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Effects of copper on sludge decomposition by benthic
macro-invertebrates
Bachelor project; J. van Burik, supervisors; T. V. van der meer, MSC and Dr. Michiel H.S. Kraak.
Institute for Biodiversity and Ecosystem Dynamics (IBED) Freshwater And Marine Ecology (FAME)
31-05-2021, Amsterdam ==============
Abstract
The use of macroinvertebrates as decomposers of sludge in wastewater treatment plants (WWTPs) could potentially increase the circularity of the waste water treatment process. Different macroinvertebrate species have different feeding trait, which may positively influence the decomposition of organic matter (OM). However, high concentrations of toxicants in the sludge may exert adverse effects on the macro-invertebrates and thereby slowdown the sludge degradation. The aim of this study was therefore to investigate the effects of copper (Cu) on sludge decomposition by a combination of benthic
macroinvertebrates with different feeding traits. To this end survival, growth and sludge degradation were investigated for Chironomus riparius and Physa acuta in separate and combined treatments at different copper concentrations in a 7-day toxicity test. Cu resulted in a decrease in survival and growth of the organisms and a decrease in sludge degradation by P. acuta and C. riparius. At sublethal Cu concentrations there was facilitation in sludge degradation by the two species. At high Cu concentrations the survival of C. riparius was affected by the presence of the more sensitive P. acuta. This study showed that in slightly contaminated sludge a combination of macroinvertebrates with different feeding traits can facilitate each other’s sludge consumption, which results in higher degradation rates compared to the use of a single species. However, if contamination levels become too high, survival, facilitation and sludge decomposition ceased. Hence, it is concluded that macroinvertebrates with different feeding traits may facilitate sludge decomposition, as long as the sludge is not too contaminated.
Keywords: C. riparius - P. acuta - Copper - survival - growth - sludge degradation.
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Introduction
The Dutch population produces 1.9 billion cubic meters of wastewater every year (CBS, 2017), which is treated by wastewater treatment plants (WWTPs). During the treatment process, WWTP’s
produce excess sludge. Since this sludge generally contains organic and inorganic contaminants, which make direct application as a fertilizer or for landfilling unsuitable, most of the sludge in the Netherlands is incinerated (Herzel et al., 2016). The disposal of sludge is very costly and potentially useful nutrients and organic substances are lost (Tarpani & Azapagic, 2018). Therefore several methods have been proposed to decrease the amount of WWTP sludge that needs to be incinerated (Chen et al., 2001).
A possible solution could be the use of macroinvertebrate species as natural decomposers of WWTP sludge. Some macroinvertebrate species can occur on very eutrophic sediments and the OM in these places is (structurally and chemically) similar to the sludge produced in a WWTP (Dignac et al., 2000). These macro-invertebrates play an important role in nutrient dynamics in these natural eutrophic aquatic ecosystem (Anderson, 1979). They feed on detritus and are able to consume sludge and convert the OM into biomass, nutrients (such as, PO4 en NH4/NOx) and CO2 (Mitchell, 1979; Vink & Atkinson, 1985). They can also stimulate microbial activity and biogeochemical processes, which further increases the breakdown of the OM (Mermillod-Blondin, 2011). The use of macro-invertebrates for the natural decomposition of wastewater sludge reduces the total amount of sludge and thereby can result in lower costs for the WWTP (Zang et al., 2015; Basim et al., 2016). Aquatic worms, such as the Lumbriculus variegatus, are already being used in some pilot WWTP to reduce the amount of sludge (Basim et al., 2016). But aquatic worms might not be the only types of macro-invertebrates suitable for decomposition of sludge. In aquatic ecosystems there are multiple decomposers that breakdown OM, all these decomposers having different feeding traits with which they decompose different parts of OM in different ways (Scherer et al., 2017; Culp et al., 1983). Thereby macro-invertebrate species interact with each other, which may affect the sludge consumption by the macroinvertebrates (Wallace & Webster, 1996). Therefore, it is essential to investigate whether the different feeding traits of the different macro-invertebrate species cause a difference in sludge consumption and whether a combination of macro-invertebrates with different feeding strategies can cause a difference in the degradation of the sludge.
