Dr. William Mills (principal investigator). Caleb Nienow, David Scwope, Chrissy Bloomgren, Jeanne Hutcherson, Ruby Brinegar,. Bernard Huettl, Sarah Klingbiel ...
PCB EMISSIONS FROM PCB TRANSFORMERS
Dr. William Mills (principal investigator) Caleb Nienow, David Scwope, Chrissy Bloomgren, Jeanne Hutcherson, Ruby Brinegar, Bernard Huettl, Sarah Klingbiel (research assistants)
University of Illinois at Chicago August 29, 2006
Introduction Polychlorinated Biphenyls (PCBs) were produced in the USA from 1929 until banned in 1978. However the use of PCBs was still permitted for many applications. Monitoring of PCBs in the Great Lakes has shown that PCB concentrations in urban areas are greater than in rural areas, with Chicago having the most elevated levels being reported. [1-3] This project was undertaken to address the issue of whether in-use transformers are contributing to the observed levels of PCBs in the Chicago area. A steel mill in the Lake Michigan industrial area volunteered to allow air testing in the vicinity of operating PCB transformers. This facility requested that their name not be publicly revealed. Sampling was carried out at the steel mill in the motor room for the hot rolling mill (motor room) where both PCB and non-PCB transformers were located, and in outdoor air near offices on the same property, approximately 1 km away with no known PCB transformers. High volume air samplers (Hi-Vols, Tisch Environmental, Inc. model GPNY-1123) were installed and samples were collected over the course of approximately two years (2004-2006) at the steel mill site as well as two sites (IIT and UIC) in Chicago. The IIT and UIC sites (and IADN data from IIT) were used to obtain background level information for the Chicago area. Analysis of these samples would serve multiple purposes: first, the determination of whether emissions of PCBs may be occurring from the transformers, and second the contribution of these emissions to the observed PCB levels in the Great Lakes area environment. The sampling dates and locations are available in the sample logbook (Appendix A) and the project QAPP. [4]
Additional sampling at a PCB Transformer decommissioning site had been proposed initially. However, while the facility was willing to allow on-site sampling, the corporate management, located in another state, declined to allow the sampling to be carried out. Investigations of possible sampling at the property line revealed significant logistical and quality assurance issues that resulted in this work not being able to be performed. Note however that routine industrial hygiene air monitoring data is available for this site as it is reported to USEPA.
Methods Sampling Methods Hi-Vol Sampling was performed using High Volume Air Samplers (Hi-Vols, Tisch Environmental, Inc. model GPNY-1123). The samplers draw air through a metal sampling cartridge containing XAD2 using a vacuum. The samplers were calibrated using a calibrated orifice flow rate transfer standard (validated in lab) which was then used to generate a five point calibration curve for flow calculations. This calibration was carried out before each sampling campaign, or each time the samplers were moved from their locations. The samplers were operated on 24 hour cycles using a mechanical timing device and checked using the elapsed time indicator of each Hi-Vol Sampler. The top of the sampler was fitted with quartz fitler (Tisch Model TE-QMA) to prevent the passage of small particulates through the sorbent cartridge and collect particulate PCBs. The sorbent cartridge was filled with a measured amount of XAD2 resin obtained from Supelco. Prior to use, the XAD2 was cleaned using a cleaning process described in Schwope. [5] The XAD2 resin was spiked with a field surrogate to determine loss of compounds of interest from handling and storage. Hi-Vol air samplers were installed and operated at the steel mill sampling site near operating PCB transformers, near operating non-PCB transformers, and throughout the indoor facility in addition to outside the facility as far as 1 km away. Sampling was also conducted at the IADN sampling site at the Illinois Institute of Technology (IIT) at 3100 S Michigan, and the University of Illinois at Chicago at 2121 W Taylor St. Multiple sampling campaigns were carried out at the steel mill and the sampling location
for each hi-vol sampler was noted in the sample logbook. The sampling plan is described further in the project QAPP. [4] Passive Air Sampling Passive air sampling was also carried out on several occasions. The passive air samplers used are constructed of two metal bowls used to house a polyurethane foam (PUF) disc. The methodology and theory of passive sampling is further described in Gouin and Harner. [6-8] The PUF discs are cleaned in the same manner as the XAD2 resin. A field surrogate is added to the PUF disc prior to installation in the PAS. The normal cycling time for a passive air sample is three months ±2 weeks. PAS were installed at the steel mill sampling site as well as the IADN sampling site at IIT. Wipe Samples Wipe samples were also taken from the steel sampling site. These swabs were used to determine background information on PCB profiles of the steel mill. The swabs used were sterile gauze pads. The swab was wetted with acetone and then wiped over a surface of the steel mill. Wall and floor samples near Hi-Vols and PAS were taken. The swab was then stored in a glass jar for transportation and storage until extraction and analysis. Area swabs for concentration were not performed.
Sample Preparation Air Samples After sampling, the XAD2 resin was transferred to a precleaned amber glass jar with a PTFE lined lid and stored in a freezer until extraction.
