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Physiographically, the map area ranges from the high glaciated mountains of the Alaska and Aleutian Ranges and the Chugach Mountains to the coastal lowlands of Cook Inlet and the Copper River delta. Structurally, the map area is cut by a number of major faults and postulated faults, the most important of which are the Border Ranges, Contact, and Bruin Bay Fault systems. The rocks of the map area belong to the Southern Margin composite terrane, a Tertiary and Cretaceous or older subduction-related accretionary complex, and the Alaska Peninsula terrane. Mesozoic rocks between these two terranes have been variously assigned to the Peninsular or the Hidden terranes. The oldest rocks in the map area are blocks of Paleozoic age within the mélange of the McHugh Complex; however, the protolith age of the greenschist and blueschist within the Border Ranges Fault zone is not known. 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The selection criteria for the satellite imagery used in our mosaics were images having (1) the highest solar-elevation angles (near summer solstice) and (2) the least cloud, cloud-shadow, and snow cover. The multispectral and panchromatic data were orthorectified with ALOS satellite ephemeris data, a process which is not as accurate as orthorectification using digital elevation models (DEMs); however, the ALOS processing center did not have a precise DEM. As a result, the multispectral and panchromatic image pairs were generally not well registered to the surface and not coregistered well enough to perform resolution enhancement on the multispectral data. 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Within the Dusar-Shaida study area, three subareas were designated for detailed field investigations (that is, the Dahana-Misgaran, Kaftar VMS, and Shaida subareas); these subareas were extracted from the area’ image mosaic and are provided as separate embedded geotiff images.","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan (DS 709)","largerWorkSubtype":{"id":5,"text":"USGS Numbered Series"},"language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds709I","collaboration":"Prepared in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations and the Afghanistan Geological Survey. This report is Chapter I in Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan. 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ALOS was launched on January 24, 2006, and provides multispectral images from the AVNIR (Advanced Visible and Near-Infrared Radiometer) sensor in blue (420–500 nanometer, nm), green (520–600 nm), red (610–690 nm), and near-infrared (760–890 nm) wavelength bands with an 8-bit dynamic range and a 10-meter (m) ground resolution. The satellite also provides a panchromatic band image from the PRISM (Panchromatic Remote-sensing Instrument for Stereo Mapping) sensor (520–770 nm) with the same dynamic range but a 2.5-m ground resolution. The image products in this DS incorporate copyrighted data provided by the Japan Aerospace Exploration Agency (©JAXA,2008), but the image processing has altered the original pixel structure and all image values of the JAXA ALOS data, such that original image values cannot be recreated from this DS. As such, the DS products match JAXA criteria for value added products, which are not copyrighted, according to the ALOS end-user license agreement. 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Within the Kundalyan study area, three subareas were designated for detailed field investigations (that is, the Baghawan-Garangh, Charsu-Ghumbad, and Kunag Skarn subareas); these subareas were extracted from the area’s image mosaic and are provided as separate embedded geotiff images.","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan (DS 709)","largerWorkSubtype":{"id":5,"text":"USGS Numbered Series"},"language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds709H","collaboration":"Prepared in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations and the Afghanistan Geological Survey. This report is Chapter H in Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan. 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As part of the National Water-Quality Assessment Program of the U.S. Geological Survey, this study examines the occurrence of nine trace elements in bed sediment of varying mineralogy and land use and assesses the possible effects of these trace elements on aquatic-macroinvertebrate community structure. Samples of bed sediment and macroinvertebrates were collected from 154 streams at sites representative of undeveloped, agricultural, urban, mined, or mixed land-use areas and 12 intermediate-scale ecoregions within the conterminous western United States, Alaska, and Hawaii from 1992 to 2000. The nine trace elements evaluated during this study—arsenic (As), cadmium (Cd), chromium (Cr), copper (Cu), lead (Pb), mercury (Hg), nickel (Ni), selenium (Se), and zinc (Zn)—were selected on the basis of potential ecologic significance and availability of sediment-quality guidelines. At most sites, the occurrence of these trace elements in bed sediment was at concentrations consistent with natural geochemical abundance, and the lowest concentrations were in bed-sediment samples collected from streams in undeveloped and agricultural areas. With the exception of Zn at sampling sites influenced by historic mining-related activities, median concentrations of all nine trace elements in bed sediment collected from sites representative of the five general land-use areas were below concentrations predicted to be harmful to aquatic macroinvertebrates. The highest concentrations of As, Cd, Pb, and Zn were in bed sediment collected from mined areas. Median concentrations of Cu and Ni in bed sediment were similarly enriched in areas of mining, urban, and mixed land use. Concentrations of Cr and Ni appear to originate largely from geologic sources, especially in the western coastal states (California, Oregon, and Washington), Alaska, and Hawaii. In these areas, naturally high concentrations of Cr and Ni can exceed concentrations that may adversely affect aquatic macroinvertebrates. Generally, Hg concentrations were below the sediment-quality guideline for this trace element but appeared elevated in urbanized areas and at sites contaminated by historic mining practices. Lastly, although there was no distinctive pattern in Se concentrations with land use, median bed-sediment concentrations were slightly elevated in urbanized areas.

Macroinvertebrate community structure was influenced by topographic, geologic, climatic, and in-stream characteristics. To account for inherent distribution patterns resulting from these influences, samples of macroinvertebrates were stratified by ecoregion to assess the influence of trace elements on community structure. Cumulative toxic units (CTUs) were used to evaluate gradients in trace-element concentrations in mixture. Correlation analyses among the trace elements under different land-use conditions indicate that trace-element mixtures vary among bed sediment and can have a marked influence on CTU composition. Macroinvertebrate response to bed-sediment trace-element exposure was evident only at the most highly contaminated sites, notably at sites classified as contaminated by the Comprehensive Environmental Response, Compensation, and Liability Act (CERCLA) as a result of historic mining activities. Results of this study agree with the findings of other studies evaluating trace-element exposure to in-stream macroinvertebrate community structure in that generally lower richness metrics and taxa dominance occur in streams where high trace-element enrichment occurs; however, not all streams in all areas have the same characterizing taxa. In the mountain and xeric ecosystems, the mayfly, Baetis sp.; the Diptera, Simulium sp.; caddisflies in the family Hydropsychiidae; midges in the family Orthocladiinae; and the worms belonging to Turbellaria and Naididae all demonstrated resilience to trace-element exposure and, in some cases, possible changes in physical habitat within stream ecosystems. The taxa characteristics within the Ozark Highland ecoregion were different than other ecoregions as evidenced by generally more diverse mayfly populations. In addition, Baetis sp. was common and dominated many of the mayfly populations found in the Rocky Mountain streams within the Mountain Southern Rockies and Mountain Northern Rockies ecoregions; however, within the Ozark Highland ecoregion, Tricorythodes sp. appeared to be more common than Baetis sp.

