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Baseline levels and trophic transfer of persistent organic pollutants insediments and biota from the Congo River Basin (DR Congo)
Vera Verhaert a,⁎, Adrian Covaci b, Steven Bouillon c, Katya Abrantes c, Dieudonné Musibono d,Lieven Bervoets a, Erik Verheyen e,f, Ronny Blust a
a Systemic Physiological & Ecotoxicological Research, University of Antwerp, Groenenborgerlaan 171, 2020 Antwerp, Belgiumb Toxicological Centre, University of Antwerp, Universiteitsplein 1, 2610 Wilrijk-Antwerp, Belgiumc Department of Earth & Environmental Sciences, KULeuven, Celestijnenlaan 200E, 3001 Leuven, Belgiumd Laboratory of Ecotoxicology, University of Kinshasa, the Democratic Republic of Congoe Evolutionary Ecology Group, University of Antwerp, Groenenborgerlaan 171, 2020 Antwerp, Belgiumf Vertebrate Department, Royal Belgian Institute of Natural Sciences, Vautierstraat 29, 1000 Brussels, Belgium
⁎ Corresponding author at: Laboratory of Systemic Phcal Research, Department of Biology, University of Ant2020 Antwerp, Belgium. Tel.: +32 3 2653541; fax: 32 3
Article history:Received 1 November 2012Accepted 28 May 2013Available online 17 July 2013
Keywords:Congo River BasinPersistent organic pollutantsBioaccumulationTrophic transferTrophic magnification factors
The present study aimed to evaluate the occurrence of persistent organic pollutants (POPs: (PCBs, PBDEs,DDTs, HCHs, CHLs and HCB) in sediments and biota from the middle Congo River Basin (CRB) and to inves-tigate their trophic transfer through the aquatic food web using nitrogen stable isotope ratios. To our knowl-edge, no data on levels of POPs in sediment and biota from the CRB are present in the literature, and studieson trophic transfer and biomagnification profiles of POPs using δ15N are scarce in tropical regions.POP levels in the sediment and biota were low, with exception of total PCB levels found in fish from theItimbiri River (1.4 to 44 ng/g ww). Compared to concentrations found in fish from pristine to relatively in-dustrial developed areas, the ∑PCB levels in fish from the Itimbiri were high, indicating the presence of alocal PCB contamination source in this catchment. Based on minimum risk level criteria formulated byATSDR, the consumption of PCB contaminated fish from the Itimbiri river poses a potential risk for humans.The POP levels in biota were not significantly related to the POP levels in sediments, and the BSAF concept(Biota-Sediment Accumulation Factor) was found to be a poor predictor of the bioavailability andbioaccumulation of environmental pollutants in the present study. With increasing trophic levels, a signifi-cant increase in PCB 95, 101, 110, 138, 146, 149, 153, 174, 180 & 187 and p,p′-DDT in Itimbiri and BDE 47& 99 in Itimbiri, Aruwimi & Lomami river basins was observed. Trophic magnification factors were higherthan 1, indicating that biomagnification occurs through the tropical food web.
During the last century, persistent organic pollutants (POPs) such asorganochlorine pesticides (OCPs: DDT, chlordanes, hexachlorobenzene),polychlorinated biphenyls (PCBs) and polybrominated diphenyl ethers(PBDEs) have been introduced by man in the environment. POPs arelipophilic and can be transferred across trophic levels of the food webby the processes of bio-accumulation and bio-magnification and becometoxic as accumulation levels increase (Zhou et al., 2007). Their semi-volatile character and persistence result in long-range atmospherictransport leading to a global distribution in the environment, includingsome of the most remote areas (Daly et al., 2007; Fernandez andGrimalt, 2003; Lohmann et al., 2007; Ondarza et al., 2011). The fate and
ysiological and Ecotoxicologi-werp, Groenenborgerlaan 171,2653497.
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distribution of POPs have been intensively investigated in marine andfreshwater ecosystems from temperate and arctic regions (Bervoets etal., 2005; Covaci et al., 2005; Fisk et al., 2001; Hallanger et al., 2011).However, a large data gap still exists for tropical regions (Ikemoto et al.,2008; Kidd et al., 2004; Noegrohati et al., 2008).
The environmental fate of POPs in tropical ecosystems is predictedto be different from that in temperate and cold ones, because ofthe prevailing high temperatures and heavy rainfall (Sarkar et al.,2008). These factors could contribute to higher leaching andvolatilisation of POPs (UNEP, 2002). The theory of the Global Distilla-tion Effect predicts the transport of POPs from the warmer tropical ortemperate source areas, to the colder, higher latitude regions(Fernandez and Grimalt, 2003; Gioia et al., 2011; Iwata et al., 1994;Wurl et al., 2006). Other studies suggest that tropical regions alsomay act as a sink since removal processes (microbial transformationand chemical hydrolysis) may be faster compared to temperate andarctic regions (Karlsson et al., 2000; Macdonald et al., 2000; UNEP,2002). The behaviour, fate and distribution of POPs in tropicalreservoirs is poorly studied and further work is clearly required
291V. Verhaert et al. / Environment International 59 (2013) 290–302
(MacDonald et al., 2000). Subsequently, risk assessments in tropicalregions often rely on temperate fate and distribution data of POPs, al-though it is debatable whether these are comparable in geographical-ly distinct ecosystems.
Two risk assessment tools that are used in temperate and arcticaquatic ecosystems to investigate bioavailability, bioaccumulationand biomagnification of POPs are (1) the biota-sediment accumula-tion factor (BSAF) model and (2) stable isotopes and trophic magnifi-cation factors (TMFs). In temperate regions, sediments act as a sinkfor POPs and represent an important potential exposure pathwayfor aquatic species. The BSAF model is a simple empirical methodto evaluate bioavailability of POPs in the sediment and to predictbioaccumulation in aquatic organisms. This model is based on equi-librium partitioning between the sediment organic carbon and bioticlipid pools and assumes that the relationship can be described as aconstant (Burkhard et al., 2005; De la Cal et al., 2008). Little researchhas been conducted on the role of sediments in tropical aquatic sys-tems regarding the distribution of POPs, and the applicability of theBSAF model for tropical regions needs further investigation.
