Fischer, Cornelius; Arvidson, Rolf S; Lüttge, Andreas (2012): Dissolution rate spectra data of calcite single crystal and micrite material [dataset]. PANGAEA, https://doi.org/10.1594/PANGAEA.829556, Supplement to: Fischer, C et al. (2012): How predictable are dissolution rates of crystalline material? Geochimica et Cosmochimica Acta, 98, 177-185, https://doi.org/10.1016/j.gca.2012.09.011
Always quote citation above when using data! You can download the citation in several formats below.
Published: 2012 (exact date unknown) • DOI registered: 2014-05-26
Abstract:
The large discrepancy between field and laboratory measurements of mineral reaction rates is a long-standing problem in earth sciences, often attributed to factors extrinsic to the mineral itself. Nevertheless, differences in reaction rate are also observed within laboratory measurements, raising the possibility of intrinsic variations as well. Critical insight is available from analysis of the relationship between the reaction rate and its distribution over the mineral surface. This analysis recognizes the fundamental variance of the rate. The resulting anisotropic rate distributions are completely obscured by the common practice of surface area normalization. In a simple experiment using a single crystal and its polycrystalline counterpart, we demonstrate the sensitivity of dissolution rate to grain size, results that undermine the use of "classical" rate constants. Comparison of selected published crystal surface step retreat velocities (Jordan and Rammensee, 1998) as well as large single crystal dissolution data (Busenberg and Plummer, 1986) provide further evidence of this fundamental variability. Our key finding highlights the unsubstantiated use of a single-valued "mean" rate or rate constant as a function of environmental conditions. Reactivity predictions and long-term reservoir stability calculations based on laboratory measurements are thus not directly applicable to natural settings without a probabilistic approach. Such a probabilistic approach must incorporate both the variation of surface energy as a general range (intrinsic variation) as well as constraints to this variation owing to the heterogeneity of complex material (e.g., density of domain borders). We suggest the introduction of surface energy spectra (or the resulting rate spectra) containing information about the probability of existing rate ranges and the critical modes of surface energy.
Project(s):
Event(s):
Comment:
Comparison of VSI rate data (histograms for dt = 4 h) with published calcite dissolution rates. Our (new) rate data are not simple means, but instead preserve the contribution of certain height step retreats that constitute a total rate spectrum.
BP (Busenberg and Plummer, 1986).
JR (Jordan and Rammensee, 1998).
SC: single crystal
Parameter(s):
# | Name | Short Name | Unit | Principal Investigator | Method/Device | Comment |
---|---|---|---|---|---|---|
1 | Calcite dissolution rate | Cal diss rate | µmol/m2/s | Fischer, Cornelius | Vertical scanning interferometer (VSI), Zemetrics ZeMapper (Tucson AZ) | |
2 | Frequency | Frequency | % | Fischer, Cornelius | Vertical scanning interferometer (VSI), Zemetrics ZeMapper (Tucson AZ) | |
3 | Frequency | Frequency | % | Fischer, Cornelius | Vertical scanning interferometer (VSI), Zemetrics ZeMapper (Tucson AZ) | micrite |
4 | Frequency | Frequency | % | Fischer, Cornelius | Vertical scanning interferometer (VSI), Zemetrics ZeMapper (Tucson AZ) | JR |
5 | Frequency | Frequency | % | Fischer, Cornelius | Vertical scanning interferometer (VSI), Zemetrics ZeMapper (Tucson AZ) | BP |
6 | Frequency | Frequency | % | Fischer, Cornelius | Vertical scanning interferometer (VSI), Zemetrics ZeMapper (Tucson AZ) | SC mean |
7 | Frequency | Frequency | % | Fischer, Cornelius | Vertical scanning interferometer (VSI), Zemetrics ZeMapper (Tucson AZ) | M mean |
8 | Surface height | Surface h | µm | Fischer, Cornelius | Vertical scanning interferometer (VSI), Zemetrics ZeMapper (Tucson AZ) |
License:
Creative Commons Attribution 3.0 Unported (CC-BY-3.0)
Size:
6744 data points
Download Data
View dataset as HTML (shows only first 2000 rows)