scholarly journals Coupling Suspect and Nontarget Screening with Mass Balance Modeling to Characterize Organic Micropollutants in the Onondaga Lake–Three Rivers System

2021 ◽  
Author(s):  
Shiru Wang ◽  
MaryGail Perkins ◽  
David A. Matthews ◽  
Teng Zeng
Keyword(s):  
Mass Balance ◽  
Onondaga Lake ◽  
Organic Micropollutants ◽  
Nontarget Screening ◽  
Three Rivers

scholarly journals Stochastic Method for Evaluating Removal, Fate and Associated Uncertainties of Micropollutants in a Stormwater Biofilter at an Annual Scale

Water ◽  
2019 ◽  
Vol 11 (3) ◽  
pp. 487 ◽  
Author(s):  
Kelsey Flanagan ◽  
Philippe Branchu ◽  
Lila Boudahmane ◽  
Emilie Caupos ◽  
Dominique Demare ◽  
...  
Keyword(s):  
Mass Balance ◽  
Uncertainty Propagation ◽  
Construction Materials ◽  
Stochastic Method ◽  
Road Runoff ◽  
Organic Micropollutants ◽  
Rain Events ◽  
Annual Scale ◽  
Ethylhexyl Phthalate

A stochastic method for evaluating the in situ mass balance of micropollutants in a stormwater biofilter, accounting for inlet and outlet loads and the evolution of pollutant mass in the filter media (ΔMsoil) at an annual scale, is proposed. In the field context, this type of calculation presents a number of methodological challenges, associated with estimating water quality for unsampled rain events, reconstituting missing or invalidated flow data and accounting for significant uncertainties associated with these estimations and experimental measurements. The method is applied to a biofiltration swale treating road runoff for two trace metals, Cu and Zn and six organic micropollutants: pyrene (Pyr), phenanthrene (Phen), bisphenol-A (BPA), octylphenol (OP), nonylphenol (NP) and bis(2-ethylhexyl) phthalate (DEHP). Pollutant loads were reduced by 27–72%. While organic micropollutants are likely to be lost to degradation or volatilization processes in such systems, dissipation could not be demonstrated for any of the organic micropollutants studied due to emissions from construction materials (case of BPA, OP, NP and DEHP) or high uncertainties in ΔMsoil (case of Pyr and Phen). The necessary conditions for establishing an in situ mass balance demonstrating dissipation, which include acquisition of data associated with all terms over a period long enough that uncertainty propagation is limited and the absence of additional sources of pollutants in the field, are discussed.

Total mercury and methylmercury mass balance in an alkaline, hypereutrophic urban lake (Onondaga Lake, NY)

1995 ◽  
Vol 80 (1-4) ◽  
pp. 509-517 ◽  
Author(s):  
E. A. Henry ◽  
L. J. Dodge-Murphy ◽  
G. N. Bigham ◽  
S. M. Klein ◽  
C. C. Gilmour
Keyword(s):  
Mass Balance ◽  
Total Mercury ◽  
Onondaga Lake ◽  
Urban Lake

Total Mercury and Methylmercury Mass Balance in an Alkaline, Hypereutrophic Urban Lake (Onondaga Lake, NY)

1995 ◽  
pp. 509-517 ◽  
Author(s):  
E. A. Henry ◽  
L. J. Dodge-Murphy ◽  
G. N. Bigham ◽  
S. M. Klein ◽  
C. C. Gilmour
Keyword(s):  
Mass Balance ◽  
Total Mercury ◽  
Onondaga Lake ◽  
Urban Lake

scholarly journals GC×GC-HRMS nontarget fingerprinting of organic micropollutants in urban freshwater sediments

2020 ◽  
Author(s):  
Josephine Susanne Lübeck ◽  
Guilherme Lionello Alexandrino ◽  
Jan H Christensen
Keyword(s):  
Principal Component ◽  
Dilution Effect ◽  
Retention Indices ◽  
Gas Chromatography Mass Spectrometry ◽  
Organic Micropollutants ◽  
Freshwater Sediments ◽  
Baseline Subtraction ◽  
Urban Sediments ◽  
Weathered Oil ◽  
Nontarget Screening

