Challenges in the Analyses of Organophosphate ... - ACS Publications

May 23, 2017 - Wellington Laboratories Inc., 345 Southgate Drive, Guelph, Ontario N1G 3M5, Canada ..... retardants in furniture foam and U.S. house du...
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Letter pubs.acs.org/journal/estlcu

Challenges in the Analyses of Organophosphate Esters William A. Stubbings,† Nicole Riddell,‡ Brock Chittim,‡ and Marta Venier*,† †

School of Public and Environmental Affairs, Indiana University, Bloomington, Indiana 47405, United States Wellington Laboratories Inc., 345 Southgate Drive, Guelph, Ontario N1G 3M5, Canada



S Supporting Information *

ABSTRACT: Organophosphate esters (OPEs) have been subject to considerable scientific and public scrutiny in recent years. The combination of their physicochemical characteristics and lack of standard analytical methods has resulted in growing concerns with respect to the validity of OPE concentrations reported in the literature. The goal of this study was to address the analytical challenges in analyses of OPEs by comparing the precision and accuracy of data generated for individual target analytes by different laboratories. Eleven international research laboratories were recruited in this study, and a total of 16 OPEs, chosen among the most frequently reported ones, were targeted. Results demonstrate the participating laboratories had generally good to very good consistency for the suite of OPEs analyzed, but accuracy was found to be a problem for several OPEs and laboratories. Methods utilized for the quantification of tri-m-tolyl phosphate, tri-p-tolyl phosphate, and tris(2butoxyethyl) phosphate performed worst overall, as highlighted by their zeta-scores, suggesting that interpretation and comparison of results for these OPEs should be made with caution and that current analytical methods may need to be improved. Liquid chromatography and tandem mass spectrometry performed best for both precision and accuracy.



INTRODUCTION Organophosphate esters (OPEs) make up a group of phosphoric acid esters that have been in use as flame retardant (FR) chemicals for more than 150 years.1 OPEs have been applied to a wide range of commercial products such as textiles, rubber, polyurethane foam (PUF), cellulose, cotton, electronic equipment cables, casting resins, glues, engineering thermoplastics, epoxy resins, and phenolic resins to comply with fire safety codes, standards, and regulations.2 Ubiquitous contamination of indoor air and dust, gaseous and particulate outdoor air phases, lakes, river sediment, and lacustrine and marine biota is globally well-documented.3−11 Studies of the toxicity of OPEs are still somewhat limited, but a growing body of evidence indicates that several OPEs are toxic,12,13 carcinogenic, or potentially carcinogenic.14−18 These concerns over the health implications of OPEs combined with the ubiquitous nature of these compounds have meant that OPEs are widely considered chemicals of interest with potential to affect both public and environmental health. Globally, a significant number of laboratories have developed methods to measure OPEs in various matrices, but the reliability and reproducibility of the reported measurements between laboratories remain undetermined. The aims of this interlaboratory study were to evaluate the quality of submitted participant data (and hence their performance), to improve data quality by supplying feedback to the participants, and to identify precautionary measures that could improve the reliability and quality of OPE analyses. © XXXX American Chemical Society

Because OPEs have received a growing level of attention from researchers over the past few years, ensuring reliable measurements is not only crucial but also urgent, especially if the data are used to determine exposure levels and associated risks.



METHODS

Eleven participating laboratories were asked to analyze 16 OPEs (10 alkyl phosphates and 6 aryl phosphates) combined into two injection ready solutions representing low and high concentrations of the target analytes that were prepared and tested by Wellington Laboratories Inc. (Table S1). All solutions were produced using a Quality Management System registered to the latest versions of ISO 9001, ISO/IEC 17025, and ISO Guide 34. NIST-traceable Class A volumetric glassware was used to prepare test mixtures from gravimetrically (w/v) prepared stock solutions through the dissolution of an accurately weighed mass of each OPE into toluene. The balances utilized for solution preparation can be traced to an external ISO 17025:2005 accredited laboratory, and the calibration was verified prior to each weighing using traceable external weights. All of the laboratories involved in this study had previously established methods for OPE analysis and are Received: May 19, 2017 Accepted: May 23, 2017