The use of stable isotopes to characterise trophic transfer andbiomagnification of POPs through the food web has advanced rapidlythe last decade (Ikemoto et al., 2008). Nitrogen stable isotope ratios(δ15N) increase during dietary assimilation and thus are a relativeproxy of an organism's trophic level. Consequently, when δ15N andPOP levels are measured in the same samples, trophic transfer andbiomagnification of these POPs through the food web can be estimat-ed. TMFs were suggested as a reliable tool for biomagnification as-sessment of POPs. TMFs are based on lipid-normalised contaminantconcentrations and relative trophic levels, and represent the averagefood web accumulation (Borgå et al., 2011). Most studies on POPsand trophic transfer have been conducted in the temperate to borealregions of the world (Borgå et al., 2011; Hallanger et al., 2011; Hop etal., 2002; Sobek et al., 2010), while studies on biomagnification pro-files of POPs in tropical aquatic food webs have seldom beenconducted. Borgå et al, 2011 suggested important issues to considerwhen comparing tropical versus temperate or arctic TMFs. (1) Tropi-cal food webs are more complex because of higher biodiversity whichlikely promotes greater diversity of diets, (2) higher biomass or tissueturnover may decrease TMFs due to higher biomass dilution of con-taminants and (3) bioavailability in tropical systems may be affectedby the higher microbial activity and organic matter. The effects ofthese factors on TMFs remain unknown and warrant further investi-gation (Borgå et al., 2011; Kidd et al., 2005).
The present study focuses on POP pollution and trophic transferin a tropical fresh water food web of the Congo River Basin (CRB).The CRB is mainly located in the Democratic Republic of Congo (DRCongo), which is characterised by a tropical climate. The CRB isconsidered relatively pristine, although very little information isavailable concerning the presence of anthropogenic pollution andits impact on biodiversity and human health (UNDP, 2009; UNEP &GEF, 2009; UNITAR, 2006). The DR Congo has ratified the StockholmConvention in 2005 and most POPs are banned from production, im-portation, exportation and use. Nevertheless, there is evidence oftheir presence and continued use in vector management and in theindustrial and agricultural sector. The absence of appropriate legisla-tion and continued armed conflicts facilitate illegal trade of thesepollutants (UNDP, 2009; UNEP & GEF, 2009). With a hot and humidtropical climate that promotes the growth of pests and disease vec-tors, OCPs have been used in many sectors including agriculture, in-dustry and public health to control pests and diseases (UNDP, 2009).DDT was officially reintroduced in DR Congo by the World HealthOrganisation (2011) for Indoor Residual Spraying (IRS) to controlmalaria. A serious problem faced by the whole African region is thepresence of stocks of obsolete OCPs (UNDP, 2009). Potential sourcesof PCBs and PBDEs are usage of equipment containing these com-pounds and the dumping of PCB and PBDE containing wastes that
are exported from Europe to Africa (Klánová et al., 2009). In additionto pollution by direct use of POPs, global pollution by atmospherictransport can be another source of pollution but it remains uncertainwhether Africa is a net source or sink of global POPs (Karlsson et al.,2000; UNEP, 2002).
This study aimed to evaluate the occurrence of the major POPs indifferent aquatic compartments of the CRB. More in particular, the ap-plicability of risk assessment models used in temperate and arcticaquatic ecosystems to investigate bioavailability, bioaccumulationand biomagnification of POPs was evaluated for a tropical freshwaterfood web. The specific objectives were to (1) produce a baselinePOP dataset for concentrations in sediment and biota from the CRB;(2) evaluate the use of BSAFs; (3) to investigate the trophic transferand biomagnification of POPs through a tropical freshwater foodweb using stable isotopes and TMFs; and (4) determine the potentialhuman health risk by consumption of POP contaminated fish. To ourknowledge, this is the first study to present data on levels of POPsin sediment, invertebrates and fish from the CRB.
2. Materials and methods
2.1. Study area
The Congo River Basin (CRB) is situated in Central Africa, mainly inthe DR Congo (Fig. 1). The CRB is the second largest watershed of theworld (3.7 million km2), after the Amazon and the river is the secondlargest in Africa, after the Nile (Dupré et al., 1996; WCS, 2003). As itrepresents 25% of the renewable water supply in Africa, the CRB isan important freshwater resource. From a global perspective, themain importance of the CRB is its uniquely rich biodiversity and itsclimate-relevant functions (carbon stock) (UNEP, 2011). The CRBcan be divided into three main parts: the upper, mid and lowerCongo (UNEP, 2011). The study area was situated in the mid Congobetween Kisangani and Bumba. In these major towns (populationKisangani: 812 000, Bumba: 103 000; CIA, 2012), urban and industri-al wastes and sewage are dumped untreated in the river. The antici-pated post-war expansions of agricultural, industrial, and urbanactivities in the Congo basin are likely to result in increased rates ofdeforestation, habitat destruction and deterioration of the waterquality (WCS, 2003). To date, no specific data on the use of POPsexist for this area.
The study area comprised five sampling locations downstream ofKisangani, including three tributaries: Itimbiri (1), Aruwimi (2) andLomami) (3), and two locations in the Congo River itself: near Isangi(4) and Kisangani (5) (Fig. 1). The region has a tropical climate whichis characterised by a high humidity, a mean annual rainfall of1620 mm and temperatures which are uniformly high throughoutthe year with an average of 25 °C (CIA, 2012).
2.2. Sample collection
At each location, sediment, fish and invertebrates were collectedat different sampling points between May and June 2010. Sedimentsamples were taken with a Petite Ponar Grab (Wildco). At eachpoint, 3 sediment grabs were pooled. In the laboratory, sedimentsamples were divided into subsamples for POP analysis and organicmatter content determination (total organic carbon, TOC). TOC wasdetermined through Loss on Ignition. For this, the sediment sampleswere incinerated at 550 °C for 4 h and weight loss was determined(Heiri et al., 2001).
Fish were collected with gill nets, and then filleted and skinned.Six fish species were selected based on their distribution throughoutthe study area: Marcusenius sp. (Mormyridae), Shoulderspot catfish(Schilbemarmoratus, Schilbeidae), Blackline glass catfish (Schilbe grenfelli,Schilbeidae), Bigeye squeaker (Synodontis alberti, Mochokidae), Spot-tailrobber (Brycinus imberi, Alestidae) and Sharktail distichodus (Distichodus
BUMBA1
2
3
4
5
100 km
1
54
3
2
Fig. 1. Sampling locations along the Congo River Basin: 1. Itimbiri, 2. Aruwimi, 3. Lomami, 4. Congo River (Isangi), 5. Congo River (Kisangani) (Runge et al., 2007).
292 V. Verhaert et al. / Environment International 59 (2013) 290–302
fasciolatus, Distichodontidae). Biological characteristics (length andweight) were determined. Concerning invertebrates, the shrimpsAfrican Caridina (Caridina africana, Atyidae) and Macrobrachium sp.(Palaemonidae) were collected with hand nets, and two species ofapple snail (Lanistes cf. ovum and Pila sp., Ampullariidae)were purchasedfrom the local population.
To obtain sufficient material for POP analyses, several individualsneeded to be pooled for the species C. africana and Macrobrachiumsp. Biota samples were divided into subsamples for POP and isotopeanalysis. Tissues used for POP analyses were caudal muscle for fishand homogenised whole soft body for invertebrates (i.e. shells wereremoved). For stable isotope analysis, only white muscle tissue wasused. This was removed from the tail region of fish, the abdomen ofshrimps and the muscular foot of gastropods. Samples were storedat −20 °C until analysis. Table S1 of the Electronic SupplementaryMaterial lists the collected samples.
