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Influence of pH on the toxicity of ionisable pharmaceuticals and personal care products to freshwater invertebrates.

15 Mar 2020-Ecotoxicology and Environmental Safety (Academic Press)-Vol. 191, pp 110172-110172

TL;DR: The results of this study show that pH fluctuations can have a considerable influence on toxicity thresholds, and should be taken into account for the risk assessment of ionisable pharmaceuticals and personal health-care products.

AbstractThe majority of pharmaceuticals and personal health-care products are ionisable molecules at environmentally relevant pHs. The ionization state of these molecules in freshwater ecosystems may influence their toxicity potential to aquatic organisms. In this study we evaluated to what extent varying pH conditions may influence the toxicity of the antibiotic enrofloxacin (ENR) and the personal care product ingredient triclosan (TCS) to three freshwater invertebrates: the ephemeropteran Cloeon dipterum, the amphipod Gammarus pulex and the snail Physella acuta. Acute toxicity tests were performed by adjusting the water pH to four nominal levels: 6.5, 7.0, 7.5 and 8.0. Furthermore, we tested the efficiency of three toxicity models with different assumptions regarding the uptake and toxicity potential of ionisable chemicals with the experimental data produced in this study. The results of the toxicity tests indicate that pH fluctuations of only 1.5 units can influence EC50-48 h and EC50-96 h values by a factor of 1.4–2.7. Overall, the model that only focuses on the fraction of neutral chemical and the model that takes into account ion-trapping of the test molecules showed the best performance, although present limitations to perform risk assessments across a wide pH range (i.e., well above or below the substance pKa). Under such conditions, the model that takes into account the toxicity of the neutral and the ionized chemical form is preferred. The results of this study show that pH fluctuations can have a considerable influence on toxicity thresholds, and should therefore be taken into account for the risk assessment of ionisable pharmaceuticals and personal health-care products. Based on our results, an assessment factor of at least three should be used to account for toxicity differences between standard laboratory and field pH conditions. The models evaluated here can be used to perform refined risk assessments by taking into account the influence of temporal and spatial pH fluctuations on aquatic toxicity.

Topics: Acute toxicity (56%), Aquatic toxicology (52%)

Summary (4 min read)

1. Introduction

  • Residues of pharmaceuticals and chemicals contained in personal health care products , have been monitored in a wide range of aquatic ecosystems across the world (Boxall et al.
  • Bioaccumulation and toxicity predictive models used for the ecological risk assessment of pharmaceuticals and PHCPs are generally based on the hydrophobic nature of chemicals and may therefore provide less accurate predictions when applied for ionisable substances.
  • The second model is based on the ion trap effect and assumes a preferential uptake of the neutral form of the chemical followed by a fast intracellular dissociation.
  • The main objectives of the present study were to assess the toxicity of a pharmaceutical and a PHCP ingredient to three aquatic invertebrates under a gradient of environmentally relevant pH conditions, and to evaluate the suitability of the aforementioned pH-dependent toxicity models for them.
  • The selected compounds were enrofloxacin (ENR) and triclosan (TCS).

2.1. Study chemicals

  • ENR (active ingredient ≥ 98%) and TCS (active ingredient ≥ 97%) were purchased from Sigma Aldrich (St Louis USA).
  • Separate stock solutions of ENR (50 g/L) and TCS (2 g/L) were prepared by diluting the pure substances in Milli-Q water with the help of NaOH, and were stored at −20 °C until their use in the experiments.

2.2. Test organisms

  • The toxicity of ENR and TCS was evaluated on three invertebrate species: the amphipod crustacean Gammarus pulex, the insect nymphs of Cloeon dipterum and the freshwater snail Physella acuta.
  • G. pulex were collected from an uncontaminated stream in Heelsum, the Netherlands.
  • Prior to the experiments the water content, the lipid content and the internal pH of the test organisms was evaluated (Table 1).
  • After evaporation, the vials were weighed again and the total lipid content of the sample was determined to calculate the lipid content of the aquatic organisms.
  • Then, both micro sensors were inserted into the solution formed and the pH was read from this sample.

2.3. Toxicity experiments

  • Toxicity experiments were performed following a 4 × 6 factorial design, with 4 different pHs (6.5, 7, 7.5 and 8), one control and 5 chemical concentrations.
  • The experiments were performed following some general recommendations provided in the Organisation for Economic Co-operation and Development (OECD): test guideline No. 202 (OECDOrganization for Economic Cooperation and Development, 2004).
  • The chosen temperature and light:dark regime was 20 °C and 12:12 h, respectively.
  • Temperature, conductivity and dissolved oxygen concentration in the exposure media were measured at the beginning and at the end of the toxicity experiment (Table S3).
  • G. pulex and C. dipterum individuals were counted as immobile when they showed inability to move after a tactile stimulus provided with a glass Pasteur pipette.

