Stochastic analysis of the effect of heterogeneity and fractures on radionuclide transport in a low-permeability clay layer

Deep low-permeability clay layers are considered as safe environments for disposal of high-level radioactive waste. In Belgium, the Boom Clay is a candidate host rock for deep geological disposal. In this study, we analyze the effects of fractures and spatially variable hydraulic conductivity on radionuclide migration through the clay. Fracture geometry and properties are simulated with Monte Carlo simulation. The heterogeneity of hydraulic conductivity is simulated by direct sequential co-simulation using measurements of hydraulic conductivity and four types of secondary variables. The hydraulic conductivity and fracture simulations are used as input for a transport model. Radionuclide fluxes computed with this heterogeneous model are compared with fluxes obtained with a homogeneous model. The output fluxes of the heterogeneous model differ at most 8% from the homogeneous model. The main safety function of the Boom Clay is thus not affected by the fractures and the spatial variability of hydraulic conductivity.     

多个相关随机参数的空间变异性对溶质运移的影响

根据给定渗透系数、孔隙度以及吸附系数的概率分布,采用顺序高斯模拟生成相关的多参数随机场的实现,作为地下水流和溶质运移模型的输入参数,对污染物浓度进行随机分析。研究结果表明,与仅考虑渗透系数空间变异性相比,考虑相关的多参数空间变异性导致污染羽的扩散程度有显著不同。当孔隙度与渗透系数呈正相关关系时,会减少污染羽的扩散程度,反之,当孔隙度与渗透系数为负相关关系时,会加剧污染羽的扩散程度。吸附系数也是如此。在考虑吸附系数的空间变异性之后,污染羽的分布表现出拖尾现象。同时考虑渗透系数、孔隙度以及吸附系数空间变异性时,孔隙度非均质性对溶质运移的影响较吸附系数非均质性的影响更大。     

Stochastic analysis of the effect of spatial variability of diffusion parameters on radionuclide transport in a low permeability clay layer

Most studies that incorporate subsurface heterogeneity in groundwater flow and transport models only analyze and simulate the spatial variability of hydraulic conductivity. Heterogeneity of the other flow and transport parameters are usually neglected. This approach is often justified, but there are, however, cases in which disregarding the heterogeneity of the other flow and transport parameters can be questionable. In low permeability media, for instance, diffusion is often the dominant transport mechanism. It therefore seems logical to incorporate the spatial variability of the diffusion parameters in the transport model. This study therefore analyses and simulates the spatial variability of the effective diffusion coefficient and the diffusion accessible porosity with geostatistical techniques and incorporates their heterogeneity in the transport model of a low permeability formation. The formation studied was Boom clay (Belgium), a candidate host rock for the deep geological disposal of high-level radioactive waste. The calculated output radionuclide fluxes of this model are compared with the fluxes calculated with a homogeneous model and a model with a heterogeneous hydraulic conductivity distribution. This analysis shows that the heterogeneity of the diffusion parameters has a much larger effect on the calculated output radionuclide fluxes than the heterogeneity of hydraulic conductivity in the low permeability medium under study.     

运移参数对GCL中污染物运移的影响研究

分析了运移参数的变化对GCL中污染物运移的影响。从衬垫底部浓度比、对流和扩散通量、污染物累积运移量等方面,对污染物在GCL中的运移进行了计算。结果表明,减小渗透系数和扩散系数可以有效减缓衬垫底部浓度比的增加速度。渗透系数对对流通量的大小、扩散通量的变化速度的影响较大;扩散系数主要影响最大扩散通量。当渗透系数较大时,可以忽略扩散累积运移量,用对流累积运移量代替总累积运移量引起的误差很小。当渗透系数较小时,忽略扩散运移量可能产生较大的误差,尤其是在扩散系数也较大的情况下误差更加明显。     