After the treatment of wastewater in a WWTP, the concentration of contaminants, including heavy metals, in the remaining sludge can be high (Tao et al., 2011). These contaminants can exert adverse lethal and sublethal effects on the macro-invertebrates, which could also impact the degradation of the sludge by these organisms (Schultheis et al., 1997; Archaimbault et al., 2010). This could make the use of macro-invertebrates for sludge reduction in a WWTP less efficient. Thereby, different species have different sensitivity to certain contaminants, which in turn can have an effect on the possible interactions between species (Friberg et al., 2010). It is thus important to know whether the different species interact with each other and in this way affect the degradation of the sludge. Therefore, the aim of this research was to investigate the effects of copper (Cu) on sludge decomposition by a combination of benthic macroinvertebrates with different feeding traits.
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To this end, we conducted a sludge degradation experiment under ambient and high chemical stress conditions with single and multi-species. Growth, mortality and sludge degradation were selected as endpoints for the effects of copper on the macro-invertebrates and OM degradation. Cu was used as a model chemical stressor because it often occurs in relatively high concentrations in wastewater sludge (Hunting et al., 2013). Since sludge from different WWTP can differ in the amount and composition of contaminants, we used sludge from one WWTP and spiked this with Cu. For this research, a 7-day toxicity test has been conducted. The selected benthic macro-invertebrate species were Chironomus riparius, collector-gatherer and Physa acuta, a scraper and surface grazer (Scherer, 2017; Dodds & Whiles, 2010). Previous studies suggested that P. acuta would have a higher
sensitivity to copper than C. riparius (de Haas et al. 2004; Gao et al. 2017). Because of this difference in sensitivity, we expected that the survival, growth and sludge degradation by P. acuta would already be affected at lower Cu concentrations than the survival, growth and sludge degradation by
C. riparius. Thereby, it was expected that survival and growth of the organisms and sludge
degradation would decrease at an increasing Cu concentration (Schultheis et al., 1997; Archaimbault et al., 2010). Since C. riparius and P. acuta have different feeding traits, our expectation was that they would consume different parts of the OM and that there would be no competition for food. The combination of the two species would therefore cause the same amount of sludge degradation as the two individual treatments added together, if the biomasses of the two species are equal.
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Materials and Methods
Test organisms and culture conditions
Two benthic invertebrate test species, Chironomus riparius and Physa acuta, with different feeding traits based on particle size preference, were selected as test organisms (Scherer et al., 2017; Culp et al., 1983). Both species were cultured at the University of Amsterdam at 20 ◦C with a light-dark regime of 16 hours light and 8 hours dark. They were fed twice a week with fish food flakes from the brand Tetra Phyll. C. riparius was kept in an aquarium with a layer of sediment (sand) and a layer of Dutch Standardised Water, (DSW: deionized water with 200 mg/L CaCl2 . 2H2O, 180 mg/L MgSO4 . H2O, 100 mg/L NaHCO3, and 20 mg/L KHCO3; hardness is 210 mg as CaCO3/L and pH 8.2). P. acuta were kept in an aquarium which only contained DSW.
Chironomus riparius
Larvae of the non-biting midge Chironomus riparius are part of the Chironomidae family. This species is commonly used in ecotoxicity studies (OECD, 2004a). They are collector-gatherers (Scherer, 2017), the larvae feed non-selectively and enhance downward transport of particles (Mermillod-Blondin et al., 2002). They create macropores, which limits microbial activity (Mermillod-Blondin et al., 2002).
C. riparius often occurs in organically enriched environments (Girling et al., 2000). The larvae used in
this experiment had an average length of 7,53 mm.
Physa acuta
Physa acuta is a surface breathing freshwater pulmonate snail, of the family Physidae. It is a
common species in Europe and North America. This snail species is a scraper and surface grazer (Scherer, 2017). The snails feed on films of organic material on substrate surfaces (Dodds & Whiles, 2010). P. acuta can tolerate relatively eutrophic conditions (Lance et al., 2010). The shell length of the snails used in this experiment was between 5.5 and 6.5 mm.
