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Article

Distribution of Polybrominated Diphenyl Ethers in Sewage Sludge, Sediments, and Fish from Latvia

by
Juris Aigars
,
Natalija Suhareva
* and
Rita Poikane
Latvian Institute of Aquatic Ecology, Voleru Street 4, Riga LV1007, Latvia
*
Author to whom correspondence should be addressed.
Environments 2017, 4(1), 12; https://doi.org/10.3390/environments4010012
Submission received: 1 December 2016 / Revised: 29 January 2017 / Accepted: 1 February 2017 / Published: 8 February 2017
Browse Figures
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Abstract

:
The polybrominated diphenyl ethers (PBDEs) are bioaccumulative, persistent, and toxic. They have a high risk of emission into the environment via volatile losses and diffuse sources, such as commercial product disposal or the use of sewage sludge. The PBDEs’ congeners were analyzed in municipal waste water treatment plant (WWTP) sludge, river and lake water, sediment, and fish samples, to investigate the concentrations in urban and natural locations. The sum of eight PBDE congener (∑8PBDE 28, 47, 99, 100, 153, 154, 183, 209) concentrations in WWTP sludge varied from 78 ng·g−1 DW, to 714 ng·g−1 DW. The BDE 209 constituted up to 93%–98% of ∑8PBDE. In water, the concentrations of all of the measured PBDE congeners were below the limit of detection. Similarly, the concentration of BDE 209 in the sediments was below the limit of detection in all samples. The sum of seven PBDE congener concentrations in the sediments varied from 0.01 to 0.13 ng·g−1 DW. The sum of eight PBDE congener concentrations in fish (European perch) tissues varied from 0.13 to 0.82 ng·g−1 WW. As was recorded for the WWTP sludge, the BDE 209 was the dominant congener, constituting 24%–93% of ∑8PBDE. The sum of seven PBDE congener concentrations, excluding BDE 209, as well as the concentrations of BDE 209 that were measured in WWTP sludge, exhibited a weak negative correlation (Pearson’s r = −0.56, p = 0.1509 and r = −0.48, p = 0.2256, respectively) with the content of dry matter in the sludge. The sum of seven PBDE congener concentrations measured in sediments exhibited a strong negative correlation (Pearson’s r = −0.82, p = 0.0006) with the content of dry matter in the sediments, and a strong positive correlation (Pearson’s r = 0.68, p = 0.0109) with the total carbon content. The obtained results indicated that the fine-grained WWTP sludge particles, with a larger relative surface area, adsorbed BDE 209 the most effectively. This finding was supported by the relatively low environmental concentrations of PBDE congeners, especially BDE 209, which can be explained by the lack of using sewage sludge in agricultural application in Latvia. Furthermore, it seems that, at present, the observed differences in the PBDE congener concentrations in sediments can be attributed to differences in the physical-chemical properties of sediments.