A

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Repeatability Limit, r. This parameter indicates the relative percent variation expected for a given analyte (i.e., r should have a deviation lower than that of repeated analyses by 95% of laboratories). The value of r is calculated as follows:

currently involved in the analysis of OPEs in environmental matrices. Glass ampules containing 1.2 mL aliquots of each test mixture were shared with participants. Approximate concentration ranges for each target analyte were provided (Table S1). The samples were analyzed using routinely applied and validated procedures, independently developed by each laboratory. If any target OPEs were not included in a laboratory’s established suite of analytes, they could choose to omit them from the analysis and/or report. Participating laboratories were asked to determine each test mixture in three independent replicates, report results individually in nanograms per milliliter, and provide details about the instrumentation and analytical methods used (Table S2).

r = 2.8sr*

where sr* is the repeatability standard deviation for a particular analyte, excluding outliers. Outlier analysis was performed using Grubbs tests on logarithmically transformed data for each analyte at both concentration levels. No significant outliers were observed at a p = 0.01 significance level. To derive the percent variability that can be expected for repeated measurements of a particular analyte under consistent conditions, r was divided by the average concentration reported by all laboratories and multiplied by 100, yielding the relative repeatability limit. Percentage Bias. The percentage bias (% bias) provides a measure of the disparity between the known reference value and the mean reported value. The value of % bias is



STATISTICAL ANALYSES Statistical analyses were performed using either IBM SPSS Statistics 24 or Microsoft Excel 2013. Laboratories have been assigned alphanumeric codes to protect their anonymity. The results of a Shapiro−Wilk W test showed that the data were not normally distributed, and the data were logarithmically transformed before performing one-way analyses of variance (ANOVAs). The interlaboratory comparison results were evaluated using the following statistical equations as described in detail by Melymuk et al.19 Repeatability Standard Deviation (sr). The repeatability standard deviation represents the minimum variability to be expected in the measurement of a specific analyte. The value of sr is

% bias =

p

ζ=

s sr

p p−1 F

u X̅ 2 + uRV 2

(6)

RESULTS AND DISCUSSION Overview. Compound abbreviations are listed in Table 1. Only five laboratories reported values for all 16 target OPEs (Table S1). The least frequently reported OPEs included in the test mixtures were tri-m-tolyl phosphate (TMTP) and tri-ptolyl phosphate (TPTP) (seven laboratories each) and tris(2,3dibromopropyl) phosphate (TDBPP) (eight laboratories). Of the 11 participating laboratories, five measured OPEs using gas chromatography and mass spectrometry (GC−MS), two using GC−MS/MS, and four using liquid chromatography−MS/MS (Table S2). The best performances for both accuracy and precision were by laboratories using LC−MS/MS (laboratories H−K). The relatively poorer performance of laboratory I, in comparison to those of laboratories H, J, and K, is likely due to the choice of the LC column. Laboratory I used a column with a larger particle size and a longer length than the columns used by the other LC−MS/MS laboratories in this study. Via selection of a smaller particle diameter, both an increase in the efficiency of the column (plate height reduction) and an increase in the optimal linear velocity at which the minimal plate height can be attained are obtained. Increasing the flow rate can achieve more efficient peak separations, a reduction in analysis time, and potentially an increase in resolution. Shorter diffusion paths

(2)

1+

X̅ − RV



If the variability of a laboratory’s reported triplicates is greater than the average for all other laboratories, then k > 1. To better evaluate this parameter, k values are often compared with a critical k value at a p = 0.05 significance level. The value of critical k is calculated as follows: kcrit =

(5)

where u X̅ is the uncertainty in the laboratory result, which in this study is represented through laboratory standard deviation, and uRV is the uncertainty in the reference value (±5%; calculated as the expanded maximum combined percent relative uncertainty associated with solution preparation with a coverage factor of 2 and a level of confidence of 95%).

