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Source Apportionment of Atmospheric Polychlorinated Biphenyls in New Jersey 1997- 2011 Pornsawai Praipipat, Qing Yu Meng, Robert J. Miskewitz, and Lisa A. Rodenburg Environ. Sci. Technol., Just Accepted Manuscript • DOI: 10.1021/acs.est.6b04572 • Publication Date (Web): 04 Jan 2017 Downloaded from http://pubs.acs.org on January 4, 2017

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Source Apportionment of Atmospheric Polychlorinated Biphenyls in New

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Jersey 1997- 2011

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Pornsawai Praipipat1,2, Qingyu Meng3, Robert J. Miskewitz1, and Lisa A. Rodenburg1* 1

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Department of Environmental Sciences, Rutgers University, 14 College Farm

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Road, New Brunswick, NJ 08901, USA 2

Current affiliation: Department of Environmental Science, Faculty of Science, Khon Kaen

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University, Khon Kaen 40002, Thailand 3

School of Public Health, Rutgers University, Piscataway, New Jersey 08854, USA

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* Corresponding author, formerly Lisa A. Totten. Email: [email protected], Phone:

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848-932-5774 Fax: 732-932-8644

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Abstract

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Concentrations of polychlorinated biphenyls (PCBs) in the Delaware River currently

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exceed the Water Quality Criteria of 16 pg/L for the sum of PCBs due in part to atmospheric

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deposition. The purpose of this work was to use a source apportionment tool called Positive

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Matrix Factorization (PMF) to identify the sources of PCBs to the atmosphere in this area and

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determine whether their concentrations are declining over time. The data set was compiled by

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the Delaware Atmospheric Deposition Network (DADN) from samples taken in Camden, NJ

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from 1999 to 2011 and New Brunswick, NJ from 1997 to 2011. The PMF analysis revealed four

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resolved factors at each site. The factors that dominate the PCB burden in the atmosphere at

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both Camden and New Brunswick resemble Aroclor 1242. These factors declined in

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concentration during some portions of the monitoring period, but this decline slowed or stopped

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during 2003-2011. None of the factors displayed consistent declines in concentration throughout

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the monitoring periods, and some factors actually increased in concentration during some

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periods. This suggests natural attenuation alone will not control atmospheric PCB

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concentrations, and additional efforts are needed to control PCB atmospheric emissions as well

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as the numerous other sources of PCBs to the estuary.

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Introduction

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Polychlorinated biphenyls (PCBs) are toxic, persistent, and bioaccumulative chemicals

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that are targeted for phase out under the Stockholm Convention on Persistent Organic

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Pollutants.1 PCB levels in most US environmental compartments have declined dramatically

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since PCBs were banned in the 1970s.2-5 However, PCB concentrations in the Delaware River

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currently exceed the Water Quality Criteria of 16 pg/L for the sum of PCBs due in part to

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atmospheric deposition.6 The sources of atmospheric PCBs are not clear. They may include old

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PCB-containing equipment, joint sealants, caulks, waste incineration, storage and disposal

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facilities, superfund sites and accidental releases.7-17 Because the sources are not known, it is not

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clear what measures would be effective in reducing atmospheric PCB concentrations. Several

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recent studies have examined the long-term temporal trends in atmospheric PCB

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concentrations.4, 18-26 However, most of these studies measured a short list of PCB congeners24, 25,

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27

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sources of atmospheric PCBs,28-31 it is important to investigate temporal trends in urban

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atmospheric PCB concentrations. Only one other study 13 has examined temporal trends for a

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comprehensive list of PCB congeners and conducted source apportionment of the congeners to

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examine temporal trends in atmospheric source categories. This previous study used data from

and/or examined trends in rural or remote areas. Since urban areas appear to be the primary

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the Integrated Atmospheric Deposition Network (IADN) from Chicago, IL, USA. 13 The present

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work examines temporal trends for a long list of PCB congeners and their source categories for

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urban (Camden) and suburban (New Brunswick) sites in New Jersey using data from the

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Delaware Atmospheric Deposition Network (DADN). The DADN gathered data on atmospheric

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PCB concentrations in support of the Total Maximum Daily Loads (TMDLs) for PCBs

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developed by the Delaware River Basin Commission (DRBC) for the entire tidal portion of the

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Delaware River and Delaware Bay. The DADN included as many as eleven sites over various

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years. In the present work, data from the New Brunswick and Camden sites were chosen for

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examination via Positive Matrix Factorization (PMF) because they have the longest data history.