1. Introduction

The polybrominated diphenyl ethers (PBDEs) are halogenated compounds, which were listed as persistent organic pollutants (POPs) by the Stockholm Convention in 2009 [1]. The lipophilic, bioaccumulative, and toxic nature of these compounds [2], combined with the diversity of sources and transport mechanisms [3,4], have been causing significant public concern during the last decades. Three commercial mixtures (penta-, octa-, and deca-BDE), introduced in the 1970s, have been widely used as additive flame retardants in various industrial applications, such as plastics, textiles, electronics, building materials, furniture, and other products for manufacturing [3,5,6]. However, they have a high risk of emission into the environment [7]. Due to volatile losses and discharges during the constant use and recycling of the products containing these compounds, the diffuse sources of PBDEs, represented by commercial product disposal, the use of sewage sludge, agricultural run-off, and domestic wastewater [8,9], become even more significant than the point sources [10], imposing an additional environmental concern.
The first recorded detection of the presence of PBDEs in the environment was published by Andersson and Blomqvist, in 1981 [11]. Since then, PBDEs have been found in various environmental and biological samples across the globe [4,12,13,14,15]. Notably, the contamination of PBDEs was even reported in places with no local point source or industrial production [16,17]. PBDEs tightly bind to solid particles due to their properties [14], however, they can be transferred to the air due to volatilization [10], and transported over large distances. In the environment, PBDEs are transferred to aquatic systems, accumulated in sediments and biota [3,10,13], and are eventually biomagnified in top predators [18,19,20], to the point at which they can be transferred to humans through the consumption of contaminated food sources [2]. The transport mechanism described above is supported by environmental studies, which report on the increased levels of tetra- to deca-BDE isomers found in marine mammals, bird eggs, and human tissues [5,14]. According to several recent studies, the toxic effect caused by PBDEs can be observed as suppression of the immune system, reproductive dysfunction, endocrine disruption, change of thyroid hormone levels [5,8,21,22,23], damage of liver and kidney morphology, and fetal toxicity/teratogenicity cases [24,25,26,27,28,29]. Due to the toxicological effects, the production of PBDE congeners (penta- and octa-BDE) and their commercial availability were banned in the European Union [30,31,32]. These restrictions promoted a general decrease of PBDE concentrations in soils within Europe [33]. In addition, a decline of penta- and octa-mix PBDE concentrations has been observed in sewage sludge during recent years [34]. At the same time, concentrations of BDE 209 in sewage sludge, have exhibited a clear increase between 2004 and 2010 [34]. This fact poses a serious environmental concern, since current evidence suggests that some aquatic organisms, including fish, have a capacity to de-brominate BDE 209 to lower-brominated congeners [35,36], which have higher mobility and toxicological properties. Furthermore, it has been demonstrated that benthic fauna is able to re-mobilize buried PBDEs from sediments [37], and consequently, sediments become an important secondary source of these compounds.
The aim of this study was to evaluate the concentration levels and composition of PBDE congeners in the water, fish tissues, and sediments, as well as in the sludge collected from different WWTPs in Latvia.

2. Materials and Methods

Sewage sludge samples from effluent, after the dewatering step, were collected from eight urban WWTPs (Table 1), located in the biggest cities and smaller towns of Latvia. The WWTPs were selected based on a range of city sizes and the type of effluents treated by WWTPs.
The water and sediment samples were collected from sampling locations of five rivers and eight lakes (Table 2). Samples of fish dorsal muscles were collected from the same sampling sites as the sediment samples (Table 2), however, the biomass was only sufficient for analysis purposesin 10 cases out of the 13 sampled biota European perch (Perca fluviatilis),. The selection of the sampling sites was based on previously reported cases of trans-boundary impact, and the human influence on urban, agricultural, or industrial land use location. The selection of European perch (Perca fluviatilis) for the biota matrix was based on its trophic level (predator), and the high abundance of the species occurring in both fresh and brackish waters of the region.

2.1. Sample Collection

The sewage sludge, water, and sediment samples were placed and kept in previously unused amber-glass sample containers, precleaned and Certified to meet US EPA performance-based specification.
The integrated (1 h) sewage sludge samples were collected between June 2010 and February 2011 by the WWTP operational staff in 500 mL containers, and were covered by polytetrafluoroethylene-lined (PTFE) plastic screw-caps. To avoid the adsorption of PBDEs at the PTFE parts of the screw-cap, the container neck was kept isolated by aluminum folium.
The water and sediment samples were collected between the July and September of 2012. Water was sampled by a Van Dorn water sampler 0.3–0.5 m below the water surface, and immediately upon sampling, the water was transferred to prepared glass jars. Sediment samples were collected with a hand-operated Wildco Ponar or VanVeen bottom grab sampler. Sampling was performed at five to seven points around the observation site. All sub-samples were mixed together and sieved, to remove particles larger than 2.0 mm. Sieved sediment samples were then transferred to prepared glass jars.
European perch (Perca fluviatilis) individuals were sampled by means of fish hooks. Sampling was performed by dully authorized personnel, possessing valid fishing permits. Thereafter, the fish tissues were obtained for analysis, in accordance with animal ethic care guidelines. Every sample collected during the study was directly transported from the sampling site to the laboratory, in a mobile cool box filled with cooling agent cartridges.
The obtained sewage sludge, water, and sediment samples were stored in dark conditions, at a temperature of 4–8 °C, until the chemical analysis had been performed. The soft tissues obtained from the fish were stored in a freezer at a temperature of −18 °C, until the chemical analysis had been carried out.