The samples were then extracted at a later date using soxlhet extraction apparatuses. Prior to extraction, the samples were spiked using extraction surrogates (PCB 14, 65, 166) in order to determine extraction efficiency. The soxlhet extraction was performed using acetone:hexane (1:1) for a minimum period of 18 hours. The samples were then concentrated to a 5-10 mL volume by rotary evaporation to prepare them for column cleanup. Columns were prepared using approximately 3.5 g (6 inches) of silica gel (3.5% deactivated) and topped with a layer of dehydrated sodium sulfate. The samples were run on the columns and eluted with a single rinse of 25ml of hexanes to ensure a maximum amount of PCBs were removed. The samples were concentrated by rotary evaporation before final concentration and addition of internal standards (PCB 30 and 204). The above procedure was certified by analysis of a NIST Standard Reference Material. The sampling material was NIST SRM 1939a: PCBs in Sediment. A sediment SRM was used because no SRM exists for air sampling. The procedure used was similar to that used for air samples, with only minor changes being employed to further clean the sediment matrix. This included addition of copper to the soxlhet apparatus to remove sulfur and the rinsing of the columns with dichloromethane. The sample was also verified through the use of spike samples of a 20 congener mix solution of differing concentrations. Wipe Samples The swab samples were removed from the glass storage jars and placed in Erlenmeyer flasks. Extraction surrogates were added to the swabs. Then 100 mL of acetone:hexanes (1:1) were added to the flask and the flask was swirled manually. The
flask was then subjected to sonication for a minimum of two minutes. The solvent was then decanted into a round bottom flask. This procedure was repeated two times. The sample was then concentrated by rotary evaporation, and carried through the same cleaning and final concentration process as the air samples. The procedure was verified through the use of the same NIST sediment (1939a) used to certify the XAD2 extraction. This sediment was added to a swab and then folded into the center of the swab before being placed in an Erlenmeyer flask. The swabs were also subjected to spike samples using both the 20 congener mix solution and the NIST injection SRM 1493. Compounds of Note A field surrogate was employed to determine loss of PCBs during sampling and transport. TCMX was used for this purpose and each XAD2 sample was spiked with 200 µl (1 µg/ml) prior to sampling. Prior to extraction, the sample was spiked with 200 µl (175 ng/ml)of each extraction surrogate: PCB 14, 65, and 166. These surrogates were used to determine extraction and cleanup efficiency for each sample. Internal standards were added to each sample before final dilution. 200 µl of PCB 30 and 204 (175 ng/ml) were added for quantification of PCBs in each sample. A calibration curve for each of these compounds was developed, and this calibration curve allowed for % recovery/loss from field sampling, transportation, extraction, and cleanup to be determined.
Analysis Samples were analyzed using a gas chromatograph (GC, Agilent Technologies model 6890N) fitted with an electron capture device detector (ECD). The GC-ECD was initially calibrated for analysis using a 144 PCB congener mix (Accustandard, Inc, PCB
Mix #1-5) containing most (>98%) of the known Aroclor PCB congeners. The accuracy of this instrument and calibration curve was certified using NIST SRM 1493: PCBs in Solution. A continuing calibration standard (144 congener mix at 10 ng/ml) was also included in each GC sequence to check daily conditions. A running control chart for the internal standards (primarily PCB 30) was also maintained for quality assurance purposes. Several columns were used over the course of this project. Analysis was conducted primarily using a 60 m column or a 40 m column obtained from SGE. The columns were HT-8 columns designed for analysis of PCBs. The 60 m column had an internal diameter of 0.25 mm and a film thickness of 0.1 µm. The 40 m column had an internal diameter of 0.18 mm and a similar phase ratio. An optimal temperature ramp was developed on the 60 m column and that method was converted using the Agilent Method Translator software when the 40 m column was installed. Testing of this converted temperature ramp yielded similar results in terms of number of peaks resolved, however the run time was reduced from 61 minutes to 34 minutes. Confirmatory analysis was conducted on a gas chromatograph/mass spectrometer (Agilent Technologies model 6890N/5975). This instrument was used primarily to confirm the presence of PCBs and possible chlorobenzene contamination. Additional information on sampling and analysis methods can be found in Schwope [5] as well as the various project presentations. [9-14]
Results QA/QC Results The GC used met all quality assurance/quality control standards set by the QAPP. [4] The precision for the instrument was tested by repeat injections of the same solution. The area results for each compound from these runs are summarized in Figure 1. The average relative 95% confidence interval for all twenty compounds in the solution was found to be 4.15% on the 40 m HT8 column. The calibration curves developed for the PCB compounds appeared to have an excellent correlation coefficient, all of which were visually check for linearity. An example of one of these calibration curves can be seen in Figure 2. The accuracy of this curve was tested using the NIST injection SRM 1493. The results of the calculated concentration from this test are summarized in Figure 3. The average error of each of the compounds was 6.4%, but the maximum was 24% (PCB 28). This error can be attributed to the fact that PCB 28 is a coelutor for the method with PCB 53, therefore the calibration curve must be adjusted to account for this as well as the relative response of each congener. In general the peaks without coelution provided more accurate results than those with coelution. For coeluting peaks the measurement uncertainty is larger due to the differences in response factors (refernce the spreadsheet sarah has prepared no this and provide a copy ) The instrument still met the accuracy requirements set out by the QAPP. [4] The extraction method was validated using NIST sediment SRM 1939a. The results of the calculated concentrations from this extraction performed by three analysts are summarized in Figure 4-6. These analysts were able to obtain concentrations for each
2500000000
2000000000 209
118
195
Average Area
1500000000
204
170 206
180
128 105 137 66
30
1000000000
187 153
101 28 44
185
77 69
500000000 18 5
0 0
50
100
150
200
PCB Congener
Figure 1: Precision Study 20 congener mix 10 injections; error bars = 95% confidence intervals.
250
Figure 2: Concentration Calibration Plot for PCB 29
25
Concentration (ng/ml)
20
15 Expected (ng/ml) Observed (ng/ml) 10
5
0 18
28
52
44
66
101
153
105
138
187
128
180
170
195
206
209
Congener
Figure 3: Calculated Concentrations for NIST SRM1493 using 060110Curve; 10% error bars provided for scale 120
100
Concentration (ng/ml)
80
Expected
60
Observed
40
20
0 99
105
118
128
138
149
151
153
170
180
187
194
206
Congener
Figure 4: Calculated Concentrations for NIST SRM 1939 a by CKN; 10% Error Bars provided for scale
100
90
80
Concentration(ng/ml)
70
60 Expected
50
Observed
40
30
20
10
0 105
128
138
151
153
156
170
180
187
194
206
Congener
Figure 5: Calculated Concentrations for NIST SRM 1939 a by BJH; 10% Error Bars provided for scale
120
100
Concentration (ng/ml)
80
Expected
60
Observed
40
20
0 99
105
128
138
151
153
156
180
187
194
206
Congeners
Figure 6: Calculated Concentrations for NIST SRM 1939 a by BJH; 10% Error Bars provided for scale
PCB compound (excluding coelutions) of within 7, 9, and 11% of the expected values. All compounds’ calculated concentrations were within the QAPP requirements of 60125% of the expected value, with the exception being PCB 183, but PCB 165 (extraction surrogate) interfered with this compound so an accurate concentration could not be calculated. The results of these QA/QC results are summarized in Table 1 with a summary of the control chart for PCB 30 and 204. The control charts are presented in Figure 7 and Figure 8 respectively.