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Afghanistan","interactions":[],"lastModifiedDate":"2013-02-01T11:10:42","indexId":"ds709G","displayToPublicDate":"2013-01-04T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":310,"text":"Data Series","code":"DS","onlineIssn":"2327-638X","printIssn":"2327-0271","active":false,"publicationSubtype":{"id":5}},"seriesNumber":"709","chapter":"G","title":"Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Zarkashan mineral district in Afghanistan: Chapter G in Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan","docAbstract":"The U.S. Geological Survey (USGS), in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations, prepared databases for mineral-resource target areas in Afghanistan. The purpose of the databases is to (1) provide useful data to ground-survey crews for use in performing detailed assessments of the areas and (2) provide useful information to private investors who are considering investment in a particular area for development of its natural resources. The set of satellite-image mosaics provided in this Data Series (DS) is one such database. Although airborne digital color-infrared imagery was acquired for parts of Afghanistan in 2006, the image data have radiometric variations that preclude their use in creating a consistent image mosaic for geologic analysis. Consequently, image mosaics were created using ALOS (Advanced Land Observation Satellite; renamed Daichi) satellite images, whose radiometry has been well determined (Saunier, 2007a,b). This part of the DS consists of the locally enhanced ALOS image mosaics for the Zarkashan mineral district, which has copper and gold deposits. ALOS was launched on January 24, 2006, and provides multispectral images from the AVNIR (Advanced Visible and Near-Infrared Radiometer) sensor in blue (420–500 nanometer, nm), green (520–600 nm), red (610–690 nm), and near-infrared (760–890 nm) wavelength bands with an 8-bit dynamic range and a 10-meter (m) ground resolution. The satellite also provides a panchromatic band image from the PRISM (Panchromatic Remote-sensing Instrument for Stereo Mapping) sensor (520–770 nm) with the same dynamic range but a 2.5-m ground resolution. The image products in this DS incorporate copyrighted data provided by the Japan Aerospace Exploration Agency (©JAXA,2006,2007, 2008), but the image processing has altered the original pixel structure and all image values of the JAXA ALOS data, such that original image values cannot be recreated from this DS. As such, the DS products match JAXA criteria for value added products, which are not copyrighted, according to the ALOS end-user license agreement. The selection criteria for the satellite imagery used in our mosaics were images having (1) the highest solar-elevation angles (near summer solstice) and (2) the least cloud, cloud-shadow, and snow cover. The multispectral and panchromatic data were orthorectified with ALOS satellite ephemeris data, a process which is not as accurate as orthorectification using digital elevation models (DEMs); however, the ALOS processing center did not have a precise DEM. As a result, the multispectral and panchromatic image pairs were generally not well registered to the surface and not coregistered well enough to perform resolution enhancement on the multispectral data. Therefore, it was necessary to (1) register the 10-m AVNIR multispectral imagery to a well-controlled Landsat image base, (2) mosaic the individual multispectral images into a single image of the entire area of interest, (3) register each panchromatic image to the registered multispectral image base, and (4) mosaic the individual panchromatic images into a single image of the entire area of interest. The two image-registration steps were facilitated using an automated control-point algorithm developed by the USGS that allows image coregistration to within one picture element. Before rectification, the multispectral and panchromatic images were converted to radiance values and then to relative-reflectance values using the methods described in Davis (2006). Mosaicking the multispectral or panchromatic images started with the image with the highest sun-elevation angle and the least atmospheric scattering, which was treated as the standard image. The band-reflectance values of all other multispectral or panchromatic images within the area were sequentially adjusted to that of the standard image by determining band-reflectance correspondence between overlapping images using linear least-squares analysis. The resolution of the multispectral image mosaic was then increased to that of the panchromatic image mosaic using the SPARKLE logic, which is described in Davis (2006). Each of the four-band images within the resolution-enhanced image mosaic was individually subjected to a local-area histogram stretch algorithm (described in Davis, 2007), which stretches each band’s picture element based on the digital values of all picture elements within a 315-m radius. The final databases, which are provided in this DS, are three-band, color-composite images of the local-area-enhanced, natural-color data (the blue, green, and red wavelength bands) and color-infrared data (the green, red, and near-infrared wavelength bands). All image data were initially projected and maintained in Universal Transverse Mercator (UTM) map projection using the target area’s local zone (42 for Zarkashan) and the WGS84 datum. The final image mosaics were subdivided into two overlapping tiles or quadrants because of the large size of the target area. The two image tiles (or quadrants) for the Zarkashan area are provided as embedded geotiff images, which can be read and used by most geographic information system (GIS) and image-processing software. The tiff world files (tfw) are provided, even though they are generally not needed for most software to read an embedded geotiff image. Within the Zarkashan study area, three subareas were designated for detailed field investigations (that is, the Mine Area, Bolo Gold Prospect, and Luman-Tamaki Gold Prospect subareas); these subareas were extracted from the area’s image mosaic and are provided as separate embedded geotiff images.","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan (DS 709)","largerWorkSubtype":{"id":5,"text":"USGS Numbered Series"},"language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds709G","collaboration":"Prepared in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations and the Afghanistan Geological Survey. This report is Chapter G in Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan. For more information, see: Data Series 709.","usgsCitation":"Davis, P.A., and Cagney, L.E., 2012, Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Zarkashan mineral district in Afghanistan: Chapter G in Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan: U.S. Geological Survey Data Series 709, Readme; 2 Maps: 11 x 8.5 inches and 37.63 x 40.38 inches; 10 Images; 10 Metadata Files; Shapefiles; DS 709, https://doi.org/10.3133/ds709G.","productDescription":"Readme; 2 Maps: 11 x 8.5 inches and 37.63 x 40.38 inches; 10 Images; 10 Metadata Files; Shapefiles; DS 709","onlineOnly":"Y","additionalOnlineFiles":"Y","costCenters":[{"id":387,"text":"Mineral Resources Program","active":true,"usgs":true}],"links":[{"id":265290,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/usgs_thumb.jpg"},{"id":265281,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/ds/709/g/"},{"id":265283,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/ds/709/g/index_maps/Zarkashan_Area-of-Interest_Index_Map.pdf"},{"id":265282,"type":{"id":20,"text":"Read Me"},"url":"https://pubs.usgs.gov/ds/709/g/1_readme.txt"},{"id":265284,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/ds/709/g/index_maps/Zarkashan_Image_Index_Map.pdf"},{"id":265285,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/ds/709/g/index_maps/index_maps.html"},{"id":265286,"type":{"id":14,"text":"Image"},"url":"https://pubs.usgs.gov/ds/709/g/image_files/image_files.html"},{"id":265287,"type":{"id":16,"text":"Metadata"},"url":"https://pubs.usgs.gov/ds/709/g/metadata/metadata.html"},{"id":265288,"type":{"id":2,"text":"Additional Report Piece"},"url":"https://pubs.usgs.gov/ds/709/g/shapefiles/shapefiles.html"},{"id":265289,"type":{"id":22,"text":"Related Work"},"url":"https://pubs.usgs.gov/ds/709/index.html"}],"country":"Afghanistan","otherGeospatial":"Zarkashan Mineral District","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ 67.0,32.5 ], [ 67.0,33.5 ], [ 68.0,33.5 ], [ 68.0,32.5 ], [ 67.0,32.5 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"50e7f9ede4b033ce2d2433ed","contributors":{"authors":[{"text":"Davis, Philip A. pdavis@usgs.gov","contributorId":692,"corporation":false,"usgs":true,"family":"Davis","given":"Philip","email":"pdavis@usgs.gov","middleInitial":"A.","affiliations":[],"preferred":true,"id":471401,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Cagney, Laura E. 0000-0003-3282-2458 lcagney@usgs.gov","orcid":"https://orcid.org/0000-0003-3282-2458","contributorId":4744,"corporation":false,"usgs":true,"family":"Cagney","given":"Laura","email":"lcagney@usgs.gov","middleInitial":"E.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":471402,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70046851,"text":"70046851 - 2012 - Copper-nickel-rich, amalgamated ferromanganese crust-nodule deposits from Shatsky Rise, NW Pacific","interactions":[],"lastModifiedDate":"2013-07-11T13:12:01","indexId":"70046851","displayToPublicDate":"2013-01-01T13:01:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1757,"text":"Geochemistry, Geophysics, Geosystems","active":true,"publicationSubtype":{"id":10}},"title":"Copper-nickel-rich, amalgamated ferromanganese crust-nodule deposits from Shatsky Rise, NW Pacific","docAbstract":"A unique set of ferromanganese crusts and nodules collected from Shatsky Rise (SR), NW Pacific, were analyzed for mineralogical and chemical compositions, and dated using Be isotopes and cobalt chronometry. The composition of these midlatitude, deep-water deposits is markedly different from northwest-equatorial Pacific (PCZ) crusts, where most studies have been conducted. Crusts and nodules on SR formed in close proximity and some nodule deposits were cemented and overgrown by crusts, forming amalgamated deposits. The deep-water SR crusts are high in Cu, Li, and Th and low in Co, Te, and Tl concentrations compared to PCZ crusts. Thorium concentrations (ppm) are especially striking with a high of 152 (mean 56), compared to PCZ crusts (mean 11). The deep-water SR crusts show a diagenetic chemical signal, but not a diagenetic mineralogy, which together constrain the redox conditions to early oxic diagenesis. Diagenetic input to crusts is rare, but unequivocal in these deep-water crusts. Copper, Ni, and Li are strongly enriched in SR deep-water deposits, but only in layers older than about 3.4 Ma. Diagenetic reactions in the sediment and dissolution of biogenic calcite in the water column are the likely sources of these metals. The highest concentrations of Li are in crust layers that formed near the calcite compensation depth. The onset of Ni, Cu, and Li enrichment in the middle Miocene and cessation at about 3.4 Ma were accompanied by changes in the deep-water environment, especially composition and flow rates of water masses, and location of the carbonate compensation depth.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Geochemistry, Geophysics, Geosystems","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"AGU","doi":"10.1029/2012GC004286","usgsCitation":"Hein, J., Conrad, T., Frank, M., Christl, M., and Sager, W., 2012, Copper-nickel-rich, amalgamated ferromanganese crust-nodule deposits from Shatsky Rise, NW Pacific: Geochemistry, Geophysics, Geosystems, v. 13, no. 10, Q10022, https://doi.org/10.1029/2012GC004286.","productDescription":"Q10022","ipdsId":"IP-041319","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":487193,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"text":"External Repository"},{"id":274879,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":274878,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1029/2012GC004286"}],"otherGeospatial":"Shatsky Rise","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ 152.0,30.0 ], [ 152.0,44.0 ], [ 168.0,44.0 ], [ 168.0,30.0 ], [ 152.0,30.0 ] ] ] } } ] }","volume":"13","issue":"10","noUsgsAuthors":false,"publicationDate":"2012-10-30","publicationStatus":"PW","scienceBaseUri":"51dfd3e1e4b0d332bf22f372","contributors":{"authors":[{"text":"Hein, J.R. 0000-0002-5321-899X","orcid":"https://orcid.org/0000-0002-5321-899X","contributorId":61429,"corporation":false,"usgs":true,"family":"Hein","given":"J.R.","affiliations":[],"preferred":false,"id":480468,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Conrad, T.A.","contributorId":21791,"corporation":false,"usgs":true,"family":"Conrad","given":"T.A.","email":"","affiliations":[],"preferred":false,"id":480466,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Frank, M.","contributorId":103396,"corporation":false,"usgs":true,"family":"Frank","given":"M.","email":"","affiliations":[],"preferred":false,"id":480470,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Christl, M.","contributorId":76626,"corporation":false,"usgs":true,"family":"Christl","given":"M.","email":"","affiliations":[],"preferred":false,"id":480469,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Sager, W.W.","contributorId":54487,"corporation":false,"usgs":true,"family":"Sager","given":"W.W.","email":"","affiliations":[],"preferred":false,"id":480467,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70044817,"text":"70044817 - 2012 - Exploration review","interactions":[],"lastModifiedDate":"2013-04-29T08:58:39","indexId":"70044817","displayToPublicDate":"2013-01-01T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2755,"text":"Mining Engineering","active":true,"publicationSubtype":{"id":10}},"title":"Exploration review","docAbstract":"This summary of international mineral exploration activities for the year 2011 draws upon available information from industry sources, published literature and U.S. Geological Survey (USGS) specialists. This summary provides data on exploration budgets by region and mineral commodity, identifies significant mineral discoveries and areas of mineral exploration, discusses government programs affecting the mineral exploration industry and presents surveys returned by companies primarily focused on precious (gold, platinum-group metals and silver) and base (copper, lead, nickel and zinc) metals.