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Effect of E-waste Recycling on Urinary Metabolites of Organophosphate Flame Retardants and Plasticizers and Their Association with Oxidative Stress Shaoyou Lu, Yanxi Li, Tao Zhang, Dan Cai, Jujun Ruan, Mingzhi Huang, Lei Wang, JianQing Zhang, and Rong-Liang Qiu Environ. Sci. Technol., Just Accepted Manuscript • DOI: 10.1021/acs.est.6b05462 • Publication Date (Web): 17 Jan 2017 Downloaded from http://pubs.acs.org on January 18, 2017

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Environmental Science & Technology

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Effect of E-waste Recycling on Urinary Metabolites of Organophosphate

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Flame Retardants and Plasticizers and Their Association with Oxidative Stress

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Shao-you Lu1,2,3#, Yan-xi Li1#, Tao Zhang1,3*, Dan Cai1, Ju-jun Ruan1, Ming-zhi Huang4, Lei

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Wang5, Jian-qing Zhang2, Rong-liang Qiu1

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1

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Laboratory of Environmental Pollution Control and Remediation Technology (Sun Yat-Sen University),

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Guangzhou 510275, China

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Shenzhen Center for Disease Control and Prevention, Shenzhen 518055, PR China

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Guangzhou Key Laboratory of Environmental Exposure and Health, School of Environment, Jinan University,

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Guangzhou 510632, China

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4

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simulation, Sun Yat-sen University, Guangzhou 510275, PR China

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School of Environmental Science and Engineering, Sun Yat-Sen University; Guangdong Provincial Key

School of Geograghy and Planning, Guangdong Provincial Key Laboratory of Urbanization and Geo-

College of Environmental Science and Engineering, Nankai University, Tianjin 300350, PR China

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#These authors contributed equally to this work

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*Corresponding Author:

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Tao Zhang School of Environmental Science and Engineering, Sun Yat-Sen University 135 Xingang West Street, Guangzhou, 510275, China Tel: 86-20-84113454 Fax: 86-20-84113454 Email: [email protected]

Submission to: Environmental Science and Technology

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ACS Paragon Plus Environment


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Abstract

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In this study, three chlorinated (Cl–mOPs) and five nonchlorinated (NCl–mOPs)

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organophosphate metabolites were determined in urine samples collected from participants living

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in electronic waste (e-waste) dismantling area (n = 175) and two reference areas (rural: n = 29;

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urban: n = 17) in southern China. Bis(2-chloroethyl) phosphate [BCEP, geometric mean (GM):

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0.72 ng/mL] was the most abundant Cl–mOP, and diphenyl phosphate (DPHP, 0.55 ng/mL) was

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the most abundant NCl–mOP. The GM concentrations of mOPs in the e-waste dismantling sites

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were higher than those in the rural control site. These differences were significant for BCEP (p
97% purity) was

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purchased from Sigma-Aldrich (St. Louis, MO, USA)15. N5-8-OHdG (98% purity) was purchased

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from Cambridge Isotope Laboratories (Andover, MA, USA). Methanol was high-performance

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liquid chromatography (HPLC)-grade and was obtained from Merck (Darmstadt, Germany).

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Deionized water was used in all experiments through a Millipore system (Billerica, MA, USA).

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Formic acid, ammonium acetate, and ammonia were purchased from Fisher Scientific (Houston,

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TX, USA). Solid-phase extraction (SPE) cartridges (CNW P-WAX, 60 mg/3 mL) for mOPs

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analysis was obtained from Anpel (Shanghai, China).

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Study Areas and Sample Collection. The e-waste dismantling areas involved in this

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study are located in Longtang Town, Qingyuan City (Figure S1). Detailed information on the

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sampling sites has been previously provided.33 In this study, two villages in Longtang Town were

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selected based on the different scale of e-waste dismantling workshops. Village #1 has a large

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number of e-waste workshops (> 50% of families have e-waste workshops) mainly involved in

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equipment dismantling and plastic sorting, whereas village #2 has similar types of workshops but

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less dense (approximately 20% of families). The distance between village #1 and #2 is

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approximately 0.5 km. In addition, a village located 80 km northwest of Longtang Town, having

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no e-waste dismantling operation, was selected as a rural reference site (Figure S1). The two e-

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waste dismantling villages and the rural reference village mentioned above are all located in

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Qingyuan City. Guangzhou, located 60 km southeast of Longtang Town, is the capital city of

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Guangdong Province. It does not have any e-waste dismantling operation and thus was chosen as

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the urban reference site (Figure S1).

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Urine sample collection was carried out in July 2014. First morning voids were collected

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from residents living in village #1 (total: n = 98; males: n = 56; age range: 3–86 yrs) and #2 (total:

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n = 77; males: n = 40; age range: 0.4–87 yrs) located in e-waste dismantling area. First morning

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voids were also collected from study participants in the rural (total: n = 29; males: n = 16; age

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range: 3–78 yrs) and urban (total: n = 17; males: n = 9; age range: 18–58 yrs) reference areas.

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Sample collection method was approved by the ethics committee of Sun Yat-sen University,

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China. All the participants and guardians of the children consented to participate. Before sample

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collection, each participant was required to complete a questionnaire, which covered personal

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information on sex, age, and place of residence. Detailed information is shown in Table S2. All

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participants were healthy and without any infectious disease. No female participant was on their

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menstrual period during urine sample collection. Local residents were chosen in the e-waste

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dismantling and rural reference sites; participants living in the urban reference site were required

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to have resided in Guangzhou for more than three yrs. Approximately 50 mL of urine sample was

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collected in a polypropylene tube and stored at −20 °C until chemical analysis.