2.2. Analytical Procedures

The pretreatment and analyses of all types of the samples were performed according to the method US EPA 1614, with modification. Water and sewage sludge samples were analyzed by the accredited commercial laboratory, ALS Laboratory Group (Czech Republic), with the estimation of uncertainty for each PBDE congener being equal to 30%. Sediments and fish samples were treated on a commercial basis by the Institute of Food Safety, Animal Health, and Environment–“BIOR” (Latvia), and the recovery range for the PBDEs was 75%–123%. The method of determining the PBDEs in the required matrices was accredited for both engaged laboratories. The limits of quantification were defined on the basis of the blank level (see Supplementary Materials).

2.2.1. Sample Preparation and Clean-Up for PBDEs Analysis

Sample aliquots of sediment (10 ± 2 g) and the fresh dorsal muscle of fish (10 ± 2 g), were spiked with 500 µL of 13C12-labeled PBDE 138 congener mixture solution, diluted with toluene to a final concentration of 1–5 pg·µL−1, before being mixed with 100 g of anhydrous sodium sulfate. After equilibration for 12 h, at UV-protected conditions, e.g., room temperature under an aluminum foil cover, the samples were ground and extracted, using Soxhlet extraction with a dichloromethane/n-hexane (1:1, v/v) mixture for at least 16 h. The extracts were filled into round-bottom flasks and the solvent was removed using a rotary evaporator at <30 °C. The high molecular substances were removed by gel permeation chromatography (GPC). The system was equipped with a glass column (50 × 2.5 cm), filled with 50 g of non-polar divinyl-benzene/styrene copolymer Bio-Beads S-X3 (Bio-Rad, Philadelphia, PA, USA, 3% cross linkage, 40–80 µm bead size, ≤2000 MW limit) stationary phase, and eluted with cyclohexane/ethyl acetate (1:1, v/v) mobile phase, at a flow rate of 5 mL#xB7;min−1. The automated GPC program was as follows: dump time 0–19 min, collection time 19–45 min; the collected eluate was concentrated by rotary evaporation at <30 °C. The pre-purified sample extract was placed on top of a glass column (25 × 1.2 cm) filled with 2.5 g of silica gel, containing 50% (v/v) sulfuric acid for the degradation of remaining lipids. The analytes were eluted with 1.0 mL of toluene, and subsequently, with 25 mL of n-hexane. After rotary evaporation to about 150–200 µL, the sample extracts were transferred to 2 mL chromatographic vials, treated with 37 N sulfuric acid (30 µL), and mixed. The mixture was allowed to stand for 20 min, before being centrifuged at 3000 rpm (1508 RCF), in order to separate the acidic and organic layers. The acidic bottom layer was discarded, the organic layer was evaporated, and recovery standard (13C12 PBDE 138) solution in n-nonane was added until the solution was 50 µL, at which point content of PBDEs was analyzed [38].

2.2.2. Instrumental Analysis and Quantification of PBDEs by GC-HRMS

The instrumental analysis was performed by a Micromass Autospec Premier high resolution mass spectrometer (Milford, CT, USA), coupled with an Agilent 6890 N gas chromatograph (Santa Clara, CA, USA), according to the procedure and GC conditions described by Zacs, et al. [38].

2.2.3. Analysis of Dry Matter Content, Total Carbon, and Lipid Content

The dry-matter content of fish muscle, sediment, and sludge samples, was detected by a gravimetric method, during which separate wet subsamples were dried at 105 ± 5 °C until a constant dry weight was observed.
The total content of carbon in the sediments was determined according to the ISO method 10694:1995, “Soil quality—Determination of organic and total carbon after dry combustion (elementary analysis)”. A 2 mg DW sub-sample was used to measure the total content of carbon, and was recorded by a Vario EL III CHNOS Elemental Analyzer (Elementar Analysensysteme GmbH, Langenselbold, Germany).
A 20 g DW sub-sample was used in Soxhlet extraction with a dichloromethane and n-hexane (1:1, v/v) mixture, in order to determine the lipid content. The extraction time was 16 h, after which the extracts were filled into pre-weighted round-bottom flasks for solvent evaporation, by a rotary evaporator at <30 °C. The lipid content was determined gravimetrically.

