White Canyon Research Articles

The Where of Mineral Names: Greenlizardite, Green Lizard Mine, Low Canyon, White Canyon Uranium District, San Juan County, Utah

The Where of Mineral Names: Greenlizardite, Green Lizard Mine, Low Canyon, White Canyon Uranium District, San Juan County, Utah

Calorimetry and structural analysis of uranyl sulfates with rare topologies

Abstract Uranyl sulfate minerals are the most rapidly expanding group of uranium minerals, with dozens of species described in the past decade from the localities of White Canyon, U.S.A. and Jáchymov, Czech Republic. Synthetic analogs of a suite of uranyl sulfate minerals were crystallized, characterized, and the standard-state enthalpies of formation (ΔHfo) were determined. Synthetic lussierite is monoclinic, space group Cc, a = 9.2896, b = 28.685, c = 9.6155 Å, β = 93.504°. Synthetic geschieberite is ortho-rhombic, space group Pna21, a = 13.7408, b = 7.2713, c = 11.5844 Å. The standard-state enthalpies of formation from the binary oxides for lussierite, péligotite, shumwayite, geschieberite, and bluelizardite are –3214 ± 78, –2026 ± 33, –587 ± 22, –966.1 ± 10.9, and –2084 ± 21 kJ/mol, respectively, while the standard-state enthalpies of formation of each phase from its elements are –9743 ± 78, –7220 ± 33, –5255 ± 22, –3916 ± 20, and –7117 ± 21 kJ/mol, respectively. The ΔHfo of péligotite was accurately estimated using the ΔHfo of lussierite, bluelizardite, and literature values of the oxide components of each phase. This implies that estimates can be made accurately of the ΔHfo of uranyl sulfates of minerals without synthetic analogs.

Navrotskyite, K2Na10(UO2)3(SO4)9·2H2O, a new sodium and potassium uranyl-sulfate mineral from the Blue Lizard mine, Red Canyon, White Canyon District, San Juan County, Utah

Navrotskyite, K2Na10(UO2)3(SO4)9·2H2O, a new sodium and potassium uranyl-sulfate mineral from the Blue Lizard mine, Red Canyon, White Canyon District, San Juan County, Utah

Shinarumpite, a new cobalt uranyl sulfate mineral from the Scenic mine, San Juan County, Utah, USA, structurally related to leydetite

AbstractThe new mineral shinarumpite (IMA2021-105), [Co(H2O)6][(UO2)(SO4)2(H2O)]⋅4H2O, was found in the Scenic mine on Fry Mesa, White Canyon district, San Juan County, Utah, USA, where it occurs as a secondary phase on granular quartz matrix in association with gypsum, deliensite, Co-rich rietveldite, scenicite, shumwayite and sulfur. Shinarumpite crystals are transparent, yellow, blades or prisms, up to 1 mm in length. The mineral has white streak, vitreous lustre and is nonfluorescent. It is brittle with irregular, curved fracture. The Mohs hardness is ~2½ and it has a perfect {100} cleavage. The density is 2.58(2) g⋅cm–3. Optically, the mineral is biaxial (–) with α = 1.515(2), β = 1.526(2), γ = 1.529(2) (white light); 2V = 55(1)°; extreme r < v dispersion; orientation: Z = b, X ^ a = 30° in obtuse β; pleochroism: X = very pale yellow, Y = pale yellow, Z = light yellow; X < Y < Z. The Raman spectrum exhibits bands consistent with UO22+, SO42– and O–H. Electron microprobe analysis provided the empirical formula [(Co0.51Ni0.28Fe0.21)Σ1.00(H2O)6][(UO2)(SO4)2(H2O)]⋅4H2O. The five strongest powder X-ray diffraction lines are [dobs Å(I)(hkl)]: 10.37(100)(200), 5.73(43)(111), 5.20(70)(400, 202, 211), 4.70(31)($\bar{3}$11) and 3.326(30)(213, 021). Shinarumpite is monoclinic, P21/c, a = 21.0549(15), b = 6.8708(5), c = 12.9106(5), β = 96.678(7)°, V = 1885.03(17) Å3 and Z = 4. In the structure of shinarumpite (R1 = 0.0336 for 2623 I > 2σI), linkages of pentagonal bipyramids and tetrahedra form an infinite [(UO2)(SO4)2(H2O)]2– sheet. Isolated Co(H2O)6 octahedra and H2O groups occupy the interlayer region linking the sheets via an extensive system of hydrogen bonds. The structure of shinarumpite is very similar to that of leydetite. Uranyl sulfate structural unit types are discussed with respect to frequency and charge deficiency per anion (CDA).

