Download to read offline
More Related Content
![KG Final Paper for EWRI[1]](https://cdn.slidesharecdn.com/ss_thumbnails/8e27fbb4-ae66-4b11-bc29-74d2face4624-150320184608-conversion-gate01-thumbnail.jpg?width=640&height=640&fit=bounds)
000828 - Forsvar - revised text
- 2. Environmental Risk Assessment of Antimicrobials Hans-ChristianHolten Lützhøft Section of Environmental Chemistry Department of Analytical and Pharmaceutical Chemistry The Royal Danish School of Pharmacy
- 3. Demand from theEuropean Community (EMEA, 1998) Antimicrobial discharge can be expected after medication due to limited effluent treatment at the fish farm resulting in possible exposure to the environment Why Bother?
- 4.
- 5.
- 6. Outline Main objective The antimicrobials Environmentalfate Environmental effects Exposure scenarios Environmental risk assessment
- 7. Main Objective Assess theaquatic environmental risk associated with application of antimicrobials in freshwater fish farming
- 8.
- 9.
- 10.
- 11. Application Treat infections amongfish in fish farming Enteric red mouth disease Furunculosis Vibriosis Fry mortality syndrome FLU, OXA, SAF SDZ/TMP AMX, OTC AMX, OTC OXA and SDZ/TMP are commercially available as medicated feed
- 12. Consumption in DanishFish Farming, kg Year OXAa SDZa TMPa AMXb OTCb Otherb Total 1994 700 1,000 200 6 94 132 2,132 1995 906 1,241 248 78 67 242 2,782 1996 511 845 169 141 27 177 1,870 1997 587 1,677 335 132 16 181 2,928 a : Viuf (Personal communication), b : Data from 3 counties (Danske amter, Personal communication), Other: dimetridazole (antiprotozoal), florfenicol, metronidazole, sulfamerazine, and antimicrobials as such.
- 13. Compared with otherCountries mg/kg(fish) mg/L (effluent) Country 1987 1994 1997 1995 Scotlanda - 40 8 na Norwayb 885 7 - na Denmarkc - 61 84 0.7 USAd - - - 4 a : Baird et al. (Personal communication), b : Markestad and Grave (1997), c : Viuf (Personal communication) and Danske amter (Personal communication), d : Vicari et al., (Personal communication), -: not available, na: not applicable.
- 14. Biotic Fate Low oralbioavailability (ca. 10%)a Various degrees of biotransformationb Mainly excreted as parent compoundsc a : Bjørklund and Bylund (1991); b : Grondel et al. (1989), Ishida (1992), Tan and Wall (1995); c : Bergsjø et al. (1979), Rogstad et al. (1991), Ishida (1992), Tan and Wall (1995)
- 15. Preliminary Environmental Assessment Low oralbioavailability and low biotransformation result mainly in excretion of a parent compound The principal exposure is to the aquatic environment, however the distribution is widely pH-dependent Environmental exposure of biological active chemicals may affect non-target organisms
- 16.
- 17.
- 18. Objectives Determine distributioncoefficients (DDOC) of 4-quinolones between dissolved organic carbon (DOC) and water using SPME-HPLC analysis What influence does pH have? pH? DOC? N F CH3 COOH O N O COOH CH3 O O N F O COOH N HN F Holten Lützhøft et al. (Accepted)
- 19. Principles of SPME Negligibledepletion solid phase microextraction (nd-SPME) Kinetic extraction approach Measurement of the free concentration MXMX ⇔+ MXMXFibreXFibre ⇔++⇔
- 20. Interaction with DOC ChemicalLog KOW Log KOC from QSARa Log DDOC FLU 1.7b 1.7 3.4± 0.27c OXA 1.0d 1.0 3.9± 0.05c SAF - - 4.8± 0.01c DDT 6.9e 6.8 5.6± 0.18f HxCBz 5.7e 5.6 5.0± 0.05f PeCBz 5.2e 5.1 4.5± 0.03f a : Di Toro (1985), b : Takács-Novák and Avdeef (1996), c : Holten Lützhøft et al. (Accepted) III, d : Holten Lützhøft et al. (2000) II, e : Bruijn et al. (1989), f : Urrestarazu Ramos et al. (1998).
