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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 Please do not cite the old paper anymore.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 oxygen (O) → Carboxylic acids (RCOOH) and peroxy carboxylic acids (RCOOOH) → hexanoic acid

FORMULA:C5H11COOH
TRIVIAL NAME: caproic acid
CAS RN:142-62-1
STRUCTURE
(FROM NIST):
InChIKey:FUZZWVXGSFPDMH-UHFFFAOYSA-N

Hscp d ln Hs cp / d (1/T) References Type Notes
[mol/(m3Pa)] [K]
1.3×101 6100 Staudinger and Roberts (2001) L
9.9 Kim and Kim (2016) M
7.5 von Hartungen et al. (2004) M
1.3×101 6300 Khan et al. (1995) M
1.3×101 5900 Khan and Brimblecombe (1992) M
1.7×101 Mackay et al. (2006c) V
1.7 Mackay et al. (1995) V
1.1×101 Brimblecombe et al. (1992) V
2.0×101 Hwang et al. (1992) V
8700 Abraham (1984) V
8100 Abraham (1984) R 490)
2.4×101 Yaws (2003) X 12) 238)
6.1 Keshavarz et al. (2022) Q
5.9×101 Duchowicz et al. (2020) Q 185)
1.7×101 Gharagheizi et al. (2012) Q
6.2 Raventos-Duran et al. (2010) Q 243) 244)
2.5×101 Raventos-Duran et al. (2010) Q 245)
6.2 Raventos-Duran et al. (2010) Q 246)
1.4×101 Gharagheizi et al. (2010) Q 247)
2.4×101 Hilal et al. (2008) Q
1.7×101 Modarresi et al. (2007) Q 68)
7500 Kühne et al. (2005) Q
1.4×101 Yaffe et al. (2003) Q 249) 250)
8.3 Abraham (2003) Q
3.9×101 Yao et al. (2002) Q 230) 268)
1.1×101 English and Carroll (2001) Q 231) 232)
7.9 Katritzky et al. (1998) Q
1.7×101 Nirmalakhandan et al. (1997) Q
1.3×101 Duchowicz et al. (2020) ? 21) 186)
7200 Kühne et al. (2005) ?
1.5×101 Yaws (1999) ? 12) 21)
1.5×101 Abraham et al. (1990) ?

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.: Thermodynamics of solution of homologous series of solutes in water, J. Chem. Soc. Faraday Trans. 1, 80, 153–181, doi:10.1039/F19848000153 (1984).
  • Abraham, M. H.: The determination of air/water partition coefficients for alkyl carboxylic acids by a new indirect method, J. Environ. Monit., 5, 747–752, doi:10.1039/B308175C (2003).
  • Abraham, M. H., Whiting, G. S., Fuchs, R., & Chambers, E. J.: Thermodynamics of solute transfer from water to hexadecane, J. Chem. Soc. Perkin Trans. 2, pp. 291–300, doi:10.1039/P29900000291 (1990).
  • Brimblecombe, P., Clegg, S. L., & Khan, I.: Thermodynamic properties of carboxylic acids relevant to their solubility in aqueous solutions, J. Aerosol Sci., 23, S901–S904, doi:10.1016/0021-8502(92)90557-C (1992).
  • 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).
  • 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).
  • Gharagheizi, F., Eslamimanesh, A., Mohammadi, A. H., & Richon, D.: Empirical method for estimation of Henry’s law constant of non-electrolyte organic compounds in water, J. Chem. Thermodyn., 47, 295–299, doi:10.1016/J.JCT.2011.11.015 (2012).
  • 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).
  • Hwang, Y.-L., Olson, J. D., & Keller, II, G. E.: Steam stripping for removal of organic pollutants from water. 2. Vapor-liquid equilibrium data, Ind. Eng. Chem. Res., 31, 1759–1768, doi:10.1021/IE00007A022 (1992).
  • 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).
  • Khan, I. & Brimblecombe, P.: Henry’s law constants of low molecular weight (<130) organic acids, J. Aerosol Sci., 23, S897–S900, doi:10.1016/0021-8502(92)90556-B (1992).
  • Khan, I., Brimblecombe, P., & Clegg, S. L.: Solubilities of pyruvic acid and the lower (C1-C6) carboxylic acids. Experimental determination of equilibrium vapour pressures above pure aqueous and salt solutions, J. Atmos. Chem., 22, 285–302, doi:10.1007/BF00696639 (1995).
  • Kim, Y.-H. & Kim, K.-H.: A simple method for the accurate determination of the Henry’s law constant for highly sorptive, semivolatile organic compounds, Anal. Bioanal. Chem., 408, 775–784, doi:10.1007/S00216-015-9159-3 (2016).
  • 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).
  • 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).
  • Raventos-Duran, T., Camredon, M., Valorso, R., Mouchel-Vallon, C., & Aumont, B.: Structure-activity relationships to estimate the effective Henry’s law constants of organics of atmospheric interest, Atmos. Chem. Phys., 10, 7643–7654, doi:10.5194/ACP-10-7643-2010 (2010).
  • Staudinger, J. & Roberts, P. V.: A critical compilation of Henry’s law constant temperature dependence relations for organic compounds in dilute aqueous solutions, Chemosphere, 44, 561–576, doi:10.1016/S0045-6535(00)00505-1 (2001).
  • von Hartungen, E., Wisthaler, A., Mikoviny, T., Jaksch, D., Boscaini, E., Dunphy, P. J., & Märk, T. D.: Proton-transfer-reaction mass spectrometry (PTR-MS) of carboxylic acids. Determination of Henry’s law constants and axillary odour investigations, Int. J. Mass Spectrom., 239, 243–248, doi:10.1016/J.IJMS.2004.09.009 (2004).
  • 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).
  • Yaws, C. L.: Yaws’ Handbook of Thermodynamic and Physical Properties of Chemical Compounds, Knovel: Norwich, NY, USA, ISBN 1591244447 (2003).

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

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.
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.
232) Value from the training dataset.
238) Value given here as quoted by Gharagheizi et al. (2010).
243) Value from the training dataset.
244) Calculated using the GROMHE model.
245) Calculated using the SPARC approach.
246) Calculated using the HENRYWIN method.
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.
268) Value from the test set.
490) Abraham (1984) smoothed the values from a plot of enthalpy against carbon number.

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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