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 Please do not cite the old paper anymore.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: | C7H5Cl3 |
TRIVIAL NAME:
|
2,4,5-trichlorotoluene
|
CAS RN: | 6639-30-1 |
STRUCTURE
(FROM
NIST):
|
|
InChIKey: | ZCXHZKNWIYVQNC-UHFFFAOYSA-N |
|
|
References |
Type |
Notes |
[mol/(m3Pa)] |
[K] |
|
|
|
6.6×10−3 |
|
Oliver (1985) |
M |
|
1.2×10−2 |
|
Hilal et al. (2008) |
Q |
|
6.2×10−3 |
|
Modarresi et al. (2007) |
Q |
68)
|
4.1×10−3 |
|
Meylan and Howard (1991) |
Q |
|
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
-
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).
-
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).
-
Oliver, B. G.: Desorption of chlorinated hydrocarbons from spiked and anthropogenically contaminated sediments, Chemosphere, 14, 1087–1106, doi:10.1016/0045-6535(85)90029-3 (1985).
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
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. |
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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