- 21. pH-Dependent Interaction with DOC N F CH3 COOH O pKa= 6.5 FLU N O COOH CH3 O O pKa= 6.9 OXA 23 4 5 6 7 8 3 4 5 6 SAF OXA FLU pH LogDDOC N F O COOH N HN F pKa= 6.8 pKa= 4.1 SAF pKa= 8.6
- 22. Conclusions DDOC valuesfor the investigated 4-quinolones appeared to be remarkably high DDOC values for the investigated 4-quinolones were shown to be pH dependent, suggesting electrostatic interactions to work in the system
- 23. Summary of EnvironmentalFate Log DSED values of 2.3-2.7a Similar physical chemical properties for sulphadiazine and amoxicillin suggest log DSED in the same range Photodegradation is negligibleb Non-biodegradablec Oxytetracycline is biodegradable in freshwater sediment slurries (t½: 2-8 days) a :Lai et al. (1995), Holten Lützhøft (Unpublished); b : Lunestad et al. (1995); c : Hektoen et al. (1995), Lai et al. (1995)
- 24.
- 25. Objectives Investigate the suitabilityof using the standard test algae Selenastrum capricornutum to represent micro-algae for evaluation of antimicrobials, e.g. ISO (1989) and EMEA (1998) Establish toxicity data for antimicrobials towards algae Holten Lützhøft et al. (1999)
- 26. Tested Algae Microcystis aeruginosa(freshwater cyanobacteria) Rhodomonas salina (marine cryptophycean) Selenastrum capricornutum (freshwater green algae) Bacteria Procaryotic No nucleus 0.5-2.0 µm No photosynthesis Modified from Brock and Madigan (1991) Cyanobacteria Procaryotic No nucleus 0.5-60 µm Photosynthesis Algae Eucaryotic Nucleus 2-200 µm Photosynthesis
- 27. Overview of AcuteEffect Data 0,1 1 10 100 1000 AMX SAF FLU SDZ OXA OTC TMP LC50,mg/L a : Migliore et al. (1997); b : Andersen (1999), Andersen (Personal Communication); c : Andersen (1999), Wollenberger et al. (2000), Halling-Sørensen et al. (In press); d : Andersen (1999), Halling-Sørensen et al. (In press) : NOEC Artemia sp.a A. tonsab B. reriod D. magnac
- 28. Overview of ChronicEffect Data 0,0001 0,001 0,01 0,1 1 10 100 1000 10000 AMX SAF FLU SDZ OXA OTC TMP EC50,mg/L : NOEC a : Backhaus et al. (2000); b : Holten Lützhøft et al. (1999) IV; c : Wollenberger et al. (2000) V. fischeria M. aeruginosab R. salinab S. capricornutumb D. magnac
- 29. Conclusion Environmental evaluation ofantimicrobials requires tests of cyanobacteria The effect concentrations are comparable to concentrations of antimicrobials found in the environment
- 30.
- 31. Overview of ExposureScenarios
- 32.
- 33.
- 34. Procedure to DerivePNEC Constant assessment factor approach proposed by the OECDa and EMEAb Assessment factor depends on quality of data i.e. acute/chronic, NOEC/EC50, trophic levels a : OECD (1992); b : EMEA (1998) FactorAssessment ECorNOECLowest PNEC 50 =
- 35. 0 50 100 NOEC Chronic Acute EC50 ⇓ AF=10 Log C ⇓ AF=100 NOEC Effect,% EC50 AssessmentFactors Three trophic levels Less than three trophic levels 0 50 100 Log C ⇓ AF=1,000 NOEC EC50 Effect,%
- 36.
- 37.
- 38. Main Objective Assess theaquatic environmental risk associated with application of antimicrobials in freshwater fish farming
- 39. Environmental Ranking TMP OTCSDZ SAF OXA FLU AMX Harmless under studied scenarios More studies required RQ 10-3 10-2 10-1 1 101 102 103
- 40. I would liketo thank... Sven Erik Jørgensen and Bent Halling-Sørensen for the thorough supervision during my Ph.D. project the last 3-4 years
Editor's Notes
- #3 Thank you Birthe/Jens. I would like to welcome you all to the defence of my Ph.D. thesis. I am now going to give a lecture for about 45 min. The title of the lecture is the same as the title of my thesis: “Environmental Risk Assessment of Antimicrobials”. As my thesis does, this lecture will deal with environmental risk assessment of antimicrobials and the elements therein. Antimicrobials is a widely used group of drugs and one of several relevant environmental applications is in fish farming, where they are used to control infections among the fish. The subject is thus limited to antimicrobials used in fish farming.