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Sludge collection and spiking
The sludge was derived form a aeration tank from a WWTP in Rhenen, the Netherlands (latitude: 51.95917; longitude:5.56 806 ). Sludge was collected on 29-03-2021 and on 12-04-2021. The ambient Cu concentration in the sludge from the WWTP in Rhenen was 198 mg/kg dry weight (van der Meer, pers. comm. 2020). The day we collected the sludge, solids concentration in the sludge was 4.52 g/L. The sludge was put in 500 ml glass bottles and manually stirred. Part of the sludge was spiked with CuCl2 . 2H2O, which was done drip wise to ensure homogenous spiking of the sludge. The
500 ml glass bottles were then placed under aeration for a day to prevent the formation of an anoxic layer and to ensure mixing of the sludge (Hailea aco-2206 (airflow4)). After 24 hours of
homogenization, the homogenized sludge was pipetted into the corresponding replicate 50 ml beakers, while stirring the 500 ml bottles. Each replicate beaker contained 25 ml sludge and 15 ml DSW.
Outline of the study
To determine which copper concentrations resulted in nonlethal effects for both species, a range finding experiment was conducted. Based on the outcomes of the range finding experiment, we chose the appropriate Cu concentrations for an interaction experiment. In the interaction
experiment we tested the effects of Cu on survival, growth and sludge degradation of C. riparius and
P. acuta in a combination treatment. Range finding experiment
In this experiment we exposed Chironomus riparius and Physa acuta separately to five different Cu concentrations, consisting of ambient sludge (control), 3x, 10x, 30x and 100x the amount of the control (spiked with 216 (3x), 722(10x), 2167(30x) and 7223(100x) mg CuCl2 . 2H2O per liter). This
resulted in the following nominal concentration range: 594 (3x), 1980 (10x), 5940 (30x), 19800 (100x) mg Cu per kg DW sludge. The experiment was conducted in duplicate, but there were three replicates for the controls with the lowest (ambient sludge) and highest (100x) concentration, to ensure sufficient quality control of the experiment. The Chironomus riparius density was 12 individuals per beaker and the P. acuta density 4 individuals per beaker.
Interaction experiment
Based on the on the survival of C. riparius and P. acuta in the range finding experiment we selected two Cu concentrations, 30x (5940 mg/kg) and 60x (11880 mg/kg) the Cu concentration of the original sludge. Therefore, part of the sludge was spiked with 2167 (30x) and 4334 (60x) mg CuCl2 . 2H2O per liter, resulting in three Cu concentrations: Cu0 (ambient sludge), CuL (30x), CuH (60x). The setup of the experiment was as follows (Fig.1):
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Figure 1: Experimental setup of the interaction experiment. On the horizontal axis the Cu concentrations are shown, Cu0= 198 mg/kg (no spike), CuL= 5940 mg/kg, CuH= 11880 mg/kg. The vertical axis shows the different species, Con= no species, Chi= C. riparius, Phy= P. acuta, C+P= C. riparius & P. acuta.
The experiment consisted of control treatments (no species), single treatment (either C. riparius or
P. acuta) and combination treatments (both species). This resulted in twelve different treatments
(Fig. 1). Cu0 was the ambient sludge, in CuL the sludge was spiked with 30 times the amount of Cu in the control and in CuH the sludge was spiked with 60 times the amount of the control. Different species were added (Con= control, no species, Chi= C. riparius, Phy= P. acuta and C+P= C. riparius +
P. acuta). The C. riparius treatment contained 28 individuals, the P. acuta treatment consisted of 6
individuals and the combination treatment contained 14 C. riparius and 3 P. acuta individuals.
Toxicity experiments
The same procedure was followed in both the range-finding experiment and the interaction experiment. 24 hours before the start of the experiment, the macro-invertebrates were placed in beakers with DSW without food or sludge to empty their stomach and intestines. C. riparius and P.
acuta were kept separately to avoid interaction. After that day, the experiment was initiated with
the introduction of the organisms into the prepared beakers with sludge (+ spiked Cu) and DSW. Both experiments had a duration of 7 days. All beakers were kept at 20 +/- degrees Celsius, closed with a parafilm and the water layer above the sludge was constantly aerated (Hailea aco-2206 (airflow4)). At the start of the experiments, after 3 days and at the end of the 7-day experiments, the oxygen concentration, conductivity, pH and temperature of the overlying water were measured in
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every beaker with a Hach Multimeter. At the end of the 7-day experiment, we collected the macro-invertebrates from the sludge and counted the number of surviving macro-invertebrates for each replicate. The sludge and organisms were dried in the oven at 70 degrees Celsius for 14 hours, after which we determined the dry weight of the sludge and the organisms.