2.4. Chemical analyses

  • ENR and TCS concentrations were measured in the test medium at 2 h and 96 h after the application of the test compounds to verify the nominal concentrations and to assess the dissipation of the test compounds (Table S4).
  • Water samples were filtered through a 0.22-μm cellulose acetate membrane.
  • Chemical quantification was performed by injecting the amber glass vials into a triple quadrupole LC/MS system equipped with an ESI+.
  • A full description of the equipment and conditions used for the analysis of ENR and TCS are provided in the Supporting Information (see also Tables S5 and S6).
  • Additional tests were performed to evaluate the recovery of ENR and TCS from the test medium, using a concentration of 1 mg/L of ENR and 634 μg/L of TCS, which are in the low-to-middle range of the concentrations used in the toxicity tests.

2.5.1. Model 1: Only the neutral chemical form is active

  • The model considers the speciation of compounds in the exposure medium, and assumes that the neutral chemical form is taken up faster than the charged, so that the charged form does not contribute at all to the observed effect and can be neglected (Boström and Berglund, 2015).
  • Hence, the slope coefficient ( )1 N is calculated and used as independent variable in a linear regression, and the EC50 is determined from the regression slope coefficient.

2.5.2. Model 2: Both chemical forms are active and act additively

  • The model assumes that both the and the forms are biologically active but with different effect concentrations, EC50 and EC50 , and that the and the concentration act additively in the mixture, i.e., using the concentration addition model (Neuwoehner and Escher, 2011).
  • For simplicity, the authors assume that the cationic chemical form (in the case of ENR) does not contribute to the overall effect and consider only the anionic form.

2.5.3. Model 3: Only the neutral chemical fraction is active and results in an ion-trap effect

  • Similarly to model 1, this model assumes that the uptake of neutral chemical form by the aquatic organisms is much faster than that of the charged one, and therefore assumes permeability of the neutral chemical form only.
  • Moreover it considers dissociation of the chemical inside the organisms due to a difference between the pH of the exposure medium and the internal pH of the organisms, leading to an ion trap effect.

2.5. Data analyses

  • The data obtained from the toxicity experiments were used to calculate EC50 values, and their 95% confidence intervals, after an exposure period of 48 h and 96 h.
  • The calculations were performed using a log-logistic regression model as described by Rubach et al. (2011), and using the GenStat 11th edition software (VSN International Ltd., Oxford, UK).
  • All calculations were done on the basis of the average measured exposure concentrations during the experimental period.
  • Models 1–3 were implemented in Mathematica 12.0 (Wolfram Research) and fitted to experimental data.
  • Linear regression coefficients (R2) and Pearson p-values were calculated using the method “LinearModelFit”, and were used as indicators of correspondence between the calculated experimental data and the fitted models.

3.1. Invertebrate's sensitivity at different pH levels

  • Toxicity tests were performed to evaluate the sensitivity of the three invertebrate species to ENR and TCS at four different nominal pH levels.
  • Differences between the measured pH values and the nominal pH in the test medium of the toxicity experiments were generally within 0.2 units, with few exceptions going up to 0.3 units (Table 2).
  • According to Aranami and Readman (2007), the fast water dissipation of this compound is explained by its photolytic nature, its high sorption capacity to organic matter, and to a lower extent by hydrolisis.
  • The dissociation of TCS in the tested pH range was a bit lower than for ENR, and ranged from 3% to 35%, approximately (Table 2).
  • For G. pulex, TCS EC50-96 h values were low and showed less marked differences; however EC50-48 h values showed the same trend as for the other invertebrates, with a toxicity value that was 1.5 times higher in the pH 8 treatment as compared to the 6.5 treatment (Table 2).

3.2. pH-dependent toxicity models

  • Model 1 showed a good representation of the variability in the pHvariable toxicity values for both tested compounds (Figs. 1 and 2, Table 3), with R2 values above 94% and 85% for ENR and TCS, respectively, and significant Pearson correlations (p-values < 0.05).
  • From a theoretical point of view, Model 2 would be the preferred option as compared to Model 1 since it assumes that both the charged and the neutral chemical forms are active, and altough have different toxic potency, they act additively.
  • Model 2 showed the poorest fit for ENR and TCS, with Pearson correlation p-values above 0.05 (Table 3).
  • The latter confirms that for ENR the EC50s is more toxic than the EC50s .
  • These results must be interpreted taking into account that only a narrow pH range could be tested, the internal pH values of the tested organisms were close to neutrality, and the variability in the EC50 values was comparatively large.

4. Conclusions

  • This study supports the need to take into account the variability in pH conditions of aquatic ecosystems for the risk assessment of ionisable pharmaceuticals and PHCPs.
  • Moreover, this study shows the efficiency of three models that can be used to extrapolate toxicity values under different pH conditions.
  • Conceptualization, Investigation, also known as Frits Gillissen.
  • Paul J. Van den Brink: Conceptualization, Writing - original draft.
  • The authors declare no conflicts of interest.