2.3. Data Exploration and Statistical Assessment

Data exploration and statistical analyses were performed using R software for Windows, Release 3.3.2. The strength of the linear associations between the measured PBDE concentrations, content of dry matter (DM) in sewage sludge, content of dry material (DW), total organic carbon (TOC) in sediments, and content of lipids in fish samples, was investigated by means of the Pearson Correlation Coefficient, with a statistical significance level set at α = 0.05. Simple regression models with a single independent parameter were developed, to evaluate the dependence of the concentration of BDE 209 on the content of dry matter in sewage sludge, and the variations in the PBDEs concentrations, depending on the content of dry matter and the total organic carbon in sediment samples. The obtained regression models were evaluated via regression diagnostic tools, including graphical methods and formal statistical tests.

3. Results

3.1. WWTP Sludge

The concentrations of PBDE congeners (BDE 28, 47, 99, 100, 153, 154, 183, 209) in WWTPs sludge ranged from 0.1 ng·g−1 DW (BDE 28) to 700 ng·g−1 DW (BDE 209). Both values were observed at the Valmiera WWTP (Figure 1). The sum of all of the detected congeners (∑8PBDE) varied substantially among WWTPs, from 78 ng·g−1 DW at the Liepaja WWTP, to 714 ng·g−1 DW at the Valmiera WWTP. The concentrations of PBDEs in the sewage sludge reported in this study, are at the low end of the wide concentration range reported elsewhere for WWTPs’ sludge [6,39,40], and similar to the earlier studies, the concentrations of BDE 209 (on average 296 ng·g−1 DW) constituted 89%–98% of the ∑8PBDE concentration registered. The second (BDE 99) and third (BDE 47) most abundant PBDE congeners corresponded to only 0.8%–4.9% and 0.7%–4.4% of the ∑8PBDE, respectively, while the remaining congeners constituted less than 1% of the ∑8PBDE.
The average concentration of the PBDEs, excluding BDE 209, (∑7PBDE) was 13 ng·g−1 DW. The ∑7PBDE, as well as BDE 209, exhibited a weak negative correlation (Pearson’s r = −0.56, p = 0.1509 and r = −0.48, p = 0.2256, respectively) with the dry-matter content of WWTP sludge (Table 3). The correlation between BDE 209 and the dry-matter content of WWTP sludge is substantially improved (Pearson’s r = −0.98, p = 0.0008) if the data from two WWTPs, Saldus and Rezekne, are not included in the analysis (Table 3). The decision to exclude the outlying observations was based on the statistical diagnosis of linear regression (Figure 2), and a comparison of the significance levels of the accessed interactions (p-value = 0.2256 for initial model versus p-value = 8.018 × 10−4 for the ameliorated model). At the same time, BDE 209 concentration did not exhibit significant correlation with concentrations of other congeners (Table 3).

3.2. Water and Sediments

The concentrations of all measured PBDE congeners, in all of the water samples, were between the limit of detection (LOD) and the limit of quantification (LOQ). The LOD and LOQ of congeners (BDE 28, 47, 99, 100, 153 and 154), for which the sum of the Ecological Quality Standard (EQS) (140 ng·L−1) is set in Directive 2013/39/EU for inland surface waters, varied in the samples, between 0.8 and 1.1 ng·L−1 for LOD, and 1.7 and 2.3 ng·L−1 for LOQ. For these congeners, it is possible to use LOD values to calculate the assumed maximal concentration of 2.3 ng·L−1. This estimated concentration is below the EQS that is set in Directive 2013/39/EU. The congeners BDE 183 and 209 are not included in the group of priority PBDEs, for which the EQS is set. However, it is reasonable to evaluate their concentrations in water due to the ability of biological organisms to de-brominate them to lower-brominated congeners. Since the possible concentrations of BDE 183 (below LOQ 0.38 ng·L−1) and BDE 209 (below LOQ 2.70 ng·L−1) could also be considered as very low, it can be safe to assume that the set EQS would not be exceeded, even if all of the BDE 183 and 209 would be de-brominated.
The concentrations of BDE 209 in sediments were below LOD (0.2 ng·g−1 DW) in all samples. The concentrations of other PBDE congeners in sediment samples (Figure 3) varied significantly, from 1.3 × 10−4 ng·g−1 DW for BDE 28 in the sediments of river Pedele, to 0.052 ng·g−1 DW for BDE 47 in the sediments of lake Trikata. Similarly, as is the case for WWTP sludge, the levels of PBDE congeners and the ∑7PBDE (range 0.01–0.13 ng·g−1 DW, on average 0.05 ng·g−1 DW) detected in the sediments, were on the low end of the range of values observed elsewhere [10,41,42].
The ∑7PBDE exhibited non-linear relations (Figure 4) and a significant (Pearson’s r = −0.82, p = 0.0006) negative correlation with the content of dry matter, and a positive (Pearson’s r = 0.68, p = 0.0107) nonlinear correlation with the total content of carbon in the sediments (Table 4).