Growth and endpoints
Prior to the experiments a calibration curve was made to convert the length of the C. riparius larvae to the dry weight. C. riparius larvae were photographed per treatment at the start of the
experiments. From these photographs we measured the length of the midges using the Fiji imageJ app. This length was then converted to the theoretical dry weight at the start of the experiment. At the end of the experiment we weighted the dry weight of C. riparius larvae. The average dry weight per individual at the start of the experiment was then subtracted from the average dry weight per individual at the end of the experiment. This data was then used in the data analyses.
At the start of the experiment, the length of the shells of P. acuta were measured and only the snails with a shell length between 5.5 and 6.5 mm were used for the experiment. Using these calibration lines, we chose the densities for the interaction experiment in such a way that the biomasses in the different treatments were equal.
Data analysis
To determine the effect of copper on macroinvertebrate survival and growth and on sludge degradation, tests for significant differences were performed in the statistical program R (R Core Team, 2018). To check whether the assumptions for normality and equal variances were met, the Shapiro-Wilk test and the Levene’s test were applied (citation (‘’car’’)(‘’ dpLyr’’)). In cases where assumptions of normality were not violated an ANOVA was used to test whether the survival and weight of the organisms and the sludge degradation differed significantly between the different treatments. For the data of survival and weight of the organisms the Tuckey’s Honestly Significant Difference (HSD) post-hoc test was used the investigate which groups differed significantly from each other. In some data of the survival, assumptions of normality were not met. There we applied a Kruskal Wallis test with a pairwise Wilcox post-hoc test. From the results of the survival in the range finding experiments LC50 values were derived. The results were visualized in graphs (citation
(‘’tidyverse’’)(‘’ggplot’’)). Data was assumed significant at a p-value lower than 0.05.
To determine any interactive effects on sludge degradation, a predicted sludge degradation was calculated for the combination treatments. Based on the sludge degradation in the single treatments within the different concentrations, a model was created to calculate 4 random degradation values (4 replicates) for the expected sludge degradation in the combination treatments, assuming no facilitation or competition took place. The differences between the observed sludge degradation values (derived from the experiment) and the random sludge degradation values were statistically tested using an ANOVA. This was done for ten different random sludge degradation values, from which the mean p-value was derived.
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Results
Physical and chemical parameters
The Hach measurements of the range finding experiment resulted in the following average values: oxygen content= 7.89 mg/L pH= 7.13, conductivity= 693 us/cm, temperature= 20.25 degrees Celsius. The values from the Hach measurements in the interaction experiment had the following mean: oxygen content= 7.15 mg/L, pH= 7.02, conductivity= 682 us/cm, temperature= 20.5 degrees Celsius. The oxygen content was influenced by the Cu treatment (AOV: df=2; F=3.265; p=0.0497). The Cu and the species as well as the combination of Cu and species all influenced the conductivity (AOV: concentration: df=2; F=54.528, p=1.28e-11, species: df=3; F=13.095; p=6.18e-06,
concentration:species: df=6; F=8.288; p=1.14e-05), since the conductivity in the CuH concentration was significantly higher than the conductivity in CuL and the control (p<0.05). Thereby, the pH affected by the Cu concentrations, but not by the different species treatments (Kruskal-Wallis: concentration: df=2; p=0.02136, species: df=3; p=0.3569). The pH in the CuH concentration was significantly higher compared to the control (p<0.05). In addition, the Cu concentration influenced the temperature (AOV: df=2; F=5.469; p=0.00843), since the temperature in the CuH concentration was significantly higher than in CuL (p<0.05).
Range finding experiment
Survival in the control treatment was above 80% for both species, 88% for P. acuta and 96% for C.
riparius. For P. acuta survival decreased from the concentration Cu30 onward, while for C. riparius a
difference in survival with the control was only observed at the Cu100 concentration. Clear dose-response relationships were obtained for the effect of Cu on the survival of both species. From the results a LC50 of Cu45 (8910 mg/kg dry weight) was derived for P. acuta and a LC50 of Cu62 (12078
mg/kg dry weight) for C. riparius.
