Chemosphere 91 (2013) 205–211
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Exposure to typical persistent organic pollutants from an electronic waste recycling site in Northern China q Qiaoyun Yang a, Xinghua Qiu a,⇑, Ran Li a, Shasha Liu b, Keqiu Li c, Fangfang Wang c, Ping Zhu d, Guang Li c,⇑, Tong Zhu a a State Key Joint Laboratory for Environmental Simulation and Pollution Control, College of Environmental Sciences and Engineering and Center for Environment and Health, Peking University, Beijing 100871, PR China b Tianjin Central Hospital of Gynecology Obstetrics, Tianjin 300100, PR China c Basic Medical College, Tianjin Medical University, Tianjin 300070, PR China d Department of Hematology, Peking University First Hospital, Beijing 100034, PR China
h i g h l i g h t s " We measured organohalogen pollutants in human serum from an e-waste site unreported. " Multivariate regression was applied to explore influencing factors of exposure. " Elevated exposure to most pollutants was associated with imported e-waste. " Local residents suffered equal exposure to relatively high volatile pollutants.
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Article history: Received 25 June 2012 Received in revised form 6 November 2012 Accepted 15 December 2012 Available online 31 January 2013 Keywords: E-waste recycling Organohalogen pollutants Serum Exposure Multivariate linear regression Northern China
a b s t r a c t Human exposure to pollutants from e-waste is an important scientific issue for their health effects. In this study, organohalogen pollutants in human serum sample from an e-waste dismantling site (n = 35) and a control site (n = 21), both located in Tianjin, Northern China, were analyzed using GC–ECNI–MS. Geometric mean concentrations of tetra- through hexa-BDEs, hepta- through nona-BDEs, PCBs, PBB-153, and DP in the exposure group were 2.77, 12.2, 44.1, 0.52, and 7.64 ng g1 lipid, respectively, which ranged from 1.5 to 7.4-fold higher than those in the control group through multivariate regression analysis, indicating that working and/or living in the e-waste site was associated with elevated body concentrations of these pollutants. Pollutants with low vapor pressures (i.e., hepta- through nona-BDEs and DP) were at significantly higher levels for e-waste dismantling workers than for local residents living around the e-waste site, suggesting higher exposure to these pollutants might exist for the occupational workers. Ó 2012 Elsevier Ltd. All rights reserved.
1. Introduction Halogenated persistent organic pollutants (POPs), such as polychlorinated biphenyls (PCBs), polybrominated diphenyl ethers (PBDEs), and polybrominated biphenyls (PBBs), are of great concern because of their persistence in the environment, bioaccumulation in biota, and potential toxicity (Hites, 2004). Because of their ubiquity and adverse health effects on human beings, these
q Main finding: E-waste imported leads to elevated exposure for both dismantling workers and local residents, especially for pollutants such as PCBs, PBB-153, tetrathrough nona-BDEs, and DP. ⇑ Corresponding authors. Tel.: +86 10 6275 3184; fax: +86 10 6276 0755 (X. Qiu). Tel./fax: 86 22 2354 2553 (G. Li). E-mail addresses:
[email protected] (X. Qiu),
[email protected] (G. Li).