低渗透岩土有效扩散系数的室内测定与分析

低渗透岩土是水文地质及环境地质研究的重点关注对象,有效扩散系数是研究低渗透岩土的关键参数之一。文章以原状黏土和粉砂质黏土为例,以Cl-为示踪剂,利用自主研发的室内径向扩散实验装置,建立Cl-径向运移模型,模拟其扩散运移过程。以实验模型为初始条件和边界条件,利用COMSOL软件模拟溶质理论浓度随时间变化的曲线,与实验数据进行拟合,利用绝对残差平均值进行理论浓度与实测值拟合优度统计,提取试样的有效扩散系数。结果表明:试样塘沽G1孔101.2~101.5 m、苏北SY1孔147.1~147.3 m、170.48~170.68 m的有效扩散系数分别为6.0×10-10 m2/s、4.5×10-10 m2/s、3.9×10-10 m2/s 时,理论浓度的绝对残差平均值最小,且孔隙度和有效扩散系数高度相关,进一步证明了该实验方法的可行性。同时,利用Archie定律有效孔隙度与有效扩散系数的关系,取常量n=1.9,预测了试验样品的有效孔隙度,分别为0.26,0.19,0.16。     

The effect of dislocations on bulk diffusion in feldspars during metamorphism

ABSTRACT There is no significant difference in the diffusion profiles across albite-adularia bicrystals that were simultaneously deformed at a strain rate of 10^-6S^-1 and those from hydrostatic experiments at the same conditions (1500 MPa and 1000°C for 156 h). This indicates that the bulk alkali diffusion rate, which is the sum of lattice diffusion (D, ₁) and dislocation pipe diffusion (Dp), is not significantly enhanced by dislocations at these conditions, and that the maximum value for the ratio of D_p/D₁ is about 10⁵. This is equal to the value previously reported for‘oxygen’diffusion in albite. If this ratio is independent of temperature, the contribution of either static (pre-deformed) or moving (syn-deformed) dislocations to the bulk diffusion rate of alkalis is probably minor at all metamorphic conditions. For Al and Si diffusion the ratio of D_p/D₁ may be larger if D₁ is lower. Thus a significant contribution from dislocations to bulk diffusion cannot be ruled out, especially during simultaneous deformation.     

The influence of conceptual model of sedimentary formation hydraulic heterogeneity on contaminant transport simulation

Development of heterogeneity model of layered sandy-clay formation and impact of this model on transport is considered. The lithological data of more than 250 wells that captured 300 meters formation at the investigated area of 40 km² are used for model of heterogeneity construction. Two models of heterogeneity were developed with using these well data: TP/MC model based on 3D Markov chain simulation for four hydrofacies and 2D kriging interpolation of thicknesses of elementary lithological layers. Simulation of conservative transport by particle tracking algorithm shows that horizontal transport along layers is similar for both models. The main difference is in vertical transport cross formation bedding. The kriging interpolation model gives more conservative results than TP/MC model due to larger characteristic horizontal length of layers in the kriging model. As the result vertical effective hydraulic conductivity of formation is in two times larger and the first particle arriving time is in four times faster in TP/MC model.     

The effect of aquifer heterogeneity on natural attenuation rate of BTEX

Monitored natural attenuation can be a viable option for remediation of groundwater contamination by BTEX compounds. Under the field conditions, the rate of contaminant mass attenuation through natural processes, such as biodegradation, to a large extent affected by the groundwater flow regime, which is primarily controlled by the aquifer heterogeneity. Numerical simulation techniques were used to describe quantitatively the relationship between biodegradation rate of BTEX and aquifer heterogeneity. Different levels of aquifer heterogeneity were described by random hydraulic conductivity fields (K) having different statistical parameters, the coefficient of variation (CV) and the correlation length (h). The Turning Bands Algorithm was used to generate such K fields. Visual MODFLOW/RT3D was used to simulate the fate and transport of dissolved BTEX plume within heterogeneous aquifers. The multispecies reactive transport approach described BTEX degradation using multiple terminal electron-accepting processes. First-order biodegradation rate constants were calculated from simulated BTEX plumes in heterogeneous flow fields. The results showed that aquifer heterogeneity significantly affected biodegradation rate; it decreased with increasing CV when h was in the range of up to 12 m, whereas it increased with increasing CV when h was greater than about 12 m. For well characterized aquifers, this finding could be of great value in assessing the effectiveness of natural attenuation during feasibility studies at BTEX contaminated sites.     

