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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 Please do not cite the old paper anymore.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 → Hydrocarbons (C, H) → Aliphatic alkenes and cycloalkenes → 2-methyl-1,3-butadiene

FORMULA:C5H8
TRIVIAL NAME: isoprene
CAS RN:78-79-5
STRUCTURE
(FROM NIST):
InChIKey:RRHGJUQNOFWUDK-UHFFFAOYSA-N

Hscp d ln Hs cp / d (1/T) References Type Notes
[mol/(m3Pa)] [K]
1.3×10−4 2700 Plyasunov and Shock (2000) L
1.3×10−4 Mackay and Shiu (1981) L
3.0×10−4 Schuhfried et al. (2015) M
3.4×10−4 4400 Leng et al. (2013) M
1.2×10−4 4400 Ooki and Yokouchi (2011) M 71)
2.9×10−4 Karl et al. (2003) M 28)
1.3×10−4 Duchowicz et al. (2020) V 187)
1.3×10−4 Martins et al. (2017) V 316)
1.3×10−4 HSDB (2015) V
1.3×10−4 Mackay et al. (2006a) V
1.3×10−4 Copolovici and Niinemets (2005) V
1.3×10−4 Mackay et al. (1993) V
1.3×10−4 Hine and Mookerjee (1975) V
1.3×10−4 Yaws (2003) X 238)
1.8×10−3 Duchowicz et al. (2020) Q
4.1×10−4 Wang et al. (2017) Q 81) 239)
1.6×10−4 Wang et al. (2017) Q 81) 240)
1.9×10−4 Wang et al. (2017) Q 81) 241)
1.8×10−4 Gharagheizi et al. (2012) Q
1.6×10−4 Raventos-Duran et al. (2010) Q 243) 244)
1.6×10−4 Raventos-Duran et al. (2010) Q 245)
7.8×10−5 Raventos-Duran et al. (2010) Q 246)
1.0×10−4 Gharagheizi et al. (2010) Q 247)
2.7×10−4 Hilal et al. (2008) Q
1.1×10−5 Modarresi et al. (2005) Q 248)
1.3×10−4 Yaffe et al. (2003) Q 249) 250)
1.0×10−4 Yao et al. (2002) Q 230)
1.1×10−4 Yao et al. (2002) Q 230)
1.0×10−4 English and Carroll (2001) Q 231) 232)
1.4×10−4 Suzuki et al. (1992) Q 233)
6.7×10−5 Nirmalakhandan and Speece (1988) Q
1.1×10−4 Yaws (1999) ? 21)
1.3×10−4 Yaws (1999) ? 21)
1.3×10−4 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

  • Copolovici, L. O. & Niinemets, U.: Temperature dependencies of Henry’s law constants and octanol/water partition coefficients for key plant volatile monoterpenoids, Chemosphere, 61, 1390–1400, doi:10.1016/J.CHEMOSPHERE.2005.05.003 (2005).
  • 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).
  • 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).
  • 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).
  • Karl, T., Yeretzian, C., Jordan, A., & Lindinger, W.: Dynamic measurements of partition coefficients using proton-transfer-reaction mass spectrometry (PTR-MS), Int. J. Mass Spectrom., 223-224, 383–395, doi:10.1016/S1387-3806(02)00927-2 (2003).
  • Leng, C., Kish, J. D., Kelley, J., Mach, M., Hiltner, J., Zhang, Y., & Liu, Y.: Temperature-dependent Henry’s law constants of atmospheric organics of biogenic origin, J. Phys. Chem. A, 117, 10 359–10 367, doi:10.1021/JP403603Z (2013).
  • 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. III of Volatile Organic Chemicals, Lewis Publishers, Boca Raton, ISBN 0873719735 (1993).
  • 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).
  • Martins, M. A. R., Silva, L. P., Ferreira, O., Schröder, B., Coutinho, J. A. P., & Pinho, S. P.: Terpenes solubility in water and their environmental distribution, J. Mol. Liq., 241, 996–1002, doi:10.1016/J.MOLLIQ.2017.06.099 (2017).
  • Modarresi, H., Modarress, H., & Dearden, J. C.: Henry’s law constant of hydrocarbons in air–water system: The cavity ovality effect on the non-electrostatic contribution term of solvation free energy, SAR QSAR Environ. Res., 16, 461–482, doi:10.1080/10659360500319869 (2005).
  • Nirmalakhandan, N. N. & Speece, R. E.: QSAR model for predicting Henry’s constant, Environ. Sci. Technol., 22, 1349–1357, doi:10.1021/ES00176A016 (1988).
  • Ooki, A. & Yokouchi, Y.: Determination of Henry’s law constant of halocarbons in seawater and analysis of sea-to-air flux of iodoethane (C2H5I) in the Indian and Southern Oceans based on partial pressure measurements, Geochem. J., 45, e1–e7, doi:10.2343/GEOCHEMJ.1.0122 (2011).
  • Plyasunov, A. V. & Shock, E. L.: Thermodynamic functions of hydration of hydrocarbons at 298.15K and 0.1MPa, Geochim. Cosmochim. Acta, 64, 439–468, doi:10.1016/S0016-7037(99)00330-0 (2000).
  • 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).
  • Schuhfried, E., Aprea, E., Märk, T. D., & Biasioli, F.: Refined measurements of Henry’s law constant of terpenes with inert gas stripping coupled with PTR-MS, Water Air Soil Pollut., 226, 120, doi:10.1007/S11270-015-2337-2 (2015).
  • 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).
  • 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).
  • 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).

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.
28) Value at T = 291 K.
71) Solubility in sea water.
81) Value at T = 288 K.
187) Estimation based on the quotient between vapor pressure and water solubility, 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.
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).
239) Calculated using linear free energy relationships (LFERs).
240) Calculated using SPARC Performs Automated Reasoning in Chemistry (SPARC).
241) Calculated using COSMOtherm.
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.
248) Modarresi et al. (2005) use different descriptors for the QSPR models. They conclude that their "COSA" method and the artificial neural network (ANN) are best. However, as COSA is not ideal for hydrocarbons with low solubility, only results obtained with ANN are shown here.
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.
316) Values for the Henry's law constants shown in Fig. 3 of Martins et al. (2017) were obtained from Simão Pinho (personal communication, 2022).

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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