Debris-Flow Channel Headwater Dynamics: Examining Channel Recharge Cycles With Terrestrial Laser Scanning

Debris-flows present a natural hazard to the safe operation of linear infrastructure in mountainous environments. The most significant contributor to debris-flow occurrence is a supply of readily erodible material, often created by rockfalls and other shallow landslides. The spatial distribution and total volume of storage are also critical factors, controlling the initiation location, predominant flow type, and termination location of debris-flow surges. Therefore, there is a need to be able to systematically incorporate debris recharge processes and timeframes into the monitoring and characterization of debris-flow hazards. In this work, the authors present the results of 7 years of terrestrial laser scanning (TLS) captured at the White Canyon. The White Canyon represents an analog to large scale, steep catchments to investigate the role of sediment supply on debris-flow processes. The TLS dataset was collected at monthly to quarterly intervals, providing a basis for analysis of debris transfer processes occurring on the study slope. A rockfall database of over 72,000 events was generated from 52 change detection analyses and is linked to catchment recharge and transfer processes. The results indicate that the 17 channels analyzed in the White Canyon do not directly match the conceptual models proposed from the supply theory. The channels display a variety of behaviors when exposed to the same climate signature. The temporal data acquisition rate was found to have a significant influence on the dynamics of movement that can be interpreted from TLS change detection analysis. The work highlights the need for higher frequency monitoring and the integration of climate data into the analysis, in order to better understand these dynamic processes.

Scenicite, a new uranyl-sulfate mineral from the White Canyon district, San Juan County, Utah, USA

AbstractThe new mineral scenicite (IMA2021-057), [(UO2)(H2O)2(SO4)]2⋅3H2O, was found in the Green Lizard, Giveaway–Simplot, Markey and Scenic mines, White Canyon district, San Juan County, Utah, USA, where it occurs as a secondary phase on granular quartz matrix in association with various combinations of deliensite, gypsum, natrozippeite, rietveldite and shumwayite. Scenicite crystals are transparent, light green yellow, poorly formed blades or prisms, up to 0.1 mm in length. The mineral has white streak and vitreous lustre. It exhibits bright greenish-white fluorescence (405 nm laser). It is brittle with irregular, curved fracture and a Mohs hardness of ~2. It has excellent {100} and good {001} cleavages. The calculated density is 3.497 g cm–3. Optically, the mineral is biaxial (–) with α = 1.556(2), β = 1.573(2), γ = 1.576(2) (white light); 2V = 45(3)°; extreme r < v dispersion; orientation: X = c, Y = a, Z = b; pleochroism: X and Y = colourless, Z = light green–yellow; and X = Y < Z. The Raman spectrum exhibits bands consistent with UO22+, SO42– and O–H. Electron microprobe analysis provided the empirical formula U1.996S2.005O19H13.997. The five strongest powder X-ray diffraction lines are [dobs Å(I)(hkl)]: 7.69(70)(201), 5.63(100)(111), 4.92(84)(202,310), 4.80(93)(401) and 3.398(55)(020,120,511,601). Scenicite is orthorhombic, Pca21, a = 21.2144(15), b = 6.8188(3) c = 11.2554(6) Å, V = 1628.18(16) Å3 and Z = 4. In the structure of scenicite (R1 = 0.0365 for 1259 I > 2σI), linkages of pentagonal bipyramids and tetrahedra form an infinite neutral [(UO2)(SO4)(H2O)2] chain. The structure of shumwayite contains topologically identical chains.

Three-dimensional rockfall shape back analysis: methods and implications

Abstract. Rockfall is a complex natural process that can present risks to the effective operation of infrastructure in mountainous terrain. Remote sensing tools and techniques are rapidly becoming the state of the practice in the characterization, monitoring and management of these geohazards. The aim of this study is to address the methods and implications of how the dimensions of three-dimensional rockfall objects, derived from sequential terrestrial laser scans (TLSs), are measured. Previous approaches are reviewed, and two new methods are introduced in an attempt to standardize the process. The approaches are applied to a set of synthetic rockfall objects generated in the open-source software package Blender. Fifty rockfall events derived from sequential TLS monitoring in the White Canyon, British Columbia, Canada, are used to demonstrate the application of the proposed algorithms. This study illustrates that the method used to calculate the rockfall dimensions has a significant impact on how the shape of a rockfall object is classified. This has implications for rockfall modelling as the block shape is known to influence rockfall runout.

