Letter Cite This: Environ. Sci. Technol. Lett. XXXX, XXX, XXX−XXX
pubs.acs.org/journal/estlcu
Atmospheric Concentrations of PCB-11 Near the Great Lakes Have Not Decreased Since 2004 Ronald A. Hites* School of Public and Environmental Affairs, Indiana University, Bloomington, Indiana 47405, United States S Supporting Information *
ABSTRACT: 3,3′-Dichlorobiphenyl (PCB-11) is thought to be a byproduct of the production of yellow pigments, and thus, it has sources to the environment that differ both in type and magnitude compared to the PCBs that made up the, now banned, Aroclor commercial products. To assess these differences, the temporal trends of atmospheric concentrations of PCB-11 relative to those of 31 specific Aroclor-related congeners and relative to those of total Aroclor-PCBs at six sites near the North American Great Lakes were investigated. About 1800 atmospheric samples were collected over the period of 2004−2015 (inclusive). A multiple linear regression approach was used to isolate the variations in the atmospheric concentrations due to the human population near the sampling sites, seasonal effects, and long-term temporal changes. The atmospheric concentrations of the Aroclor-PCBs are decreasing with halving times of about 12 years, but the atmospheric concentrations of PCB-11 have not changed significantly over this time period. These results suggest that PCB-11 is still leaking into the environment, while at the same time sources of Aroclor-PCBs are coming under control. This effect is particularly notable at the most remote site on Lake Superior, where PCB-11 levels are, on average, 11% of those of total Aroclor-PCBs; this is a not insignificant abundance of a single PCB congener.
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INTRODUCTION Hornbuckle et al. have found that 3,3′-dichlorobiphenyl (PCB11) has a source to the environment that is different and distinct from that of the polychlorinated biphenyl (PCB) congeners found in the commercially produced Aroclor-PCB mixtures.1 PCB-11 is thought to be an impurity in the production of yellow pigments, and hence, it enters the environment whenever these pigments are used or handled.2 PCB-11 is also known to bioaccumulate in humans.3,4 Hornbuckle et al. initially focused on air collected in Chicago,1 but Basu et al. soon reported that PCB-11 is widely distributed in atmospheric samples collected at five locations around the Great Lakes and that its atmospheric levels are much higher in the summer than in the winter.5 Other work has shown that PCB-11 is relatively abundant in water and sediment from the Delaware River6 and from the New York/New Jersey7 and Portland Harbors8 and in Antarctic and Mediterranean bivalves.9 Environmental levels of PCB-11 have recently been reviewed by Vorkamp.10 Aroclor-PCB mixtures were primarily used as dielectric fluids, and they entered the environment when the devices in which they were used were filled, leaked, or wasted. In the United States, all uses of PCBs (as Aroclor mixtures) were restricted in the late 1970s, while yellow pigments containing PCB-11 are still in use. Thus, the concentrations of Aroclor-PCBs in the environment should have been decreasing over the last few decades, while those of PCB-11 may not have changed significantly. It was resolved to test this hypothesis using PCB data from the U.S. Environmental Protection Agency’s Integrated Atmospheric Deposition Network (IADN), which © XXXX American Chemical Society
has been measuring the atmospheric concentrations of AroclorPCBs in the Great Lakes region since 1990 and those of PCB11 since 2004. IADN collects air samples at six locations around the Great Lakes.11 In order of decreasing population they are Chicago, Illinois; Cleveland, Ohio; Sturgeon Point, New York; Sleeping Bear Dunes, Michigan; Point Petre, Ontario; and Eagle Harbor, Michigan. Air is collected once every 12 days, except at Point Petre, where the collection frequency is once every 36 days. The samples are returned to the laboratory at Indiana University where they are analyzed for, among many other compounds, PCBs. The resulting concentration data are then analyzed by a multiple regression approach to isolate variations due to the human population near the sampling site and seasonal effects, on the one hand, from variations due to longterm temporal trends, on the other. It was suspected that there would be differences between the Aroclor-PCB and the PCB-11 temporal trends.
