Environ Sci Pollut Res DOI 10.1007/s11356-014-3899-z
RESEARCH ARTICLE
Environmental risk of combined emerging pollutants in terrestrial environments: chlorophyll a fluorescence analysis Víctor González-Naranjo & Karina Boltes & Irene de Bustamante & Pino Palacios-Diaz
Received: 17 September 2014 / Accepted: 20 November 2014 # Springer-Verlag Berlin Heidelberg 2014
Abstract The risk assessment in terrestrial environments has been scarcely studied for mixtures of organic contaminants. To estimate toxicity due to these compounds, an ecotoxicological test may be done with the appropriate organism and biomarker. Photosynthesis is principally performed at photosystem II, and its efficiency is affected by any environmental stress. Consequently, the measure of this efficiency may be a good indicator of toxicity if different parameters are employed, e.g., the quantum efficiency of photosystem II and the photochemical quenching coefficient. We did a series of assays to determine the toxicity of two organic contaminants, ibuprofen and perfluorooctanoic acid, using a higher plant (Sorghum bicolor). The results showed more toxicity for the perfluorinated compound and greater sensibility for the quantum efficiency of photosystem II. Regarding the binary combination, three methods were applied to calculate EC50: combination index, concentration addition, and independent Responsible editor: Leif Kronberg Electronic supplementary material The online version of this article (doi:10.1007/s11356-014-3899-z) contains supplementary material, which is available to authorized users. V. González-Naranjo : K. Boltes Department of Chemical Engineering, University of Alcalá, 28771 Alcalá de Henares, Madrid, Spain V. González-Naranjo (*) : K. Boltes : I. de Bustamante Advanced Study Institute of Madrid, IMDEA-Agua, Parque Científico Tecnológico, 28805 Alcalá de Henares, Madrid, Spain e-mail: [email protected] I. de Bustamante Department of Geology, University of Alcalá, 28771 Alcalá de Henares, Madrid, Spain P. Palacios-Diaz Department of Animal Pathology, Animal Production, Food Science and Food Technology, Universidad de Las Palmas de Gran Canaria, 35001 Las Palmas de Gran Canaria, Spain
action. Synergistic behavior is the principal toxicological profile for this mix. Therefore, the combination index, which considers interactions among chemicals, gave the best estimation to determine risk indices. We conclude that the inhibition of photosynthesis efficiency can be a useful tool to determine the toxicity of the mixtures of organic pollutants and to estimate ecological risks in terrestrial environments. Keywords Combination index . Hazard quotient . Organic compounds . Photosynthesis . Phytotoxicity . Quantum efficiency of PSII
Introduction The environmental risk due to the presence of mixtures of organic micropollutants has been scarcely studied, especially in terrestrial environments. Some works have focused on risk analyses in aquatic environments (Vázquez-Roig et al. 2011; Stasinakis et al. 2012), but very few research works have assessed the risk of these contaminants occurring in soils (Martín et al. 2012; González-Naranjo et al. 2013). This environmental risk is studied from the toxicity of the compounds analyzed, which has been extensively determined for the effect exerted when they act individually. In the environment, however, these pollutants appear like mixtures, and the ecotoxicity effects of mixtures may differ from those obtained for individual compounds (Rodea-Palomares et al. 2010). Unfortunately, toxicity values strongly depend on the conceptual model chosen to assess the mixture. Furthermore, an organism representative of soil and some specific signal of stress have to be selected to determine the toxicity effect of organic pollutants in this environmental compartment. Photosynthesis is an important process in plants, the primary producers in the Earth’s ecosystem, which is based on
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their growth and development. Chlorophyll fluorescence emitted by higher plants can reflect photosynthetic activities in a complex manner (Hussain and Reigosa 2011). The fluorescence emission of chlorophyll is a fast, cheap, powerful, noninvasive, and reliable tool to determine photosynthetic activity due to stress in plants (Zarco-Tejada et al. 2009). A stress situation for a plant is defined as an external factor that exerts an undesirable influence on it, which causes different responses at all physiological levels. By altering the photosynthetic electron transfer, plants can cope with this stress (Ibáñez et al. 2010). Dark-adapted oxygenic photosynthetic organisms show a change in PSII photochemistry, which is based on the theory of energy flux in biomembranes when they are illuminated with high-intensity actinic light (Strasser 1978). Advances in fluorescence spectroscopy and reflectance-derived fluorescence may be put to good use in toxicity testing by bioassays, which enable the detection of stress in plants, especially before the changes in chlorophyll content become visible. The quantum yield of photosystem II (ΦII) is the most widely used fluorescence parameter as it responds rapidly to exposure to toxins (Ralph et al. 2007; Buonasera et al. 2011; Iriel et al. 2014). Many studies have assessed the effect of different stress situations by applying this method on photosynthetic organisms, such as high plants, algae, and lichens. Environmental stress conditions, such as temperature, salinity, or water stress, have been extensively studied (Faraloni et al. 2011; Oukarroum et al. 2012). Different metals have also been analyzed, e.g., copper, cadmium, silver, or chromium (Redondo-Gómez et al. 2010, 2011; Xu et al. 2010, 2012; Vantová et al. 2013), and several authors have investigated inhibition of PSII caused by ozone (Riddell et al. 2012). Nevertheless, there are very few research works available that have studied the effect of organic compounds, such as metolachlor, benz(a)anthracene and fluoranthene in phytoplankton (Othman et al. 2012; Thakkar et al. 2013), various herbicides commonly used in agriculture in green algae (Magnusson et al. 2010; Kumar and Han 2011; Bi et al. 2012), bisphenol A in soya bean seedlings (Qiu et al. 2013), cytokinin in aubergine seedlings (Wu et al. 2012), or TNT in two high plants (Naumann et al. 2010). Yet no studies have used PSII inhibition to study the toxicity of organic micropollutants, such as pharmaceuticals or industrial chemicals. Some works have studied their toxicity to photosynthetic organisms, like algae and aquatic plants (Rosal et al. 2010; Xu et al. 2013) or high plants (Zhao et al. 2011; Furtula et al. 2012; González-Naranjo and Boltes 2013). Emerging pollutants are found extensively in environmental samples of water and soil, such as pharmaceuticals or industrial chemicals. Among pharmaceuticals, ibuprofen, a nonsteroidal anti-inflammatory drug, is frequently present given its mass consumption worldwide (Gottschall et al. 2012; Duan et al. 2013; Aznar et al. 2013). In soil, this drug
has been found in concentrations up to 318.50 ng g−1 (Karnjanapiboonwong et al. 2011). When focusing on both toxicological data and environmental concentrations, chronic toxic effects cannot be excluded (Grung et al. 2008). Perfluorooctanoic acid (PFOA), a final decomposition product of fluorinated alkyl compounds of widespread application in industrial processes, has also been found in aquatic and terrestrial environments (Meng et al. 2013; Perkola and Sainio 2013; Pico et al. 2012), reaching concentrations of 47.50 ng g−1 in soil (Li et al. 2010). It is widespread, persistent, and bioaccumulative, and its ecotoxicity has been demonstrated. Much research has been conducted to study the presence and mechanisms by which it contaminates the environment (Skutlarek et al. 2006). It is known that given the limited removal efficiency of organic chemicals of WWTP, significant pollution exists in receiving surface waters and soils when effluents are used in agriculture for irrigation purposes (Martínez-Bueno et al. 2012). Consequently, the occurrence of these pollutants may lead to toxicological effects in the environment, especially when they appear as a mixture of compounds, which is how they generally occur, and this situation may lead to a combined effect (Schnell et al. 2009). The objective of the present work was to assess not only the toxicological effects of ibuprofen and PFOA on PSII of Sorghum bicolor but also the ecological risk that both contaminants exert in terrestrial environments, when they act individually and in combination. The evaluation of the negative effect of both pollutants on the selected plant was done measuring a physiological response such as the changes in chlorophyll fluorescence.
