Temperature-dependence of soil/air partition coefficient for polychlorinated biphenyls at subzero temperatures

He, Xin; Chen, Shuo; Quan, Xie; Liu, Zhenyu; Zhao, Yongjie

doi:10.1016/j.chemosphere.2009.09.001

Cited by 9 publications

(8 citation statements)

References 28 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…OCs showed more scattering than the PCBs since PCBs have similar structures, while structures among the OCs are more diverse. He et al , reported the modeled K SA was greater that those measured experimentally for PAHs, PCBs, and OCs, and the difference was less than 1 order of magnitude. A soil-air flux chamber study showed the fugacity calculations based on the Karickhoff model underestimated the volatilization of PCBs and OCs, particularly for the HMW chemicals and in high organic carbon soils .…”

Section: Resultsmentioning

confidence: 90%

“…The dimensionless soil-air partition coefficient ( K SA = C SOILS /C AIR ) has been conventionally estimated by the modified Karickhoff model , K SA = 0.411 ρ s ϕ oc K OA where ϕ oc is the fraction of soil organic carbon, ρ S is soil density (kg L −1 ), K OA is the octanol-air partition coefficient, and 0.411 is a constant with units of L kg −1 . Over the years, there have been many studies carried out to directly measure K SA under various environmental conditions − . Hippelein and McLachlan reported that the above model systematically underestimated the measured K SA by a factor of 2 for polychlorinated biphenyls (PCBs) and chlorobenzenes.…”

Section: Introductionmentioning

confidence: 99%

“…Hippelein and McLachlan reported that the above model systematically underestimated the measured K SA by a factor of 2 for polychlorinated biphenyls (PCBs) and chlorobenzenes. Other studies have shown differences up to an order-of-magnitude between experimental and predicted K SA for organochlorine pesticides (OCs), polyaromatic hydrocarbons (PAHs), and PCBs ,,, . Niederer et al found that the partition coefficient of a chemical between natural organic matter/air was highly variable and showed up to an order of magnitude difference depending on the source of the humic and fulvic acids (such as terrestrial vs aquatic).…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Aging of Organochlorine Pesticides and Polychlorinated Biphenyls in Muck Soil: Volatilization, Bioaccessibility, and Degradation

Wong

Bidleman

2011

Environ. Sci. Technol.

View full text Add to dashboard Cite

An organic rich muck soil which is highly contaminated with native organochlorine pesticide (OCs) was spiked with known amounts of (13)C-labeled OCs and nonlabeled polychlorinated biphenyls (PCBs). Spiked soils were aged under indoor, outdoor, and sterile conditions and the change in volatility, surrogate bioaccessibility, and degradation of chemicals was monitored periodically over 730 d. Volatility was measured using a fugacity meter to characterize the soil-air partition coefficient (K(SA) = C(SOIL)/C(AIR)). The fraction of bioaccessible residues was estimated by comparing recoveries of chemical with a mild extractant, hydroxylpropyl-β-cyclodextrin (HPCD) vs a harsh extractant, DCM. K(SA) of the spiked OCs in the nonsterile (Indoor, Outdoor) soils were initially lower and approached the K(SA) of native OCs over time, showing reduction of volatility upon aging. HPCD extractability of spiked OCs and PCBs were negatively correlated with K(SA), which suggests that volatility can be used as a surrogate for bioaccessibility. Degradation of endosulfans, PCB 8 and 28 was observed in the nonsterile soils, and (13)C(6)-α-HCH showed selective degradation of the (+) enantiomer. Enantiomer fractions (EF) in air and HPCD extracts were lower than in nonsterile soils, suggesting greater sequestering of the (+) enantiomer in the soil during microbial degradation.

show abstract

Section: Resultsmentioning

confidence: 90%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Aging of Organochlorine Pesticides and Polychlorinated Biphenyls in Muck Soil: Volatilization, Bioaccessibility, and Degradation

Wong

Bidleman

2011

Environ. Sci. Technol.