Surface Reconstruction for Three-Dimensional Rockfall Volumetric Analysis

Laser scanning is routinely being used for the characterization and management of rockfall hazards. A key component of many studies is the ability to use the high-resolution topographic datasets for detailed volume estimates. 2.5-Dimensional (2.5D) approaches exist to estimate the volume of rockfall events; however these approaches require rasterization of the point cloud. These 2.5D volume estimates are therefore sensitive to picking an appropriate cell size to preserve resolution while minimizing interpolation, especially for lower volume rockfall events. To overcome the limitations of working with 2.5D raster datasets, surface reconstruction methods originating from the field of computational geometry can be implemented to assess the volume of rockfalls in 3D. In this technical note, the authors address the methods and implications of how the surface of 3D rockfall objects, derived from sequential terrestrial laser scans (TLS), are reconstructed for volumetric analysis. The Power Crust, Convex Hull and Alpha-shape algorithms are implemented to reconstruct a synthetic rockfall object generated in Houdini, a procedural modeling and animation software package. The reconstruction algorithms are also implemented for a selection of three rockfall cases studies which occurred in the White Canyon, British Columbia, Canada. The authors find that there is a trade-off between accurate surface topology reconstruction and ensuring the mesh is watertight manifold; which is required for accurate volumetric estimates. Power Crust is shown to be the most robust algorithm, however, the iterative Alpha-shape approach introduced in the study is also shown to find a balance between hole-filling and loss of detail.

Combining temporal 3-D remote sensing data with spatial rockfall simulations for improved understanding of hazardous slopes within rail corridors

Abstract. Remote sensing techniques can be used to gain a more detailed understanding of hazardous rock slopes along railway corridors that would otherwise be inaccessible. Multiple datasets can be used to identify changes over time, creating an inventory of events to produce magnitude–frequency relationships for rockfalls sourced on the slope. This study presents a method for using the remotely sensed data to develop inputs to rockfall simulations, including rockfall source locations and slope material parameters, which can be used to determine the likelihood of a rockfall impacting the railway tracks given its source zone location and volume. The results of the simulations can be related to the rockfall inventory to develop modified magnitude–frequency curves presenting a more realistic estimate of the hazard. These methods were developed using the RockyFor3D software and lidar and photogrammetry data collected over several years at White Canyon, British Columbia, Canada, where the Canadian National (CN) Rail main line runs along the base of the slope. Rockfalls sourced closer to the tracks were more likely to be deposited on the track or in the ditch, and of these, rockfalls between 0.1 and 10 m3 were the most likely to be deposited. Smaller blocks did not travel far enough to reach the bottom of the slope and larger blocks were deposited past the tracks. Applying the results of the simulations to a database of over 2000 rockfall events, a modified magnitude–frequency can be created, allowing the frequency of rockfalls deposited on the railway tracks or in ditches to be determined. Suggestions are made for future development of the methods including refinement of input parameters and extension to other modelling packages.

Redcanyonite, (NH4)2Mn[(UO2)4O4(SO4)2](H2O)4, a new zippeite-group mineral from the Blue Lizard mine, San Juan County, Utah, USA

