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Henry's Law Constants

www.henrys-law.org

Rolf Sander

Atmospheric Chemistry Division

Max-Planck Institute for Chemistry
Mainz, Germany

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Henry's Law Constants

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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 Please do not cite the old paper anymore.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 chlorine (Cl) → Oxygenated chlorocarbons (C, H, O, Cl) → 4-hydroxychlorobenzene

FORMULA:C6H5ClO
TRIVIAL NAME: p-chlorophenol
CAS RN:106-48-9
STRUCTURE
(FROM NIST):
InChIKey:WXNZTHHGJRFXKQ-UHFFFAOYSA-N

Hscp d ln Hs cp / d (1/T) References Type Notes
[mol/(m3Pa)] [K]
6.7 Chao et al. (2017) M
1.4×103 11000 Tabai et al. (1997) M 11)
1.6×101 HSDB (2015) V
1.1×101 Mackay et al. (2006c) V
1.2×101 Fogg and Sangster (2003) V
1.8×101 Lide and Frederikse (1995) V
1.1×101 Mackay et al. (1995) V
1.1×101 Shiu et al. (1994) V
5.8×101 Abraham et al. (1994a) R
1.8×101 Howard (1989) X 420)
4.3 Keshavarz et al. (2022) Q
1.5×102 Duchowicz et al. (2020) Q 185)
2.4×101 Li et al. (2014) Q 242)
1.3×101 Hilal et al. (2008) Q
9.8 Modarresi et al. (2007) Q 68)
6200 Kühne et al. (2005) Q
5.8×101 Yaffe et al. (2003) Q 249) 250)
3.4×101 Yao et al. (2002) Q 230)
2.3×101 English and Carroll (2001) Q 231) 261)
3.0×101 Katritzky et al. (1998) Q
1.8×102 Nirmalakhandan et al. (1997) Q
1.6×101 Duchowicz et al. (2020) ? 21) 186)
6400 Kühne et al. (2005) ?
7.8 Yaws (1999) ? 12) 21)
1.1×101 Chiou et al. (1980) ? 80)

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

  • Abraham, M. H., Andonian-Haftvan, J., Whiting, G. S., Leo, A., & Taft, R. S.: Hydrogen bonding. Part 34. The factors that influence the solubility of gases and vapours in water at 298 K, and a new method for its determination, J. Chem. Soc. Perkin Trans. 2, pp. 1777–1791, doi:10.1039/P29940001777 (1994a).
  • Chao, H.-P., Lee, J.-F., & Chiou, C. T.: Determination of the Henry’s law constants of low-volatility compounds via the measured air-phase transfer coefficients, Wat. Res., 120, 238–244, doi:10.1016/J.WATRES.2017.04.074 (2017).
  • Chiou, C. T., Freed, V. H., Peters, L. J., & Kohnert, R. L.: Evaporation of solutes from water, Environ. Int., 3, 231–236, doi:10.1016/0160-4120(80)90123-3 (1980).
  • 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).
  • English, N. J. & Carroll, D. G.: Prediction of Henry’s law constants by a quantitative structure property relationship and neural networks, J. Chem. Inf. Comput. Sci., 41, 1150–1161, doi:10.1021/CI010361D (2001).
  • Fogg, P. & Sangster, J.: Chemicals in the Atmosphere: Solubility, Sources and Reactivity, John Wiley & Sons, Inc., ISBN 978-0-471-98651-5 (2003).
  • 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).
  • Howard, P. H.: Handbook of Environmental fate and exposure data for organic chemicals. Vol. I: Large production and priority pollutants, Lewis Publishers Inc. Chelsea, Michigan, ISBN 0873711513 (1989).
  • HSDB: Hazardous Substances Data Bank, TOXicology data NETwork (TOXNET), National Library of Medicine (US), URL https://www.nlm.nih.gov/toxnet/Accessing_HSDB_Content_from_PubChem.html (2015).
  • 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).
  • Keshavarz, M. H., Rezaei, M., & Hosseini, S. H.: A simple approach for prediction of Henry’s law constant of pesticides, solvents, aromatic hydrocarbons, and persistent pollutants without using complex computer codes and descriptors, Process Saf. Environ. Prot., 162, 867–877, doi:10.1016/J.PSEP.2022.04.045 (2022).
  • 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).
  • Lide, D. R. & Frederikse, H. P. R.: CRC Handbook of Chemistry and Physics, 76th Edition, CRC Press, Inc., Boca Raton, FL, ISBN 0849304768 (1995).
  • Li, H., Wang, X., Yi, T., Xu, Z., & Liu, X.: Prediction of Henry’s law constants for organic compounds using multilayer feedforward neural networks based on linear salvation energy relationship, J. Chem. Pharm. Res., 6, 1557–1564 (2014).
  • Mackay, D., Shiu, W. Y., & Ma, K. C.: Illustrated Handbook of Physical-Chemical Properties and Environmental Fate for Organic Chemicals, vol. IV of Oxygen, Nitrogen, and Sulfur Containing Compounds, Lewis Publishers, Boca Raton, ISBN 1566700353 (1995).
  • Mackay, D., Shiu, W. Y., Ma, K. C., & Lee, S. C.: Handbook of Physical-Chemical Properties and Environmental Fate for Organic Chemicals, vol. III of Oxygen Containing Compounds, CRC/Taylor & Francis Group, doi:10.1201/9781420044393 (2006c).
  • 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).
  • Nirmalakhandan, N., Brennan, R. A., & Speece, R. E.: Predicting Henry’s law constant and the effect of temperature on Henry’s law constant, Wat. Res., 31, 1471–1481, doi:10.1016/S0043-1354(96)00395-8 (1997).
  • Shiu, W.-Y., Ma, K.-C., Varhaníčková, D., & Mackay, D.: Chlorophenols and alkylphenols: A review and correlation of environmentally relevant properties and fate in an evaluative environment, Chemosphere, 29, 1155–1224, doi:10.1016/0045-6535(94)90252-6 (1994).
  • Tabai, S., Rogalski, M., Solimando, R., & Malanowski, S. K.: Activity coefficients of chlorophenols in water at infinite dilution, J. Chem. Eng. Data, 42, 1147–1150, doi:10.1021/JE960336H (1997).
  • 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).
  • Yao, X., aand X. Zhang, M. L., Hu, Z., & Fan, B.: Radial basis function network-based quantitative structure-property relationship for the prediction of Henry’s law constant, Anal. Chim. Acta, 462, 101–117, doi:10.1016/S0003-2670(02)00273-8 (2002).
  • Yaws, C. L.: Chemical Properties Handbook, McGraw-Hill, Inc., ISBN 0070734011 (1999).

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

11) Measured at high temperature and extrapolated to T⊖ = 298.15 K.
12) Value at T = 293 K.
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.
80) Value at T = 297 K.
185) Value from the validation set for checking whether the model is satisfactory for compounds that are absent from the training set.
186) Experimental value, extracted from HENRYWIN.
230) Yao et al. (2002) compared two QSPR methods and found that radial basis function networks (RBFNs) are better than multiple linear regression. In their paper, they provide neither a definition nor the unit of their Henry's law constants. Comparing the values with those that they cite from Yaws (1999), it is assumed that they use the variant Hvpx and the unit atm.
231) English and Carroll (2001) provide several calculations. Here, the preferred value with explicit inclusion of hydrogen bonding parameters from a neural network is shown.
242) Temperature is not specified.
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.
261) Value from the validation dataset.
420) Value given here as quoted by Shiu et al. (1994).

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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