3.3. Fish

The PBDE congener concentration range (Figure 5) in analyzed fish tissues ranged from 3 × 10−4 ng·g−1 WW (BDE 28 in lake Murats), to 0.36 ng·g−1 WW (BDE 209 in lake Trikata). Similar to sewage sludge, BDE 209 was a dominant congener, constituting 24%–93% (53% on average) of the ∑PBDE8.
The concentrations of BDE 47, BDE 99, BDE 100, BDE 153, and BDE 154, constituted 18.6%, 7%, 4.9%, 1.5%, and 3.2%, respectively, of the total, while other PBDE congeners represented less than 1% of the total amount. The accumulation of BDE 209 in the fish tissues observed in this study, is consistent with previous observations [43,44]. It is important to note that the sum of the concentrations of the congener numbers 28, 47, 99, 100, 153, and 154 (range from 0.017 to 0.624 ng·g−1 WW), exceeded the EQS (0.0085 ng·g−1 WW) set for biota in Directive 2013/39/EU, in all of the rivers and lakes targeted by this study.
The majority of the investigated PBDE congeners demonstrated a good correlation among themselves, except for the concentrations of BDE 209 and BDE 183, which did not correlate to any of the other congeners (Table 5). The established lipophilic properties of PBDEs [2] have been previously used to explain the accumulation of PBDEs in fish tissues, corresponding to their lipid content [45]. However, in our study, only the concentrations of BDE 183 exhibited a medium-strong correlation (Table 5) with the lipid content of fish tissues (Pearson’s r = 0.46, p = 0.1803). The lipid content of the fish tissues observed in this study was between 1.1% and 3.5%. This is at the low end of the lipid content range presented in previous studies [44]. Therefore, we have to assume that, in our study area, factors other than the lipid content could also be important. For example, Bertelsen et al. [46] suggested that proteins and other non-lipid components have a large influence on the bioaccumulation of PBDEs, if the lipid content is low. However, since we did not measure proteins or other non-lipid parameters in our experiment, we have no observational data to support the conclusion on the importance of proteins, or other components, on the accumulation of PBDEs.