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Sample Preparation. Urine samples were prepared for mOPs analysis as follows. Briefly,

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2 mL of urine sample was transferred to a glass tube and spiked with 10 µL of internal standard

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solution (0.25 ng/µL). The pH value of each sample was adjusted to 3.0 using 12 µL formic acid.

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Then, the urine sample was sequentially loaded onto a CNW P-WAX SPE cartridge conditioning

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using 2.0 mL of methanol (containing 5% ammonia) and 3.0 mL of 0.6% formic acid. Then, after

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sample loading, the cartridge was rinsed with 2.0 mL of 30% methanol to remove any potential

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interfering matrix components, and the mOPs were eluted with 2.0 mL of methanol (containing

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5% ammonia). The eluted solution was concentrated to 200 µL under nitrogen gas and filtered

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with a 0.22 µm nylon filter for instrumental analysis.

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Instrumental Analysis. Concentrations of mOPs in urine samples were measured using a

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20A HPLC system (Shimadzu, Japan) coupled with a Q-Trap 5500 mass spectrometer (Applied

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Biosystems, Foster City, CA, USA). Each analyte was quantified with its own deuterated internal

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standard (Table S1). All analytes were separated on an XTerra-C18 column (5 µm, 4.6 mm × 250

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mm, Waters, USA). Water containing 10 mM ammonium acetate and methanol were used as

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mobile phases. The gradient elution program was set as follows: 0–5 min, 55% methanol; 5–18

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min, 55%–68% methanol; 18–20 min, 68%–100% methanol; 20–25 min, 100% methanol; 25–27

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min, 100%–55% methanol; 27–30 min, 55% methanol. The flow rate was set at 0.6 mL/min, and

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the column temperature was maintained at 40 °C. A 10 µL of extract was injected for each

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sample.

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Electrospray ionization was operated in negative mode. The multiple reaction monitoring

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mode was used for the quantification of all mOPs with a dwell time of 50 ms. The ionization

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voltage was −4500 V, and the source temperature was 450 °C. Other optimized mass

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spectrometric parameters, including precursor ion, product ion, declustering potential, entrance

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potential, collision energies, and collision cell exit potential for each compound, as well as the

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corresponding internal standard, are listed in Table S1. An example chromatogram of mOPs in

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human urine is shown in Figure S2. No measures of specific gravity and creatinine were

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available for analyzed urine samples.

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For the 8-OHdG analysis, urine samples were prepared according to a previously

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described procedure.29 Briefly, 0.1 mL of urine was diluted five-fold with Milli-Q water, 20 ng of

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labeled internal standard (15N5–8-OHdG) was added, and the sample was analyzed through

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HPLC−MS/MS.

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Quality Assurance and Quality Control. Calibration curves were obtained using

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standard solutions of the target analytes over a concentration range of 0.01–100.0 µg/L. The

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calibration curves for all the individual mOPs exhibited excellent linearity with regression

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coefficients (r2) above 0.99. Mixed internal standard solution with moderate levels was used to

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check for the stability of detector response during instrumental analysis. Relative standard

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deviation was confirmed to be less than 10%. The limits of quantification, defined as ten times

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the signal-to-noise (S/N) ratio, ranged from 0.010–0.10 ng/mL. Under the chromatographic

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conditions described above, DoCP and DpCP were metabolites of the same OP (i.e., tricresyl

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phosphate) and could not be completely separated from each other; therefore, both chemicals

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were referred to as DoCP&DpCP.

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Eight corresponding internal standards were spiked into samples prior to preparation

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(Table S1). We quantified mOPs in studied samples through isotope dilution. Matrix-spike

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recoveries of individual mOPs through the analytical procedure were determined by spiking eight

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mOPs into randomly selected urine samples. Recoveries of mOPs were calculated by subtracting

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the background levels from the spike levels. Mean recoveries of mOPs spiked into urine samples

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ranged from 75 ± 9% (DBP) to 127 ± 20% (BCEP) when spiking level was at 0.25 ng/mL in

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sample (n = 4) and ranged from 76 ± 5% (DBP) to 97 ± 12% (BCIPP) when spiking level was at

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2.5 ng/mL (n = 4). The recoveries of mOPs in Milli-Q water blank spikes (n = 8, 2.5 ng/mL in

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water) ranged from 91 ± 13% (BDCIPP) to 121 ± 18% (BCIPP). Procedural blanks and solvent

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blanks were analyzed in each batch of ten urine samples to check for potential contamination in

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the laboratory, and all blanks were free of detectable concentrations of the target mOPs analyzed.

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Statistical Analysis. The sum concentration of all Cl–mOPs and NCl–mOPs was denoted

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as ΣCl–mOPs and ΣNCl–mOPs. In the present study, the concentrations of mOPs and 8-OHdG in

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urine samples were not normally distributed (Kolmogorov-Smirnov test). However, the dataset

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became normally distributed after log transformation. Therefore, Pearson correlation coefficients

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were used to test the associations between variables. One-way ANOVA was used to investigate

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the differences between groups when the data were distributed normally; otherwise, Mann–

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Whitney U test was used. The statistical significance level was set as p < 0.05.

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Results and Discussion

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Table 1 shows concentrations (GM, median, mean, and range) of mOPs in human urine samples collected from e-waste recycling sites and two reference sites in southern China.

