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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 Please do not cite the old paper anymore.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 → Hydrocarbons (C, H) → Polynuclear aromatics → 2-ethylnaphthalene

FORMULA:C10H7C2H5
CAS RN:939-27-5
STRUCTURE
(FROM NIST):
InChIKey:RJTJVVYSTUQWNI-UHFFFAOYSA-N

Hscp d ln Hs cp / d (1/T) References Type Notes
[mol/(m3Pa)] [K]
1.2×10−2 Mackay and Shiu (1981) L
1.8×10−2 Altschuh et al. (1999) M
1.3×10−2 Mackay et al. (2006a) V
1.6×10−2 Eastcott et al. (1988) V
1.3×10−2 Mackay et al. (1992b) X 366)
8.8×10−3 Yaws (2003) X 238)
2.2×10−2 Keshavarz et al. (2022) Q
1.2×10−2 Duchowicz et al. (2020) Q 300)
1.9×10−2 Schröder et al. (2013) Q 372)
3.6×10−2 Gharagheizi et al. (2012) Q
1.6×10−2 Gharagheizi et al. (2010) Q 247)
1.9×10−2 Hilal et al. (2008) Q
2.2×10−2 Modarresi et al. (2007) Q 68)
1.2×10−2 Yaffe et al. (2003) Q 249) 250)
1.8×10−2 Duchowicz et al. (2020) ? 21) 186)
1.6×10−2 Yaws and Yang (1992) ? 21)

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

  • Altschuh, J., Brüggemann, R., Santl, H., Eichinger, G., & Piringer, O. G.: Henry’s law constants for a diverse set of organic chemicals: Experimental determination and comparison of estimation methods, Chemosphere, 39, 1871–1887, doi:10.1016/S0045-6535(99)00082-X (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).
  • Eastcott, L., Shiu, W. Y., & Mackay, D.: Environmentally relevant physical-chemical properties of hydrocarbons: A review of data and development of simple correlations, Oil Chem. Pollut., 4, 191–216, doi:10.1016/S0269-8579(88)80020-0 (1988).
  • 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).
  • 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).
  • Mackay, D. & Shiu, W. Y.: A critical review of Henry’s law constants for chemicals of environmental interest, J. Phys. Chem. Ref. Data, 10, 1175–1199, doi:10.1063/1.555654 (1981).
  • Mackay, D., Shiu, W. Y., & Ma, K. C.: Illustrated Handbook of Physical-Chemical Properties and Environmental Fate for Organic Chemicals, vol. II of Polynuclear Aromatic Hydrocarbons, Polychlorinated Dioxins, and Dibenzofurans, Lewis Publishers, Boca Raton, ISBN 0873715837 (1992b).
  • Mackay, D., Shiu, W. Y., Ma, K. C., & Lee, S. C.: Handbook of Physical-Chemical Properties and Environmental Fate for Organic Chemicals, vol. I of Introduction and Hydrocarbons, CRC/Taylor & Francis Group, doi:10.1201/9781420044393 (2006a).
  • 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).
  • Schröder, B., Coutinho, J., & Santos, L. M. N. B. F.: Predicting physico-chemical properties of alkylated naphthalenes with COSMO-RS, Polycyclic Aromat. Compd., 33, 1–19, doi:10.1080/10406638.2012.683231 (2013).
  • 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.: 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).

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.
186) Experimental value, extracted from HENRYWIN.
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.
300) Value from the test set for true external validation.
366) Value given here as quoted by Haynes (2014).
372) Calculated using the COSMO-RS method.

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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