Diffusion chronometry: Difference between revisions

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Updated the topic to be more comprehensive. I added relevant sections, equations and examples.
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== Introduction ==
'''Diffusion chronometry''' is a geological technique that examines the chemical zoning within [[phenocrysts]] to estimate the duration between the events that occur in magmatic system and their associated eruptions.<ref>{{cite journal |last1=Rosen |first1=Julia |title=Crystal clocks |journal=Science |date=18 November 2016 |volume=354 |issue=6314 |pages=822–825 |doi=10.1126/science.354.6314.822 |pmid=27856862 }}</ref> Diffusion chronometry should not be confused with [[geospeedometry]]. Both utilize the theory of chemical diffusion but the latter is more commonly used for analyzing rates of metamorphic events whereas the former is used to analyze features of eruptive events.
'''Diffusion chronometry''' is a geological technique that examines the chemical zoning within [[phenocrysts]] to estimate the duration of events in a magmatic system (e.g. magma mixing, magma decompression, magma degassing, etc.) and their associated eruptions. In simple terms, the phenocryst acts as a “crystal clock” to determine how long a magmatic process took<ref>{{Cite journal |last=Rosen |first=Julia |date=2016-11-18 |title=Crystal clocks |url=https://www.science.org/doi/10.1126/science.354.6314.822 |journal=Science |language=en |volume=354 |issue=6314 |pages=822–825 |doi=10.1126/science.354.6314.822 |issn=0036-8075}}</ref>. Diffusion chronometry takes advantage of the common chemical disequilibrium found in volcanic phenocrysts and examines their kinetic window to obtain timescale information<ref name=":0">{{Cite journal |last=Costa |first=F. |last2=Shea |first2=T. |last3=Ubide |first3=T. |date=2020-04-01 |title=Diffusion chronometry and the timescales of magmatic processes |url=https://www.nature.com/articles/s43017-020-0038-x |journal=Nature Reviews Earth & Environment |language=en |volume=1 |issue=4 |pages=201–214 |doi=10.1038/s43017-020-0038-x |issn=2662-138X}}</ref><ref>{{Cite journal |last=Chakraborty |first=Sumit |date=2008-05-01 |title=Diffusion in Solid Silicates: A Tool to Track Timescales of Processes Comes of Age |url=https://www.annualreviews.org/doi/10.1146/annurev.earth.36.031207.124125 |journal=Annual Review of Earth and Planetary Sciences |language=en |volume=36 |issue=1 |pages=153–190 |doi=10.1146/annurev.earth.36.031207.124125 |issn=0084-6597}}</ref>. Diffusion chronometry should not be confused with [[geospeedometry]]. Both utilize the theory of chemical diffusion, but the latter is more commonly used for analyzing rates of metamorphic events whereas the former is used to analyze features of eruptive events.


Eruptive events can occur on a time scale of days or months which, geologically speaking, is very hard to analyze using traditional [[radiometric dating]] techniques. The benefit with diffusion chronometry is the ability to analyze chemical zoning changes and is only limited by the resolution of the [[scanning electron microscope]] used.<ref>{{cite journal |last1=Rosen |first1=Julia |title=Smudged volcanic crystals offer clues to past eruptions |journal=Science |date=17 November 2016 |doi=10.1126/science.aal0393 }}</ref> From a geological hazard standpoint the use of diffusion chronometry could help in forecasting eruptions by gaining a better understanding of the timescales between magma and crystal interaction.{{fact|date=September 2020}}
Eruptive events can occur on a time scale of days or months which, geologically speaking, is very hard to analyze using traditional [[radiometric dating]] techniques. The use of diffusion chronometry on past eruptions can help in forecasting eruptions by gaining a better understanding of the timescales of magmatic processes and can aid in determining timescales for [[Volcano warning schemes of the United States|volcano alert levels]] during an eruptive event<ref>{{Cite journal |last=Winson |first=Annie E G |last2=Costa |first2=Fidel |last3=Newhall |first3=Christopher G |last4=Woo |first4=Gordon |date=2014-12 |title=An analysis of the issuance of volcanic alert levels during volcanic crises |url=https://appliedvolc.biomedcentral.com/articles/10.1186/s13617-014-0014-6 |journal=Journal of Applied Volcanology |language=en |volume=3 |issue=1 |pages=14 |doi=10.1186/s13617-014-0014-6 |issn=2191-5040}}</ref>.


