Engineering and Analysis Division Brian Englert 

Office of Science and Technology 202-566-0754 

04/15/2010 

Summary: 

Malcolm Pirnie compared polychlorinated biphenyl (PCB) congener data from the Cooperating 

Parties Group (CPG) 2008 Low Resolution Coring Program and split1

 samples collected by 

Malcolm Pirnie for the U.S. Environmental Protection Agency (USEPA) as part of the lower 

Passaic River oversight program.2,3 Both laboratories used Method 1668A when performing 

PCB congener analyses. 

In their assessment, Malcolm Pirnie selected all PCB homologues and total PCBs for 

comparison. Malcolm Pirnie also selected six PCB congeners to represent the trichloro to 

octachloro homologue groups (congeners 18, 52, 110, 153, 187 and 195), and four additional 

congeners that will be modeled to examine future surface sediment concentrations (congeners 

31, 77, 105 and 118), and included them in the analyses. For all PCB congener data, only 

samples for which the two laboratories’ reported concentrations were at least five times the 

sample-specific quantitation limit (SSQL) were considered. 

Malcolm Pirnie used a combination of graphical methods and statistical analyses to assess 

whether there was a consistent bias between the two laboratories. While statistically significant 

differences were observed for some of the PCB congeners, the medians of the differences 

between the two laboratories’ results were mostly within 20 percent, and all were within 30 

percent. 

While the purpose of the Malcolm Pirnie assessment was to determine whether there was a bias 

between the two laboratories analyzing the Passaic River samples, these data also may be used to 

summarize the performance of Method 1668A. Therefore, a separate assessment of the split 

sample data was performed across all congeners and coeluting congener groups to assess the 

between-laboratory variability. Both laboratories also analyzed various types of QC samples. A 

subset of these QC data, including matrix spike/matrix spike duplicate (MS/MSD) results, 

laboratory duplicate results, and standard reference material (SRM) results, were used to 

estimated the precision and bias of the method. Other QC data reported for the Passaic River 

assessment, such as laboratory control samples (LCS) and labeled recoveries in study samples, 

has previously been used in evaluations and modifications of Method 1668 QC acceptance 

criteria, and therefore were not included in this assessment. 

Comparison of USEPA and CPG Split Samples: 

A total of 30 split samples were analyzed as part of the Lower Passaic River assessment. For 

each sample, both analytical laboratories performed PCB congener analyses using EPA Method 

1668A. A total of 151 individual PCB congeners or congener groups were reported by both 

laboratories with the same coelution structure. For these congeners and coeluting groups, results 

from the two laboratories could be compared for each sample. While the statistical analyses 

performed by Malcolm Pirnie were chosen to determine whether there was a bias between 

laboratories, this would not necessarily indicate an issue with the method itself. However, an 

examination of the distribution of relative percent differences (RPDs) can be used to assess 
Engineering and Analysis Division Brian Englert 

Office of Science and Technology 202-566-0754 

04/15/2010 

whether appropriately similar results between the two laboratories can be obtained using the 

method. 

For each congener or congener group, descriptive statistics of the RPDs of each split sample pair 

were calculated. To be consistent with the Malcolm Pirnie assessment, only pairs for which both 

laboratories’ results exceeded 5 times their SSQLs were included. Additionally, one sample that 

was removed by Malcolm Pirnie due to suspected matrix heterogeneity also was excluded for 

this assessment. RPDs also were summarized across congeners in each level of chlorination, and 

across levels of chlorination. 

Across all congeners, there were 1,500 pairs for which both laboratories’ results exceeded 5 

times their sample-specific quantitation limits. When calculated across these pairs, the pooled 

RPD (calculated as the square root of the mean of the squared RPDs) was 27.5%, and the median 

RPD was 13.5%. Only 21.3% of the pairs across all congeners yielded RPDs exceeding 30%, 

and only 6.8% of the pairs yielded RPDs exceeding 50%. Generally, pairs were more precise in 

chlorination levels 4-7, and were the less precise for chlorination levels 1-3 and level 8. This 

was likely due to the lower concentrations observed in the lower-weight chlorination levels. As 

concentrations approach the sample-specific quantitation limit, relative variability (as expressed 

by an RPD) tends to become larger, therefore these higher RPDs indicate a concentration effect 

rather than a method performance issue. 

Performance of USEPA QC Samples: 

The laboratory analyzing the USEPA split samples reported results of NIST SRM samples and 

laboratory duplicates. These results can be used to assess the bias and precision of the method, 

based on the laboratory’s performance. These assessments are described below. 

Bias: The QAPP used by USEPA in this project required that laboratory results for the SRM 

samples be within 30 percent of the certified NIST values, with no more than 35 percent of the 

congener recoveries exceeding this criterion. When these data were validated as part of the 

original project, the validator applied a more stringent acceptance limit of 20%. The SRM 

results were all within 15 percent of the certified values. 

Precision: Internal laboratory precision for the samples was assessed by evaluating the results 

from the two laboratory duplicate pairs analyzed by the laboratory working for USEPA. Among 

duplicate pairs for which both the sample and duplicate result each exceeded 5 times their 

SSQLs, all but 30 PCB congeners in one of the pairs (12.7% of the 236 congener pairs) where 

less than 40%. The overall pooled RPD for pairs with results exceeding 5 times the SSQL was 

27.1%. 

Quality Review of CPG QC Samples: 

Although not a requirement of Method 1668A, the laboratory performing the CPG sample 

analyses analyzed MS and MSD samples as part of the Lower Passaic River project. These data 

were used to assess the bias and precision of the method, and the results are described below. 
Engineering and Analysis Division Brian Englert 

Office of Science and Technology 202-566-0754 

04/15/2010 

Bias: Results from 33 MS/MSD pairs were reported for a subset of the PCB congeners. Mean 

MS/MSD recoveries were calculated for each congener. An MS/MSD pair was included in this 

calculation only if the spike level exceeded the concentration measured in the background 

sample. While pairs for which this was not the case would tend to have worse recoveries, this 

was due to the inappropriateness of the spike level for assessing bias, rather than a method 

performance issue. 

A total of 1,240 MS or MSD recoveries were calculated for native PCB congeners. Mean 

recoveries of the native congeners ranged between 90% and 124%, with an overall mean of 

105%. Only 4.7% of these MS or MSD recoveries fell outside the 70-130% bound that was used 

to assess the SRM results. Recoveries were more likely to fall outside this window for 

congeners in chlorination levels 8-10. 

Precision: Precision was assessed by calculating the RPD of the matrix spike and matrix spike 

duplicate result for each pair. RPDs were then summarized by congener, and across all 

congeners. Congener-specific pooled RPDs ranged between 4.2% and 22.6%, with an overall 

pooled RPD of 13.9%. Among the 859 pairs, only six duplicate pairs (most for congeners 206 

and 208) yielded RPDs exceeding 40%. 

References: 

 

1

 Split refers to government oversight split samples (referred to as “USEPA split samples”) which were collected 

from 4 percent of the CPG samples, yielding 30 split samples plus two field duplicates. The purpose of the split 

sample program was to provide an independent analytical dataset that can be compared to the CPG samples to 

investigate precision, accuracy, and potential bias. 2

 Statistical Comparison of 2008 Low Resolution Split Sample Sediment Data. Lower Passaic River Restoration 

Project. W912DQ-08-D-0017, Task Order 0010. Malcolm Pirnie. October 5th, 2009. 3

 Quality Review of CPG 2008 Low Resolution Sediment Coring Data. Lower Passaic River Restoration Project. 

W912DQ-08-D-0017, Task Order 0010. Malcolm Pirnie. September 23, 2009.