Air Sampling Results Air sampling was conducted at the previously identified sampling sites. Prior to each campaign, the air samplers were calibrated and the results tabulated as indicated in Appendix B. Sampling was carried out and all samples were recorded in the sample log book (Appendix A). These samples were analyzed on GC and GCMS. The dates and method for each sample analysis are indicated in Appendix C. The amount of air sampled had to be calculated for each sample using a flow calculation summarized in Schwope, P.73. [5] The amount of sampled air calculated for each sample is available in Table 2. Analysis of samples taken from Hi-Vol samplers throughout the sampling campaigns is summarized in Table 3. Outdoor samples taken from the roof at 2121 W Taylor St. resulted in an average of 0.227 ng/m3, and a range of 0.0245 to 0.591. Outdoor samples taken from 3100 S Michigan Ave (IIT) resulted in an average
Table 1: Significant QA/QC Results Precision (Instrument) Repeat Injections 10 Avg rel 95% CI 4.150744 Max rel 95% CI 4.388291 Min rel 95%CI 3.802555 Accuracy (Instrument) Average Error 0.063538 Max Error 0.24459 Min Error 0.005528
Accuracy (Extraction; Multiple Analyst) Average Error 0.088715 0.093398 Max Error 0.220504 0.299848 Min Error 0.006813 0.003166 Control Chart PCB 30 Mean 9.4E+08 Max 1.68E+10 Min 4.67E+08 Range 1.64E+10 Size 837 St Dev 1.04E+09 Rsd 110.5905 95% CI 70449618 Rel 95% CI 7.49209 Max/Min 3607.917 Control Chart PCB 204 Mean 9.41E+08 Max 2.48E+09 Min 4.34E+08 Range 2.05E+09 Size 601 St Dev 2.15E+08 Rsd 22.84904 95% CI 17181687 Rel 95% CI 1.826749 Max/Min 571.4454
mean max min
0.111142 0.272849 0.003687
2.10E+09 2.00E+09 1.90E+09 1.80E+09 1.70E+09 1.60E+09 1.50E+09
Area
1.40E+09 1.30E+09 1.20E+09 1.10E+09 1.00E+09 9.00E+08 8.00E+08 7.00E+08 6.00E+08 5.00E+08 4.00E+08 0
100
200
300
400
500
600
700
800
900
Run
Figure 7: Control Chart PCB 30; solid line = average area; inner dashed line = 95% CI; outer dashed line = 99% CI
2.60E+09 2.50E+09 2.40E+09 2.30E+09 2.20E+09 2.10E+09 2.00E+09 1.90E+09 PCB 204 Area
1.80E+09 1.70E+09 1.60E+09 1.50E+09 1.40E+09 1.30E+09 1.20E+09 1.10E+09 1.00E+09 9.00E+08 8.00E+08 7.00E+08 6.00E+08 5.00E+08 -5
95
195
295
395
495
Run
Figure 8: PCB 204 Control Chart; solid line = average; dashed line = 95% CI
595
Table 2: Total Volumes of Air Sampled
Sample ID ISG040121-1 ISG040121-2 ISG040121-3 ISG040121-4 ISG040121-5 ISG040126-1 ISG040126-2 ISG040126-3 ISG040126-4 ISG040126-5 IIT040601-1 IIT040601-2 IIT040620-1 IIT040620-2 IIT040702-1 IIT040702-2 UIC040702-1 UIC040702-2 UIC040726-1 UIC040726-2 UIC040902-1 UIC040902-2 UIC040913-1 UIC040913-2 ISG040918-1 ISG040918-2 ISG040918-3 ISG040918-4 ISG040918-5 ISG040918-6 ISG040918-7 ISG040927-1 ISG040927-2 ISG040927-3 ISG040927-4 ISG040927-5 ISG040927-6 ISG041001-1 ISG041001-2 ISG041001-3 ISG041001-4 ISG041008-1 ISG041008-2 ISG041008-3 ISG041008-4
sampler number 1 2 3 4 6 1 2 3 4 6 1 6 1 6 1 6 2 5 2 5 2 5 2 5 NA 4 1 6 5 3 2 1 3 6 2 4 5 3 2 5 6 1 2 3 4
Temp Avg 313.15 313.15 297 297 297 290 290 290 265.5 295.5 291.5044 291.5044 291.7611 291.7611 298.7056 298.7056 298.7 298.7 293.15 293.15 295.6239 295.6239 300.9 300.9 303.15 303.15 301.65 295.15 302.65 301.65 301.65 297.4 297.15 292.9 297.15 297.4 297.4 298.499 298.9781 297.8479 290.7958 304.6448 298.9781 298.499 308.65
Total Volume m3 765.0148 751.0439 811.2423 484.5798 560.5328 859.3738 777.7559 858.1116 648.2426 608.8897 855.6484 791.2418 725.5943 797.9334 596.0764 776.838 727.3954 636.3024 781.8158 770.7223 729.2276 864.9846 769.2002 687.6013 859.6861 586.1804 681.2994 824.4365 846.328 592.736 671.4467 325.0232 742.2485 145.4142 696.7408 808.3584 1024.64 382.7039 810.2338 749.1175 530.2451 512.4259 513.2425 464.7293
ISG041008-5 ISG041008-6 ISG041010-1 ISG041010-2 ISG041010-3 ISG041010-4 ISG041107-1 ISG041107-2 ISG041107-3 ISG041107-4 ISG041107-5 ISG041107-6 ISG041112-1 ISG041112-2 ISG041112-3 ISG041112-4 ISG041112-5 ISG041112-6 ISG041121-1 ISG041121-2 ISG041121-3 ISG041121-4 ISG041121-5 ISG041121-6 ISG041123-1 ISG041123-2 ISG041123-3 ISG041123-4 ISG041123-5 UIC050531-1 UIC050531-2 UIC050531-3 UIC050614-1 UIC050620-1 UIC050620-2 UIC050806-1 UIC050806-2 UIC050806-3 UIC050806-4 UIC050806-5 UIC050806-6 UIC051001-1 UIC051001-2 UIC051001-3 UIC051001-4 UIC051001-5 UIC051001-6 IIT051107-1 IIT051107-2 UIC051107-1
5 6 6 5 3 2 1 2 3 4 5 6 1 2 3 4 5 6 1 2 3 4 5 6 1 2 3 5 6 1 6 5 1 1 5 1 2 3 4 5 6 1 2 3 4 5 6 6 6 1