2.3. POPs
2.3.1. Chemicals and sample preparationThe following compounds were included in the analysis: 33 PCB
congeners (IUPAC numbers: CB 18, 28, 44, 49, 52, 87, 95, 99, 101,105, 110, 118, 128, 138, 146, 149, 151, 153, 156, 170, 171, 172, 174,177, 180, 183, 187, 194, 195, 199, 205, 206, 209), 7 PBDEs (IUPACnumbers: 28, 47, 99, 100, 153, 154, 183), DDT and metabolites (o,p′-DDD, o,p′-DDE, o,p′-DDT, p,p′-DDD, p,p′-DDE, p,p′-DDT), chlordanes—CHLs (trans-chlordane (TC), cis-chlordane (CC), cis-nonachlor(CN), trans-nonachlor (TN), oxychlordane (OxC)), HCHs (α-, β-,γ-hexachlorocyclohexanes) and HCB. BDE 209 was also targeted insediment samples. All solvents and chemicals were purchased or pre-pared as described previously (Chu et al., 2002; Covaci et al., 2002).
The methods used for the determination of POPs in sediment andbiota samples have been previously described and validated (Covaciet al., 2005, 2008) and are summarised below. For the biota samples,the whole fresh fish muscle (0.2–6.2 g) and invertebrates (0.1–4.1 g)were homogenised with anhydrous Na2SO4, spiked with internalstandards (CB 143, BDE 77, ε-HCH) and extracted for 2 h by hotSoxhlet with 100 ml hexane/acetone (3/1, v/v). After lipid determina-tion, the extract was cleaned-up on 8 g acidified silica and analyteswere eluted with 20 ml hexane and 15 ml dichloromethane. Thecleaned extract was then concentrated and reconstituted in 100 μLiso-octane. For the sediment (3 g), the same procedure was followed,but 5 g of activated copper powder was added and mixed with thesample. The samples were spiked with internal standards (CB 143,
BDE 77, 13C-BDE 209 and ε-HCH). For the clean-up step, 2 g of copperpowder was added on top of the acid silica.
2.3.2. POP analysisPBDEs, HCHs and CHLs were measured with an Agilent 6890-5973
gas chromatograph coupled to a mass spectrometer (GC–MS) andequipped with a 30 m × 0.25 mm × 0.25 μm DB-5 capillary column.The MS was operated in electron capture negative ionisation (ECNI)mode and was used in the selected ion-monitoring (SIM) modewith ions m/z = 79 and 81 monitored during the entire run and spe-cific ions for OCPs acquired in well-defined windows. PCBs, DDXs, andHCB were measured with a similar GC–MS system as for the PBDE de-termination, operated in electron ionisation (EI) mode and equippedwith a 25 m × 0.22 mm × 0.25 μm HT-8 capillary column. The MSwas used in the SIM mode with 2 ions monitored for each PCB homo-logue group or OCP. More details are found in the Electronic Supple-mentary Material.
2.3.3. Quality assurance/quality control (QA/QC)Retention times, ion chromatograms and relative abundance of
the monitored ions were used as identification criteria. A deviationof ion abundance ratios within 15% of the mean values for calibrationstandards was considered acceptable. Quantification was based onfive-point calibration curves. The peaks were positively identified astarget compounds if: (1) the retention time matched that of thestandard compound within ±0.1 min and (2) the signal-to-noiseratio (S/N) was higher than 3:1.
One blank was analysed for each batch of 10 samples and this foreach type of samples (fish, invertebrates and sediments). The blankvalues were for most compounds not detectable, while for com-pounds with detectable (but very low) blanks, the variation betweenthe blanks was b30%. For each analyte detected in the blanks, themean procedural blank value was used for subtraction. After blanksubtraction, the limit of quantification (LOQ) was set at 3 times thestandard deviation of the procedural blank, which ensures >99% cer-tainty that the reported value is originating from the sample. Foranalytes that were not detected in procedural blanks, LOQs werecalculated for a ratio S/N equal to 10. LOQs depended on the sampleintake and on the analyte and ranged between 1 and 4 ng/g lipidweight (lw) for biota and 10 and 50 pg/g dry weight (dw) forsediments.
QC was performed by regular analyses of procedural blanks, byrandom injection of standards and solvent blanks. Mean ± SD recov-eries of the internal standards PCB 143 and BDE 77 were 86 ± 6% and
293V. Verhaert et al. / Environment International 59 (2013) 290–302
93 ± 10%, respectively. A standard reference material SRM 1945(OCPs, PCBs and PBDEs in whale blubber) and CRM 536 (PCBs inharbour sediment) was used to test the accuracy of the method.Obtained values were not deviating more than 20% from the certifiedvalues (more details are given in the Electronic Supplemental Materi-al, see Tables S2–S4). The QC scheme is also assessed through regularparticipation to interlaboratory comparisons organised by the USNational Institute of Standards and Technology where z-scores be-tween −2 and 2 have usually been obtained (Kucklick et al., 2006,2007, 2009).
2.4. Stable isotope analysis
Stable isotope analyses were performed on 17 invertebrate and 51fish samples. Samples were dried at 60 °C, homogenised with a mor-tar and pestle into a fine powder, weighed to the nearest 0.001 mgand encapsulated in pre-weighed 5 × 8 mm Sn capsules to determineC and N concentrations, as well as δ13C and δ15N. Stable isotope mea-surements were performed using a Thermo Flash HT/EA coupled to aThermo DeltaV Advantage IRMS with a Conflo IV interface. Stable iso-tope results are expressed in the standard notation, as defined by:
δ13C; δ15N ¼ Rsample=Rreference
� �−1
h i� 1000;
with R = 13C/12C for carbon and 15 N/14 N for nitrogen.Data were calibrated using a combination of IAEA-C6, IAEA-N1,
and acetanilide, which had been calibrated in house for both δ13Cand δ15N. Estimated precision is generally better than 0.15 ‰ forboth δ13C and δ15N.
2.5. Statistical analysis
Statistical analyses were conducted using GraphPad Prism 5(GraphPad Software, Inc) and the SPSS 15.0 statistical package. Thelevel of statistical significance was defined at p b 0.05. For concentra-tions below the LOQ, a value of f ∗ LOQ (with f, detection frequency)was used. After testing the normality of the data and homogeneity ofvariances, data were log-transformed when necessary. Differences inconcentrations among species and locations were detected usingone-way ANOVA followed by the Tukey HSD test. Pearson's correla-tion coefficients were calculated between pollution levels in sedimentand in biota tissues and between biological characteristics (length,weight, lipid content) and POP levels in biota.
