{"title":"Earth Observation Applications and Global Policy Frameworks","authors":"","doi":"10.1002/9781119536789","DOIUrl":"https://doi.org/10.1002/9781119536789","url":null,"abstract":"","PeriodicalId":12504,"journal":{"name":"Geophysical Monograph Series","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-08-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77901087","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
J. Watkins, J. Christensen, D. DePaolo, F. Ryerson
Laboratory experiments were used to investigate diffusive isotopic fractionation of calcium and potassium in phonoliterhyolite diffusion couples. The starting compositions have very different SiO2 and K2O, but similar CaO. These were juxtaposed and held in a completely molten state at 1450°C and 1.0 GPa for durations of 2.5 or 6 hours in a piston cylinder apparatus. The resulting majorelement diffusion profiles exhibit many complexities, including uphill diffusion of all major oxide components. The diffusive fluxes for SiO2, K2O, and CaO were modeled using a published modified effective binary diffusion model, whereby diffusion is driven by activity gradients that are solely a function of the timeevolving SiO2 concentration. Both Ca and K exhibit large diffusive isotope effects that can be explained by imposing a mass dependence on the diffusion coefficients used to model the majorelement profiles. The mass dependence is parameterized in terms of the inverse ratio of the isotope masses raised to an empirically determined exponent β (i.e., Di/Dj = [mj/mi] β). Our results confirm that β factors vary depending on the element as well as liquid composition, and that large diffusive isotope effects can arise even in the absence of a large initial concentration gradient. The retrieved β factor for Ca (0.10 ± 0.02) is typical of Ca in natural silicate liquids, whereas the β factor for K (0.25 ± 0.03) is the highest value yet reported, suggesting that large diffusive K isotope effects may yet be found in highT environments. 1 Department of Earth Sciences, University of Oregon, Eugene, Oregon, USA 2 Earth and Environmental Science Area, Energy Geosciences Division, Lawrence Berkeley National Laboratory, Berkeley, California, USA 3 Department of Earth and Planetary Science, University of California, Berkeley, California, USA 4 Atmospheric, Earth, and Energy Division, Lawrence Livermore National Laboratory, Livermore, California, USA melting and (re)crystallization. Experimental studies have shown that diffusion is capable of generating measurable (subpermil) to large (tens of permil) kinetic isotopic fractionations that can account for some of this variability, and detailed knowledge of these effects can yield unique insights into the molecular level controls on diffusive transport and the role of kinetics in the formation of minerals in high temperature settings (Antonelli et al., 2019b; Barrat et al., 2005; Beck et al., 2006; Chen et al., 2018; Chopra et al., 2012; Dauphas, 2007; Dauphas et al., 2010; Gallagher & Elliott, 2009; Gao et al., 2011; Jeffcoate et al., 2007; Kil et al., 2016; Lundstrom et al., 2005; Marschall et al., 2007; Mueller et al., 2014; Oeser et al., 2015; Parkinson et al., 2007; Richter et al., 2009, 2014, 2016, 2017; Roskosz et al., 2006; Rudnick & Ionov, 2007; Sio et al., 2013; 28 ISOTOPIC CONSTRAINTS ON EARTH SYSTEM PROCESSES Su et al., 2016; Teng et al., 2006, 2011; Wu et al., 2018; Zhao et al., 2017). Current knowledge of
利用室内实验研究了钙、钾在浮岩扩散对中的扩散同位素分馏。初始组分SiO2和K2O差异很大，但CaO相似。这些并置，并保持在完全熔融状态在1450°C和1.0 GPa在一个活塞缸装置的持续时间为2.5或6小时。所得到的元素扩散曲线表现出许多复杂性，包括所有主要氧化物成分的上坡扩散。SiO2、K2O和CaO的扩散通量使用已发表的修正有效二元扩散模型进行建模，其中扩散由活性梯度驱动，活性梯度仅是SiO2浓度随时间变化的函数。Ca和K都表现出很大的扩散同位素效应，这可以通过施加质量依赖于用于模拟元素剖面的扩散系数来解释。质量依赖性参数化为同位素质量与经验确定的指数β的反比(即Di/Dj = [mj/mi] β)。我们的结果证实，β因子随元素和液体组成的不同而变化，即使在没有大的初始浓度梯度的情况下，也会产生大的扩散同位素效应。Ca的β因子(0.10±0.02)是天然硅酸盐液体中典型的Ca，而K的β因子(0.25±0.03)是迄今为止报道的最高值，这表明在高环境中可能存在较大的扩散K同位素效应。1美国俄勒冈州尤金市俄勒冈大学地球科学系2美国加利福尼亚州伯克利市劳伦斯伯克利国家实验室地球与环境科学区能源地球科学部3美国加利福尼亚州伯克利市加利福尼亚大学地球与行星科学系4美国加利福尼亚州利弗莫尔市劳伦斯利弗莫尔国家实验室大气、地球和能源部熔融和(再)结晶。实验研究表明，扩散能够产生可测量的(亚permil)到大的(数十permil)动力学同位素分异，可以解释这种变化的一些原因，对这些影响的详细了解可以对扩散运输的分子水平控制和动力学在高温环境下矿物形成中的作用产生独特的见解(Antonelli等人，2019b;Barrat et al.， 2005;Beck et al.， 2006;Chen et al.， 2018;Chopra et al.， 2012;道法斯,2007;Dauphas等人，2010;Gallagher & Elliott, 2009;Gao et al.， 2011;Jeffcoate et al.