0045-6535/$ - see front matter Ó 2012 Elsevier Ltd. All rights reserved. http://dx.doi.org/10.1016/j.chemosphere.2012.12.051
chemicals have been listed in the Stockholm Convention on persistent organic pollutants (Stockholm Convention Homepage, 2011), and most of these compounds have been banned or withdrawn for commerce (Fries, 1985; Renner, 2004). However, as mass production and widespread use in the past (Breivik et al., 2002; Patterson et al., 2009), for instance, added into the electronic products as flame retardants, these pollutants may re-enter the environment during the process of elimination and dismantling of discarded electronic waste (e-waste) (Wang et al., 2007). It is estimated that the global annual output of e-waste is 20– 50 million tons (Chen et al., 2010), which contain 76,200– 182,000 kg PBDEs (Ni et al., 2010). In China, in addition to domestic e-waste, cross-border transfers of e-waste are a major concern. Significant amounts of e-waste from overseas have been exported to China (Schwarzer et al., 2005; Schmidt et al., 2006; Cobbing
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et al., 2008; Robinson, 2009; Chen et al., 2011a,b; Zhou et al., 2010). Zhou and Xu, (2012) reported that imports of e-waste from overseas to China by illegal ways were nearly 28 million tons in 2010. At these sites, e-waste dismantling workers strip electronic wires and cables, recycle printed circuit boards and electrical appliances, and burn e-waste residues without taking personal protection measures. Under these circumstances, pollutants contained in e-wastes are released and partly enter the human body through multiple exposure pathways, such as inhalation, dermal contact and dust ingestion (Jones-Otazo et al., 2005; Stapleton et al., 2005; Allen et al., 2008). The elevated levels of pollutants released from e-wastes which workers, and possibly local residents, are exposed and taken up can cause serious health effects (Bi et al., 2007). Lots of studies have found that high levels of exposure to PBDEs and PCBs may be related to health problems such as thyroid hormone disruption and gene damage (Yuan et al., 2008; Zhang et al., 2010b; Chen et al., 2011a,b). Evaluating pollutant exposure levels in the e-waste recycling region is required in order to assess subsequent health effects. The aim of this study was: (1) to investigate levels of exposure to typical pollutants related to e-waste dismantling and recycling processes, including PBDEs, PBBs, Dechlorane Plus (DP), and PCBs, by measuring their concentrations in serum samples of a population (including e-waste dismantling workers and local residents) from a town in Northern China. This town, as a large-scale e-waste recycling site, has never been reported before; and (2) multivariate regression models were used to investigate the major factors impacting serum levels of these pollutants and further to explore characteristics of different pollutants. Serum pollutant levels are important to reveal the subsequence health effects of e-waste recycling.
2. Experimental methods 2.1. Subjects The e-waste recycling site (N 38.825°, E 116.777°; Fig. S1) in this study is located about 50 km southwest of Tianjin in Northern China, and has been a site of e-waste dismantling and recycling for more than 20 years. The site is composed of many family workshops scattered throughout the town, and has become the largest in Northern China and one of the main receivers of overseas ewaste. In these small workshops, dismantling and recycling procedures, which include stripping and open burning, are still crude and unsafe with no controls or protection measures. In this study, people living in the e-waste recycling region were defined as the exposure group, and those living 40 km away (N 38.636°, E 117.135°; Fig. S1) were chosen as the control group. The exposure and control groups are located in the same county (Fig. S1), and share similar environmental conditions and personal lifestyles, except that no e-waste dismantling occurred or occur in the control region. The exposure group consists of e-waste dismantling workers and local residents; the latter group lives in proximity to the ewaste plants but has never been engaged in dismantling. All study participants were randomly recruited, and blood samples of theirs were collected on April, 2009 and November, 2010. Whole blood samples were collected in 5-mL separation gel vacuum blood tubes, and centrifuged at 2000 rpm for 10 min to collect the serum fraction. All serum samples were frozen at 20 °C until analysis. The demographic information of the study population, including age, gender, occupation, and personal lifestyle was obtained through face to face questionnaire surveys (Table S1). This study was approved by the Institutional Review Board of Tianjin Medical University, and informed consent was obtained from every participant.