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Influence of pH on the toxicity of ionisable pharmaceuticals and personal care
products to freshwater invertebrates
Ecotoxicology and Environmental Safety
Sun, Ming; Duker, Rahmat Quaigrane; Gillissen, Frits; Brink, Paul J.; Focks, Andreas et al
https://doi.org/10.1016/j.ecoenv.2020.110172
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Contents lists available at ScienceDirect
Ecotoxicology and Environmental Safety
journal homepage: www.elsevier.com/locate/ecoenv
Influence of pH on the toxicity of ionisable pharmaceuticals and personal
care products to freshwater invertebrates
Ming Sun
a
, Rahmat Quaigrane Duker
b
, Frits Gillissen
b
, Paul J. Van den Brink
b,c
, Andreas Focks
c
,
Andreu Rico
d,
a
Marine Biology Institute of Shandong Province, Qingdao, 266104, PR China
b
Department of Aquatic Ecology and Water Quality Management, Wageningen University, Wageningen University and Research Centre, P.O. Box 47, 6700 AA
Wageningen, the Netherlands
c
Wageningen Environmental Research, P.O. Box 47, 6700 AA Wageningen, the Netherlands
d
IMDEA Water Institute, Science and Technology Campus of the University of Alcalá, Avenida Punto Com 2, 28805, Alcalá de Henares, Madrid, Spain
ARTICLE INFO
Keywords:
Ionisable compounds
pH-related toxicity
Freshwater invertebrates
Pharmaceuticals
Personal care products
ABSTRACT
The majority of pharmaceuticals and personal health-care products are ionisable molecules at environmentally
relevant pHs. The ionization state of these molecules in freshwater ecosystems may influence their toxicity
potential to aquatic organisms. In this study we evaluated to what extent varying pH conditions may influence
the toxicity of the antibiotic enrofloxacin (ENR) and the personal care product ingredient triclosan (TCS) to three
freshwater invertebrates: the ephemeropteran Cloeon dipterum, the amphipod Gammarus pulex and the snail
Physella acuta. Acute toxicity tests were performed by adjusting the water pH to four nominal levels: 6.5, 7.0, 7.5
and 8.0. Furthermore, we tested the efficiency of three toxicity models with different assumptions regarding the
uptake and toxicity potential of ionisable chemicals with the experimental data produced in this study. The
results of the toxicity tests indicate that pH fluctuations of only 1.5 units can influence EC50-48 h and EC50-96 h
values by a factor of 1.4–2.7. Overall, the model that only focuses on the fraction of neutral chemical and the
model that takes into account ion-trapping of the test molecules showed the best performance, although present
limitations to perform risk assessments across a wide pH range (i.e., well above or below the substance pKa).
Under such conditions, the model that takes into account the toxicity of the neutral and the ionized chemical
form is preferred. The results of this study show that pH fluctuations can have a considerable influence on
toxicity thresholds, and should therefore be taken into account for the risk assessment of ionisable pharma-
ceuticals and personal health-care products. Based on our results, an assessment factor of at least three should be
used to account for toxicity differences between standard laboratory and field pH conditions. The models
evaluated here can be used to perform refined risk assessments by taking into account the influence of temporal
and spatial pH fluctuations on aquatic toxicity.
1. Introduction
Residues of pharmaceuticals and chemicals contained in personal
health care products (PHCPs), have been monitored in a wide range of
aquatic ecosystems across the world (Boxall et al. 2004, 2012; Kümerer,
2009; Ankley et al., 2007). Although monitored concentrations are
generally low (i.e., ng/L to μg/L range), some of these chemicals are
continuously emitted (Monteiro and Boxall, 2010), and might pose risks
for aquatic organisms (Brown et al., 2007; Bringolf et al., 2010; Kidd
et al., 2014). More than 80% of the available pharmaceuticals and
PHCPs are known to be ionisable substances at environmentally re-
levant pH conditions (Manallack, 2007). Some studies have
demonstrated that changes in water pH can influence the bioavail-
ability, uptake and toxicity of ionisable pharmaceuticals to aquatic
model organisms, where ionisable substances are generally more
bioaccumulative and toxic in their neutral than in their charged form
(Valenti et al., 2009; Kim et al., 2010; Rendal et al., 2011a; Meredith-
Williams et al., 2012; Karlsson et al., 2017).
The three main processes that influence the behavior of ionisable
compounds with changing pHs are: i) the reduction in lipophilicity
when a neutral compound becomes ionized, which limits uptake and
toxicity, ii) electrical attraction, which influences the uptake of cations
in negatively charged cells, and iii) the ion trap effect, which depends
on the pH gradient between the exposure medium and inside the
https://doi.org/10.1016/j.ecoenv.2020.110172
Received 3 October 2019; Received in revised form 23 December 2019; Accepted 2 January 2020
Corresponding author.
E-mail address: andreu.rico@imdea.org (A. Rico).
Ecotoxicology and Environmental Safety 191 (2020) 110172
Available online 21 January 2020
0147-6513/ © 2020 Elsevier Inc. All rights reserved.
T