4. Discussion

The largest variations for a single congener in the WWTPs, were observed for BDE 209, as has also been observed in previous studies [6], while the levels of other congeners exhibited lower levels of variation. The observed variability in the BDE 209 levels could not be attributed to the city size, or the capacity of the WWTP, which is in agreement with conclusions from earlier studies [47]. At the same time, the approach for explaining the variance in BDE 209 levels, in relation to the different effluent types, e.g., industrial versus domestic [6], cannot be used in this study, since domestic sources of waste water dominated over industrial sources, in all cases. We cannot exclude that, in cities, such as Valmiera or Dobele, where comparatively high levels of BDE 209 in WWTP sludge were observed, the elevated BDE 209 input was generated by industrial objects. However, to the best of our knowledge, this is not the case. So, it is plausible to assume that the generation of the BDE 209 load per inhabitant, could be rather similar in all observed cities, but the capacity of WWTP to trap BDE 209, is different, depending on sludge properties. This assumption is supported by the observed negative correlation (r = −0.48, p = 0.2256) between the content of dry matter and the BDE 209 concentration (Table 3), which clearly demonstrates that fine-grained sludge particles, with a larger relative surface area, adsorb BDE 209 much more effectively than relatively coarser-grained sludge particles (Figure 2). At the same time, it should be recognized that this correlation is built on a limited number of observation points, and two cases clearly diverge from the obtained linear regression curve (Figure 2). Therefore, prior to drawing a final conclusion, the factors that can possibly affect the effectiveness of BDE 209 retention in WWTP sludge, should be tested in a more detailed study.
It should be noted that the effectiveness of BDE 209 removal by WWTP sludge, poses a certain problem in relation to the widely practiced land-application of sludge in agriculture [6,47]. As has been previously shown, terrestrial plants can de-brominate BDE 209 to more mobile and toxic congeners [48,49]. Furthermore, substantial amounts of sludge applied to land are bound to enter aquatic environments, due to soil erosion. Although it can be expected that sludge particles will rapidly settle on the water basin floor, the ability of benthic animals to re-mobilize brominated flame retardants from sediments, can create a secondary pollution source [37]. Thereafter, the re-mobilized BDE 209 can be de-brominated by aquatic biota [35,36]. Since the fine-grained WWTP sludge, exhibiting a high capacity to accumulate BDE 209, would be best suited for land-application purposes, it is very likely that substantial amounts of BDE 209 might be introduced into the environment as a result of poorly evaluated WWTP sludge management actions.
The environmental concentrations of PBDE congeners observed in this study, especially BDE 209, are relatively low in comparison to previously reported values [10,41,42]. This can most likely be explained by the lack of using sewage sludge in agricultural applications in Latvia. Furthermore, it seems that, at present, the observed differences of PBDE congener concentrations in lake and river sediments, can be attributed to differences in sediment properties. For example, the sediments that have a low content of dry matter, and a relatively high content of organic carbon, exhibit substantially higher concentrations of PBDEs than those with a high content of sediment dry matter (Figure 4).

5. Conclusions

Although, relatively low environmental concentrations were indicated during the study, the risk of future concentration increase in the environment exists since WWTP sludge can be considered as a resource of monetary benefit and due to continuous investments in WWTP sector there is steady growing pressure on WWTP sludge utilization capacity. Therefore, it is necessary to invest particular attention to WWTP sludge utilization management practices and if necessary to modify them basing recommendations on further more detailed study about sewage sludge retention properties and affecting factors.

Supplementary Materials

The following are available online at www.mdpi.com/2076-3298/4/1/12/s1, Table S1: Concentrations of PBDEs (ng·g−1) and content of dry matter (DM) in sewage sludge, Table S2: Concentrations of PBDEs (ng·g−1), content of dry material (DW) and total organic carbon (TOC) in sediments, Table S3: Concentrations of PBDEs (ng·g−1) and content of lipids in tissues of European perch (Perca fluviatilis), Table S4: Limits of detection of PBDE concentration in water samples.

Acknowledgments

The study was supported by LIFE+ project “Baltic Actions for the reduction of Pollution of the Baltic Sea from Priority Hazardous Substances” (Project nr. LIFE07 ENV EE 000122) and Estonia-Latvia program project “Towards joint management of the transboundary Gauja/Koiva river basin district” (EU 38839).

Author Contributions

Juris Aigars analyzed the data. Juris Aigars and Natalija Suhareva were involved in writing the paper. Rita Poikane designed the experiments, performed the sampling campaign, and was involved in sample pretreatment and data interpretation.

Conflicts of Interest

The authors declare no conflict of interest.