Materials and methods Chemicals Ibuprofen sodium salt (C13H17NaO2, CAS no. 31121-93-4, 98 %) and PFOA (C8HF15O2, CAS no. 335-67-1, 99.2 %) were purchased from Sigma-Aldrich (Spain). Soil sample The surface soil samples (0–20 cm) were collected at Carrión de los Céspedes, Seville, Spain. The soil was air-dried and passed through a 2-mm sieve before conducting the experiments. Particle size distribution was analyzed following the Bouyoucos method. Soil pH and electrical conductivity (EC) were measured in a soil-water suspension (1:2.5 and 1:5 soilwater ratio, respectively). It was moderately alkaline with a low EC and obtained the values of 8.11 and 0.21, respectively. The percentage of calcium carbonate (CaCO3) equivalent, measured in a Bernard calcimeter, was 0.17. The organic
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matter value (OM), determined by the potassium dichromatesulphuric acid method, was 2.26 %. Texture was evaluated according to the Bouyoucos method, which was loamy soil with a clay content of 20 %. Toxicity bioassay Sorghum bicolor seeds were purchased from Microbiotest (Belgium). S. bicolor is included in the list of the OECD guideline for the testing of chemicals in terrestrial plants (OECD 2003). It was selected due to the uniformity of the seeds, since they are available from standard sources; the uniformity of the seedling growth; and the amenability to testing in the laboratory. Three seeds were placed in glass pots with 200 g of soil. One pot was used for each pollutant concentration. They were irrigated with 70 ml of deionized water up to the holding capacity of the soil and were kept in the darkness at 25 °C until germination. One pot with three control plants was also included, consisting leaves of the plants grown in soil without contaminants. After the second true leaf of each plant had grown (about 15 days after germination), the pots were placed in a light room at 25 °C and irrigated with 60 ml of the contaminant. The stock solutions of ibuprofen and PFOA were prepared in phosphate buffer solution, pH 7, by preparing serial dilutions of each compound individually and with a fixed constant ratio (1:1) based on their individual EC50 values, up to four concentrations for each combination (two individual compounds and the binary mixture) and using a dilution factor of 2 for the ibuprofen and PFOA mixture. The chlorophyll a fluorescence was measured daily in the morning, during 5 days for all leaves, after 10 min of dark adaptation period. Chlorophyll fluorescence parameters The fluorescence parameters were calculated by a portable modulated fluorimeter, FMS-2 (Hansatech Instruments Ltd., UK) based on dark-adapted and light-adapted fluorescence measurements, obtaining the fluorescence induction curves, or Kautsky’s curves. The determined parameters were F0, which corresponds to the minimal fluorescence with a pulse of modulated light, and Fm, the maximal fluorescence after a saturation pulse. The Fv/Fm ratio was also obtained, which is the maximal quantum efficiency of PSII. Here, Fv is the difference between Fm and F0. In addition, Fs (steady-state fluorescence yield) was measured when the stable state of photosynthesis is reached (applying actinic light). Furthermore, we determine some parameters after a second saturation pulse when the plant is light adapted, and they were as follows: F′0 (light-adapted minimum fluorescence), F′m (light-adapted maximum fluorescence), and F′v/F′m (the efficiency of excitation capture by open PSII centers), where F′v is the difference between F′0 and F′m.
Using the fluorescence parameters described above, and according to the Eqs. 1 to 4, we calculated the following: the quantum efficiency of PSII (ΦPSII), which measures the proportion of light absorbed by chlorophyll associated with PSII; qP (photochemical quenching coefficient); qNP; and NPQ. These last two are related to the nonphotochemical quenching processes, as was described by Maxwell and Johnson 2000: 0 F m− F s ΦPSII ¼ ð1Þ 0 Fm
0 F − Fs qP ¼ 0m 0 F m− F 0
ð2Þ
0
qNP ¼
F m −F m 0 F m− F 0
NPQ ¼
F m −F m 0 Fm
ð3Þ
0
ð4Þ
Stability of exposure concentration The stability and biodegradability of pollutants under the test conditions were tested according to OECD guideline for testing chemicals (OECD 2008). Briefly, after 4 days of incubation, toxicant concentrations were added to three different soil samples: natural with plants, natural without plants, and autoclaved without plants. Each assay condition was simultaneously replicated three times. The soil sorption of each contaminant was estimated by mass balance, taking into account the concentration added to the sterile soil and the concentrations measured in the extract prepared after the incubation period. Biodegradation was also estimated by the difference between the concentrations of chemicals measured in the extract of the sterile and nonsterile soil samples. Finally, the concentrations assimilated by plants were estimated by the difference between the concentration recovered from sterile soil and the concentration measured in the extract of soil incubated with plants. The soil extraction was carried out using methanol in 2:5 proportions (soil to methanol). The extraction procedure was overnight shaking and 1 h of sonication. Ibuprofen was analyzed by high-performance liquid chromatography (HPLC)-UV (1200 Series, Agilent Technologies), equipped with a Phenomenex C-18 column (15×4.60 mm, 5 μm). Elution was done using 2 ml min−1 of
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37:63 acetonitrile/water at pH 2.5 adjusted with orthophosphoric acid. The chromatographic separation took place at 22 min. PFOA was measured using the HPLC quadrupole time-of-flight mass spectrometry equipment, with a Phenomenox C-18 column (Gemini 3 μm, 110 Å). Here elution was done using 0.4 ml min−1 of a mixture containing 80:20 of acetonitrile/water (with 0.1 % formic acid). Chromatographic separation took place at 14 min.
whereas the independent action model assumes a dissimilar mode of action for the components:
ECmix ¼
n X pi EC xi i
!−1
where pi is the molar fraction of each component, ECmix is the effect concentration of the mixture which provokes x% effect, and ECxi is the concentration of component i:
Calculation of dose-response parameters
n
E ðcmix Þ ¼ 1− ∏ ð1−Eðci ÞÞ The response of S. bicolor to toxic exposure was assessed for each contaminant individually and as a mixture, using to the median-effect Eq. 5 (Chou and Talalay 1984), which is based on the mass action law: fa ¼ 1−f a
D EC50
m ð5Þ
where D is the toxicant concentration, fa is the fraction of the exposed population affected by a certain dose D, EC50 is the concentration for 50 % effect through the selected end point of the organism, and m is the coefficient of the sigmoidicity of the dose-response curve. The combination index (CI) was also determined for all the effect levels in accordance with the general combination index Eq. 6 (Chou 2006), as reported in González-Naranjo and Boltes (2013): 7 6 7 6 7 6 6 ½D 7 j 7 6 ðDx Þ1−n 6 X 7 5 4 n ½ D n n h i X X 1 n Dj ðCIÞ ¼ =ðDx Þ j ¼ ð6Þ h ð f Þ i m1 j ax j j¼1 j¼1 ðD Þ m j 1−ð f Þ ax j
where n(CI)x represents the combination index for n chemicals at x% effect, (Dx)1−n is the sum of the dose of n chemicals that exerts x% inhibition in the combination, [Dj]/∑n1[D] is the proportion of the dose of each chemical that exerts x % inhibition in the combination, and (Dm)j{(fax)j/[1 −(fax)j]}1/mj is the dose of each individual compound that exerts x% inhibition. The CompuSyn software was run to calculate EC50, m, CI, and also EC10, EC20, and EC90 (Chou and Martin 2005). We also apply the two most widely used equations to predict the toxicity of mixtures: the concentration addition (CA) (Eq. 7) and the independent action (IA) (Eq. 8), as they were recognized by Faust et al. 2001 and Altenburger et al. 2004. The concentration addition model is based on the assumption of a similar mode of actions for the components,
ð7Þ
ð8Þ
i¼1
where cmix is the total concentration, E(cmix) is the total effect of the mixture, and E(ci) is the effect of each component with concentration ci. Hazard quotient assessment The hazard quotient (HQ) was used to estimate the actual potential ecological risk of the pollutants, either individually or combined (Eq. 9). This is the ratio between measured environmental concentration (MEC) and predicted no-effect concentration (PNEC): HQ ¼
MEC PNEC
ð9Þ
MEC values were obtained from the literature for individual contaminants. For the mixture, the calculations were made from the sum of the maximum concentrations detected in soil or sediment. The PNEC values were derived by dividing the EC50 values obtained in this study by 1,000 (Sanderson et al. 2003; EMEA 2006; Von der Ohe et al. 2011), a conservative and protective factor recommended to consider the toxicity to other terrestrial organisms more sensitive than used.
Results and discussion Table 1 shows the final concentrations of ibuprofen and PFOA measured in extracts prepared with soils contaminated with 600 and 300 mg kg−1 of each pollutant, respectively. Here we present the concentrations found in soil samples incubated under different conditions (with plant, soil without plant, and sterile soil). These values were used for the calculation of the recovery percentages, in order to estimate the relevance of natural attenuation processes, which could modify the concentration of exposition. The results for sterile soil were 92.75 and 98.11 % recovery for ibuprofen and PFOA, respectively. For the nonsterile soil,
Environ Sci Pollut Res Table 1 Ibuprofen and PFOA concentrations in soil after incubation under three different conditions
Soil with plant Soil without plant Sterile soil
Ibuprofen (mg kg−1)
PFOA (mg kg−1)
490.30±6.24 499.99±5.53 556.50±4.61
226.68±4.06 252.67±7.01 294.34±5.97
Initial concentration added to soil: ibuprofen 600 mg kg−1 and PFOA 300 mg kg−1 (±standard deviation for three replicates)
83.33 and 84.22 % were obtained for ibuprofen and PFOA, respectively. In the same way, 81.72 and 75.56 % of ibuprofen and PFOA, respectively, were recovered from soil with plants. According to these values, both contaminants have high affinity by soil matrix but the sorption was almost completely reversible under inert conditions. For the incubation using nonsterile soil, the biodegradation by soil microflora could be responsible for a slight decrease in the recovery of both chemicals. Similarly, in presence of plant, it was the recovery lower levels of both pollutants that could indicate likewise the slight adsorption of these compounds by the plant. In this way, PFOA shows a lower soil sorption and biodegradability than ibuprofen, but high retention in plant, as it was deduced by the concentration measured in extracts prepared from assays including the presence of plants. However, considering all the possible processes (sorption and biodegradation), we obtain a maximum variation in pollutant concentration of 11 % for ibuprofen and 22 % for PFOA in extracts, so the exposure concentrations for S. bicolor can be considered stable under our experimental conditions. In addition, these change in pollutants recovered was due to the presence of the plant.