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Urinary OP Metabolite Concentrations. To our knowledge, the present study is the first

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to report on urinary levels of mOPs in China. Among participants (n = 221), NCl–mOPs (i.e.,

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DoCP&DpCP, 90%; BBOEP, 93%; DBP, 99%; DPHP, 100%) had high detection frequencies in

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urine at greater than 90% (Table 1), whereas relatively low detection frequencies (50%–80%)

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were observed for Cl–mOPs (i.e., BCIPP, 56%; BCEP, 71%; BDCIPP, 76%). Low detection

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frequencies of Cl–mOPs might be partly due to high LOQs obtained for these chemicals (0.05–

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0.10 ng/mL for Cl–mOPs; 0.01–0.06 ng/mL for NCl–mOPs). Among analyzed Cl–mOPs, highest

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GM concentration in all participants was observed with BCEP (0.72 ng/mL), followed by BCIPP

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(0.094 ng/mL) and BDCIPP (0.091 ng/mL); DPHP (0.55 ng/mL) exhibited highest GM level

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among all NCl–mOPs, followed by DBP (0.29 ng/mL), BBOEP (0.065 ng/mL), and

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DoCP&DpCP (0.012 ng/mL; Table 1). Human exposure to OPs are thus widespread in e-waste

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dismantling areas and rural and urban reference areas in southern China.

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In e-waste dismantling areas, urinary concentration of ΣCl–mOPs varied and ranged from

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< LOQ to 58 ng/mL; GM value (1.7 ng/mL) was significantly higher (Mann–Whitney U test, p
18 to 60 yrs old, while donors living in e-waste sites aged from 0.4 to 87 yrs old (Table

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S2). We therefore compared urinary levels of mOPs for 18-60 age group between e-waste sites

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and urban area; similarly, 18-60 age group in e-waste sites had significant higher urinary

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concentrations of BCEP (p < 0.05; 0.76 vs. 0.43 ng/mL), BCIPP (p < 0.01; 0.089 vs. 0.028

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ng/mL), and BDCIPP (p < 0.01; 0.075 vs. 0.019 ng/mL) than those in participants from urban

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area (Table S3). Although limited sample size possibly contributed to bias of urinary mOP

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concentrations in reference areas, these comparisons suggest that participants living in e-waste

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sites had high possibility of exposure to Cl–OPs. Cl–OPs are mostly used as FRs and are

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therefore typically added to widely used materials in e-products.1–3 For example, TCEP (parent

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compound of BCEP) and TDCIPP (parent compound of BDCIPP) are used as FRs in plastic;

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TCEP, TCIPP (parent compound of BCIPP), and TDCIPP are used in polyurethane foam.2,3 Thus,

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primitive e-waste recycling activities can result in emission of Cl–OPs into environment.10,23 He

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et al. observed that house dust from e-waste dismantling area contained much higher median

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levels of TCIPP (4.77 µg/g) and TDCIPP (0.41 µg/g) than those from rural (TCIPP: 1.22 µg/g;

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TDCIPP: 0.15 µg/g) and urban (TCIPP: 0.75 µg/g; TDCIPP: 0.13 µg/g) reference areas.10

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Furthermore, in home-produced eggs, median levels of TCEP and TCIPP were higher in three e-

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waste dismantling villages (TCEP: 0.67–1.08 µg/g, TCIPP: 0.33–0.56 µg/g) than in control

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village (TCEP: 0.65 µg/g, TCIPP: 0.17 µg/g).23 As observed in present study, in e-waste sites,

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elevated urinary concentrations of ΣCl–mOPs are consistent with reported environmental

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pollution of Cl–OPs in e-waste sites, implying human exposure to OPs. Meanwhile, individual

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Cl–mOP concentrations were all lower in urban area than in rural reference area (Mann–Whitney

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U test, p < 0.05 for BCIPP and BDCIPP; Table 1 and Table S3) when the entire data set from all

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age groups (or 18-60 age group) was collectively analyzed. TCIPP and TDCIPP are commonly

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used in similar products (e.g., polymers, resins, latexes, and foams). This finding was unexpected

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and inconsistent with prevailing perception that urban people are more frequently in contact with

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Cl–OP-containing products than rural people. Many OPs (e.g., TCEP, TNBP and TPHP) have

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high vapor pressures and solubility in water,3 thus OPs release from a point source may exhibit

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more extensive environmental transport to adjacent environment. In this study, however, air

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samples were not collected, and concentrations of Cl–OPs were not measured, therefore, further

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research is needed to explore origins of human exposure to Cl–OPs in rural areas in China.

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Urinary concentration of ΣNCl–mOPs was within 0.32–8.4 ng/mL in e-waste area.

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Urinary levels of ΣNCl–mOPs (GM: 1.5 ng/mL) and DPHP (0.57 ng/mL) were significantly

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higher in participants from e-waste area (Mann–Whitney U test, p < 0.01) than those from rural

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reference area (ΣNCl–mOPs: 0.60 ng/mL, DPHP: 0.37 ng/mL). TPHP (parent compound of

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DPHP) and TCP (parent compound of DoCP&DpCP) are widely used as plasticizers in e-

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products, and TNBP (parent compound of DBP) is used as plasticizer in plastic.1–3 Thus, NCl–

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OPs may also be released from uncontrolled e-waste recycling activities because e-product (e.g.,

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air conditioner, television, fridge, washing machine, and computer) contain 20%–50% plastic by

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weight.34 Bi et al. analyzed chemical constituents of air particle samples from workshops engaged

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in recycling printed circuit board waste and discovered that major organic compounds were OPs

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consisting mainly of TPHP.7 In addition, e-waste recycling area located in Longtang Town had

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higher indoor dust levels of NCl–OPs [i.e., TPHP, ethylhexyl diphenyl phosphate (EHDPP),

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TNBP, and TCP] than in rural reference area;10 in present study, consistency was noted with

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geographic difference in NCl–OP concentrations in indoor dust samples and NCl–mOP

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concentrations in urine between e-waste recycling and rural reference sites. Thus, e-waste

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dismantling activities may contribute to human exposure to NCl–OPs. However, in the present

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study, significant differences (Mann–Whitney U test, p = 0.100–0.830) were not observed

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between e-waste and urban sites in urinary concentrations of individual NCl–mOPs and ΣNCl–

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mOPs, when the entire data set from all age groups (or 18-60 age group) was collectively

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analyzed (Table 1 and Table S3). Urinary levels of mOPs were not previously compared between

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e-waste and urban sites, whereas in outdoor air particles, comparable NCl–OP levels were

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previously observed between e-waste dismantling area located in Qingyuan (126 ng/m3) and

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urban reference area (i.e., Guangzhou, 132 ng/m3).5 These findings indicate that NCl–OPs are not

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only contained in e-products but are also applied in various commercial and consumer products.