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MATERIALS AND METHODS Sampling. Details on the six site locations are given elsewhere; see https://iadnviz.iu.edu/#/about/. Details of the sample collection, extraction, and analysis procedures have been previously published,11 and only a brief description is presented here. A modified Anderson high-volume air sampler (General Received: January 11, 2018 Revised: February 15, 2018 Accepted: February 15, 2018
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DOI: 10.1021/acs.estlett.8b00019 Environ. Sci. Technol. Lett. XXXX, XXX, XXX−XXX
Letter
Environmental Science & Technology Letters
Table 1. Results for Multiple Linear Regression Fit of Eq 1 to Atmospheric Concentrations (in pg/m3) of Various PCBs Measured at Six Sites around the North American Great Lakesa N % detected r2 const (a0) sin(zt) (a1) cos(zt) (a2) max date pop (a3) date (a4 × 104) t1/2 (years)
Average PCBs
Aroclor-PCB
PCB-11
PCB-100
PCB-11/ΣPCB
PCB-100/ΣPCB
1745 95 77.1 4.59 ± 0.55 −0.328 ± 0.024 −0.778 ± 0.024 Jul 23 ± 1.7 0.0978 ± 0.0014 −1.63 ± 0.14 12.6 ± 1.2
1830 100 79.8 8.86 ± 0.48 −0.304 ± 0.021 −0.691 ± 0.021 Jul 23 ± 1.6 0.0948 ± 0.0013 −1.63 ± 0.12 11.6 ± 0.9
1691 92 51.4 P = 0.404 −0.330 ± 0.032 −1.085 ± 0.033 Jul 17 ± 1.6 0.0492 ± 0.0019 P = 0.931 not sig
1183 65 59.5 −4.28 ± 0.69 −0.186 ± 0.029 −0.537 ± 0.030 Jul 20 ± 3.0 0.0661 ± 0.0018 P = 0.130 not sig
1691 92 43 −7.56 ± 0.61 P = 0.118 −0.421 ± 0.027 Jul 7 ± 3.6 −0.0471 ± 0.0016 1.45 ± 0.15 −13.1 ± 1.3
1183 65 31.8 −13.5 ± 0.6 0.128 ± 0.026 0.167 ± 0.026 Feb 10 ± 7.1 −0.0277 ± 0.0018 1.94 ± 0.15 −9.8 ± 0.8
a
The errors are all standard errors from the regression. Negative halving times are actually doubling times. When the regression parameter is not significant, the probability level is given (P =).
sum of all of the measured GC peaks before the application of any selection protocol.
Metal Works, model GS2310) was used to collect air samples for 24 h at a flow rate giving a total sample volume of about 820 m3. The vapor phase organics were collected on Amberlite XAD-2 resin (Supelco, 20−60 mesh) held in a stainless steel cartridge. Virtually all of the PCBs are present in the vapor phase;11 thus, only this phase is discussed here. The samples presented here cover the years 2004−2015 (inclusive). Extraction and Analysis. After sampling, XAD was extracted for 24 h with 1:1 (v:v) acetone in hexane. Prior to extraction, surrogate standards (PCB-14, PCB-65, and PCB166) were spiked into the sample. The extract was reduced in volume by rotary evaporation, and the solvent was exchanged to hexane. This solution was fractionated on a column containing 3.5% (w/w) water-deactivated silica gel. The column was eluted with 25 mL of hexane (fraction 1) and 25 mL of 1:1 (v:v) hexane in dichloromethane (fraction 2). PCBs were in fraction 1. After nitrogen blow down, the samples were spiked with internal standards (PCB-30 and PCB-204), and the PCBs were analyzed by gas chromatography (GC) on HewlettPackard 5890 and Agilent 6890 instruments equipped with 63Ni electron capture detectors and with DB-5 and DB-1701 (J&W Scientific, 60-m, 250-μm i.d., 0.1-μm film thickness) columns. Quantitation was done using the internal standard method. Surrogate standards were used to estimate recoveries of each compound in each sample. Quality Control and Quality Assurance. Quality control and quality assurance procedures were followed to ensure data accuracy. The detailed procedures are described in the IADN Quality Assurance Program Plan and in the IADN Quality Control Project Plan, and detailed QA/QC results have been reported by Wu et al.12 In general, the QA/QC results were satisfactory. Neither PCB-11 nor PCB-100 were found in the field blanks. Data Selection. The full list of congeners measured is given in Table S1. Because IADN’s measurements of PCB-11 began in 2004, all of the data were trimmed for the Aroclor-PCB congeners to start at that time too. For the data analysis that follows, congeners that were not measured as separate GC peaks were not used. Fr example, PCB-4 and PCB-10 could not be separated by the GC system; thus, neither congener was included. Congeners which were detected in less than 70% of the measured samples were not used; it was felt that no more than 30% left-censored data could be tolerated.13,14 In the calculations, a nondetect was an empty cell. The total PCB concentrations were also included, which in this case are the
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RESULTS AND DISCUSSION PCB concentrations at any given site and on any given day are related to the number of people living near the sampling site and to the atmospheric temperature on the sampling day.11 One needs to account for these variations if one wants to determine the long-term temporal trends of each PCB congener. This has been done using a multiple linear regression technique based on the following equation ln(C) = a0 + a1 sin(zt ) + a 2 cos(zt ) + a3 log 2(pop) + a4t (1)
where C is the measured PCB congener concentration in pg/ m3, t is the sampling date, z is 2π/365.25 (which fixes the periodicity to one year), and pop is the number of people living and working within a 25-km radius of the sampling site.11 Regression results in which the overall r2 value was