(1)

where s is the standard deviation of the triplicate measurements for an analyte from a given laboratory and p is the number of laboratories that reported measuring the analyte. The parameter sr was then divided by the average concentration reported by all laboratories and multiplied by 100, yielding the relative repeatability standard deviation, expressed as the percentage variability achieved by repeated measurements of a specific analyte. This facilitated comparison of the two test mixture concentration ranges. Within-Laboratory Consistency Statistic (k). To evaluate the consistency in each laboratory’s triplicate tests for each analyte relative to all other laboratories, we calculated k as follows

k=

X̅ − RV × 100 RV

where RV is the reference value and X̅ is the mean reported value. ζ-Score. The ζ-score (zeta-score) is a comprehensive measure of the overall performance of a laboratory because it incorporates precision and accuracy. The ζ-score is calculated with the following expression:

p ∑1 s 2

sr =

(4)

(3)

where F is the F ratio at a p = 0.05 significance level. Poor within-laboratory consistency is indicated by k > kcrit (i.e., a laboratory has a significantly critical k parameter for a particular analyte). B

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significant differences were observed between the GC−MS and GC−MS/MS methods, but there were significant differences between the GC−MS and LC−MS/MS results. While there was not a significant difference at the 95% confidence level between the GC−MS/MS and LC−MS/MS methods (p = 0.112), the p value was considerably lower than that observed between the GC−MS and GC−MS/MS methods (p = 0.793), giving the following tentative order: GC−MS = GC−MS/MS < LC−MS/MS. This analysis suggests that the GC−MS method is not the preferred method for use for the measurement of both OPE groups at low concentrations. GC−MS/MS and LC−MS/MS methods are more suitable. At high concentrations, significant differences were observed among all instruments for both the alkyl and the aryl OPEs (groups a and b, respectively). By using the assessments of accuracy, it is possible to derive orders of instrument performance: GC−MS < GC−MS/MS < LC−MS/MS. The LC−MS/MS method outperformed both GC−MS and GC− MS/MS methods. At high concentrations, the LC−MS/MS method provides the best performance. Assessment of Precision. The relative repeatability standard deviation percentage for all analytes was in the range of 2.6−11% for the low-concentration samples and 1.8− 5.5% for the high-concentration samples (Figure S1). Of particular note was TDMPP, with 11 and 5.5% relative standard deviations in the low- and high-concentration samples, respectively. This indicates that the repeatability of measuring this OPE is the most challenging, resulting in a higher variability in the literature. A higher level of caution should be used when comparing TDMPP results obtained from different laboratories. TCEP had the lowest relative standard deviations for the low-concentration samples (2.6%), while for the highconcentration samples, TMTP and TPTP performed best with 2.2 and 1.8%, respectively. The participating laboratories had generally good to very good consistency for the suite of OPEs analyzed. Only one laboratory exceeded the kcrit for target analytes (lab 4). The within-laboratory consistency statistics and frequency of cases for which k > kcrit for all target analytes and laboratories can be found in Tables S4−S6, and the laboratory means are given in Figure S2. The relative repeatability limits for each analyte are reported in Table S7. The relative repeatability limits are used to assess the normal variability for repeated analyses of an analyte when using similar conditions. TOTP and TDMPP had repeatability that was significantly poorer than those of other target OPEs for the low concentrations, while the same was true for TPhP and TOTP at the high concentrations. Assessment of Accuracy. Figure 1 shows the distributions, means, and reference values for both test solutions analyzed by the 11 laboratories (see Figure S3 for details). Of particular note were differences between the reference value and laboratory means for TCEP, TBOEP, TOTP, and TDBPP. The tightest boxes, and hence the best overall accuracy, were observed for TPrP, TnBP, EHDP, TDCIPP, TMTP, and TDMPP at low concentrations and TEP, TPhP, TMTP, TDMPP, and TIPPP at high concentrations. We calculated the percentage bias for the analyte concentration averaged from all 11 laboratories, further quantifying the differences between the laboratory-reported means and the reference values (Figure S4). Overall, the analytes with the highest mean absolute percentage bias and therefore poorest accuracy among laboratories were TOTP and