organism's body, and the differences in dissociation of the chemicals in
these two compartments (Rendal et al., 2011b). Bioaccumulation and
toxicity predictive models used for the ecological risk assessment of
pharmaceuticals and PHCPs are generally based on the hydrophobic
nature of chemicals and may therefore provide less accurate predictions
when applied for ionisable substances. Some studies have proposed
alternative bioaccumulation modelling approaches based on the pH-
corrected octanol/water partition coefficient or the pH-corrected lipo-
some/water partition coefficients to predict the bioaccumulation of
ionisable substances in aquatic organisms (Paterson and Metcalfe,
2008; Fu et al., 2009; Meredith-Williams et al., 2012). For example,
Karlsson et al. (2017) presented a combined experimental and model-
ling approach to characterize the uptake of three ionisable chemicals to
the annelid Lumbriculus variegatus over time at different pH conditions
in contaminated water and sediment exposure scenarios. Taking into
account the range of water pHs measured in European streams,
Karlsson et al. (2017) estimated that uptake of highly ionisable sub-
stances may vary by a factor of more than 3000 depending on the pH
conditions, which may have severe consequences for the bioaccumu-
lation and ecotoxicological potential of these substances.
Several authors have proposed toxicity models of different com-
plexity to predict toxicity variation of pharmaceuticals regarding fluc-
tuating pH values. Boström and Berglund (2015) proposed a simple
model to predict acute toxicity to D. magna based on the fraction of
neutral chemical and assuming that only this fraction is active.
Neuwoehner and Escher (2011) tested the pH-dependent toxicity of five
basic pharmaceuticals on the green algae Scenedesmus vacuolatus and
developed two mechanistic models that take into account the differ-
ences in toxicity related to the neutral and the charged chemical form.
The first model assumes that the neutral and the charged form of the
chemical are biologically active but have different toxicities, and that
the effect of the two forms can be predicted based on the concentration
addition model. The second model is based on the ion trap effect and
assumes a preferential uptake of the neutral form of the chemical fol-
lowed by a fast intracellular dissociation. Recently, Baumer et al.
(2017) tested the three afore-mentioned models for 42 pharmaceuticals
with a pH gradient of 5.5–9, using the bioluminescence inhibition test
with the bacterium Aliivibrio fischeri. These authors concluded that
neither the model that neglects uptake of the charged fraction, nor the
model that accounts for equal uptake between the charged and un-
charged fraction fully explain the observed results. Probably the actual
processes interfering with the compound's toxicity are in between the
two assumptions proposed by these models. On the other hand, the
model that takes into account ion trapping improved predictions for
some pharmaceuticals and pH values, but not for all (Baumer et al.,
2017).
The quantitative estimation of the pH-dependency of effects of
pharmaceuticals and PHCPs chemicals on aquatic organisms is im-
portant for several reasons. First, to provide recommendations on
worst-case pH values (or ranges) to be used in further toxicity testing.
Second to assess their toxicity taking into account daily pH fluctuations
of freshwater ecosystems. And third, to make risk extrapolations across
different aquatic ecosystems with substantial pH differences (e.g. oli-
gotrophic vs eutrophic). To date, the available models for assessing pH-
dependent toxicity have been mainly evaluated with microorganisms
and D. magna, while there is little or no information regarding their
predictive power for non-standard test invertebrates and other higher
aquatic organisms. This leaves a margin of uncertainty on the suitability
of the proposed modelling tools for making risk predictions for species
with different biological traits, which should be further studied and
incorporated into future hazard and risk assessments.
The main objectives of the present study were to assess the toxicity
of a pharmaceutical and a PHCP ingredient to three aquatic in-
vertebrates under a gradient of environmentally relevant pH condi-
tions, and to evaluate the suitability of the aforementioned pH-depen-
dent toxicity models for them. The selected compounds were
enrofloxacin (ENR) and triclosan (TCS). ENR is a fluoroquinolone an-
tibiotic which is frequently used as veterinary medicine in livestock and
aquaculture production (Rico et al., 2014; Sun et al., 2016). It can be
considered as a weak acid or a weak base due to its dual pKa value
(pKa
1
= 6.06; pKa
2
= 7.70) and has a relatively low bioaccumulation
potential (log Kow = 0.39; Table S1). TCS is an antimicrobial com-
pound used as component of a wide range of PHCPs such as body soaps
and toothpastes (Singer et al., 2002; Tsai et al., 2008). It is a weak acid
(pKa = 8.14) with relatively high hydrophobic characteristics (log
Kow = 4.76; Table S1). Some studies have shown high dissociation
properties and varied toxicity exerted by these chemicals to aquatic
standard test organisms depending on the tested pH (Kim et al., 2010;
Khatikarn et al., 2016; Li et al., 2018). In this study we extend these
evaluations with non-standard test organisms and provide some re-
commendations on the extrapolation factors needed to account for
toxicity differences between standard laboratory and varying pH con-
ditions usually observed in the field.
2. Materials and methods
2.1. Study chemicals
ENR (active ingredient 98%) and TCS (active ingredient 97%)
were purchased from Sigma Aldrich (St Louis USA). Separate stock
solutions of ENR (50 g/L) and TCS (2 g/L) were prepared by diluting
the pure substances in Milli-Q water with the help of NaOH, and were
stored at −20 °C until their use in the experiments.
2.2. Test organisms
The toxicity of ENR and TCS was evaluated on three invertebrate
species: the amphipod crustacean Gammarus pulex, the insect nymphs of
Cloeon dipterum and the freshwater snail Physella acuta. G. pulex were
collected from an uncontaminated stream in Heelsum, the Netherlands.
C. dipterum and P. acuta were collected from the outdoor mesocosms of
the Sinderhoeve research station (Renkum, the Netherlands, www.
sinderhoeve.org). The collected organisms were acclimatized to the
laboratory conditions for at least 48 h prior to the start of the experi-
ments. For this, organisms were kept in plastic buckets filled with un-
contaminated groundwater, using a constant temperature of 20 °C and a
light:dark regime of 12:12 h.
Prior to the experiments the water content, the lipid content and the
internal pH of the test organisms was evaluated (Table 1). The first two
parameters were measured to characterize the test organisms, while the
internal pH was used for the modelling calculations. The water content
was calculated as the difference between the wet weight of the animals
measured alive (after external water elimination with a paper tissue)
and the dry weight measured after water evaporation in the oven
(105 °C) for 24 h (APHAAmerican Public Health Association, 2005).
The lipid content was determined using an adaptation of the method
described by Folch et al. (1957). Briefly, dried individuals were
weighed and introduced into a chloroform and methanol (2:1) solution.
The sample was homogenized using an orbital shaker at 20 °C and then
centrifuged for 20 min at 1400 rpm. The supernatant was transferred
into a new centrifuge tube. The sample volume was measured and
Table 1
Water content, lipid content and internal pH of the tested organisms
(mean ± SD).
Species Water content (%)
(n = 30)
Internal pH
(n = 5)
Lipid content (%)
(n = 4)
G. pulex 80.9 ± 3.36 7.91 ± 0.20 1.37 ± 0.21
C. dipterum 42.0 ± 14.1 7.10 ± 0.08 6.22 ± 0.25
P. acuta 87.7 ± 4.40 6.97 ± 0.26 1.98 ± 0.06
M. Sun, et al.
Ecotoxicology and Environmental Safety 191 (2020) 110172
2