， 2007;Kil等人，2016;Lundstrom等人，2005;marshall et al.， 2007;Mueller et al.， 2014;Oeser et al.， 2015;帕金森等人，2007;Richter et al.， 2009、2014、2016、2017;Roskosz et al.， 2006;Rudnick & Ionov, 2007;Sio et al.， 2013;28地球系统过程的同位素约束[j] .科学通报，2016;Teng等，2006,2011;Wu et al.， 2018;赵等人，2017)。目前关于熔融硅酸盐中扩散同位素分馏的知识是基于几种元素(Ca、Fe、Mg、Li和Si)和硅酸盐熔体成分(参见Watkins等人，2017年的综述)。质量对扩散系数的依赖随阳离子和液体成分的不同而不同。例如，在玄武岩扩散对中，主要元素(Ca, Fe, Mg)的稳定同位素的质量分辨(β < 0.075)小于微量元素Li的稳定同位素(β≈0.215)(Richter et al.， 2003,2009;Watkins et al.， 2009)。在简化的硅酸盐液体中，已经发现Ca和Mg的β因子在0.05和0.21之间变化，这取决于液体成分，并且与“溶剂标准化”扩散率(例如，DCa/DSi)相关，这表明快速扩散的元素表现出更大的质量辨别，因为它们作为单个原子或小运动运动，其扩散与主要熔体结构/组分解耦(Goel等人，2012;Watkins et al.， 2009, 2011)。这个简单的关系为在扩散模型中选择合适的β值和预测自然界中可能存在较大扩散同位素效应的地方提供了一个有用的框架。在这篇文章中，我们提出了新的扩散偶实验的结果，并考虑了两个激励因素。首先，溶剂归一化扩散率只能在有一个大的初始浓度梯度感兴趣的组分和有效的二元扩散模型适用的情况下定义。然而，我们意识到，即使在没有大的初始浓度梯度的情况下，也可能出现大的扩散同位素效应。一个这样的例子是在乌干达黄岩扩散偶联实验中，由于CaO与Al2O3的扩散偶联，Ca同位素被分馏了~ 2‰(Watkins et al.， 2009)。 这种强烈的多组分扩散效应值得进一步研究，因为它们可能有助于在高环境中形成的矿物内部和之间的同位素变化。其次，对于大量存在的元素，Di/DSi的比率往往较低，接近于一，因为一种主要元素的净通量需要液体中其他主要成分的协同运动。Li的β因子可以很高，因为它扩散快，它可以快速扩散，因为它的存在是微量的。同样的道理也适用于Ca;在实验中，Ca的β因子接近Li的β因子，其中Ca以少量存在(~ 2 wt%);Watkins et al.， 2011)。这些观察结果提出了一个问题，即(通常)快速扩散的K2O组分是否会像Li一样具有高β因子，或者它是否会像其他主要元素一样具有接近零的β因子。2.2. 方法
{"title":"Isotopic Constraints on Earth System Processes","authors":"J. Watkins, J. Christensen, D. DePaolo, F. Ryerson","doi":"10.1002/9781119595007","DOIUrl":"https://doi.org/10.1002/9781119595007","url":null,"abstract":"Laboratory experiments were used to investigate diffusive isotopic fractionation of calcium and potassium in phonoliterhyolite diffusion couples. The starting compositions have very different SiO2 and K2O, but similar CaO. These were juxtaposed and held in a completely molten state at 1450°C and 1.0 GPa for durations of 2.5 or 6 hours in a piston cylinder apparatus. The resulting majorelement diffusion profiles exhibit many complexities, including uphill diffusion of all major oxide components. The diffusive fluxes for SiO2, K2O, and CaO were modeled using a published modified effective binary diffusion model, whereby diffusion is driven by activity gradients that are solely a function of the timeevolving SiO2 concentration. Both Ca and K exhibit large diffusive isotope effects that can be explained by imposing a mass dependence on the diffusion coefficients used to model the majorelement profiles. The mass dependence is parameterized in terms of the inverse ratio of the isotope masses raised to an empirically determined exponent β (i.e., Di/Dj = [mj/mi] β). Our results confirm that β factors vary depending on the element as well as liquid composition, and that large diffusive isotope effects can arise even in the absence of a large initial concentration gradient. The retrieved β factor for Ca (0.10 ± 0.02) is typical of Ca in natural silicate liquids, whereas the β factor for K (0.25 ± 0.03) is the highest value yet reported, suggesting that large diffusive K isotope effects may yet be found in highT environments. 1 Department of Earth Sciences, University of Oregon, Eugene, Oregon, USA 2 Earth and Environmental Science Area, Energy Geosciences Division, Lawrence Berkeley National Laboratory, Berkeley, California, USA 3 Department of Earth and Planetary Science, University of California, Berkeley, California, USA 4 Atmospheric, Earth, and Energy Division, Lawrence Livermore National Laboratory, Livermore, California, USA melting and (re)crystallization. Experimental studies have shown that diffusion is capable of generating measurable (subpermil) to large (tens of permil) kinetic isotopic fractionations that can account for some of this variability, and detailed knowledge of these effects can yield unique insights into the molecular level controls on diffusive transport and the role of kinetics in the formation of minerals in high temperature settings (Antonelli et al., 2019b; Barrat et al., 2005; Beck et al., 2006; Chen et al., 2018; Chopra et al., 2012; Dauphas, 2007; Dauphas et al., 2010; Gallagher & Elliott, 2009; Gao et al., 2011; Jeffcoate et al., 2007; Kil et al., 2016; Lundstrom et al., 2005; Marschall et al., 2007; Mueller et al., 2014; Oeser et al., 2015; Parkinson et al., 2007; Richter et al., 2009, 2014, 2016, 2017; Roskosz et al., 2006; Rudnick & Ionov, 2007; Sio et al., 2013; 28 ISOTOPIC CONSTRAINTS ON EARTH SYSTEM PROCESSES Su et al., 2016; Teng et al., 2006, 2011; Wu et al., 2018; Zhao et al., 2017). Current knowledge of","PeriodicalId":12504,"journal":{"name":"Geophysical Monograph Series","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81242710","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Douglas Alsdorf, Merci Beaucoup, Raphael M. Tshimanga, G. D. M. N'kaya, Douglas Alsdorf