== Kinetics ==
If there is a chemical gradient present in the crystal, then [[Fick's second law|Fick’s second law]] can be applied to calculate the timescale of the magmatic process that produced the gradient<ref>{{Cite journal |last=Chakraborty |first=Sumit |date=2008-05-01 |title=Diffusion in Solid Silicates: A Tool to Track Timescales of Processes Comes of Age |url=https://www.annualreviews.org/doi/10.1146/annurev.earth.36.031207.124125 |journal=Annual Review of Earth and Planetary Sciences |language=en |volume=36 |issue=1 |pages=153–190 |doi=10.1146/annurev.earth.36.031207.124125 |issn=0084-6597}}</ref> <ref name=":1">{{Cite journal |last=Costa |first=F. |last2=Shea |first2=T. |last3=Ubide |first3=T. |date=2020-04 |title=Diffusion chronometry and the timescales of magmatic processes |url=https://www.nature.com/articles/s43017-020-0038-x |journal=Nature Reviews Earth & Environment |language=en |volume=1 |issue=4 |pages=201–214 |doi=10.1038/s43017-020-0038-x |issn=2662-138X}}</ref><ref name=":2">{{Cite book |last=Lasaga |first=Antonio C. |url=https://www.degruyter.com/document/doi/10.1515/9781400864874/html |title=Kinetic Theory in the Earth Sciences: |date=1998-12-31 |publisher=Princeton University Press |isbn=978-1-4008-6487-4 |doi=10.1515/9781400864874}}</ref>(Chakraborty 2008, Lasaga 2014, Costa et al 2020). Fick’s second law is:


<math>\partial C /\partial t = D*\partial ^2 C /\partial x^2</math>
The diffusion profiles of crystals within a single eruption have been used to constrain the time taken to assemble and erupt a magma reservoir<ref>{{cite journal |last1=Kilgour |first1=G. N. |last2=Saunders |first2=K. E. |last3=Blundy |first3=J. D. |last4=Cashman |first4=K. V. |last5=Scott |first5=B. J. |last6=Miller |first6=C. A. |title=Timescales of magmatic processes at Ruapehu volcano from diffusion chronometry and their comparison to monitoring data |journal=Journal of Volcanology and Geothermal Research |date=1 November 2014 |volume=288 |pages=62–75 |doi=10.1016/j.jvolgeores.2014.09.010 |bibcode=2014JVGR..288...62K |url=https://www.pure.ed.ac.uk/ws/files/17163025/Diffusion_paper_revised.pdf |hdl=20.500.11820/9f936702-74df-4f75-9adf-90b2f70f8907 |hdl-access=free }}</ref> and to track the dynamic events within a magma region over a period of months.<ref>https://www.scopus.com/record/display.uri?eid=2-s2.0-84873377455&origin=inward&txGid=db561414c19d1b0ca5cf45bf9c669691{{dead link|date=September 2020}}</ref>

Where C is the concentration of the element in question, t is time, D is the [[diffusion coefficient]], and x is distance. A common analytical solution to Fick’s second law that is used in diffusion chronometry is<ref name=":2" /> <ref>{{Cite book |last=Crank |first=John |title=The Mathematics of Diffusion |publisher=Oxford Science Publications |year=1979 |isbn=9780198534112 |edition=1st}}</ref>:

<math>C = C_2+((C_1-C_2)/2)*Erfc(x/(2\sqrt{Dt}))</math>

Where C is concentration at the current point, C<sub>1</sub> is the concentration of the depleted region, C<sub>2</sub> is the concentration of the enriched area, Erfc is the complementary error function, D is the diffusion coefficient, and t is the time. A common [[Finite difference method|finite difference]] numerical solution to Fick’s second law is<ref name=":1" />:

<math>C_2new = C_2old + (D\Delta t/ \Delta x^2) * (C_3old - 2C_2old + C_1old)</math>

Where C<sub>2new</sub> is the concentration of the second point at the current timestep, C<sub>2old</sub> is the concentration of the second point at the previous timestep, C<sub>3old</sub> is the concentration of the next point at the previous timestep, C<sub>1old</sub> is the concentration of the previous point at the previous timestep, Δt is the timestep size in seconds, and Δx is the step distance, and D is the diffusion coefficient. If the (DΔt/Δx<sup>2</sup>) term is larger than 0.5, this finite difference model is unstable and will not produce a usable result.