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Mining Engineering","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"SME","usgsCitation":"Wilburn, D., Rapstine, T., and Lee, E., 2012, Exploration review: Mining Engineering, v. 64, no. 5, p. 40-60.","productDescription":"21 p.","startPage":"40","endPage":"60","ipdsId":"IP-036880","costCenters":[{"id":432,"text":"National Minerals Information Center","active":true,"usgs":true}],"links":[{"id":271593,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"64","issue":"5","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"517f9668e4b0e41721f7a350","contributors":{"authors":[{"text":"Wilburn, D.R.","contributorId":98911,"corporation":false,"usgs":true,"family":"Wilburn","given":"D.R.","email":"","affiliations":[],"preferred":false,"id":476364,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Rapstine, T.D.","contributorId":60103,"corporation":false,"usgs":true,"family":"Rapstine","given":"T.D.","email":"","affiliations":[],"preferred":false,"id":476363,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lee, E.C.","contributorId":16191,"corporation":false,"usgs":true,"family":"Lee","given":"E.C.","email":"","affiliations":[],"preferred":false,"id":476362,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70041292,"text":"70041292 - 2012 - Modeling the formation of porphyry-copper ores","interactions":[],"lastModifiedDate":"2019-05-30T12:37:17","indexId":"70041292","displayToPublicDate":"2013-01-01T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3338,"text":"Science","active":true,"publicationSubtype":{"id":10}},"title":"Modeling the formation of porphyry-copper ores","docAbstract":"Porphyry-copper ore systems, the source of much of the world's copper and molybdenum, form when metal-bearing fluids are expelled from shallow, degassing magmas. On page 1613 of this issue, Weis et al. (1) demonstrate that self-organizing processes focus metal deposition. Specifically, their simulation studies indicate that ores develop as consequences of dynamic variations in rock permeability driven by injection of volatile species from rising magmas. Scenarios with a static permeability structure could not reproduce key field observations, whereas dynamic permeability responses to magmatic-fluid injection localized a metal-precipitation front where enrichment by a factor of 103 could be achieved [for an overview of their numerical-simulation model CSMP++, see (2)].","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Science","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"AAAS","doi":"10.1126/science.1231706","usgsCitation":"Ingebritsen, S.E., 2012, Modeling the formation of porphyry-copper ores: Science, v. 338, no. 6114, p. 1551-1552, https://doi.org/10.1126/science.1231706.","productDescription":"2 p.","startPage":"1551","endPage":"1552","ipdsId":"IP-041919","costCenters":[{"id":148,"text":"Branch of Regional Research-Western Region","active":false,"usgs":true},{"id":615,"text":"Volcano Hazards Program","active":true,"usgs":true}],"links":[{"id":274352,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":274351,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1126/science.1231706"}],"volume":"338","issue":"6114","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"51d2a4ebe4b0ca1848338a6b","contributors":{"authors":[{"text":"Ingebritsen, Steven E. 0000-0001-6917-9369 seingebr@usgs.gov","orcid":"https://orcid.org/0000-0001-6917-9369","contributorId":818,"corporation":false,"usgs":true,"family":"Ingebritsen","given":"Steven","email":"seingebr@usgs.gov","middleInitial":"E.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":469489,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70044949,"text":"70044949 - 2012 - Alaska's rare earth deposits and resource potential","interactions":[],"lastModifiedDate":"2013-04-08T08:30:02","indexId":"70044949","displayToPublicDate":"2013-01-01T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2755,"text":"Mining Engineering","active":true,"publicationSubtype":{"id":10}},"title":"Alaska's rare earth deposits and resource potential","docAbstract":"Alaska’s known mineral endowment includes some of the largest and highest grade deposits of various metals, including gold, copper and zinc. Recently, Alaska has also been active in the worldwide search for sources of rare earth elements (REE) to replace exports now being limitedby China. Driven by limited supply of the rare earths, combined with their increasing use in new ‘green’ energy, lighting, transportation, and many other technological applications, the rare earth metals neodymium, europium and, in particular, the heavy rare earth elements terbium, dysprosium and yttrium are forecast to soon be in critical short supply (U.S. Department of Energy, 2010).","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Mining Engineering","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"SME","publisherLocation":"Englewood, CO","usgsCitation":"Barker, J.C., and Van Gosen, B.S., 2012, Alaska's rare earth deposits and resource potential: Mining Engineering, v. 64, no. 1, p. 20-32.","productDescription":"13 p.","startPage":"20","endPage":"32","ipdsId":"IP-031110","costCenters":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"links":[{"id":270646,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":270645,"type":{"id":15,"text":"Index Page"},"url":"https://me.smenet.org/abstract.cfm?preview=1&articleID=2502&page=20"}],"country":"United States","state":"Alaska","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ 172.5,51.2 ], [ 172.5,71.4 ], [ -130.0,71.4 ], [ -130.0,51.2 ], [ 172.5,51.2 ] ] ] } } ] }","volume":"64","issue":"1","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5163e6e2e4b0b7010f820147","contributors":{"authors":[{"text":"Barker, James C.","contributorId":77014,"corporation":false,"usgs":true,"family":"Barker","given":"James","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":476502,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Van Gosen, Bradley S. 0000-0003-4214-3811 bvangose@usgs.gov","orcid":"https://orcid.org/0000-0003-4214-3811","contributorId":1174,"corporation":false,"usgs":true,"family":"Van Gosen","given":"Bradley","email":"bvangose@usgs.gov","middleInitial":"S.","affiliations":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true},{"id":387,"text":"Mineral Resources Program","active":true,"usgs":true}],"preferred":true,"id":476501,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70191927,"text":"70191927 - 2012 - Dzhezkazgan and associated sandstone copper deposits of the Chu-Sarysu basin, Central Kazakhstan","interactions":[],"lastModifiedDate":"2017-11-16T10:41:03","indexId":"70191927","displayToPublicDate":"2012-12-31T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"title":"Dzhezkazgan and associated sandstone copper deposits of the Chu-Sarysu basin, Central Kazakhstan","docAbstract":"
Sandstone-hosted copper (sandstone Cu) deposits occur within a 200-km reach of the northern Chu-Sarysu basin of central Kazakhstan (Dzhezkazgan and Zhaman-Aibat deposits, and the Zhilandy group of deposits). The deposits consist of Cu sulfide minerals as intergranular cement and grain replacement in 10 ore-bearing members of sandstone and conglomerate within a 600- to 1,000-m thick Pennsylvanian fluvial red-bed sequence. Copper metal content of the deposits ranges from 22 million metric tons (Mt, Dzehzkazgan) to 0.13Mt (Karashoshak in the Zhilandy group), with average grades of 0.85 to 1.7% Cu and significant values for silver (Ag) and rhenium (Re). Broader zones of iron reduction (bleaching) of sandstones and conglomerates of the red-bed sequence extend over 10 km beyond each of the deposits along E-NE-trending anticlines, which began to form in the Pennsylvanian. The bleached zones and organic residues within them are remnants of ormer petroleum fluid accumulations trapped by these anticlines. Deposit sites along these F1anticlines are localized at and adjacent to the intersections of nearly orthogonal N-NW-trending F2synclines. These structural lows served to guide the flow of dense ore brines across the petroleum-bearing anticlines, resulting in ore sulfide precipitation where the two fluids mixed. The ore brine was sourced either from the overlying Early Permian lacustrine evaporitic basin, whose depocenter occurs between the major deposits, or from underlying Upper Devonian marine evaporites. Sulfur isotopes indicate biologic reduction of sulfate but do not resolve whether the sulfate was contributed from the brine or from the petroleum fluids. New Re-Os age dates of Cu sulfides from the Dzhezkazgan deposit indicate that mineralization took place between 299 to 309 Ma near the Pennsylvanian-Permian age boundary. At the Dzhezkazgan and some Zhilandy deposits, F2fold deformation continued after ore deposition. Copper orebodies in Lower Permian shale near the Zhaman-Aibat deposit indicate that at least some of the mineralization there is younger than at Dzhezkazgan, consistent with the Re-Os age and with differences in their ore Pb isotopes.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Society of Economic Geologists Special Publication","language":"English","publisher":"Society of Economic Geologists","usgsCitation":"Box, S.E., Seltmann, R., Zientek, M.L., Syusyura, B., Creaser, R., and Dolgopolova, A., 2012, Dzhezkazgan and associated sandstone copper deposits of the Chu-Sarysu basin, Central Kazakhstan, chap. of Society of Economic Geologists Special Publication, v. 16, p. 303-328.","productDescription":"26 p.","startPage":"303","endPage":"328","ipdsId":"IP-037813","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":348873,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Kazakhstan","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n 63,\n 41\n ],\n [\n 77,\n 41\n ],\n [\n 77,\n 48.5\n ],\n [\n 63,\n 48.5\n ],\n [\n 63,\n 41\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"16","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5a61053fe4b06e28e9c25526","contributors":{"authors":[{"text":"Box, Stephen E. 0000-0002-5268-8375 sbox@usgs.gov","orcid":"https://orcid.org/0000-0002-5268-8375","contributorId":1843,"corporation":false,"usgs":true,"family":"Box","given":"Stephen","email":"sbox@usgs.gov","middleInitial":"E.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":713737,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Seltmann, Reimar","contributorId":73450,"corporation":false,"usgs":true,"family":"Seltmann","given":"Reimar","email":"","affiliations":[],"preferred":false,"id":713740,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Zientek, Michael L. 0000-0002-8522-9626 mzientek@usgs.gov","orcid":"https://orcid.org/0000-0002-8522-9626","contributorId":2420,"corporation":false,"usgs":true,"family":"Zientek","given":"Michael","email":"mzientek@usgs.gov","middleInitial":"L.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":713736,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Syusyura, Boris","contributorId":72104,"corporation":false,"usgs":true,"family":"Syusyura","given":"Boris","email":"","affiliations":[],"preferred":false,"id":713739,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Creaser, Robert A.","contributorId":71042,"corporation":false,"usgs":true,"family":"Creaser","given":"Robert A.","affiliations":[],"preferred":false,"id":713741,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Dolgopolova, Alla","contributorId":96943,"corporation":false,"usgs":true,"family":"Dolgopolova","given":"Alla","email":"","affiliations":[],"preferred":false,"id":713738,"contributorType":{"id":1,"text":"Authors"},"rank":14}]}} ,{"id":70189076,"text":"70189076 - 2012 - Pyrite–sulfosalt reactions and semimetal fractionation in the Chinkuashih, Taiwan, copper–gold deposit: A 1 Ma paleo-fumarole","interactions":[],"lastModifiedDate":"2019-12-21T07:34:49","indexId":"70189076","displayToPublicDate":"2012-12-31T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1765,"text":"Geofluids","active":true,"publicationSubtype":{"id":10}},"title":"Pyrite–sulfosalt reactions and semimetal fractionation in the Chinkuashih, Taiwan, copper–gold deposit: A 1 Ma paleo-fumarole","docAbstract":"