- #4 “Why bother?”, one could ask and the answer may be manifold. One answer could be that the European Community in 1998 adopted an environmental assessment guideline for veterinary drugs, thus all new veterinary drugs send on the market after 1998 need an evaluation of their environmental impact. (What about existing drugs?) Another could be that the medication of fish in fish farming obviously results in a discharge of antimicrobials to the receiving stream due to f. inst. limited effluent treatment. Or that investigations from different places in Europe have shown that antimicrobials can be found in the sediment around fish farms as a possible result of medication/treatment of the farmed fish.
- #5 This table shows you some of the findings that have been reported in the literature. A more detailed list can be found in my thesis. It is mainly in Norway and Finland that investigations have been performed, however one investigation showed that OXA could be found 300 m downstream the outlet of a Danish freshwater fish farm 21 days after end of medication. This is in contrast to the finding in Finland, where it was not possible to detect OXA 6 days after medication. An explanation may be that there is a much larger dilution potential in the Baltic compared to a Danish stream! As is indicated here, all other findings are made in a marine environment. In those cases the fish are kept in cages in the sea. Regarding OTC, investigations in Norway have shown that OTC persist in the sediment up 560 days after medication, even in relatively high environmental concentrations of 15 µg/g sediment. Furthermore investigations have shown that also the wild fauna suffer from the use of antimicrobials in fish farming. In fish caught up to 400 m from the fish farm, it was possible to find OXA.
- #6 <number> 30/09/15 Basically this figure shows you two things - one is the schematic illustration of the structure of a freshwater fish farm, as those in Denmark. You see where the water from the stream flows into the fish farm, through it and back again to the stream, thus the stream serves both as the water supply and as the recipient. You can imagine, that if antimicrobials applied in the fish farm are not degraded, they may enter the stream by the water flow. The other thing this figure shows you is the tasks that were performed during the project. In the upper left corner, you see the part concerning collation of basic data in order to make an initial environmental assessment. This will be discussed in a moment. Next you see a part concerning environmental occurrence. I will not discuss that further during the lecture. Down in the middle, you see a part dealing with the environmental fate. Two articles have been written on this subject, one that is published deals with the pH dependency of octanol/water distribution coefficients of OXA. The other that is accepted, deals with distribution coefficients between dissolved organic carbon and water for three 4-quinolones among them OXA. The last mentioned part of the subject will be discussed later on. Further to the right, you see the part dealing with environmental effects. On that subject one article is published. That one deals with growth inhibiting effects of antimicrobials towards algae. Together with these results I will show you other relevant results found in the literature. Finally, in the right bottom corner you find the environmental risk assessment. I will conclude this lecture by explaining the exposure scenarios I have used in my calculations. These will be related to the effects just mentioned and I will end the lecture by showing what environmental impact you can risk from these antimicrobials, based on the data that I have presented.
- #7 Well this introduction to my project brings me to the outline for the rest of my lecture: First I will state the objective for the Ph.D. project. As indicated I will then give a physical chemical description of the investigated antimicrobials in order to see what can be predicted from the structures and the bare physical chemical data. This will be followed by an examination of their environmental fate, which gives knowledge of where in the environment the chemicals will end if they are stable and if degradation products will be formed. Then I will look at the possible toxic effects the antimicrobials may have when they occur in the environment. These fate and effect data need to be compared with the likely concentration that can be found in the environment. Thus I will explain the exposure scenarios I have used in my calculations leading to the likely environmental concentrations. Based on the presented knowledge, the data on fate and effects and the defined exposure scenarios, I will finally show the ranking of the possible environmental impact due to the use of antimicrobials in freshwater fish farming. Kan gøres kortere!!!!
- #8 The main objective in my Ph.D. project has been to “quantify the environmental risk in the aquatic environment associated with application of antimicrobials in freshwater fish farming” Om muligt, tag en slurk vand for at lade et par sekunder gå. In order to fulfil the main objective, several objectives were formulated, which can be read in my thesis, but not all of them will be discussed in this lecture.