Abstract Background: Sediments are sinks for organic micropollutants, which are traditionally analysed by gas chromatography-mass spectrometry (GC-MS). Although GC-MS and GC-MS/MS (tandem MS) are preferred for target screening, they provide only limited chromatographic resolution for nontarget screening. In this study, a comprehensive two-dimensional GC-high-resolution MS method (GC×GC-HRMS) was developed for nontarget screening and source identification of organic micropollutants in sediments from an urban channel and adjacent lake in Copenhagen, Denmark. The GC×GC-HRMS data were processed by pixel-based chemometric analysis using baseline subtraction, alignment, normalisation, and scaling before principal component analysis (PCA) of the pre-processed GC×GC-HRMS base peak ion chromatograms (BPCs). The analysis was performed to identify organic micropollutants of high abundance and relevance in the urban sediments and to identify pollution sources. Tentative identifications were based on match factors and retention indices and tagged according to the level of identification confidence. Results: The channel contained both significantly higher concentrations of micropollutants and a higher diversity of compounds compared to the lake. The PCA models were able to isolate distinct sources of chemicals such as a natural input (viz. a high relative abundance of mono-, di- and sesquiterpenes) and a weathered oil fingerprint (viz. alkanes, naphthenes and alkylated polycyclic aromatic hydrocarbons). A dilution effect of the weathered oil fingerprint was observed in lake samples that were close to the channel. Several benzothiazole-like structures were identified in lake samples close to a high-traffic road which could indicate a significant input from asphalt or tire wear particles. In total, 104 compounds and compound groups were identified. Conclusions: Several chemical fingerprints of different sources were described in urban freshwater sediments in Copenhagen using a pixel-based chemometric approach of GC×GC-HRMS BPCs. Various micropollutants of anthropogenic origin were identified. Tailored pre-processing and careful interpretation of the identification results is inevitable and still requires further research for an automated workflow.

scholarly journals GC×GC-HRMS nontarget fingerprinting of organic micropollutants in urban freshwater sediments

2020 ◽  
Author(s):  
Josephine Susanne Lübeck ◽  
Guilherme Lionello Alexandrino ◽  
Jan H Christensen
Keyword(s):  
Principal Component ◽  
Dilution Effect ◽  
Retention Indices ◽  
Gas Chromatography Mass Spectrometry ◽  
Organic Micropollutants ◽  
Freshwater Sediments ◽  
Baseline Subtraction ◽  
Urban Sediments ◽  
Weathered Oil ◽  
Nontarget Screening

Abstract Background Sediments are sinks for organic micropollutants, which are traditionally analysed by gas chromatography-mass spectrometry (GC-MS). Although GC-MS and GC-MS/MS (tandem MS) are preferred for target screening, they provide only limited chromatographic resolution for nontarget screening. In this study, a comprehensive two-dimensional GC-high-resolution MS method (GC×GC-HRMS) was developed for nontarget screening and source identification of organic micropollutants in sediments from an urban lake and channel in Copenhagen, Denmark. The GC×GC-HRMS data were processed by pixel-based chemometric analysis using baseline subtraction, alignment, normalisation, and scaling before principal component analysis (PCA) of the pre-processed GC×GC-HRMS base peak ion chromatograms (BPCs). The analysis was performed to identify organic micropollutants of high abundance and relevance in the urban sediments, to identify pollution sources. Tentative identifications were based on match factors and retention indices and tagged according to the level of identification confidence. Results The channel contained both significantly higher concentrations of micropollutants and a higher diversity of compounds compared to the lake. The PCA models were able to isolate distinct sources of chemicals such as a natural input (viz. a high relative abundance of mono-, di- and sesquiterpenes) and a weathered oil fingerprint (viz. alkanes, naphthenes and alkylated polycyclic aromatic hydrocarbons). A dilution effect of the weathered oil fingerprint was observed in lake samples that were close to the channel. Several benzothiazole-like structures were identified in lake samples close to a high-traffic road which could indicate a significant input from asphalt or tire wear particles. Conclusions Several chemical fingerprints of different sources were described in urban freshwater sediments in Copenhagen using a pixel-based chemometric approach of GC×GC-HRMS chromatograms. Various micropollutants of anthropogenic origin were identified. Tailored pre-processing and careful interpretation of the identification results is inevitable and still requires further research for an automated workflow.

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