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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 Please do not cite the old paper anymore.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 → Hydrocarbons (C, H) → Mononuclear aromatics → 1,2,3-trimethylbenzene

FORMULA:C6H3(CH3)3
CAS RN:526-73-8
STRUCTURE
(FROM NIST):
InChIKey:FYGHSUNMUKGBRK-UHFFFAOYSA-N

Hscp d ln Hs cp / d (1/T) References Type Notes
[mol/(m3Pa)] [K]
2.4×10−3 4600 Brockbank (2013) L
2.7×10−3 4800 Fogg and Sangster (2003) L
2.6×10−3 4500 Plyasunov and Shock (2000) L
3.1×10−3 Mackay and Shiu (1981) L
1.1×10−3 Järnberg and Johanson (1995) M 14)
2.4×10−3 4500 Sanemasa et al. (1982) M
2.9×10−3 Mackay et al. (2006a) V
2.9×10−3 Shiu and Ma (2000) V
3.1×10−3 Abraham et al. (1994a) V
2.9×10−3 Mackay et al. (1992a) V
2.7×10−3 Eastcott et al. (1988) V
1.3×10−3 Yaws (2003) X 238)
1.8×10−3 Keshavarz et al. (2022) Q
7.9×10−4 Duchowicz et al. (2020) Q 300)
1.4×10−3 Wang et al. (2017) Q 81) 239)
2.2×10−3 Wang et al. (2017) Q 81) 240)
3.5×10−3 Wang et al. (2017) Q 81) 241)
8.8×10−4 Gharagheizi et al. (2012) Q
7.8×10−4 Raventos-Duran et al. (2010) Q 243) 244)
2.5×10−3 Raventos-Duran et al. (2010) Q 245)
1.2×10−3 Raventos-Duran et al. (2010) Q 246)
1.6×10−3 Gharagheizi et al. (2010) Q 247)
3.1×10−3 Hilal et al. (2008) Q
8.2×10−4 Modarresi et al. (2007) Q 68)
3900 Kühne et al. (2005) Q
3.1×10−3 Yaffe et al. (2003) Q 249) 250)
2.0×10−3 English and Carroll (2001) Q 231) 275)
4.6×10−4 Katritzky et al. (1998) Q
8.2×10−4 Nirmalakhandan et al. (1997) Q
2.3×10−3 Duchowicz et al. (2020) ? 21) 186)
4400 Kühne et al. (2005) ?
1.3×10−3 Yaws (1999) ? 21)
2.7×10−3 Yaws and Yang (1992) ? 21)
2.1×10−3 Abraham et al. (1990) ?

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

  • Abraham, M. H., Whiting, G. S., Fuchs, R., & Chambers, E. J.: Thermodynamics of solute transfer from water to hexadecane, J. Chem. Soc. Perkin Trans. 2, pp. 291–300, doi:10.1039/P29900000291 (1990).
  • 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).
  • Brockbank, S. A.: Aqueous Henry’s law constants, infinite dilution activity coefficients, and water solubility: critically evaluated database, experimental analysis, and prediction methods, Ph.D. thesis, Brigham Young University, USA, URL https://scholarsarchive.byu.edu/etd/3691/ (2013).
  • 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).
  • Eastcott, L., Shiu, W. Y., & Mackay, D.: Environmentally relevant physical-chemical properties of hydrocarbons: A review of data and development of simple correlations, Oil Chem. Pollut., 4, 191–216, doi:10.1016/S0269-8579(88)80020-0 (1988).
  • 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).
  • Fogg, P. & Sangster, J.: Chemicals in the Atmosphere: Solubility, Sources and Reactivity, John Wiley & Sons, Inc., ISBN 978-0-471-98651-5 (2003).
  • 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).
  • Järnberg, J. & Johanson, G.: Liquid/air partition coefficients of the trimethylbenzenes, Toxicol. Ind. Health, 11, 81–88, doi:10.1177/074823379501100107 (1995).
  • 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).
  • 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. I of Monoaromatic Hydrocarbons, Chlorobenzenes, and PCBs, Lewis Publishers, Boca Raton, ISBN 0873715136 (1992a).
  • 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).
  • 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).
  • 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).
  • Sanemasa, I., Araki, M., Deguchi, T., & Nagai, H.: Solubility measurements of benzene and the alkylbenzenes in water by making use of solute vapor, Bull. Chem. Soc. Jpn., 55, 1054–1062, doi:10.1246/BCSJ.55.1054 (1982).
  • Shiu, W. Y. & Ma, K.-C.: Temperature dependence of physical-chemical properties of selected chemicals of environmental interest. I. mononuclear and polynuclear aromatic hydrocarbons, J. Phys. Chem. Ref. Data, 29, 41–130, doi:10.1063/1.556055 (2000).
  • 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).
  • 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

14) Value at T = 310 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.
81) Value at T = 288 K.
186) Experimental value, 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).
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.
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.
275) Value from the test dataset.
300) Value from the test set for true external validation.

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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