Organic contaminants and heavy metals in indoor dust from e-waste recycling, rural, and urban areas in South China: Spatial characteristics and implications for human exposure

Ecotoxicology and Environmental Safety 140 (2017) 109–115

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Organic contaminants and heavy metals in indoor dust from e-waste recycling, rural, and urban areas in South China: Spatial characteristics and implications for human exposure

MARK

⁎

Chun-Tao Hea,b, Xiao-Bo Zhengc,d, Xiao Yanb, Jing Zhengb, , Mei-Huan Wangb, Xiao Tana, ⁎ Lin Qiaoa,b, She-Jun Chend, Zhong-Yi Yanga, , Bi-Xian Maid a

Laboratory for Biocontrol, School of Life Sciences, Sunat-sen University, Guangzhou 510275, China State Environmental Protection Key Laboratory of Environmental Pollution Health Risk Assessment, South China Institute of Environmental Sciences, Ministry of Environmental Protection, Guangzhou 510655, China c College of Resources and Environment, South China Agricultural University, Guangzhou 510642, China d State Key Laboratory of Organic Geochemistry and Guangdong Key Laboratory of Environmental Protection and Resources Utilization, Guangzhou Institute of Geochemistry, Chinese Academy of Sciences, Guangzhou 510640, China b

A R T I C L E I N F O

A B S T R A C T

Keywords: E-waste recycling Organic contaminants Heavy metals Human exposure Indoor dust

The concentrations of several organic contaminants (OCs) and heavy metals were measured in indoor dust from e-waste recycling, rural, and urban areas in South China to illustrate the spatial characteristics of these pollutants and to further evaluate human exposure risks. The median concentrations of polychlorinated biphenyls (PCBs), polybrominated diphenyl ethers (PBDEs), decabromodiphenyl ethane (DBDPE), and dechlorane plus (DPs) were 38.6–3560, 2360–30,100, 665–2720, and 19.5–1860 ng/g, while the median concentrations of Cd, Pb, Cu, Cr, and Zn were 2.46–40.4, 206–1380, 217- 1200, 25.3–134, and 176–212 μg/g in indoor dust. The levels of all pollutants, except Zn, in dust from the e-waste recycling area were significantly higher than those from the other areas. Cd, Pb, and most OCs exhibited similar pollution patterns in the three areas, indicating that e-waste recycling activities are the major pollution source. In contrast, Cu, Cr, Zn, and penta-BDE are likely derived from household products in the rural and urban areas. The highest estimated daily intakes (EDIs) of PCBs, PBDEs, DBDPE, and DPs were 0.15–163, 3.97–1470, 1.26–169, and 0.11–134 ng/kg bw/day for toddlers and adults. The highest EDIs of BDE 209 and Pb in toddlers in the e-waste recycling area were 16% and 18 times higher than the reference doses, indicating the high exposure risk of these pollutants in the e-waste recycling area.

1. Introduction Industrial additives are widely used to meet specific product standards and can be converted to organic contaminants (OCs) after their release into the environment. Polychlorinated biphenyls (PCBs) were historically used in electrical transformers and capacitors in heat transfer and insulating fluids before their classification as persistent organic pollutants (POPs) in the Stockholm Convention (UNEP, 2001) and subsequent ban. Polybrominated diphenyl ethers (PBDEs) are important flame retardants (FRs) that are widely applied in electronic products to meet rigorous flammability standards. Because of their persistence, bioaccumulation, and toxic characteristics, penta- and octa-BDEs are listed as POPs in the Stockholm Convention (UNEP, 2009). The use of BDE 209 has also been restricted in the USA (US EPA IRIS, 2013). Market demand for PBDE alternatives has boosted the

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production of alternative FRs, such as dechlorane plus (DPs) and decabromodiphenyl ethane (DBDPE) (Covaci et al., 2011; Sverko et al., 2011). Different OCs exhibit various biotoxicities, such as oxidative stress, hepatotoxicity, neurotoxicity and endocrine disruption (Costa and Giordano, 2007; Delfosse et al., 2015; Liu et al., 2012; Lu et al., 2016). Apart from OCs, heavy metals are another kind of pollutant, despite their natural presence in rock and soil. An elevated body burden of heavy metals in humans can result in acute and chronic toxicity, such as damage to the kidneys and bones (Leung et al., 2008). Indoor dust ingestion has been recognized as a main route of human exposure to environmental pollutants (Harrad et al., 2008; Jones-Otazo et al., 2005; Ni et al., 2013; Trudel et al., 2011). Numerous studies have reported the occurrences of heavy metals (Kurt-Karakus, 2012; Rasmussen et al., 2001) as well as OCs, such as PBDEs, in indoor dust worldwide (Suzuki et al., 2009; Wensing et al., 2005; Whitehead et al.,

Corresponding authors. E-mail addresses: [email protected] (J. Zheng), [email protected] (Z.-Y. Yang).

http://dx.doi.org/10.1016/j.ecoenv.2017.02.041 Received 4 January 2017; Received in revised form 23 February 2017; Accepted 24 February 2017 0147-6513/ © 2017 Elsevier Inc. All rights reserved.