297.8479 290.7958 290.7958 297.8479 298.499 298.9781 304.6448 205.1813 300.1135 308.65 305.499 294.5302 296.2362 299.1741 306.3442 318.3086 304.0776 284.2052 300.6865 303.7333 297.0146 315.2125 304.6135 286.9417 297.8219 301.0406 301.1448 304.8896 288.7385 298.1898 306.8161 316.2175 293.55 294.0877 307.0969 302.4926 310.823 315.2901 292.15 311.2867 307.6431 291.15 293.55 293.55 293.55 291.15 293.55 286.9908
508.6453 556.4919 888.7823 575.2975 693.1422 431.2232 642.0055 668.3702 828.597 857.1692 668.1748 714.3127 716.9301 627.3583 722.9533 554.706 694.2249 681.8198 659.2773 566.3622 747.7798 653.6836 685.543 603.5725 622.5063 572.2636 843.244 702.6932 569.532 820.8611 593.9916 726.0206 571.3948 536.3168 723.7315 1896.008 447.5601 513.9094 723.0397 720.9751 555.4385 636.1229 527.8887 579.6455 727.1802 727.8764 536.4871 568.1405
284.1413
506.0646
UIC051107-2 UIC051121-1 UIC051121-2 UIC051121-3 UIC051212-1 ISG051212-1 ISG051212-2 ISG051212-3 ISG051212-4 ISG051212-5 ISG051212-6 ISG051214-1 ISG051214-2 ISG051214-3 ISG051214-4 ISG051214-5 ISG051214-6 ISG051216-1 ISG051216-2 ISG051216-3 ISG051216-4 UIC060316-1 ISG060316-1 ISG060316-2 ISG060316-3 ISG060316-4 ISG060316-5 ISG060316-6 ISG060318-1 ISG060318-2 ISG060318-3 ISG060318-4 ISG060318-5 ISG060318-6 UIC060318-1
5 1 5 6 4 1 2 3 5 6 7 1 2 3 5 6 7 1 3 5 6 4 1 2 3 5 6 7 1 2 3 5 6 7 4
284.1413 278.2611 282.2316 281.9069 276.0684 302.7906 304.3132 274.9486 300.3045 272.3497 304.1361 301.4313 305.2108 275.7559 306.2507 273.3618 302.5372 301.7351 270.2507 296.3323 268.2698 278.0771 305.6309 303.4972 279.4226 301.7125 279.6622 296.2819 304.4712 303.0701 276.6795 300.9347 278.4156 297.8757 278.7802
699.9414 563.928 775.7951 594.3269 730.2585 642.8867 589.4669 745.2815 601.9166 556.4101 582.3141 668.9859 533.526 696.5694 534.6392 577.9223 454.4184 663.1727 784.8744 598.5738 743.3197 727.4952 652.8838 536.6969 690.551 548.0591 601.7736 208.7009 630.6564 517.9818 676.0463 570.3142 578.8097 283.1459 680.432
Table 3: Summary of Calculated Concentrations for Air Samples
sample ID ISG040121-1 ISG040121-1 ISG040121-2 ISG040121-2 ISG040121-3 ISG040121-3 ISG040121-4 ISG040121-4 ISG040121-4 ISG040121-5 ISG040121-5 ISG040126-1 ISG040126-3 ISG040126-4 ISG040126-5 iit040601-1-1 iit040601-1-1 iit040601-2 iit040601-2 iit040601-2 iit040702-1 isg040918-2 isg040918-4 isg040918-5 isg040918-6 isg040918-7 isg040927-1 isg040927-2 isg040927-3 isg040927-4 isg040927-5 isg040927-6 isg041001-1 isg041001-2 isg041001-3 isg041001-4 isg041008-5 isg041008-6 isg041010-3 back isg041010-3 front isg041010-4 back isg041010-4 front
Date Analyzed
Analysis Method
PCB (total) Concentration (ng per cu. M) 18.31476255 27.19393618 88.11369063 114.5908995 152.4285593 108.2628965 131.9131459 25.46981914 169.3880212 109.9421198 246.4840496 20.38950333 16.52793819 14.81287753 24.14383345 3.862 29.48942857 5.458571429 6.751685714 2.956057143 2.873658276 7.149237017 1.295641912 15.93812304 19.0527623 15.03033477 17.58105333 13.35347052 4.466751963 6.226903978 10.13984021 22.3498148 12.38381612 21.95511779 16.84897579 0.837932364 19.82798942 1.674193655 1.294537426 17.78661289 1.509919407 27.50564986
isg041010-1 ISG041010-2 isg041107-6 isg041112-6 isg041121-6 isg041123-5 uic050620-1 uic050620-2 uic050806-1 uic051001-1 uic051001-2 uic050806-4 uic050806-5 uic051001-5 iit051107-1B uic051107-1 uic051107-2 uic051001-4 uic051121-1B uic051121-2B uic051121-3 uic051212-1 isg051214-3 isg051216-2 isg051216-4 isg060316-1 isg060316-4 isg060318-1 isg060318-4 isg060316-3 uic060316-1 isg060316-6B uic060318-1 isg060318-3
051010 051010 051010 051011 051011 051018 060110 060110 060120 060120 060120 060127 060127 060131 060131 060203 060203 060214 060214 060214 060214 060217 060324 060324 060324 060519 060519 060519 060519 060713 060713 060714 060714 060714
GC GC GC GC GC GC GC GC GC GC GC GC GC GC GC GC GC GC GC GC GC GC GC GC GC GC GC GC GC GC GC GC GC GC
0.008190983 6.164879638 0.037798571 0.0545892 0.004937269 0.00396817 0.958500709 0.351456311 0.024451369 0.063383982 1.705700446 0.141790272 0.058004774 0.061466477 0.064561498 0.264432635 0.079720959 0 0.591103875 0.479276062 0.346206801 0.415031135 0.359389893 0.608759833 0.28305453 12.91608118 16.80099872 13.05991657 14.42068128 0.2684523 0.137375486 18.80413142 0.193582911 0.340864225
concentration of 1.09 ng/m3, and a range of 0.0646 to 2.87. Samples taken at a site approximately 1 km from the transformer site resulted in an average concentration of 2.32 ng/m3 and a range of 0.00819 to 14.8. Samples taken from immediately outside the steel mill facility resulted in an average of 0.372 ng/m3, and a range of 0.268 to 0.609. Samples taken from the inside of the steel mill facility resulted in an average of 14.26 ng/m3, and a range of 6.22 to 27.5.