The mineralized fracture system that underlay paleo-fumarole field at Chinkuashih, Taiwan has been exposed by copper–gold mining to depths of about 550 m below the paleo-surface. Its mineralogy and systematic variations in metal and semimetal (Fe, Cu, As, Sb, Bi, Hg, Cd, Sn, Zn, Pb, Se, Te, Au, Ag) concentrations provide insights into the chemical responses of a magmatic-vapor phase as it expands through fracture arrays to the surface and discharges as fumaroles associated with more extensive solfatara. At Chinkuashih, following initial sealing of the fractures by silica-alunite alteration, brittle failure reestablished discharge from an underlying reservoir of magmatic vapor. Crystalline pyrite was deposited first in the fractures and was succeeded and replaced by ‘enargite’ (Cu3(As,Sb)S4) as sulfosalt encrustations (‘sublimate’) on fracture surfaces and in extensional cracks. Subsequent recrystallization resulted in complex exsolution intergrowths with antimony fractionation to the evolving crystal–vapor interface. Heavy metal fractionation between sulfosalt and vapor enriched the vapor phase in heavy metals that subsequently precipitated as complex Bi–Hg–Sn sulfosalts in discrete areas (paleo-fumaroles) close to the paleo-surface in a manner analogous to modern-day fumaroles on active volcanoes such as Vulcano, Italy. As in similar paleo-fumaroles (e.g., El Indio, Chile and Lepanto, Philippines), the most characteristic reaction sequence is the partial replacement of the early pyrite by enargite and Fe-tennantite. It is proposed that this reaction tracks the decrease in the pressure of the underlying magmatic-vapor reservoir because of the sustained discharge of vapor to the surface.