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samples are presented in Supplementary material.

2015). High levels of OCs and heavy metals have been reported in indoor dust from e-waste recycling areas over the past decades (Fujimori et al., 2012; He et al., 2015; Tue et al., 2013). PBDE concentrations in indoor dust from e-waste recycling areas ranged from 685 to 63,300 ng/g, and PCBs were also observed at higher levels in ewaste recycling areas (Leung et al., 2011; Wang et al., 2010; Zheng et al., 2015) than those in domestic dust from urban areas (Harrad et al., 2008). Similar trends were discovered for heavy metal contamination of indoor environments in e-waste recycling areas (Liu et al., 2013; Song and Li, 2014; Zhu et al., 2012). Meanwhile, an increasing trend in alternative FRs was observed. For instance, the median level of DBDPE grew at least 18-fold from 2010 to 2015 in an e-waste recycling area in South China (Wang et al., 2010; Zheng et al., 2015). E-waste recycling activities are regarded as a significant source of contaminants in workshops and homes in e-waste recycling areas (Labunsk et al., 2013; Ma et al., 2009b). Nevertheless, the profiles of these contaminants are different in rural and urban homes, partly due to their emission from ornamental and electronic products, which have been recognized as the major source of indoor contamination (Allen et al., 2008; Kurt-Karakus, 2012; Rauert and Harrad, 2015). Although multiple organic and inorganic contaminants in indoor dust have been identified, the spatial characteristics and potential sources in different types of microenvironments still needs further investigation. Therefore, further analysis of indoor contamination is performed to elucidate the pollutant sources and potential exposure risks. In the present study, the contamination patterns of organic contaminants and heavy metals were studied in e-waste recycling, rural, and urban areas located in Guangdong province in South China. The aims of this study were (1) to investigate the levels and compositions of OCs and heavy metals from different areas; (2) to characterize the spatial characteristics and sources of pollutants in e-waste recycling, rural, and urban areas; and (3) to estimate the human exposure to organic contaminants and heavy metals via indoor dust ingestion for both adults and toddlers.

2.3. Instrumental analysis Details of the organic chemicals analysed in the present study are shown in Table S2 in Supplementary Material. Analysis was performed with an Agilent 6890-GC coupled to an Agilent 5975-MS operated with electron capture negative ionization (ECNI) in ion monitoring mode. A DB-5MS capillary column (60 m×0.25 mm ×0.25 µm, J & W Scientific, Folsom, CA) was used to separate the PCB congeners. A DB-XLB (30 m×0.25 mm ×0.25 µm, Agilent, USA) capillary column was used for the analysis of di- to hepta-BDE congeners and DPs, while a DB-5HT (15 m×0.25 mm ×10 µm, Agilent, USA) capillary column was adopted for the analysis of octa- to deca-BDEs and DBDPE. The analytical parameters were provided previously by Zheng et al. (2013) and Wang et al. (2010). Heavy metals were analysed by the atomic absorption spectroscopy (Shimazhu A7000, Japan). The instrument parameters for each heavy metal are shown in Table S3 in Supplementary material. 2.4. Quality control Procedural blanks (n =5) were conducted with each batch of samples in the analysis of organic pollutants. The mean recoveries of PBDEs, PCBs, DBDPE and DPs ranged from 65% to 114% in the three spiked blanks. The recoveries of surrogate standards (mean ± standard deviation) ranged from 66.7 ± 5.4% to 93.4 ± 1.5%. The limits of quantification (LOQs) were set as the mean values of the target compounds detected in the procedural blanks plus three times the standard deviation. For non-detected compounds in the blanks, the limits of detection (LODs) were defined as a signal to noise ratio of 3. The LOQs ranged from 0.1 to 13 ng/g for all detected organic pollutants. The levels of the studied analytes were all blank-corrected. Repeatability of the analysis was assessed by analysing three replicate dust samples, and the relative standard deviation was within 10% for studied chemicals. Procedural blanks (n =5) were run with each batch during sample digestion for heavy metal determination. The reliability of the analytical procedure was assessed with standard reference materials (SRMs) obtained from the National Research Center for Certified Reference Materials (Beijing, China, soil GBW07403). The SRMs (n =3) were prepared in the same batches as the dust samples. The values of the detected heavy metals were in agreement (RSD < 15%) with reference values or published values.