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For example, TPHP and EHDPP are commonly used in hydraulic fluid and PVC, tris(2-

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butoxyethyl) phosphate (TBOEP) is widely used in daily plastic products, floor polishes, rubber,

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and lacquers.3 People living in urban areas are more frequently in contact with NCl–OP-

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containing products than those living in rural areas; this condition increases urinary levels of

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NCl–mOPs in urban dwellers. This observation is supported by our present study, in which higher

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concentration of ΣNCl–mOPs was calculated in urban area (GM: 0.96 ng/mL) than in rural

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reference area (GM: 0.60 ng/mL; Table 1).

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Interestingly, although urinary levels of ΣCl-mOPs and ΣNCl-mOPs observed in e-waste

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dismantling area were significantly (Mann-Whitney U test, p < 0.05) higher than those observed

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in rural control area (Table 1), comparable urinary levels of ΣCl-mOPs (p = 0.952; 1.6 vs. 1.7

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ng/mL) and ΣNCl-mOPs (p = 0.281; 1.6 vs. 1.4 ng/mL) were obtained between village #1 (> 50%

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of families have e-waste workshops) and #2 (approximately 20% of families) (Table 1). Thus, the

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scale of e-waste recycling activities seem to have no associations with human OPs exposure;

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however, we need to emphasize that village #1 and #2 were in a distance of less than 1.0 km,

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environmental transport of OPs generated from e-waste dismantling may be a reason for the

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comparable urinary mOPs levels obtained between both of villages. As we mentioned before, OPs

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(e.g. TCEP, TNBP, TPHP) have high vapor pressures and good water solubility.3 Therefore, e-

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waste dismantling activities in village #1 and #2 may cause environmental pollution of OPs for

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each other. Similar, no significant differences (Mann-Whitney U test, p = 0.311-0.836) on urinary

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levels of individual mOPs (except BCIPP and BDCIPP) were found between village #1 and #2.

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Nevertheless, the urinary concentrations of BCIPP and BDCIPP obtained in village #1 (GM:

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BCIPP, 0.16 ng/mL; BDCIPP, 0.15 ng/mL) were significantly (p < 0.05) higher than those

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observed in village #2 (GM: BCIPP, 0.071 ng/mL; BDCIPP, 0.074 ng/mL). The vapor pressure

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(2.6×10-9 mm Hg) and solubility in water (1.50 mg/L) of TDCIPP are several orders of magnitude

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lower than other OPs (e.g. TNBP, TCEP, TPHP),3 and these properties reduce the mobility of

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TDCIPP in the environment. This may lead to residents living in village #1 had higher urinary

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BDCIPP concentrations than people living in village #2.

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Comparison of OP Metabolite Concentrations in Urine with Previously Reported

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Concentrations. Urinary concentrations of mOPs were also reported for residents from U.S.,

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Canada, Norway, Germany, and Australia.9,31,32,35–44 In several of studies, specific gravity-

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corrected concentrations were reported;31,38,41,43,44 while urinary levels of mOPs were not

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corrected in this study. We therefore compared uncorrected urinary mOPs observed in China

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(present study) with those uncorrected mOPs levels reported in other countries (previous studies;

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Table 2). In general, BDCIPP and DPHP were the two most common mOPs analyzed in previous

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studies (Table 2). In present study, among adults living in rural and urban reference areas,

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BDCIPP and DPHP urinary levels were less than those observed in adults from other countries

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(Table 2). Similarly, adults from our reference areas also had lower or comparable urinary

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concentrations of other mOPs (i.e., BCEP, BCIPP, BBOEP, DBP, and DoCP&DpCP) than those

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reported from other countries (Table 2). These findings imply that OPs are not used in large

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quantities in household products in southern China.

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Although e-waste dismantling activities were associated with elevated urinary levels of

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mOPs in the present study (Table 1 and Table 2), concentrations of mOPs in adults living in e-

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waste sites in China were lower than or comparable to those reported in U.S., Canada, and

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Australia (Table 2). These findings were inconsistent with our speculation that urinary mOP

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levels in adults from e-waste recycling sites in China are higher than or in line with those in

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developed countries because considerable proportion of e-waste processed in China come from

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overseas. Possibly, in e-waste site, unexpectedly low levels of mOPs were caused by addition of

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OPs, which probably decreased in concentration during lifetime of treated products; therefore,

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percentage composition of OPs in e-waste may be much lower than those in new e-products.3

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Furthermore, non-occupational residents of e-waste sites are exposed to OPs mainly through food

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chain or inhalation of polluted air. However, contact with OP-containing products is considered

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important route of OP exposure for people living in unpolluted areas.45–47 Hence, in the present

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study, indirect exposure to OP-containing e-waste also possibly resulted in relatively lower or

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comparable levels of urinary mOPs in e-waste dismantling areas compared with those in

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developed countries (Table 2). Human urine and indoor dust samples have rarely been

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investigated in the same sampling area of other countries,9 lower or comparable level of TDCIPP

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and TPHP in house dust were found in e-waste sites (i.e., Qingyuan city) of China (median:

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TDCIPP, 0.41 µg/g; TPHP, 1.09 µg/g) compared with those obtained in the U.S. (GM: TDCIPP,

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1.39 µg/g; TPHP, 1.02 µg/g),9,10 thus, the geographic difference in mOPs concentrations in urine

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are coincide with that in house dust between China and the U.S.9,10

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Gender- and Age-Related Patterns of Urinary OP Metabolite Levels. We also

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examined gender-related patterns of urinary mOP concentrations in e-waste and two reference

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sites. Significant gender-related differences were not observed (Mann–Whitney U test, p > 0.05)

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for all mOPs across all sampling sites.