2.2. Chemicals Standard mixtures of brominated flame retardants (including PBDEs, PBB-153, 1,2-bis(2,4,6-tribromophenoxy)ethane, and decabromodiphenyl ethane), PCBs, syn- and anti-DP, and 13C12-BDE209 were purchased from Wellington Laboratories (Guelph, ON, Canada). PCB-65, -153, -155, -194, and BDE-77 and -118 were obtained from AccuStandard (New Haven, CT, USA), and 13C12-BDE208 from Cambridge Isotope Laboratories (Cambridge, MA, USA). All standard chemicals were diluted with isooctane and stored at 20 °C. All organic solvents and water were residue grade from Fisher Scientific (Fair Lawn, NJ, USA). Bio-Beads S-X3 from BioRad Laboratories (Hercules, CA, USA) were used as filler for the gel permeation chromatogram (GPC) column. Alumina (50– 200 lm, MP BioMedicals, Solon, OH, USA) and anhydrous sodium sulfate (Sigma–Aldrich, St. Louis, MO, USA) were baked at 450 °C for 4 h before use. 2.3. Sample preparation All participants in this study were randomly selected for analysis, including 35 serum samples from the exposure group (17 dismantling workers and 18 local residents) and 21 samples from the control group. Each sample (from 0.79 to 2.64 g, with an average weight of 1.72 g) was transferred into a clean centrifuge tube, weighed, and spiked with BDE-77, 13C-BDE-209, and PCB-65 as recovery surrogate standards. After treated with 20 lL b-glucuronidase/sulfatase (Helix Pomatia; Sigma–Aldrich, St. Louis, MO, USA) at 37 °C for 12 h, samples were extracted with 3 mL of hexane/ methyl tert-butyl ether (MTBE) (1:1, by volume) by vortex-mixture. After centrifugation, the extracts were transferred into a new tube, and the residue was extracted three more times. The combined extracts were blown down to 1.5 mL with nitrogen; 1.5 mL of potassium hydroxide (0.5 M, in 50% ethanol) was added, and samples were extracted three times with hexane. The extracts were concentrated to 2 mL, and interference by high molecular weight materials (e.g., lipid materials) was removed with a GPC column (1.34 cm i.d., packed with 9 g fully swollen beads). Samples were eluted with 70 mL of mixture solvent (cyclohexane/ethyl acetate, 1:1, by volume), and 21–40 mL were collected. The elution was then condensed and further cleaned with alumina column chromatography (6 cm 0.6 cm i.d., deactivated with 3% H2O overnight prior to use, with 0.5 cm anhydrous sodium sulfate on top). Target pollutants were eluted with 8 mL of hexane/dichloromethane (3:2 by volume) mixture solvent. Finally, samples were blown down and spiked with BDE-118, 13C12-BDE-208, and PCB155 as internal standards for GC/MS analysis. During these steps, samples were protected from light by wrapping the tubes and vials with aluminum foil or by using amber glassware. 2.4. Instrumental analysis The samples were analyzed by GC/MS (Agilent 7890/5975, Santa Clara, CA, USA) with an electronic capture negative ionization (ECNI) source. A non-polar Rtx-5 ms capillary column (15 m 0.25 mm i.d., 0.1 lm film thickness; Restek Corporation, Bellefonte, PA, USA) was used to separate all analytes with 1.5 mL min1 helium as the carrier gas. For PBDEs, 2,20 ,4,40 ,5,50 hexabromobiphenyl (PBB-153), and DP, the injection port and transfer line were at 280 and 290 °C, respectively. The GC oven temperature program was as follows: hold at 110 °C for 1 min, increase by 20 °C min1 to 200 °C and 5 °C min1 to 300 °C, and hold for 5 min. For PCBs, the injection port and transfer line were at 250 and 280 °C, respectively. The GC oven temperature program was as follows: hold at 70 °C for 1 min, increase by 6 °C min1 to 235 °C and 25 °C min1 to 300 °C, and hold for 2 min. The ion source
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and quadrupole temperature were both set at 150 °C. The following ions were monitored: m/z 487 and 489 for BDE-207, 208, and 209; m/z 409 and 411 for BDE-197 and 201; m/z 79 and 81 for all the other brominated chemicals; m/z 654 and 652 for DP; m/z 326, 324, and 328 for penta-CBs; m/z 360, 358, and 362 for hexaCBs; m/z 394, 396, and 398 for hepta-CBs; m/z 430 and 428 for octa-CBs; m/z 464, 462, and 466 for nona-CBs; and m/z 498 and 496 for deca-CB. The instrument detection limit (IDL) was determined as three times of standard deviation from six standard solutions, in which concentrations of the target compounds could produce a signal-to-noise ratio of about 10. The method detection limit (MDL) was estimated based on IDL. The MDL was estimated at 0.045–0.24 ng g1 lipid for PCBs, 0.074–0.68 ng g1 lipid for PBDEs, 0.049 ng g1 lipid for PBB-153, 0.19 and 0.30 ng g1 lipid for anti-DP and syn-DP, respectively.
2.6. Statistics Concentration data of all the chemicals were logarithmically transformed to obtain normal distribution; and log-transformed normal distribution was confirmed by Kolmogorov–Smirnov test (Perry et al., 2004; Mathur, 2010). Differences between groups were examined by independent-samples t-test. A two-tailed P value of 0.05). The data collected were blank but not recovery corrected. In this study, concentration data were expressed on a lipid basis. The lipid concentrations were determined as described previously (Rylander et al., 2006). The median concentrations on wet weight basis are also shown in the Supplementary material (Tables S2 and S3).