2. Experimental 2.1. Sampling Indoor dust samples (n =78) were collected from three different areas in southern China between September 2013 and March 2014. The urban house dust samples (n =28) were collected from residential rooms, such as homes and school dormitories, in Guangzhou City. Twenty dust samples were collected from family-run e-waste recycling workshops in several villages in Qingyuan. Details of the dismantled ewaste are presented in Table S1 in Supplementary material. Dust samples (n =30) from villages without e-waste recycling activities (approximately 2–3 km away from the e-waste recycling region) were collected. The indoor dust samples were mainly obtained from the surface of furniture with woollen brushes and from floors of the bedroom and living rooms with a vacuum cleaner. The samples were wrapped in aluminium foil and sealed in locking polyethylene bags at −20 °C before further analysis. All dust samples were sieved through a 100 µm mesh stainless-steel sieve before further determination.

2.5. Exposure assessment The mean, 25th, and 95th percentile values of the pollutant concentrations in the dust samples were adopted. Mean dust ingestion rates of 20 and 50 mg/day and high dust ingestion rates of 50 and 200 mg/day were used for adults and toddlers, respectively (Van den Eede et al., 2011). The absorption efficiency was assumed to be 100% due to the lack of information on human absorption efficiency (JonesOtazo et al., 2005; Van den Eede et al., 2011). The average body weight (bw) of adults and toddlers (1–4 years old) were 63 and 13.8 kg, respectively, according to the 2010 National Physique Monitoring Bulletin in China.

2.2. Sample preparation Approximately 50 mg of the sieved samples was used for chemical analysis. Internal standards (CB 30, CB 65, and CB 204, BDE 77, BDE 181, BDE 205, and 13C-BDE 209) were added to the dust samples before extraction. The methods of sample extraction and purification are detailed in Supplementary material. Prior to injection, surrogate standards (4-F-BDE 67, 4-F-BDE 153, BDE 118, BDE 128, CB 24, CB 82, and CB 198) were added to each sample. For heavy metal determination, the samples were digested in a microwave digestion system (Topex, Preekem, China). The digestion and preparation of dust

2.6. Statistical analysis Statistical analysis was performed using the SPSS 18.0 software package (SPSS, Inc.). For sample concentrations under the LOQs, the values were assigned as 1/2 LOQs for further analysis. Log-transform was applied to pollutant concentrations to obtain the normal distribution before statistical analysis. One-way analysis of variance (ANOVA) was conducted to compare the concentrations of contaminants from 110

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Table 1 Concentrations of heavy metals (μg/g) and organic contaminants (ng/g) in indoor dust from the three studied areas. E-waste recycling region

Cd Pb Cu Cr Zn CB 28 CB 52 CB 101 CB 118 CB 138 CB 153 CB 180 ∑7PCBs BDE 47 BDE 99 BDE 100 BDE 153 BDE 154 BDE 183 BDE 206 BDE 207 BDE 208 BDE 209 ∑PBDEs DBDPE syn-DP anti-DP

Rural region

Urban region

mean

median

range

mean

median

range

mean

median

range

49.3 1980 1340 170 306 1050 588 467 556 557 580 180 3980 180 318 46.4 102 40.6 313 2930 3060 1300 34,800 44,200 4270 954 2090

40.4 1380 1200 134 212 778 477 349 338 389 421 132 3560 147 234 36.8 71.0 32.7 143 1620 1540 730 23,800 30,100 2720 558 1250

14.5–186 410–4620 943–4060 14.1–629 180–752 154–3940 65.9–2770 50.4–1480 65.0–1990 88.5–2110 94.4–2150 49.5–573 568– 11,500 45.9–600 72.7–1070 11.6–150 21.4–405 10.9–122 38.0–1370 418–23,200 389–24,100 185–9460 8530–152,000 9960–211,000 669–15,000 141–3420 236–9480

4.18 392 505 29.4 254 50.2 34.1 15.2 23.6 33.2 34.5 23.0 214 110 187 31.7 27.0 16.4 48.9 352 440 145 4110 5650 747 115 212

2.65 262 351 25.3 176 38.5 31.7 10.6 15.1 26.2 28.8 23.2 179 14.2 17.3 3.11 8.72 3.91 29.7 289 356 117 3570 4810 665 85.8 145

