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 Please do not cite the old paper anymore.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 nitrogen (N) → Amines (C, H, N) → ethylenediamine

FORMULA:	H₂NCH₂CH₂NH₂
CAS RN:	107-15-3
STRUCTURE (FROM NIST):
InChIKey:	PIICEJLVQHRZGT-UHFFFAOYSA-N

$H_{s}^{cp}$	$d ln H_{s}^{cp} / d (1/ T)$	References	Type	Notes
[mol/(m³Pa)]	[K]
1.8×10³	6700	Nguyen (2013)	M	11)
5.8×10³		Westheimer and Ingraham (1956)	M
1.5×10²	9200	Cabani et al. (1978)	T
6.7×10³		Keshavarz et al. (2022)	Q
2.2×10³		Duchowicz et al. (2020)	Q
5.6×10³		Hilal et al. (2008)	Q
1.4×10⁴		Modarresi et al. (2007)	Q	68)
6.2×10²		Yao et al. (2002)	Q	230)
5.7×10³		Duchowicz et al. (2020)	?	21) 186)
2.3×10²		Yaws (1999)	?	12) 21)

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

Cabani, S., Mollica, V., & Lepori, L.: Thermodynamic study of dilute aqueous solutions of organic compounds. Part 5. – Open-chain saturated bifunctional compounds, J. Chem. Soc. Faraday Trans. 1, 74, 2667–2671, doi:10.1039/F19787402667 (1978).
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).
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).
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).
Nguyen, T.: Amine Volatility in CO₂ Capture, Ph.D. thesis, The University of Texas at Austin, USA, URL https://rochelle.che.utexas.edu/files/2015/02/Nguyen-2013-Amine-Volatility-in-CO2-Capture.pdf (2013).
Westheimer, F. H. & Ingraham, L. L.: The entropy of chelation, J. Phys. Chem., 60, 1668–1670, doi:10.1021/J150546A024 (1956).
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).

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

11)	Measured at high temperature and extrapolated to T^⊖ = 298.15 K.
12)	Value at T = 293 K.
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.
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 H_v^px and the unit atm.

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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