== Experimental Methods ==
Geochemical experiments are performed in order to determine the diffusivity of an element in a mineral<ref name=":3">{{Citation |last=Watson |first=E. Bruce |title=Chemical Diffusion in Magmas: An Overview of Experimental Results and Geochemical Applications |date=1991 |url=http://link.springer.com/10.1007/978-1-4612-3128-8_4 |work=Physical Chemistry of Magmas |volume=9 |pages=120–151 |editor-last=Perchuk |editor-first=Leonid L. |access-date=2023-05-11 |place=New York, NY |publisher=Springer New York |doi=10.1007/978-1-4612-3128-8_4 |isbn=978-1-4612-7806-1 |last2=Baker |first2=Don R. |editor2-last=Kushiro |editor2-first=Ikuo}}</ref>. The three most common types of experiments are diffusion couple experiments, thin-film experiments, and powder source (constant surface) experiments<ref name=":3" />. In the diffusion couple experiment, 2 of the same minerals, with different concentrations of the intended diffusant element, are fused together and put in a high temperature furnace to induce diffusion across the mineral boundaries. [[Thin film]] experiments are set up with a thin film (nm to um thickness) doped with the diffusant element is fused to the surface of the mineral and is put in a high temperature furnace to induce diffusion from the thin film to the mineral. The powder source experiments are set up with the mineral packed into and surrounded by a powder source doped in the diffusant element within an alumina or quartz glass crucible and placed in a high temperature furnace to induce diffusion from the powder source to the mineral. Experiments are typically run at varying temperatures (and to a lesser extent pressure and oxygen fugacity), with the goal of producing an [[Arrhenius plot]]. From the Arrhenius plot the frequency factor (D<sub>o</sub>) and the activation energy (Ea) can be determined for the specific mineral-element pair, these terms are then used in applying the diffusion equation to determine the diffusivity of the element in the mineral at the magmatic conditions of the system.

With the growth of new technology and therefore new experimental methods and analytical methods, the number of available element-mineral diffusivities are growing rapidly<ref>{{Cite journal |last=Brady |first=J. B. |last2=Cherniak |first2=D. J. |date=2010-01-01 |title=Diffusion in Minerals: An Overview of Published Experimental Diffusion Data |url=https://pubs.geoscienceworld.org/rimg/article/72/1/899-920/140905 |journal=Reviews in Mineralogy and Geochemistry |language=en |volume=72 |issue=1 |pages=899–920 |doi=10.2138/rmg.2010.72.20 |issn=1529-6466}}</ref>.

== Measuring Diffusion Profiles ==
Samples are typically prepared as thin sections or crystal separates. [[Thin section|Thin sections]] are thin slices (typically 30 um) of rock that allow the mineral to be analyzed in-situ. Crystal separates involve either crushing a rock or sampling a [[tephra]] layer and then picking through the material to find the required mineral and then mounting it in epoxy for analysis.

Depending on the relative abundance of the element of interest, this will dictate what analytical methods you use<ref>{{Cite journal |last=Cherniak |first=D. J. |last2=Hervig |first2=R. |last3=Koepke |first3=J. |last4=Zhang |first4=Y. |last5=Zhao |first5=D. |date=2010-01-01 |title=Analytical Methods in Diffusion Studies |url=https://pubs.geoscienceworld.org/rimg/article/72/1/107-170/140878 |journal=Reviews in Mineralogy and Geochemistry |language=en |volume=72 |issue=1 |pages=107–170 |doi=10.2138/rmg.2010.72.4 |issn=1529-6466}}</ref>. For major elements, on the order of a few weight percent, the common analytical tool [[electron microprobe]] analyses. For trace elements, on the scale of ppm, the common analytical tool is [[Inductively coupled plasma mass spectrometry|LA-ICP-MS]]. If the study is interested in analyzing the diffusion of isotopes, then [[Secondary ion mass spectrometry|Secondary Ion Mass Spectrometry]] (SIMS) or [[Mass spectrometry|Multi-Collector]] LA-ICP-MS are the most common analytical tools.

When selecting analytical points to measure a diffusion profile, a certain spacing should be used based on the ratio of the diffusion length to spot size (ratio greater than 2) to avoid convolution effects<ref>{{Cite journal |last=Bradshaw |first=Richard W. |last2=Kent |first2=Adam J.R. |date=2017-09 |title=The analytical limits of modeling short diffusion timescales |url=https://linkinghub.elsevier.com/retrieve/pii/S0009254117304163 |journal=Chemical Geology |language=en |volume=466 |pages=667–677 |doi=10.1016/j.chemgeo.2017.07.018}}</ref>.