矿物中稀土元素扩散作用的理论研究及其扩散参数的预测

矿物中的微量元素在地质环境下能否保持有效封闭,主要取决于其扩散性质,而稀土元素(REE)是探讨地质作用过程及其物理化学条件等重要的示踪剂,查明其在不同矿物中的扩散行为对于地学研究具有重要意义。本文通过分析矿物晶格结构和离子类型对元素扩散行为的制约规律,探讨了REE在不同矿物中的扩散迁移。在此基础上,利用多元统计分析方法得出扩散参数与扩散体系不同晶体化学参数之间的关系方程,建立了计算1atm、无水环境下REE在不同矿物中扩散参数的多变量模型,由此模型预测的REE在不同矿物中的扩散参数E和lnD0的值,与实验测定结果在实验误差范围内具有很好的一致性。与以往的预测模型相比,多变量模型能更全面地反映扩散体系晶体化学因素对扩散速率的制约。此外本研究结果显示,REE在矿物晶格中扩散作用的主要影响因素是阳离子,而非当前认为的阴离子。     

氯化物对方解石和白云石矿物溶解度的影响

借助PHREEQC软件,文章对方解石、白云石分别在无CO2和大气PCO2条件下NaCl、KCl、CaCl2和MgCl2溶液中的溶解度进行了模拟计算,结果显示:方解石在NaCl、KCl、和MgCl2溶液中以及白云石在NaCl、KCl溶液中的溶解度比纯水中大得多,其原因主要是盐效应。由于同离子效应,在CaCl2溶液中可降低方解石溶解度,而白云石在较高浓度CaCl2或MgCl2溶液中,虽发生同离子效应,其溶解度仍较纯水中有不同程度提高。模拟还显示,方解石在MgCl2溶液中以及白云石在CaCl2溶液中溶解时将分别发生白云石化和去白云石化反应,从而促使不全等溶解继续发生。在常规离子中,按方解石、白云石溶解度提高发挥作用的重要性排序为:阴离子中都是SO24->Cl-;对于方解石溶解,阳离子中Mg2+>Na+>K+>Ca2+;对于白云石溶解,当PCO2=0或PCO2=10-3.5bar且CaCl2浓度大约在1.5mol/L以下时,Na+>K+>Ca2+>Mg2+;当PCO2=10-3.5bar且CaCl2浓度大约在1.5mol/L以上时,Ca2+>Na+>K+>Mg2+。     

砾石土层中注浆扩散参数的研究

采用注浆模拟试验与数值分析等研究方法,探讨了砾石土层中注浆的注浆量、浆液扩散半径及注浆形成的结石体抗压强度等参数预测计算模型,并设计试验对其进行了验证。试验结果表明,砾石土层中注浆的注浆量、浆液扩散半径及结石体的抗压强度等参数预测计算模型计算的注浆量、浆液扩散半径与注浆结石体抗压强度的理论值与试验实测值间虽分别有10%、5%、10%左右的差异,但均相差不大,因此,可用来预测砾石土层实际注浆工程中的注浆量、浆液扩散半径及注浆形成的结石体的抗压强度等参数。研究成果不仅可为砾石土层实际注浆工程实践提供理论支撑,还可为砾石土诱发的滑坡、泥石流等灾害的防灾减灾提供技术参考。     

Influence of temporal fluctuations and spatial heterogeneity on pollution transport in porous media

The combined influence of temporal fluctuations and spatial heterogeneity on non-reactive solute transport mechanisms in porous media can be understood by performing simulations of steady and unsteady flow and transport in heterogeneous media. The study focuses on issues such as the degree of heterogeneity, correlation length, separation of the combined effects of temporal and spatial variations, and ergodicity conditions under unsteady flow conditions. It is shown that the effect of temporal variations on solute transport is masked by the strong effect of spatial heterogeneity. There is no obvious difference in plume shape between steady and unsteady flow conditions; the first and the second spatial moments of the plume of the unsteady-state flow condition fluctuate around the steady-state flow condition with the same period of oscillations as the input signal at small storage coefficient (S????0.001). At a relatively high standard deviation in hydraulic conductivity and a small storage coefficient, the unsteady flow condition sharpens the temporal variations in macrodispersion coefficients. The magnitude of the longitudinal macrodispersion coefficient under unsteady flow condition is almost doubled at the maximum values. However, the transverse macrodispersion coefficient fluctuates around zero. The Kubo number and Peclet number ranges are 1.2?C64 and 10?C250, respectively.     