Effect of ibuprofen and PFOA on the chlorophyll fluorescence parameters in S. bicolor seedlings Kautsky’s kinetics of the S. bicolor leaves obtained after the pollutant applications are presented in Supplementary Fig. 1. No considerable effects were observed for any of the direct parameters, which agree with similar studies carried out with different toxicants (Cambrollé et al. 2013; Qiu et al. 2013). Millaleo et al. (2012) found that excess Mn causes minimal changes in the Fv/Fm ratio, corresponding to the maximal quantum efficiency of PSII, because no significant change in the relative abundance of PSII-associated polypeptides was observed. In contrast, the plants grown under excess Mn exhibited increased susceptibility to PSII photoinhibition. In addition, the in vivo measurements of the redox transients of the PSI reaction center (P700) considerably decreased P700 photooxidation gradually (P700+) at increasing Mn concentrations compared to the control. This was accompanied by a
slower P700+ re-reduction rate, indicating the downregulation of the PSI-dependent cyclic electron flow. However, the most representative ratios linked to the photochemistry of photosynthesis in this experiment are ΦPSII and qP. The values of these parameters showed very marked tendencies related to the concentrations of pollutants. Figure 1 depicts how both parameters decrease with the increment pollutants concentrations, showing concentration dependence profiles. In addition, the values of ΦPSII and qP for controls (without pollutants added), as well as their variation ranges in the presence of contaminants, are very similar to those measured by other authors, using different photosynthetic organisms (Wu et al. 2012; Qiu et al. 2013; Zezulka et al. 2013). The relationship was almost linear when toxicants act individually (Fig. 1a, b, d, e). This is more evident for ibuprofen (Fig. 1a, d), where values of qP present higher reduction than ΦPSII for the same range of concentrations assayed. However, plant sensibility was higher for PFOA than for ibuprofen. Interestingly, these results are in accordance to the recovery values for pollutants discussed above. In this sense, we found that ibuprofen is best recovered than PFOA from soil incubated with plants (81.72 vs 75.56 %, respectively). This could demonstrate that the industrial contaminant is more available for plants than the pharmaceutical product in our experimental conditions. Similar results were found for other organic contaminants, such as herbicides metolachlor and isoproturon, which caused ΦPSII to lower in photosynthetic aquatic organisms. For metolachlor, a 7 % inhibition was achieved due to exposure at concentrations of 5 mg l−1, while for isoproturon, a total inhibition was accomplished by exposure at the 20 mg l−1 concentration (Laviale et al. 2011; Thakkar et al. 2013). In terrestrial plants, the quantum efficiency of PSII has also been observed to diminish when bisphenol A was applied to soya bean seedlings (Qiu et al. 2013) or when atrazine was applied to Spathiphyllum wallisi (Iriel et al. 2014). The reaction for the mixture was similar, although the tendency in this case was milder as the effect of the reduction in both parameters for higher concentrations was not so marked. Therefore, the curves describing these inhibitions profile are better described by an exponential equation than by a linear equation. Finally, unlike the individual toxicant effects, ΦPSII proved more sensitive than qP. Regarding to the mode of toxic action of pollutants studied in this work and the changes in chlorophyll fluorescence parameters measured, we found previous works which try to explain the mechanisms that causes stress in plants. In this sense, Dordio et al. 2011 reported that ibuprofen can modify the oxidative status of plant cells by enhancing the production of reactive oxygen species (ROS). In this context, the measurements of membrane lipid peroxidation and antioxidative enzyme activity gave different results, depending on
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d)
PSII
a)
e)
PSII
b)
f)
PSII
c)
Fig. 1 Mean values of ΦPSII as a function of ibuprofen concentrations (a), PFOA concentrations (b), ibuprofen + PFOA concentrations (c), mean values of qP as a function of ibuprofen concentrations (d), PFOA
concentrations (e), and ibuprofen+PFOA concentrations (f). Error bars are standard deviations of triplicate cultures
the plant species and ibuprofen concentration (Shan and Liang 2010; Dordio et al. 2011). More recently, Iori et al. 2013 use the chlorophyll fluorescence tools to evaluate the effect of ibuprofen in two clones of Salix alba L., under hydroponic conditions. These authors found that the pharmaceutical compound affected in a different way to each clone, and they recognized the existence of several mechanisms involved in the changes of the photosynthetic activity and the antioxidative defense developed by plants. They related the decrease in the maximum quantum efficiency of PSII, with damage to the PSII centers. In our experiments, in a similar way that has been observed by Iori et al. 2013, we obtained a clear decrease in quantum efficiency of PSII (ΦPSII) and in photochemical quenching (qP), which indicates an overexcitation of the PSII system. In this way, the presence of ibuprofen
probably produces a stress action and an impartment of protective mechanism to ROS generation, which damage the PSII components as was indicated by Krause and Weis 1991. For PFOA, it was pointed out that this chemical is likely to be incorporated into the lipid bilayer of the cell membrane, increasing its permeability and causing toxic effects on green algae (Liu et al. 2008). But for plants, there are only a few studies focused on the uptake of this toxicant by different species. In this sense, Stahl et al. 2009 evaluated the growth of crop plants exposed to perfluorinated compounds, including PFOA. They suggested that the toxic effect of pollutants to plants was dependent on plant species. More recently, Wen et al. 2013 found that the transport of PFOA into maize roots was likely an energy-dependent process, but until now neither
IBU ibuprofen, PFOA perfluorooctanoic acid, CI combination index
Toxicity of individual pollutants expressed as EC10, EC20, EC50, and EC90 to S. bicolor (values in mg kg−1 ) with their 95 % confidence intervals. For mixtures, dose-effect parameters and mean combination index (CI) indicating 95 % confidence intervals. EC10, EC20, EC50,, and EC90 are the doses that inhibited growth by 10, 20, 50, and 90 %, respectively. CI1 indicate synergism, additive effect, and antagonism, respectively. Synergistic responses have been stressed in italics.
0.954 0.983 284.27±0.88 1,413.91±0.97 1.44±0.31 69.50±0.12 166.92±0.52 0.73±0.02 28.57±0.96 43.36±0.33 0.47±0.99 16.99±0.18 19.71±1.05 0.37±0.14 0.972 0.994 336.04±1.03 1,451.79±2.01 1.98±0.26 65.96±0.70 137.02±0.99 0.75±0.08 12.95±0.15 12.93±1.01 0.29±0.06 PFOA Mixtures (IBU+PFOA) CI values
23.61±0.11 30.90±0.22 0.41±0.03
1,909.62±1.01 420.86±0.87 162.08±1.40 92.75±0.73 0.993 956.96±3.01 282.15±1.10
EC90 (mg kg−1) EC50 (mg kg−1) EC20 (mg kg−1)
130.56±1.27 83.19±0.89
EC20 (mg kg−1) EC10 (mg kg−1) EC10 (mg kg−1)
r
qP ΦPSII
Dose-effect relationship parameters of individual compounds and binary mixtures for S. bicolor toxicity tests Table 2
The dose-effect parameters, EC10, EC20, EC50, and EC90 (mg kg−1), on S. bicolor for ibuprofen and PFOA are shown in Table 2. The values were determined using a 95 % confidence interval and the linear interpolation method independent of any particular dose-effect model (USEPA 2002). The linear correlation was good for the median-effect plots because all the r values were over 0.95. The EC50 calculated for both compounds showed that ibuprofen is not harmful for the plant, with values above 100 mg kg−1, in accordance with Regulation (EC) No. 1272/2008, unlike PFOA, which obtained values below 100 mg kg−1 for the quantum efficiency of PSII and photochemical quenching coefficient. ΦPSII appeared to be more sensitive than qP by the pharmaceutical product, although the industrial pollutant presented similar inhibition constant for both parameters and also low toxic concentrations. As other authors have demonstrated, ΦPSII is the parameter that gave a faster response to the presence of pollutants (Ralph et al. 2007; Buonasera et al. 2011). In our previous study, where we used the same plant to analyze root elongation inhibition, ibuprofen also caused less inhibition than PFOA (GonzálezNaranjo and Boltes 2013). For the low and high percentages of the affected population, calculated as EC10 and EC20 for the first case and as EC90 for the second one, ibuprofen proved less toxic than PFOA. As the affected population increased, the difference between toxicities for both compounds lowered for ΦPSII and increased for qP. For the binary combination, although the presence of PFOA considerably increased the toxicity of ibuprofen, neither ΦPSII nor qP obtained values lower than 100 mg kg−1. Thus, it was not toxic, as occurred with the root elongation inhibition measurements, although was sensibility poorer (González-Naranjo and Boltes 2013). Figure 2 presents the CI values in relation to the percentage of affected population. Evolution was similar for the two endpoints studied. Regarding ΦPSII, the binary mixture shows a synergistic behavior in almost the entire range of concentrations assayed, and its became slightly antagonistic at fa =0.9. The toxicological profile for qP also displayed the synergistic behavior until fa =0.7, when this close to additive effect began, which changed to antagonism at fa =0.8. Our previous work reports similar results but with a smaller range of concentrations with synergistic behavior and a wider-ranging section with antagonism, which was even harder. Once again, we demonstrated more sensibility for chlorophyll a fluorescence parameters than for root elongation to evaluate toxicity in terrestrial organisms (González-Naranjo and Boltes 2013).