ABSTRACTRedcanyonite (IMA2016-082), (NH4)2Mn[(UO2)4O4(SO4)2](H2O)4, occurs underground in the Blue Lizard mine, Red Canyon, White Canyon district, San Juan County, Utah, USA. It occurs with natrozippeite, brochantite, devilline, posnjakite, johannite, gypsum, bobcookite, pickeringite, pentahydrite and the NH4-analogue of zippeite: ammoniozippeite. Redcanyonite occurs as radial aggregates of red–orange needles and blades individually reaching up to 0.2 mm long, with aggregates measuring up to 1 mm in diameter. Crystals are flattened on {010} and elongated along [100], exhibit perfect cleavage on {010}, and exhibit the forms {010}, {001}, {101} and {10$\bar{1}$}. Twinning is ubiquitous, by 180° rotation on [100]. Redcanyonite is translucent with a pale orange streak, is non-fluorescent, has a Mohs hardness of 2, and has brittle tenacity with uneven fracture. Optically, redcanyonite is biaxial (+), α = 1.725(3), β = 1.755(3), γ = 1.850(5) (white light); 2V (meas.) = 60(2)°, 2V (calc.) = 61.3°; and dispersion isr<v, very strong. Pleochroism is:X= orange,Y= yellow andZ= orange;Y<<X<Z. The optical orientation isX=b,Y≈c*,Z≈a. The empirical formula is (NH4)2.02(Mn0.49Cu0.09Zn0.06)Σ0.64H+0.72[(UO2)4O4(S0.99P0.01O4)2](H2O)4, based on 4 U and 24 O apfu. Redcanyonite is monoclinic,C2/m,a= 8.6572(17),b= 14.155(3),c= 8.8430(19) Å, β = 104.117(18)°,V= 1050.9(4) Å3andZ= 2. The structure was refined toR1= 0.0382 for 1079 reflections withIobs> 3σI. Uranyl oxo-sulfate sheets in redcanyonite adopt the well-known zippeite topology, which consists of zigzag chains of uranyl pentagonal bipyramids linked by sulfate tetrahedra to form sheets. The sheets are linked to each other through bonds to interlayer NH4+groups and octahedrally coordinated Mn2+, and by hydrogen bonds from H2O groups. Redcanyonite is named for Red Canyon in southeast Utah, USA.

The Use of Unmanned Aerial Vehicles (UAVs) in Slope Stability Assessment

The use and applications of unmanned aerial vehicles (UAVs) in geotechnical engineering is rapidly growing, leading to changes in the way that data is acquired, analyzed and processed. UAVs can reach areas previously inaccessible via ground or helicopter, while also being quickly deployed. Cameras are the current standard for data collection and 3D model creation.
 There are multiple types of UAV’s currently available. Quadcopters can take off and land in spatially constrained areas, but carry a small stabilized camera producing low quality models. Octocopters permit an increased payload, so a higher quality camera can be attached, allowing for increased model accuracy. Flight time is reduced by the additional weight. Fixed wing UAVs create higher quality photogrammetry models, and are commonly deployed over large surface areas. Transport Canada certification must be approved prior to any flights occurring for research or work. A detailed application must be created, including a flight plan and demonstration of prior flight experience.
 At the White Canyon site in B.C., a Phantom 4 Quadcopter was flown for geotechnical analysis of a complex geometry slope, which has previously been studied for several years. The terrain has occluded the data available from the ground or from permissible helicopter flight paths. Therefore, detailed information from the slope has not been previously available. The process of using a UAV to obtain these data sets, to develop a full 3D model of these areas of the slope is discussed, considering the accuracy and quality of the data available.

Additional species for the Jemez Mountains, New Mexico, U.S.A.

In this paper, we note 161 species and varieties of plants in the Jemez Mountains verified through voucher specimens. These species were not previously listed in the most detailed previous floristic study in this area Floristic Studies in North Central New Mexico, U.S.A. the Tusas Mountains and the Jemez Mountains by Reif et. al. (2009). Most of these specimens are housed in the Jemez Mountain Herbarium (JMH) at the Los Alamos, New Mexico Nature Center. Others are housed in the herbarium at the Museum of Southwestern Biology at the University of New Mexico (UNM), and a few elsewhere as noted (SEINet).
 If this number is added to the total for the Jemez Mountains from Reif’s work, the new total for the Jemez Mountains is 1,504 taxa. These additions include seven new state records, as well as several species not expected in the Jemez Mountains environment and altitude range. Of special interest are the flora of the San Pedro Parks Wilderness in the northwest part of the range, White Rock Canyon along the Rio Grande, and the desert shrublands west of San Ysidro at the extreme southwest part of the Jemez Mountains. For completeness, we include species escaped from cultivation but apparently well established in the wild, and a list of species that have not recurred where they were collected. Finally, there are comments on aspects of Reif et al. (2009).

