Þ
ð6Þ
WQC2;4;6−TCP ¼ expð0:8937 pH−1:1374Þ
ð7Þ
WQCPCP ¼ expð0:7330 pH−3:2847Þ
ð8Þ
WQC for chronic exposure (μg/l):
WQC2;4−DCP ¼ expð0:6274 pH−2:1056Þ
ð9Þ
WQC2;4;6−TCP ¼ expð0:8937 pH−2:9706Þ
ð10Þ
WQCPCP ¼ expð0:7330 pH−4:3564Þ
ð11Þ
3.4. Derivation of water quality criteria for three chlorophenols
Toxicity potencies at various pH values were adjusted to a common pH 7.8. Then, based on the intra-species variation and proportions of taxonomic groups, four cases (see Section 1) were derived
and SSD analyses were used to estimate WQC (Table 3 and Fig. 3).
Values of HC5s (5% hazard concentrations) based on SSDs of data
normalized to pH 7.8 for acute exposure ranged 446.8–953.3 μg
2,4-DCP/l, 570.6–872.6 μg 2,4,6-TCP/l and 21.2–30.9 μg PCP/l, respectively considering the four cases such as intra-species variation weighted by the use of geometric means, and unweighted proportions of
taxonomic groups; intra-species variation weighted by each data to
give each species the same weight, and unweighted proportions of taxonomic groups; intra-species variation weighted by geometric mean,
and weighted proportions of taxonomic groups; intra-species variation
weighted by each data to give each species the same weight, and
weighted proportions of taxonomic groups. Values of HC5s based on
SSDs of data normalized to pH 7.8 for chronic exposure ranged 10.6–
31.8 μg 2,4-DCP/l, 49.0–62.5 μg 2,4,6-TCP/l and 3.4–5.1 μg PCP/l
(Table 3). The final WQC for acute exposure were calculated by dividing
the HC5s by 2 (EU, 2003; Stephan et al., 1985). Combined with the linear
relationships (Eqs. (3)–(5)), the final WQC expressed as μg/l are given
4. Discussion
The effects of pH on toxic potency of three CPs on two domestic
organisms existing widely in aquatic environment were investigated
to provide complementary toxicity data. Values of pH studied ranged
from 6.86 to 8.90 for D. magna, and 6.47 to 9.05 for S. obliquus; which
are proper survival or growth pH range (Neuwoehner and Escher,
2011; OECD, 2004).
There were some deviations between measured pH values and the
desired pH values for D. magna, a result that is consistent with the
results of a previous study by Altenburger et al. (2010) which showed
that only when the buffer constitution of the medium was increased
to 20 mmol/l, would the pH remain constant over the test period.
However, the greater concentration of buffer can affect survival of
D. magna (De Schamphelaere et al., 2004). In spite of the fact that
pH values are not always consistent with the desired pH values, the
Table 2
Toxicity (mg/l) of three chlorophenols to D. magna at various pH.
Chemicals
2,4-DCP
2,4,6-TCP
PCP
pH = 7.13
pH = 8.05
pH = 8.81
24-h EC50
48-h EC50
24-h EC50
48-h EC50
24-h EC50
48-h EC50
3.46
(2.90–4.01)
2.30
(1.91–2.69)
0.16
(0.16–0.17)
0.76
(0.55–1.05)
1.17
(0.71–1.63)
0.06
(0.03–0.09)
4.44
(4.13–4.76)
10.92
(7.58–14.26)
0.99
(0.99–1.00)
1.50
(0.56–4.03)
3.76
(1.07–6.45)
0.35
(0.32–
0.37)
16.53
(14.42–18.64)
–
1.83
(0.63–5.37)
6.26
3.77
(3.75–3.79)
1.23
(0.85–1.61)
Note: numerical values in brackets represent 95% confidence intervals.
Author's personal copy
L. Xing et al. / Science of the Total Environment 441 (2012) 125–131
6
7
8
9
5
10
2
0
-4
-1
-1
5
1 Algae
4 Crustaceans
2 Fish
1 Molluscs
1 Insects
-2
ln(EC50)(mg/l)
1
2
3
4
1 Algae
1 Crustacean
2 Fish
0
ln(EC50)(mg/l)
4
3
2
1
PCP (n=37)
4
2,4,6-TCP (n=13)
1 Algae
1 Crustacean
1 Fish
0
ln(EC50)(mg/l)
5
2,4-DCP (n=12)
129
6
pH
7
8
9
10
4
5
pH
6
7
8
9
10
pH
Fig. 1. Relationships between log-transformed acute toxicity data of three chlorophenols and pH values. n is the total number of toxicity data.
1.2E+6
derived from this study were similar to those determined in previous
studies (Jin et al., 2011; Jin et al., 2012a; Jin et al., 2012b). Based on
the endpoints selected for use in generating SSD (generally MATC or
EC10 ≥NOEC), the previous values would be expected to be greater
than WQC derived in this study. These results are not consistent with
those of some previous studies which showed no significant difference
between native species sensitivity and non-native species sensitivity to
2,4-DCP (Jin et al., 2011). Since these CPs contain a basic OH group that
is protonated and thus positively charged at physiological pH. Only
non-ionized molecules are lipid-soluble and can diffuse easily across
the cell membranes. In contrast, the ionized molecules are usually
unable to penetrate the lipid membrane transport and distribution of
drugs that are weak organic acids or bases that are usually determined
by their pKa and the pH gradient across the membrane. The different
acidity constant (pKa) values of the three CPs are 7.89 for 2,4-DCP,
5.99 for 2,4,6-TCP and 4.70 for PCP, respectively (Czaplicka, 2004). The
fraction of neutral molecules f(A-OH) was calculated (Eq. 12).
fðA OHÞ ¼
Chemicals
Intra-species variation
2,4-DCP
Geometric
(acute)
Weighted
(acute)
Geometric
(chronic)
Weighted
(chronic)
Geometric
(acute)
Weighted
(acute)
Geometric
(chronic)
Weighted
(chronic)
Geometric
(acute)
Weighted
(acute)
Geometric
(chronic)
Weighted
(chronic)
n=18
2,4,6-TCP
n=18
4.0E+2
2.2E+4
n=32
n=13
PCP
2,4-DCP
2,4,6-TCP
PCP
Fig. 2. Boxplot of toxicity data distribution of three chlorophenols. n is the number of
aquatic species; geometric mean was used when there were more than one toxicity
values for a species.
ð12Þ
Table 3
The results of calculated HC5 and 95% CI (μg/L) for three chlorophenols (pH = 7.8).