water was added (20% of the sample volume). Next, the centrifuge
tubes containing the sample were vortexed for 30 s to separate the
water from the lipid layer of the sample. The lipid phase was transferred
into a pre-weighed vial and the excess solvent contained in this sample
was evaporated under a nitrogen stream. After evaporation, the vials
were weighed again and the total lipid content of the sample was de-
termined to calculate the lipid content of the aquatic organisms. The
internal pH of the test organisms was determined according to the
method described by Sommer et al. (2000). The internal pH was mea-
sured using an ion-selective pH sensor (unisensor), which contained a
reference sensor and a measuring micro sensor. Before measurements,
measuring and reference micro sensors were both calibrated with pH 4
and 7. After this, we inserted both micro sensors into one organism of P.
acuta. The same technique could not be applied to G. pulex and C.
dipterum due to their small size as compared to P. acuta. For G. pulex and
C. dipterum, three individual organisms were put together and smashed
in 2 mL of Milli-Q water. Then, both micro sensors were inserted into
the solution formed and the pH was read from this sample.
2.3. Toxicity experiments
Toxicity experiments were performed following a 4 × 6 factorial
design, with 4 different pHs (6.5, 7, 7.5 and 8), one control and 5
chemical concentrations. The pHs were considered environmentally
relevant, and were selected taking into account the dissociation con-
stant of the test chemicals and the pH tolerance range of the test or-
ganisms based on preliminary tests. The test concentrations were
decided according to the outcomes of previously performed toxicity
range-finding tests (Table S2). The toxicity experiments were carried
out in triplicate using glass beakers containing 500 mL of exposure
media (groundwater) and 10 individuals per test unit, except for the P.
acuta with ENR, for which 8 individuals were used. The experiments
lasted for 96 h and the pH of the exposure media was measured and
adjusted every 24 h by titration with 0.1 M hydrochloride acid (HCl) in
the 6.5, 7 and 7.5 pH levels, and with 0.1 M tris(hydroxymethyl)ami-
nomethane hydrochloride buffer in the 8 pH level.
The experiments were performed following some general re-
commendations provided in the Organisation for Economic Co-opera-
tion and Development (OECD): test guideline No. 202
(OECDOrganization for Economic Cooperation and Development,
2004). For example, experiments were only considered as valid when
the immobility did not exceed 10% during the experimental period in
the chemical controls. The chosen temperature and light:dark regime
was 20 °C and 12:12 h, respectively. The beakers of the G. pulex ex-
periment contained a stainless steel mesh that was used as distraction
material to prevent cannibalism among them. Temperature, con-
ductivity and dissolved oxygen concentration in the exposure media
were measured at the beginning and at the end of the toxicity experi-
ment (Table S3). Immobilisation was used as evaluation endpoint,
which can be considered a proxy of mortality and is commonly used to
assess effects on small organisms, for which it is difficult to distinguish
between immobile and dead ones. The number of immobile animals
was counted in each replicate at 48 h and 96 h after the start of the
exposure period. G. pulex and C. dipterum individuals were counted as
immobile when they showed inability to move after a tactile stimulus
provided with a glass Pasteur pipette. P. acuta individuals were con-
sidered as immobile when no reaction was observed after tactile stimuli
of the soft body for three times with a glass Pasteur pipette or when
they were turned upside down.
2.4. Chemical analyses
ENR and TCS concentrations were measured in the test medium at
2 h and 96 h after the application of the test compounds to verify the
nominal concentrations and to assess the dissipation of the test com-
pounds (Table S4). Water samples were filtered through a 0.22-μm
cellulose acetate membrane. Next, the sample was diluted by adding
200 μL of acetonitrile to 800 μL of test medium sample in glass amber
vials. The samples taken for the analysis of TCS were centrifuged at
4500 rpm for 20–30 min. Finally, 1 mL of the supernatant was trans-
ferred to 2 mL-amber glass vials using a glass Pasteur pipette.
Chemical quantification was performed by injecting the amber glass
vials into a triple quadrupole LC/MS system equipped with an ESI+. A
full description of the equipment and conditions used for the analysis of
ENR and TCS are provided in the Supporting Information (see also
Tables S5 and S6). Additional tests were performed to evaluate the
recovery of ENR and TCS from the test medium, using a concentration
of 1 mg/L of ENR and 634 μg/L of TCS, which are in the low-to-middle
range of the concentrations used in the toxicity tests. The mean re-
covery rates for ENR and TCS from the water medium ranged between
64% and 98%, and between 108% and 141%, respectively (Table S7).
2.5. Toxicity models
2.5.1. Model 1: Only the neutral chemical form is active
The model considers the speciation of compounds in the exposure
medium, and assumes that the neutral chemical form is taken up faster
than the charged, so that the charged form does not contribute at all to
the observed effect and can be neglected (Boström and Berglund, 2015).
The fractions of neutral molecules are calculated based on the Hen-
derson-Hasselbach equation according to:
=
+ +
for ENR
1
1 10 10
N
pKa pH pH pKa
1 2
(1)
=
+
For TCS
1
1 10
,
N
pH pKa
(2)
For ENR, we used pKa
1
= 6.06 and pKa
2
= 7.7 (Kim et al., 2010);
for TCS, we used pKa = 8.14 (Aldous et al., 2012).
The EC50 (pH) at a given water pH value is defined as:
=EC pH EC neutral( )
1
· ( )
N
50 50
(3)
where
N
refers to the fraction of neutral or uncharged chemical, and
EC50 (neutral) refers to the EC50 of the neutral chemical form. Hence,
the slope coefficient
( )
1
N
is calculated and used as independent vari-
able in a linear regression, and the EC50 (neutral) is determined from
the regression slope coefficient.
2.5.2. Model 2: Both chemical forms are active and act additively
The model assumes that both the neutral and the charged forms are
biologically active but with different effect concentrations, EC50
(neutral) and EC50 (charged), and that the neutral and the charged
concentration act additively in the mixture, i.e., using the concentration
addition model (Neuwoehner and Escher, 2011). The EC50 at a given
pH is defined as:
(4)
Hence, the fraction of neutral chemical (
N
) is used as independent
variable in a linear regression, and the EC (neutral) and EC50 (charged)
are determined from the slope and intercept regression coefficients. For
simplicity, we assume that the cationic chemical form (in the case of
ENR) does not contribute to the overall effect and consider only the
anionic form.
2.5.3. Model 3: Only the neutral chemical fraction is active and results in an
ion-trap effect
Similarly to model 1, this model assumes that the uptake of neutral
chemical form by the aquatic organisms is much faster than that of the
charged one, and therefore assumes permeability of the neutral
M. Sun, et al.
Ecotoxicology and Environmental Safety 191 (2020) 110172
3

