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 Please do not cite the old paper anymore.
|
FORMULA: | C7H8O2 |
TRIVIAL NAME:
|
guaiacol; 2-methoxyphenol
|
CAS RN: | 90-05-1 |
STRUCTURE
(FROM
NIST):
|
|
InChIKey: | LHGVFZTZFXWLCP-UHFFFAOYSA-N |
|
|
References |
Type |
Notes |
[mol/(m3Pa)] |
[K] |
|
|
|
8.6 |
|
McFall et al. (2020) |
M |
|
9.0 |
7900 |
Wieland et al. (2015) |
M |
549)
|
7.7 |
|
Sagebiel et al. (1992) |
M |
|
9.1 |
7600 |
Sagebiel et al. (1992) |
M |
|
9.6 |
|
Mackay et al. (2006c) |
V |
|
7.7 |
|
Sagebiel et al. (1992) |
V |
|
4.1×101 |
|
Leuenberger et al. (1985) |
V |
418)
|
5.0 |
|
Abraham et al. (1994a) |
R |
|
1.1×101 |
|
Keshavarz et al. (2022) |
Q |
|
5.6×10−1 |
|
Abney (2021) |
Q |
401)
|
8.7 |
|
Duchowicz et al. (2020) |
Q |
300)
|
8.2 |
|
McFall et al. (2020) |
Q |
476)
|
5.2 |
|
Hilal et al. (2008) |
Q |
|
7.7 |
|
Modarresi et al. (2007) |
Q |
68)
|
|
6700 |
Kühne et al. (2005) |
Q |
|
1.2×101 |
|
English and Carroll (2001) |
Q |
231)
275)
|
6.4×101 |
|
Katritzky et al. (1998) |
Q |
|
5.1×102 |
|
Nirmalakhandan et al. (1997) |
Q |
|
8.2 |
|
Duchowicz et al. (2020) |
? |
21)
186)
|
|
7800 |
Kühne et al. (2005) |
? |
|
3.3×10−1 |
|
Yaws (1999) |
? |
14)
21)
|
Data
The first column contains Henry's law solubility constant
at the reference temperature of 298.15 K.
The second column contains the temperature dependence
, also at the
reference temperature.
References
-
Abney, C. A.: Predicting Henry’s Law constants of volatile organic compounds present in bourbon using molecular simulations, Master’s thesis, University of Louisville, Kentucky, USA, doi:10.18297/etd/3440 (2021).
-
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).
-
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).
-
Leuenberger, C., Ligocki, M. P., & Pankow, J. F.: Trace organic compounds in rain: 4. Identities, concentrations, and scavenging mechanisms for phenols in urban air and rain, Environ. Sci. Technol., 19, 1053–1058, doi:10.1021/ES00141A005 (1985).
-
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).
-
McFall, A. S., Johnson, A. W., & Anastasio, C.: Air–water partitioning of biomass-burning phenols and the effects of temperature and salinity, Environ. Sci. Technol., 54, 3823–3830, doi:10.1021/ACS.EST.9B06443 (2020).
-
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).
-
Sagebiel, J. C., Seiber, J. N., & Woodrow, J. E.: Comparison of headspace and gas-stripping methods for determining the Henry’s law constant (H) for organic compounds of low to intermediate H, Chemosphere, 25, 1763–1768, doi:10.1016/0045-6535(92)90017-L (1992).
-
Wieland, F., Neff, A., Gloess, A. N., Poisson, L., Atlan, S., Larrain, D., Prêtre, D., Blank, I., & Yeretzian, C.: Temperature dependence of Henry’s law constants: An automated, high-throughput gas stripping cell design coupled to PTR-ToF-MS, Int. J. Mass Spectrom., 387, 69–77, doi:10.1016/J.IJMS.2015.07.015 (2015).
-
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
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. |
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. |
275) |
Value from the test dataset. |
300) |
Value from the test set for true external validation. |
401) |
Calculated for an aqueous solution containing 60 % ethanol by volume as the solvent. |
418) |
Value at T = 281 K. |
476) |
Calculated using the experimental value adjusted (EVA) method; see McFall et al. (2020) for details. |
549) |
The data from Wieland et al. (2015) were fitted to the three-parameter equation: Hscp= exp( −96.39127 +11107.87195/T +10.76466 ln(T)) mol m−3 Pa−1, with T in K. |
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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