Acute
Chronic
n=11
1
1 þ 10ðpKapHÞ
At pH 7.8, there are only 50% of non-ionized molecules for
2,4-DCP, much lesser than the 2,4,6-TCP and PCP. There are some
inevitable uncertainties in the process of deriving WQC including
n=22
7.4E+0
E(L)C50 or MATC/EC10 (µg/l)
achieved measured pH values were sufficient to develop a relationship between toxic potency and pH. There were strong correlations
between log EC50s and pH for both D. magna and S. obliquus. For
D. magna, 24-h EC50 for 2,4-DCP, 48-h EC50s for 2,4,6-TCP and PCP
were used to establish linear regressions due to stronger correlations
with pH; while for S. obliquus, 48-h EC50s for all three chlorophenols
were used to establish the function between toxic potency (Table
A.1, A.3, A.5 of the Supplementary information). Relationships between toxic potency and pH observed in the study results of which
are reported here are consistent with those of the previous studies
(Fisher et al., 1999; Fisher and Wadleigh, 1986; Saarikoski and
Viluksela, 1982; Salkinoja-Salonen et al., 1981; Spehar et al., 1985),
in which obvious linear correlation between toxic potency with pH
was observed.
The linear regression between the log of potency and pH was
significant (p b 0.05) for acute toxicity. However, there were insufficient studies on the effect of pH on chronic toxicity to aquatic organisms, and not enough evidence to establish relationships between
chronic toxicity and pH. In the study upon which we reported here,
the slopes calculated from acute toxicity were used to adjust toxicity
values and estimate WQC for chronic (continuous concentration)
exposures. Slopes of the functions between pH and toxic potency
based on 48-h EC50 and 72-h EC10 of S. obliquus are similar (Fig. A.2
of the Supplementary Information). This result is consistent with the
slope (1.005) used by the USEPA for both acute and chronic WQC for
PCP (http://www.epa.gov/ost/criteria/wqctable/). The slope for PCP
based on Chinese species was 0.7330, which was lesser than the slope
of 1.005 used by USEPA. In addition, at pH 7.8, the recommended
WQC for PCP given USEPA were 19 and 15 μg/l for acute and chronic
exposures, respectively; while the calculated WQC for PCP based on
Chinese species were lesser with values of 11.4 μg/l for acute and
3.9 μg/l for chronic continuous exposures. Although the WQC results
mean
mean
mean
mean
mean
mean
Proportions of taxonomic groups
Unweighted
Weighted
953.3
(669.1–1428.0)
511.9
(407.1–639.7)
31.8
(18.6–55.9)
17.1
(11.0–27.4)
738.2
(587.0–937.3)
872.6
(733.6–1042.1)
59.7
(42.7–84.4)
62.5
(45.6–87.4)
30.9
(20.3–48.1)
29.
(24.8–34.1)
4.1
(2.4–7.3)
5.1
(3.2–8.1)
733.3
(358.2–1496. 7)
446.8
(306.4–635.9)
24.9
(10.3–52.9)
10.6
(4.7–23.1)
570.6
(370.9–814.0)
817.8
(618.9–1087.9)
49.0
(31.0–72.3)
60.9
(41.6–89.7)
21.2
(11.3–39.5)
24.5
(19.3–31.1)
3.4
(1.8–6.547)
4.5
(2.8–7.2)
Note: HC5 is the 5% hazard concentration; numerical values in brackets represent 95%
confidence intervals (CI).
Author's personal copy
12
6
8
10
12
2
4
6
8
10
12
100
60
acute
chronic
4
6
8
10
10
12
14
100
60
20
0
Species affected [%]
100
60
20
8
2
4
6
8
10
12
log Conc (µg/l)
12
acute
chronic
4
6
8
10
12
14
100
B-4
60
acute
chronic
2
4
6
8
10
12
log Conc (µg/l)
C-3
2
10
20
60
acute
chronic
4
8
0
100
B-3
2
6
log Conc (µg/l)
log Conc (µg/l)
C-2
2
6
20
100
0
20
60
acute
chronic
0 20
Species affected [%]
100
60
20
0
Species affected [%]
acute
chronic
4
4
log Conc (µg/l)
C-1
log Conc (µg/l)
2
log Conc (µg/l)
B-2
log Conc (µg/l)
2
14
Species affected [%]
10
12
12
log Conc (µg/l)
C-4
100
8
10
acute
chronic
60
6
8
acute
chronic
20
4
Species affected [%]
100
20
60
acute
chronic
0
Species affected [%]
B-1
2
6
log Conc (µg/l)
A-4
0
4
0
100
60
20
2
Species affected [%]
14
0
12
Species affected [%]
10
100
8
acute
chronic
60
6
log Conc (µg/l)
A-3
0 20
4
acute
chronic
Species affected [%]
2
A-2
Species affected [%]
0
20
60
acute
chronic
0
100
A-1
Species affected [%]
L. Xing et al. / Science of the Total Environment 441 (2012) 125–131
Species affected [%]
130
2
4
6
8
10
12
log Conc (µg/l)
Fig. 3. The simulated species sensitivity distribution curves for 2,4-DCP (A), 2,4,6-TCP (B) and PCP (C) calculated using log-logistic. Letters A, B, C stand for different chemicals;
numbers stand for consideration of toxicity data: (1) intra-species variation weighted by geometric mean, and unweighted proportions of taxonomic groups; (2) intra-species
variation weighted by each data to give each species the same weight, and unweighted proportions of taxonomic groups; (3) intra-species variation weighted by geometric
mean, and weighted proportions of taxonomic groups; (4) intra-species variation weighted by each data to give each species the same weight, and weighted proportions of
taxonomic groups.
applied statistical method, toxicity data and other hypotheses
(Duboudin et al., 2004; Versteeg et al., 1999). Different results can
be obtained based on the same toxicity data due to different methods,
hypotheses or data choice (Duboudin et al., 2004; Wheeler et al.,
2002). In this study, intra-species variation, inclusion of taxonomic
groups and pH were considered when deriving WQC that would be
protective under actual eco-environment (Duboudin et al., 2004;
Forbes and Calow, 2002). The WQC derived based on four cases
were similar (Table 3), a result that might be due to the distribution
of toxicity data, in which for most species the toxic potency has
been developed at only one pH (Maltby et al., 2005). Until now,
intra-species variation sensitivities were incorporated into WQC by the
use of geometric mean (CCME, 2007; EU, 2003; Stephan et al., 1985;
Zhong et al., 2010). In order to avoid a bias that might be introduced
by the use of this method, geometric means of HC5 calculated by cases
(3) and (4) (see Section 1) were used to estimate the final WQC.