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PMF is an advanced source apportionment tool developed by Paatero and Tapper32 that

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has been used to identify PCBs sources in water, sediment, and air.10-12, 33-36 The present work

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builds on previous studies in which PMF was used to apportion PCB sources to the water

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column35, point source dischargers37, and sediment36 of the Delaware River Basin. The present

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work also builds on our previous effort to apportion PCB sources in the air of Chicago.13

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Therefore, the goals of this work were to apportion the major sources of PCBs to the air in New

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Jersey and the Delaware River Basin and to determine whether atmospheric PCB concentrations

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are declining over time in order to predict when the concentrations of PCBs in the Delaware

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River might drop below the water quality standard, thus achieving the TMDL. Another goal was

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to compare the PCB sources in Camden (Philadelphia) to another major US city, Chicago.11, 13

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Methodology

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Study Sites

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Camden, NJ is located across the river from Philadelphia, PA which is currently the fifth largest city in the US, and was 4th largest in 1970 during the years of peak PCB usage.38 In a

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previous work, PCB sources in the Camden DADN samples from 1999 to 2002 were

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investigated using PMF.11 The present study updates the previous one and includes data gathered

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from 1999 to 2011, allowing an evaluation of temporal trends. The DADN network did not

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operate in Camden from August 2002 to March 2004 due to lack of funding. New Brunswick is a

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suburban city in New Jersey with a population of about 55,000 in the 2010 census.39 New

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Brunswick and nearby Piscataway host the main campus of Rutgers, the State University of New

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Jersey, which is host to about 40,000 students.

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PCB measurements

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The methods used to measure PCBs in the DADN samples have been described

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previously and are summarized in the Supporting Information section 1.40, 41 In brief, 24-hour

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air samples were collected using high-volume air samplers with quartz fiber filters (QFF) to

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capture the particle phase and polyurethane foam (PUF) to the collect PCBs in the gas phase.

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PUFs and QFFs were extracted in a Soxhlet apparatus, cleaned up on florisil, and analyzed for 60

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PCB peaks representing 93 congeners via electron capture detection on an Agilent 6890 gas

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chromatograph. Methods remained the same throughout the data collection period.

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PMF analysis

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For this study, Positive Matrix Factorization (PMF) version 2.0 software (Yp-Tekniika

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Ky Co., Helsinki, Finland) was used to examine the gas phase PCB concentrations only (particle

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phase concentrations were ignored). In contrast, our previous PMF analysis of PCBs in Camden

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utilized the gas plus particle phase concentrations, however, that analysis isolated a factor that

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represented particle phase PCBs.11 The gas phase typically contains about ten times higher PCB

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concentrations than the particle phase, so excluding the particle phase excludes only a small

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fraction of the total atmospheric PCB mass.28 Data from the two DADN sites were analyzed in

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separate PMF runs. (A pooled data set from both sites was analyzed, but the results produced

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only three factors and are not shown here.) The relative standard deviation of the recoveries of

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the applicable surrogate was used as the uncertainty for the detected concentrations of individual

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congeners. Non-detects were substituted with a random number between zero and the detection

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limit, and assigned three times the uncertainty of the detected concentrations.