Figure 2: Dose-response curve for the effect of Cu on the survival of P. acuta (purple) and C. riparius (blue) at different nominal Cu concentrations on the x-axis (Log). Cu0= 198 mg/kg, Cu3= 594 mg/kg, Cu10= 1980mg/kg, Cu30= 5940 mg/kg, Cu100= 19800 mg/kg dry weight. The y-axis shows the average survival. (%) and standard deviation. The LC50 for both
organisms are visualised with different points (LC50phy, LC50chi) The dose-response curve is based on two replicates for the concentration, Cu3, Cu10 and Cu30 and three replicates for the control and the Cu100 concentration.
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Interaction experiment
Survival of the test organisms
Figure 3: Average survival of C. riparius and P. acuta in the single and combination treatment at different Cu concentrations. The x-axis shows the different treatments, the y-axis shows the average survival (%). Top left (A) = C.
riparius single treatment, top right (B) = P. acuta single treatment, bottom left (B) = C. riparius combination treatment,
bottom right (C) = P. acuta combination treatment. The boxplots show the effect of Cu on the survival of the organisms in single and combination treatment and each treatment consisted of 4 replicates. Different letters ( ) indicate a significant difference in survival between different Cu concentrations within a species treatment.
The survival in all control treatments of the interaction experiment was higher than 80%. Cu0 P.
acuta; 83%, Cu0 C. riparius; 96%, Cu0 C. riparius in combination treatment; 95%, Cu0 P. acuta in the
combination treatment; 83% (Fig. 3).
The survival of C. riparius in the single treatment was not affected by the different Cu concentrations (AOV: df=2; F=3.5; p=0.0751) (Fig. 3A). In contrast, in the combination treatment (C+P) the highest Cu concentration did affect the survival of the C. riparius (AOV: df=2; F=403.7; p=1.55e-09) (Fig. 3C), since the survival in the CuH treatment was significantly lower than in the CuL treatment and the control (Cu0) (p<0.05). The survival at the Cu concentration CuL was not significantly different from the control (p>0.05).
The different Cu concentrations also had an effect on the survival of P. acuta in the single treatments (AOV: df=2; F=77.4; p=2.14e-06) (Fig. 3B), since the survival in the CuH treatment was significantly lower than in the CuL treatment and the control. There was no significant difference in survival between the control and the CuL treatment (p>0.05).
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combination treatment (C+P) (Kruskal-Wallis: df=2; p=0.01616) (Fig. 3D), since the survival in the Cu H treatment was significantly lower than the survival in the CuL treatment and the control (p<0.05). The Cu concentration CuL was not significantly different from the control (p>0.05). There
was no significant difference in survival of P. acuta between the single and combination treatment (p <0.05).
Growth of the test organisms
The different Cu treatments had an effect on the weight increase of C. riparius (AOV: df=5; F=33.59; p=4.05e-08) (Fig. 4). In the single treatment as well as in the combination treatment (C+P) the weight increase in Cu0 and CuL was significantly higher than the weight increase in CuH. In the treatment with only C. riparius and in the combination treatment (C+P) there was no significant difference in weight increase between the Cu0 and CuL treatments. Thereby, the weight increase of C. riparius in the combination treatment (C+P) was significantly higher than the weight increase of C. riparius in the single treatment.
Figure 4: Average weight increase per individual C. riparius for the different Cu treatments in the single and combination treatment. The x-axis shows the different treatments. Cu0, CuL and CuH are the Cu concentration in the treatment with only C. riparius. Cu0 c+p, CuL c+p and CuH c+p are the Cu concentrations in the combination treatment. The Y-axis shows the weight increase of the species within the experiment in milligram and the standard deviation. The boxplot shows the effect of Cu on the weight increase of C. riparius in the single and combination treatments, based on 4 replicates per treatment. Significant differences are visualized by different letters (ac, a, b, c, c).
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Sludge degradation
Figure 5: Degradation of the sludge in milligram per treatment. On the x-axis the different species treatments are shown and at the top of the graph the different Cu concentrations are given. The different colours represent the different Cu concentrations. The y-axis shows the sludge degradation in milligram. The black dots represent the outliers. Con = control, chi = C. riparius, phy = P. acuta, CP = C. riparius and P. acuta. The boxplots shows the effect of Cu and the addition of macroinvertebrates on the sludge degradation. Each treatment consisted of 4 replicates.
