title: Improving predictability of sediment-porewater partitioning models using trends observed with PCB-contaminated field sediments.
abstract: More than 1900 sediment-water partitioning coefficients were measured for 58 polychlorinated biphenyl (PCB) congeners in 53 historically contaminated sediments collected from 10 urban and rural waterways in the United States and Canada. Freely dissolved porewater concentrations were determined using passive sampling with polyoxymethylene. Measured total organic carbon (TOC)/water partitioning coefficients, K(TOC), ranged from one to nearly three orders-of-magnitude higher than typical literature values based on spiking experiments and model predictions. Although total PCB concentrations ranged from 0.08 to 194 mg/kg, the more highly contaminated sediments showed only slightly lower K(TOC) values than less-contaminated sediments. No correlation was observed between log K(TOC) values and sediment TOC, black carbon (BC), or BC/TOC fractions (r(2) typically <0.1). Utilizing a two-carbon model incorporating anthropogenic BC did not improve predictions over a one-carbon TOC model. A comparison of models recently validated for field data showed that a coal-tar poly parameter linear-free energy relationship (PP-LFER) and a Raoult's Law model were successful at predicting average log K(TOC) values, without the need for any calibration or fitting (within a factor of 10 more than 90% of the time, and within a factor of 30 more than 99% of the time). Predictions were further improved by the introduction of a Weathering Factor (WF) that accounts for the relative depletion of lower molecular weight congeners due to weathering. Highly weathered sediments (with a WF near 1) tended to follow the coal-tar PP-LFER and Raoult's Law model the closest. Less-weathered sediments (with WF ≪ 1) sorbed less than predicted by these models. Noncalibrated WF inclusive coal-tar PP-LFER and Raoult's Law models performed as well or better than a quantitative-structure activity relationship (QSAR) model calibrated specifically to the data. These recommended partitioning models here can readily be used for all 209-PCB congeners.
authors.affiliation: Energy and Environmental Research Center, University of North Dakota, 15 North 23rd Street, Grand Forks, North Dakota 58203, United States. shawthorne@undeerc.org
authors.forename: Steven B
authors.initials: SB
authors.lastname: Hawthorne
authors.forename: Carol B
authors.initials: CB
authors.lastname: Grabanski
authors.forename: David J
authors.initials: DJ
authors.lastname: Miller
authors.forename: Hans Peter H
authors.initials: HP
authors.lastname: Arp
mesh_terms: D002170:Canada; D004784:Environmental Monitoring / Q000379:methods; D019015:Geologic Sediments / Q000737:chemistry*; D006801:Humans; D008962:Models, Theoretical; D011078:Polychlorinated Biphenyls / Q000032:analysis*; D011084:Polycyclic Aromatic Hydrocarbons / Q000032:analysis; D053260:Soot / Q000032:analysis; D014481:United States; D014867:Water / Q000737:chemistry*; D014874:Water Pollutants, Chemical / Q000032:analysis*
chemical_list: D011084:Polycyclic Aromatic Hydrocarbons; D053260:Soot; D014874:Water Pollutants, Chemical; D014867:Water; D011078:Polychlorinated Biphenyls