EC50 (mg kg−1)
Ibuprofen and PFOA toxicity for PSII
IBU
EC90 (mg kg−1)
r
data was published about the effect of perfluorinated chemicals on the photochemistry of photosynthesis in plants, so a discussion of our results compared with those of other authors is therefore not possible.
0.962
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a)
b)
5 4.5
4.5
4
4
Combination index (CI)
Combination index (CI)
5
3.5
3 2.5 2 1.5
3.5 3 2.5
2 1.5
1
1
0.5
0.5
0
0
0
0.2
0.4
0.6
0.8
1
Fraction affected (fa)
0
0.2
0.4
0.6
0.8
1
Fraction affected (fa)
Fig. 2 Combination index plot for mixtures of ibuprofen and PFOA on S. bicolor, obtained from qP (a) and ΦPSII (b). The line at CI=1 represents additivity. CI combination index value, fa population fraction inhibited.
Error bars indicate 95 % confidence intervals for CI values based on sequential deletion analysis (SDA) (Chou and Martin 2005)
The difference between the effects of both contaminants related readily to the organic carbon distribution coefficients, KOC, as explained in the work of Katayama et al. (2010). For the most toxic substance, PFOA, this parameter obtained values of around 115 l kg−1 (Higgins and Luthy 2006), while for ibuprofen, values were over 200 l kg−1 (González-Naranjo et al. 2013). This demonstrates that when KOC increases, the toxicity trend decreases because reduced compound mobility is assumed. Although no experimental data on EC50 were found in the literature for toxicological effects on PSII for high plants due to the presence of organic chemicals, some studies have studied how different herbicides affect other photosynthetic organisms, such as aquatic plants or microalgae. Kumar and Han (2011) determined the toxicity of atrazine, diuron, hexazinone, and simazine both individually and for the binary combination to Lemna sp., by quantifying the inhibition of the PSII maximum efficiency (Fv/Fm). As expected, the four herbicides produced much more damage than ibuprofen and PFOA if the target of the products was taken into account. Synergy was the predominant behavior in combinations, and antagonism occurred in all cases when herbicides were added at high concentrations, similarly to the sum of both pollutants in our experimental data. Meanwhile, Magnusson et al. (2010) investigated the affect on different microalgae. They noted that Cylindrotheca closterium was the most sensitive organism to the compounds used (diuron, tebuthiuron, atrazine, simazine, hexazinone, and desethyl-atrazine). The inhibition of PSII quantum efficiency was estimated for not only individual compounds but also for the binary combinations, which were estimated by assuming an additive behavior by applying the TU (toxic units) method that resulted in good prediction, unlike our results for the mixture. Simazine presented similar toxicity to ibuprofen, with an EC50 of 242 mg l−1. Tebuthiuron and atrazine, with 76.9 and 76.7 mg l−1 of EC50, respectively, showed toxicities which came close to the toxicity of PFOA.
Attending to the toxicity mechanisms reported in bibliography and discussed in “Effect of ibuprofen and PFOA on the chlorophyll fluorescence parameters in S. bicolor seedlings” section, the most probable explanation to the synergistic effect observed could be due to nonspecific interaction of PFOA with cell membranes, disturbing their structures and enhancing the ibuprofen uptake by plant, which finally produce an overexcitation of PSII system and a lost of photosynthetic capability of plants. Risk quotients assessment of the binary mixture The HQs were derived from dividing the MEC obtained from the literature for soil and river sediments (Supplementary Table 1) by the experimentally calculated PNEC (Sanderson et al. 2003; EMEA 2006; Von der Ohe et al. 2011). The values of these calculated ratios mean the following: HQ10 a high risk is probable (EMEA 2006). Three different equations were used to determine PNEC: the concentration addition, independent action, and combination index. Supplementary Table 2 presents the MEC, PNEC, and the HQ for individual pollutants and the binary combination of pollutants. Figure 3 shows the HQs for the pollutants as individuals and for the binary combinations in the two terrestrial environments studied. For PFOA, whose HQs were always higher than for ibuprofen, a moderate risk was estimated for soil and sediments in relation to both endpoints, ΦPSII (HQ=4.851 and 3.077) and qP (HQ=5.605 and 2.921), which were respectively higher for soil and lower for sediments since the expected likelihood of the pollutant occurring was higher in soils than in sediments. For ibuprofen, no risk was expected, except for soil when considering ΦPSII and at a moderate level (HQ=1.129).
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Fig. 3 HQ profiles determined from EC50 values for qP (a) and ΦPSII (b) inhibition on S. bicolor of ibuprofen and PFOA as individual compounds and HQ profiles for ΦPSII (c) and qP (d) inhibition on S. bicolor calculated by CI, CA, and IA methods in terrestrial environments
In the literature, no ecological risks data in terrestrial environments were found, except for one study done on ibuprofen by Martín et al. (2012). These authors assessed the risk in amended soil with wastewater treatment plant sludge, and they estimated PNEC from aquatic toxicological data and the solid-water partition coefficient (Kd). The quotient was 0.03, so no risk was detected. A difference was found between the two parameters for the mixtures, and the highest HQ was obtained for ΦPSII in soils and sediments. Of the three methods applied to estimate PNEC for the mixtures, CI offered the highest HQs, followed by CA, and finally by IA with the lowest values. When comparing root elongation (González-Naranjo and Boltes 2013), chlorophyll fluorescence was more sensitive to the risk assessment study in terrestrial environments when using terrestrial high plants. The importance of the interactions between the components of a mixture, where a different mode of action is expected, is highlighted herein in accordance with the experimental results. Consequently, ecological risks may be overestimated or underestimated if the CA or IA methods are used to calculate the mixtures’ toxicity, although they are the most widely applied ones for this purpose. Similar conclusions have been drawn in other works which also compared ecological risk assessment methods in aquatic environmental compartments. For example, in their study on the toxicity of different mixtures of phenylureas for algal communities where
the CA and IA were compared, Arrhenius et al. (2004) observed that CA was a good method for calculating EC50, although it could be overestimated. González-Pleiter et al. (2013) also compared the CI method with CA and IA in their study about toxicity of antibiotic mixtures to two aquatic organisms, microalgae, and cyanobacteria. Like us, they saw that CI indicates that synergistic behavior is the most obtained profile for toxicity in their combinations. Finally, in relation to the environmental matrices used for the HQ calculations, soil is seen to be more susceptible than river sediments to contamination for PFOA and ibuprofen given the occurrence of both pollutants in these terrestrial environments.
Conclusions The inhibition of the fluorescence parameters ΦPSII and qP is directly related to the exposure concentration of ibuprofen and PFOA for S. bicolor, with less sensibility found for the pharmaceutical compound, which was less available for the plant than the industrial compound. Therefore, they can be useful tools for quantifying toxicity in terrestrial environments. Besides when compared to other endpoints in plants, such as root elongation, they proved more sensitive. Consequently, this technique permits to evaluate the harmfulness on a more
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advanced state of development of the plant, not only in the germination state. The binary combination of both compounds shows predominant synergistic behavior. Hence, we conclude that for terrestrial photosynthetic organisms, interactions among pollutants play a key role and, consequently, classical methods for determining ecological risk, concentration addition, and independent action may imply underestimating these risks in terrestrial environments if caused by such mixtures. Acknowledgments This research was funded by the next research projects: CSD2006-00044, MICINN-CGL2009-13168-C03-01, CGL2012-39520-C03-01, and P2009/AMB-1588.