The species and the Cu concentrations as well as the combination of species and Cu concentrations had an effect on the sludge degradation (AOV: species: df=3; F=4.745; p=0.006874, concentration: df=3; F=9.120, p=0.000625, species:concentration: df=6; F=5.789; p=0.000268) (Figure 5). The sludge degradation in the CuH concentration was significantly lower than the sludge degradation in the CuL concentration and the control (Cu0) (p<0.05). The sludge degradation in the CuL concentration was not significantly lower the sludge degradation in the control treatments (p>0.05). Thereby, the species treatments with C. riparius (chi) and the combination treatment (C+P) causes a significant increase in sludge degradation compared to the control (con). P. acuta did not cause a significant increase in sludge degradation compared to the control treatment without macroinvertebrates (p>0.05).
Moreover, when the sludge degradation in the CuL concentration of the combination treatment (C+P) was compared to the expected sludge degradation of this treatment, based on the outcomes of the single treatments, the observed sludge degradation in CuL by C+P was significantly higher than the expected sludge degradation (AOV: df=1, F=10.87, p=0.0246). In the Cu concentrations Cu0 and CuH the expected sludge degradation was not significantly different from the observed sludge degradation (p>0.05).
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Discussion
Experimental considerations
We did not analyze the actual Cu exposure concentration of the organisms in the different
treatments, but only the nominal concentrations, which is a limitation of this research. When the Cu concentrations in the sludge would have been measured again at the end of the experiment, we could have determined whether the organisms in the combination treatment in CuL were indeed exposed to lower Cu concentrations than the organisms in the single CuL treatment. However, these measurements did not fit the time frame of this study. Moreover, we observed a negative sludge degradation in the control treatment in the Cu0 concentration. A negative sludge degradation is not possible, as no sludge was added to the beakers during the experiment. To calculate the sludge degradation, the mean weight of 25 ml of dried sludge for all three Cu concentrations was determined at the start of the experiment. The dry weight of the sludge at the end of the
experiment was subtracted from the mean start weight for each replica. This resulted in the actual sludge degradation. The negative sludge degradation may have been caused by variation in the start weight of the sludge. In one 25 ml sludge there may have been a slightly higher concentration of solid matter than in another 25 ml sludge. In addition, there may have been hard pieces in the sludge that cannot be broken down, so that the weight of the sludge remained high. Nonetheless, the present experimental setup allowed us to evaluate the effects of Cu on the sludge degradation by macroinvertebrates with different feeding traits, as discussed below.
Effects of Cu on macroinvertebrates and sludge degradation
It was hypothesized that P. acuta would have a higher sensitivity to Cu than C. riparius (de Haas et al. 2004; Gao et al. 2017). The range finding experiment confirmed this difference in sensitivity. The interaction experiment showed again that the survival of P. acuta in the single treatment as well as in the combination treatment was affected by increased Cu concentrations in the sludge. The survival of C. riparius in the single treatment was not affected by increased Cu concentration in the sludge, CuL as well as CuH did not cause a difference in survival of this species compared to the control (Cu0). Contrary, the survival of C. riparius in the combination treatment was affected by the increased Cu concentrations, since the survival in the CuH treatment was lower than the survival in the Cu0 and CuL treatments. This indicates that the sensitivity of P. acuta to the increased Cu concentrations also affected the survival of C. riparius. This could have been caused the release of waste products, such as ammonia, through the decomposition of the dead snails. Ammonia can be toxic to chironomids (Schubaur‐Berigan et al. 1995) (Monda et al., 1995). The low weight increase of the larvae at the CuH concentration in the single treatment already showed that C. riparius was negatively affected by the high copper concentrations. Therefore, it could be possible that the higher ammonia concentrations in the CuH concentration in the combination treatment became fatal to C.
riparius.