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To prepare the data for PMF analysis, first congeners and samples in which a large

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number of measurements were below detection limit (i.e. more than 130 non-detects at New

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Brunswick and more than 145 non-detects at Camden) were removed. Detection limits for

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individual PCB congeners (or co-eluting groups) ranged from 0.013 to 1468 pg m-3 at Camden

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and from 0.002 to 612 pg m-3 at New Brunswick for PUFs. This yielded 54 PCB congeners in

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234 samples at Camden and 48 PCB congeners in 307 samples at New Brunswick. After

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preliminary PMF runs, several samples were removed because they were outliers in the

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preliminary PMF solutions due to more than 20 congeners below detection. Thus the final data

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matrices consisted of 49 congeners in 226 samples at Camden, and 46 PCB congeners in 307

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samples at New Brunswick. These congeners represented the tetra through nona homologues.

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The number of factors was determined to be four each for Camden and New Brunswick (see

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Supporting Information section 2 for justification). For clarity, these are hereafter referred to as

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factors 1C, 2C, 3C, and 4C (from Camden) and factors 1NB, 2NB, 3NB, and 4NB (from New

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Brunswick).

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Results and Discussion

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At Camden, average (± standard deviation) gas-phase 93PCB concentrations (Figure S-

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1) fell from 4600 ± 3300 pg/m3 in 1999 to 1600 ± 1000 pg/m3 in 2011. New Brunswick, average

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gas-phase 93PCB concentrations (Figure S-1) similarly declined from 330 ± 220 pg/m3 in 1997

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to 110 ± 60 pg/m3 in 2011. Camden is therefore similar to other urban areas of the US, such as

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Chicago 23, in having relatively high atmospheric PCB concentrations. In comparison to sites

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from the Integrated Atmospheric Deposition Network which surrounds the North American

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Great Lakes, concentrations at New Brunswick are more similar to sites that have some urban

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influence, such as Sleeping Bear and Sturgeon Point, but are higher than truly remote sites such

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as Brule River or Eagle Harbor.23

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Before doing the PMF analysis, it is important to investigate the raw data for trends.

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Gas-phase PCB concentrations almost always display a temperature dependence that roughly

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follows a Clausius-Clapeyron relationship, because more energy is available to drive their

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volatilization at higher temperatures.4, 13, 23, 26, 42, 43 In particular, the measured gas-phase

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concentrations of each congener were investigated as a function of both temperature and time via

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the widely-used approach4, 13, 23, 26, 42, 43 of fitting the natural log of concentration (ln Cgas) versus

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time (t in days) and inverse temperature (1/T in Kelvin) via a least-squares regression:

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1 ln C gas  a0  a1    a2t T 

(Eqn. 1)

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where a0, a1 and a2 represent the coefficients for the intercept, temperature, and time parameters,

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respectively. As is typical of gas-phase PCB concentrations, all PCB congeners displayed a

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significant correlation (p < 0.05) with temperature, with higher PCB concentrations at higher

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temperatures (Supporting Information Figure S-2 and S-3). As observed in other studies, lower

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molecular weight congeners displayed weaker temperature dependence43, in keeping with their

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lower enthalpies of vaporization.44 Figure S-4 demonstrates that the temperature dependence of

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most PCB congener concentrations was greater and a stronger function of vapor pressure at the

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urban site, Camden, than at suburban New Brunswick. A stronger temperature dependence of

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gas-phase PCB concentrations in urban versus rural areas has been observed in other studies.43, 45,

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Simcik et al. 45 have suggested that this occurs because urban monitoring sites are nearer to

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PCB sources. In contrast, the effect of temperature on PCB concentrations is muted at rural

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locations because the PCBs must travel farther to reach them.

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Most congeners displayed significant negative values of a2 over the full monitoring

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period, implying that their concentrations are decreasing over time. At Camden, PCBs 40,

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85+136, 153+132, 137+176+130, 163+138, 158, 187+182, 183, 185, 202+171+156, 199,

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170+190, 201, 203+196, and 194 displayed no significant correlation with time (i.e. neither

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increasing nor decreasing). PCBs 195+208 and 206 were increasing over time (i.e. a2 was

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positive and significant p