- #10 The physical chemical properties of the investigated antimicrobials are shown on this and on the next slide. Obviously they are not identical chemicals, but they show great similarity for the individual properties. Please note, that I will use the three letter abbreviations throughout the lecture, thus FLU means flumequine and so on. What you see is chemicals that are relatively water soluble with several mg/L. This is also reflected in the DOW where log values less than 1.1 indicate hydrophilic chemicals with highest affinity for the aqueous environment. Furthermore, all the antimicrobials contain ionizable groups, with pKa values mainly around 7. This means that when pH shift around 7, the chemicals will change between neutral and ionized chemicals. They can be expected to occur in the aquatic environment, however ionic interactions are likely due to the variety in ionizable groups.
- #11 For the last four antimicrobials you find a similar pattern. Water soluble, hydrophilic and ionizable chemicals. They are all broad spectrum antimicrobials, and except for OTC they are synthetic chemicals. SDZ and TMP are co-administered in a ratio of 5 to 1 which makes this agent bactericidal as well. Once more you see rather complex structures with a variety of functional groups.
- #12 Antimicrobials are used in fish farming to treat infections among the fish. I will not go into details regarding the clinical or pharmacological aspects, but mention that the typical diseases that occur is Enteric red mouth disease, Furunculosis, Vibriosis and with respect to the fry Fry mortality syndrome. On the right I have indicated which antimicrobials that typically are used to treat the diseases. FLU and SAF are not used in DK and AMX and OTC are only used to treat the first three mentioned diseases when failure in the previous treatment with the other agents is observed. AMX and OTC are thus mainly limited to treat the fry. Furthermore these two antimicrobials are only used on dispensation. OXA and SDZ/TMP are commercially available as medicated feed which facilitate the administration and limits the exposure of the fish farmer.
- #13 In DK there does not exist a consistent reporting system for the consumption of vet. Drugs. However, some reporting has taken place. The consumption shown in this table can be considered as a minimum. It is seen, that during the 4 years of reporting, 2-3 tonnes are used on a yearly basis.
- #14 Due to vaccination programmes espeically in Norway, they have managed to reduce the antimicrobial consumption in their fish farms, whereas in DK no changes has been observed, Norway and Scotland has substantially reduced the consumption. Compared to USA DK uses a little less, when calculated as the total antimicrobial consumption dissolved in the total water body of all fish farms.
- #15 First I will say, surprisingly not all the data that I requested could be found for all the antimicrobials but in general when antimicrobials are administered to fish through the food, the oral bioavailability is rather low. For the current chemicals it is approx. 10 %, meaning that only 10 % reaches the systemic circulation where it can be exposed to various degradation processes in the fish. Furthermore, the degree of bitransformation varies. For OTC it is almost zero, whereas for OXA up to 70 % can be found as glucoronide 24 h. after administration. Nevertheless, most of an administered dose will be excreted as a parant compound.
- #16 After this presentation of the basic data of the investigated antimicrobials, their application and their biotic fate it is possible to make a preliminary environmental assessment. First of all, the antimicrobials suffer from low oral bioavailability and low biotransformation mainly resulting in excretion of parent compounds. Second, due to the physical chemical properties the principal exposure is to the aquatic environment, however the distribution is widely pH-dependent. Third, the environmental exposure of biological active chemicals may affect non-target organisms.
- #18 This figure represents an illustration of the processes that chemicals in general and antimicrobials in this case encounter when they enter the aquatic environment. To what extent depend on the physical chemical properties of the chemical. On this slide OXA is shown as an example. As you can see there are a lot of possible reactions that may influence the presence of the antimicrobial. The antimicrobial may interact with cations with humic acids, here measured as DOC and also with f. inst. sediment. There are several degradation possibilities - the light may have an impact on the presence of the antimicrobial, in form of photodegradation. The pH may influence the hydrolysis, the temperature may also influence the stability and also bacteria may biodegrade the chemical. Finally the antimicrobial may have some impact on the fauna and flora which is exemplified with algae. All the shown processes influence the presence of the antimicrobial and knowledge about the individual parts need to be obtained if a proper ERA should be performed. In the following I will focus on the distribution to DOC and then I will give you a summary of relevant other degradation and distribution data.
- #19 Normally it is assumed that only hydrophobic chemicals bind to DOC due to the hydrophobic cavities within the DOC, but knowing that humic material consists of different carboxylic acids, phenolic groups and amines, it would be interesting to see if any interactions would occur between antimicrobials and Aldrich humic acids used as a surrogate to natural organic matter. Thus the objective was to determine distribution coefficients of 4-quinolones between DOC and water using SPME-HPLC analysis. Furthermore, what influence does pH have on the distribution coefficient. In a moment I will explain the reason to use SPME as the extraction technique. Aldrich humic acid was used since the results can then be compared with other experiments and chemicals. However, Aldrich humic acids are not similar to natural occurring humic acids. The concentrations that were used in the investigation are in the same range as can be found in the environment, which in the literature is reported to be up to 50 mg/L, but mainly between 2 and 10 mg/L.