淮南煤田太原组铝质泥岩元素地球化学特征

华北聚煤盆地南缘淮南煤田晚石炭世-早二叠世太原组含煤岩系普遍沉积铝质泥岩,然而,对于多层铝质泥岩的形成条件及其地球化学特征尚未开展深入研究。在本次研究中,系统采集了淮南煤田张集煤矿补Y1钻孔岩心样品,采用XRF和ICP-OES、ICP-MS分别测试了主量元素和微量元素,对铝质泥岩地球化学特征及其地质成因进行分析。结果表明：不同层位的铝质泥岩来源于同一源区,铝土质泥岩可能受到了更强烈的红土化作用导致其明显偏离SiO₂/Al₂O₃和Fe₂O₃/Al₂O₃趋势线;Sr/Ba的结果表明铝质泥岩是在不稳定的海陆交互沉积环境下形成的,V/Cr和V/（V+Ni）的结果表明铝质泥岩是在贫氧到厌氧的沉积环境中形成的;综合主量元素和微量元素的结果,表明了不同层位铝质泥岩的母岩可能是附近古陆的中酸性火成岩,母岩风化产物经迁移至淮南地区沉积成岩。     

The effect of aqueous metal-chlorophenolate complexation on contaminant transport in groundwater systems

Aqueous metals and chlorophenols are common co-contaminants of groundwater systems. However, the importance of aqueous metal-chlorophenolate complexation cannot be accurately assessed because the stability constants for environmentally important aqueous metal-phenolate and metal-chlorophenolate complexes have not been measured. In order to determine the role these complexes play in contaminant transport, this study applies a correlation technique to the limited data that do exist to estimate the stabilities of metal-chlorophenolate complexes of environmental interest. Speciation calculations that are based on these estimated stability constants indicate that aqueous metal-chlorophenolate complexation may significantly affect both aqueous metal and dissolved chlorophenolate species distributions. Therefore, aqueous metal-chlorophenolate complexation may affect the extent of adsorption of both metals and chlorophenolates onto mineral surfaces. In addition, aqueous complexation may significantly enhance dissolution of aquifer aluminosilicate minerals. This study suggests that aqueous complexation between metals and chlorophenolates can significantly affect the mobility of metal and phenolic contaminants.     

The effect of silica activity on the diffusion of Ni and Co in olivine

The diffusion of Ni and Co was measured at atmospheric pressure in synthetic monocrystalline forsterite (Mg₂SiO₄) from 1,200 to 1,500 °C at the oxygen fugacity of air, along [100], with the activities of SiO₂ and MgO defined by either forsterite + periclase (fo + per buffer) or forsterite + protoenstatite (fo + en buffer). Diffusion profiles were measured by three methods: laser-ablation inductively-coupled-plasma mass-spectrometry, nano-scale secondary ion mass spectrometry and electron microprobe, with good agreement between the methods. For both Ni and Co, the diffusion rates in protoenstatite-buffered experiments are an order of magnitude faster than in the periclase-buffered experiments at a given temperature. The diffusion coefficients D _M (M = Ni or Co) for the combined data set can be fitted to the equation:

$$\log \,D_{\text{M}} \,\left( {{\text{in}}\,{\text{m}}^{2} \,{\text{s}}^{ - 1} } \right) = - 6.77( \pm 0.33) + \Delta E_{\text{a}} (M)/RT + 2/3\log a_{{SiO_{2} }}$$

with E_a(Ni) = ? 284.3 kJ mol^?1 and E_a(Co) = ? 275.9 kJ mol^?1, with an uncertainty of ±10.2 kJ mol^?1. This equation fits the data (24 experiments) to ±0.1 in log D _M. The dependence of diffusion on \(a_{{{\text{SiO}}_{2} }}\) is in agreement with a point-defect model in which Mg-site vacancies are charge-balanced by Si interstitials. Comparative experiments with San Carlos olivine of composition Mg_1.8Fe_0.2SiO₄ at 1,300 °C give a slightly small dependence on \(a_{{{\text{SiO}}_{2} }}\), with D \(\propto\) (\(a_{{{\text{SiO}}_{2} }}^{0.5}\)), presumably because the Mg-site vacancies increase with incorporation of Fe³⁺ in the Fe-bearing olivines. However, the dependence on fO₂ is small, with D \(\propto\) (fO₂)^0.12±0.12. These results show the necessity of constraining the chemical potentials of all the stoichiometric components of a phase when designing diffusion experiments. Similarly, the chemical potentials of the major-element components must be taken into account when applying experimental data to natural minerals to constrain the rates of geological processes. For example, the diffusion of divalent elements in olivine from low SiO₂ magmas, such as kimberlites or carbonatites, will be an order of magnitude slower than in olivine from high SiO₂ magmas, such as tholeiitic basalts, at equal temperatures and fO₂.