The results obtained in this study are based on toxicity tests
conducted under laboratory conditions. When site-specific WQC are
derived, water-effect ratio (WER) is an important method to adjust
the difference between the toxicity in laboratory dilution water and
that in the water at the site. A WER is calculated by dividing the
toxicity value (e.g., LC50) determined in water of interest (certain
site), by the corresponding toxicity value determined in a standard
laboratory water. Thus, studies on WER are further needed to set
site-specific WQC.
5. Conclusions
The toxic potencies of 2,4-DCP, 2,4,6-TCP and PCP to aquatic
organisms were inversely proportional to pHs. Recommended WQC
values were functions of pH (Eqs. (6)–(11)). When normalized to
a pH of 7.8, the acute WQC values were 286.2 μg 2,4-DCP/l, 341.5 μg
2,4,6-TCP/l and 11.4 μg PCP/l, while chronic WQC values were
16.3 μg 2,4-DCP/l, 54.6 μg 2,4,6-TCP/l and 3.9 μg PCP/l.
Acknowledgments
This research was supported by the Natural Science Foundation
of China (No. 20977047), Major State Basic Research Development
Program (No. 2008CB418102) and the National Major Project of
Science & Technology Ministry of China (No. 2012ZX07529-003-02,
2008ZX08526-003, 2012ZX07506-001). Prof. Giesy was supported
by the Canada Research Chair program, an at large Chair Professorship at the Department of Biology and Chemistry and State Key Laboratory in Marine Pollution, City University of Hong Kong, and the
Einstein Professor Program of the Chinese Academy of Sciences.
Appendix A. Supplementary data
Supplementary data to this article can be found online at http://
dx.doi.org/10.1016/j.scitotenv.2012.09.060.
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pH-dependent aquatic life criteria for 2,4-dichlorophenol, 2,4,6-trichlorophenol
and pentachlorophenol
Liqun Xing1, Hongling Liu1*, John P. Giesy1,2,3, and Hongxia Yu1*
1
State Key Laboratory of Pollution Control and Resource Reuse, School of the Environment,
Nanjing University, Nanjing 20046, China
2
Department of Veterinary Biomedical Sciences and Toxicology Centre, University
of Saskatchewan, Saskatoon, Saskatchewan, Canada
3
Department of Biology & Chemistry and State Key Laboratory for Marine Pollution,,
City University of Hong Kong, Kowloon, Hong Kong, SAR, China
Authors for correspondence:
School of the Environment
Nanjing University
Nanjing 210046, China
Tel: 86-25-89680356
Fax: 86-25-89680356
E-mail: hlliu@nju.edu.cn (H. Liu); yuhx@nju.edu.cn (H.Yu)
Table S1
Species
Group
Acute toxicity data for Chinese species used to calculate water quality criteria for 2,4-dichlorophenol.
Duration time
(d)
Effect
Methods
Endpoints
R, U
LC50
MORT
measurements
Concentrations
Concentrations
(μg/l)
(μg/l) pH=7.8
7.24
19250
pH
Geomean
References
27347.66
27347.66
(Jin, et al., 2009)
4524.73
(Yin, et al., 2003b)
Corbicula fluminea
Invertebrate
4
Chironomus sp.
Invertebrate
4
S, U
LC50
MORT
7.0
2740
4524.73
Daphnia magna
Invertebrate
2
S, M
LC50
MORT
8
3680
3246.29
(Kim, et al., 2006)
Daphnia magna
Invertebrate
2
S, U
LC50
MORT
7.0
2120
3500.89
(Yin, et al., 2003b)
Daphnia magna*
Invertebrate
1
S, U
EC50
IMBL
7.1
3460
This study
Daphnia magna*
Invertebrate
1
S, U
EC50
IMBL
8.0
4440
This study
Daphnia magna*
Invertebrate
1
S, U
EC50
IMBL
8.8
16530
This study
Daphnia magna
Invertebrate
2
S, U
EC50
IMBL
7.1
763
1165.01
This study
Daphnia magna
Invertebrate
2
S, U
EC50
IMBL
8.0
1500
1286.43
This study
Daphnia magna
Invertebrate
2
S, U
EC50
IMBL
8.8
1830
974.51
1134.58
This study
Limnodrilus hoffmeisteri
Invertebrate
4
S, U
LC50
MORT
7.0
9890
16331.96
16331.96
(Yin, et al., 2003b)
Radix plicatula
Invertebrate
4
R, U
LC50
MORT
7.0
3370
5565.09
5565.09
(Yin, et al., 2003b)
Vertebrate
4
R, U
LC50
MORT
7.0
9460
15621.88
15621.88
(Yin, et al., 2003b)
Vertebrate
4
R, U
MORT
7.0
5250
8669.65
8669.65
(Yin, et al., 2003b)
Carassius auratus
Vertebrate
4
R, U
LC50
MORT
7.0
7940
13111.81
(Yin, et al., 2003b)
Carassius auratus
Vertebrate
4
F, M
LC50
MORT
7.8
1240
1240
(Birge, et al., 1979)
Carassius auratus
Vertebrate
4
F, M
LC50
MORT
7.8
1760
1760
Ictalurus punctatus
Vertebrate
4.5
F, M
LC50
MORT
7.8
1700
1700
Ictalurus punctatus
Vertebrate
4.5
F, M
LC50
MORT
7.8
1850
1850
1773.42
(Birge, et al., 1979)
Vertebrate
4
R, NR
MORT
7.24
4010
5696.84
5696.84
(Jin, et al., 2010)
Vertebrate
4
R, NR
MORT
6.21
2630
7127.17
7127.17
(Kennedy, 1990)
Bufo bufo gargarizans
Ctenopharyngodon
idellus
Mylopharyngodon
piceus
Oncorhynchus mykiss
LC50
LC50
LC50
3058.67
(Birge, et al., 1979)
(Birge, et al., 1979)
Species
Group
Duration time
(d)
Methods
Poecilia reticulata*
Vertebrate
4
R, NR
Poecilia reticulata*
Vertebrate
4
R, NR
Poecilia reticulata*
Vertebrate
4
R, NR
Poecilia reticulata*
Vertebrate
14
R, NR
Poecilia reticulata*
Vertebrate
14
R, NR
Poecilia reticulata*
Vertebrate
14
R, NR
Vertebrate
4
R, NR
Rana nigromaculata
Vertebrate
4
R, U
Tilapia mossambica
Vertebrate
4
Tilapia zilli
Vertebrate
Lemna minor
Endpoints
LC50
Effect
measurements
pH
Concentrations
Concentrations
(μg/l)
(μg/l) pH=7.8
Geomean
References
(Saarikoski and Viluksela,
MORT
6
3483.37
10768.24
MORT
7
5520.77
9116.79
MORT
8
7620.79
6722.63
MORT
6.1
3250.87
MORT
7.3
4187.94
MORT
7.8
5915.62
MORT
7.24
2480
3523.23
3523.23
(Jin, et al., 2010)
LC50
MORT
7.0
9850
16265.91
16265.91
(Yin, et al., 2003b)
R, U
LC50
MORT
7.0
8350
13788.37
13788.37
(Yin, et al., 2003b)
2
R, U
LC50
MORT
6.6
2297
4874.43
4874.43
(Yen, et al., 2002)
Plant
3
S, U
LC50
MORT
5.1
59000
320678
320678
(Blackman, et al., 1955)
Scenedesmus obliquus*
Plant
2
S, U
EC50
GGRT
6.5
13810
This study
Scenedesmus obliquus*
Plant
2
S, U
EC50
GGRT
7.5
19530
This study
Scenedesmus obliquus*
Plant
2
S, U
EC50
GGRT
9.0
71810
This study
Scenedesmus obliquus
Plant
1
S, U
EC50
GGRT
6.5
30160
68143.55
Scenedesmus obliquus
Plant
1
S, U
EC50
GGRT
7.5
32080
38719.09
Scenedesmus obliquus
Plant
1
S, U
EC50
GGRT
9.0
137480
64785.28
Plagiognathops
microlepis
LC50
LC50
LC50
LC50
LC50
LC50
1982)
(Saarikoski and Viluksela,
1982)
8706.47
(Saarikoski and Viluksela,
1982)
(Könemann and Musch,
1981)
(Könemann and Musch,
1981)
(Könemann and Musch,
1981)
This study
This study
55497.75
This study
Table S2 Chronic toxicity data for Chinese species used to calculate water quality criteria for 2,4-dichlorophenol.