For all detected compounds, BSAFs were calculated as the ratio ofthe lipid-normalised concentration of a chemical in an organism tothe organic carbon-normalised concentration of the chemical in theupper layer of the sediment (Burkhard et al., 2005; De la Cal et al.,2008). One-way ANOVA with Tukey test was used to compareBSAFs between species. Pearson's correlation coefficients were calcu-lated between trophic level and BSAFs and TOC normalised sedimentconcentrations and BSAFs for all POPs.
Relative trophic levels were derived from animal δ15N valuesusing the following equation (Post, 2002):
TLconsumer ¼ 2þ δ15Nconsumer−δ15Nprimary consumer
� �=Δδ15N ð1Þ
where TLconsumer is the trophic level of the organism, δ15Nconsumer isδ15N of the organism, δ15Nprimary consumer is the mean δ15N of a locallong-lived primary consumer, 2 is the trophic level of the primaryconsumer and Δδ15N is the trophic enrichment factor, or the shift inδ15N between consecutive trophic levels (Post, 2002). In the presentstudy, the primary consumer used as a baseline was Pila sp., as it oc-curred in almost all sampling sites. A Δδ15N trophic fractionation of3‰was used, as this is the most adequate estimate for non-acid treat-ed muscle tissue (McCutchan et al., 2003; Vanderklift and Ponsard,
2003). Although Δδ15N can be somewhat variable, depending ontaxa, diet and environment (McCutchan et al., 2003; Vanderklift andPonsard, 2003), the use of an exact value is less important for thisstudy, as the value used will only affect the absolute TL estimatesbut not the relative position between species, or relationships be-tween POPs and estimated trophic levels.
TMFs were based on lipid-normalised contaminant concentrationsand relative trophic levels, and were calculated from the slope of theregression of the log-transformed concentrations of pollutants versustrophic level calculated based on δ15N (Borgå et al., 2011).
Log POP½ � lwð Þ ¼ aþ b TL and TMF ¼ 10b ð2Þ
Finally, the Pearson's correlation coefficients were calculated be-tween trophic level and log normalised concentrations in the biotatissues for all compounds.
3. Results and discussion
3.1. POP levels in sediments
TOC values together with ranges and median concentrations of∑PCBs, ∑PBDEs, ∑DDXs, ∑HCHs, ∑CHLs and HCB measured insediment samples are given in Table 1. Fig. 2 shows the median levelsof ∑PCBs, ∑PBDEs, ∑DDXs and ∑HCHs in sediment per location.
3.1.1. PCBsConcentrations of ∑PCBs ranged from bLOQ to 1.4 ng/g dry
weight (dw). PCB congeners 18, 28, 44, 49, 52, 87, 172, 194, 195,205, 206, 209 were found to be below the detection limit in all sedi-ment samples. The most dominant PCB congeners were CB 153(19% of ∑PCB), CB 149 (14%), CB 101 (12%), and CB 138 (11%).
From the seven indicator PCBs, only five were detected (CB 101,118, 138, 153 and 180) accounting for 49% of total PCB concentrationsin surface sediment in the CRB and varying from bLOQ to 0.65 ng/g dw,with a mean of 0.23 (±0.21) ng/g dw.
To understand the magnitude of contamination, the concentra-tions of PCBs in the sediment from DR Congo were compared withPCB levels reported in studies on other tropical regions and in moreindustrial developed countries around the world. However, the avail-ability of data on POPs in environmental media in tropical areas islimited (Batterman et al., 2009; Mansour, 2009; Spongberg andWitter, 2008; UNEP & GEF, 2009).
PCB levels in the sediment from the CRB were comparable withthose from other river systems in Africa: the Nile River, Egypt(El-Kady et al., 2007) and samples from the Kabete region, Kenya(Mirikau et al., 2011). The levels were lower then found in the Klipand Vaal Rivers in South Africa (Quinn et al., 2009), which are situat-ed in an industrial, agricultural and urban region. The results are alsoin the range of data found in sediments from tropical areas in Asia:Tam-Giang-Cau Hai Lagoon, Central Vietnam (Frignani et al., 2007),the Mekong Vietnam (Carvalho et al., 2008), the Wonokromo River,Indonesia (Ilyas et al., 2011). Compared to concentrations reportedfor industrialised areas (Europe and the USA), the levels of PCBs inthe sediment of the CRB are relatively low (Ashley et al., 2009;Covaci et al., 2005; Kohušová et al., 2011; Samara et al., 2006).
3.1.2. PBDEsConcentrations of∑PBDEs ranged from bLOQ to 1.9 ng/g dw. The
most dominant compound was BDE 209 (90% of ∑PBDE; bLOQ–1.7 ng/g dw) followed by BDE47 (5% of ∑PBDE) and BDE 99 (3%of ∑PBDE). Higher brominated flame retardants, such as BDE 209,are less mobile in the environment. Due to their low volatility andwater solubility, they are strongly adsorbed on sediments (Viganòet al., 2011; Watanabe and Sakai, 2003). The lower brominated
Table 1Ranges and median of total organic carbon (TOC %) and sediment concentrations of ∑PCBs, ∑7PCBs, BDE209, ∑PBDEs, ∑DDTs, ∑HCHs and HCB in ng/g dw per sampling lo-cation. Locations are ordered from downstream to upstream.
294 V. Verhaert et al. / Environment International 59 (2013) 290–302
congeners BDE 28, 100 and 153 were not detected in the sedimentsamples.
The sampling site with the highest concentration is located in theLomami (∑PBDEs = 1.9 ng/g dw).
Data on PBDE levels in sediment samples of Africa are very scarce.Olukunle et al. (2011) reports on PBDE concentrations in sedimentsfrom the Juksei River, South Africa. Concentrations of ∑PBDE(11 congeners including BDE 209) ranged from 0.92 to 6.8 ng/g dw.The levels found in the present study and in South Africa are lowerthan values found in developed countries (Covaci et al., 2005;Eljarrat et al., 2005; Hale et al., 2003; Lacorte et al., 2006; Olukunleet al., 2011; Samara et al., 2006).
3.1.3. OCPsConcentrations of ∑DDXs ranged from bLOQ to 0.37 ng/g dw.
The principal contributors to ∑DDXs in sediments were p,p′-DDE(48% of ∑DDXs) and p,p′-DDT (40%). The o,p′-DDD, o,p′-DDT, o,p′-DDE isomers were found to be below the detection limit. Compared toconcentrations found in other studies, DDT levels in the CRB are verylow. Similar DDT levels were found in river sediments from Kenya(Lalah et al., 2003; Mirikau et al., 2011) and Ghana (Ntow, 2001).
Location
ng P
C B
s/g
ww
(B
iota
)ng
P C
B s
/g d
w (
Sed
imen
t)
1 2 3 4 50
5
10
1525
30
Marcusenius sp.
