Henry's Law Constants

Rolf Sander

Atmospheric Chemistry Division

Max-Planck Institute for Chemistry
Mainz, Germany

Errata

Contact, Imprint, Acknowledgements

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 Please do not cite the old paper anymore.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 chlorine (Cl) → Chlorocarbons with nitrogen (C, H, O, N, Cl) → 1-amino-4-chlorobenzene

FORMULA:	C₆H₆ClN
TRIVIAL NAME:	p-chloroaniline
CAS RN:	106-47-8
STRUCTURE (FROM NIST):
InChIKey:	QSNSCYSYFYORTR-UHFFFAOYSA-N

$H_{s}^{cp}$	$d ln H_{s}^{cp} / d (1/ T)$	References	Type	Notes
[mol/(m³Pa)]	[K]
8.5		Duchowicz et al. (2020)	V	187)
3.2		HSDB (2015)	V
1.0×10¹		Mackay et al. (2006d)	V
9.1×10⁻¹		Lide and Frederikse (1995)	V
1.0×10¹		Mackay et al. (1995)	V
2.5×10¹		Meylan and Howard (1991)	V
8.6		Abraham et al. (1994a)	R
3.4		Yaws (2003)	X	12) 238)
9.2×10⁻¹		Howard (1989)	X	414)
8.3		Duchowicz et al. (2020)	Q
4.9		Gharagheizi et al. (2010)	Q	247)
8.6		Hilal et al. (2008)	Q
1.6×10¹		Modarresi et al. (2007)	Q	68)
8.8		Yaffe et al. (2003)	Q	249) 250)
5.4		English and Carroll (2001)	Q	231) 261)
1.5×10¹		Katritzky et al. (1998)	Q
5.3		Nirmalakhandan et al. (1997)	Q
7.0		Meylan and Howard (1991)	Q

Data

The first column contains Henry's law solubility constant

H_{s}^{cp}

at the reference temperature of 298.15 K.
The second column contains the temperature dependence

d ln H_{s}^{cp} / d
(1/ T)

, also at the reference temperature.

References

Abraham, M. H., Andonian-Haftvan, J., Whiting, G. S., Leo, A., & Taft, R. S.: Hydrogen bonding. Part 34. The factors that influence the solubility of gases and vapours in water at 298 K, and a new method for its determination, J. Chem. Soc. Perkin Trans. 2, pp. 1777–1791, doi:10.1039/P29940001777 (1994a).
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).
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).
Howard, P. H.: Handbook of Environmental fate and exposure data for organic chemicals. Vol. I: Large production and priority pollutants, Lewis Publishers Inc. Chelsea, Michigan, ISBN 0873711513 (1989).
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).
Lide, D. R. & Frederikse, H. P. R.: CRC Handbook of Chemistry and Physics, 76th Edition, CRC Press, Inc., Boca Raton, FL, ISBN 0849304768 (1995).
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).
Meylan, W. M. & Howard, P. H.: Bond contribution method for estimating Henry’s law constants, Environ. Toxicol. Chem., 10, 1283–1293, doi:10.1002/ETC.5620101007 (1991).
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).
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).

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.
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.
187)	Estimation based on the quotient between vapor pressure and water solubility, extracted from HENRYWIN.
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.
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.
261)	Value from the validation dataset.
414)	Value given here as quoted by Mackay et al. (1995).

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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