Species
Group
Duration time
(d)
Methods
Endpoints
Effect
measurements
pH
Concentrations
Concentrations (μg/l)
(μg/l)
pH=7.8
Geomean
References
(Jin, et al., 2011)
Corbicula fluminea
Invertebrate
21
R, M
MATC
SURV
7.24
1410
2003.12
2003.12
Daphnia magna
Invertebrate
21
R, U
MATC
GREP
7.0
556
918.16
918.16
Vertebrate
30
R, U
MATC
WGHT
7.0
707
1167.51
1167.51
Vertebrate
60
F, U
MATC
GREP
7.0
707
1167.51
1167.51
Carassius auratus
Vertebrate
8
F, M
LC01
MORT
7.8
39.8
39.8
Carassius auratus
Vertebrate
8
F, M
LC01
MORT
7.8
48.1
48.1
Carassius auratus
Vertebrate
30
R, U
MATC
GREP
7.0
354
584.58
103.82
Vertebrate
28
R, M
MATC
GGRO
7.24
490
696.12
696.12
Ictalurus punctatus
Vertebrate
8.5
F, M
LC01
MORT
7.8
1.6
1.6
Ictalurus punctatus
Vertebrate
8.5
F, M
LC01
MORT
7.8
2.8
2.8
Vertebrate
28
R, NR
MATC
GGRO
7.24
141.42
200.91
Vertebrate
28
R, M
MATC
GGRO
7.24
140
198.89
Bufo bufo gargarizans
Ctenopharyngodon
idellus
Erythroculter
ilishaeformis
Mylopharyngodon
piceus
Mylopharyngodon
piceus
(Yin, et al.,
2003b)
(Yin, et al.,
2003b)
(Yin, et al.,
2003b)
(Birge, et al.,
1979)
(Birge, et al.,
1979)
(Yin, et al.,
2003b)
(Jin, et al., 2011)
(Birge, et al.,
1979)
2.12
(Birge, et al.,
1979)
(Jin, et al., 2010)
199.90
(Jin, et al., 2011)
Macrobrachium
Vertebrate
21
R, M
MATC
SURV
7.24
70
99.45
Oncorhynchus mykiss
Vertebrate
27
F, M
LC01
MORT
7.8
1.7
1.7
Oncorhynchus mykiss
Vertebrate
27
F, M
LC01
MORT
7.8
2.8
2.8
Vertebrate
28
R, NR
MATC
GGRO
7.24
282.84
401.82
Vertebrate
28
R, M
MATC
GGRO
7.24
280
397.78
399.79
(Jin, et al., 2011)
Soirodela polyrhiza
Plant
10
R, M
MATC
CHLO
7.24
2500
3551.64
3551.64
(Jin, et al., 2011)
Scenedesmus obliquus
Plant
3
S, U
EC10
GGRT
6.5
9760
22051.76
Scenedesmus obliquus
Plant
3
S, U
EC10
GGRT
7.5
15080
18200.87
Scenedesmus obliquus
Plant
3
S, U
EC10
GGRT
9.0
50450
23773.77
superbum
Plagiognathops
microlepis
Plagiognathops
microlepis
99.45
(Jin, et al., 2011)
(Birge, et al.,
1979)
2.18
(Birge, et al.,
1979)
(Jin, et al., 2010)
This study
This study
21210.19
This study
Table S3
Species
Acute toxicity data for Chinese species used to calculate water quality criteria for 2,4,6-trichlorophenol.
Group
Duration
time (d)
Methods
Endpoints
Invertebrate
4
S, U
LC50
Brachionus calyciflorus
Invertebrate
2
S, U
Chironomus sp.