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Associations between age (in yrs) and log-transformed mOPs were analyzed in e-waste

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sites (Pearson’s Correlation test), whereas reference areas were excluded because of limited

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sample size (Table 1 and Figure S3). Increasing age was associated with significant decreases in

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BCEP (r = −0.208, p < 0.05), BCIPP (r = −0.235, p < 0.05), BDCIPP (r = −0.245, p < 0.01), and

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DPHP (r = −0.419, p < 0.001) concentrations. On the other hand, urinary concentrations of

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BBOEP, DBP, and DoCP&DpCP exhibited non-significant negative correlations with age (r = -

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0.039–0.079, p > 0.05) (Table 1). Similar age-related patterns were also found for each mOPs,

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when urinary mOPs concentrations were presented for different age groups (i.e., 0-6, > 6-18, >

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18-60, and > 60 yrs) (Figure S3). In previous study from Australia, urinary levels of BCIPP and

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DPHP were significantly higher in children than in adults, suggesting higher exposure to OPs of

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young children.32 In U.S., children also had higher urinary levels of BDCIPP and DPHP

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compared with their mothers, and BDCIPP levels in infants were substantially higher than those

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in adults.44,46 Possibly, significant negative correlations of urinary mOPs with age may be related

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to increased hand–mouth contact and elevated dust exposure of children;44 children showed an

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order of magnitude higher daily intake of OPs via dust ingestion than in adults.8,10 Children’s

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products that contain polyurethane foam are also commonly treated with OPs; Hoffman et al.

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observed that number of infant products owned was strongly associated with urinary BDCIPP;46

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thus, use of OP-containing children’s products may be another reason for negative associations of

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urinary mOPs with age.

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Sources Analysis of Human Exposure to OPs. Pearson’s correlation analysis was used

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to test associations between individual urinary mOPs (log-transformed) in e-waste and reference

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areas. Based on statistical results (Table 3 and Figure S4), significant and positive correlations

363

were calculated between 14 of 21 pairs of urinary mOPs in e-waste sites, and coefficients ranged

364

from 0.180 (p < 0.05 for DBP:BDCIPP) to 0.551 (p < 0.01 for BCIPP:BDCIPP). By contrast,

365

significant relationships were discovered in 6 of 21 pairs of mOPs (r values: 0.485–0.607) in

366

rural area, and no significant associations were obtained in urban reference area (Table 3). These

367

results imply that sources of human exposure to OPs are common or related to e-waste areas,

16


Page 17 of 31

368


whereas diverse sources of OPs exist in rural and urban areas.

369

As we mentioned above, OPs were widely used in e-products for decades;1–3 limited

370

studies showed that crude e-waste recycling activities release OPs into environment.7,10,23 In e-

371

waste sites, exposure to OPs by participants can be via inhalation of polluted air, dermal contact

372

with contaminated dust, or ingestion of food produced (or grown) in OP-polluted

373

environment.8,9,10,23 Thus, significant associations in e-waste areas resulted from release of OPs

374

during e-waste recycling. In addition to e-products, OPs are also used to treat many consumer

375

products, such as furniture, baby products, and construction materials, that contain polyurethane

376

foam.3 Stapleton et al. observed high prevalence of TCIPP and TDCPP in furniture foam samples,

377

which were collected from couches, chairs, mattress pads, and pillows.48 In previous study on

378

OPs in baby products, common FR detected was TDCPP; TCEP was also widely found as

379

impurity in baby products. OP emissions from OP-containing products were also identified,

380

suggesting that use of OP-treated products may affect indoor air quality and is possible route of

381

OP exposure for humans.46–48 Overall, OPs are used in wide range of commercial products,

382

suggesting that multiple sources may be responsible for OPs detected in participants in rural and

383

urban reference areas. Interestingly, BCIPP correlated well with BCEP, BDCIPP, BBOEP, and

384

DBP in both e-waste and rural reference areas. TCIPP is important OP (global production: 30,000

385

tons), representing approximately 60% of Cl–OPs and is widely used in polyurethane foam.

386

Several OPs are commonly used in some products,3,46,48 thus our results indicate that other OPs

387

(e.g., TCEP, TDCIPP, TBOEP, and TNBP) may be used in electronic and other commercial

388

products as mixtures of TCIPP.

389

Difficulty arises from identifying valid indicator for human OP exposure because OPs are

390

used in wide range of products, resulting in diverse exposure sources. All mOP compounds were

17



Page 18 of 31

391

less probable to be useful indicator of human exposure to OPs in reference areas because of weak

392

and non-significant correlations observed among mOPs. On the other hand, both DPHP and

393

BCIPP had significant positive associations with all other mOPs in e-waste sites, except that

394

BCIPP did not correlate well with DoCP&DpCP (Table 3). DPHP and BCIPP are possible

395

indicators for OP exposure in e-waste dismantling area, but they pose several disadvantages when

396

one of them was used as indicator. For example, BCIPP showed low detection rate and

397

concentration (GM concentration: 0.11 ng/mL; detection rate: 60%) (Table 1); DPHP can be

398

present in many products as parent compound and is also metabolite of variety of plasticizers,

399

lubricants, and FRs.3 Therefore, combination of BCIPP and DPHP may be more suitable indicator

400

strategy for OP exposure in e-waste dismantling areas.