The aim of this research was to investigate the effects of copper on sludge decomposition by macroinvertebrates with different feeding traits. The hypotheses was that survival of the organisms, growth of P. acuta and sludge degradation by P. acuta would already be affected at lower Cu concentrations than C. riparius (Schultheis et al., 1997; Archaimbault et al., 2010). Moreover, it was
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hypothesized that the different feeding traits of C. riparius and P. acuta would result in the two organisms consuming different parts of the OM and thus no competition would take place (Scherer, 2017; Dodds & Whiles, 2010). Survival and growth of the organisms and sludge degradation were indeed negatively affected at higher Cu concentrations, which confirms the hypotheses. Contrary to our hypothesis, in the CuL treatment the observed sludge degradation in the combination treatment was significantly higher than the expected sludge degradation for this treatment, based on the single species treatments. This indicates that facilitation could have taken place between P. acuta and C.
riparius at the CuL concentration. Besides, the weight increase of C. riparius in the combination
treatment at the CuL concentration was significantly higher than the weight increase of C. riparius in
the single treatment at the CuL concentration. This is again an indication that there is facilitation
between the organisms in this treatment, so the results do not support the hypothesis. A possible explanation for the fact that there is more sludge degradation in the combination treatment at the CuL concentration than expected, could be that the presence of the snails decreased the copper exposure of C. riparius. Both the snail itself and the slime trail that the snail leaves behind could act as a sink for the copper, reducing the actual exposure of the chironomids. Previous research showed that Cu bioaccumulation in freshwater snails, including P. acuta, can be high (Spyra et al., 2019; Das & Khangarot, 2011). The bioaccumulation factors of Cu in Lymnaea
luteola range between 2.3 and 18.7 (Das & Khangarot, 2011). In addition, heavy metals, including Cu,
can stick to cytosol (silk) of the caddis fly (Cian & Lyoma, 1998). There are indications that the mucus of snail could also form a sink for contaminants (Triebskorn & Albert, 1989). The copper might therefore have accumulated in the snails or could have been bound to the mucus of P. acuta, so that the final exposure concentration for C. riparius in the combination treatment could have been lower than the exposure concentration in the single treatments. Due to the lower exposure to Cu, the larvae in the combination treatment in CuL could have consumed more sludge and grew more than the larvae in the single treatment the CuL concentration.
What does this mean for the WWTP?
In order to achieve the highest sludge reduction in a WWTP, the degree of sludge contamination should be carefully examined. Sludge from different WWTPs may vary in contamination composition and concentration, influencing the amount of sludge degradation by the macroinvertebrates. When several macroinvertebrate species are jointly present, the exposure to certain contaminants could be reduced by means of bioaccumulation in some species or by the substances they excrete. As a result, a combination of different types of macroinvertebrates could cause more sludge degradation at sublethal contamination levels than when only one type of species is used. However, in highly contaminated sludge, a combination of macroinvertebrates with different sensitivities to certain contaminants could cause higher mortality by all species as a consequences of increased
concentrations of degradation products from the dead species. Therefore, the degree of contamination of WWTP sludge and the different sensitivities of macroinvertebrates should be determined in advance, in order to receive the highest sludge degradation by a combination of different macroinvertebrates. However, although facilitation occurred at the CuL concentration, sludge degradation by the macroinvertebrates was still highest in the ambient sludge (which already had some Cu contamination, 198 mg Cu/kg dry weight sludge). Therefore, for the use of
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macroinvertebrates for waste water sludge decomposition, it is important that sludge contains low contamination levels.
Conclusions
For the use of macroinvertebrates as natural decomposers in WWTPs, the effects of contaminants on sludge degradation by a combination of macroinvertebrate species needs to be known. This research showed that Cu affects the sludge degradation by macroinvertebrates and that P. acuta can facilitate the sludge degradation of C. riparius at increased Cu concentrations. However, if the Cu concentration becomes to high, the survival of C. riparius will be decreased by the presence of P.
acuta. So, at sublethal concentrations of contaminants, facilitation can take place resulting in higher
sludge decomposition rates than in the case of single macroinvertebrate species. When the concentration of the contaminant becomes lethal for one species, the other species may suffer as well. Therefore, the different compositions of sludge and the sensitivity of macroinvertebrate
species need to be investigated to ensure the high sludge reduction and to take full advantage of this method. Hence, macroinvertebrates can facilitate each other’s sludge decomposition as long as the sludge is not too contaminated.
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Acknowledgements
I would like to thank Emma Schroeijers, with whom I conducted the experiments together, for her contribution to this project. I would also like to thanks Lisa van Eck for helping us in conducting the experiments. Thereby, I thank Tom van der Meer and Michiel kraak for their help and guidance during this research.