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RESEARCH ARTICLE
Environmental risk of combined emerging pollutants in terrestrial environments: chlorophyll a fluorescence analysis Víctor González-Naranjo & Karina Boltes & Irene de Bustamante & Pino Palacios-Diaz
Received: 17 September 2014 / Accepted: 20 November 2014 # Springer-Verlag Berlin Heidelberg 2014
Abstract The risk assessment in terrestrial environments has been scarcely studied for mixtures of organic contaminants. To estimate toxicity due to these compounds, an ecotoxicological test may be done with the appropriate organism and biomarker. Photosynthesis is principally performed at photosystem II, and its efficiency is affected by any environmental stress. Consequently, the measure of this efficiency may be a good indicator of toxicity if different parameters are employed, e.g., the quantum efficiency of photosystem II and the photochemical quenching coefficient. We did a series of assays to determine the toxicity of two organic contaminants, ibuprofen and perfluorooctanoic acid, using a higher plant (Sorghum bicolor). The results showed more toxicity for the perfluorinated compound and greater sensibility for the quantum efficiency of photosystem II. Regarding the binary combination, three methods were applied to calculate EC50: combination index, concentration addition, and independent Responsible editor: Leif Kronberg Electronic supplementary material The online version of this article (doi:10.1007/s11356-014-3899-z) contains supplementary material, which is available to authorized users. V. González-Naranjo : K. Boltes Department of Chemical Engineering, University of Alcalá, 28771 Alcalá de Henares, Madrid, Spain V. González-Naranjo (*) : K. Boltes : I. de Bustamante Advanced Study Institute of Madrid, IMDEA-Agua, Parque Científico Tecnológico, 28805 Alcalá de Henares, Madrid, Spain e-mail: [email protected] I. de Bustamante Department of Geology, University of Alcalá, 28771 Alcalá de Henares, Madrid, Spain P. Palacios-Diaz Department of Animal Pathology, Animal Production, Food Science and Food Technology, Universidad de Las Palmas de Gran Canaria, 35001 Las Palmas de Gran Canaria, Spain
action. Synergistic behavior is the principal toxicological profile for this mix. Therefore, the combination index, which considers interactions among chemicals, gave the best estimation to determine risk indices. We conclude that the inhibition of photosynthesis efficiency can be a useful tool to determine the toxicity of the mixtures of organic pollutants and to estimate ecological risks in terrestrial environments. Keywords Combination index . Hazard quotient . Organic compounds . Photosynthesis . Phytotoxicity . Quantum efficiency of PSII
Introduction The environmental risk due to the presence of mixtures of organic micropollutants has been scarcely studied, especially in terrestrial environments. Some works have focused on risk analyses in aquatic environments (Vázquez-Roig et al. 2011; Stasinakis et al. 2012), but very few research works have assessed the risk of these contaminants occurring in soils (Martín et al. 2012; González-Naranjo et al. 2013). This environmental risk is studied from the toxicity of the compounds analyzed, which has been extensively determined for the effect exerted when they act individually. In the environment, however, these pollutants appear like mixtures, and the ecotoxicity effects of mixtures may differ from those obtained for individual compounds (Rodea-Palomares et al. 2010). Unfortunately, toxicity values strongly depend on the conceptual model chosen to assess the mixture. Furthermore, an organism representative of soil and some specific signal of stress have to be selected to determine the toxicity effect of organic pollutants in this environmental compartment. Photosynthesis is an important process in plants, the primary producers in the Earth’s ecosystem, which is based on
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their growth and development. Chlorophyll fluorescence emitted by higher plants can reflect photosynthetic activities in a complex manner (Hussain and Reigosa 2011). The fluorescence emission of chlorophyll is a fast, cheap, powerful, noninvasive, and reliable tool to determine photosynthetic activity due to stress in plants (Zarco-Tejada et al. 2009). A stress situation for a plant is defined as an external factor that exerts an undesirable influence on it, which causes different responses at all physiological levels. By altering the photosynthetic electron transfer, plants can cope with this stress (Ibáñez et al. 2010). Dark-adapted oxygenic photosynthetic organisms show a change in PSII photochemistry, which is based on the theory of energy flux in biomembranes when they are illuminated with high-intensity actinic light (Strasser 1978). Advances in fluorescence spectroscopy and reflectance-derived fluorescence may be put to good use in toxicity testing by bioassays, which enable the detection of stress in plants, especially before the changes in chlorophyll content become visible. The quantum yield of photosystem II (ΦII) is the most widely used fluorescence parameter as it responds rapidly to exposure to toxins (Ralph et al. 2007; Buonasera et al. 2011; Iriel et al. 2014). Many studies have assessed the effect of different stress situations by applying this method on photosynthetic organisms, such as high plants, algae, and lichens. Environmental stress conditions, such as temperature, salinity, or water stress, have been extensively studied (Faraloni et al. 2011; Oukarroum et al. 2012). Different metals have also been analyzed, e.g., copper, cadmium, silver, or chromium (Redondo-Gómez et al. 2010, 2011; Xu et al. 2010, 2012; Vantová et al. 2013), and several authors have investigated inhibition of PSII caused by ozone (Riddell et al. 2012). Nevertheless, there are very few research works available that have studied the effect of organic compounds, such as metolachlor, benz(a)anthracene and fluoranthene in phytoplankton (Othman et al. 2012; Thakkar et al. 2013), various herbicides commonly used in agriculture in green algae (Magnusson et al. 2010; Kumar and Han 2011; Bi et al. 2012), bisphenol A in soya bean seedlings (Qiu et al. 2013), cytokinin in aubergine seedlings (Wu et al. 2012), or TNT in two high plants (Naumann et al. 2010). Yet no studies have used PSII inhibition to study the toxicity of organic micropollutants, such as pharmaceuticals or industrial chemicals. Some works have studied their toxicity to photosynthetic organisms, like algae and aquatic plants (Rosal et al. 2010; Xu et al. 2013) or high plants (Zhao et al. 2011; Furtula et al. 2012; González-Naranjo and Boltes 2013). Emerging pollutants are found extensively in environmental samples of water and soil, such as pharmaceuticals or industrial chemicals. Among pharmaceuticals, ibuprofen, a nonsteroidal anti-inflammatory drug, is frequently present given its mass consumption worldwide (Gottschall et al. 2012; Duan et al. 2013; Aznar et al. 2013). In soil, this drug
has been found in concentrations up to 318.50 ng g−1 (Karnjanapiboonwong et al. 2011). When focusing on both toxicological data and environmental concentrations, chronic toxic effects cannot be excluded (Grung et al. 2008). Perfluorooctanoic acid (PFOA), a final decomposition product of fluorinated alkyl compounds of widespread application in industrial processes, has also been found in aquatic and terrestrial environments (Meng et al. 2013; Perkola and Sainio 2013; Pico et al. 2012), reaching concentrations of 47.50 ng g−1 in soil (Li et al. 2010). It is widespread, persistent, and bioaccumulative, and its ecotoxicity has been demonstrated. Much research has been conducted to study the presence and mechanisms by which it contaminates the environment (Skutlarek et al. 2006). It is known that given the limited removal efficiency of organic chemicals of WWTP, significant pollution exists in receiving surface waters and soils when effluents are used in agriculture for irrigation purposes (Martínez-Bueno et al. 2012). Consequently, the occurrence of these pollutants may lead to toxicological effects in the environment, especially when they appear as a mixture of compounds, which is how they generally occur, and this situation may lead to a combined effect (Schnell et al. 2009). The objective of the present work was to assess not only the toxicological effects of ibuprofen and PFOA on PSII of Sorghum bicolor but also the ecological risk that both contaminants exert in terrestrial environments, when they act individually and in combination. The evaluation of the negative effect of both pollutants on the selected plant was done measuring a physiological response such as the changes in chlorophyll fluorescence.