1.32–12.1 124–1370 196–1200 0.00–77.6 119–750 16.2–131 nd −64.1 4.83–42.8 5.70–128 nd −128 nd −114 nd −69.3 55.3–658 4.19–2490 3.23–4920 0.73–819 0.89–471 1.13–360 2.82–374 2.49–1890 3.13–2290 17.9–839 257– 11,600 372–16,800 211–1900 8.61–679 15.2–1040

2.45 214 235 41.6 180 15.3 17.2 5.25 2.52 nd nd nd 61.7 3.08 4.52 1.02 2.77 1.33 6.09 133 156 34.5 2620 3080 1030 7.44 28.2

2.46 206 217 35.4 185 nd nd nd nd nd nd nd 38.6 2.21 2.37 0.76 1.34 0.99 nd 86 129 nd 2050 2360 727 4.74 13.2

0.00–5.16 75.6–456 12.8–470 0.00–158 159–204 nd −77.0 nd −103 nd −37.6 nd −17.5 nd nd nd 38.6–226 nd−14.0 0.32–19.1 nd−2.86 nd−25.1 nd−6.15 nd−52.7 6.39–302 30.2–386 nd−199 333–19,300 186–20,400 241–4420 0.21–43.5 0.15–152

ranged from 9960 to 211,000 ng/g in the e-waste recycling area with a mean concentration of 44,200 ng/g, which is higher than those in ewaste recycling areas in southeast (14,800 ng/g) (Leung et al., 2011) and southern (1440 ng/g) China (Wang et al., 2010) and far higher than those (89.6–143 ng/g) from eastern China (Ma et al., 2009a). Notably, a comparable median PBDE concentration (30,100 ng/g) was reported in the same studied area with a median value of 23,600 ng/g (Zheng et al., 2015), indicating more severe PBDE contamination in our studied ewaste recycling area than in other e-waste recycling sites in China. The median concentration of PBDEs was 4810 and 2360 ng/g in the rural and urban areas, respectively, which were significantly lower than the PBDE concentration in the e-waste recycling area (p < 0.05). The median concentration of PBDEs in indoor dust from the urban area in the current study was comparable to the median PBDE levels in indoor dust from Canada (2200 ng/g) and USA (3500 ng/g) (Harrad et al., 2008; Shoeib et al., 2012) and several times higher than those from Kuwait (356 ng/g), Pakistan (145 ng/g), Romania (375 ng/g), and Belgium (613 ng/g) (Ali et al., 2012; D'Hollander et al., 2010; Dirtu and Covaci, 2010), suggesting that PBDE application in household products in the urban area in the present study was similar that in North America. Since the continuous use of PBDEs is permitted in China, it is reasonable to expect the accumulation of PBDEs in residential indoor environments would continue. The contributions of BDE 209 were 80.1%, 73.7% and 77.2% in the e-waste recycling, rural and urban areas, respectively (Fig. S2 in Supplementary material). The predominance of BDE 209 has also been frequently reported in literature, which is derived from the pollution of deca-BDE mixtures. Median concentrations of DBDPE were 2720, 665 and 727 ng/g in the e-waste recycling, rural, and urban areas, respectively. The concentration of DBDPE in the e-waste recycling area was higher than that from e-waste recycling areas in Vietnam (peak at 1600 ng/g) (Tue et al., 2013) and South China (63.1 ng/g, median) (Wang et al., 2010). In rural and urban areas, the DBDPE levels were also higher than that from an urban area in Vietnam (peak at 150 ng/g) (Tue et al., 2013). The concentration of DPs ranged from 377 to 12,700, 26.6 to 1200, and 0.36 to 195 ng/g in the e-waste recycling, rural, and urban areas,