","language":"English","publisher":"Elsevier","doi":"10.1111/j.1468-8123.2012.00367.x","usgsCitation":"Henley, R., and Berger, B.R., 2012, Pyrite–sulfosalt reactions and semimetal fractionation in the Chinkuashih, Taiwan, copper–gold deposit: A 1 Ma paleo-fumarole: Geofluids, v. 12, no. 3, p. 245-260, https://doi.org/10.1111/j.1468-8123.2012.00367.x.","productDescription":"16 p.","startPage":"245","endPage":"260","ipdsId":"IP-037251","costCenters":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"links":[{"id":343199,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Taiwan","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n 120.904541015625,\n 21.87169463514272\n ],\n [\n 121.058349609375,\n 22.63429269379353\n ],\n [\n 121.26708984374999,\n 22.755920681486405\n ],\n [\n 121.56372070312499,\n 23.41284706430993\n ],\n [\n 121.871337890625,\n 24.287026865376436\n ],\n [\n 122.00317382812499,\n 24.70691524106633\n ],\n [\n 121.915283203125,\n 24.806681353851964\n ],\n [\n 122.23388671874999,\n 25.145284610685064\n ],\n [\n 121.805419921875,\n 25.284437746983055\n ],\n [\n 121.57470703125,\n 25.37380917154398\n ],\n [\n 121.36596679687499,\n 25.37380917154398\n ],\n [\n 121.13525390625,\n 25.284437746983055\n ],\n [\n 120.673828125,\n 24.926294766395593\n ],\n [\n 120.30029296875,\n 24.246964554300924\n ],\n [\n 120.02563476562501,\n 23.52370005882413\n ],\n [\n 119.84985351562499,\n 22.806567100271522\n ],\n [\n 120.201416015625,\n 22.553147478403194\n ],\n [\n 120.41015624999999,\n 22.339914425562032\n ],\n [\n 120.55297851562499,\n 22.055096050575845\n ],\n [\n 120.728759765625,\n 21.841104749065032\n ],\n [\n 120.904541015625,\n 21.87169463514272\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"12","issue":"3","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2012-05-23","publicationStatus":"PW","scienceBaseUri":"595611c6e4b0d1f9f05067da","contributors":{"authors":[{"text":"Henley, R.W.","contributorId":52810,"corporation":false,"usgs":true,"family":"Henley","given":"R.W.","email":"","affiliations":[],"preferred":false,"id":702969,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Berger, Byron R. bberger@usgs.gov","contributorId":1490,"corporation":false,"usgs":true,"family":"Berger","given":"Byron","email":"bberger@usgs.gov","middleInitial":"R.","affiliations":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":702785,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70042049,"text":"sir20105090G - 2012 - Porphyry copper assessment of the Mesozoic of East Asia: China, Vietnam, North Korea, Mongolia, and Russia: Chapter G in Global mineral resource assessment","interactions":[{"subject":{"id":70042049,"text":"sir20105090G - 2012 - Porphyry copper assessment of the Mesozoic of East Asia: China, Vietnam, North Korea, Mongolia, and Russia: Chapter G in Global mineral resource assessment","indexId":"sir20105090G","publicationYear":"2012","noYear":false,"chapter":"G","title":"Porphyry copper assessment of the Mesozoic of East Asia: China, Vietnam, North Korea, Mongolia, and Russia: Chapter G in Global mineral resource assessment"},"predicate":"IS_PART_OF","object":{"id":70040436,"text":"sir20105090 - 2010 - Global mineral resource assessment","indexId":"sir20105090","publicationYear":"2010","noYear":false,"title":"Global mineral resource assessment"},"id":1}],"isPartOf":{"id":70040436,"text":"sir20105090 - 2010 - Global mineral resource assessment","indexId":"sir20105090","publicationYear":"2010","noYear":false,"title":"Global mineral resource assessment"},"lastModifiedDate":"2019-12-30T14:20:50","indexId":"sir20105090G","displayToPublicDate":"2012-12-21T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2010-5090","chapter":"G","title":"Porphyry copper assessment of the Mesozoic of East Asia: China, Vietnam, North Korea, Mongolia, and Russia: Chapter G in Global mineral resource assessment","docAbstract":"