Schilbe marmoratus
Synodontis alberti
Brycinus imberi
Distichodus fasciolatus
Schilbe grenfelli
Location
ng D
D T
/g w
w (
Bio
ta)
ng D
D T
/g d
w (
Sed
imen
t)
1 2 3 4 50.0
0.5
1.0
1.54
5
6
Fig. 2. Median levels of ∑PCBs, ∑PBDEs, ∑DDXs and ∑HCHs in sedime
Concentrations of ∑HCHs ranged from bLOQ to 0.40 ng/g dw.The most dominant compound was α-HCH (84% of ∑HCHs). Com-pared to levels found in other river basins in Africa, the levels of thepresent study are very low (Darko et al., 2008; Getenga et al., 2004;Kishimba et al., 2004). The sediments of all studied rivers have∑CHLs below LOQ (0.02 ng/g dw). HCB was only found at very lowconcentrations in the Itimbiri river.
The overall detection frequency and detected concentrations ofPOPs in the sediment samples were low. It has been suggested thatlow absolute levels of POPs in sediments from tropical regions arenot necessarily an indication of low exposure to or usage of POPs inthose regions. Volatilisation dominates the environmental distribu-tion and partitioning of semi-volatile POPs in the tropics. Combinedwith their low aqueous solubility and elevated ambient temperatures,this leads to higher atmospheric concentrations and lower aquaticecosystem concentrations in tropical regions relative to temperate re-gions (Iwata et al., 1994; Kannan et al., 1995; Larsson et al., 1995). Inaddition to higher potential for volatilisation and subsequent atmo-spheric dispersal, POPs may be subject to faster rates of degradationin tropical regions due to increased metabolic activity in biota, furtherreducing potential levels in sediments (Peters et al., 2001).
Location
ng P
B D
E /g
ww
(B
iota
)n
g P
B D
E /g
dw
(S
edim
ent)
1 2 3 4 50.0
0.5
1. 0
1.5
Lanistes cf. ovum
Caridina africana
Macrobrachium sp.
Pila sp.
Sediment
Location
ng H
C H
s/g
ww
(B
iota
)ng
H C
H s
/g d
w (
Sed
imen
t)
1 2 3 4 50.0
0.2
0.4
0.6
0.8
1.0
nt samples and the different invertebrate and fish species per location.
295V. Verhaert et al. / Environment International 59 (2013) 290–302
3.2. POP levels in aquatic biota
3.2.1. InvertebratesRanges and medians of lipid levels and concentrations of ∑PCBs,
∑PBDEs, ∑DDXs, ∑HCHs, ∑CHLs and HCB, measured in differentinvertebrate species, are given in Table 2. Fig. 2 shows the medianlevels of ∑PCBs, ∑PBDEs, ∑DDXs and ∑HCHs in the different in-vertebrates per location.
The lipid content in the investigated invertebrates varied between0.84% for C. africana and 2.4 ± 1.2% (±SD) for Pila sp. No significantdifferences in lipid content of the same species collected at differentlocations.
3.2.1.1. PCBs. The measured POP concentrations in the invertebrateswere higher than in the sediment. Although PCB congeners 18, 28,44, 49, 87, 99, 105, 128, 151, 156,170, 171, 172, 177, 183, 194, 195,199, 205, 206, 209 were not detected, PCBs were the predominantpollutants in the invertebrate species. ∑PCBs ranged from bLOQ to4.4 ng/g wet weight (ww) (bLOQ–507 ng/g lipid weight lw). Themost dominant was PCB 153 (17% of ∑PCBs), followed by PCB 101(15% of ∑PCBs), PCB 149 (15% of ∑PCBs), PCB 95 (12% of∑PCBs) and PCB 138 (10% of ∑PCBs). This profile is comparablewith the profiles found in the sediment samples.
The highestmean concentrationswere detected in invertebrates fromthe Itimbiri River, but no significant differences between locations were
Table 2Ranges and medians of lipid levels (%), ∑PCBs, ∑7PCBs, ∑PBDEs, ∑DDXs, ∑HCH and
observed. Levels of CB101, CB153, CB138 and ∑PCBs were significantlyhigher in Pila sp. than in C. africana (CB101: F2,19 = 6, p = 0.011;CB153: F2,19 = 4, p = 0.033; CB138: F2,19 = 4, p = 0.046 and ∑PCBs:F2,19 = 3, p = 0.05). Fu et al. (2011) reported that apple snail speciesare good bio-indicators for PCB pollution because the apple snailsreflected the contamination status of PCBs in their habitat.
Senthilkumar et al. (2000) reported low PCB concentrations(mean concentrations of 4.8 ng/g ww) in apple snails collectedin wetlands and coastal areas in South India. Ikemoto et al. (2008)measured PCB concentrations in crustaceans from the Mekong Delta,Vietnam. The Mekong Delta is situated in a rapidly growing agriculturaland urban area, and environmental contamination by trace metals andPOPs is thus expected. Concentrations in different Macrobrachium spe-cies ranged from 0.51 to 3.4 ng/g ww (Ikemoto et al., 2008).
Compared to the results of studies in Europe and the USA, thelevels in the present study are low. Bervoets et al. (2005) reportedconcentrations in mussels from different waterbodies in Flanders,Belgium ranging from 8.6 to 116 ng/g ww and Ashley et al. (2009)measured levels in amphipods from the Delaware River, New Jersey,up to 240 ng/g ww.
3.2.1.2. PBDEs. Among PBDEs, congeners 28, 100, 153 and 183 werebelow LOQ in all invertebrate samples. ∑PBDE varied from bLOQ to0.11 ng/g ww (bLOQ to 7.9 ng/g lw). BDE 99 was the most dominantcongener (66% of ∑PBDE), followed by BDE47 (18% of ∑PBDE) and
HCB (ng/g ww) and of δ15N (‰) in biota from the Congo River Basin.
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BDE154 (15% of ∑PBDE). No significant differences are found betweenspecies and locations and overall concentrations were low compared toother studies (0.12–0.40 ng/g ww, China, Hu et al., 2010; 0.20–30 ng/gww, Belgium, Voorspoels et al., 2003). Little to no research has beendone in Africa on PBDEs in freshwater invertebrates.
3.2.1.3. OCPs. As for the sediment samples, o,p′-DDD, o,p′-DDT, o,p′-DDE, p,p′-DDD were not detected in the invertebrates. ∑DDXsranged from bLOQ to 1.2 ng/g ww (bLOQ–27 ng/g lw) with asmajor contributor p,p′-DDE (69% of ∑DDXs). Levels are similar toconcentrations found in other tropical countries with limited use ofOCPs. Mdegela et al. (2009) reported low concentrations of OCPs ininvertebrates of different rivers of Tanzania (1.9 ng/g ww in hairyriver prawn, Macrobrachium rude). The authors state that the reasonfor these low levels might be the ban on the use of DDT in Tanzaniain response to the Stockholm Convention on the use of POPs in2004. Kidd et al. (2001) detected concentrations ranging from 0.41to 0.69 ng/g ww in snails from Lake Malawi. Compared to levelsfound in invertebrates from Spanish rivers (0.03–183 mg/kg lw,López-Martín et al., 1995), levels from the present study are low.The World Health Organisation allows the use of DDT in DR Congo,but the applicability is restricted to residual indoor spraying (WHO,2011). The concentrations found in the invertebrates do not showevidence of either problematic or recent pollution by DDT in the sam-pled area in the Congo Basin.