- #20 Negligible depletion solid phase micro-extraction is abbreviated nd-SPME. This SPME application is an extraction technique using a kinetic approach for the extraction of a compound which can be absorbed in a polymer. The figure on the slide represents the SPME fibre consisting of a fused silica fibre which can be coated with different polymers. That is the polymer which functions as the extracting phase when it is submerged in an aqueous solution, f.inst. Into a 2 mL HPLC-vial. Imagine a compound X in equilibrium with a matrix M, as shown in the upper equation, where M can be different phases like for instance humic acids or a protein matrix. If one is interested in the free concentration of X, a normal extraction will disturb the equilibrium which will be displaced to the left, and in principle it will result in a total extraction of X. In accordance with the just mentioned experiment, one can replace M with the SPME fibre and a similar equilibrium for X will be established between the fibre and the aqueous phase. An extraction from a certain matrix by means of SPME will contrary to a traditional extraction only extract a certain fraction, defined by the circumstances, of the free concentration. Usually the experiment is designed to extract a few per mille and the equilibrium between the compound X and the matrix M is left almost undisturbed; so called nd-SPME. The concentration which is then determined, will be the free or the bioavailable concentration assuming that the SPME fibre behaves as a biological membrane. The aim of this method is to measure free concentrations instead of total concentrations. That is also the reason for applying this method to establish DOC/water distribution coefficients.
- #21 This table shows you several things. First you may distinguish between the two groups of chemicals: the three 4-quinolones, FLU, OXA and SAF, and the three very hydrophobic chemicals, DDT, hexachlorobenzene and pentachlorobenzene. The next column gives the octanol/water distribution coefficient - showing a distinct difference in hydrophobicity between the two groups. The third column represents the respective chemicals QSAR estimated KOC values. This QSAR was developed for pesticides with log KOW values in the range 1 to 7 and use log KOW to estimate log KOC. As mentioned earlier, it is often assumed that organic matter is cabable of binding hydrophobic chemicals due to hydrophobic interactions - thus it is expected that the KOC is proportional to the KOW and in the same range. That is also the case here. However, experimental data as shown in the last column reveal DDOC values rather different from the estimated values. The values shown here in purple are from the study applying the SPME approach, which was performed at a pH of 3, where FLU and OXA can be considered neutral, as is the case for the other group of chemicals. The distribution coefficients shown here are surprisingly high, in fact they are in the same order of magnitude as the values for highly hydrophobic chemicals, like DDT, hexa-chlorobenzene and pentachlorobenzene. These experiments suggest that the 4-quinolones interact with DOC, and based on the structures of the chemicals a kind of electrostatic interactions involving dipole dipole interactions and hydrogenbonding is likely to occur. Furthermore it would be expected that these chemicals could then accumulate in the environment even though QSAR-based estimates predict the opposite.
- #22 As indicated earlier the influence of pH on the DDOC was also studied. The pH interval studied can be considered environmentally relevant in freshwater systems. The graphs on this slide show these results. When the pH increases the ionization of FLU and OXA increases as well and an increase in DDOC is observed too. However, one can expect that the hydrophobicity of a carboxylic acid decreases when the pH increases due to ionization of the chemical - thus decreased DDOC would be expected. Taking this into account the results again suggest that it is electrostatic forces that work in this system rather than hydrophobic interactions. For SAF an optimum around 5 is seen. At this pH value SAF is positively charged due to the secondary amine function in the piperazine moiety, which has a pKa of 8.6. This positive charge could interact with some negatively charged carboxylic acids in the humic acids. However, since this charge is present throughout the pH range studied, it can not alone count for this peak. But for this chemical as well, the attention towards electrostatic interactions, and not hydrophobic interactions alone, was drawn. Another thing that is worth to notice is that when log KOW is taken as the hydrophobicity of the chemical the most hydrophilic antimicrobial shows the highest interaction with DOC. However, this is most outspoken at low pH values where FLU and OXA can be considered to have neutral charge. Finally, with such DDOC values humic acid concentrations of 2-10 mg/L will reduce the free concentration of these antimicrobials with up to 35 %, depending on chemical.