== Applying Diffusion Chronometry ==
To apply diffusion chronometry an appropriate mineral-element pair which represents the process that is to be timed must be chosen. As seen in ure 7 different mineral-element pairs capture different timescales and therefore different magmatic processes. From there, a temperature estimate for the system in question must be determined. For example, temperature can be calculated through [[geothermobarometry]]. Though the uncertainty on temperature can propagate through calculations and greatly influence the timescale extracted from the crystal. Using experimentally derived D<sub>o</sub> and Ea, temperature is plugged into the diffusion equation to get the diffusivity of the mineral-element pair in the system of question.

<math>D = D_oexp(-Ea/RT)</math>

Where D is the diffusion coefficient, D<sub>o</sub> is the frequency factor specific to your mineral element pair, Ea is the activation energy in joules, R is the gas constant, and T is temperature in kelvin. This diffusivity (D) is then used in the appropriate analytical or numerical solutions to Fick’s second law to calculate a timescale. Diffusion chronometry timescales typically have large uncertainties or ranges of timescales, but this information is critical when forecasting an eruption<ref name=":0" />.

== Recent Applications of Diffusion Chronometry ==
The diffusion profiles of crystals within a single eruption have been used to constrain the time of magmatic processes at a variety of systems. This section will briefly highlight a number of studies where diffusion chronometry was successfully applied. Note that this list is not comprehensive.

Diffusion chronometry was applied to the 1999 eruption of [[Mount Shishaldin|Shishaldin volcano]] and displayed the connection between volcano monitoring signals and diffusion timescales from Fe-Mg interdiffusion in [[Olivine|olivines]] from the eruptive product<ref>{{Cite journal |last=Rasmussen |first=Daniel J. |last2=Plank |first2=Terry A. |last3=Roman |first3=Diana C. |last4=Power |first4=John A. |last5=Bodnar |first5=Robert J. |last6=Hauri |first6=Erik H. |date=2018-03 |title=When does eruption run-up begin? Multidisciplinary insight from the 1999 eruption of Shishaldin volcano |url=https://linkinghub.elsevier.com/retrieve/pii/S0012821X18300050 |journal=Earth and Planetary Science Letters |language=en |volume=486 |pages=1–14 |doi=10.1016/j.epsl.2018.01.001}}</ref>. Diffusion timescales showed that eruption run-up started 9 months before the eruption, with more immediate run-up occurring 50 and 10 days prior to the eruption. The 9-month diffusion timescales correlate well with the start of deep earthquakes, a typical precursor to eruption, the ~50 day timescales correlate well with a temperature anomaly (i.e. intruding magma), steam, and a 5.2 magnitude earthquake, and the ~10 day timescales correspond to rapid remobilization of the magma during its final ascent to the surface. This study by Rassmusen and colleagues in 2018, is a prime example of how diffusion chronometry can aid in forecasting volcanic eruptions.

Shamloo and Till (2019)<ref>{{Cite journal |last=Shamloo |first=Hannah I. |last2=Till |first2=Christy B. |date=2019-04 |title=Decadal transition from quiescence to supereruption: petrologic investigation of the Lava Creek Tuff, Yellowstone Caldera, WY |url=http://link.springer.com/10.1007/s00410-019-1570-x |journal=Contributions to Mineralogy and Petrology |language=en |volume=174 |issue=4 |pages=32 |doi=10.1007/s00410-019-1570-x |issn=0010-7999}}</ref> applied Ba and Sr in sanidine and Ti in quartz diffusion chronometry to the Lava Creek Tuff in [[Yellowstone Caldera]], to understand the timing of eruption triggers for super eruptions. Here they determined that the super eruption occurred years to at most a decade after magma rejuvenation occurred, triggering the Lava Creek Tuff super eruption.