Leószilárdite, the first Na,Mg-containing uranyl carbonate from the Markey Mine, San Juan County, Utah, USA

AbstractLeószilárdite (IMA2015-128), Na6Mg(UO2)2(CO3)6·6H2O, was found in the Markey Mine, Red Canyon, White Canyon District, San Juan County, Utah, USA, in areas with abundant andersonite, natrozippeite, gypsum, anhydrite, and probable hydromagnesite along with other secondary uranium minerals bayleyite, čejkaite and johannite. The new mineral occurs as aggregates of pale yellow bladed crystals flattened on ﹛001﹜ and elongated along [010], individually reaching up to 0.2 mmlong. More commonly it occurs as pale yellow pearlescent masses to 2 mm consisting of very small plates. Leószilárdite fluoresces green under both longwave and shortwave ultraviolet light, and is translucent with a white streak, hardness of 2 (Mohs), and brittle tenacity with uneven fracture. The new mineral is readily soluble in room temperature H2O. Crystals have perfect cleavage along ﹛001﹜, and exhibit the forms ﹛110﹜,﹛001﹜,﹛100﹜,﹛101﹜ and ﹛101﹜. Optically, leószilárdite is biaxial (-), α= 1.504(1), β= 1.597(1), γ= 1.628(1) (white light); 2V (meas.) = 57(1)°, 2V (calc.) = 57.1°; dispersion r > v, slight. Pleochroism: X= colourless, Y and Z= light yellow; X<Y ≈ Z The average of six wavelength dispersive spectroscopic analyses provided Na2O 14.54, MgO 3.05, UO3 47.95, CO2 22.13, H2O 9.51, total 97.18 wt.%. The empirical formula is Na5.60Mg0.90U2O28C6H12.60, based on 28 O apfu. Leószilárdite is monoclinic, C2/m, a = 11.6093(21), b = 6.7843(13), c = 15.1058(28) Å, β = 91.378(3)°, V= 1189.4(4) Å3 and Z = 2. The crystal structure (R1 = 0.0387 for 1394 reflections with Iobs > 4σI), consists of uranyl tricarbonate anion clusters [(UO2)(CO3)3]4- held together in part by irregular chains of NaO5(H2O) polyhedra sub parallel to [010]. Individual uranyl tricarbonate clusters are also linked together by three-octahedron units consisting of two Na-centred octahedra that share the opposite faces of a Mg-centred octahedron at the centre (Na–Mg–Na), and have the composition Na2MgO12(H2O)4. The name of the new mineral honours the Hungarian-American physicist, inventor and biologist Dr. Leó Szilárd (1898–1964).

An analysis of failure mechanism constraints on pre-failure rock block deformation using TLS and roto-translation methods

Rockfall hazards increase the risk of train derailment along railway corridors in western Canada. In this study, repeated terrestrial laser scanning (TLS) datasets were collected every 2–3 months at three different sites along the Thompson and Fraser River corridors in British Columbia, referred to as the Goldpan, White Canyon, and Mile 109 sites. A total of 207 rockfall events occurring across all three sites between November 11, 2014 and October 18, 2016 were recorded in a database. For each of these rockfalls, pre-failure deformation was measured using a method of three-dimensional roto-translation block tracking. Each rockfall was classified by its deformation behaviour and further categorised based on failure mechanism, volume, lithology, and the roughness condition of the failure plane. Results reveal that detectable levels of deformation were measured in 33% of the total number of rockfall events using the present methods. Rotation deformation was most commonly observed in toppling failures with relatively steep joint orientations. Conversely, planar sliding blocks generally exhibited the least measurable deformation, with the majority not showing any precursory translation or rotation. It is postulated that overhanging rockfall configurations may suppress the expression of deformation in rockfall source blocks, though additional research is required to confirm this.

Shumwayite, [(UO2)(SO4)(H2O)2]2·H2O, a new uranyl sulfate mineral from Red Canyon, San Juan County, Utah, USA

