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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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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 Please do not cite the old paper anymore.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 oxygen (O)Heterocycles with oxygen → oxacyclopentadiene

FORMULA:C4H4O
TRIVIAL NAME: furan; furfuran
CAS RN:110-00-9
STRUCTURE
(FROM NIST):
InChIKey:YLQBMQCUIZJEEH-UHFFFAOYSA-N

Hscp d ln Hs cp / d (1/T) References Type Notes
[mol/(m3Pa)] [K]
1.8×10−3 HSDB (2015) V
1.8×10−3 Mackay et al. (2006c) V
1.8×10−3 Mackay et al. (1993) V
1.8×10−3 Yaws (2003) X 259)
1.8×10−3 Yaws (2003) X 238)
2.2×10−3 Dupeux et al. (2022) Q 260)
4.6×10−3 Hayer et al. (2022) Q 20)
3.1×10−2 Raventos-Duran et al. (2010) Q 243) 244)
2.0×10−3 Raventos-Duran et al. (2010) Q 245)
2.0×10−3 Raventos-Duran et al. (2010) Q 246)
1.9×10−3 Gharagheizi et al. (2010) Q 247)
2.3×10−3 Hilal et al. (2008) Q
1.9×10−3 Yaffe et al. (2003) Q 249) 250)
4.3×10−3 Yao et al. (2002) Q 230)
1.2×10−2 Katritzky et al. (1998) Q
1.8×10−3 Yaws (1999) ? 21)
1.8×10−3 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

  • Dupeux, T., Gaudin, T., Marteau-Roussy, C., Aubry, J.-M., & Nardello-Rataj, V.: COSMO-RS as an effective tool for predicting the physicochemical properties of fragrance raw materials, Flavour Fragrance J., 37, 106–120, doi:10.1002/FFJ.3690 (2022).
  • 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).
  • 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).
  • 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).
  • 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. III of Oxygen Containing Compounds, CRC/Taylor & Francis Group, doi:10.1201/9781420044393 (2006c).
  • 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).
  • 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

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.
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.
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.
259) Value given here as quoted by Dupeux et al. (2022).
260) 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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