Diffusion chronometry profiles helped reconstruct the dynamics of the magma plumbing system underneath [[Mount Etna]] during 1991-1993<ref>{{Cite journal |last=Kahl |first=Maren |last2=Chakraborty |first2=Sumit |last3=Costa |first3=Fidel |last4=Pompilio |first4=Massimo |date=2011-08 |title=Dynamic plumbing system beneath volcanoes revealed by kinetic modeling, and the connection to monitoring data: An example from Mt. Etna |url=https://linkinghub.elsevier.com/retrieve/pii/S0012821X11002792 |journal=Earth and Planetary Science Letters |language=en |volume=308 |issue=1-2 |pages=11–22 |doi=10.1016/j.epsl.2011.05.008}}</ref>. This study employed Fe-Mg interdiffusion in [[Olivine|olivines]] to determine the timescales of magmatic processes that a number of crystal populations experienced and determined 3 significant timescales. The first timescale tracked magma transfer between differing magmas and occurred 3-6 months before eruption. The second timescale is a short residence time of less than a month which is thought to be the final mixing process. The third and longest timescale, up to 1 year, represents crystals that were recycled through different magmatic environments prior to eruption.


==References==
==References==

Revision as of 20:12, 11 May 2023

Introduction

Diffusion chronometry is a geological technique that examines the chemical zoning within phenocrysts to estimate the duration of events in a magmatic system (e.g. magma mixing, magma decompression, magma degassing, etc.) and their associated eruptions. In simple terms, the phenocryst acts as a “crystal clock” to determine how long a magmatic process took[1]. Diffusion chronometry takes advantage of the common chemical disequilibrium found in volcanic phenocrysts and examines their kinetic window to obtain timescale information[2][3]. Diffusion chronometry should not be confused with geospeedometry. Both utilize the theory of chemical diffusion, but the latter is more commonly used for analyzing rates of metamorphic events whereas the former is used to analyze features of eruptive events.

Eruptive events can occur on a time scale of days or months which, geologically speaking, is very hard to analyze using traditional radiometric dating techniques. The use of diffusion chronometry on past eruptions can help in forecasting eruptions by gaining a better understanding of the timescales of magmatic processes and can aid in determining timescales for volcano alert levels during an eruptive event[4].

Kinetics

If there is a chemical gradient present in the crystal, then Fick’s second law can be applied to calculate the timescale of the magmatic process that produced the gradient[5] [6][7](Chakraborty 2008, Lasaga 2014, Costa et al 2020). Fick’s second law is:

Where C is the concentration of the element in question, t is time, D is the diffusion coefficient, and x is distance. A common analytical solution to Fick’s second law that is used in diffusion chronometry is[7] [8]:

Where C is concentration at the current point, C1 is the concentration of the depleted region, C2 is the concentration of the enriched area, Erfc is the complementary error function, D is the diffusion coefficient, and t is the time. A common finite difference numerical solution to Fick’s second law is[6]:

Where C2new is the concentration of the second point at the current timestep, C2old is the concentration of the second point at the previous timestep, C3old is the concentration of the next point at the previous timestep, C1old is the concentration of the previous point at the previous timestep, Δt is the timestep size in seconds, and Δx is the step distance, and D is the diffusion coefficient. If the (DΔt/Δx2) term is larger than 0.5, this finite difference model is unstable and will not produce a usable result.

Experimental Methods

Geochemical experiments are performed in order to determine the diffusivity of an element in a mineral[9]. The three most common types of experiments are diffusion couple experiments, thin-film experiments, and powder source (constant surface) experiments[9]. In the diffusion couple experiment, 2 of the same minerals, with different concentrations of the intended diffusant element, are fused together and put in a high temperature furnace to induce diffusion across the mineral boundaries. Thin film experiments are set up with a thin film (nm to um thickness) doped with the diffusant element is fused to the surface of the mineral and is put in a high temperature furnace to induce diffusion from the thin film to the mineral. The powder source experiments are set up with the mineral packed into and surrounded by a powder source doped in the diffusant element within an alumina or quartz glass crucible and placed in a high temperature furnace to induce diffusion from the powder source to the mineral. Experiments are typically run at varying temperatures (and to a lesser extent pressure and oxygen fugacity), with the goal of producing an Arrhenius plot. From the Arrhenius plot the frequency factor (Do) and the activation energy (Ea) can be determined for the specific mineral-element pair, these terms are then used in applying the diffusion equation to determine the diffusivity of the element in the mineral at the magmatic conditions of the system.

With the growth of new technology and therefore new experimental methods and analytical methods, the number of available element-mineral diffusivities are growing rapidly[10].