Method Improvements A 40 m column was used for analysis of most air samples in this project on both GC and GCMS. Prior to this, a 60 m column of similar composition had been used. Installation of the 40 m column required adapting the method to the shorter column length. A summary of these method parameters are included in Appendix D. The results provided similar separation of PCB congeners by relative retention time (Figure 9), as well as similar linear range for calculated concentrations (1-100 ng/ml). The result was a reduction in method run time from 61 min to 34 min, with a loss of only 2 resolved peaks (117 to 115) in the 144 congener mix. This represents a 44% reduction in run time with only a 1.7% reduction in resolved peaks.
4
2
y = 0.1159x + 1.0868x - 0.1834 2
3.5
y = 0.8417x + 0.176
Uic 40m ECD vs Matsumara 60m
4 3
2
R = 0.9965
2
y = 0.1159x + 1.0868x - 0.1834 Poly. (UIC 40m ECD vs 2
60 LRMS) UICm40m ECD vs 60 m Poly. LRMS(Uic 40m ECD vs Matsumara 60m) Uic 40m ECD vs
3.5 2.5
60m RRT30 60m RRT30
R = 0.9994
UIC 40m ECD vs 60 m LRMS
R = 0.9994 y = 0.8417x + 0.176 2
Linear (UIC 60m 40m ECD vs Matsumara 60 m LRMS) Poly. (UIC 40m ECD vs
3 2
R = 0.9965
60 m LRMS) Poly. (Uic 40m ECD vs Matsumara 60m)
2.5 1.5
UIC 40m vs 60m 2
y = -0.0686x + 1.1043x - 0.0487
Linear (UIC 40m ECD vs 60 m LRMS)
2 1
2
R = 0.9993 UIC 40m vs 60m
1.5 0.5
2
y = -0.0686x + 1.1043x - 0.0487 2
R = 0.9993
1 0 0
0.5
1
1.5
2
2.5
3
3.5
2.5
3
3.5
UIC 40m RRT30
0.5
0 0
0.5
1
1.5
2
UIC 40m RRT30
Figure 9: Comparison of HT8 40 m PCB column and HT8 60 m column and Matsumara [15] 60 m column by relative retention times of PCB congeners to PCB 30 retention time.
Discussion Analytical Method Improvements Throughout the course of this project many improvements to the original procedures were made in order to improve accuracy and efficiency. The most significant change made was the analytical column used in the GC instrument. The first column used was DB-5 column and the oven cycle method was 175 minutes long. The next column used was a DB-XLB column and the method time was shortened to 120 minutes. The next column used was the 60 m HT8 column and the run time was reduced to 61 minutes. The first of the air samples were analyzed on this column. Finally, a 40 m HT8 column and method was used for all samples to the present day. The method for this column has a run time of only 34 minutes which has allowed much greater throughput of samples. This column has been shown to provide separation comparable to previous columns and literature values. (Figure 9) The efficiency of separation (115 of 144 possible peaks) is considered well within in the limits of the QAPP. [4] Analysis in this project was conducted by congener specific analysis. The individual PCB congeners within the 144 congener mix are all quantitated and summed to determine the total amount of PCBs in the sample. Although historically, many projects have reported PCB content in terms of Aroclor concentration, more recent results, including those of IADN have utilized congener specific methods. [1, 3, 15-20] Aroclors are the PCB mixtures used as transformer fluids in PCB transformers. The specific congeners and relative concentrations of PCBs in Aroclors can be determined through quantification of the standard Aroclor mixture chromatograms (Appendix E). Aroclor content can be reported by establishing a database for each mixture however the
Aroclor content can also be determined through the use of statistical programs as outlined in Schwope. [5] This showed that congener specific data profiling can provide statistically similar data to Arocolor profiling. Congener specific analysis provides data for Aroclor content as well as additional data for use in tabulating the total amount of PCBs present in each sample. It is important to note that aroclor pattern analysis is really only applicable to liquids or fresh spills where the aroclor pattern is unchanged by weathering etc.. for air samples the use of aroclor quantitation is fraught with difficulty and is far less accurate than the congener specific method used here. Unfortunately little work has been performed looking at the congener composition of air samples classified or quantified as Aroclors.
