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

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 (∑ 8 PBDE 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 ∑ 8 PBDE. 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 ∑ 8 PBDE. 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.

Full text

environments
Article
Distribution of Polybrominated Diphenyl Ethers in
Sewage Sludge, Sediments, and Fish from Latvia
Juris Aigars, Natalija Suhareva * and Rita Poikane
Latvian Institute of Aquatic Ecology, Voleru Street 4, Riga LV1007, Latvia; juris.aigars@lhei.lv (J.A.);
rita.poikane@lhei.lv (R.P.)
*Correspondence: natalija.suhareva@lhei.lv; Tel.: +371-2-601-7080
Academic Editor: Yu-Pin Lin
Received: 1 December 2016; Accepted: 1 February 2017; Published: 8 February 2017
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 (
∑8
PBDE 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
∑8
PBDE. 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
∑8
PBDE. 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.
Keywords: PBDEs; sewage sludge; sediments; fish; distribution
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
Environments 2017,4, 12; doi:10.3390/environments4010012 www.mdpi.com/journal/environments

Environments 2017,4, 12 2 of 16
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
–
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
–
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
–
23
], damage of liver and
kidney morphology, and fetal toxicity/teratogenicity cases [
24
–
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
–
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.
Table 1. General information on city-size, waste water type, and the amount treated by WWTP.
WWTP Population,
Inhabitants
Treatment,
m3/Day Waste Water Type
Riga WWTP 696,593 350,000 Municipal and industrial waste water
Daugavpils WWTP 96,028 12,600
Municipal and manufacturing waste water, rain water
Liepaja WWTP 78,413 18,400 Municipal waste water, manufacturing and industrial
waste water
Ventspils WWTP 40,057 19,200 Municipal and manufacturing waste water
Rezekne WWTP 31,591 5600 Municipal waste water and bio-toilets, manufacturing
and industrial waste water
Valmiera WWTP 25,318 5000 Municipal waste water
Saldus WWTP 11,625 2900 Municipal waste water only
Dobele WWTP 10,231 3500 Industrial and municipal waste water

Environments 2017,4, 12 3 of 16
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.
Table 2. Description of the investigated water bodies and sediment characteristics.
Name Type Coordinates
WGS84
Mean
Depth, m
Length,
km
Surface
Area, ha
Biota
Sampled
Sediments
DM (%) OC (%)
Salaca river 57.756183,
24.351069 0.15 95 NA Yes 61.1 1.88
Mazsalaca
river 57.857745,
25.051484 0.15 95 NA Yes 80.0 0.17
Pedele river 57.778913,
26.024400 0.3 31 NA No 81.3 0.16
Gauja river 57.160162,
24.265724 2.0 452 NA Yes 68.0 0.47
Abuls river 57.549172,
25.680512 0.4 52 NA No 58.9 1.92
D
¯
u
n¸
ezers
lake 57.150275,
24.358443 1.1 NA 145.6 Yes 17.6 18.9
Burtnieks
lake 57.740413,
25.241186 2.9 NA 4006.0 Yes 14.0 10.5
Mur¯
ats lake 57.575807,
27.085749 2.2 NA 77.5 Yes 15,2 14.7
Juveris lake 57.218670,
25.676606 8.5 NA 77.5 Yes 16.4 11.2
Lizdoles lake 57.293444,
25.838392 4.4 NA 53.9 Yes 8.8 15.7
Trik¯
atas lake 57.541006,
25.714902 1.8 NA 13.0 Yes 8.1 10.5
Alauksts lake 57.091547,
25.774342 3.3 NA 774.8 No 7.0 16.4
Limbažu lake 57.486541,
24.699041 3.8 NA 24.8 Yes 47.2 15.4
NA: not applicable.
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,

Environments 2017,4, 12 4 of 16
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
µ
L of
13
C
12
-labeled PBDE 138 congener mixture solution, diluted with toluene
to a final concentration of 1–5 pg
·µ
L
−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
µ
m 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
·
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
µ
L, the sample
extracts were transferred to 2 mL chromatographic vials, treated with 37 N sulfuric acid (30
µ
L), 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 (
13
C
12
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].

Environments 2017,4, 12 5 of 16
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 (
∑8
PBDE) 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
∑8
PBDE
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
∑8
PBDE, respectively, while the remaining
congeners constituted less than 1% of the ∑8PBDE.
The average concentration of the PBDEs, excluding BDE 209, (
∑7
PBDE) was 13 ng
·
g
−1
DW.
The
∑7
PBDE, 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).

Environments 2017,4, 12 6 of 16
Environments 2017, 4, 12 6 of 18
Figure 1. Concentrations of PBDEs in sewage sludge from eight urban WWTPs in Latvia.
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).
Figure 1. Concentrations of PBDEs in sewage sludge from eight urban WWTPs in Latvia.
Environments 2017, 4, 12 7 of 18
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.