chemical form only. Moreover it considers dissociation of the chemical
inside the organisms due to a difference between the pH of the exposure
medium and the internal pH of the organisms, leading to an ion trap
effect. According to Büttner and Büttner (1980), the relationship be-
tween the internal concentration of the neutral chemical form and the
external concentration can be formulated as:
=
+
+
=C C BCF·
1 10
1 10
C ·
int neutral ext neutral
pH pKa
pH
ext neutral N, , ,
int
ext pKa
(5)
where C
int, neutral
refers to the internal concentration of the neutral
chemical form, C
ext, neutral
the external concentration of the neutral
chemical form, and BCF
N
to the bioconcentration factor calculated for
the neutral chemical.
Then, the following equation can be derived to estimate the EC50 at
a given pH:
=EC pH
BCF
EC neutral int pH( )
1
· ( , )
N
50 50
(6)
where the independent variable
( )
BCF
1
N
is plotted in a linear regression
form, and the EC50 (neutral, int pH) is determined from the slope re-
gression coefficient.
2.5. Data analyses
The immobility data obtained from the toxicity experiments were
used to calculate EC50 (immobility) values, and their 95% confidence
intervals, after an exposure period of 48 h and 96 h. The calculations
were performed using a log-logistic regression model as described by
Rubach et al. (2011), and using the GenStat 11th edition software (VSN
International Ltd., Oxford, UK). All calculations were done on the basis
of the average measured exposure concentrations during the experi-
mental period. Models 1–3 were implemented in Mathematica 12.0
(Wolfram Research) and fitted to experimental data. Linear regression
coefficients (R
2
) and Pearson p-values were calculated using the
method “LinearModelFit”, and were used as indicators of correspon-
dence between the calculated experimental data and the fitted models.
3. Results and discussion
3.1. Invertebrate's sensitivity at different pH levels
Toxicity tests were performed to evaluate the sensitivity of the three
invertebrate species to ENR and TCS at four different nominal pH levels.
Differences between the measured pH values and the nominal pH in the
test medium of the toxicity experiments were generally within 0.2
units, with few exceptions going up to 0.3 units (Table 2). This indicates
the pH was succesfully controlled in the different treatments. No im-
mobility was recorded in the controls of the ENR experiments, while in
the test units without TCS addition some immobility was observed only
for G. pulex and P. acuta, reaching maximum values of 7% and 10%,
respectively. No clear relationship was observed between the pH in the
chemical controls and the observed immobility. This supports the as-
sumption that any potential differences of the toxicity of the chemicals
is related to their dissociation at different pH conditions, and not to an
influence of the pH on the fitness of the test organisms. The observed
immobility could have been caused by some damage due to the ma-
nipulation of the organisms when setting up the experiments, and was
considered acceptable since it was within or close to the maximum
treshold (10%) established by the OECD guideline (OECD, 2004).