Measuring Diffusion Profiles

Samples are typically prepared as thin sections or crystal separates. Thin sections are thin slices (typically 30 um) of rock that allow the mineral to be analyzed in-situ. Crystal separates involve either crushing a rock or sampling a tephra layer and then picking through the material to find the required mineral and then mounting it in epoxy for analysis.

Depending on the relative abundance of the element of interest, this will dictate what analytical methods you use[11]. For major elements, on the order of a few weight percent, the common analytical tool electron microprobe analyses. For trace elements, on the scale of ppm, the common analytical tool is LA-ICP-MS. If the study is interested in analyzing the diffusion of isotopes, then Secondary Ion Mass Spectrometry (SIMS) or Multi-Collector LA-ICP-MS are the most common analytical tools.

When selecting analytical points to measure a diffusion profile, a certain spacing should be used based on the ratio of the diffusion length to spot size (ratio greater than 2) to avoid convolution effects[12].

Applying Diffusion Chronometry

To apply diffusion chronometry an appropriate mineral-element pair which represents the process that is to be timed must be chosen. As seen in ure 7 different mineral-element pairs capture different timescales and therefore different magmatic processes. From there, a temperature estimate for the system in question must be determined. For example, temperature can be calculated through geothermobarometry. Though the uncertainty on temperature can propagate through calculations and greatly influence the timescale extracted from the crystal. Using experimentally derived Do and Ea, temperature is plugged into the diffusion equation to get the diffusivity of the mineral-element pair in the system of question.

Where D is the diffusion coefficient, Do is the frequency factor specific to your mineral element pair, Ea is the activation energy in joules, R is the gas constant, and T is temperature in kelvin. This diffusivity (D) is then used in the appropriate analytical or numerical solutions to Fick’s second law to calculate a timescale. Diffusion chronometry timescales typically have large uncertainties or ranges of timescales, but this information is critical when forecasting an eruption[2].

Recent Applications of Diffusion Chronometry

The diffusion profiles of crystals within a single eruption have been used to constrain the time of magmatic processes at a variety of systems. This section will briefly highlight a number of studies where diffusion chronometry was successfully applied. Note that this list is not comprehensive.

Diffusion chronometry was applied to the 1999 eruption of Shishaldin volcano and displayed the connection between volcano monitoring signals and diffusion timescales from Fe-Mg interdiffusion in olivines from the eruptive product[13]. Diffusion timescales showed that eruption run-up started 9 months before the eruption, with more immediate run-up occurring 50 and 10 days prior to the eruption. The 9-month diffusion timescales correlate well with the start of deep earthquakes, a typical precursor to eruption, the ~50 day timescales correlate well with a temperature anomaly (i.e. intruding magma), steam, and a 5.2 magnitude earthquake, and the ~10 day timescales correspond to rapid remobilization of the magma during its final ascent to the surface. This study by Rassmusen and colleagues in 2018, is a prime example of how diffusion chronometry can aid in forecasting volcanic eruptions.

Shamloo and Till (2019)[14] applied Ba and Sr in sanidine and Ti in quartz diffusion chronometry to the Lava Creek Tuff in Yellowstone Caldera, to understand the timing of eruption triggers for super eruptions. Here they determined that the super eruption occurred years to at most a decade after magma rejuvenation occurred, triggering the Lava Creek Tuff super eruption.

Diffusion chronometry profiles helped reconstruct the dynamics of the magma plumbing system underneath Mount Etna during 1991-1993[15]. This study employed Fe-Mg interdiffusion in olivines to determine the timescales of magmatic processes that a number of crystal populations experienced and determined 3 significant timescales. The first timescale tracked magma transfer between differing magmas and occurred 3-6 months before eruption. The second timescale is a short residence time of less than a month which is thought to be the final mixing process. The third and longest timescale, up to 1 year, represents crystals that were recycled through different magmatic environments prior to eruption.