The U.S. Geological Survey (USGS) collaborated with the China Geological Survey (CGS) to conduct a mineral resource assessment of Mesozoic porphyry copper deposits in East Asia. This area hosts several very large porphyry deposits, exemplified by the Dexing deposit in eastern China that contains more than 8,000,000 metric tons of copper. In addition, large parts of the area are undergoing active exploration and are likely to contain undiscovered porphyry copper deposits.

\n

Three tracts were delineated to be permissive for Mesozoic porphyry copper deposits in East Asia: the Manchuride, Coastal Pacific, and East Qinling tracts, all Jurassic through Cretaceous in age. The tracts are based on mapped and inferred subsurface distributions of igneous rocks that define areas where the occurrence of porphyry copper deposits is possible. These tracts range in area from about 170,000 to about 1,400,000 km2. Although maps at a variety of scales were used in the assessment, the final tract boundaries are intended for use at a scale of 1:1,000,000.

\n

These Mesozoic deposits in East Asia all formed in post-subduction environments, environments newly recognized as permissive for the occurrence of porphyry copper deposits. Based on the grade, tonnage, and geologic characteristics of the known deposits, two tracts, Manchuride and Coastal Pacific, were evaluated using the general (Cu-Mo-Au) porphyry copper grade and tonnage model. The East Qinling tract was evaluated using the molybdenum-rich (Cu-Mo) model. Assessment participants estimated numbers of undiscovered deposits at different levels of confidence for each permissive tract. These estimates were then combined with the selected grade and tonnage models using Monte Carlo simulation to generate quantitative probabilistic estimates of undiscovered resources. Resources in future extensions of deposits with identified resources were not specifically evaluated.

\n

Assessment results, presented in tables and graphs, show mean amounts of metal and rock in undiscovered deposits at different quantile levels, as well as the arithmetic mean for each tract. This assessment estimated a mean total of about 44 undiscovered porphyry copper deposits within the assessed permissive tracts in East Asia. This represents nearly 4 times the 12 known deposits. Predicted mean (arithmetic) resources that could be associated with these undiscovered deposits are about 198,000,000 metric tons (t) of copper and about 3,900 t of gold, as well as byproduct molybdenum and silver. The reported identified resources for those 12 known deposits total about 23,000,000 t of copper and about 850 t of gold. The assessment area is estimated to contain nearly nine times as much copper in undiscovered porphyry copper deposits as has been identified to date.