Measured concentrations of ENR in the three toxicity experiments
were within 67% and 130% of the nominal concentrations at the start
of the experiment (2 h after the application) and were kept relatively
constant during the experimental period. Measured concentrations of
TCS at the start of the experiment were within 77–132% of the nominal
concentrations in the three tests. TCS, however, showed a faster dis-
sipation rate as compared to ENR with concentrations becoming 30% of
the initial measured concentrations at the end of the 96 h exposure
period. The dissipation was taken into account in the EC50 calculations
(by using the average measured concentrations), and was not found to
be pH-dependent. According to Aranami and Readman (2007), the fast
water dissipation of this compound is explained by its photolytic
nature, its high sorption capacity to organic matter, and to a lower
extent by hydrolisis. Given the test conditions in our study (i.e., no
sediment and low density of living organisms), photolysis and
Table 2
EC50 values for enrofloxacin (ENR) and triclosan (TCS) on the three test invertebrate species at different pH conditions. The measured pH conditions in the test
medium are provided together with the calculated fraction of neutral chemical (
N
).
Species Nominal pH 48 h 96 h
Chemical Measured pH (mean ± SD)
N
EC50 (mg/L) (95% CI) Measured pH (mean ± SD)
N
EC50 (mg/L) (95% CI)
ENR G. pulex 6.5 6.75 ± 0.04 0.76 35.5 (29.4–42.8) 6.65 ± 0.04 0.74 16.3 (NC)
7.0 7.12 ± 0.02 0.74 42.1 (33.9–52.4) 7.1 ± 0.02 0.74 15.6 (11.9–20.5)
7.5 7.49 ± 0.02 0.61 55.1 (NC) 7.49 ± 0.01 0.60 22.1 (17.8–27.4)
8.0 7.88 ± 0.04 0.40 58.2 (48.1–70.5) 7.91 ± 0.03 0.38 24.3 (NC)
C. dipterum 6.5 6.72 ± 0.04 0.76 26.7 (19.9–35.9) 6.68 ± 0.03 0.75 21.4 (15.8–29.1)
7.0 7.16 ± 0.03 0.73 34.6 (27.0–44.4) 7.13 ± 0.02 0.74 26.9 (21.4–33.8)
7.5 7.54 ± 0.02 0.58 34.4 (26.8–44.1) 7.53 ± 0.01 0.58 26.8 (21.2–34.0)
8.0 7.94 ± 0.02 0.36 69.5 (58.4–82.7) 7.95 ± 0.02 0.36 29.2 (22.6–37.7)
P. acuta 6.5 6.68 ± 0.04 0.75 115 (NC) 6.63 ± 0.05 0.74 79.7 (68.6–92.6)
7.0 7.28 ± 0.06 0.69 133 (110–160) 7.20 ± 0.04 0.72 112 (91.6–137)
7.5 7.50 ± 0.04 0.60 192 (154–239) 7.50 ± 0.03 0.60 121 (99.3–148)
8.0 7.88 ± 0.06 0.39 206 (163–259) 7.92 ± 0.04 0.37 143 (116–176)
TCS G. pulex 6.5 6.74 ± 0.03 0.96 0.36 (0.26–0.50) 6.64 ± 0.02 0.97 0.08 (0.05–0.11)
7.0 7.04 ± 0.05 0.93 0.19 (0.11–0.33) 7.06 ± 0.03 0.92 0.09 (0.06–0.13)
7.5 7.49 ± 0.02 0.82 0.25 (NC) 7.49 ± 0.02 0.82 0.10 (NC)
8.0 7.85 ± 0.02 0.66 0.55 (0.54–0.56) 7.89 ± 0.01 0.64 0.06 (0.03–0.11)
C. dipterum 6.5 6.70 ± 0.06 0.96 0.26 (0.18–0.38) 6.69 ± 0.04 0.97 0.09 (0.06–0.15)
7.0 7.15 ± 0.02 0.91 0.45 (0.37–0.54) 7.15 ± 0.01 0.91 0.09 (0.06–0.14)
7.5 7.54 ± 0.01 0.80 0.49 (0.37–0.65) 7.54 ± 0.01 0.80 0.10 (0.06–0.19)
8.0 7.91 ± 0.01 0.63 0.51 (0.40–0.65) 7.93 ± 0.01 0.62 0.24 (0.18–0.31)
P. acuta 6.5 6.62 ± 0.05 0.97 0.51 (0.49–0.55) 6.62 ± 0.03 0.97 0.33 (0.24–0.45)
7.0 7.07 ± 0.04 0.92 0.75 (0.61–0.94) 7.05 ± 0.04 0.92 0.45 (0.40–0.50)
7.5 7.42 ± 0.02 0.84 1.29 (NC) 7.43 ± 0.01 0.84 0.29 (NC)
8.0 7.78 ± 0.02 0.70 0.55 (0.55–0.56) 7.83 ± 0.01 0.67 0.70 (0.66–0.73)
NC: could not be calculated.
M. Sun, et al.
Ecotoxicology and Environmental Safety 191 (2020) 110172
4

