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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 Please do not cite the old paper anymore.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 ConstantsOrganic species with sulfur (S)Sulfur (C, H, O, N, Cl, S) → ethanethiol

FORMULA:C2H5SH
TRIVIAL NAME: ethyl mercaptan
CAS RN:75-08-1
STRUCTURE
(FROM NIST):
InChIKey:DNJIEGIFACGWOD-UHFFFAOYSA-N

Hscp d ln Hs cp / d (1/T) References Type Notes
[mol/(m3Pa)] [K]
2.8×10−3 3700 Burkholder et al. (2019) L
2.8×10−3 3700 Burkholder et al. (2015) L
2.8×10−3 3700 Sander et al. (2011) L
2.8×10−3 3700 Sander et al. (2006) L
2.3×10−3 3500 Plyasunova et al. (2004) L
2.4×10−3 2800 Jou et al. (2021) M
2.8×10−3 3700 Przyjazny et al. (1983) M
2.2×10−3 Vitenberg et al. (1975) M
3.4×10−3 Mackay et al. (2006d) V
3.4×10−3 Mackay et al. (1995) V
3.4×10−3 Hwang et al. (1992) V
3.6×10−3 Hine and Mookerjee (1975) V
3.4×10−3 Yaws (2003) X 238)
1.8×10−3 Hayer et al. (2022) Q 20)
1.8×10−3 Gharagheizi et al. (2012) Q
2.9×10−3 Gharagheizi et al. (2010) Q 247)
3.9×10−3 Hilal et al. (2008) Q
5.6×10−3 Modarresi et al. (2007) Q 68)
3600 Kühne et al. (2005) Q
2.2×10−3 Yaffe et al. (2003) Q 249) 250)
5.8×10−3 Yao et al. (2002) Q 230)
3.6×10−3 English and Carroll (2001) Q 231) 232)
2.9×10−3 Katritzky et al. (1998) Q
1.9×10−3 Nirmalakhandan et al. (1997) Q
1.0×10−2 Russell et al. (1992) Q 280)
2.9×10−3 Suzuki et al. (1992) Q 233)
3700 Kühne et al. (2005) ?
3.4×10−3 Yaws et al. (2003) ? 21)
3.4×10−3 Yaws (1999) ? 21)
3.4×10−3 Yaws and Yang (1992) ? 21)
2.8×10−3 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., 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).
  • Burkholder, J. B., Sander, S. P., Abbatt, J., Barker, J. R., Huie, R. E., Kolb, C. E., Kurylo, M. J., Orkin, V. L., Wilmouth, D. M., & Wine, P. H.: Chemical Kinetics and Photochemical Data for Use in Atmospheric Studies, Evaluation No. 18, JPL Publication 15-10, Jet Propulsion Laboratory, Pasadena, URL https://jpldataeval.jpl.nasa.gov (2015).
  • Burkholder, J. B., Sander, S. P., Abbatt, J., Barker, J. R., Cappa, C., Crounse, J. D., Dibble, T. S., Huie, R. E., Kolb, C. E., Kurylo, M. J., Orkin, V. L., Percival, C. J., Wilmouth, D. M., & Wine, P. H.: Chemical Kinetics and Photochemical Data for Use in Atmospheric Studies, Evaluation No. 19, JPL Publication 19-5, Jet Propulsion Laboratory, Pasadena, URL https://jpldataeval.jpl.nasa.gov (2019).
  • 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).
  • Hayer, N., Jirasek, F., & Hasse, H.: Prediction of Henry’s law constants by matrix completion, AIChE J., 68, e17 753, doi:10.1002/AIC.17753 (2022).
  • 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).
  • Hine, J. & Mookerjee, P. K.: The intrinsic hydrophilic character of organic compounds. Correlations in terms of structural contributions, J. Org. Chem., 40, 292–298, doi:10.1021/JO00891A006 (1975).
  • 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).
  • Jou, F.-Y., Mather, A. E., & Schmidt, K. A. G.: Solubility of ethanethiol in water, J. Chem. Eng. Data, 66, 4174–4179, doi:10.1021/ACS.JCED.1C00358 (2021).
  • 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).
  • 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. IV of Nitrogen and Sulfur Containing Compounds and Pesticides, CRC/Taylor & Francis Group, doi:10.1201/9781420044393 (2006d).
  • 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).
  • Plyasunova, N. V., Plyasunov, A. V., & Shock, E. L.: Group contribution values for the thermodynamic functions of hydration at 298.15 K, 0.1 MPa. 2. aliphatic thiols, alkyl sulfides, and polysulfides, J. Chem. Eng. Data, 50, 246–253, doi:10.1021/JE0497045 (2004).
  • Przyjazny, A., Janicki, W., Chrzanowski, W., & Staszewski, R.: Headspace gas chromatographic determination of distribution coefficients of selected organosulphur compounds and their dependence on some parameters, J. Chromatogr., 280, 249–260, doi:10.1016/S0021-9673(00)91567-X (1983).
  • Russell, C. J., Dixon, S. L., & Jurs, P. C.: Computer-assisted study of the relationship between molecular structure and Henry’s law constant, Anal. Chem., 64, 1350–1355, doi:10.1021/AC00037A009 (1992).
  • Sander, S. P., Friedl, R. R., Golden, D. M., Kurylo, M. J., Moortgat, G. K., Keller-Rudek, H., Wine, P. H., Ravishankara, A. R., Kolb, C. E., Molina, M. J., Finlayson-Pitts, B. J., Huie, R. E., & Orkin, V. L.: Chemical Kinetics and Photochemical Data for Use in Atmospheric Studies, Evaluation Number 15, JPL Publication 06-2, Jet Propulsion Laboratory, Pasadena, CA, URL https://jpldataeval.jpl.nasa.gov (2006).
  • Sander, S. P., Abbatt, J., Barker, J. R., Burkholder, J. B., Friedl, R. R., Golden, D. M., Huie, R. E., Kolb, C. E., Kurylo, M. J., Moortgat, G. K., Orkin, V. L., & Wine, P. H.: Chemical Kinetics and Photochemical Data for Use in Atmospheric Studies, Evaluation No. 17, JPL Publication 10-6, Jet Propulsion Laboratory, Pasadena, URL https://jpldataeval.jpl.nasa.gov (2011).
  • Suzuki, T., Ohtaguchi, K., & Koide, K.: Application of principal components analysis to calculate Henry’s constant from molecular structure, Comput. Chem., 16, 41–52, doi:10.1016/0097-8485(92)85007-L (1992).
  • Vitenberg, A. G., Ioffe, B. V., Dimitrova, Z. S., & Butaeva, I. L.: Determination of gas-liquid partition coefficients by means of gas chromatographic analysis, J. Chromatogr., 112, 319–327, doi:10.1016/S0021-9673(00)99964-3 (1975).
  • 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).
  • Yaws, C. L. & Yang, H.-C.: Henry’s law constant for compound in water, in: Thermodynamic and Physical Property Data, edited by Yaws, C. L., pp. 181–206, Gulf Publishing Company, Houston, TX, ISBN 0884150313 (1992).
  • Yaws, C. L., Bajaj, P., Singh, H., & Pike, R. W.: Solubility & Henry’s law constants for sulfur compounds in water, Chem. Eng., pp. 60–64 (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

20) Calculated using machine learning matrix completion methods (MCMs).
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.
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.
233) Calculated with a principal component analysis (PCA); see Suzuki et al. (1992) for details.
238) Value given here as quoted by Gharagheizi et al. (2010).
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.
280) Value from the training set.

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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