Quantitation Issues There are several issues that must be addressed in regards to the quantitation of PCBs. Linear range While initial attempts were made to establish a 1 to 1000 ng/mL calibration curve it was found that the linear range for the 6890 micro ECD only goes from 1 to 100 ng/ml based on the NIST injection SRM performance. Outside of this range the curve develops a sigmoidal shape. Therefore any of the values reported lower than 1 ng/ml may not be as accurate since it is based on a linear extrapolation of the curve. These values are still used to identify those compounds that were reported by the instrument as PCBs. This issue poses another problem since any values below 1 ng/ml could be as little as zero ng/ml but also as much as 1 ng/ml. A PCB congener which is not detected by the
instrument is reported to have a concentration of zero ng/ml, but it must be considered to possibly be as high as 1 ng/ml without confirmatory analysis. The issue of how to handle values less than detection limits (or lowest calibration limit) has been discussed in some detail by Mills. [21] In regards to air samples, while the HT8 column generally provided better analytical results, there were unforeseen problems with interference for the extraction surrogates resulting in coelutions. Interferences with native-PCBs were not predicted by the 144 congener mix, but practical analysis indicated that interferences took place. Thus PCB 14 was interfered with PCB 19, PCB 65 was interfered with PCB 104, 75, 48, and 47, and PCB 166 was interfered with PCB 126 and 183. This issue could not be resolved fully, even with GC-MS anslysis. and because of this, the calculated concentrations for these congeners were removed from the calculation for concentration in the samples. . The surrogate recoveries could also not be calculated reliably for these compounds with a high degree of certainty because of this issue. In addition, interference from chlorobenzenes and other compounds made analysis of TCMX difficult or impossible for most samples. The issue was recognized and the use of F-PCBs was investigated. However there were insufficient numbers of F-PCBs available to pursue this fully. Further investigation into this problem, including additional F-PCBs, is recommended. The monochlorinated PCBs were also excluded in quantitation of these samples. The response factors for these compounds were very low due to their low degree of chlorination and as a result the compounds were barely visible at environmentally relevant levels. Monochlorinated PCBs also elute first and very early relative to other PCBs and as such are more subject to interference issues from chlorobenzenes and
similar compounds. As a result, they were excluded from the quantitation, although additional research may provide better response through the use of better defined SIM windows on GCMS or development of a method that can distinguish between the chlorobenzenes and monochlorinated PCBs. It is noted that pcb1-4 have often been excluded in other work in the Chicago area. [3]
Air Sampling Discussion of air sampling results is limited to those samples that resulted in chromatograms that could be analyzed by the GC software. Many samples contained interferences from unknown chemicals that made it impossible as there was no baseline resolution. An example chromatogram of one such sample is presented in Figure 10 and the ECD chromatogram for the same sample is presented in Figure 11. Any XAD2 sample listed in the sample logbook (Appendix A) that is not listed in the Air Sample Summary Table (Table 3) was judged to contain interferences that prevented reliable data to be reported. Data discussed in this report is also limited to data not already presented in Schwope, [5] which consists primarily of data taken from different sampling campaigns at UIC as the steel mill site since January of 2005. A great amount of variation can be observed in the air samples. The indoor samples from the steel mill site contained the highest concentration of PCBs, as was hypothesized. The indoor samples were higher than the air that is brought in by the ventilation system by approximately an order of magnitude so the motor room is a source. However, it is difficult to assess if the PCB concentrations observed in the motor
Figure 10: GCMS Chromatogram for sample ISG060316-3 analyzed on SIM mode with CCS overlay (green) provided for scale.
Figure 11: GC-ECD Chromatogram for sample ISG060316-3.
room are a sole result of the PCB transformers since the wipe samples taken show the presence of PCBs present on the surfaces within the facility (Figure 12). It is not known if these are present due to historical spills or other sources. Swabs of known area would need to be taken in order to determine the magnitude of possible contribution to the air samples from background PCBs. This is especially important since the calculated concentrations for interior PCB samples are at least one order of magnitude higher that the samples taken immediately outside the facility. Passive samplers will also provide information regarding levels of PCBs, in the motor room however there were qa/qc issues with how many of the PAS were setup and extraction of these samples was not completed as of the writing of this document.
IIT v UIC Using the data available, a number of comparisons can be made. First, the data from samples taken in the Chicago area at UIC and at IIT can be analyzed for profiles and for concentrations. The data indicates that air sampled at UIC (0.227 ng/m3) had a lower average concentration of PCBs than air sampled at IIT (1.09 ng/m3). This is misleading however since the data from IIT contains a much wider range of concentrations (2.87 to 0.0646) in only three samples than the UIC data (0.591 to 0.0580) over many more samples over a greater period of time. It is also observed that samples obtained on the same date from both locations resulted in higher values observed at the UIC site than at the IIT site. This agrees with previously published results in Basu, et. al. [1] There are only two dates for which this data is available so it therefore
Figure 12: GC-ECD chromatogram for sample RJB060327-9, a wipe sample taken inside the motor room.
difficult to state with any certainty that one location differs greatly in concentration from the other. Comparing the profiles of these two locations shows many similarities in the relative percentage of PCBs. (Figure 13) All samples contain very few of the heavily substituted PCB homolog groups (octa, nona, or decachlorinated). PCBs 5/8, 18, 31, 53/28, and 44 were present in significant (greater than 2% of the total) concentrations in all the samples, and PCB 51 was present in all but one of the samples (UIC051107-1). These congeners represent more than 50% of the total PCBs in all of the samples except for UIC051107-1. This sample contained a significant contributor (PCB 117/97, 16.5%) that was not present or at a very low level (0.53%) in all other samples. PCB 22 was the largest contributor in this sample (25.7%) although in all other samples this congener was much less significant (maximum of 2.18%). The PCB congener profile for this sample was therefore skewed, and the actual concentrations of the congeners was similar to that found in sample UIC051107-2 with the exception of the largest two congeners (PCB 117/97 and 22). Cursory analysis indicates that the profiles are similar to each other, although further analysis for cosine theta values would help determine if the profiles are statistically similar.