401

Associations between OP Exposure and Oxidative Stress. 8-OHdG is marker for

402

oxidative damage to DNA and oxidative stress.28,29 In the present study, we evaluated correlation

403

between urinary concentrations (log-transformed) of individual mOPs and 8-OHdG by Pearson’s

404

correlation analysis for e-waste and rural reference area, respectively. These results are important

405

because they provide first-hand report, using data from human population, of associations

406

between elevated OP exposure and oxidative stress.

407

In all the participants, 8-OHdG was found be significantly correlated with BCIPP (r = 0.394,

408

p < 0.001), DBP (r = 0.230, p < 0.01), and DPHP (r = 0.338, p < 0.001). We also observed that

409

urinary 8-OHdG levels significantly increased with increasing levels of BCIPP in e-waste sites (r

410

= 0.484, p < 0.01) and rural (r = 0.610, p < 0.05) reference area (Figure 1). Furthermore, data in

411

e-waste recycling area showed significant association between urinary concentrations of 8-OHdG

412

and BCEP (r = 0.504, p < 0.01), DBP (r = 0.214, p < 0.05), and DPHP (r = 0.440, p < 0.01),

413

whereas no such associations were obtained in rural reference area (Figure 1). Both areas

18


Page 19 of 31


414

demonstrated non-significant associations between urinary 8-OHdG and BDCIPP, BBOEP, and

415

DoCP&DpCP (Figure 1). These results suggest that TCIPP exposure is correlated with oxidative

416

damage to DNA across sampling sites, and that human exposure to TCEP, TNBP, and TPHP (or

417

EHDPP) were correlated with elevated oxidative stress in e-waste dismantling sites. Notably,

418

limited sample size possibly affected statistical power of association analysis. Therefore, in rural

419

reference area (n = 29), association results between mOPs and 8-OHdG should be interpreted

420

with caution.

421

Although no previous study explored association between OP exposure and 8-OHdG in

422

humans, limited animal or in vitro studies were performed to examine OP-induced oxidative

423

stress.25–27 Chen et al. evaluated effects of TPHP (300 mg/kg body weight) and TCEP (100 mg/kg

424

body weight) on induction of oxidative stress in liver of male mice and witnessed that oral

425

administration evidently affected oxidative status.25 Similarly, TPHP (60 µg/mL in cell culture)

426

and TCEP (300 µg/mL in cell culture) also induced oxidative stress in TM3 cells.26 In study from

427

Duke University, in vitro model (i.e., PC12 cells) was used to assess developmental neurotoxicity

428

of TCIPP, TCEP, and TDCIPP; TDCIPP (50 µmol/L in cell culture) resulted in elevated oxidative

429

stress but was insufficient to compromise cell viability.27 Furthermore, few studies explored

430

underlying mechanism of OP-induced oxidative stress,25 but information on mechanism remains

431

lacking for OPs.

432

Notably, urinary levels of mOPs (GM weight concentrations: 0.012 to 0.81 ng/mL; GM

433

molar concentrations: 0.057 to 3.6 nmol/L) obtained in participants by the present study were

434

several orders of magnitude less than the effect values of OPs spiked into studied animal or

435

cell.25-27 According to previous reports,7,10,23,33,49-51 e-waste dismantling activities not only release

436

OPs but also release other toxicants into environment. Thus, high oxidative stress may also

19



Page 20 of 31

437

resulted from many other pollutants produced by e-waste recycling. In our previous studies,

438

increased urinary levels of bisphenols (BPs) and monohydroxy-polycyclic aromatic hydrocarbons

439

(OH-PAHs) were obtained from participants in same investigated e-waste site and indicated that

440

bisphenol A and PAH exposures are correlated with high oxidative stress.33,49 Ni et al. and Wen et

441

al. further reported association between exposure to polychlorinated dibenzo-p-dioxin and

442

dibenzofuran, PBDEs, and heavy metals and increased urinary 8-OHdG levels in e-waste

443

dismantling areas.50,51 Furthermore, associations of urinary concentrations between 8-OHdG and

444

mOPs [and other pollutants (i.e, BPs and OH-PAHs)] were also estimated by linear regression

445

model (Table S4), and our results showed that NCl-mOPs may the main contributor to oxidative

446

stress among these types of pollutants. However, co-exposure to more e-waste-pollutants should

447

be considered to investigate their associations with oxidative stress.

448

In summary, this study is the first to report urinary levels of mOPs in China. Participants

449

living in e-waste dismantling areas yielded significantly higher concentrations of BCEP and

450

DPHP than those in rural reference areas. These findings suggested high possibility of exposure

451

to TCEP and TPHP or EHDPP in e-waste sites. Age is possible factor influencing OP exposure

452

because of negative correlation of urinary BCEP, BCIPP, BDCIPP, and DPHP with age (p < 0.05).

453

Our findings also suggested that sources of human exposure to OPs were common in or related to

454

e-waste sites. Furthermore, correlation was observed in human exposure to TCIPP, TCEP, TNBP,

455

and TPHP (or EDHPP) and high oxidative stress in e-waste dismantling sites. This study provided

456

novel information on association between OP exposure and oxidative stress in humans.

457

Acknowledgments

458

The Natural Science Foundation of China (No. 41225014 and No. 41303094), Pear River

459

S&T Nova Program of Guangzhou, and the Fundamental Research Funds for the Central

20


Page 21 of 31


460

Universities are acknowledged for their partial research supports. The present study was also

461

supported by the Guangzhou Key Laboratory of Environmental Exposure and Health (No.

462

GZKLEEH201606). We gratefully acknowledge the donors who contributed the urine samples

463

for this study.

464

Supporting Information Available

465

Supporting information as noted in text is available free of charge via the Internet at

466

http://pubs.acs.org.