Invertebrate
4
S, U
Corbicula fluminea
Invertebrate
4
Daphnia magna
Invertebrate
Daphnia magna
Effect
measurements
pH
Concentrations
Concentrations
(μg/l)
(μg/l) pH=7.8
Geomean
References
MORT
7.39
5500
7934.06
7934.06
(Holcombe, et al., 1987)
EC50
PROG
7.5
3000
3922.47
3922.47
(Radix, et al., 1999)
LC50
MORT
7.0
2060
4210.86
4210.86
(Yin, et al., 2003a)
R, U
LC50
MORT
7.24
41900
69114.04
69114.04
(Jin, et al., 2012a)
2
S, M
LC50
MORT
8
6640
5553.19
(Kim, et al., 2006)
Invertebrate
2
S, U
LC50
MORT
6.5
270
862.84
(Virtanen, et al., 1989)
Daphnia magna
Invertebrate
2
S, U
LC50
MORT
6.5
330
1054.59
(Virtanen, et al., 1989)
Daphnia magna
Invertebrate
2
S, U
LC50
MORT
7.0
1730
3536.30
(Yin, et al., 2003a)
Daphnia magna*
Invertebrate
2
S, U
EC50
IMBL
7.1
1167
2181.53
This study
Daphnia magna*
Invertebrate
2
S, U
EC50
IMBL
8.0
3760
3144.58
This study
Daphnia magna*
Invertebrate
2
S, U
EC50
IMBL
8.8
6260
2561.21
2273.51
This study
Limnodrilus hoffmeisteri
Invertebrate
4
S, U
LC50
MORT
7.0
7520
15371.67
15371.67
(Yin, et al., 2003a)
Macrobrachium superbum
Invertebrate
4
R, U
LC50
MORT
7.24
2050
3381.47
3381.47
(Jin, et al., 2012a)
Radix plicatula
Invertebrate
4
R, U
LC50
MORT
7.0
2950
6030.11
6030.11
(Yin, et al., 2003a)
Bufo bufo gargarizans
Vertebrate
4
R, U
LC50
MORT
7.0
8630
17640.63
17640.63
(Yin, et al., 2003a)
Ctenopharyngodon idellus
Vertebrate
4
R, U
LC50
MORT
7.0
3540
7236.13
7236.13
(Yin, et al., 2003a)
Carassius auratus*
Vertebrate
0.208
S, U
LC50
MORT
10
70000
9799.73
(Kishino and Kobayashi, 1995)
Carassius auratus*
Vertebrate
0.208
S, U
LC50
MORT
8
7000
5854.26
(Kishino and Kobayashi, 1995)
Carassius auratus*
Vertebrate
0.208
S, U
LC50
MORT
6
1500
7494.17
(Kishino and Kobayashi, 1995)
Carassius auratus*
Vertebrate
0.208
S, U
LC50
MORT
7
4008.24
8193.26
(Kishino and Kobayshi, 1996)
Carassius auratus
Vertebrate
4
R, U
LC50
MORT
7.0
4310
8810.09
8810.09
(Yin, et al., 2003a)
Erythroculter ilishaeformis
Vertebrate
4
R, U
LC50
MORT
7.24
1990
3282.50
3282.50
(Jin, et al., 2012a)
Lepomis macrochirus
Vertebrate
4
F, M
LC50
MORT
7.39
410
591.45
591.45
(Holcombe, et al., 1987)
Aplexa hypnorum
Species
Group
Duration
time (d)
Methods
Endpoints
Effect
measurements
pH
Concentrations
Concentrations
(μg/l)
(μg/l) pH=7.8
Geomean
References
2012.39
(Jin, et al., 2012a)
Mylopharyngodon piceus
Vertebrate
4
R, U
LC50
MORT
7.24
1220
2012.39
Oncorhynchus mykiss
Vertebrate
4
R, NR
LC50
MORT
6.2
1991
8319.13
Oncorhynchus mykiss
Vertebrate
4
S, U
LC50
MORT
7.8
572.03
572.03
Oncorhynchus mykiss
Vertebrate
4
F, M
LC50
MORT
7.39
730
1053.07
Poecilia reticulata
Vertebrate
4
R, M
LC50
MORT
7
2200
4497.03
(Salkinoja-Salonen, et al., 1981)
Poecilia reticulata*
Vertebrate
4
R, U
LC50
MORT
7
2288.1
4677.12
(Saarikoski and Viluksela, 1981)
Poecilia reticulata*
Vertebrate
4
R, U
LC50
MORT
5
611.48
7466.95
(Saarikoski and Viluksela, 1981)
Poecilia reticulata*
Vertebrate
4
R, U
LC50
MORT
8
7850.55
6565.60
(Saarikoski and Viluksela, 1981)
Poecilia reticulata*
Vertebrate
4
R, U
LC50
MORT
6
887.63
4434.70
5395.57
(Saarikoski and Viluksela, 1981)
Plagiognathops microlepis
Vertebrate
4
R, U
LC50
MORT
7.24
1100
1814.45
1814.45
(Jin, et al., 2012a)
Rana nigromaculata
Vertebrate
4
R, U
LC50
MORT
7.0
7460
15249.02
15249.02
(Yin, et al., 2003a)
Plant
3
S, U
LC50
MORT
5.1
5900
65887.08
65887.08
(Blackman, et al., 1955)
Lemna minor
(Kennedy, 1990)
(Hodson, 1985)
1711.27
(Holcombe, et al., 1987)
Spirostomum teres
Plant
1
S, U
LC50
MORT
7
2000
4088.21
4088.21
(Twagilimana, et al., 1998)
Soirodela polyrhiza
Plant
4
R, U
LC50
MORT
7.24
8490
14004.25
14004.25
(Jin, et al., 2012a)
Scenedesmus obliquus*
Plant
2
S, U
EC50
GGRT
6.5
2710
This study
Scenedesmus obliquus*
Plant
2
S, U
EC50
GGRT
7.5
3430
This study
Scenedesmus obliquus*
Plant
2
S, U
EC50
GGRT
9.0
25830
This study
Scenedesmus obliquus
Plant
1
S, U
EC50
GGRT
6.5
4370
13965.26
This study
Scenedesmus obliquus
Plant
1
S, U
EC50
GGRT
7.5
3760
4916.17
This study
Scenedesmus obliquus
Plant
1
S, U
EC50
GGRT
9.0
30690
10501.28
8966.84
This study
Table S4 Chronic toxicity data for Chinese species used to calculate water quality criteria for 2,4,6-trichlorophenol.