ISG Comparison The samples taken at the steel mill site indicate that samples taken inside the motor room with the PCB and non-PCB transformers contain much higher levels of PCBs than those taken even immediately outside the air exchanges for the building. The average concentration for the samples taken within the building was 13.7 ng/m3 with a
Relative % of Total PCBs
30 25 iit051107-1B
20
uic051107-1 uic051107-2
15 10 5
_205
_167
_157
_129
_122
_130
_144
_123
_56
_67
_66
_48
_87_115
_196_190_203
PCB Congener
_64
_25
_46
_14
_32
_10_4
0
Figure 13: PCB congener profiles for samples taken from UIC and IIT sampling sites on Nov. 7, 2005.
range of 6.16 to 18.8. The average concentration for samples taken immediately outside the building was 0.372 ng/m3 with a range of 0.268 to 0.609. The samples taken approximately 1 km away resulted in an average concentration of 0.0219 ng/m3 with a range of 0.00397 to 0.0546. The samples taken inside the building therefore had a concentration of at least one order of magnitude greater than samples taken outside the building. This indicates that the PCB levels observed inside the building do not appear to be caused by sources outside of the building. The PCBs observed outside the building may or not originate inside the building. Samples taken of ambient air at the intakes contain much lower concentrations of PCBs than interior air as well. The profiles of the samples show significant differences between the indoor and outdoor air samples (Figure 14). The indoor samples significant contributors include PCBs 8/5, 18, 31, 53/28, 52/69, 44, 93/95, 101, 110/81, and 118. These congeners represent more than 40% of the total PCBs in all of the indoor samples. The outdoor samples (taken immediately next to the building) significant contributors include 8/5, 18, 17, 13/12/24, 27, 32, 31, 53/28, 52/69, and 24. The outdoor samples taken approximately 1 km away from the site exhibited no consistent pattern. This data must be viewed with skepticism since many of the calculated concentrations are lower than the calibration curve. In general, the air samplers taken inside the facility contain more varied PCBs and heavier PCBs than those seen in the outdoor samples. Parts of the profile are similar, however, and statistical analysis would reveal if similar Aroclor mixtures contribute significantly to both samples. Cursory analysis of the profiles for samples taken at different locations inside the building does not indicate any significant differences in profiles (Figure 15). The air inside the motor room does appear to be well mixed and
14
Relative % of Total PCBs
12 10 isg060316-3 (outdoor) 8
isg060316-4 (indoor)
6 4 2
_209
_207
_193
_183
_197
_176
_118
_85
_82_77
_84
_119
_164_163
PCB Congener
_93_95
_44
_41
_25
_46
_14
_32
_10_4
0
Figure 14: PCB congener profiles for samples taken indoors and outdoors at the steel mill sampling site on March 16, 2006.
Relative % of Total PCBs
12 10
isg060316-1 (near Transformers)
8 6
isg060316-4 (center of room)
4 2
_209
_193
_207
_183
_197
_164_163
_118
_176
_85
_82_77
_84
_119
_41
PCB Congener
_93_95
_10_4 _14 _32 _25 _46 _44
0
Figure 15: PCB congener profiles for samples taken at different locations in the motor room at the steel mill sampling site on March 16, 2006.
lower concentrations were not observed where there were non-PCB transformers. Further statistical analysis is necessary to determine if there are any differences in Aroclor contributors. It is also important to note at this time that calculated concentrations for samples collected from all sites during the discussed sampling campaigns are significantly lower than those discussed in Scwope. [5] The previously analyzed data showed much greater average concentrations of ambient air in Chicago as detailed by Mills, et.al. [10] This data must be reviewed closely to determine if any significant changes occurred that lead to lower observed levels of PCBs or if the data accurately reflects an actual change of PCB levels in the environment.
GCMS Interference Issues Confirmatory analysis was attempted using a GCMS run on selective ion monitoring (SIM) mode. It was hoped that this would provide better, confirmatory data for coelutions of PCB congeners, expecially cases when the coeluting PCBs were of different homolog groups since the GCMS would be able to distinguish between congeners with different mass ions. It was also hoped that GCMS SIM monitoring would be able to clear up some interference problems caused by possible chlorobenzenes, PAHs, and other related compounds. However, the resulting chromatograms did not successfully resolve these issues as contaminants remained in the samples, and new interference problems arose in samples that did exist on GC-ECD analysis. Figure 10 shows an example chromatogram from the GCMS instrument on the standard methods on SIM analysis mode. Figure 11 shows the same sample analyzed on GC-ECD. The
sample could not be quantitated on the GCMS due to the large amount of interference and complete lack of baseline resolution. This was typical of air samples analyzed on the GCMS. Further cleaning of these samples may be necessary, or a new method for GCMS analysis could be developed that may resolve some of these issues. Some preliminary work has been performed on sample cleanup.
Mass Balance Calculations It is possible to estimate a mass balance for total PCBs in the motor room at the sampling site. The total volume of the motor room is estimated to be 159282.3 m3 based on a simple average cross section multiplied by the length of the building. The average PCB concentration was determined to be 6.16 to 18.8 ng/m3 inside the motor room. Using this data, the total amount of PCBs in the motor room is calculated to be 9.81*10-7 to 2.99*10-6 kg. These values are based on calculations for daily loadings. The total yearly loading can be calculated to be 3.58*10-4 to 1.09*10-3 kg/yr. These numbers are to be considered preliminary estimates only at the present time until further review of the data is completed.
Challenges Encountered During the course of this project several challenges were encountered. The most significant challenge was the administrative delays encountered due to the manner in which the different funding sources were combined. This resulted in a nine month period of paralysis for the research, primarily due to instrumental problems with the GC-ECD which could not be resolved without a service contract with the instrument manufacturer, which could not be awarded while the administrative problems were occurring. While the use of ht8 column provided numerous analytical improvements, the surrogates that were used, pcb 14, 65 and 166 (based on IADN and other work) did suffer from potential interferences. However the SRM results would tend to indicate that extraction and cleanup were not generally a problem.
A more significant problem was the interference from the steel mill air. All filters were found to exhibit significant particulate matter and were black or grey in appearance. While the exact nature of the interferences are not known, steel mills sampling is a challenging environment. The use of more extensive cleanup is the primary method of addressing this issue but time and budgetary constraints prevented further investigation of a new method.
