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Henry's Law Constants

www.henrys-law.org

Rolf Sander

NEW: Version 5.0.0 has been published in October 2023

Atmospheric Chemistry Division

Max-Planck Institute for Chemistry
Mainz, Germany

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Henry's Law Constants

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References

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When referring to the compilation of Henry's Law Constants, please cite this publication:

R. Sander: Compilation of Henry's law constants (version 5.0.0) for water as solvent, Atmos. Chem. Phys., 23, 10901-12440 (2023), doi:10.5194/acp-23-10901-2023

The publication from 2023 replaces that from 2015, which is now obsolete. Please do not cite the old paper anymore.

Henry's Law Constants → Organic species with oxygen (O) → Ketones (RCOR) → 3-hexanone

FORMULA:C6H12O
CAS RN:589-38-8
STRUCTURE
(FROM NIST):
InChIKey:PFCHFHIRKBAQGU-UHFFFAOYSA-N

Hscp d ln Hs cp / d (1/T) References Type Notes
[mol/(m3Pa)] [K]
7.9×10−2 7100 Brockbank (2013) L
7.5×10−2 Plyasunov and Shock (2001) L
7.6×10−2 6400 Hovorka et al. (2019) M
Dewulf et al. (1999) M 364)
7.9×10−2 Duchowicz et al. (2020) V 187)
8.0×10−2 Yaws (2003) X 238)
3.2×10−2 Duchowicz et al. (2020) Q
3.8×10−2 Wang et al. (2017) Q 81) 239)
8.9×10−2 Wang et al. (2017) Q 81) 240)
1.5×10−1 Wang et al. (2017) Q 81) 241)
6.2×10−2 Gharagheizi et al. (2010) Q 247)
6.9×10−2 Hilal et al. (2008) Q
1.6×10−1 Modarresi et al. (2007) Q 68)
6600 Kühne et al. (2005) Q
7.9×10−2 Yaffe et al. (2003) Q 249) 250)
2.1×10−2 Katritzky et al. (1998) Q
5800 Kühne et al. (2005) ?
8.0×10−2 Yaws (1999) ? 21)
8.0×10−2 Yaws et al. (1998) ?

Data

The first column contains Henry's law solubility constant Hscp at the reference temperature of 298.15 K.
The second column contains the temperature dependence d ln Hs cp / d (1/T), also at the reference temperature.