- #23 The conclusions on the 4-quinolone interaction with DOC are: Surprisingly, due to the lower estimated distribution coefficients based on KOW values, the investigated 4-quinolones appeared to have remarkably high DDOC values. And the results showed also a pH dependent distribution to DOC, suggesting electrostatic interactions to be responsible for the interaction rather than hydrophobic interactions.
- #24 The just mentioned experiments with humic acids facilitated some simple experiments aiming to establish distribution coefficients between freshwater sediment and water. The experiments showed that FLU, OXA, SAF, TMP and OTC distribute to sediment with log values of 2.3 to 2.7. Due to the similar physical chemical properties and substructures AMX and SDZ is anticipated to distribute to sediment as well. Experiments have shown that FLU, OXA, SDZ and TMP are photostable at subsurface light intensities, although OTC is easily photodegraded at the same conditions, it is not anticipated that the antimicrobials are photodegraded. This is based on the fact that the antimicrobials often are administered incorporated in the feed. Except for OTC the other antimicrobials do not seem to be biodegradable in sediment. OTC was shown to be biodegradable in sediment slurries wiht half-lives decreasing from 8-10 days when respiked and when spiking with higher concentrations.
- #25 This brings me to the environmental effects!
- #26 <number> 30/09/15 In the guideline from 1998 adopted by the EC several tests are proposed. Among the effect studies a test for algal growth inhibiting effects is found. In this guideline and in standard toxicity tests with algae, Selenastrum capricornutum, that is a green algae, is often suggested as test organism. Knowing that antimicrobials are specifically acting chemicals aiming at inhibiting or preventing the growth of bacteria, is S. capricornutum thus a suitable algae for evaluation of antimicrobials?
- #27 <number> 30/09/15 In order to test whether S. capricornutum is a suitable algae three different algae were selected, representing three different groups of algae: Microcystis was chosen to represent freshwater cyanobacteria, Rhodomonas was chosen to represent marine algae, and Selenastrum was chosen as the standard test algae and to represent freshwater green algae. This selection was made because it would be interesting to show whether there was any difference among the three groups of algae. In some way Microcystis is expected to be more sensitive than the other algae because Microcystis is procaryotic of nature as shown in the list, and therefore Microcystis has structure more like bacteria. Microcystis is called cyanobacteria instead of blue-green algae, to indicate clearly that they are not eucaryotic. However, they share the photosynthesizing abilities with algae and may be important organisms in the ecosystem.
- #28 <number> 30/09/15 This figure shows the acute effect data of the investigated antimicrobials. Apparently it is the LC50 value that is on the Y-axis and the antimicrobials on the X-axis. But, some of the data are reported as the NOEC - on this figure they are marked with a star. As seen the data material is limited. The organisms tested for acute mortality are crustaceans and one fish.
- #29 <number> 30/09/15 The next figure represents the chronic effect data. Here the EC50 is plotted at the Y-axis and again the stars indicate NOECs. As seen, the chronic data comprise a more comprehensive data set. The organisms tested here are mainly algae, as mentioned before a cyanobacteria - the bluegreen colour, a marine algae - the reddish colour and the green colour represents the green algae Selenastrum capricornutum. For all algae the effect is growth inhibition. The purple colour represents the bacteria Vibrio fischeri, where the effect is bioluminescence inhibition and the whitish colour represents the crustacean Daphna magna where the effect is on the reproduction system. The data have been ordered with respect to decreasing toxicity towards the cyanobacteria. Two things are worth to notice. The first thing is that the antimicrobial that shows the least toxicity is TMP with effect concentrations between 10 and 100 mg/L. The other thing is that in all other cases, the cyanobacteria is more sensitive than the two other algae - a difference that reaches 6 orders of magnitude for AMX.
- #30 <number> 30/09/15 From these experiments it can be concluded that the environmental risk assessment of antimicrobials requires that a cyanobacteria is tested, since Microcystis in most cases is two to three orders of magnitude more sensitive than the standard test algae. Furthermore, the effect concentrations are comparable to concentrations of antimicrobials that can be found in the environment.
- #31 Now I will explain the exposure scenarios that I have used for the calculations of the predicted environmental concentrations.