     

The effect of wind speed and bed slope on sand transport

This paper reports on a wind tunnel study of the effects of bed slope and wind speed on aeolian mass transport. The use of a sloping wind tunnel has enabled estimation of the friction angle α to be about 40° for saltating particles in the range 170–540 μm. A formula relating dimensionless mass transport to friction speed and bed slope is proposed, and mass transport data for five uniform sand samples and one non-uniform sand sample are shown to fit the equation well. In particular, the relationship reveals an overshoot in mass transport slightly above threshold collisions, a feature also evident when previous experimental data is re-examined. As the number of mid-air collisions between the saltating particles increases greatly with wind speed, the overshoot may occur as a result of increasing energy losses resulting from the collisions. Finally, it is demonstrated that data for saltating snow shows a similar overshoot in the dimensionless transport rate.     

The effect of halogens on Zr diffusion and zircon dissolution in hydrous metaluminous granitic melts

Diffusion of Zr and zircon solubility in hydrous, containing approximately 4.5 wt% H₂O, metaluminous granitic melts with halogens, either 0.35 wt% Cl (LCl) or 1.2 wt% F (MRF), and in a halogen-free melt (LCO) were measured at 1.0 GPa and temperatures between 1,050 and 1,400 °C in a piston-cylinder apparatus using the zircon dissolution technique. Arrhenius equations for Zr diffusion in each hydrous melt composition are, for LCO with 4.4ǂ.4 wt% H₂O: % MathType!MTEF!2!1!+- % feaaeaart1ev0aaatCvAUfKttLearuavP1wzZbItLDhis9wBH5garm % Wu51MyVXgaruWqVvNCPvMCG4uz3bqee0evGueE0jxyaibaieYlf9ir % Veeu0dXdh9vqqj-hEeeu0xXdbba9ev6pc9fs0-rqaqpepmKs4qpepe % I8kaL8kuc9pgc9q8qqaq-dhH6hb9hs0dXdHu6deP0u0-vr0-vr0db8 % meaabaqaciGacaGaaeaabaWaaeaaeaaakeaacqWGebarcqGH9aqpcq % aIYaGmcqGGUaGlcqaI4aaocqaI4aaocqGHXcqScqaIWaamcqGGUaGl % cqaIWaamcqaIZaWmcqWG4baEcqaIXaqmcqaIWaamdaahaaWcbeqaai % abgkHiTiabiIda4aaakiGbcwgaLjabcIha4jabcchaWnaabmaabaWa % aSaaaeaacqGHsislcqaIXaqmcqaI0aancqaIWaamcqGGUaGlcqaIXa % qmcqGHXcqScqaIZaWmcqaIZaWmcqGGUaGlcqaI5aqoaeaacqWGsbGu % cqWGubavaaaacaGLOaGaayzkaaaaaa!571F! D = 2.88 ±0.03x10 ^{- 8} exp( [( - 140.1 ±33.9)/(RT)] )D = 2.88 \pm 0.03x10^{ - 8} \exp \left( {{{ - 140.1 \pm 33.9} \over {RT}}} \right) , for LCl with 4.5ǂ.5 wt% H₂O: % MathType!MTEF!2!1!