{"title":"Hydrologie, Climat et Biogéochimie du Bassin du Congo","authors":"Douglas Alsdorf, Merci Beaucoup, Raphael M. Tshimanga, G. D. M. N'kaya, Douglas Alsdorf","doi":"10.1002/9781119842125","DOIUrl":"https://doi.org/10.1002/9781119842125","url":null,"abstract":"","PeriodicalId":12504,"journal":{"name":"Geophysical Monograph Series","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-02-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89395049","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Isotopes provide valuable insights into the complex geochemical behavior of iron. To put the wealth of Fe isotopic data measured in natural samples into a quantitative framework, it is important to know how iron isotopes are fractionated at equilibrium between co-existing iron-bearing phases or species. These isotopic equilibrium fractionation factors can be derived from isotopic exchange experiments and the study of natural samples, but can also be calculated from partition functions, whose main contribution is the vibrational energy. This approach relies on first-principles calculations (atomistic modeling based on quantum mechanics) and vibrational spectroscopies (Mössbauer and Nuclear Resonant Inelastic X-ray Scattering – NRIXS). Comparison of the results obtained from these techniques provides confidence in their reliability and improves our understanding of the parameters controlling iron isotopic fractionation among coexisting phases. After an introduction to the theory and methods applied in this field, the chapter will review how NRIXS and first-principles calculations help interpret iron isotopic variations in natural rocks and minerals. At equilibrium, the heavy isotopes of iron will concentrate in the phases where the interatomic force constants are the greatest, meaning in the phases where iron bonds are the stiffest. Higher oxidation state, higher covalency, and lower coordination (shorter bond length) tend to be associated with stronger bonds and heavy iron isotope enrichments.
{"title":"Magma Redox Geochemistry","authors":"M. Blanchard, N. Dauphas","doi":"10.1002/9781119473206","DOIUrl":"https://doi.org/10.1002/9781119473206","url":null,"abstract":"Isotopes provide valuable insights into the complex geochemical behavior of iron. To put the wealth of Fe isotopic data measured in natural samples into a quantitative framework, it is important to know how iron isotopes are fractionated at equilibrium between co-existing iron-bearing phases or species. These isotopic equilibrium fractionation factors can be derived from isotopic exchange experiments and the study of natural samples, but can also be calculated from partition functions, whose main contribution is the vibrational energy. This approach relies on first-principles calculations (atomistic modeling based on quantum mechanics) and vibrational spectroscopies (Mössbauer and Nuclear Resonant Inelastic X-ray Scattering – NRIXS). Comparison of the results obtained from these techniques provides confidence in their reliability and improves our understanding of the parameters controlling iron isotopic fractionation among coexisting phases. After an introduction to the theory and methods applied in this field, the chapter will review how NRIXS and first-principles calculations help interpret iron isotopic variations in natural rocks and minerals. At equilibrium, the heavy isotopes of iron will concentrate in the phases where the interatomic force constants are the greatest, meaning in the phases where iron bonds are the stiffest. Higher oxidation state, higher covalency, and lower coordination (shorter bond length) tend to be associated with stronger bonds and heavy iron isotope enrichments.","PeriodicalId":12504,"journal":{"name":"Geophysical Monograph Series","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87779597","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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