References

  • Brockbank, S. A.: Aqueous Henry’s law constants, infinite dilution activity coefficients, and water solubility: critically evaluated database, experimental analysis, and prediction methods, Ph.D. thesis, Brigham Young University, USA, URL https://scholarsarchive.byu.edu/etd/3691/ (2013).
  • Dewulf, J., van Langenhove, H., & Everaert, P.: Determination of Henry’s law coefficients by combination of the equilibrium partitioning in closed systems and solid-phase microextraction techniques, J. Chromatogr. A, 830, 353–363, doi:10.1016/S0021-9673(98)00877-2 (1999).
  • Duchowicz, P. R., Aranda, J. F., Bacelo, D. E., & Fioressi, S. E.: QSPR study of the Henry’s law constant for heterogeneous compounds, Chem. Eng. Res. Des., 154, 115–121, doi:10.1016/J.CHERD.2019.12.009 (2020).
  • Gharagheizi, F., Abbasi, R., & Tirandazi, B.: Prediction of Henry’s law constant of organic compounds in water from a new group-contribution-based model, Ind. Eng. Chem. Res., 49, 10 149–10 152, doi:10.1021/IE101532E (2010).
  • Hilal, S. H., Ayyampalayam, S. N., & Carreira, L. A.: Air-liquid partition coefficient for a diverse set of organic compounds: Henry’s law constant in water and hexadecane, Environ. Sci. Technol., 42, 9231–9236, doi:10.1021/ES8005783 (2008).
  • Hovorka, Š., Vrbka, P., Bermúdez-Salguero, C., Böhme, A., & Dohnal, V.: Air–water partitioning of C5 and C6 alkanones: measurement, critical compilation, correlation, and recommended data, J. Chem. Eng. Data, 64, 5765–5774, doi:10.1021/ACS.JCED.9B00726 (2019).
  • Katritzky, A. R., Wang, Y., Sild, S., Tamm, T., & Karelson, M.: QSPR studies on vapor pressure, aqueous solubility, and the prediction of water-air partition coefficients, J. Chem. Inf. Comput. Sci., 38, 720–725, doi:10.1021/CI980022T (1998).
  • Kühne, R., Ebert, R.-U., & Schüürmann, G.: Prediction of the temperature dependency of Henry’s law constant from chemical structure, Environ. Sci. Technol., 39, 6705–6711, doi:10.1021/ES050527H (2005).
  • Modarresi, H., Modarress, H., & Dearden, J. C.: QSPR model of Henry’s law constant for a diverse set of organic chemicals based on genetic algorithm-radial basis function network approach, Chemosphere, 66, 2067–2076, doi:10.1016/J.CHEMOSPHERE.2006.09.049 (2007).
  • Plyasunov, A. V. & Shock, E. L.: Group contribution values of the infinite dilution thermodynamic functions of hydration for aliphatic noncyclic hydrocarbons, alcohols, and ketones at 298.15 K and 0.1 MPa, J. Chem. Eng. Data, 46, 1016–1019, doi:10.1021/JE0002282 (2001).
  • Wang, C., Yuan, T., Wood, S. A., Goss, K.-U., Li, J., Ying, Q., & Wania, F.: Uncertain Henry’s law constants compromise equilibrium partitioning calculations of atmospheric oxidation products, Atmos. Chem. Phys., 17, 7529–7540, doi:10.5194/ACP-17-7529-2017 (2017).
  • Yaffe, D., Cohen, Y., Espinosa, G., Arenas, A., & Giralt, F.: A fuzzy ARTMAP-based quantitative structure-property relationship (QSPR) for the Henry’s law constant of organic compounds, J. Chem. Inf. Comput. Sci., 43, 85–112, doi:10.1021/CI025561J (2003).
  • Yaws, C. L.: Chemical Properties Handbook, McGraw-Hill, Inc., ISBN 0070734011 (1999).
  • Yaws, C. L.: Yaws’ Handbook of Thermodynamic and Physical Properties of Chemical Compounds, Knovel: Norwich, NY, USA, ISBN 1591244447 (2003).
  • Yaws, C. L., Sheth, S. D., & Han, M.: Using solubility and Henry’s law constant data for ketones in water, Pollut. Eng., 30, 44–46 (1998).

Type

Table entries are sorted according to reliability of the data, listing the most reliable type first: L) literature review, M) measured, V) VP/AS = vapor pressure/aqueous solubility, R) recalculation, T) thermodynamical calculation, X) original paper not available, C) citation, Q) QSPR, E) estimate, ?) unknown, W) wrong. See Section 3.1 of Sander (2023) for further details.

Notes

21) Several references are given in the list of Henry's law constants but not assigned to specific species.
68) Modarresi et al. (2007) use different descriptors for their calculations. They conclude that a genetic algorithm/radial basis function network (GA/RBFN) is the best QSPR model. Only these results are shown here.
81) Value at T = 288 K.
187) Estimation based on the quotient between vapor pressure and water solubility, extracted from HENRYWIN.
238) Value given here as quoted by Gharagheizi et al. (2010).
239) Calculated using linear free energy relationships (LFERs).
240) Calculated using SPARC Performs Automated Reasoning in Chemistry (SPARC).
241) Calculated using COSMOtherm.
247) Calculated using a combination of a group contribution method and neural networks.
249) Yaffe et al. (2003) present QSPR results calculated with the fuzzy ARTMAP (FAM) and with the back-propagation (BK-Pr) method. They conclude that FAM is better. Only the FAM results are shown here.
250) Value from the training set.
364) The values of Dewulf et al. (1999) are not used here because, according to them, the calculated regression does not match the theoretical expectation for this species.

The numbers of the notes are the same as in Sander (2023). References cited in the notes can be found here.

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