3.1. Serum levels of analytes We assessed 34 PBDE congeners, 19 of which (including BDE47, -49, -66, -99, -100, -138, -153, -154, -171, -180, -183, -184, 196, -197, -201, -203, -207, -208, and -209) were reported here after performing a blank check and excluding congeners with a detection rate of lower than 50%. To correspond with commercial products, PBDEs in this study were grouped into three categories: PBDE4–6, PBDE7–9, and BDE-209 (Table 1), which were mainly from commercial penta-, octa-, and deca-BDE, respectively. The geometric mean concentrations of these three groups in human serum samples from the exposure area were 2.8, 12.2, and 4.5 ng g1 lipid, respectively. Those from the control area were 1.1, 5.9, and 4.0 ng g1 lipid, respectively. For PBDE4–6 and PBDE7–9, serum levels of the exposure group were significantly higher than those of the control group (P < 0.001), but this was not the case for BDE209 (P = 0.83).
Table 1 Concentrations (ng g-1 lipid) of PBDEs, PCBs, BB-153, and DP in human serum samples from exposure and control areas. Pollutant
Exposure group (n = 35) %
BDE-47 BDE-99 BDE-100 BDE-153 BDE-183 BDE-209 PBDE4–6d PBDE7–9e P f 19PBDEs PCB-105 PCB-118 PCB-153 PCB-156 PCB-194 PCB-209 P g 17PCBs BB-153 DP h a b c d e f g h
a
97 100 100 100 100 91 – – – 100 100 100 100 100 100 – 100 –
Control group (n = 21) b
Exposure/control ratio (95% CI; P)
Geometric mean
Median (IQR)
%
Geometric mean
Median (IQR)
0.43 0.081 0.14 1.59 0.61 4.52 2.77 12.2 24.2 4.52 12.0 19.5 1.61 1.63 0.88 44.1 0.52 7.64
0.50 (0.21–0.80) 0.084 (0.048–0.13) 0.14 (0.085–0.21) 1.45 (0.93–2.37) 0.53 (0.34–1.21) 5.73 (1.80–12.3) 2.67 (1.77–4.21) 12.3 (7.49–17.2) 23.0 (10.9–34.8) 4.28 (2.44–7.63) 11.8 (6.45–22.2) 19.5 (9.10–31.3) 1.67 (0.81–3.56) 1.40 (0.90–2.8) 0.86 (0.49–1.5) 39.6 (20.0–72.9) 0.52 (0.25–1.04) 6.29 (4.21–12.4)
95 91 100 100 100 86 – – – 100 100 100 100 100 100 – 43 –
0.13 0.051 0.072 0.55 0.17 4.00 1.08 5.87 16.5 1.01 2.43 6.47 0.40 0.48 0.33 12.4 0.029 1.05
0.16 (0.11–0.25) 0.045 (0.023–0.081) 0.059 (0.050–0.081) 0.58 (0.21–0.90) 0.17 (0.12–0.29) 5.87 (0.64–25.9) 0.97 (0.59–1.52) 5.77 (4.10–8.18) 14.6 (7.35–35.5) 0.99 (0.61–1.34) 2.33 (1.41–3.48) 6.52 (3.65–10.5) 0.38 (0.24–0.70) 0.45 (0.29–0.83) 0.33 (0.21–0.53) 12.4 (7.3–19.3) 0.024 (0.024–0.033) 1.06 (0.53–1.79)
Detection rate of the specific pollutants. IQR: interquartile range. Calculated by multivariate linear regression models with stepwise approach. PBDE4–6: sum of BDE-47, -49, -66, -99, -100, -138, -153, and -154. PBDE7–9: sum of BDE-171, -180, -183, -184, -196, -197, -201, -203, -207, and -208. P PBDEs: sum of all 19 PBDE congeners. P19 17PCBs: sum of PCB-105, -114, -118, -123, -126, -153, -156, -157, -167, -169, -189, -194, -202, -205, -206, -208, and -209. DP: sum of anti-DP and syn-DP.
2.7 (1.4–5.3;