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Abstract: Set your standards with these standard methods. This is it: the most widely read publication in the water industry, your all-inclusive reference tool. This comprehensive reference covers all aspects of USEPA-approved water analysis methods. More than 400 methods - all detailed step-by-step; 8 vibrant, full-color pages of aquatic algae illustrations; Never-before-seen figures that will help users with toxicity testing and the identification of apparatus used in the methods; Over 300 superbly illustrated figures; A new analytical tool for a number of inorganic nonmetals; Improved coverage of data evaluation, sample preservation, and reagant water; And much more!

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Frequently Asked Questions (1)
Q1. What are the contributions mentioned in the paper "Influence of ph on the toxicity of ionisable pharmaceuticals and personal care products to freshwater invertebrates" ?

In this study the authors evaluated to what extent varying pH conditions may influence the toxicity of the antibiotic enrofloxacin ( ENR ) and the personal care product ingredient triclosan ( TCS ) to three freshwater invertebrates: the ephemeropteran Cloeon dipterum, the amphipod Gammarus pulex and the snail Physella acuta. Acute toxicity tests were performed by adjusting the water pH to four nominal levels: 6. 5, 7. 0, 7. 5 and 8. 0. Furthermore, the authors tested the efficiency of three toxicity models with different assumptions regarding the uptake and toxicity potential of ionisable chemicals with the experimental data produced in this study. The results of this study show that pH fluctuations can have a considerable influence on toxicity thresholds, and should therefore be taken into account for the risk assessment of ionisable pharmaceuticals and personal health-care products.