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Environments 04 00012 g001 550
Figure 1. Concentrations of PBDEs in sewage sludge from eight urban WWTPs in Latvia.
Figure 1. Concentrations of PBDEs in sewage sludge from eight urban WWTPs in Latvia.
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Figure 2. Linear regression curve of BDE 209 concentrations with the sewage sludge content of dry matter.
Figure 2. Linear regression curve of BDE 209 concentrations with the sewage sludge content of dry matter.
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Figure 3. Concentrations of PBDEs in sediments from rivers and lakes in Latvia.
Figure 3. Concentrations of PBDEs in sediments from rivers and lakes in Latvia.
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Figure 4. Non-linear regression showing dependency of ∑7PBDE concentration from the sediment content of dry matter in lakes and rivers of Latvia.
Figure 4. Non-linear regression showing dependency of ∑7PBDE concentration from the sediment content of dry matter in lakes and rivers of Latvia.
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Figure 5. Concentrations of PBDEs and lipid content in tissues of European perch (Perca fluviatilis) from rivers and lakes of Latvia.
Figure 5. Concentrations of PBDEs and lipid content in tissues of European perch (Perca fluviatilis) from rivers and lakes of Latvia.
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Table
Table 1. General information on city-size, waste water type, and the amount treated by WWTP.
Table 1. General information on city-size, waste water type, and the amount treated by WWTP.
WWTPPopulation, InhabitantsTreatment, m3/DayWaste Water Type
Riga WWTP696,593350,000Municipal and industrial waste water
Daugavpils WWTP96,02812,600Municipal and manufacturing waste water, rain water
Liepaja WWTP78,41318,400Municipal waste water, manufacturing and industrial waste water
Ventspils WWTP40,05719,200Municipal and manufacturing waste water
Rezekne WWTP31,5915600Municipal waste water and bio-toilets, manufacturing and industrial waste water
Valmiera WWTP25,3185000Municipal waste water
Saldus WWTP11,6252900Municipal waste water only
Dobele WWTP10,2313500Industrial and municipal waste water
Table
Table 2. Description of the investigated water bodies and sediment characteristics.
Table 2. Description of the investigated water bodies and sediment characteristics.
NameTypeCoordinates WGS84Mean Depth, mLength, kmSurface Area, haBiota SampledSediments
DM (%) OC (%)
Salacariver57.756183, 24.3510690.1595NAYes61.11.88
Mazsalacariver57.857745, 25.0514840.1595NAYes80.00.17
Pedeleriver57.778913, 26.0244000.331NANo81.30.16
Gaujariver57.160162, 24.2657242.0452NAYes68.00.47
Abulsriver57.549172, 25.6805120.452NANo58.91.92
Dūņezerslake57.150275, 24.3584431.1NA145.6Yes17.618.9
Burtniekslake57.740413, 25.2411862.9NA4006.0Yes14.010.5
Murātslake57.575807, 27.0857492.2NA77.5Yes15,214.7
Juverislake57.218670, 25.6766068.5NA77.5Yes16.411.2
Lizdoleslake57.293444, 25.8383924.4NA53.9Yes8.815.7
Trikātaslake57.541006, 25.7149021.8NA13.0Yes8.110.5
Alaukstslake57.091547, 25.7743423.3NA774.8No7.016.4
Limbažulake57.486541, 24.6990413.8NA24.8Yes47.215.4
NA: not applicable.
Table
Table 3. Pearson correlation coefficients and p-values calculated for PBDE concentrations and the content of dry matter analyzed in sewage sludge samples.
Table 3. Pearson correlation coefficients and p-values calculated for PBDE concentrations and the content of dry matter analyzed in sewage sludge samples.
SludgeBDE 28BDE 47BDE 99BDE 100BDE 153BDE 154BDE 183BDE 209∑7PBDEBDE 209 6 WWTPs 1DM 2
BDE 281.00−0.50−0.20−0.860.310.630.14−0.44−0.320.25−0.39R
BDE 470.31721.000.820.720.740.780.720.250.970.45−0.55
BDE 990.70650.01211.000.780.510.640.390.310.930.42−0.38