∑HCHs ranged from bLOQ to 0.98 ng/g ww (bLOQ to 46 ng/g lw)with γ-HCH contributing for 52%. Among the CHLs, only OxC could bedetected. OxC concentrations ranged from bLOQ to 0.040 ng/g lw.HCB concentrations varied from bLOQ to 0.035 ng/g lw.
3.2.2. FishRanges and median levels of lipid content (%) and ∑PCBs,
∑PBDEs, ∑DDTs and ∑HCHs expressed in ng/g ww measured indifferent fish species from the Congo River Basin are given inTable 2. Fig. 2 shows the median levels of ∑PCBs, ∑PBDEs,∑DDXs and ∑HCHs in the different fish species per location.
The lipid content in the investigated fish species varied between1.5 ± 0.91% for S. marmoratus and 1.9 ± 0.28% for B. imberi. Foreach species, lipid content was consistent between locations and nosignificant differences in lipid content are found between species.
3.2.2.1. PCBs. Measured concentrations of PCBs ranged from b LOQ to66 ng/g ww (bLOQ to 3664 ng/g lw). Some PCB congeners (18, 28,44, 49, 99, 172, 194, 195, 199, 205, 206 and 209) were not detected.Penta- and hexa-CBs were the major homologues in all fish samples.PCB 153 was the major contributor (17% of ∑PCBs), followed byPCB 149 (15%), PCB 101 (13%), PCB 138 (10%) and PCB 95 (9%). Inter-estingly, the same PCB profile was found in the sediment samples andinvertebrates. This congener profile indicates a dominant use of thePCB mixture Aroclor 1254 (ATSDR, 2000).
Overall, PCB concentrations (IUPACNo: 52, 95, 101, 87, 110, 118, 105,151, 149, 146, 138, 128, 156, 187, 183, 174, 177, 171, 172, 180, 170) infish from the Itimbiri Riverwere significantly higher than concentrationsmeasured at the other sampling locations (22 ± 15 ng/g ww, 1464 ±870 ng/g lw;∑PCBs: F4,65 = 7.003; p b 0.001).
The concentrations found in fish from the Itimbiri River werelower than levels found in fish from industrialised areas like Europeand USA (Ashley et al., 2009; Belpaire et al., 2011; Bordajandi et al.,2003; Peré-Trepat et al., 2006; Van Ael et al., 2012; Wan et al.,2010). In comparison with concentrations found in fish from pristine(Kidd et al., 2004; Manirakiza et al., 2002; Moon et al., 2006) to rela-tively industrial developed areas (Minh et al., 2006; Nie et al., 2005),the ∑PCB levels in fish from the Itimbiri are high and indicate thepresence of a PCB contamination source in the Itimbiri basin. A poten-tial source of this contamination is the use of PCB contaminated oil inold engines and power transformers on boats and in industrial (railway
Bumba-Aketi and timber processing) and agricultural (palm oil, tea,coffee) activities (Carvalho et al., 2009; UNEP & GEF, 2009).
The global comparison of PCBs confirms that developed countriesare generally more contaminated by PCBs than developing nations al-though comparison between results is sometimes difficult due to thevariability of PCB congeners that have been analysed in the differentsurveys and differences in the way results are expressed (ww, lw, dw).
3.2.2.2. PBDEs. ∑PBDEs ranged between bLOQ and 2.3 ng/g ww(bLOQ–188 ng/g lw). PBDE congeners 28 and 183 could not bedetected. The most dominant compound was BDE 99 (57% of∑PBDEs) followed by BDE 47 (34% of ∑PBDEs) and BDE 100 (3%).The presence of these three congeners is observed in fish samplescollected around the world and refers to the commonly usedPenta-BDE formulation flame retardant (Luross et al., 2002). Com-pared to Europe and USA, the levels of PBDEs in fish from the presentstudy are low (Blocksom et al., 2010; Eljarrat et al., 2005; Labandeiraet al., 2007; Mariussen et al., 2003; Viganò et al., 2008; Voorspoels etal., 2003). Studies on PBDE levels in fish from Africa are extremelyscarce. Asante et al. (2011) report on PBDE levels in fish from lakesin Ghana. Concentrations of PBDEs ranged from 0.01 to 52 ng/g lw.They conclude that PBDEs levels in fish from Ghana were in the lowor medium range among the levels around the world. Wepener etal. (2011) also reported on PBDE levels in fish from the Vaal River,South Africa, which ranged from 6.0 to 54 ng/g lw. Compared tolevels found in areas of Asia and South America, the levels found inthe present study were similar or higher (Hu et al., 2010; Minh etal., 2006; Ondarza et al., 2011; Su et al., 2010). The highest concentra-tions were found in Marcusenius sp. collected at the market ofKisangani.
3.2.2.3. OCPs. Regarding DDT andmetabolites, o,p′-DDD, o,p′-DDT, o,p′-DDE isomers could not be detected in any sample. ∑DDX concen-trations ranged from bLOQ to 11 ng/g ww (bLOQ to 504 ng/g lw).The most dominant isomer is p,p′-DDE (51% of ∑DDTs) followed byp,p′-DDT (30% of ∑DDTs). This metabolite profile indicates that theobserved concentrations originate from historical use rather than re-cent DDT application.
Compared to studies in other African tropical aquatic systems, themeasured concentrations are low (Adu-Kumi et al., 2010; Kidd et al.,2001; Manirakiza et al., 2002; Mdegela et al., 2009; Mwevura et al.,2002). The highest concentrations are found in Marcusenius sp. fromthe Kisangani market, but no significant differences in concentrationswere found among locations and species.
For HCHs, β-HCH could not be detected. ∑HCHs ranged frombLOQ to 0.56 ng/g ww (bLOQ to 66 ng/g lw) with the highest contri-bution of the γ-HCH isomer (62% of ∑HCHs). Total HCH concentra-tions were lower (Abbassy et al., 2003; Gitahi et al., 2002; Kasozi et al.,2006) or similar (Ikemoto et al., 2008; Lalah et al., 2003; Ondarzaet al., 2010) to other tropical regions.
Although CHLs were not detected in the sediment, they werepresent in fish, yet at low concentrations. The sum of CHLs rangedfrom bLOQ to 0.35 ng/g ww (bLOQ to 8.1 ng/g lw). OxC was themost dominant CHL compound (72% of ∑CHLs). No significant dif-ferences among locations and species were observed. Concentrationsfor HCB ranged from bLOQ to 0.13 ng/g ww (bLOQ to 12 ng/g lw).