\n

This report includes an overview of the assessment results and summary tables. Descriptions of each tract are included in appendixes, with estimates of numbers of undiscovered deposits, and probabilistic estimates of amounts of copper, molybdenum, gold, and silver that could be contained in undiscovered deposits for each permissive tract. A geographic information system that accompanies the report includes tract boundaries and a database of known porphyry copper deposits and prospects.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20105090G","collaboration":"Prepared in cooperation with the Russian Academy of Sciences, China Geological Survey, Chinese Academy of Geological Sciences, the Coordinating Committee for Geoscience Programs in East and Southeast Asia, and XDM Geological Consultants, Inc.","usgsCitation":"Ludington, S., Mihalasky, M.J., Hammarstrom, J.M., Robinson, G.R., Frost, T.P., Gans, K.D., Light, T., Miller, R.J., and Alexeiev, D.V., 2012, Porphyry copper assessment of the Mesozoic of East Asia: China, Vietnam, North Korea, Mongolia, and Russia: Chapter G in Global mineral resource assessment: U.S. Geological Survey Scientific Investigations Report 2010-5090, Report: vii, 53 p.; Appendix D; Appendix E metadata folder; Appendix E GIS data, https://doi.org/10.3133/sir20105090G.","productDescription":"Report: vii, 53 p.; Appendix D; Appendix E metadata folder; Appendix E GIS data","numberOfPages":"66","onlineOnly":"Y","additionalOnlineFiles":"Y","costCenters":[{"id":387,"text":"Mineral Resources Program","active":true,"usgs":true}],"links":[{"id":264693,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir_2010_5090_g.gif"},{"id":264690,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2010/5090/g/sir2010-5090g_text.pdf","text":"Report","size":"4.7 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Report"},{"id":264691,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2010/5090/g/EASIA_metadata","text":"Appendix E metadata","size":"31 kB","description":"Appendix E metadata"},{"id":264692,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2010/5090/g/GIS_SIR5090G_appendix_E.zip","text":"Appendix E GIS data","size":"19 MB","linkFileType":{"id":6,"text":"zip"},"description":"Appendix E GIS data"},{"id":264688,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2010/5090/g/"},{"id":264689,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2010/5090/g/EAM_DEPPROS.xlsx","text":"Appendix D","size":"86 kB","linkFileType":{"id":3,"text":"xlsx"},"description":"Appendix D"}],"projection":"Asia North Albers Equal Area Conic Projection","country":"China, Mongolia, North Korea, Russia, Vietnam","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n 105.1171875,\n 8.059229627200192\n ],\n [\n 109.86328125,\n 12.983147716796578\n ],\n [\n 106.962890625,\n 19.394067895396613\n ],\n [\n 120.673828125,\n 26.82407078047018\n ],\n [\n 122.607421875,\n 35.67514743608467\n ],\n [\n 128.056640625,\n 42.4234565179383\n ],\n [\n 132.275390625,\n 46.98025235521883\n ],\n [\n 136.58203125,\n 52.96187505907603\n ],\n [\n 132.71484375,\n 56.46249048388979\n ],\n [\n 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Jr. 0000-0002-9676-9564 grobinso@usgs.gov","orcid":"https://orcid.org/0000-0002-9676-9564","contributorId":172765,"corporation":false,"usgs":true,"family":"Robinson","given":"Gilpin","suffix":"Jr.","email":"grobinso@usgs.gov","middleInitial":"R.","affiliations":[{"id":245,"text":"Eastern Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":false,"id":470685,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Frost, Thomas P. 0000-0001-8348-8432 tfrost@usgs.gov","orcid":"https://orcid.org/0000-0001-8348-8432","contributorId":203,"corporation":false,"usgs":true,"family":"Frost","given":"Thomas","email":"tfrost@usgs.gov","middleInitial":"P.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":470680,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Gans, Kathleen D. 0000-0002-7545-9655 kgans@usgs.gov","orcid":"https://orcid.org/0000-0002-7545-9655","contributorId":5403,"corporation":false,"usgs":true,"family":"Gans","given":"Kathleen","email":"kgans@usgs.gov","middleInitial":"D.","affiliations":[],"preferred":true,"id":470684,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Light, Thomas D.","contributorId":46098,"corporation":false,"usgs":true,"family":"Light","given":"Thomas D.","affiliations":[],"preferred":false,"id":470686,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Miller, Robert J. rjmiller@usgs.gov","contributorId":2516,"corporation":false,"usgs":true,"family":"Miller","given":"Robert","email":"rjmiller@usgs.gov","middleInitial":"J.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":470682,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Alexeiev, Dmitriy V.","contributorId":89425,"corporation":false,"usgs":true,"family":"Alexeiev","given":"Dmitriy","email":"","middleInitial":"V.","affiliations":[],"preferred":false,"id":470687,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70041450,"text":"70041450 - 2012 - Low-level copper exposures increase visibility and vulnerability of juvenile coho salmon to cutthroat trout predators","interactions":[],"lastModifiedDate":"2020-12-29T19:35:54.199227","indexId":"70041450","displayToPublicDate":"2012-12-18T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1450,"text":"Ecological Applications","active":true,"publicationSubtype":{"id":10}},"title":"Low-level copper exposures increase visibility and vulnerability of juvenile coho salmon to cutthroat trout predators","docAbstract":"

Copper contamination in surface waters is common in watersheds with mining activities or agricultural, industrial, commercial, and residential human land uses. This widespread pollutant is neurotoxic to the chemosensory systems of fish and other aquatic species. Among Pacific salmonids (Oncorhynchus spp.), copper-induced olfactory impairment has previously been shown to disrupt behaviors reliant on a functioning sense of smell. For juvenile coho salmon (O. kisutch), this includes predator avoidance behaviors triggered by a chemical alarm cue (conspecific skin extract). However, the survival consequences of this sublethal neurobehavioral toxicity have not been explored. In the present study juvenile coho were exposed to low levels of dissolved copper (5-20 microg/L for 3 h) and then presented with cues signaling the proximity of a predator. Unexposed coho showed a sharp reduction in swimming activity in response to both conspecific skin extract and the upstream presence of a cutthroat trout predator (O. clarki clarki) previously fed juvenile coho. This alarm response was absent in prey fish that were exposed to copper. Moreover, cutthroat trout were more effective predators on copper-exposed coho during predation trials, as measured by attack latency, survival time, and capture success rate. The shift in predator-prey dynamics was similar when predators and prey were co-exposed to copper. Overall, we show that copper-exposed coho are unresponsive to their chemosensory environment, unprepared to evade nearby predators, and significantly less likely to survive an attack sequence. Our findings contribute to a growing understanding of how common environmental contaminants alter the chemical ecology of aquatic communities.