Species
Group
Duration
Methods
Endpoints
2
S, U
EC10
time (d)
Brachionus calyciflorus
Invertebrate
Corbicula fluminea
Invertebrate
21
R, M
Daphnia magna
Invertebrate
21
R, U
Daphnia magna
Invertebrate
21
Bufo bufo gargarizans
Vertebrate
Carassius auratus
Effect
measurements
pH
Concentrations
Concentrations
(μg/l)
(μg/l) pH=7.8
Geomean
References
(Radix, et al., 1999)
PROG
7.5
420
549.15
549.15
MATC
SURV
7.24
2830
4668.08
4668.08
(Jin, et al., 2012a)
NOEC
PROG
8.5
500
267.47
267.47
(Radix, et al., 1999)
R, U
MATC
GREP
7.0
283
578.48
578.48
(Yin, et al., 2003a)
30
R, U
MATC
GGRO
7.0
707
1445.18
1445.18
(Yin, et al., 2003a)
Vertebrate
30
R, U
MATC
GMOR
7.0
354
723.61
723.61
(Yin, et al., 2003a)
Ctenopharyngodon idellus
Vertebrate
60
F, U
MATC
GREP
7.0
707
1445.18
1445.18
(Yin, et al., 2003a)
Erythroculter ilishaeformis
Vertebrate
28
R, M
MATC
GGRO
7.24
350
577.33
577.33
(Jin, et al., 2012a)
Macrobrachium superbum
Vertebrate
21
R, M
MATC
SURV
7.24
140
230.93
230.93
(Jin, et al., 2012a)
Mylopharyngodon piceus
Vertebrate
28
R, M
MATC
GGRO
7.24
70
115.47
115.47
(Jin, et al., 2012a)
Plagiognathops microlepis
Vertebrate
28
R, M
MATC
GGRO
7.24
140
230.93
230.93
(Jin, et al., 2012a)
2606.21
(Jin, et al., 2012a)
Soirodela polyrhiza
Plant
10
R, M
MATC
CHLO
7.24
1580
2606.21
Scenedesmus obliquus
Plant
3d
S, U
EC10
GGRT
6.5
2000
6391.43
This study
Scenedesmus obliquus
Plant
3d
S, U
EC10
GGRT
7.5
2450
3203.35
This study
Scenedesmus obliquus
Plant
3d
S, U
EC10
GGRT
9.0
14200
4858.85
4633.53
This study
Table S5
Species
Ceriodaphnia dubia
Group
Invertebrate
Acute toxicity data for Chinese species used to calculate water quality criteria for pentachlorophenol.
Duration time
Methods
Endpoints
2
F, M
LC50
(d)
Effect
measurements
pH
MORT
8
Concentrations
Concentrations
(μg/l)
(μg/l) pH=7.8
307
Geomean
References
265.14
265.14
(Hedtke, et al., 1986)
Corbicula fluminea
Invertebrate
4
R, M
LC50
MORT
7.24
230
346.73
346.73
(Jin, et al., 2012b)
Ceriodaphnia reticulata
Invertebrate
2
F, M
LC50
MORT
7.3
150
216.40
216.40
(Hedtke, et al., 1986)
Invertebrate
4
F, M
LC50
MORT
8.5
1344
804.57
(Spehar, et al., 1985)
Invertebrate
4
F, M
LC50
MORT
6.5
139
360.46
(Spehar, et al., 1985)
Invertebrate
4
F, M
LC50
MORT
7.5
465
579.37
(Spehar, et al., 1985)
Invertebrate
4
F, M
LC50
MORT
8
929
802.32
Chironomus riparius*
Invertebrate
1
S, U
LC50
MORT
9
1948
808.32
(Fisher and Wadleigh, 1986)
Chironomus riparius*
Invertebrate
1
S, U
LC50
MORT
4
384
6223.22
(Fisher and Wadleigh, 1986)
Chironomus riparius*
Invertebrate
1
S, U
LC50
MORT
6
465
1739.65
2060.73
(Fisher and Wadleigh, 1986)
Brachionus calyciflorus
Invertebrate
2
S, U
EC50
HTCH
7.5
1310
1632.2
1632.2
(Radix, et al., 2000)
Daphnia magna
Invertebrate
2
S, M
LC50
MORT
8.58
145
81.86
(Spehar, et al., 1985)
Daphnia magna
Invertebrate
2
S, U
LC50
MORT
6.5
55
142.63
(Oikari, et al., 1992)
Daphnia magna
Invertebrate
2
S, U
LC50
MORT
6.5
38
98.54
(Virtanen, et al., 1989)
Daphnia magna
Invertebrate
2
S, U
LC50
MORT
6.5
55
142.63
(Virtanen, et al., 1989)
Daphnia magna
Invertebrate
2
S, M
LC50
MORT
8
860
742.73
(Kim, et al., 2006)
Daphnia magna*
Invertebrate
2
S, U
EC50
IMBL
7.1
61.5
102.73
This study
Daphnia magna*
Invertebrate
2
S, U
EC50
IMBL
8.0
346
298.82
Daphnia magna*
Invertebrate
2
S, U
EC50
IMBL
8.8
1232
591.93
Crangonyx
pseudogracilis*
Crangonyx
pseudogracilis*
Crangonyx
pseudogracilis*
Crangonyx
pseudogracilis*
605.94
(Spehar, et al., 1985)
This study
196.41
This study
Dreissena polymorpha*
Invertebrate
1
S, U
LC50
MORT
6.5
23.97
62.16
(Fisher, et al., 1999)
Dreissena polymorpha*
Invertebrate
1
S, U
LC50
MORT
7.5
53.27
66.37
(Fisher, et al., 1999)
Dreissena polymorpha*
Invertebrate
1
S, U
LC50
MORT
6.5
213.07
552.54
(Fisher, et al., 1999)
Dreissena polymorpha*
Invertebrate
1
S, U
LC50
MORT
8.5
319.61
191.33
(Fisher, et al., 1999)
Dreissena polymorpha*
Invertebrate
1
S, U
LC50
MORT
7.5
3089.54
3849.42
(Fisher, et al., 1999)
Dreissena polymorpha*
Invertebrate
1
S, U
LC50
MORT
7.5
612.58
763.25
(Fisher, et al., 1999)
Dreissena polymorpha*
Invertebrate
1
S, U
LC50
MORT
6.5
932.19
2417.37
(Fisher, et al., 1999)
Dreissena polymorpha*
Invertebrate
1
S, U
LC50
MORT
8.5
9135.46
5468.82
(Fisher, et al., 1999)
Dreissena polymorpha*
Invertebrate
1
S, U
LC50
MORT
8.5
2077.45
1243.64
Invertebrate
4
F, M
LC50
MORT
7.5
121
150.76
(Spehar, et al., 1985)
Invertebrate
4
F, M
LC50
MORT
8
484
418.00
(Spehar, et al., 1985)
Invertebrate
4
F, M
LC50
MORT
8.5
790
472.92
(Spehar, et al., 1985)
Invertebrate
4
F, M
LC50
MORT
6.5
92
238.58
290.38
(Spehar, et al., 1985)
Lymnaea acuminata
Invertebrate
2
R, U
LC50
MORT
7.9
228
211.89
211.89
(Gupta and Rao, 1982)
Limnodrilus hoffmeisteri
Invertebrate
4
R, U
LC50
MORT
7
500
898.75
898.75
(Chapman, et al., 1982)
Mesocyclops leuckarti
Invertebrate
2
S, U
LC50
MORT
7.3
138
199.09
Mesocyclops leuckarti
Invertebrate
2
S, U
LC50
MORT
7.3
173
249.58
222.91
(Willis, 1999)
Invertebrate
4
R, M
LC50
MORT
7.24
140
211.06
211.06
(Jin, et al., 2012b)
Rhabditis sp.