different sampling areas. Pearson's correlation analysis was adopted to explore correlations among the contaminants. Principal component analysis (PCA) was performed on the log-transformed contaminant values. The level of significance was set at p=0.05 throughout the study. 3. Results and discussion 3.1. Concentrations and congener profiles of organic pollutants The concentrations of the studied OCs and heavy metals are shown in Table 1. The median concentration of seven indicator PCBs (CB 28, CB 52, CB 101, CB 118, CB 138, CB 153, and CB 180) in indoor dust was 3560 ng/g in the e-waste recycling area, which is comparable with the PCB concentration reported in other e-waste recycling areas in Taizhou (2820 ng/g, mean) (Xing et al., 2011) and Qingyuan (2900 ng/g, median) (Zheng et al., 2015) in South China. Significant differences between the concentration of PCBs in the e-waste recycling area and the other two areas (179 and 38.6 ng/g in rural and urban areas, respectively) (p < 0.05) were observed, which is probably ascribed to the e-waste recycling of old electronic products. The PCB concentration in indoor dust from the urban area was slightly lower than that in Birmingham (48 ng/g) and New Zealand (46 ng/g) (Harrad et al., 2009). The low levels of PCBs in the urban area may be the outcome of the long-term ban of PCBs worldwide, and the value was similar to that in other urban areas (Chen et al., 2014). However, the dismantling of obsolete e-waste could still cause PCB contamination in the e-waste recycling area in the current study as well as other e-waste recycling sites around the world (Tue et al., 2013; Zheng et al., 2015). In regard to the PCB profiles, CB 28 and CB 52 were the dominant PCB congeners in the e-waste recycling area, which was similar to PCB profiles from other e-waste recycling areas (Xing et al., 2011; Zheng et al., 2013), implying e-waste was the most likely source of the PCBs. The concentration of PBDEs (BDE 28, BDE 47, BDE 66, BDE 85, BDE 99, BDE 100, BDE 138, BDE 153, BDE 154, BDE 183, BDE 196, BDE 197, BDE 202, BDE 203, BDE 206, BDE 207, BDE 208 and BDE 209) 111

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the median concentrations of Cd, Pb, Cu, Cr, and Zn were 40.4, 1380, 1200, 134, and 212 μg/g, respectively. The levels of Cd, Pb, Cu, and Cr in indoor dust from the e-waste recycling area were 3–15 times higher than those from urban and rural areas, which was obviously due to ewaste recycling activities. The Cd, Cu, and Pb concentrations in the ewaste recycling area in the current study were higher than the concentrations in indoor dust from another e-waste recycling area (Cd: 1.8 μg/g, Cu: 225 μg/g, Pb: 253 μg/g) (Zhu et al., 2012), while Pb concentration was lower than that (18,300 μg/g) in the study of Xue et al. (2012). These discrepancies among different e-waste recycling areas may mostly rely on the e-waste composition since the application of heavy metals in dismantled e-waste differs. The Zn concentration in indoor dust was comparable to that in e-waste recycling, urban, and rural areas, which implied that Zn is not derived from e-waste recycling but more likely from household products. The median concentration of Pb in dust from the urban and rural areas was 206 and 262 μg/g, respectively. The Pb concentration in indoor dust from urban homes was higher than those from Istanbul (28 μg/g), Warsaw (124 μg/g), and Sydney (76 μg/g) but slightly lower than those from Ottawa (222 μg/g) and Kwun Tong (308 μg/g) (Chattopadhyay et al., 2003; Kurt-Karakus, 2012; Rasmussen et al., 2001; Tong and Lam, 2000). The mean concentration of Cr in indoor dust from the rural and urban areas was 29.4 and 41.6 μg/g, respectively, which was lower than other areas (55–90 μg/g), while the Cd concentration in dust from the urban and rural areas was comparable to that in other studies (0.8–4.3 μg/g) (Chattopadhyay et al., 2003; KurtKarakus, 2012; Rasmussen et al., 2001; Tong and Lam, 2000). The background occurrence of heavy metals may significantly effect the different heavy metal levels between the studied areas and other cities around the world, since no occupational source was observed in the residents’ homes. The profiles of the five heavy metals are shown in Fig. S3 in Supplementary material. Pb was the dominant heavy metal in the ewaste recycling area with a mean contribution of 47.8%, followed by Cu (37.4%). The contributions of Zn, Cr, and Cd were 8.8%, 4.7%, and 1.3%, respectively, in the e-waste recycling area. Cu was the dominant heavy metal with contributions of 41.8% and 33.5% in the rural and urban areas, respectively. The proportion of Cd and Cr was generally lower than 5% in all studied areas.

Fig. 1. Principal component analysis results based on the log 10 transformed concentrations of PCB, PBDE, DBDPE and DP congeners, as well as that of five heavy metals (PC1, 52% variance; PC2, 26% variance). The figure legends represent the factor loadings (a) and factor scores (b).