Materials and methods Chemicals Ibuprofen sodium salt (C13H17NaO2, CAS no. 31121-93-4, 98 %) and PFOA (C8HF15O2, CAS no. 335-67-1, 99.2 %) were purchased from Sigma-Aldrich (Spain). Soil sample The surface soil samples (0–20 cm) were collected at Carrión de los Céspedes, Seville, Spain. The soil was air-dried and passed through a 2-mm sieve before conducting the experiments. Particle size distribution was analyzed following the Bouyoucos method. Soil pH and electrical conductivity (EC) were measured in a soil-water suspension (1:2.5 and 1:5 soilwater ratio, respectively). It was moderately alkaline with a low EC and obtained the values of 8.11 and 0.21, respectively. The percentage of calcium carbonate (CaCO3) equivalent, measured in a Bernard calcimeter, was 0.17. The organic
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matter value (OM), determined by the potassium dichromatesulphuric acid method, was 2.26 %. Texture was evaluated according to the Bouyoucos method, which was loamy soil with a clay content of 20 %. Toxicity bioassay Sorghum bicolor seeds were purchased from Microbiotest (Belgium). S. bicolor is included in the list of the OECD guideline for the testing of chemicals in terrestrial plants (OECD 2003). It was selected due to the uniformity of the seeds, since they are available from standard sources; the uniformity of the seedling growth; and the amenability to testing in the laboratory. Three seeds were placed in glass pots with 200 g of soil. One pot was used for each pollutant concentration. They were irrigated with 70 ml of deionized water up to the holding capacity of the soil and were kept in the darkness at 25 °C until germination. One pot with three control plants was also included, consisting leaves of the plants grown in soil without contaminants. After the second true leaf of each plant had grown (about 15 days after germination), the pots were placed in a light room at 25 °C and irrigated with 60 ml of the contaminant. The stock solutions of ibuprofen and PFOA were prepared in phosphate buffer solution, pH 7, by preparing serial dilutions of each compound individually and with a fixed constant ratio (1:1) based on their individual EC50 values, up to four concentrations for each combination (two individual compounds and the binary mixture) and using a dilution factor of 2 for the ibuprofen and PFOA mixture. The chlorophyll a fluorescence was measured daily in the morning, during 5 days for all leaves, after 10 min of dark adaptation period. Chlorophyll fluorescence parameters The fluorescence parameters were calculated by a portable modulated fluorimeter, FMS-2 (Hansatech Instruments Ltd., UK) based on dark-adapted and light-adapted fluorescence measurements, obtaining the fluorescence induction curves, or Kautsky’s curves. The determined parameters were F0, which corresponds to the minimal fluorescence with a pulse of modulated light, and Fm, the maximal fluorescence after a saturation pulse. The Fv/Fm ratio was also obtained, which is the maximal quantum efficiency of PSII. Here, Fv is the difference between Fm and F0. In addition, Fs (steady-state fluorescence yield) was measured when the stable state of photosynthesis is reached (applying actinic light). Furthermore, we determine some parameters after a second saturation pulse when the plant is light adapted, and they were as follows: F′0 (light-adapted minimum fluorescence), F′m (light-adapted maximum fluorescence), and F′v/F′m (the efficiency of excitation capture by open PSII centers), where F′v is the difference between F′0 and F′m.
Using the fluorescence parameters described above, and according to the Eqs. 1 to 4, we calculated the following: the quantum efficiency of PSII (ΦPSII), which measures the proportion of light absorbed by chlorophyll associated with PSII; qP (photochemical quenching coefficient); qNP; and NPQ. These last two are related to the nonphotochemical quenching processes, as was described by Maxwell and Johnson 2000: 0 F m− F s ΦPSII ¼ ð1Þ 0 Fm
0 F − Fs qP ¼ 0m 0 F m− F 0
ð2Þ
0
qNP ¼
F m −F m 0 F m− F 0
NPQ ¼
F m −F m 0 Fm
ð3Þ
0
ð4Þ
Stability of exposure concentration The stability and biodegradability of pollutants under the test conditions were tested according to OECD guideline for testing chemicals (OECD 2008). Briefly, after 4 days of incubation, toxicant concentrations were added to three different soil samples: natural with plants, natural without plants, and autoclaved without plants. Each assay condition was simultaneously replicated three times. The soil sorption of each contaminant was estimated by mass balance, taking into account the concentration added to the sterile soil and the concentrations measured in the extract prepared after the incubation period. Biodegradation was also estimated by the difference between the concentrations of chemicals measured in the extract of the sterile and nonsterile soil samples. Finally, the concentrations assimilated by plants were estimated by the difference between the concentration recovered from sterile soil and the concentration measured in the extract of soil incubated with plants. The soil extraction was carried out using methanol in 2:5 proportions (soil to methanol). The extraction procedure was overnight shaking and 1 h of sonication. Ibuprofen was analyzed by high-performance liquid chromatography (HPLC)-UV (1200 Series, Agilent Technologies), equipped with a Phenomenex C-18 column (15×4.60 mm, 5 μm). Elution was done using 2 ml min−1 of
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37:63 acetonitrile/water at pH 2.5 adjusted with orthophosphoric acid. The chromatographic separation took place at 22 min. PFOA was measured using the HPLC quadrupole time-of-flight mass spectrometry equipment, with a Phenomenox C-18 column (Gemini 3 μm, 110 Å). Here elution was done using 0.4 ml min−1 of a mixture containing 80:20 of acetonitrile/water (with 0.1 % formic acid). Chromatographic separation took place at 14 min.
whereas the independent action model assumes a dissimilar mode of action for the components:
ECmix ¼
n X pi EC xi i
!−1
where pi is the molar fraction of each component, ECmix is the effect concentration of the mixture which provokes x% effect, and ECxi is the concentration of component i:
Calculation of dose-response parameters
n
E ðcmix Þ ¼ 1− ∏ ð1−Eðci ÞÞ The response of S. bicolor to toxic exposure was assessed for each contaminant individually and as a mixture, using to the median-effect Eq. 5 (Chou and Talalay 1984), which is based on the mass action law: fa ¼ 1−f a
D EC50
m ð5Þ
where D is the toxicant concentration, fa is the fraction of the exposed population affected by a certain dose D, EC50 is the concentration for 50 % effect through the selected end point of the organism, and m is the coefficient of the sigmoidicity of the dose-response curve. The combination index (CI) was also determined for all the effect levels in accordance with the general combination index Eq. 6 (Chou 2006), as reported in González-Naranjo and Boltes (2013): 7 6 7 6 7 6 6 ½D 7 j 7 6 ðDx Þ1−n 6 X 7 5 4 n ½ D n n h i X X 1 n Dj ðCIÞ ¼ =ðDx Þ j ¼ ð6Þ h ð f Þ i m1 j ax j j¼1 j¼1 ðD Þ m j 1−ð f Þ ax j
where n(CI)x represents the combination index for n chemicals at x% effect, (Dx)1−n is the sum of the dose of n chemicals that exerts x% inhibition in the combination, [Dj]/∑n1[D] is the proportion of the dose of each chemical that exerts x % inhibition in the combination, and (Dm)j{(fax)j/[1 −(fax)j]}1/mj is the dose of each individual compound that exerts x% inhibition. The CompuSyn software was run to calculate EC50, m, CI, and also EC10, EC20, and EC90 (Chou and Martin 2005). We also apply the two most widely used equations to predict the toxicity of mixtures: the concentration addition (CA) (Eq. 7) and the independent action (IA) (Eq. 8), as they were recognized by Faust et al. 2001 and Altenburger et al. 2004. The concentration addition model is based on the assumption of a similar mode of actions for the components,
ð7Þ
ð8Þ
i¼1
where cmix is the total concentration, E(cmix) is the total effect of the mixture, and E(ci) is the effect of each component with concentration ci. Hazard quotient assessment The hazard quotient (HQ) was used to estimate the actual potential ecological risk of the pollutants, either individually or combined (Eq. 9). This is the ratio between measured environmental concentration (MEC) and predicted no-effect concentration (PNEC): HQ ¼
MEC PNEC
ð9Þ
MEC values were obtained from the literature for individual contaminants. For the mixture, the calculations were made from the sum of the maximum concentrations detected in soil or sediment. The PNEC values were derived by dividing the EC50 values obtained in this study by 1,000 (Sanderson et al. 2003; EMEA 2006; Von der Ohe et al. 2011), a conservative and protective factor recommended to consider the toxicity to other terrestrial organisms more sensitive than used.
Results and discussion Table 1 shows the final concentrations of ibuprofen and PFOA measured in extracts prepared with soils contaminated with 600 and 300 mg kg−1 of each pollutant, respectively. Here we present the concentrations found in soil samples incubated under different conditions (with plant, soil without plant, and sterile soil). These values were used for the calculation of the recovery percentages, in order to estimate the relevance of natural attenuation processes, which could modify the concentration of exposition. The results for sterile soil were 92.75 and 98.11 % recovery for ibuprofen and PFOA, respectively. For the nonsterile soil,
Environ Sci Pollut Res Table 1 Ibuprofen and PFOA concentrations in soil after incubation under three different conditions
Soil with plant Soil without plant Sterile soil
Ibuprofen (mg kg−1)
PFOA (mg kg−1)
490.30±6.24 499.99±5.53 556.50±4.61
226.68±4.06 252.67±7.01 294.34±5.97
Initial concentration added to soil: ibuprofen 600 mg kg−1 and PFOA 300 mg kg−1 (±standard deviation for three replicates)
83.33 and 84.22 % were obtained for ibuprofen and PFOA, respectively. In the same way, 81.72 and 75.56 % of ibuprofen and PFOA, respectively, were recovered from soil with plants. According to these values, both contaminants have high affinity by soil matrix but the sorption was almost completely reversible under inert conditions. For the incubation using nonsterile soil, the biodegradation by soil microflora could be responsible for a slight decrease in the recovery of both chemicals. Similarly, in presence of plant, it was the recovery lower levels of both pollutants that could indicate likewise the slight adsorption of these compounds by the plant. In this way, PFOA shows a lower soil sorption and biodegradability than ibuprofen, but high retention in plant, as it was deduced by the concentration measured in extracts prepared from assays including the presence of plants. However, considering all the possible processes (sorption and biodegradation), we obtain a maximum variation in pollutant concentration of 11 % for ibuprofen and 22 % for PFOA in extracts, so the exposure concentrations for S. bicolor can be considered stable under our experimental conditions. In addition, these change in pollutants recovered was due to the presence of the plant.