- #32 This table gives you the descriptions of the selected exposure scenarios. I have selected to define a worst case scenario, in which I used one day’s dose and exposed it to one pond volume. All transformation and distribution processes was ignored. The concentration obtained in the pond volume was diluted twice, due to the discharge of the effluent into the stream. In the second scenario I have included the processes that inevitable will take place. This time I used a full treatment and exposed it to the stream. All relevant distribution and degradation processes were incorporated in the calculation - meaning that the part of the chemical that distributes to sediment or is degraded is considered lost. The remaining free concentration was then diluted in the volume corresponding to the evaluated part of the stream, which was 300 m downstream the fish farm. The final scenario I called a more realistic case. It has its origin in the just mentioned scenario. The only change that was made is that I applied a dilution factor of 34, corresponding to total water exchange in the evaluated part of the stream during 21 days.
- #33 The output of the just mentioned scenarios is what you see in this table. When going from the worst case to the more realistic case you experience a difference for the individual antimicrobials of between a factor 400 and 6000, for FLU and OTC, respectively. This indicate that these calculations are encumbered with a large uncertainty. Nevertheless, in order to make an assessment, these likely environmental concentrations have to be compared with effect or no-effect concentrations.
- #34 Thus, the final part of this lecture is the ERA.
- #35 The predicted no effect concentration is a measure for the concentration that is assumed not to give any effect in the environment. An approach to predict that measure was proposed by the OECD in 1992. The use of the same approach is encouraged in the guideline adopted by the EC in 1998. The approach is called the constant assessment factor approach. The PNEC is derived by taking the lowest NOEC or EC50 and dividing it with an appropriate AF. This AF depends on the quality of the study, understood in that way that the AF depends on whether the study was acute or chronic, the endpoint was obtained as a NOEC or an EC50 and on how many trophic levels the chemical is tested. How to derive the AF is illustrated on the next slide:
- #36 At the bottom of this slide you see the three proposed AFs. When the chemical has been tested on less than three trophic levels it is only allowed to apply an AF of 1000, irrespective of the endpoint. However, if three trophic levels are tested an AF of 10 may be applied but only if the tests are chronic tests with NOEC as the endpoint. An AF of 100 is applied if again three trophic levels are tested, but none of the tests were chronic with NOEC as endpoint. Thus in the case of chronic tests on three trophic levels, algae, crustaceans and fish, giving EC50 as the endpoint, it is only allowed to apply an AF of 100.
- #37 By applying the approach explained before, the following PNECs are obtained. <Go through the table from left to right> Now both likely environmental concentrations and PNECs are available, so they only have to be related to each other.
- #38 A measure for the risk is the so called risk quotient, which is calculated as the predicted environmental concentration divided by the concentration that is predicted not to give effects. You see, that the magic output is 1. If the RQ exceeds 1, there is a risk for effects on the environment, however it is not known whether any effects will occur or not, but the likelihood increases with increasing RQ. On the other hand, when the RQ is below 1, it means that under the given circumstances there is no risk of the application of the given chemical. The table here shows you the RQ for the three selected exposure scenarios. As was the case for the PECs, there is also here a difference of approx. 1000 from the worst case to the more realistic case for the individual chemicals. It is worth to notice, that TMP is the only antimicrobial that end up with an RQ less then 1. Else there is formed a middle group consisting of OTC, SDZ, SAF and OXA with RQs from 0.5 to 15 and another group with FLU and AMX having RQs higher than 100.
- #39 Just to refresh your memory on the main objective of this project I show you this slide again. The main objective was to quantify the aquatic environmental risk associated with application of antimicrobials in freshwater fish farming. The answer to that objective is illustrated on the next and almost final slide:
- #40 Here the RQs are ranged in increasing order - the antimicrobial with the least risk on the left and then as we move towards the right the risk for environmental impact increases. The conclusion is that TMP seems to be harmless under the studied scenarios, whereas more studies are required for the rest of the antimicrobials in order to fully elucidate their environmental impact. It may be interpreted in that way that the more right the antimicrobial is placed the more studies will be required. A way to reduce the RQs is to refine the exposure scenarios or to restrict the use, either by decreasing the dose or by limiting the number of applications per year. In my opinion, especially the refinement of the exposure scenarios will improve the ERA.
- #41 I will finish my lecture by saying that … I would like to thank Sven Erik Jørgensen and Bent Halling-Sørensen for the thorough supervision during my Ph.D. project the last 3-4 years. Thank you for your attention.