Conclusions The project carried demonstrated an effective method for sampling of PCBs from ambient air and quantitation of those PCBs by GC-ECD. The analytical method validity was demonstrated by various QA/QC protocols undertaken throughout the project summarized in Table 1. Analysis of air samples yielded concentrations that confirmed previous results comparing two locations in the Chicago area. [1] As expected, the concentrations of PCBs in air in the motor room was much greater than air taken outside, even one order of magnitude greater than the concentration in samples taken at the air outtake. The PCB congener profiles for samples taken inside the motor room also show the presence of heavier PCBs as expected, suggesting heat based volatilization. [5, 21] The location of sampling within the motor room itself does not appear to have a great affect on the concentration or profile of PCBs observed. This may indicate a thorough mixing of air within the motor room or a major source of PCBs in the motor room located elsewhere in the building. Surface contamination of PCBs was observed in the motor room and quantification of surface PCBs must be undertaken to eliminate them as a source of PCBs in the ambient air. Temperatures for samples taken within the motor room were within a narrow range, indicating that outside air has little impact on the indoor temperature. A mass balance calculation was produced but must be considered preliminary until further review of the data. Further sampling is suggested at new locations, including the transformer decommissioning facility, to compare PCB levels near working transformers in both good and poor conditions. Analysis of the PAS samples will also provide more data and further use of PAS is recommended.
References 1.
Basu, I., R. Hites, and W. J. Mills. (2003). "Spatial Differences in PCBs at Two Air Monitoring Locations in Chicago." in Proceedings: International Association of Great Lakes Research. Chicago, IL.
2.
Eisenreich, S. J., B.B. Looney, and G.J. Hollod (1983). PCBs in the Lake Superior Atmosphere 1978-1980. Physical Behavior of PCBs in the Great Lakes. S. P. D. Mackay, S.J. Eisenreich, and M.S. Simmons. Ann Arbor, Ann Arbor Science Publishers, Inc.: 442.
3.
Hsu, Y. K., T. Holsen, and P.K. Hopke (2003). "Locating and Quantifying PCB Sources in Chicago: Receptor Modeling and Field Sampling." Environ. Sci. Technol.(37): 681.
4
Mills, W. J. and A. Li. (2005). "Quality Assurance Project Plan Rev. 1.2," University of Illinois at Chicago, Chicago, IL.
5.
Schwope, D. (2005). Improvements in Sampling and Analytical Methods for Polychlorinated Biphenyls in Environmental Samples. Department of Biopharmaceutical Sciences. Chicago, University of Illinois at Chicago: 260.
6.
Gouin, T., T. Harner, P. Blanchard, and D. MacKay (2005). "Passive and Active Air Samplers as Complementary Methods for Investigating Persistent Organic Pollutnts in the Great Lakes Basin." Environ. Sci. Technol. 39: 9115-9122.
7.
Harner, T., and M. Shoeib (2002). "Characterization and Comparison of Three Passive Air Samplers for Persistent Organic Pollutants." Environ. Sci. Technol. 36: 4142.
8.
Harner, T., M. Shoeib, M. Diamond, G. Stern, and B. Rosenberg (2004). "Using Passive Air Samplers To Assess Urban-Rural Trends for Persistant Organic Pollutants. 1. Polychlorinated Biphenyls and Organochloride Pesticides." Environ. Sci. Technol. 38: 4474-4483.
9.
Mills, W., D. Schwope, C. Nienow, C. Bloomgren, and A. Li (2003). Source Profiles and Emissions Quantitation of PCB to Ambient Air from Transformers. Proceedings: IEPA 2004.
10.
Mills, W., D. Schwope, C. Nienow, and C. Bloomgren (2004). Emissions from PCB Transforms - Preliminary Data. USWAG PCB Workshop.
11.
Mills, W., D. Schwope, C. Nienow, J. Hutcherson, and R. Brinegar (2006). Air Emissions of PCBs from Transformers. IAGLR 2006.
12.
Schwope, D., R. Malcolm, W. Mills, and A. Li (2003). Source Profiles and Emissions Quantitation of PCB to Ambient Air from Transformers. MWECW 2003.
13.
Schwope, D., C. Nienow, and W. Mills (2005). Congener Specific and Aroclor PCB Analysis on the HT8-PCB GC Column. Dioxin 2005 Conference.
14.
Schwope, D., C. Nienow, and W. Mills (2006). Congener-Specific and Aroclor PCB Analysis on the HT8-PCB GC Columnfor SW-846 Method 8082. Enviroanalysis 2006.
15.
Harrad, S., S. Hazrati, and C. Ibarra (2006). "Concentrations of Polychlorinated Biphenyls in Indoor Air and Polybrominated Diphenyl Ethers in Indoor Air and Dust in Birmingham, United Kingdom: Implications for Human Exposure." Environ. Sci. Technol. 40: 4633-4638.
16.
Kohler, M., M. Zennegg, and R. Waeber (2002). "Coplanar Polychlorinated Biphenyls (PCB) in Indoor Air." Environ. Sci. Technol. 36: 4735-4740.
17.
Kohler, M., J. Tremp, M. Zennegg, C. Seiler, S. Minder-Kohler, M. Beck, P. Lienemann, L. Wegmann, and P. Schmid (2005). "Joint Sealants: An Overlooked Diffuse Source of Polychlorinated Biphenyls in Buildings." Environ. Sci. Technol. 39: 1967-1973.
18.
Pozo, K., T. Harner, F. Wania, D. Muir, K. Jones, and L. Barrie (2006). "Toward a Global Network for Persistent Organic Pollutants in Air: Results from the GAPS Study." Environ. Sci. Technol. 40(4867-4873).
19.
Vorhees, D., A. Cullen, and L. Altshul (1997). "Exposure to Polychlorinated Biphenyls in Residential Indoor Air and Outdoor Air near a Superfund Site." Environ. Sci. Technol. 31: 3612-3618.
20.
Vorhees, D., A. Cullen, and L. Altshul (1999). "Polychlorinated Biphenyls in House Dust and Yard Soil near a Superfund Site." Environ. Sci. Technol. 33: 2151-2156.
21.
Mills, W. (2001). Polyhlorinated Biphenyls, Dioxins and Furans in Ambient Air During the Smithville PCB Incineration Project. Environmental and Ocupational Health Sciences. Chicago, University of Illinois at Chicago: 522.
