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Transcript of Receptor Models for PAH Source Characterisation: Opportunities and Limitations Development of this...
Receptor Models for PAH Source Characterisation: Opportunities and Limitations
Development of this presentation was supported by the Pavement Coatings Technology Council
Stephen Mudge, Kirk O’Reilly, Sungwoo Ahn, Jaana Pietari and Paul Boehm
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Receptor Models
Receptor models are mathematical or statistical procedures for characterising potential sources and quantifying their contribution to the chemicals found at receptor location.
Larson ©
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Receptor Models
Mixing Models– Example: EPA Chemical Mass Balance (CMB)
Modeller pre-identifies sources and inputs profiles Model calculates best fit to the receptor (sediment)
data to estimate relative contributions Unmixing Models– Example: PVA
Model uses receptor data to identify potential source profiles
Model calculates best fit to the receptor data to estimate relative contributions
Modeller compares identified source profiles to potential sources
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Case Study: Use of CMB to Evaluate of the Role of Refined Tar Pavement Sealers (RTS) in Urban Lake Sediments
USGS researchers used CMB to test the hypothesis that RTS is a significant PAH source (Van Metre and Mahler, 2010)
Results being used to advocate product bans
Lack of negative controls limited value for hypothesis testinghttp://water.usgs.gov/nawqa/home_maps/sealcoat.html
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Similarity Between and Variability Within Pyrogenic PAH Source Profiles can Limit Models
Gasoline Residential
Data from Li et al EST 2003
PhA An FlA Py BaA Chy BbF BkF BeP BaP IP BgP0.00
0.05
0.10
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0.35
PhA An FlA Py BaA Chy BbF BkF BeP BaP IP BgP0.00
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PhA An FlA Py BaA Chy BbF BkF BeP BaP IP BgP0.00
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PhA An FlA Py BaA Chy BbF BkF BeP BaP IP BgP0.00
0.02
0.04
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0.08
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0.12
0.14
Traffic Diesel
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Hypothesis Testing Requires a Negative Control
Comparison of three CMB Model runs
– Published Results: Model A from Van Metre et al. 2010. RTS source profile is the mean of dust from six sealed lots.
– Negative Control: Did not include RTS as a source profile. Remaining sources from Van Metre et al. 2010.
– Different RTS Source Profile: Replaced Van Metre RTS with Selbig (2009) mean of 9 RTS lot runoff samples. Remaining sources from Van Metre et al. 2010.
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Excellent Match Between Measured and Modelled Concentrations Without RTS as a Source Input
R2>0.996 for each method
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End Member Compositions
PhA An FlA Py BaA Chy BbF BkF BeP BaP IP BgP0
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PhA An FlA Py BaA Chy BbF BkF BeP BaP IP BgP0
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PhA An FlA Py BaA Chy BbF BkF BeP BaP IP BgP0
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PhA An FlA Py BaA Chy BbF BkF BeP BaP IP BgP0
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Tyres
From Van Metre & Mahler, 2010
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Conclusions
Receptor models can be helpful in determining the sources to a system.
However…– CMB pre-defines the sources in advance.
Changing these changes the outcome.– Need sufficient compounds to distinguish
between source (in all models). Overlap.– Unmixing type models may identify sources that
have yet to be characterised.
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Key References
Mahler, B.J., P.C. Van Metre, T.J. Bashara, J.T. Wilson, and D.A. Johns. 2005. Parking lot sealcoat: An unrecognized source of urban polycyclic aromatic hydrocarbons. Environ. Sci. Technol. 39: 5560-5566.
O’Reilly K, Pietari J, Boehm P. 2012. A forensic assessment of coal tar sealants as a source of polycyclic aromatic hydrocarbons in urban sediments. Environ Forensics 13:185-196.
O’Reilly K, Pietari J, Boehm P. 2013. Parsing Pyrogenic PAHs: Forensic Chemistry, Receptor Models, and Source Control Policy. Integrated Environ Assessment and Management, in press
O’Reilly, K, Ahn, S. in prep. Polycyclic Aromatic Hydrocarbon Source Contribution Modeling: Negative Controls and Source Profile Collinearity.
Van Metre PC, Mahler BJ, Wilson JT. 2009. PAHs underfoot: Contaminated dust from coal-tar seal coated pavement is widespread in the United States. Environ Sci Technol 43(1):20‑25.
Van Metre PC, Mahler BJ. 2010. Contribution of PAHs from coal–tar pavement sealcoat and other sources to 40 U.S. lakes. Sci Tot Environ 409:334-344.