Invertebrate
2
S, U
LC50
MORT
6
9188.73
34376.7
34376.7
(Kammengaet al., 1994)
Simocephalus vetulus*
Invertebrate
2
F, M
LC50
MORT
7.3
160
230.83
(Hedtke, et al., 1986)
Simocephalus vetulus*
Invertebrate
2
F, M
LC50
MORT
7.7
250
269.01
(Hedtke, et al., 1986)
Gammarus
pseudolimnaeus
Gammarus
pseudolimnaeus*
Gammarus
pseudolimnaeus*
Gammarus
pseudolimnaeus*
Macrobrachium
superbum
651.23
(Fisher, et al., 1999)
(Willis, 1999)
Simocephalus vetulus*
Invertebrate
2
F, M
LC50
MORT
8
255
220.23
Simocephalus vetulus*
Invertebrate
2
F, M
LC50
MORT
8.3
364
252.31
242.36
(Hedtke, et al., 1986)
Tylenchus elegans
Invertebrate
2
S, U
LC50
MORT
6
1704.58
6377.12
6377.12
(Kammenga, et al., 1994)
Viviparus bengalensis
Invertebrate
2
S, U
LC50
MORT
7.9
1570
1459.04
1459.04
(Gupta and Durve, 1984)
Carassius auratus*
Vertebrate
1
S, U
LC50
MORT
9
2200
(Stehly and Hayton, 1990)
Carassius auratus*
Vertebrate
1
S, U
LC50
MORT
8
250
(Stehly and Hayton, 1990)
Carassius auratus*
Vertebrate
1
S, U
LC50
MORT
7
82
(Stehly and Hayton, 1990)
Carassius auratus
Vertebrate
4
S, U
LC50
MORT
7.3
23
33.18
(Inglis and Davis, 1972)
Carassius auratus
Vertebrate
4
S, U
LC50
MORT
7.7
49
52.73
(Inglis and Davis, 1972)
Carassius auratus
Vertebrate
4
S, U
LC50
MORT
7.5
55
68.53
(Inglis and Davis, 1972)
Carassius auratus
Vertebrate
4
S, U
LC50
MORT
7.3
56
80.79
(Inglis and Davis, 1972)
Carassius auratus
Vertebrate
4
F, M
LC50
MORT
7.84
200
194.22
(Thurstonet al., 1985)
Carassius auratus
Vertebrate
4
F, M
LC50
MORT
7.94
328
296.01
90.70
(Thurston, et al., 1985)
Vertebrate
4
R, M
LC50
MORT
7.24
130
195.98
195.98
(Jin, et al., 2012b)
Gambusia affinis
Vertebrate
4
F, M
LC50
MORT
8.02
278
236.60
Gambusia affinis
Vertebrate
4
F, M
LC50
MORT
8.05
288
239.78
Ictalurus punctatus
Vertebrate
4
S, NR
LC50
MORT
7.4
66
88.49
(Mayer and Ellersieck, 1986)
Ictalurus punctatus
Vertebrate
4
S, NR
LC50
MORT
7.4
68
91.17
(Mayer and Ellersieck, 1986)
Ictalurus punctatus
Vertebrate
4
F, M
LC50
MORT
7.71
132
141.00
Lepomis macrochirus
Vertebrate
4
S, U
LC50
MORT
7.7
24
25.83
(Inglis and Davis, 1972)
Lepomis macrochirus
Vertebrate
4
F, NR
LC50
MORT
7.4
215
288.25
(Mayer and Ellersieck, 1986)
Lepomis macrochirus
Vertebrate
4
S, NR
LC50
MORT
7.4
32
42.90
Lepomis macrochirus
Vertebrate
4
F, M
LC50
MORT
8.03
202
170.66
85.92
(Thurston, et al., 1985)
Mylopharyngodon piceus
Vertebrate
4
R, M
LC50
MORT
7.24
95
143.22
143.22
(Jin, et al., 2012b)
Micropterus salmoides
Vertebrate
4
R, U
LC50
MORT
7.2
287
445.54
Erythroculter
ilishaeformis
(Hedtke, et al., 1986)
(Thurston, et al., 1985)
238.18
104.39
(Thurston, et al., 1985)
(Thurston, et al., 1985)
(Mayer and Ellersieck, 1986)
(Johansen, et al., 1985)
Micropterus salmoides
Vertebrate
4
R, U
LC50
MORT
7.2
275
426.91
(Johansen, et al., 1985)
Micropterus salmoides
Vertebrate
4
R, U
LC50
MORT
7.2
136
211.13
(Johansen, et al., 1985)
Micropterus salmoides
Vertebrate
4
R, U
LC50
MORT
7.2
189
293.40
Oncorhynchus mykiss
Vertebrate
4
S, NR
LC50
MORT
7.4
115
154.18
(Mayer and Ellersieck, 1986)
Oncorhynchus mykiss
Vertebrate
4
S, NR
LC50
MORT
7.4
34
45.58
(Mayer and Ellersieck, 1986)
Oncorhynchus mykiss
Vertebrate
4
S, NR
LC50
MORT
7.4
52
69.72
(Mayer and Ellersieck, 1986)
Oncorhynchus mykiss
Vertebrate
4
S, NR
LC50
MORT
7.4
121
162.23
(Mayer and Ellersieck, 1986)
Oncorhynchus mykiss
Vertebrate
4
F, U
LC50
MORT
7.4
66
88.49
Oncorhynchus mykiss
Vertebrate
4
F, M
LC50
MORT
7.85
115
110.86
(Thurston, et al., 1985)
Oncorhynchus mykiss
Vertebrate
4
S, U
LC50
MORT
8
160
138.18
(Sappington, et al., 2001)
Oncorhynchus mykiss
Vertebrate
4
R, NR
LC50
MORT
6.22
153
487.15
(Kennedy, 1990)
Oncorhynchus mykiss
Vertebrate
4
S, U
LC50
MORT
8
160
138.18
124.63
(Dwyer, et al., 2005)
Vertebrate
4
R, M
LC50
MORT
7.24
90
135.68
135.68
(Jin, et al., 2012b)
Poecilia reticulata
Vertebrate
4
R, M
LC50
MORT
7
400
719.00
Poecilia reticulata*
Vertebrate
4
R, U
LC50
MORT
5
42.61
331.82
Poecilia reticulata*
Vertebrate
4
R, U
LC50
MORT
6
117.19
438.43
Poecilia reticulata*
Vertebrate
4
R, U
LC50
MORT
7
442.12
794.72
Plagiognathops
microlepis
Poecilia reticulata*
Vertebrate
4
R, U
LC50
MORT
8
910.88
786.67
Poecilia reticulata
Vertebrate
4
R, U
LC50
MORT
7.7
204
219.52
329.46
(Johansen, et al., 1985)
(Dominguez and Chapman,
1984)
(Salkinoja-Salonen, et al.,
1981)
(Saarikoski and Viluksela,
1981)
(Saarikoski and Viluksela,
1981)
(Saarikoski and Viluksela,
1981)
(Saarikoski and Viluksela,
1981)
(Khangarot, 1983)