467

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26


Page 27 of 31


Table 1. Urinary Concentrations (ng/mL) of Organophosphate Metabolites in Participants Living in E-waste Dismantling and Reference Areas in China. chlorinated OP metabolites BCEP

BCIPP

BDCIPP

ΣCl-mOPs

f

BBOEP

non-chlorinated OP metabolites DoCP& DBP DPHP ΣNCl-mOPs g DpCP

e

all areas (n = 221) 71 56 76 DR a (%) GM b 0.72 c 0.094 0.091 median 1.1 0.097 0.11 mean 3.0 0.43 0.25 min < LOQ d < LOQ < LOQ max 57 23 4.5 e-waste dismantling area (total: n = 175) DR (%) 73 60 81 GM 0.81 0.11 0.11 median 1.3 0.14 0.12 mean 3.2 0.51 0.29 min < LOQ < LOQ < LOQ max 57 23 4.5 e-waste dismantling area (village #1: n = 98) DR (%) 64 72 93 GM 0.77 0.16 0.15 median 1.1 0.19 0.13 mean 3.2 0.70 0.36 min < LOQ < LOQ < LOQ max 27 23 4.5 e-waste dismantling area (village #2: n = 77) DR (%) 83 44 66 GM 1.0 0.071 0.074 median 1.3 < LOQ 0.11 mean 3.3 0.27 0.19 min < LOQ < LOQ < LOQ max 57 3.6 2.3 rural reference area (n = 29) DR (%) 69 55 76 GM 0.50 0.069 0.069 median 0.61 0.049 0.075 mean 1.8 0.15 0.15 min < LOQ < LOQ < LOQ max 15 0.77 0.75 urban reference area (n = 17) DR (%) 59 12 29 GM 0.43 0.028 0.019 median 0.67 < LOQ < LOQ mean 1.9 0.068 0.033 min < LOQ < LOQ < LOQ max 10 0.56 0.14

84 1.4 1.7 3.6 < LOQ 58

93 0.065 0.071 0.093 < LOQ 2.1

99 0.29 0.15 1.2 < LOQ 7.8

90 0.012 0.015 0.020 < LOQ 0.27

100 0.55 0.53 0.85 0.10 36

100 1.3 1.1 2.2 0.23 36

89 1.7 2.0 4.0 < LOQ 58

91 0.065 0.073 0.088 < LOQ 0.33

99 0.38 0.20 1.5 < LOQ 7.8

90 0.012 0.015 0.021 < LOQ 0.27

100 0.57 0.56 0.72 0.10 5.1

100 1.5 1.4 2.3 0.32 8.4

90 1.6 2.1 4.2 < LOQ 33

99 0.073 0.076 0.086 < LOQ 0.33

99 0.42 0.19 1.8 < LOQ 7.8

95 0.013 0.015 0.016 < LOQ 0.050

100 0.59 0.59 0.79 0.12 5.1

100 1.6 1.5 2.7 0.21 8.4

80 1.7 1.7 3.8 < LOQ 58

82 0.056 0.070 0.090 < LOQ 0.32

99 0.34 0.20 1.2 0.016 4.4

84 0.013 0.016 0.027 < LOQ 0.27

100 0.56 0.54 0.64 0.10 2.6

100 1.4 1.2 1.9 0.41 5.2

80 0.93 1.1 2.1 < LOQ 16

100 0.052 0.041 0.12 0.022 2.1

100 0.10 0.11 0.12 0.041 0.29

93 0.012 0.015 0.014 < LOQ 0.024

100 0.37 0.36 0.49 0.13 2.4

100 0.60 0.55 0.74 0.23 2.6

70 0.56 0.70 2.0 < LOQ 10

100 0.093 0.091 0.10 0.051 0.20

100 0.10 0.090 0.12 0.043 0.34

88 0.012 0.016 0.016 < LOQ 0.034

100 0.67 0.53 2.8 0.15 36

100 0.96 0.77 3.0 0.69 36

a

DR: detection rates. b GM: geometric mean values. c two effective digits has been used in this study. d < LOQ: concentrations value lower than LOQ. e n: the number of samples. f ΣCl-mOPs represented the sum urinary concentrations of all three chlorinated OP metabolites. g ΣNCl-mOPs represented the sum urinary concentrations of all four non-chlorinated OP metabolites.

626 627 628

27



Page 28 of 31

Table 2. Comparison of Urinary GM (median/mean) Organophosphate Metabolites Concentrations (ng/mL) in Adult Participants from China with Those Urinary Concentrations Reported from Other Locations around the World.

countries

population

na

sampling date

BCEP

chlorinated OP metabolites BCIPP BDCIPP

non-chlorinated OP metabolites DoCP&DpCP b DBP

DPHP

reference

China

adults (e-waste) c

121

2014

0.61 (0.98/2.6)

0.087 (0.085/0.30)

0.079 (0.11/0.18)

0.065 (0.072/0.091) 0.41 (0.20/1.6)

0.015 (0.016/0.025)

0.52 (0.53/0.62)

this study

China

adults (reference) d

39

2014

0.39 (0.54/2.0)

0.060 (0.020/0.15)

0.050 (0.057/0.11)

0.067 (0.056/0.14)

0.11 (0.11/0.13)

0.011 (0.015/0.014)

0.45 (0.36/1.7)

this study

United States

adults

13

2016 e

3.4 (1.3/3.8)

0.4 (0.3/0.9)

2.5 (2.4/3.4)

NA

NA

NA

1.5 (1.5/2.0)

(37)

United States

adults

16

2011

NC (0.63/0.76)

NC (NA/0.17)

NC (0.09/0.46)

NC (ND/ND)

NC (0.11/0.16)

NA

NC (0.44/1.10)

(42)

United States

adults

53

2012-2013

NA

NA

0.37 (NC/NC)

NA

NA

NA

1.02 (NC/NC)

(9)