Appendices
Table 1: Results of the two- way ANOVA for sludge degradation with the F-value, degrees of freedom and the p-value.
F-value Degrees of freedom p-value
Species 4,745 3 0,006874
Concentration 9,120 2 0,000625
Species : Concentration
5,789 6 0,000268
Table 2: Results of the Tuckey’s Honestly Significant Difference (HSD) post-hoc test for the sludge degradation.
Difference Lower bound Upper bound p-value
Chi-con 0.021216154 5.280358e-03 0.037151949 0.0052370 C+P-con 0.016711818 9.518641e-05 0.033328450 0.0482591 Phy-con 0.010309167 -5.942220e-03 0.026560553 0.3342601 C+P-chi -0.004504336 -2.081245e-02 0.011803775 0.8786493 Phy-chi -0.010906987 -2.684278e-02 0.005028808 0.2703601 Phy-C+P -0.006402652 -2.301928e-02 0.010213980 0.7286414 CuH-Cu0 -0.022000354 -0.034773623 -0.009227085 0.0004675 CuL-Cu0 -0.008006604 -0.020779873 0.004766665 0.2882012 CuL-CuH 0.013993750 0.001220481 0.026767019 0.0291619
Table 3: Results of the Tuckey’s Honestly Significant Difference (HSD) post-hoc test for survival of the organisms in the interaction experiment for C. riparius in the single treatment, C. riparius in the combination treatment and P. acuta in the single treatment.
difference Lower bound Upper bound p-value
CuHchi-Cu0chi -8.928571 -18.900020 1.042877 0.0787283 CuLchi-Cu0chi -1.785714 -11.757163 8.185734 0.8731219 CuLchi-CuHchi 7.142857 -2.828591 17.114306 0.1678128 CuHcpchi-Cu0cpchi -87.500000 -97.744690 -77.25531 0.0000000 CuLcpchi-Cu0cpchi 5.357143 -4.887547 15.60183 0.3533915 CuLcpchi-CuHcpchi 92.857143 82.612453 103.10183 0.0000000 CuHphy-Cu0phy -405092.59 -503423.6 -306761.54 0.0000030 CuLphy-Cu0phy -57870.37 -156201.4 40460.68 0.2779418 CuLphy-CuHphy 347222.22 248891.2 445553.27 0.0000108
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Table 4: Results of the pairwise Wilcox post-hoc test for the survival of the P. acuta in the combination treatment. Adjustm ent method ‘BH’. P-value Cu0cpphy-CuLcpphy 1.000 Cu0cpphy-CuHcpphy 0.029 CuLcpphy-CuHcpphy 0.029
Table 5: Results for the Tuckey’s Honestly Significant Difference (HSD) post-hoc test for the weight increase of C. riparius.
difference Lower bound Upper bound p-value
Cu0 c+P-Cu0 0.22632667 -0.08341340 0.53606673 0.2294887 CuH-Cu0 -0.69963333 -1.00937340 -0.38989327 0.0000233 CuH c+P-Cu0 -0.68390667 -1.01503272 -0.35278061 0.0000686 CuL-Cu0 -0.27631833 -0.58605840 0.03342173 0.0951530 CuL C+P-Cu0 0.05311417 -0.25662590 0.36285423 0.9927902 CuH-Cu0 C+P -0.92596000 -1.21272358 -0.63919642 0.0000002 CuH c+p-Cu0 c+p -0.91023333 -0.78940858 -0.60049327 0.0000008 CuL-Cu0 c+p -0.50264500 -0.45997608 -0.21588142 0.0004355 CuL c+p-Cu0 c+p -0.17321250 -0.29401340 0.11355108 0.4117908 CuH c+p-CuH 0.01572667 0.13655142 0.32546673 0.9999800 CuL-CuH 0.42331500 0.46598392 0.71007858 0.0024453 CuL c+p-CuH 0.75274750 0.09784827 1.03951108 0.0000034 CuL-CuH c+p 0.40758833 0.42728077 0.71732840 0.0068043 CuL c+p-CuH c+p 0.73702083 0.04266892 1.04676090 0.0000121 CuL c+p-CuL 0.32943250 0.04266892 0.61619608 0.0197703