Vertebrate
4
R, U
LC50
MORT
7.9
970
901.44
537.37
(Gupta, et al., 1982)
Plant
4
S, U
EC50
ABND
7.5
130
161.97
161.97
(Mostafa and Helling, 2002)
Plant
4
F, U
EC50
PGRT
7
410
736.98
736.98
(Schafer, et al., 1994)
Chlorella kessleri
Plant
4
S, U
EC50
ABND
8
34300
29622.8
29622.8
(Mostafa and Helling, 2002)
Lemna minor
Plant
3
S, U
LC50
MORT
5.1
190
1374.88
1374.88
(Blackman, et al., 1955)
Scenedesmus obliquus*
Plant
2
S, U
EC50
GGRT
6.5
293
This study
Scenedesmus obliquus*
Plant
2
S, U
EC50
GGRT
7.5
889
This study
Scenedesmus obliquus*
Plant
2
S, U
EC50
GGRT
9.0
16867
This study
Scenedesmus obliquus
Plant
1
S, U
EC50
GGRT
6.5
261
676.83
This study
Scenedesmus obliquus
Plant
1
S, U
EC50
GGRT
7.5
927
1155
This study
Scenedesmus obliquus
Plant
1
S, U
EC50
GGRT
9.0
24063
9984.91
Poecilia reticulata
Anabaena inaequalis
Chlamydomonas
reinhardtii
1983.67
This study
Table S6 Chronic toxicity data for Chinese species used to calculate water quality criteria for pentachlorophenol.
Species
Group
Duration time
(d)
Effect
methods
Endpoints
S, M
EC10
HTCH
Measurements
Concentrations
Concentrations
(μg/l)
(μg/l) pH=7.8
7.5
600
pH
Geomean
References
747.57
747.57
(Radix, et al., 2000)
Brachionus calyciflorus
Invertebrate
2
Ceriodaphnia dubia
Invertebrate
14
R, U
MATC
PROG
7.9
158
146.83
146.83
(Hickey, 1989)
Corbicula fluminea
Invertebrate
21
R, M
MATC
SURV
7.24
70
105.53
105.53
(Jin, et al., 2012b)
Daphnia carinata
Invertebrate
14
R, U
MATC
PROG
7.9
354
328.98
328.98
(Hickey, 1989)
Daphnia magna
Invertebrate
14
R, U
MATC
PROG
7.9
71
65.98
65.98
(Hickey, 1989)
Mesocyclops leuckarti
Invertebrate
6
S, U
MATC
MORT
7.3
104
150.04
150.04
(Willis, 1999)
Macrobrachium superbum
Invertebrate
21
R, M
MATC
SURV
7.24
12
18.09
18.09
(Jin, et al., 2012b)
Simocephalus vetulus
Invertebrate
14
R, U
MATC
PROG
7.9
71
65.98
65.98
(Hickey, 1989)
Vertebrate
28
R, M
MATC
GGRO
7.24
25
37.69
37.69
(Jin, et al., 2012b)
Mylopharyngodon piceus
Vertebrate
28
R, M
MATC
GGRO
7.24
14
21.11
21.11
(Jin, et al., 2012b)
Oncorhynchus mykiss
Vertebrate
30
F, M
EC10
DBMS
8.3
60
41.59
41.59
(Besser, et al., 2005)
Oncorhynchus mykiss
Vertebrate
30
F, M
MATC
DWGT
8.3
51
35.35
35.35
(Besser, et al., 2005)
Vertebrate
28
R, M
MATC
GGRO
7.24
14
21.11
21.11
(Jin, et al., 2012b)
Plant
4
S, U
EC10
ABND
7.5
20
24.92
24.92
Plant
10
F, M
NOEC
PGRT
7
360
647.10
647.10
Chlorella kessleri
Plant
2
S, U
EC10
ABND
8
8650
7470.48
7470.48
Soirodela polyrhiza
Plant
10
R, M
MATC
CHLO
7.24
350
527.64
527.64
Scenedesmus obliquus
Plant
3
S, U
EC10
GGRT
6.5
174
451.22
Erythroculter
ilishaeformis
Plagiognathops
microlepis
Anabaena inaequalis
Chlamydomonas
reinhardtii
(Mostafa and Helling,
2002)
(Schafer, et al., 1994)
(Mostafa and Helling,
2002)
(Jin, et al., 2012b)
This study
Scenedesmus obliquus
Plant
3
S, U
EC10
GGRT
7.5
301
375.03
Scenedesmus obliquus
Plant
3
S, U
EC10
GGRT
9.0
12440
1516.96
This study
635.54
This study
Note: *, species used to establish relationship between toxicity and pH. F, flow through; R, renewal; S, static; NR, not reported; U, unmeasured; M, measured; LC01/LC50, lethal concentration to
1%/50% of test organisms; EC10/EC50, effective concentration to 10%/50% of test organisms; MATC, maximum acceptable toxicant concentration; NOEC, no-observable-effect-concentration;
MORT, mortality; IMBL, immobile; GGRO, growth, general; GGRT, general growth rate; SURV, survival; reproduction, general; WGHT, weight; CHLO, chlorophyll; HTCH, hatch; ABND;
abundance; PROG, progeny counts/numbers; PGRT, population growth rate; DWGT, dry weight; DBMS, dry biomass.
Fig. S1 Four cases considerate in SSD analyses modified from Duboudin et al.(2004):(1)
intra-species variation weighted by geometric mean, but unweighted proportions of taxonomic
groups; (2) intra-species variation weighted by each data to give each species the same weight, but
unweighted proportions of taxonomic groups; (3) intra-species variation weighted by geometric
mean, and weighted proportions of taxonomic groups; (4) weighted both intra-species variation
(each data to give each species the same weight) and proportions of taxonomic groups. The total
available data were divided into three taxonomic groups: vertebrates (VE), invertebrates (INV)
and algae (AL).
Fig. S2 Relationships between pH values and acute toxicity data (48 h-EC50) or chronic toxicity
data (72 h-EC10) of three chlorophenols.
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