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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 Please do not cite the old paper anymore.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 Constants → Organic species with chlorine (Cl) → Chlorocarbons with nitrogen (C, H, O, N, Cl) → 2-chloronitrobenzene

FORMULA:C6H4ClNO2
TRIVIAL NAME: o-chloronitrobenzene
CAS RN:88-73-3
STRUCTURE
(FROM NIST):
InChIKey:BFCFYVKQTRLZHA-UHFFFAOYSA-N

Hscp d ln Hs cp / d (1/T) References Type Notes
[mol/(m3Pa)] [K]
1.1 Altschuh et al. (1999) M
2.2×10−1 Hellmann (1987) M 88)
2.8×10−1 Lide and Frederikse (1995) V
1.1 Keshavarz et al. (2022) Q
3.1 Duchowicz et al. (2020) Q 185)
6.2×10−1 Zhang et al. (2010) Q 288) 289)
1.5×10−1 Zhang et al. (2010) Q 288) 290)
1.2 Zhang et al. (2010) Q 288) 291)
4.6×10−1 Zhang et al. (2010) Q 288) 292)
3.1×10−1 Hilal et al. (2008) Q
1.8×10−1 Modarresi et al. (2007) Q 68)
4700 Kühne et al. (2005) Q
2.3×10−1 Yaffe et al. (2003) Q 249) 250)
8.1×10−1 Yao et al. (2002) Q 230)
7.5×10−1 Katritzky et al. (1998) Q
1.1 Duchowicz et al. (2020) ? 21) 186)
6000 Kühne et al. (2005) ?
9.7×10−1 Yaws (1999) ? 12) 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).
  • Hellmann, H.: Model tests on volatilization of organic trace substances in surfaces waters, Fresenius J. Anal. Chem., 328, 475–479, doi:10.1007/BF00475967 (1987).
  • 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).
  • 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).
  • 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).
  • Kühne, R., Ebert, R.-U., & Schüürmann, G.: Prediction of the temperature dependency of Henry’s law constant from chemical structure, Environ. Sci. Technol., 39, 6705–6711, doi:10.1021/ES050527H (2005).
  • Lide, D. R. & Frederikse, H. P. R.: CRC Handbook of Chemistry and Physics, 76th Edition, CRC Press, Inc., Boca Raton, FL, ISBN 0849304768 (1995).
  • 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).
  • 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).
  • Zhang, X., Brown, T. N., Wania, F., Heimstad, E. S., & Goss, K.-U.: Assessment of chemical screening outcomes based on different partitioning property estimation methods, Environ. Int., 36, 514–520, doi:10.1016/J.ENVINT.2010.03.010 (2010).

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.
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.
88) Value at T = 295 K.
185) Value from the validation set for checking whether the model is satisfactory for compounds that are absent from the training set.
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 Hvpx and the unit atm.
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.
288) Data taken from the supplement.
289) Calculated using the EPI Suite (v4.0) method.
290) Calculated using the SPARC (v4.2) method.
291) Calculated using the COSMOtherm (v2.1) method.
292) Calculated using the ABSOLV (ADMEBoxes v4.1) 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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