3.2.2.4. Biological characteristics and POP concentrations. No or weaksignificant correlations were observed between POP concentrationsand biological characteristics (length, weight, lipid content). No sig-nificant correlation between length or weight and POP concentrationsfor the different fish species was detected. Lipid content was sig-nificantly correlated to p,p′-DDE and p,p′-DDT concentrations inS. marmoratus (Fig. S-1). For other species and other pollutants, nocorrelations were found.
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Concerning the occurrence of the most important POPs in sedi-ment, invertebrates and fish from selected sites of the Congo RiverBasin, several POPs could be detected in the Congo River Basin. How-ever, in general levels, of PCBs, PBDEs and OCPs in the different envi-ronmental compartments were low compared to other studiesaround the world. Only PCB levels in fish from the Itimbiri Riverwere of the same magnitude as found in more industrialised basins.No clear trends could be observed when comparing tissue concentra-tions of the measured POPs in the different fish species.
One of the weaknesses of this study is the small sample size forsome species at several locations, due to practical limitations andthe absence of the species at these locations. We are aware of thesmall sample size for C. africana and Macrobrachium sp. Also thetotal number of fish in the Itimbiri is low (n = 9). However, thesedata represent the first baseline data for these contaminants in theCongo Basin and as such they are valuable for future studies.
3.3. Relationships between POP levels in biota and sediments
To evaluate POP-bioavailability to aquatic organisms, POP levels inthe biota tissues were related to POP concentrations in the sediment.Lipid-adjusted concentrations in biota were not correlated with sedi-ment concentrations, and normalisation of the latter for TOC contentdid not influence these relationships significantly.
Anothermethod to assess the relation between sediment concentra-tions and tissue concentrations of aquatic organisms is the use of BSAFs.The BSAF model assumes that (1) exposure time was long enough toapproach equilibrium between uptake and elimination, (2) both the or-ganism and its food are exposed to sediments, (3) the surface sedimentrepresents the sediment to which the organism is exposed and (4) theBSAF does not substantially change with varying environmental factors(Wong et al., 2001). The model is suggested as a useful first-levelscreening tool for predicting bioaccumulation and is used by regulatoryagencies to evaluate the risk of organic contaminants in the aquatic en-vironment (Bervoets et al., 2005).
The calculated BSAFs were similar to higher compared to BSAFsreported by other field based studies (Table 3). The higher BSAF valuescan be caused by different mechanisms. As discussed above, low levelsof POPs in sediments from tropical regions are not necessarily an indica-tion of low exposure. Before POPs sink to the sediment several otherdissipation processes seem to play an important role in tropical areaslike volatilisation, atmospheric dispersal and faster rates of degradation
Table 3Ranges (and median) of BSAFs for ∑PCBs, p,p′–DDE, ∑DDTs, BDE47 and BDE99 from the
(Iwata et al., 1994; Kannan et al., 1995; Larsson et al., 1995). This mayimply that the sediment POP levels are a poor indicator of the real expo-sure and bioavailability in these environments.
Additionally, it is possible that biomagnification of POPs in the foodweb is particularly strong, causing the transfer of POPs through the foodweb to be more important than the exposure to the sediment in deter-mining consumer POP levels (Ianuzzi et al., 2011; MacDonald et al.,2000;Wong et al., 2001). This hypothesis can be examined by exploringrelationships between POP levels or BSAF values and consumer trophiclevels. When only fish are taken into account, significant, but weak cor-relations are found between trophic level and the BSAF from CB118(r2 = 0.07, p = 0.04, N = 62), CB180 (r2 = 0.07, p = 0.03, N = 62),HCB (r2 = 0.09, p = 0.02, N = 62), -HCH (r2 = 0.09, p = 0.02,N = 62), BDE47 (r2 = 0.09, p = 0.02, N = 62) and BDE183 (r2 =0.08, p = 0.03, N = 62) (Fig. S-2). With invertebrates included, onlythe BSAF of BDE183 was significantly correlated with trophic level.We conclude that biomagnification of POPs through the food webdoes not offer an explanation for the observed high BSAF values.
The BSAF method assumes that sediment samples collected fromthe same location as the organism reflect the organisms' exposureto POPs but how reflective are the sediment samples for the actualorganism's recent exposure (Burkhard et al., 2005). Marcusenius sp.,S. marmoratus, S. alberti, B. imberi and S. grenfelli are demersal omniv-orous and carnivorous fish. D. fasciolatus is an herbivorous fish specieswith consequently a different route of exposure to POPs. BSAF valuesfor D. fasciolatus were significantly lower than BSAFs for Marcuseniussp., S. marmoratus, S. alberti and B. imberi of the most dominant PCBs,HCB, p,p′-DDE, p,p′-DDT, -HCH and most dominant PBDEs. However,S. grenfelli is a predatory fish and yet BSAF values of HCB, p,p′-DDE, p′,p′-DDT, -HCH and the most dominant PBDEs were significantly lowerthan for Marcusenius sp., S. alberti and B. imberi (Fig. S-3). No signifi-cant differences in BSAF values between different invertebrate spe-cies were found.
It is important to recognise that the assumptions behind the BSAFmodel are often violated in in situ riverine conditions due to non-equilibrium conditions. To evaluate the applicability of the BSAF con-cept for risk assessment, correlations between exposure concentrationsand BSAFs were analysed, using log-transformed data of sediment con-centrations and BSAF (Bervoets et al., 2005). For all considered POPs, asignificant inverse relationship was found between the sediment con-centrations and BSAF values in S. marmoratus and Pila sp. with r2 valuesfrom 0.29 to 0.93 and 0.67 to 0.95, respectively (Fig. 3). For other
present study compared with BSAFs reported in other studies.
Ianuzzi et al. (2011) Xiang et al. (2007) Wong et al. (2001)
Metapenaeus ensis Various bivalves
(3)(6)
3–12 (6)2–10 (4)
Fundulus heteroclitus Platycephalus indicus Various fish
Fig. 3. Relationship between sediment concentrations and BSAF for CB153 and BDE99 in Schilbe marmoratus (N = 17) and p,p-DDE and ɣ-HCH in Pila sp. (N = 14).
Table 4Slope, r2, and p-value of slope of regression analysis between logarithm of concentrationand TLs for which significant relations were found, and TMFs for different pollutants perlocation. Log Kow of the different pollutants are shown (a: Svendsgaard et al., 1997;b: Han et al., 2011; c: Braeckevelt et al., 2003).
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species, no relationship or weak inverse correlations were found. In theconditions of the present study, the BSAF concept appears to be a poorpredictor of the bioavailability of environmental pollutants.