Effect of ibuprofen and PFOA on the chlorophyll fluorescence parameters in S. bicolor seedlings Kautsky’s kinetics of the S. bicolor leaves obtained after the pollutant applications are presented in Supplementary Fig. 1. No considerable effects were observed for any of the direct parameters, which agree with similar studies carried out with different toxicants (Cambrollé et al. 2013; Qiu et al. 2013). Millaleo et al. (2012) found that excess Mn causes minimal changes in the Fv/Fm ratio, corresponding to the maximal quantum efficiency of PSII, because no significant change in the relative abundance of PSII-associated polypeptides was observed. In contrast, the plants grown under excess Mn exhibited increased susceptibility to PSII photoinhibition. In addition, the in vivo measurements of the redox transients of the PSI reaction center (P700) considerably decreased P700 photooxidation gradually (P700+) at increasing Mn concentrations compared to the control. This was accompanied by a
slower P700+ re-reduction rate, indicating the downregulation of the PSI-dependent cyclic electron flow. However, the most representative ratios linked to the photochemistry of photosynthesis in this experiment are ΦPSII and qP. The values of these parameters showed very marked tendencies related to the concentrations of pollutants. Figure 1 depicts how both parameters decrease with the increment pollutants concentrations, showing concentration dependence profiles. In addition, the values of ΦPSII and qP for controls (without pollutants added), as well as their variation ranges in the presence of contaminants, are very similar to those measured by other authors, using different photosynthetic organisms (Wu et al. 2012; Qiu et al. 2013; Zezulka et al. 2013). The relationship was almost linear when toxicants act individually (Fig. 1a, b, d, e). This is more evident for ibuprofen (Fig. 1a, d), where values of qP present higher reduction than ΦPSII for the same range of concentrations assayed. However, plant sensibility was higher for PFOA than for ibuprofen. Interestingly, these results are in accordance to the recovery values for pollutants discussed above. In this sense, we found that ibuprofen is best recovered than PFOA from soil incubated with plants (81.72 vs 75.56 %, respectively). This could demonstrate that the industrial contaminant is more available for plants than the pharmaceutical product in our experimental conditions. Similar results were found for other organic contaminants, such as herbicides metolachlor and isoproturon, which caused ΦPSII to lower in photosynthetic aquatic organisms. For metolachlor, a 7 % inhibition was achieved due to exposure at concentrations of 5 mg l−1, while for isoproturon, a total inhibition was accomplished by exposure at the 20 mg l−1 concentration (Laviale et al. 2011; Thakkar et al. 2013). In terrestrial plants, the quantum efficiency of PSII has also been observed to diminish when bisphenol A was applied to soya bean seedlings (Qiu et al. 2013) or when atrazine was applied to Spathiphyllum wallisi (Iriel et al. 2014). The reaction for the mixture was similar, although the tendency in this case was milder as the effect of the reduction in both parameters for higher concentrations was not so marked. Therefore, the curves describing these inhibitions profile are better described by an exponential equation than by a linear equation. Finally, unlike the individual toxicant effects, ΦPSII proved more sensitive than qP. Regarding to the mode of toxic action of pollutants studied in this work and the changes in chlorophyll fluorescence parameters measured, we found previous works which try to explain the mechanisms that causes stress in plants. In this sense, Dordio et al. 2011 reported that ibuprofen can modify the oxidative status of plant cells by enhancing the production of reactive oxygen species (ROS). In this context, the measurements of membrane lipid peroxidation and antioxidative enzyme activity gave different results, depending on
Environ Sci Pollut Res
d)
PSII
a)
e)
PSII
b)
f)
PSII
c)
Fig. 1 Mean values of ΦPSII as a function of ibuprofen concentrations (a), PFOA concentrations (b), ibuprofen + PFOA concentrations (c), mean values of qP as a function of ibuprofen concentrations (d), PFOA
concentrations (e), and ibuprofen+PFOA concentrations (f). Error bars are standard deviations of triplicate cultures
the plant species and ibuprofen concentration (Shan and Liang 2010; Dordio et al. 2011). More recently, Iori et al. 2013 use the chlorophyll fluorescence tools to evaluate the effect of ibuprofen in two clones of Salix alba L., under hydroponic conditions. These authors found that the pharmaceutical compound affected in a different way to each clone, and they recognized the existence of several mechanisms involved in the changes of the photosynthetic activity and the antioxidative defense developed by plants. They related the decrease in the maximum quantum efficiency of PSII, with damage to the PSII centers. In our experiments, in a similar way that has been observed by Iori et al. 2013, we obtained a clear decrease in quantum efficiency of PSII (ΦPSII) and in photochemical quenching (qP), which indicates an overexcitation of the PSII system. In this way, the presence of ibuprofen
probably produces a stress action and an impartment of protective mechanism to ROS generation, which damage the PSII components as was indicated by Krause and Weis 1991. For PFOA, it was pointed out that this chemical is likely to be incorporated into the lipid bilayer of the cell membrane, increasing its permeability and causing toxic effects on green algae (Liu et al. 2008). But for plants, there are only a few studies focused on the uptake of this toxicant by different species. In this sense, Stahl et al. 2009 evaluated the growth of crop plants exposed to perfluorinated compounds, including PFOA. They suggested that the toxic effect of pollutants to plants was dependent on plant species. More recently, Wen et al. 2013 found that the transport of PFOA into maize roots was likely an energy-dependent process, but until now neither
IBU ibuprofen, PFOA perfluorooctanoic acid, CI combination index
Toxicity of individual pollutants expressed as EC10, EC20, EC50, and EC90 to S. bicolor (values in mg kg−1 ) with their 95 % confidence intervals. For mixtures, dose-effect parameters and mean combination index (CI) indicating 95 % confidence intervals. EC10, EC20, EC50,, and EC90 are the doses that inhibited growth by 10, 20, 50, and 90 %, respectively. CI1 indicate synergism, additive effect, and antagonism, respectively. Synergistic responses have been stressed in italics.
0.954 0.983 284.27±0.88 1,413.91±0.97 1.44±0.31 69.50±0.12 166.92±0.52 0.73±0.02 28.57±0.96 43.36±0.33 0.47±0.99 16.99±0.18 19.71±1.05 0.37±0.14 0.972 0.994 336.04±1.03 1,451.79±2.01 1.98±0.26 65.96±0.70 137.02±0.99 0.75±0.08 12.95±0.15 12.93±1.01 0.29±0.06 PFOA Mixtures (IBU+PFOA) CI values
23.61±0.11 30.90±0.22 0.41±0.03
1,909.62±1.01 420.86±0.87 162.08±1.40 92.75±0.73 0.993 956.96±3.01 282.15±1.10
EC90 (mg kg−1) EC50 (mg kg−1) EC20 (mg kg−1)
130.56±1.27 83.19±0.89
EC20 (mg kg−1) EC10 (mg kg−1) EC10 (mg kg−1)
r
qP ΦPSII
Dose-effect relationship parameters of individual compounds and binary mixtures for S. bicolor toxicity tests Table 2
The dose-effect parameters, EC10, EC20, EC50, and EC90 (mg kg−1), on S. bicolor for ibuprofen and PFOA are shown in Table 2. The values were determined using a 95 % confidence interval and the linear interpolation method independent of any particular dose-effect model (USEPA 2002). The linear correlation was good for the median-effect plots because all the r values were over 0.95. The EC50 calculated for both compounds showed that ibuprofen is not harmful for the plant, with values above 100 mg kg−1, in accordance with Regulation (EC) No. 1272/2008, unlike PFOA, which obtained values below 100 mg kg−1 for the quantum efficiency of PSII and photochemical quenching coefficient. ΦPSII appeared to be more sensitive than qP by the pharmaceutical product, although the industrial pollutant presented similar inhibition constant for both parameters and also low toxic concentrations. As other authors have demonstrated, ΦPSII is the parameter that gave a faster response to the presence of pollutants (Ralph et al. 2007; Buonasera et al. 2011). In our previous study, where we used the same plant to analyze root elongation inhibition, ibuprofen also caused less inhibition than PFOA (GonzálezNaranjo and Boltes 2013). For the low and high percentages of the affected population, calculated as EC10 and EC20 for the first case and as EC90 for the second one, ibuprofen proved less toxic than PFOA. As the affected population increased, the difference between toxicities for both compounds lowered for ΦPSII and increased for qP. For the binary combination, although the presence of PFOA considerably increased the toxicity of ibuprofen, neither ΦPSII nor qP obtained values lower than 100 mg kg−1. Thus, it was not toxic, as occurred with the root elongation inhibition measurements, although was sensibility poorer (González-Naranjo and Boltes 2013). Figure 2 presents the CI values in relation to the percentage of affected population. Evolution was similar for the two endpoints studied. Regarding ΦPSII, the binary mixture shows a synergistic behavior in almost the entire range of concentrations assayed, and its became slightly antagonistic at fa =0.9. The toxicological profile for qP also displayed the synergistic behavior until fa =0.7, when this close to additive effect began, which changed to antagonism at fa =0.8. Our previous work reports similar results but with a smaller range of concentrations with synergistic behavior and a wider-ranging section with antagonism, which was even harder. Once again, we demonstrated more sensibility for chlorophyll a fluorescence parameters than for root elongation to evaluate toxicity in terrestrial organisms (González-Naranjo and Boltes 2013).