View full text Add to dashboard Cite

show abstract

“…K, however, is different: for a secondary source, K indicates the ratio of PCB concentration in the primary source to the concentration in the layer of adjacent building material in contact with the primary source, while for a tertiary source, K indicates the ratio of PCB concentration in air close to the material surface to the concentration in the surface of the material. Guo et al 16 and Liu et al 17 22,23 and airborne particles. 24−26 The objectives of this study were therefore (1) to develop a new linear-regression based method (named as C-depth method) that would overcome the aforementioned limitations to determine the diffusion coefficient and partition coefficient of PCBs in building materials acting as secondary sources; (2) to examine the sensitivity of the obtained parameters D and K on the following input parameters for the C-depth method: effective diffusion distance in building materials, contact time with primary sources, depth of measured concentration, and measured PCB concentrations.…”

Section: Introductionmentioning

confidence: 99%

“…Furthermore, to avoid unstable results from the data fitting, exponential correlations for D and K among PCB congeners should be assumed, and the value of one of the exponential power parameters needs to be known as input. As far as the authors know, the papers by Guo et al and Liu et al are the only work to examine these two key parameters of PCBs in building materials, while most previous efforts focus on diffusion and/or partition in sediment, − soil, , and airborne particles. − …”

Section: Introductionmentioning

confidence: 99%

C-Depth Method to Determine Diffusion Coefficient and Partition Coefficient of PCB in Building Materials

Liu

Kolařík

Gunnarsen

et al. 2015

Environ. Sci. Technol.

View full text Add to dashboard Cite

Polychlorinated biphenyls (PCBs) have been found to be persistent in the environment and possibly harmful. Many buildings are characterized with high PCB concentrations. Knowledge about partitioning between primary sources and building materials is critical for exposure assessment and practical remediation of PCB contamination. This study develops a C-depth method to determine diffusion coefficient (D) and partition coefficient (K), two key parameters governing the partitioning process. For concrete, a primary material studied here, relative standard deviations of results among five data sets are 5%-22% for K and 42-66% for D. Compared with existing methods, C-depth method overcomes the inability to obtain unique estimation for nonlinear regression and does not require assumed correlations for D and K among congeners. Comparison with a more sophisticated two-term approach implies significant uncertainty for D, and smaller uncertainty for K. However, considering uncertainties associated with sampling and chemical analysis, and impact of environmental factors, the results are acceptable for engineering applications. This was supported by good agreement between model prediction and measurement. Sensitivity analysis indicated that effective diffusion distance, contacting time of materials with primary sources, and depth of measured concentrations are critical for determining D, and PCB concentration in primary sources is critical for K.

show abstract

Theoretical predictions of thermodynamic parameters of adsorption of nitrogen containing environmental contaminants on kaolinite

Scott

Burns²,

Lafferty

et al. 2015

J Mol Model

View full text Add to dashboard Cite

In this study thermodynamic parameters of adsorption of nitrogen containing environmental contaminants (NCCs, 2,4,6, trinitrotoluene (TNT), 2,4-dinitrotoluene (DNT), 2,4-dinitroanisole (DNAN), and 3-one-1,2,4-triazol-5-one (NTO)) interacting with the tetrahedral and octahedral surfaces of kaolinite were predicted. Adsorption complexes were investigated using a density functional theory and both periodic and cluster approach. The complexes, modeled using the periodic boundary conditions approach, were fully optimized at the BLYP-D2 level to obtain the structures and adsorption energies. The relaxed kaolinite-NCCs structures were used to prepare cluster models to calculate thermodynamic parameters and partition coefficients at the M06-2X-D3 and BLYP-D2 levels from the gas phase. The entropy effect on the Gibbs free energies of adsorption of NCCS on kaolinite was also studied and compared with available experimental data. The results showed that in all calculated models, the NCCs molecules are physisorbed and they favor a parallel orientation toward both kaolinite surfaces. It was found that all calculated NCCs compounds are more stable on the octahedral than on the tetrahedral surface of kaolinite. The Gibbs free energies and partition coefficients were also predicted for interactions of NCCs with Na-kaolinite from aqueous solution. Calculations revealed adsorption of NCCs is effective from the gas phase on both cation free kaolinite surfaces and on Na-kaolinite from aqueous solution at room temperature. Theoretical data were validated against experimental results, and the reasons for small differences between calculated and measured partition coefficients are discussed.

show abstract

Temperature-dependence of soil/air partition coefficient for polychlorinated biphenyls at subzero temperatures

Cited by 9 publications

References 28 publications

Aging of Organochlorine Pesticides and Polychlorinated Biphenyls in Muck Soil: Volatilization, Bioaccessibility, and Degradation

Aging of Organochlorine Pesticides and Polychlorinated Biphenyls in Muck Soil: Volatilization, Bioaccessibility, and Degradation

C-Depth Method to Determine Diffusion Coefficient and Partition Coefficient of PCB in Building Materials

Theoretical predictions of thermodynamic parameters of adsorption of nitrogen containing environmental contaminants on kaolinite

Contact Info

Product

Resources

About