AbstractThe new mineral shumwayite (IMA2015-058), [(UO2)(SO4)(H2O)2]2·H2O, was found in the Green Lizard and Giveaway-Simplot mines, White Canyon district, San Juan County, Utah, USA, where it occurs as a secondary alteration phase. At the Green Lizard mine, it is found in association with calcite, gypsum, plášilite, pyrite, rozenite and sulfur; at the Giveaway-Simplot mine, shumwayite is associated with rhomboclase and römerite. The mineral occurs as pale greenish-yellow monoclinic prisms, elongated on [100], up to ∼0.3 mm long and commonly in subparallel to random intergrowths. The mineral is transparent with a vitreous lustre and has a white streak. It fluoresces bright greenish white under both longwave and shortwave ultraviolet radiation. The Mohs hardness is ∼2. Crystals are brittle with perfect {011} cleavage and irregular fracture. The mineral is slightly deliquescent and is easily soluble in room temperature H2O. The calculated density is 3.844 g cm–3. Optically, shumwayite is biaxial (+/–), with α = 1.581(1), β= 1.588(1), γ = 1.595(1) (measured in white light). The measured 2Vxbased on extinction data collected on a spindle stage is 89.8(8)°; the calculated 2Vxis 89.6°. Dispersion is strong, but the sense is not defined because the optic sign is ambiguous. No pleochroism was observed. The optical orientation isX=b,Y=c,Z=a. Energy-dispersive spectrometer analyses (with H2O based on the crystal structure) yielded the empirical formula U2.01S1.99O12.00·5H2O.Shumwayite is monoclinic,P21/c,a= 6.74747(15),b= 12.5026(3),c= 16.9032(12) Å, β = 90.919(6)°,V= 1425.79(11) Å3andZ= 4. The crystal structure (R1= 1.88% for 2936F> 4σF) contains UO7pentagonal bipyramids and SO4tetrahedra that link by corner-sharing to form [(UO2)(SO4)(H2O)2] chains along [100]. The chains and isolated H2O groups between them are linked together only by hydrogen bonds. The mineral is named in honour of the Shumway family, whose members account for the discovery and mining of hundreds of uranium deposits on the Colorado Plateau, including the Green Lizard mine.

Effects of sampling interval on the frequency - magnitude relationship of rockfalls detected from terrestrial laser scanning using semi-automated methods

Using change detection and semi-automated identification methods, it is possible to extract detailed rockfall information from terrestrial laser scanning data to build a database of events, which can be used in the development of the frequency-magnitude relationship for a slope. In this study, we have applied these methods to the White Canyon, a hazardous slope that presents rockfall hazards to the CN Rail line in British Columbia, to build a database of rockfalls including their locations, volumes, and block shapes. We identified over 1900 rockfall events during a 15-month period, ranging in volume from 0.01 to 45 m3. The frequency of these events changed throughout the year, with the highest periods of activity occurring over the winter months. We investigated how the sampling interval, or duration between scans, can affect how the rockfalls are identified, and therefore the frequency-magnitude relationship for the slope using datasets with fewer scans. We show that as the duration between scans becomes larger, fewer rockfalls are detected, as multiple events that have occurred in the same location cluster together into a single event. The results of this study can be used to assist the railways in planning the appropriate number and duration between future scans, in order to capture frequency-magnitude data for the slope with a desired level of detail.

Identifying rock slope failure precursors using LiDAR for transportation corridor hazard management

In the Thompson and Fraser River valleys, rockfall and rockslides are a hazard for railway traffic in the region. In June 2013, a 2600m3 rockslide occurred in the White Canyon, causing damage to infrastructure and interruption to service. In the year preceding this failure, the slope was monitored using terrestrial Light Detection And Ranging (LiDAR) as part of the Railway Ground Hazards Research Program initiative. The purpose of this study is to evaluate a hazard management strategy for transportation corridors exposed to steep slopes involving the identification of rockfall precursors prior to significant slope failures. For this failure, deformation was observed in the seven months preceding collapse with an accelerating period occurring in the final 28days. A distinct pattern of smaller rockfalls was observed around the perimeter of the deforming rock block as well as loss of surficial material over the slides tension crack. This study shows that with LiDAR monitoring, precursors to rock slope failures can be identified allowing for better rock slope hazard management by focusing attention on areas with the highest probability of failure.

Belakovskiite, Na7(UO2)(SO4)4(SO3OH)(H2O)3, a new uranyl sulfate mineral from the Blue Lizard mine, San Juan County, Utah, USA