3.4. Stable isotopes as descriptors of bio-magnification
3.4.1. Food web structureRanges and median levels of nitrogen stable isotope ratios in the
biota species are given in Table 2. Trophic levels ranged from 2.0for Pila sp. to 4.5 ± 0.23 for the S. grenfelli. Fig. S-4 shows theaverage trophic levels for each species for all locations together. Onaverage, trophic levels increased from herbivores to omnivores andto carnivores.
3.4.2. Trophic transfer and trophic magnification factorsTrophic transfer refers to the movement of chemicals from lower
to higher trophic levels of the food chain. During trophic transfer,chemicals can biomagnify, if its concentration increases from one tro-phic level to the next (Fisk et al., 2001; Gobas and Morrison, 2000).
Understanding the trophic transfer of POPs in biota from the CRBis critical to evaluate the influence of these contaminants on ecosys-tems and human health. TMFs were suggested as a reliable tool forbiomagnification assessment of POPs and represent the averagefood web accumulation. If the TMF is higher than 1, biomagnificationoccurs in the food web.
Significant relationships between TL and the log of most dominantPCBs and p,p′-DDT in the Itimbiri river, BDE47 and BDE99 in Itimbiri,Aruwimi and Lomami, HCB in Aruwimi and Lomami and -HCH inLomami were observed. From the slopes of these relationships, TMFswere calculated according to Eq. (2). Table 4 summarises the slope, r2,level of significance and calculated TMFs of these results and Fig. 4 visu-alises the relationships between TL and log pollutant concentration. Inconclusion, TL plays an important role in the movement of differentPOPs through the food web of the different tributaries of the CongoRiver Basin.
Ikemoto et al. (2008) also found also a significant positive increaseof concentrations of DDTs and a positive trend for PCBs with anincrease of TL through the Mekong Delta food web. Significantbiomagnification of DDT and PCB through a tropical aquatic food
web in Lake Malawi and Lake Chad has also been reported by Kiddet al. (2001, 2004) and in the Okavango delta, Botswana (Mbongweet al., 2003).
In the present study, TMF values are higher than 1, indicating thatbiomagnification occurs in the food web of the Congo River Basin.TMFs ranged between 1.6 for -HCH in the Lomami and 3.6 forBDE99 in the Lomami (Table 4). It was stated that organic compoundswith an octanol-water partition coefficient (log Kow) smaller than 5have lower potential for biomagnification, while organic pollutantswith a log Kow between 5 and 7 have the highest potential forbiomagnification (Ikemoto et al., 2008). Our results confirm thesefindings. Fig. 5 shows TMFs versus log Kow for the different measuredPOPs.
Fig. 4. Relationship of log concentrations of the most dominant PCBs, ppDDT, HCB, -HCH, BDE47 and BDE99 and TLs of different food webs in the Itimbiri (N = 13) (a), Aruwimi(N = 15) (b) and Lomami (N = 30) (c).
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In conclusion, dietary habits of the fish determined their contam-inant concentrations with the highest pollutant levels found in thespecies from the upper trophic levels.
3.5. Risk for human health
As discussed above, POPs are accumulated and biomagnified in theaquatic organisms of the CRB food web. The effects of POP pollution aremanifested most explicitly at the level of top-predators, including
log Kow
TM
F
2 4 6 80
1
2
3
4
C B 9 5
C B 1 0 1
C B 1 1 0 C B 1 4 9
C B 1 4 6
C B 1 5 3
C B 1 3 8
C B 1 8 7
C B 1 7 4
p p -D D T
H C B
B D E 9 9
γ -HCH
B D E 4 7
Fig. 5. TMFs versus log Kow for the different measured POPs.
human consumers of contaminated freshwater fish (Du Preez et al.,2003). The Agency for Toxic Substances and Disease Registry (ATSDR,2010) has determined Minimum Risk Levels (MRL) for oral intake ofPOPs. With these MRLs, the maximum amount of fish which can be con-sumed without risk for an average person of 70 kg is calculated withthe observed POP concentrations in Marcusenius sp. from the Itimbiririver (Table 5). For PCBs, a person of 70 kg who consumes more than70 g/day of Marcusenius sp., exceeds the MRL for PCBs (30 ng/kg bodyweight/day). The banks of the Itimbiri River are populated with subsis-tence fishermen and fish is the main protein source for these communi-ties. In addition, fish is caught, smoked and sold in larger cities. Thus, fishof the Itimbiri River is intensively consumed and thismight have implica-tions on the health of the population. PCBs have been demonstrated tocause a variety of adverse health effects such as cancer and effects onthe immune, reproductive, nervous and endocrine system (USEPA,2012). For PBDEs and OCPs in the Itimbiri, no risk for human health is
Table 5Maximum amounts which are recommended to eat without risk of pollution for an av-erage person of 70 kg based on MRLs (ATSDR, 2010) and mean concentrations of totalPCBs, PBDEs, DDXs and ɣ-HCH found in Marcusenius sp. from the Itimbiri River.
∑PCBs ∑PBDEs ∑DDXs ɣ-HCH
MRL (ng/kg body weight/day) 30 7000 500 10MRL (ng/day) for a person of 70 kg 2100 490,000 35,000 700Mean concentration in Marcusenius sp.(ng/g ww) of Itimbiri River
30 0.09 0.19 0.19
Maximum edible amount ofMarcuseniussp. per day (g ww) for a person of 70 kg
70 556,818 184,210 3684
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determined. In addition, consumption of fish from the Aruwimi, Lomamiand the CR (Isangi and Kisangani) is without risk for POP pollution.
Acknowledgements
Samples were taken during the Boyekoli-Ebale-Congo Expeditionin May–June 2010 (www.congobiodiv.org) organised by the RoyalMuseum of Central Africa (Tervuren, Belgium), the University ofKisangani (DR Congo), the Royal Belgian Institute of Natural Sciencesand the National Botanical Garden of Belgium. Financial support wasprovided by the Belgian Development Cooperation, the Belgian SciencePolicy (Boyekoli-Ebale-Congo Expedition, and SSD-COBAFISH project),and the National Lottery. Financial support for this research partiallycame from the Research Foundation Flanders, FWO (1.5.182.13N).
We would like to thank Mongindo Etimosundja Jean Papy, VrevenEmmanuel,Musschoot Tobias, VanBocxlaer Bert, FrançoisDarchambeau,and Alberto Vieira Borges for the help in the field and Liesbeth Weijs forthe help with POP analysis. Zita Kelemen provided technical assistancefor the stable isotope measurements. Adrian Covaci was financiallysupported by a postdoctoral fellowship from the Research ScientificFoundation–Flanders (FWO), and Katya Abrantes by an EU-FP7 Marie-Curie postdoctoral scholarship.
Appendix A. Supplementary data
Supplementary data to this article can be found online at http://dx.doi.org/10.1016/j.envint.2013.05.015.
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