EC50 (mg kg−1)
Ibuprofen and PFOA toxicity for PSII
IBU
EC90 (mg kg−1)
r
data was published about the effect of perfluorinated chemicals on the photochemistry of photosynthesis in plants, so a discussion of our results compared with those of other authors is therefore not possible.
0.962
Environ Sci Pollut Res
Environ Sci Pollut Res
a)
b)
5 4.5
4.5
4
4
Combination index (CI)
Combination index (CI)
5
3.5
3 2.5 2 1.5
3.5 3 2.5
2 1.5
1
1
0.5
0.5
0
0
0
0.2
0.4
0.6
0.8
1
Fraction affected (fa)
0
0.2
0.4
0.6
0.8
1
Fraction affected (fa)
Fig. 2 Combination index plot for mixtures of ibuprofen and PFOA on S. bicolor, obtained from qP (a) and ΦPSII (b). The line at CI=1 represents additivity. CI combination index value, fa population fraction inhibited.
Error bars indicate 95 % confidence intervals for CI values based on sequential deletion analysis (SDA) (Chou and Martin 2005)
The difference between the effects of both contaminants related readily to the organic carbon distribution coefficients, KOC, as explained in the work of Katayama et al. (2010). For the most toxic substance, PFOA, this parameter obtained values of around 115 l kg−1 (Higgins and Luthy 2006), while for ibuprofen, values were over 200 l kg−1 (González-Naranjo et al. 2013). This demonstrates that when KOC increases, the toxicity trend decreases because reduced compound mobility is assumed. Although no experimental data on EC50 were found in the literature for toxicological effects on PSII for high plants due to the presence of organic chemicals, some studies have studied how different herbicides affect other photosynthetic organisms, such as aquatic plants or microalgae. Kumar and Han (2011) determined the toxicity of atrazine, diuron, hexazinone, and simazine both individually and for the binary combination to Lemna sp., by quantifying the inhibition of the PSII maximum efficiency (Fv/Fm). As expected, the four herbicides produced much more damage than ibuprofen and PFOA if the target of the products was taken into account. Synergy was the predominant behavior in combinations, and antagonism occurred in all cases when herbicides were added at high concentrations, similarly to the sum of both pollutants in our experimental data. Meanwhile, Magnusson et al. (2010) investigated the affect on different microalgae. They noted that Cylindrotheca closterium was the most sensitive organism to the compounds used (diuron, tebuthiuron, atrazine, simazine, hexazinone, and desethyl-atrazine). The inhibition of PSII quantum efficiency was estimated for not only individual compounds but also for the binary combinations, which were estimated by assuming an additive behavior by applying the TU (toxic units) method that resulted in good prediction, unlike our results for the mixture. Simazine presented similar toxicity to ibuprofen, with an EC50 of 242 mg l−1. Tebuthiuron and atrazine, with 76.9 and 76.7 mg l−1 of EC50, respectively, showed toxicities which came close to the toxicity of PFOA.
Attending to the toxicity mechanisms reported in bibliography and discussed in “Effect of ibuprofen and PFOA on the chlorophyll fluorescence parameters in S. bicolor seedlings” section, the most probable explanation to the synergistic effect observed could be due to nonspecific interaction of PFOA with cell membranes, disturbing their structures and enhancing the ibuprofen uptake by plant, which finally produce an overexcitation of PSII system and a lost of photosynthetic capability of plants. Risk quotients assessment of the binary mixture The HQs were derived from dividing the MEC obtained from the literature for soil and river sediments (Supplementary Table 1) by the experimentally calculated PNEC (Sanderson et al. 2003; EMEA 2006; Von der Ohe et al. 2011). The values of these calculated ratios mean the following: HQ10 a high risk is probable (EMEA 2006). Three different equations were used to determine PNEC: the concentration addition, independent action, and combination index. Supplementary Table 2 presents the MEC, PNEC, and the HQ for individual pollutants and the binary combination of pollutants. Figure 3 shows the HQs for the pollutants as individuals and for the binary combinations in the two terrestrial environments studied. For PFOA, whose HQs were always higher than for ibuprofen, a moderate risk was estimated for soil and sediments in relation to both endpoints, ΦPSII (HQ=4.851 and 3.077) and qP (HQ=5.605 and 2.921), which were respectively higher for soil and lower for sediments since the expected likelihood of the pollutant occurring was higher in soils than in sediments. For ibuprofen, no risk was expected, except for soil when considering ΦPSII and at a moderate level (HQ=1.129).
Environ Sci Pollut Res
Fig. 3 HQ profiles determined from EC50 values for qP (a) and ΦPSII (b) inhibition on S. bicolor of ibuprofen and PFOA as individual compounds and HQ profiles for ΦPSII (c) and qP (d) inhibition on S. bicolor calculated by CI, CA, and IA methods in terrestrial environments
In the literature, no ecological risks data in terrestrial environments were found, except for one study done on ibuprofen by Martín et al. (2012). These authors assessed the risk in amended soil with wastewater treatment plant sludge, and they estimated PNEC from aquatic toxicological data and the solid-water partition coefficient (Kd). The quotient was 0.03, so no risk was detected. A difference was found between the two parameters for the mixtures, and the highest HQ was obtained for ΦPSII in soils and sediments. Of the three methods applied to estimate PNEC for the mixtures, CI offered the highest HQs, followed by CA, and finally by IA with the lowest values. When comparing root elongation (González-Naranjo and Boltes 2013), chlorophyll fluorescence was more sensitive to the risk assessment study in terrestrial environments when using terrestrial high plants. The importance of the interactions between the components of a mixture, where a different mode of action is expected, is highlighted herein in accordance with the experimental results. Consequently, ecological risks may be overestimated or underestimated if the CA or IA methods are used to calculate the mixtures’ toxicity, although they are the most widely applied ones for this purpose. Similar conclusions have been drawn in other works which also compared ecological risk assessment methods in aquatic environmental compartments. For example, in their study on the toxicity of different mixtures of phenylureas for algal communities where
the CA and IA were compared, Arrhenius et al. (2004) observed that CA was a good method for calculating EC50, although it could be overestimated. González-Pleiter et al. (2013) also compared the CI method with CA and IA in their study about toxicity of antibiotic mixtures to two aquatic organisms, microalgae, and cyanobacteria. Like us, they saw that CI indicates that synergistic behavior is the most obtained profile for toxicity in their combinations. Finally, in relation to the environmental matrices used for the HQ calculations, soil is seen to be more susceptible than river sediments to contamination for PFOA and ibuprofen given the occurrence of both pollutants in these terrestrial environments.
Conclusions The inhibition of the fluorescence parameters ΦPSII and qP is directly related to the exposure concentration of ibuprofen and PFOA for S. bicolor, with less sensibility found for the pharmaceutical compound, which was less available for the plant than the industrial compound. Therefore, they can be useful tools for quantifying toxicity in terrestrial environments. Besides when compared to other endpoints in plants, such as root elongation, they proved more sensitive. Consequently, this technique permits to evaluate the harmfulness on a more
Environ Sci Pollut Res
advanced state of development of the plant, not only in the germination state. The binary combination of both compounds shows predominant synergistic behavior. Hence, we conclude that for terrestrial photosynthetic organisms, interactions among pollutants play a key role and, consequently, classical methods for determining ecological risk, concentration addition, and independent action may imply underestimating these risks in terrestrial environments if caused by such mixtures. Acknowledgments This research was funded by the next research projects: CSD2006-00044, MICINN-CGL2009-13168-C03-01, CGL2012-39520-C03-01, and P2009/AMB-1588.
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