+- % feaaeaart1ev0aaatCvAUfKttLearuavP1wzZbItLDhis9wBH5garm % Wu51MyVXgaruWqVvNCPvMCG4uz3bqee0evGueE0jxyaibaieYlf9ir % Veeu0dXdh9vqqj-hEeeu0xXdbba9ev6pc9fs0-rqaqpepmKs4qpepe % I8kaL8kuc9pgc9q8qqaq-dhH6hb9hs0dXdHu6deP0u0-vr0-vr0db8 % meaabaqaciGacaGaaeaabaWaaeaaeaaakeaacqWGebarcqGH9aqpcq % aIYaGmcqGGUaGlcqaIZaWmcqaIZaWmcqGHXcqScqaIWaamcqGGUaGl % cqaIWaamcqaI1aqncqWG4baEcqaIXaqmcqaIWaamdaahaaWcbeqaai % abgkHiTiabisda0aaakiGbcwgaLjabcIha4jabcchaWnaabmaabaWa % aSaaaeaacqGHsislcqaIYaGmcqaI1aqncqaI0aancqGGUaGlcqaI4a % aocqGHXcqScqaI2aGncqaI0aancqGGUaGlcqaIXaqmaeaacqWGsbGu % cqWGubavaaaacaGLOaGaayzkaaaaaa!5719! D = 2.33 ±0.05x10 ^{- 4} exp( [( - 254.8 ±64.1)/(RT)] )D = 2.33 \pm 0.05x10^{ - 4} \exp \left( {{{ - 254.8 \pm 64.1} \over {RT}}} \right) and for MRF with 4.9ǂ.3 wt% H₂O: % MathType!MTEF!2!1!+- % feaaeaart1ev0aaatCvAUfKttLearuavP1wzZbItLDhis9wBH5garm % Wu51MyVXgaruWqVvNCPvMCG4uz3bqee0evGueE0jxyaibaieYlf9ir % Veeu0dXdh9vqqj-hEeeu0xXdbba9ev6pc9fs0-rqaqpepmKs4qpepe % I8kaL8kuc9pgc9q8qqaq-dhH6hb9hs0dXdHu6deP0u0-vr0-vr0db8 % meaabaqaciGacaGaaeaabaWaaeaaeaaakeaacqWGebarcqGH9aqpcq % aIYaGmcqGGUaGlcqaI1aqncqaI0aancqGHXcqScqaIWaamcqGGUaGl % cqaIWaamcqaIZaWmcqWG4baEcqaIXaqmcqaIWaamdaahaaWcbeqaai % abgkHiTiabiwda1aaakiGbcwgaLjabcIha4jabcchaWnaabmaabaWa % aSaaaeaacqGHsislcqaIYaGmcqaIYaGmcqaIZaWmcqGGUaGlcqaI4a % aocqGHXcqScqaIXaqmcqaI1aqncqGGUaGlcqaI1aqnaeaacqWGsbGu % cqWGubavaaaacaGLOaGaayzkaaaaaa!5715! D = 2.54 ±0.03x10 ^{- 5} exp( [( - 223.8 ±15.5)/(RT)] )D = 2.54 \pm 0.03x10^{ - 5} \exp \left( {{{ - 223.8 \pm 15.5} \over {RT}}} \right) . Solubilities determined by the dissolution technique were reversed for LCO +4.5ǂ.5 wt% H₂O by crystallization of a Zr-enriched glass of LCO composition at 1,200 and 1,050 °C at 1.0 GPa. The solubility data were used to calculate partition coefficients of Zr between zircon and hydrous melt, which are given by the following expressions: for LCO % MathType!MTEF!2!1!+- % feaaeaart1ev0aaatCvAUfKttLearuavP1wzZbItLDhis9wBH5garm % Wu51MyVXgaruWqVvNCPvMCG4uz3bqee0evGueE0jxyaibaieYlf9ir % Veeu0dXdh9vqqj-hEeeu0xXdbba9ev6pc9fs0-rqaqpepmKs4qpepe % I8kaL8kuc9pgc9q8qqaq-dhH6hb9hs0dXdHu6deP0u0-vr0-vr0db8 % meaabaqaciGacaGaaeaabaWaaeaaeaaakeaacyGGSbaBcqGGUbGBcq % WGebardaqhaaWcbaGaemOwaOLaemOCaihabaGaemOEaONaemyAaKMa % emOCaiNaem4yamMaem4Ba8MaemOBa4Maei4la8IaemyBa0Maemyzau % MaemiBaWMaemiDaqhaaOGaeyypa0JaeGymaeJaeiOla4IaeGOnayJa % eG4mamZaaeWaaeaadaWcaaqaaiabigdaXiabicdaWiabicdaWiabic % daWiabicdaWaqaaiabdsfaubaaaiaawIcacaGLPaaacqGHsislcqaI % 1aqncqGGUaGlcqaI4aaocqaI3aWnaaa!5924! lnD_Zr^zircon/melt = 1.63( [10000/(T)] ) - 5.87\ln D_{Zr}^{zircon/melt} = 1.63\left( {{{10000} \over T}} \right) - 5.87 , for LCl % MathType!MTEF!2!1!