References

  1. ^ Rosen, Julia (2016-11-18). "Crystal clocks". Science. 354 (6314): 822–825. doi:10.1126/science.354.6314.822. ISSN 0036-8075.
  2. ^ a b Costa, F.; Shea, T.; Ubide, T. (2020-04-01). "Diffusion chronometry and the timescales of magmatic processes". Nature Reviews Earth & Environment. 1 (4): 201–214. doi:10.1038/s43017-020-0038-x. ISSN 2662-138X.
  3. ^ Chakraborty, Sumit (2008-05-01). "Diffusion in Solid Silicates: A Tool to Track Timescales of Processes Comes of Age". Annual Review of Earth and Planetary Sciences. 36 (1): 153–190. doi:10.1146/annurev.earth.36.031207.124125. ISSN 0084-6597.
  4. ^ Winson, Annie E G; Costa, Fidel; Newhall, Christopher G; Woo, Gordon (2014-12). "An analysis of the issuance of volcanic alert levels during volcanic crises". Journal of Applied Volcanology. 3 (1): 14. doi:10.1186/s13617-014-0014-6. ISSN 2191-5040. {{cite journal}}: Check date values in: |date= (help)CS1 maint: unflagged free DOI (link)
  5. ^ Chakraborty, Sumit (2008-05-01). "Diffusion in Solid Silicates: A Tool to Track Timescales of Processes Comes of Age". Annual Review of Earth and Planetary Sciences. 36 (1): 153–190. doi:10.1146/annurev.earth.36.031207.124125. ISSN 0084-6597.
  6. ^ a b Costa, F.; Shea, T.; Ubide, T. (2020-04). "Diffusion chronometry and the timescales of magmatic processes". Nature Reviews Earth & Environment. 1 (4): 201–214. doi:10.1038/s43017-020-0038-x. ISSN 2662-138X. {{cite journal}}: Check date values in: |date= (help)
  7. ^ a b Lasaga, Antonio C. (1998-12-31). Kinetic Theory in the Earth Sciences:. Princeton University Press. doi:10.1515/9781400864874. ISBN 978-1-4008-6487-4.
  8. ^ Crank, John (1979). The Mathematics of Diffusion (1st ed.). Oxford Science Publications. ISBN 9780198534112.
  9. ^ a b Watson, E. Bruce; Baker, Don R. (1991), Perchuk, Leonid L.; Kushiro, Ikuo (eds.), "Chemical Diffusion in Magmas: An Overview of Experimental Results and Geochemical Applications", Physical Chemistry of Magmas, vol. 9, New York, NY: Springer New York, pp. 120–151, doi:10.1007/978-1-4612-3128-8_4, ISBN 978-1-4612-7806-1, retrieved 2023-05-11
  10. ^ Brady, J. B.; Cherniak, D. J. (2010-01-01). "Diffusion in Minerals: An Overview of Published Experimental Diffusion Data". Reviews in Mineralogy and Geochemistry. 72 (1): 899–920. doi:10.2138/rmg.2010.72.20. ISSN 1529-6466.
  11. ^ Cherniak, D. J.; Hervig, R.; Koepke, J.; Zhang, Y.; Zhao, D. (2010-01-01). "Analytical Methods in Diffusion Studies". Reviews in Mineralogy and Geochemistry. 72 (1): 107–170. doi:10.2138/rmg.2010.72.4. ISSN 1529-6466.
  12. ^ Bradshaw, Richard W.; Kent, Adam J.R. (2017-09). "The analytical limits of modeling short diffusion timescales". Chemical Geology. 466: 667–677. doi:10.1016/j.chemgeo.2017.07.018. {{cite journal}}: Check date values in: |date= (help)
  13. ^ Rasmussen, Daniel J.; Plank, Terry A.; Roman, Diana C.; Power, John A.; Bodnar, Robert J.; Hauri, Erik H. (2018-03). "When does eruption run-up begin? Multidisciplinary insight from the 1999 eruption of Shishaldin volcano". Earth and Planetary Science Letters. 486: 1–14. doi:10.1016/j.epsl.2018.01.001. {{cite journal}}: Check date values in: |date= (help)
  14. ^ Shamloo, Hannah I.; Till, Christy B. (2019-04). "Decadal transition from quiescence to supereruption: petrologic investigation of the Lava Creek Tuff, Yellowstone Caldera, WY". Contributions to Mineralogy and Petrology. 174 (4): 32. doi:10.1007/s00410-019-1570-x. ISSN 0010-7999. {{cite journal}}: Check date values in: |date= (help)
  15. ^ Kahl, Maren; Chakraborty, Sumit; Costa, Fidel; Pompilio, Massimo (2011-08). "Dynamic plumbing system beneath volcanoes revealed by kinetic modeling, and the connection to monitoring data: An example from Mt. Etna". Earth and Planetary Science Letters. 308 (1–2): 11–22. doi:10.1016/j.epsl.2011.05.008. {{cite journal}}: Check date values in: |date= (help)