BDE 1000.02630.04550.02171.000.200.280.350.470.750.42−0.19
BDE 1530.54950.03700.20130.63381.000.850.710.190.720.59−0.74
BDE 1540.18080.02340.08870.49670.00741.000.74−0.030.800.60−0.73
BDE 1830.78740.04500.34150.38990.04910.03561.000.310.650.69−0.73
BDE 2090.37960.55180.45470.24350.64580.93940.46131.000.30−−0.48
∑7PBDE0.5378<0.00010.00080.03120.04490.01790.07920.46931.000.50−0.56
BDE 209 6WWTPs 10.75310.36670.40480.40990.21870.20350.1293-0.30841.00−0.98
DM20.44950.16060.35500.65570.03550.03910.04170.22560.15090.00081.00
p
1 Concentration of BDE 209, excluding values from Rezekne WWTP and Saldus WWTP; 2 Content of dry matter (%).
Table
Table 4. Pearson correlation coefficients and p-values calculated for PBDE concentrations, the content of dry material, and the total organic carbon analyzed in sediment samples.
Table 4. Pearson correlation coefficients and p-values calculated for PBDE concentrations, the content of dry material, and the total organic carbon analyzed in sediment samples.
SedimentsBDE 28BDE 47BDE 99BDE 100BDE 153BDE 154BDE 183DW 1∑7PBDETOC 2
BDE 281.00−0.15−0.040.100.12−0.16−0.010.07−0.070.36R
BDE 470.63521.000.960.770.820.780.79−0.740.980.57
BDE 990.9065<0.00011.000.880.840.670.70−0.670.940.51
BDE 1000.73580.0021<0.00011.000.750.610.63−0.520.770.42
BDE 1530.68710.00060.00030.00341.000.430.44−0.370.780.34
BDE 1540.60480.00150.01280.02740.14401.000.98−0.800.830.70
BDE 1830.96770.00130.00830.02010.1279<0.00011.00−0.840.850.80
DW 10.80800.00360.01220.06820.21740.00110.00041.00−0.82−0.86
∑7PBDE0.8104<0.0001<0.00010.00220.00170.00050.00030.00061.000.68
TOC 20.23350.04260.07780.15800.25190.00770.00110.00020.01071.00
p
1 Content of dry material (%); 2 Content of total organic carbon (%).
Table
Table 5. Pearson correlation coefficients and p-values calculated for PBDE concentrations and the content of lipids analyzed in tissues of European perch (Perca fluviatilis).
Table 5. Pearson correlation coefficients and p-values calculated for PBDE concentrations and the content of lipids analyzed in tissues of European perch (Perca fluviatilis).
FishBDE 28BDE 47BDE 99BDE 100BDE 153BDE 154BDE 183BDE 209∑7PBDELipids (%)
BDE 281.000.960.800.910.840.970.620.150.930.24R
BDE 47<0.00011.000.920.980.940.990.520.110.990.06
BDE 990.00600.00021.000.920.960.900.400.030.95−0.22
BDE 1000.0003<0.00010.00021.000.970.980.450.080.98−0.03
BDE 1530.0024<0.0001<0.0001<0.00011.000.950.440.020.97−0.09
BDE 154<0.0001<0.00010.0003<0.0001<0.00011.000.550.110.990.10
BDE 1830.05740.12710.25580.19210.20170.09951.000.000.490.46
BDE 2090.66940.76700.93730.81860.94890.77120.99631.000.090.23
∑7PBDE0.0001<0.0001<0.0001<0.0001<0.0001<0.00010.14970.81461.00−0.01
Lipids (%)0.49650.86120.54780.93360.81350.77470.18030.51470.97291.00
p

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Aigars, J.; Suhareva, N.; Poikane, R. Distribution of Polybrominated Diphenyl Ethers in Sewage Sludge, Sediments, and Fish from Latvia. Environments 2017, 4, 12. https://doi.org/10.3390/environments4010012

AMA Style

Aigars J, Suhareva N, Poikane R. Distribution of Polybrominated Diphenyl Ethers in Sewage Sludge, Sediments, and Fish from Latvia. Environments. 2017; 4(1):12. https://doi.org/10.3390/environments4010012

Chicago/Turabian Style

Aigars, Juris, Natalija Suhareva, and Rita Poikane. 2017. "Distribution of Polybrominated Diphenyl Ethers in Sewage Sludge, Sediments, and Fish from Latvia" Environments 4, no. 1: 12. https://doi.org/10.3390/environments4010012

APA Style

Aigars, J., Suhareva, N., & Poikane, R. (2017). Distribution of Polybrominated Diphenyl Ethers in Sewage Sludge, Sediments, and Fish from Latvia. Environments, 4(1), 12. https://doi.org/10.3390/environments4010012

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