Table 1. Target Analytes for Interlaboratory Comparison analyte triethyl phosphate tri-n-propyl phosphate tri-n-butyl phosphate tris(2-butoxyethyl) phosphate 2-ethylhexyl diphenyl phosphate tris(2-ethylhexyl) phosphate tris(2-chloroethyl) phosphate tris[(2R)-1-chloro-2propyl] phosphate tris(1,3-dichloro-2propyl) phosphate tris(2,3dibromopropyl) phosphate triphenyl phosphate tri-o-tolyl phosphate tri-m-tolyl phosphate tri-p-tolyl phosphate tris(3,5dimethylphenyl) phosphate tris(2isopropylphenyl) phosphate

abbreviation (alternate abbreviation)

chemical formula

CAS Registry Number

TEP TnPP (TPrP)

C6H15O4P C9H21O4P

78-40-0 513-08-6

TnBP (TBP) TBOEP (TBEP)

C12H27O4P C18H39O7P

126-73-8 78-51-3

EHDP

C20H27O4P

1241-94-7

TEHP

C24H51O4P

78-42-2

TCEP

C6H12Cl3O4P

115-96-8

TCIPP (TCPP)

C9H18Cl3O4P

13674-84-5

TDCIPP (TDCPP) TDBPP

C9H15Cl6O4P

13674-87-8

C9H15Br6O4P

126-72-7

TPhP (TPP) TOTP TMTP TPTP TDMPP (T35DMPP)

C18H15O4P C21H21O4P C21H21O4P C21H21O4P C24H27O4P

115-86-6 78-30-8 563-04-2 78-32-0 25653-16-1

TIPPP (T2IPPP)

C27H33O4P

64532-95-2

and, hence, increased mass transfer kinetics are one reason for this increased efficiency. Using a longer column length will not enhance the resolution sufficiently. Laboratories that reported using GC−MS and GC−MS/MS mostly used DB-5MS columns (Agilent Technologies Inc., Santa Clara, CA), with one laboratory using a similar phase Rxi 5Sil MS column (Restek Corp., Bellefonte, PA). One laboratory reported using a RTX OPPEST (Restek Corp.) column and another a HT-8 (Trajan Scientific and Medical, Victoria, Australia) column. It is worth noting that these latter two columns did not perform any better than the DB-5MS column. GC column lengths ranged from 15 to 60 m, with 30 m being the most common length used with electron impact ionization (EI) instruments, while 15 m columns were used with electron capture negative ion (ECNI) instruments. The results of the ANOVAs with post hoc Tukey tests looking for differences in the means among the three methods are listed in Table S3. To better differentiate between their respective performances between the methods used, the target analytes were separated into two groups before the ANOVAs were performed: (a) alkyl phosphates (TEP, TnPP, TnBP, TBOEP, EHDP, TEHP, TCEP, TCIPP, TDCIPP, and TDBPP) and (b) aryl phosphates (TPhP, TOTP, TMTP, TPTP, TDMPP, and TIPPP). At low concentrations, significant differences (p = 0.05) were observed for the alkyl OPEs (group a) between GC−MS and both the GC−MS/MS and LC−MS/MS methods; however, no significant differences were observed between the GC−MS/MS and LC−MS/MS methods. This suggests that GC−MS/MS and LC−MS/MS performed equally well and an order of method performance can be derived: GC−MS < GC−MS/MS = LC−MS/MS. For the aryl OPEs (group b), however, no C

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Figure 1. Comparison of the mean of laboratory measurements (red bars) and actual test mixture reference values (colored circles) for lowand high-concentration test mixtures. The median is the black bar inside the box. The colored boxes indicate the 25th to 75th percentiles, and the whiskers indicate the 10th and 90th percentiles.