United States

pregnant women

39

2012-2013

NA

NA

1.3 (1.1/NC)

NA

NA

NA

1.9 (1.6/NC)

(40)

Canada

pregnant woman

24

2010-2012

0.37 (0.46/NC)

0.41 (0.46/NC)

0.27 (0.26/NC)

0.38 (< 0.08/NC)

NA

0.64 (0.69/NC)

2.88 (2.94/NC)

(39)

Germany

14-85 yrs

19

2011 e

NA

NA

NA

NA

NA

NA

NC (1.3/NC)

(36)

Germany

11-68 yrs

30

2009

NC (< 0.10/NC)

NA

NA

NA

NA

NC (< 1.0/NC)

NC (< 0.50/NC)

(35)

Australia

not available

28

2010-2013

NA

NA

1.00 (NC/NC)

< 0.35 (NC/NC)

< 0.43 (NC/NC)

NA

24.4 (NC/NC)

(32)

Australia

not available

23

2010-2013

NA

NA

0.66 (NC/NC)

ND (NC/NC)

< 0.43 (NC/NC)

NA

63.4 (NC/NC)

(32)

United States j

adults

40

2015

NA

ND h (ND/NC i)

2.321 (2.061/NA)

NA

NA

NA

1.137 (1.160/NA)

(41)

United States j

adults

9

2011 e

NA

NA

0.148 (0.083/NC)

NA

NA

NA

1.074 (0.803/NC)

(43)

United States j

adult females

22

2013-2015

NA

ND (NC/NC)

2.4 (NC/NC)

NA

NA

NA

1.9 (NC/NC)

(45)

United States j

adult males

45

2002-2007

NA

NA

0.13 (0.12/NC)

NA

NA

NA

0.31 (0.27/NC)

(38)

Norway j

adult females

224

2012

NA

NA

NC (0.08/0.25)

NC (0.11/0.12)

NC (0.08/0.08)

NA

NC (0.63/1.44)

(31)

a

g

f

BBOEP

the number of collected samples. b “DoCP&DpCP” represented the sum concentrations of DoCP and DpCP. c “adults (e-waste)” represented all adults from e-waste dismantling area. d “adults (reference)” represented all adults from reference areas. e published date was shown for these references due to sampling date is not available. f these values represented GM (median/mean) concentration of individual OPFR metabolite reported in other studies. g NA = not analyzed (i.e., this chemical was not analyzed in this reference). h ND = not detected (i.e., this chemical was not detected in all samples). i NC = not calculated (i.e., this chemical was analyzed, but this value was not calculated in this reference). j specific gravity-corrected concentrations of mOPs in urine were reported in these studies, we therefore excluded these studies when comparing this study with other studies.

629 630

28


Page 29 of 31


Table 3. Pearson’s Correlation Coefficients Among Individual Organophosphate Metabolites in Urine Samples Collected in Southern China, as Stratified by Sampling Locations. a

BCEP BCIPP BDCIPP BBOEP DBP O&P c DPHP age a

BCEP BCIPP BDCIPP e-waste dismantling area 1 0.378** 1 0.311** 0.551** 1 0.185* 0.434** 0.110 0.118 0.412** 0.180* 0.034 0.157 0.159 0.468** 0.529** 0.290** -0.208* -0.235* -0.245**

BBOEP

DBP

1 0.156 -0.033 0.284** -0.039

1 0.483** 0.417** -0.079

O&P

1 0.216** 0.059

age

BCEP BCIPP BDCIPP rural reference area d 1 0.607* 1 0.313 1 0.553* 0.357 0.027 0.556* 0.485* 0.647** 0.512* 0.009 -0.109 -0.190 0.006 0.146 0.026

BBOEP

DBP

1 0.220 -0.224 -0.030

1 -0.202 0.364

O&P

1 0.178

BCEP BCIPP BDCIPP urban reference area d b NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA

BBOEP

DBP

O&P

1 0.431 0.149 0.062

1 0.124 0.438

1 -0.103

-0.419**

* p < 0.05, ** p < 0.01; concentration values less than LOQ were excluded from these analysis; log-transformed concentrations were used for analysis. b NA = not available, these relationships were not analyzed due to low detection rates obtained for BCIPP (12%) and BDCIPP (29%) in urban reference area. c O&P = DoCP&DpCP. d The associations between urinary mOPs levels and age were not analyzed in reference areas due to limited sample size.

631 632

29



Page 30 of 31

In e-waste dismantling area

r = 0.504 p < 0.01

r = 0.484 p < 0.01

(c) DBP

(d) DPHP

r = 0.214 p < 0.05

r = 0.440 p < 0.01

In rural reference area (e) BCEP

(f) BCIPP

r = -0.132 p > 0.05

r = 0.610 p < 0.05

(h) DPHP

(g) DBP

r = 0.080 p > 0.05

r = 0.300 p > 0.05

633 634

Figure 1. Pearson correlations of urinary OP metabolites concentrations with urinary 8-OHdG in participants

635

living in e-waste dismantling [plot (a-d)] and rural reference [plot (e-h)] areas. Concentration values less than

636

LOQ were excluded from these association analyses, and we used log-transformed urinary concentrations for

637

these analyses. The blue dotted lines represented significant correlations, grey dotted lines represented non-

638

significant associations. Relationship between urinary BDCIPP, BBOEP, and DoCP&DpCP levels and 8-OHdG

639

were not significant (p > 0.05) in both of sampling areas, and thus were not shown.

30


Page 31 of 31


TOC Art

640 641 TNBP P TCIP CIP P TD P TCEP DP TB EH EP TP HP TCP

642

Human Exposure ？ Oxidative Stress ？

E-waste Recycling Area

643

31


Effect of E-waste Recycling on Urinary Metabolites ... - ACS Publications

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