3.3. Spatial characteristics and sources of the studied contaminants

respectively. The mean concentration of DPs in the urban (35.6 ng/g) and rural (327 ng/g) areas was higher than those reported in Wang et al. (2011) and Zheng et al. (2010), which were 18.9/18.9 and 5.99/ 64.9 in urban and rural homes, respectively. The elevated levels of DPs and DBDPE are probably ascribed to the increased market demand for alternative FRs, along with the phasing out of deca-BDE. Notably, the OCs from e-waste recycling activities were generally higher in rural area rather than the urban area, which was different from our previous observation of organophosphorus flame retardants which was higher in urban area rather than the rural (He et al., 2015). The elevated OC levels detected in the indoor dust from the rural area than in the urban area was likely due to the atmospheric transport of air/dust from the nearby e-waste recycling site. Thus, the lower concentrations of studied pollutants might be ascribed to the replacement of traditional indoor device in urban areas. Besides, the less electric and electronic products in the university dormitory might have partly explained the lower OC levels in urban area. Therefore, more attention should be paid to alternative FRs in e-waste recycling areas and urban indoor environments since new products containing alternative FRs are still in use in urban areas.

To investigate the spatial characteristics of the contaminant sources, principal component analysis (PCA) was adopted for the three studied areas (Fig. 1). The first two principal components accounted for 52% and 26% of the total variance, respectively. The factor score plot (Fig. 1a) exhibited critical information about the sample distribution for both factors. Indoor dust from the e-waste recycling area displayed high scores in factor 1, while the lowest scores were found for samples from the urban area, indicating that factor 1 mostly represents the characteristics of e-waste recycling activities. In regard to factor 2, the distribution of samples from the three areas was similar, suggesting that factor 2 reflected information about contamination from sources other than e-waste recycling activities. Different contaminants were categorized according to their loadings on both factors (Fig. 1b). PBDE congeners were classified into three clusters in relation to their commercial sources. Cluster 1 consisted of BDEs 183, 197, and 203, which are the major components in octa-BDE mixtures. Cluster 2 included the main chemicals in deca-BDE mixtures (BDEs 206, 207, 208, and 209). As replacement chemicals of the commercial product deca-BDE, DBDPE and DPs had similar loadings in PC1 and PC2 to those of BDE 209. Apparently, DBDPE, DP, octa-BDEs, and deca-BDE in dust are derived from similar sources, which can probably be attributed to ewaste recycling activities. Cd, Pb, and PCBs also showed similar loadings to octa-BDEs and deca-BDE, indicating that Cd, Pb, and PCBs were also released from the e-waste of circuit boards and electricity

3.2. Concentrations and patterns of heavy metals The concentrations of five heavy metals (Cd, Pb, Cu, Cr, and Zn) in indoor dust are summarized in Table 1. In the e-waste recycling area, 112

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Table 2 Daily intakes of contaminants (ng/kg bw/day) via indoor dust for adults and toddlers. Areas