AbstractThe new mineral belakovskiite (IMA2013-075), Na7(UO2)(SO4)4(SO3OH)(H2O)3, was found in the Blue Lizard mine, Red Canyon, White Canyon district, San Juan County, Utah, USA, where it occurs as a secondary alteration phase in association with blödite, ferrinatrite, kröhnkite, meisserite and metavoltine. Crystals of belakovskiite are very pale yellowish-green hair-like fibres up to 2 mm long and usually no more than a few mm in diameter. The fibres are elongated on [100] and slightly flattened on {021}. Crystals are transparent with a vitreous lustre. The mineral has a white streak and a probable Mohs hardness of ∼2. Fibres are flexible and elastic, with brittle failure and irregular fracture. No cleavage was observed. The mineral is readily soluble in cold H2O. The calculated density is 2.953 g cm−3. Optically, belakovskiite is biaxial (+) with α = 1.500(1), β = 1.511(1) and γ = 1.523(1) (measured in white light). The measured 2V is 87.1(6)° and the calculated 2V is 88°. The mineral is non-pleochroic. The partially determined optical orientation is X ≈ a. Electron-microprobe analysis provided Na2O 21.67, UO3 30.48, SO3 40.86, H2O 6.45 (structure), total 99.46 wt.% yielding the empirical formula Na6.83(U1.04O2)(SO4)4(S0.99O3OH)(H2O)3 based on 25 O a.p.f.u. Belakovskiite is triclinic, P, with a = 5.4581(3), b = 11.3288(6), c = 18.4163(13) Å, α = 104.786(7)°, β = 90.092(6)°, γ = 96.767(7)°, V = 1092.76(11) Å3 and Z = 2. The eight strongest X-ray powder diffraction lines are [dobs Å(I)(hkl)]: 8.96(35)(002), 8.46(29)(011), 5.19(100)(01,101,10), 4.66(58)(013,02,0,110), 3.568(37)(120,023,005,03), 3.057(59)(06,15,31), 2.930(27)(multiple) and 1.8320(29)(multiple). The structure, refined to R1 = 5.39% for 3163 Fo > 4σF reflections, contains [(UO2)(SO4)4(H2O)]6− polyhedral clusters connected via an extensive network of Na−O bonds and H bonds involving eight Na sites, three other H2O sites and an SO3OH (hydrosulfate) group. The 3-D framework, thus defined, is unique among known uranyl sulfate structures. The mineral is named for Dmitry Ilych Belakovskiy, a prominent Russian mineralogist and Curator of the Fersman Mineralogical Museum.

Crystal structure of pseudojohannite, with a revised formula, Cu3(OH)2[(UO2)4O4(SO4)2](H2O)12

The crystal structure of pseudojohannite from White Canyon, Utah, was solved by charge-flipping from single-crystal X-ray diffraction data and refined to an Robs = 0.0347, based on 2664 observed reflections. Pseudojohannite from White Canyon is triclinic, P-1, with a = 8.6744(4), b = 8.8692(4), c = 10.0090(5) A, alpha = 72.105(4)degrees, beta = 70.544(4)degrees, gamma = 76.035(4)degrees, and V = 682.61(5) A^3, with Z = 1 and chemical formula Cu3(OH)2[(UO2)4O4(SO4)2](H2O)12. The crystal structure of pseudojohannite is built up from sheets of zippeite topology that do not contain any OH groups; these sheets are identical to those found in zippeites containing Mg2+, Co2+, and Zn2+. The two Cu2+ sites in pseudojohannite are [5]- and [6]-coordinated by H2O molecules and OH groups. The crystal structure of the pseudojohannite holotype specimen from Jachymov was refined using Rietveld refinement of high-resolution powder diffraction data. Results indicate that the crystal structures of pseudojohannite from White Canyon and Jachymov are identical.

Effect of changes in water level on sediment pore water redox geochemistry at a reservoir shoreline

Pore water samplers with high vertical resolution were used to evaluate the response of sediment redox geochemistry during transient hydrologic conditions at Lake Powell, a large reservoir in Utah and Arizona, USA. Samplers were deployed at two different yet proximal shoreline locations, White and Farley Canyons, before and after exposure of sediment to air and subsequent resubmersion, which resulted from fluctuations in the water level of the reservoir. Before exposure to air, an observed increase in dissolved Mn concentrations and, at Farley Canyon, an observed decrease in dissolved U concentrations across and immediately below the sediment–water interface indicated reducing conditions in the sub-surface. After exposure and resubmersion of the sediment, pore water profiles at each site differed distinctly from those observed before the fluctuation in water level. At White Canyon, an increase in U concentrations and a decrease in Mn concentrations in pore water after exposure and subsequent resubmersion are suggestive of oxidative processes occurring during the period of sediment exposure. Data from Farley Canyon suggest that the same processes may be occurring, but to a lesser extent. Depth profiles of As and Pb were also examined, but were relatively featureless compared to those of Mn and U. At both sites, sediment evaluated for pore water chemistry in the second sampling was only fully resubmerged for 2–5 days prior to the second sampling event, yet reducing conditions were clearly evident in the Mn pore water profiles. This suggests that the dynamics of the biogeochemical processes occurring in surface sediment at Lake Powell are responsive on the timescale defined by the fluctuating water levels in the reservoir.