+- % feaaeaart1ev0aaatCvAUfKttLearuavP1wzZbItLDhis9wBH5garm % Wu51MyVXgaruWqVvNCPvMCG4uz3bqee0evGueE0jxyaibaieYlf9ir % Veeu0dXdh9vqqj-hEeeu0xXdbba9ev6pc9fs0-rqaqpepmKs4qpepe % I8kaL8kuc9pgc9q8qqaq-dhH6hb9hs0dXdHu6deP0u0-vr0-vr0db8 % meaabaqaciGacaGaaeaabaWaaeaaeaaakeaacyGGSbaBcqGGUbGBcq % WGebardaqhaaWcbaGaemOwaOLaemOCaihabaGaemOEaONaemyAaKMa % emOCaiNaem4yamMaem4Ba8MaemOBa4Maei4la8IaemyBa0Maemyzau % MaemiBaWMaemiDaqhaaOGaeyypa0JaeGymaeJaeiOla4IaeGinaqJa % eG4naCZaaeWaaeaadaWcaaqaaiabigdaXiabicdaWiabicdaWiabic % daWiabicdaWaqaaiabdsfaubaaaiaawIcacaGLPaaacqGHsislcqaI % 0aancqGGUaGlcqaI3aWncqaI1aqnaaa!5920! lnD_Zr^zircon/melt = 1.47( [10000/(T)] ) - 4.75\ln D_{Zr}^{zircon/melt} = 1.47\left( {{{10000} \over T}} \right) - 4.75 and, for MRF by % MathType!MTEF!2!1!+- % feaaeaart1ev0aaatCvAUfKttLearuavP1wzZbItLDhis9wBH5garm % Wu51MyVXgaruWqVvNCPvMCG4uz3bqee0evGueE0jxyaibaieYlf9ir % Veeu0dXdh9vqqj-hEeeu0xXdbba9ev6pc9fs0-rqaqpepmKs4qpepe % I8kaL8kuc9pgc9q8qqaq-dhH6hb9hs0dXdHu6deP0u0-vr0-vr0db8 % meaabaqaciGacaGaaeaabaWaaeaaeaaakeaacyGGSbaBcqGGUbGBcq % WGebardaqhaaWcbaGaemOwaOLaemOCaihabaGaemOEaONaemyAaKMa % emOCaiNaem4yamMaem4Ba8MaemOBa4Maei4la8IaemyBa0Maemyzau % MaemiBaWMaemiDaqhaaOGaeyypa0JaeGymaeJaeiOla4IaeGinaqJa % eG4naCZaaeWaaeaadaWcaaqaaiabigdaXiabicdaWiabicdaWiabic % daWiabicdaWaqaaiabdsfaubaaaiaawIcacaGLPaaacqGHsislcqaI % 0aancqGGUaGlcqaI5aqocqaIXaqmaaa!591C! lnD_Zr^zircon/melt = 1.47( [10000/(T)] ) - 4.91\ln D_{Zr}^{zircon/melt} = 1.47\left( {{{10000} \over T}} \right) - 4.91 . Experiments on the same compositions, but with water contents down to 0.5 wt%, demonstrated reductions in both the diffusion coefficient of Zr and zircon solubility in the melt. The addition of halogens at the concentration levels studied to metaluminous melts has a small effect on either the diffusion of Zr in the melt, or the solubility of zircon at all water concentrations and temperatures investigated. At 800 °C, the calculated diffusion coefficient of Zr is lowest in LCl, 9᎒^-17 m² s^-1, and is highest in LCO, 4᎒^-15 m² s^-1. Extrapolation of the halogen-free solubility data to a magmatic temperature of 800 °C yields solubilities of approximately one-third of those directly measured in similar compositions, predicted by earlier studies of zircon dissolution and based upon analyses of natural rocks. This discrepancy is attributed to the higher oxygen fugacity of the experiments of this study compared with previous studies and nature, and the effect of oxygen fugacity on the structural role of iron in the melt, which, in turn, affects zircon solubility, but does not significantly affect Zr diffusion.