Pollutants

Toddlers

Adults

Average ingestion

High ingestion

Average ingestion

High ingestion

mean

5th

95th

mean

5th

95th

mean

5th

95th

mean

5th

95th

E-waste recycling region

Cd Pb Cu Cr Zn PCBs PBDEs DBDPE DPs

179 7170 4850 615 1110 14.4 160 15.5 11.0

53.9 2210 3710 86 685 2.91 40.9 3.13 2.06

378 15,800 5690 1570 2310 40.7 367 42.3 33.6

715 28,700 19,400 2460 4440 57.6 640 61.8 44.2

216 8830 14,800 344 2740 11.6 164 12.5 8.25

1510 63,300 22,800 6300 9250 163 1470 169 134

15.7 629 425 53.9 97.3 1.26 14.0 1.35 0.97

4.72 193 325 7.54 60.0 0.25 3.58 0.27 0.18

33.1 1390 499 138 203 3.57 32.1 3.71 2.94

39.2 1570 1060 135 243 3.16 35.1 3.38 2.42

11.8 484 812 18.8 150 0.64 8.96 0.68 0.45

82.7 3470 1250 345 507 8.93 80.3 9.27 7.36

Rural region

Cd Pb Cu Cr Zn PCBs PBDEs DBDPE DPs

15.1 1420 1830 107 921 0.77 20.5 2.71 1.18

5.52 477 770 32.8 469 0.22 2.91 1.13 0.13

43.8 2840 4190 231 2480 1.54 47.9 5.73 3.67

60.6 5680 7320 427 3690 3.10 81.9 10.8 4.74

22.1 1910 3080 131 1880 0.87 11.7 4.53 0.50

175 11,300 16,800 922 9910 6.17 192 22.9 14.7

1.33 124 160 9.35 80.7 0.07 1.79 0.24 0.10

0.48 41.8 67.5 3.88 41.1 0.02 0.26 0.10 0.01

3.84 248 367 20.2 217 0.14 4.20 0.50 0.32

3.32 311 401 23.2 202 0.17 4.49 0.59 0.26

1.21 104 169 7.38 103 0.05 0.64 0.25 0.03

9.60 621 918 50.6 543 0.34 10.5 1.26 0.80

Urban region

Cd Pb Cu Cr Zn PCBs PBDEs DBDPE DPs

9.01 775 853 151 654 0.22 11.2 3.73 0.13

0.53 322 194 4.35 578 0.14 1.85 1.28 0.01

18.6 1460 1490 406 721 0.68 18.1 7.42 0.49

36.0 3100 3410 602 2620 0.89 44.6 14.9 0.52

2.12 1290 778 17.4 2310 0.56 7.40 5.11 0.05

74.4 5840 5970 1620 2890 2.71 72.6 29.7 1.97

0.79 67.9 74.7 13.2 57.3 0.02 0.98 0.33 0.01

0.05 28.2 17.0 0.38 50.6 0.01 0.16 0.11 0.00

1.63 128 131 35.6 63.2 0.06 1.59 0.65 0.04

1.97 170 187 33.0 143 0.05 2.44 0.82 0.03

0.12 70.6 42.6 0.95 126 0.03 0.41 0.28 0.00

4.07 320 327 88.9 158 0.15 3.97 1.62 0.11

not significantly correlated with most organic pollutants in the rural and urban areas, indicating the occurrence of Cd and Pb in dust from rural and urban areas could be attributed to local sources that are different from those of OCs. Significant correlations between BDEs 99/ 100 and Cr levels in the rural area and Zn levels in the urban area further supported the similar household source of Zn/Cr and the pentaBDE mixture in residential homes. In the three studied areas, Cd, Pb, and most of the OCs are derived from e-waste recycling activities, while Cu, Cr, Zn, and penta-BDEs are likely derived from household products in the rural and urban areas.

meters. Cluster 3 included BDEs 47, 66, 99, 100, 153, and 154, which are the main components in penta-BDE mixtures, and displayed lower scores in factor 2, which was in line with the distribution of the indoor dust from the urban area. Penta-BDEs are mainly applied in furniture and textiles, rather than electrical products. Although penta-BDEs have been banned since 2009 (UNEP, 2009), they can still leach from obsolete furniture into indoor environments in urban homes. Therefore, penta-BDEs may be derived from household products, rather than ewaste recycling activities. In addition, heavy metals, including Cr, Zn and Cu, were loaded with low scores on factor 1, which mainly reflected the effect of e-waste recycling activities. Household decorations, such as wall paint, have become a significant source of heavy metals (KurtKarakus, 2012). Yellow wall paint has been reported to be related to Cd, Pb, and Zn contamination (Chattopadhyay et al., 2003; Kurt-Karakus, 2012; Rasmussen et al., 2001; Tong and Lam, 2000). Interior paint and building materials have been reported to be significant sources of Zn, Cu, and Cr, which were derived from a common mixed origin of paints, metal objects, and soils in the study of Lin et al. (2015). Therefore, penta-BDEs, Cu, Cr, and Zn are more likely derived from household products instead of e-waste recycling activities. Apart from direct emission from indoor devices, airborne particles are also a potential source of indoor dust after deposition (Wan et al., 2016). Since the air is also largely affected by the indoor environment, contaminants released from the air should be considered to be an indirect contamination source of indoor dust by indoor devices. Correlation analysis of all organic and inorganic pollutants was performed to elucidate the source of contaminants in the different areas (Table S4 in Supplementary material). In the e-waste recycling area, significant correlations were found between the levels of Cd, Pb, most of the PCBs and PBDEs, DBDPE, and DPs (t-test, p ＜ 0.05), which confirmed that e-waste recycling activities are the source of these contaminants. However, Cu, Cr, and Zn did not show any significant correlations with Cd, Pb, and OCs. In contrast, levels of Cd and Pb were