Figure 2. Overall laboratory and overall analyte performance represented by absolute ζ-scores. Green indicates the percentage of analytes with ζ-scores of 3 (critical/unacceptable). Black crosses show the mean absolute ζ-scores (right y-axis).

TMTP (both 10.3%), TBOEP (18%), and TPhP (21%) for the low-concentration test mixture and TOTP and TPhP (both 9.0%), TnBP (9.2%), and TMTP (14%) for the highconcentration test mixture As seen in previous interlaboratory studies,18,19 laboratory performance appears to be poorer for the analyses of compounds in the lower range, which is probably due to low concentrations being closer to the detection limits. Two laboratories had poor accuracy for 50% of the analytes, and three laboratories had poor accuracy for 35−49% of the analyzed OPEs in the low-concentration test mixture (Table S8). However, for the high-concentration solution, only one laboratory demonstrated poor accuracy for half of the compounds, while the other 10 laboratories had good accuracy for >83% of the analyzed OPEs, with six laboratories having no values exceed the 25% threshold. Overall Ranking of Analytes, Laboratories, and Methods. ζ-scores (zeta-scores) can be used to evaluate the overall performance of both for the analytes and the laboratories, supplementing information obtained from precision and accuracy. The ζ-score combines the standard uncertainty of the reference value and the uncertainty of the laboratory result. Scores of 3 indicate critical performance. Tables S9 and S10 provide the ζ-scores for all analytes and laboratories, and Figure 2 gives the ζ-scores by laboratory and analyte. Eight of the 11 participating laboratories had at least some critical ζ-scores, suggesting that in general most laboratories

need to improve their analytical methods for OPE analyses. The target analytes with the worst performance were TBOEP, TMTP, and TPTP, which also performed poorly in accuracy tests. However, TBOEP, TMTP, and TPTP performed well for precision, indicating poor trueness for these OPEs and the necessity to improve the analytical methodology. Most laboratories had a larger number of critical scores for the low-concentration test mixture, averaging 4.5 analytes compared to just 4.1 for the high-concentration test mixture. Some laboratories showed a disparity in their scores for the two solutions, which might due to issues at either end of the calibration curve. ζ-scores by analyte reveal that a number of OPEs performed poorly and warrant caution in their quantification; in particular, TBOEP was difficult to measure correctly. All target analytes had some critical ζ-scores (>3), confirming that OPE analyses can be challenging. Nine of the 16 analytes had only a few scores of >2 (TEP, TPrP, TnBP, EHDP, TCIPP, TDCIPP, TPTP, TDMPP, and TIPPP), suggesting that published results for these compounds are reliable. TBOEP had both the highest mean ζ-score (5.2) and the third highest number of critical scores (45%). Additionally, ζ-scores were evaluated for the three methods used by laboratories in OPE analyses (Figure S6). A key result D

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ACKNOWLEDGMENTS The following laboratories kindly participated in this study: the Canada Centre for Inland Waters (CCIW, Burlington, Canada); Duke University (Durham, USA); the Hazardous Air Pollutants Laboratory (Environment and Climate Change Canada, Toronto, Canada); the Organic Contaminants Research Laboratory (OCRL, Ottawa, Canada); the Organic Analysis Laboratory (OAL, Toronto, Canada); RECETOX (Masaryk University, Brno, Czech Republic); Southern Illinois University (Carbondale, USA); the University of Antwerp, (Antwerp, Belgium); Environmental Organic Chemistry Laboratory at School of Public Health, University of Illinois at Chicago (Chicago, USA); and the University of Toronto (Toronto, Canada). We are very grateful to the staff at Wellington Laboratories Inc. for supplying test mixtures to all participating laboratories. We are grateful to Prof. Ron Hites for helpful discussions.