Environments 2017,4, 12 7 of 16
Table 3. Pearson correlation coefficients and p-values calculated for PBDE concentrations and the content of dry matter analyzed in sewage sludge samples.
Sludge BDE 28 BDE 47 BDE 99 BDE 100 BDE 153 BDE 154 BDE 183 BDE 209 ∑
∑
∑7PBDE BDE 209 6 WWTPs 1DM 2
BDE 28 1.00 −0.50 −0.20 −0.86 0.31 0.63 0.14 −0.44 −0.32 0.25 −0.39
R
BDE 47 0.3172 1.00 0.82 0.72 0.74 0.78 0.72 0.25 0.97 0.45 −0.55
BDE 99 0.7065 0.0121 1.00 0.78 0.51 0.64 0.39 0.31 0.93 0.42 −0.38
BDE 100 0.0263 0.0455 0.0217 1.00 0.20 0.28 0.35 0.47 0.75 0.42 −0.19
BDE 153 0.5495 0.0370 0.2013 0.6338 1.00 0.85 0.71 0.19 0.72 0.59 −0.74
BDE 154 0.1808 0.0234 0.0887 0.4967 0.0074 1.00 0.74 −0.03 0.80 0.60 −0.73
BDE 183 0.7874 0.0450 0.3415 0.3899 0.0491 0.0356 1.00 0.31 0.65 0.69 −0.73
BDE 209 0.3796 0.5518 0.4547 0.2435 0.6458 0.9394 0.4613 1.00 0.30 − −0.48
∑7PBDE 0.5378 <0.0001 0.0008 0.0312 0.0449 0.0179 0.0792 0.4693 1.00 0.50 −0.56
BDE 209 6WWTPs 10.7531 0.3667 0.4048 0.4099 0.2187 0.2035 0.1293 - 0.3084 1.00 −0.98
DM20.4495 0.1606 0.3550 0.6557 0.0355 0.0391 0.0417 0.2256 0.1509 0.0008 1.00
p
1Concentration of BDE 209, excluding values from Rezekne WWTP and Saldus WWTP; 2Content of dry matter (%).

Environments 2017,4, 12 8 of 16
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 ×10−4ng·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
∑7
PBDE (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
∑7
PBDE 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).
Environments 2017, 4, 12 9 of 18
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).
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.

Environments 2017,4, 12 9 of 16
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.
Sediments BDE 28 BDE 47 BDE 99 BDE 100 BDE 153 BDE 154 BDE 183 DW 1∑
∑
∑7PBDE TOC 2
BDE 28 1.00 −0.15 −0.04 0.10 0.12 −0.16 −0.01 0.07 −0.07 0.36
R
BDE 47 0.6352 1.00 0.96 0.77 0.82 0.78 0.79 −0.74 0.98 0.57
BDE 99 0.9065 <0.0001 1.00 0.88 0.84 0.67 0.70 −0.67 0.94 0.51
BDE 100 0.7358 0.0021 <0.0001 1.00 0.75 0.61 0.63 −0.52 0.77 0.42
BDE 153 0.6871 0.0006 0.0003 0.0034 1.00 0.43 0.44 −0.37 0.78 0.34
BDE 154 0.6048 0.0015 0.0128 0.0274 0.1440 1.00 0.98 −0.80 0.83 0.70
BDE 183 0.9677 0.0013 0.0083 0.0201 0.1279 <0.0001 1.00 −0.84 0.85 0.80
DW 10.8080 0.0036 0.0122 0.0682 0.2174 0.0011 0.0004 1.00 −0.82 −0.86
∑7PBDE 0.8104 <0.0001 <0.0001 0.0022 0.0017 0.0005 0.0003 0.0006 1.00 0.68
TOC 20.2335 0.0426 0.0778 0.1580 0.2519 0.0077 0.0011 0.0002 0.0107 1.00
p
1Content of dry material (%); 2Content of total organic carbon (%).

Environments 2017,4, 12 10 of 16
Environments 2017, 4, 12 10 of 18
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
∑7
PBDE concentration from the sediment
content of dry matter in lakes and rivers of Latvia.
3.3. Fish
The PBDE congener concentration range (Figure 5) in analyzed fish tissues ranged from
3×10−4ng·g−1WW
(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,

Environments 2017,4, 12 11 of 16
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.
Environments 2017, 4, 12 12 of 18
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.
Figure 5. Concentrations of PBDEs and lipid content in tissues of European perch (Perca fluviatilis)
from rivers and lakes of Latvia.
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
Figure 5.
Concentrations of PBDEs and lipid content in tissues of European perch (Perca fluviatilis) from
rivers and lakes of Latvia.

Environments 2017,4, 12 12 of 16
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).
Fish BDE 28 BDE 47 BDE 99 BDE 100 BDE 153 BDE 154 BDE 183 BDE 209 ∑
∑
∑7PBDE Lipids (%)
BDE 28 1.00 0.96 0.80 0.91 0.84 0.97 0.62 0.15 0.93 0.24
R
BDE 47 <0.0001 1.00 0.92 0.98 0.94 0.99 0.52 0.11 0.99 0.06
BDE 99 0.0060 0.0002 1.00 0.92 0.96 0.90 0.40 0.03 0.95 −0.22
BDE 100 0.0003 <0.0001 0.0002 1.00 0.97 0.98 0.45 0.08 0.98 −0.03
BDE 153 0.0024 <0.0001 <0.0001 <0.0001 1.00 0.95 0.44 0.02 0.97 −0.09
BDE 154 <0.0001 <0.0001 0.0003 <0.0001 <0.0001 1.00 0.55 0.11 0.99 0.10
BDE 183 0.0574 0.1271 0.2558 0.1921 0.2017 0.0995 1.00 0.00 0.49 0.46
BDE 209 0.6694 0.7670 0.9373 0.8186 0.9489 0.7712 0.9963 1.00 0.09 0.23
∑7PBDE 0.0001 <0.0001 <0.0001 <0.0001 <0.0001 <0.0001 0.1497 0.8146 1.00 −0.01
Lipids (%) 0.4965 0.8612 0.5478 0.9336 0.8135 0.7747 0.1803 0.5147 0.9729 1.00
p

Environments 2017,4, 12 13 of 16
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

Environments 2017,4, 12 14 of 16
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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