3.4. Daily intakes of contaminants through indoor dust exposure The mean, 5th and 95th estimated ingestion values of all contaminants are presented in Table 2. The daily intake of contaminants for adults and toddlers via dust ingestion was calculated as described previously (He et al., 2015). The daily intake of contaminants was ordered as follows in all studied areas: PBDEs ＞ DBDPE ＞ DPs ≈ PCBs. The estimated daily intakes (EDIs) of PCBs, PBDEs, DBDPE, and DPs for adults in the e-waste recycling area were approximately 5.7– 18.6 and 4.1–85.5 times higher than those from the rural and urban areas, respectively. In the e-waste recycling area, the EDIs of PCBs, PBDEs, DBDPE, and DPs ranged from 2.91–163, 40.9–1470, 3.13–169 and 2.06–134 ng/kg bw/day for toddlers and 0.25–8.93, 3.58–80.3, 0.27–9.27 and 0.18–7.36 ng/kg bw/day for adults, respectively. The highest EDI value of BDE 209 reached 1140 ng/kg bw/day (95 percentile value, high ingestion for toddlers), which was 16% of the oral reference dose of deca-BDE (0.007 mg/kg bw/ day) (US EPA IRIS, 2013), indicating a notable exposure risk for toddlers in the e-waste recycling area. The EDIs of heavy metals ranked in the order of Pb ≈ Cu > Zn > Cr > Cd. The highest EDIs (95 percentile value, average to high ingestion) of five heavy metals (Cd, Pb, Cu, Cr and Zn) were 378–1510, 15,800– 113

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63,300, 5690–22,800, 1570–6300, and 2310–9250 ng/kg bw/day for toddlers and 33.1–82.7, 1390– 3470, 499–1250, 138–345 and 203– 507 ng/kg bw/day for adults, respectively, in the e-waste recycling area. The highest EDIs of these metals (Cd, Pb, Cu, Cr, and Zn) in the urban and rural areas were 18.6–175, 1460–11,300, 1490–16,800, 231–1620, and 721–9910 ng/kg bw/day for toddlers and 1.63–9.60, 128–621, 131–918, 20.2–88.9, and 63.2–543 ng/kg bw/day for adults, respectively. The EDI of Cd in the e-waste recycling area was 11.8 and 19.8 times higher than those from rural and urban areas. The EDI of Pb for toddlers ranged from 775 to 63,300 ng/kg bw/day in our studied areas, which were 18 times higher than the Pb reference dose (3500 ng/ kg bw/day) (Kurt-Karakus, 2012), indicating significant risks of Pb for toddlers in all studied areas. The EDIs for Cu, Cr, and Zn in the present study were under the criteria listed in the study of Kurt-Karakus (2012) (40,000, 3000, and 300,000 ng/kg bw/day). The EDI of Cd in the high ingestion rate of the 95 percentile for toddlers (1510 ng/kg bw/day) in the e-waste recycling area exceeded the reference dose (1000 ng/kg bw/day) (Kurt-Karakus, 2012), implying the potential risk of Cd for toddlers in the e-waste recycling area. Thus, Pb was the most notable pollutant, posing significant risk in the e-waste recycling area, which warrants more attention. There were several uncertainties and limitations in the EDI assessment of the current study. First, the sample sizes were not sufficient enough to represent spatial variances of the studied areas. In addition, gender differences in body weight were not taken into account, which may lead to slight differences in the exposure period. Furthermore, the absorption efficiency was assumed to be 100%, which overestimates the risk. However, even with these uncertainties, an overall evaluation of the health risk associated with contaminant exposure in different areas in South China was obtained. 4. Conclusion Indoor dust samples were collected to investigate the levels and profiles of several organic pollutants and heavy metals in e-waste recycling, rural, and urban areas in South China. The levels of all contaminants, except Zn, in dust samples from the e-waste recycling area were significantly higher than those from the other sampling areas. BDE 209 and DBDPE were the dominant OCs, and Pb was the major heavy metal in the present study. PCA analysis revealed that Cd, Pb, and most of the OCs were derived from e-waste recycling activities, while Cu, Cr, Zn, and BDEs 47, 99, and 100 were likely derived from household products in the rural and urban areas. The highest human exposure to BDE 209 and Pb was comparable with or higher than the reference doses for residents in the e-waste recycling area, which should be given more attention. Acknowledgements Funding: this study was financially supported by the National Natural Science Foundation of China (No. 21307037, 41230639, and U1401233) and the Basic Research Foundation of National Commonwealth Research Institute (No. PM-zx703-201602-057). Appendix A. Supplementary material Supplementary data associated with this article can be found in the online version at doi:10.1016/j.ecoenv.2017.02.041. References Ali, N., Dirtu, A.C., Van den Eede, N., Goosey, E., Harrad, S., Neels, H., 't Mannetje, A., Coakley, J., Douwes, J., Covaci, A., 2012. Occurrence of alternative flame retardants in indoor dust from New Zealand: Indoor sources and human exposure assessment. Chemosphere 88, 1276–1282. Allen, J.G., McClean, M.D., Stapleton, H.M., Webstert, T.F., 2008. Linking PBDEs in house dust to consumer products using X-ray fluorescence. Environ. Sci. Technol. 42,

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