is that LC−MS/MS had not only the highest average percentage of satisfactory scores for both low and high concentrations (82 and 82%, respectively) but also the lowest mean ζ-scores for each (1.2 and 1.3, respectively), suggesting that LC−MS/MS performance in analyzing OPEs is optimal. The difference between GC−MS and GC−MS/MS was narrow, with GC−MS/MS attaining lower overall mean ζscores for low concentrations. However, GC−MS/MS achieved 59% critical scores for both the low and high concentrations compared to just 42 and 49%, respectively, for the GC−MS method. Nonetheless, care should be taken when interpreting these results as only two laboratories used GC−MS/MS in their analysis and perhaps these results are not entirely representative of the method’s capabilities. In this interlaboratory study, TDCIPP was more often correctly measured for low-concentration test mixtures than those reported in the INTERFLAB study for “novel flame retardants” (NFRs).19 Overall absolute ζ-scores for TDCIPP were greatly improved with 73% of laboratory scores within the satisfactory range, compared to just 30% of laboratory scores in the INTERFLAB study. This suggests that recommended improvements to the analyses of this compound have been adopted by laboratories and that enhancements to analytical methodologies have been realized. The correct measurement of TBOEP was slightly improved in this current OPE study compared to that of the INTERFLAB study, with 40% of laboratories reporting satisfactory overall absolute ζ-scores, however, scoring a slightly higher overall mean ζ-score of 5.2, compared to 5 in the NFR study. It is worth noting that the alternative use of GC−ECNI-MS (electron capture negative ion mass spectrometry) for the determination of TDCIPP did not improve the accuracy of the reported results and actually yielded a poorer performance compared to those of laboratories using GC−EI-MS. Similarly, the use of GC−ECNI-MS for the determination of TDBPP did not appear to offer any significant improvement. This interlaboratory study showed that the analysis of OPEs presents some analytical challenges that need to be evaluated. Laboratories should critically evaluate their performance and, if needed, improve their analytical methods at both high and low concentrations. When possible, the LC−MS/MS method is the preferred choice for performing OPE analyses. Our results also suggest that the interpretation of reported concentrations of some OPE data should be made with caution, particularly for TBOEP, TCEP, and TDBPP.





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ASSOCIATED CONTENT

S Supporting Information *

The Supporting Information is available free of charge on the ACS Publications website at DOI: 10.1021/acs.estlett.7b00195.



Letter

Tables S1−S10 and Figures S1−S6 as mentioned in the text (PDF)

AUTHOR INFORMATION

Corresponding Author

*E-mail: [email protected]. Telephone: 1-812-855-1005. ORCID

Marta Venier: 0000-0002-2089-8992 Notes

The authors declare no competing financial interest. E

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Environmental Science & Technology Letters (14) Chemicals Known to the State to Cause Cancer or Reproductive Toxicity. OEHHA. California Environmental Protection Agency: Sacramento, CA, 2011, https://oehha.ca.gov/media/ downloads/proposition-65//p65single01272017.pdf (accessed March 13, 2017). (15) Ni, Y.; Kumagai, K.; Yanagisawa, Y. Measuring emissions of organophosphate flame retardants using a passive flux sampler. Atmos. Environ. 2007, 41, 3235−3240. (16) List of Toxic Substances Managed Under CEPA (Schedule 1). Environment and Climate Change Canada: Gatineau, QC, 2016. (17) Tris (2-chloro-1-chloromethyl)ethyl) Phosphate (TDCP) Final Risk Assessment. European Union Risk Assessment Report; 2008, https://echa.europa.eu/documents/10162/13630/trd_rar_ireland_ tdcp_en.pdf (accessed December 20, 2016). (18) Brandsma, S. H.; de Boer, J.; Cofino, W. P.; Covaci, A.; Leonards, P. E. G. Organophosphorus flame-retardant and plasticizer analysis, including recommendations from the first worldwide interlaboratory study. TrAC, Trends Anal. Chem. 2013, 43, 217−228. (19) Melymuk, L.; Goosey, E.; Riddell, N.; Diamond, M. L. Interlaboratory study of novel halogenated flame retardants: INTERFLAB. Anal. Bioanal. Chem. 2015, 407, 6759−6769.

F

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