","language":"English","publisher":"Ecological Society of America","doi":"10.1890/11-2001.1","usgsCitation":"McIntyre, J.K., Baldwin, D., Beauchamp, D.A., and Scholz, N.L., 2012, Low-level copper exposures increase visibility and vulnerability of juvenile coho salmon to cutthroat trout predators: Ecological Applications, v. 22, no. 5, p. 1460-1471, https://doi.org/10.1890/11-2001.1.","productDescription":"12 p.","startPage":"1460","endPage":"1471","ipdsId":"IP-042329","costCenters":[{"id":204,"text":"Cooperative Research Unit Seattle","active":false,"usgs":true}],"links":[{"id":381736,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"22","issue":"5","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"50d20ba3e4b08b071e771b2c","contributors":{"authors":[{"text":"McIntyre, Jenifer K.","contributorId":52857,"corporation":false,"usgs":true,"family":"McIntyre","given":"Jenifer","email":"","middleInitial":"K.","affiliations":[],"preferred":false,"id":469744,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Baldwin, David H.","contributorId":94938,"corporation":false,"usgs":true,"family":"Baldwin","given":"David H.","affiliations":[],"preferred":false,"id":469745,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Beauchamp, David A. 0000-0002-3592-8381 fadave@usgs.gov","orcid":"https://orcid.org/0000-0002-3592-8381","contributorId":4205,"corporation":false,"usgs":true,"family":"Beauchamp","given":"David","email":"fadave@usgs.gov","middleInitial":"A.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":469742,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Scholz, Nathaniel L.","contributorId":51618,"corporation":false,"usgs":true,"family":"Scholz","given":"Nathaniel","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":469743,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70041732,"text":"ofr20121179 - 2012 - Gold deposits of the Carolina Slate Belt, southeastern United States--Age and origin of the major gold producers","interactions":[],"lastModifiedDate":"2018-10-15T09:02:57","indexId":"ofr20121179","displayToPublicDate":"2012-12-11T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2012-1179","title":"Gold deposits of the Carolina Slate Belt, southeastern United States--Age and origin of the major gold producers","docAbstract":"Gold- and iron sulfide-bearing deposits of the southeastern United States have distinctive mineralogical and geochemical features that provide a basis for constructing models of ore genesis for exploration and assessment of gold resources. The largest (historic) deposits, in approximate million ounces of gold (Moz Au), include those in the Haile (~ 4.2 Moz Au), Ridgeway (~1.5 Moz Au), Brewer (~0.25 Moz Au), and Barite Hill (0.6 Moz Au) mines. Host rocks are Late Proterozoic to early Paleozoic (~553 million years old) metaigneous and metasedimentary rocks of the Carolina Slate Belt that share a geologic affinity with the classic Avalonian tectonic zone. The inferred syngenetic and epithermal-subvolcanic quartz-porphyry settings occur stratigraphically between sequences of metavolcanic rocks of the Persimmon Fork and Uwharrie Formations and overlying volcanic and epiclastic rocks of the Tillery and Richtex Formations (and regional equivalents). The Carolina Slate Belt is highly prospective for many types of gold ore hosted within quartz-sericite-pyrite altered volcanic rocks, juvenile metasedimentary rocks, and in associated shear zones. For example, sheared and deformed auriferous volcanogenic massive sulfide deposits at Barite Hill, South Carolina, and in the Gold Hill trend, North Carolina, are hosted primarily by laminated mudstone and felsic volcanic to volcaniclastic rocks. The high-sulfidation epithermal style of gold mineralization at Brewer and low-sulfidation gold ores of the Champion pit at Haile occur in breccias associated with subvolcanic quartz porphyry and within crystal-rich tuffs, ash flows, and subvolcanic rhyolite. The Ridgeway and Haile deposits are primarily epithermal replacements and feeder zones within (now) metamorphosed crystal-rich tuffs, volcaniclastic sediments, and siltstones originally deposited in a marine volcanic-arc basinal setting. Recent discoveries in the region include (1) extensions of known deposits, such as at Haile where drilling has identified an extensive gold-rich feeder system; and (2) newly discovered prospects like the porphyry-style gold-copper-molybdenum occurrence reported at Deep River, N.C. Gold ores at Ridgeway and Haile represent the low-sulfidation, disseminated, shallow subaqueous tuffaceous equivalents of intrusion-related high-sulfidation ores such as those at Brewer. Haile also has mineralogical features that support a stockwork disseminated model of pyrite-gold-sericite mineralization in which a significant amount of ore was deposited in sediments at or near the surface. The potential is high for gold-rich ore at depth in the funnel-shaped feeder zones that likely underlie such surface variants of high sulfidation–low sulfidation epithermal systems and for new discoveries of similar deposits in areas undercover. Exploration strategies for large-scale gold-mineralizing systems applied to rocks of the Carolina Slate Belt, and by extension, the Carolinian-Avalonian tectonic zone of North America, benefit from applying subvolcanic and basinal epithermal models for gold mineralization.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20121179","usgsCitation":"Foley, N.K., and Ayuso, R.A., 2012, Gold deposits of the Carolina Slate Belt, southeastern United States--Age and origin of the major gold producers: U.S. Geological Survey Open-File Report 2012-1179, iv, 26 p., https://doi.org/10.3133/ofr20121179.","productDescription":"iv, 26 p.","numberOfPages":"30","onlineOnly":"Y","costCenters":[{"id":245,"text":"Eastern Mineral and Environmental Resources Science Center","active":true,"usgs":true},{"id":410,"text":"National Center","active":false,"usgs":true}],"links":[{"id":263948,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr_2012_1179.gif"},{"id":263946,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2012/1179/"},{"id":263947,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2012/1179/pdf/ofr2012-1179.pdf"}],"country":"United States","state":"North Carolina;South Carolina;Virginia;Georgia","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"50c85611e4b03bc63bd679a2","contributors":{"authors":[{"text":"Foley, Nora K. 0000-0003-0124-3509 nfoley@usgs.gov","orcid":"https://orcid.org/0000-0003-0124-3509","contributorId":4010,"corporation":false,"usgs":true,"family":"Foley","given":"Nora","email":"nfoley@usgs.gov","middleInitial":"K.","affiliations":[{"id":245,"text":"Eastern Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":470122,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ayuso, Robert A. 0000-0002-8496-9534 rayuso@usgs.gov","orcid":"https://orcid.org/0000-0002-8496-9534","contributorId":2654,"corporation":false,"usgs":true,"family":"Ayuso","given":"Robert","email":"rayuso@usgs.gov","middleInitial":"A.","affiliations":[{"id":387,"text":"Mineral Resources Program","active":true,"usgs":true},{"id":245,"text":"Eastern Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":470121,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70041731,"text":"sir20105090F - 2012 - Porphyry copper assessment of the Tibetan Plateau, China: Chapter F in Global mineral resource assessment","interactions":[{"subject":{"id":70041731,"text":"sir20105090F - 2012 - Porphyry copper assessment of the Tibetan Plateau, China: Chapter F in Global mineral resource assessment","indexId":"sir20105090F","publicationYear":"2012","noYear":false,"chapter":"F","title":"Porphyry copper assessment of the Tibetan Plateau, China: Chapter F in Global mineral resource assessment"},"predicate":"IS_PART_OF","object":{"id":70040436,"text":"sir20105090 - 2010 - Global mineral resource assessment","indexId":"sir20105090","publicationYear":"2010","noYear":false,"title":"Global mineral resource assessment"},"id":1}],"isPartOf":{"id":70040436,"text":"sir20105090 - 2010 - Global mineral resource assessment","indexId":"sir20105090","publicationYear":"2010","noYear":false,"title":"Global mineral resource assessment"},"lastModifiedDate":"2019-12-30T14:15:51","indexId":"sir20105090F","displayToPublicDate":"2012-12-11T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2010-5090","chapter":"F","title":"Porphyry copper assessment of the Tibetan Plateau, China: Chapter F in Global mineral resource assessment","docAbstract":"

The U.S. Geological Survey collaborated with the China Geological Survey to conduct a mineral-resource assessment of resources in porphyry copper deposits on the Tibetan Plateau in western China. This area hosts several very large porphyry deposits, exemplified by the Yulong and Qulong deposits, each containing at least 7,000,000 metric tons (t) of copper. However, large parts of the area are underexplored and are likely to contain undiscovered porphyry copper deposits.

\n

Three tracts were delineated as permissive for porphyry copper deposits on the Tibetan Plateau—the Yulong (Eocene and Oligocene), Dali (Eocene through Miocene), and Gangdese (Oligocene and Miocene) tracts. The tracts were defined based on mapped and inferred subsurface distributions of igneous rocks of specific age ranges in which the occurrence of porphyry copper deposits is possible. These tracts range in area from about 95,000 to about 240,000 square kilometers. Although maps of different scales were used in the assessment, the final tract boundaries are intended for use at a scale of 1:1,000,000.

\n

The deposits on the Tibetan Plateau all formed in a post-subduction environment, one newly recognized as permissive for the occurrence of porphyry copper deposits. Based on the grade, tonnage, and geologic characteristics of the known deposits, two tracts, Yulong and Gangdese, were evaluated using the general (Cu-Mo-Au) porphyry copper grade and tonnage model. The Dali tract was evaluated using the gold-rich (Cu-Au) submodel. Assessment participants estimated numbers of undiscovered deposits at different levels of confidence for each permissive tract. These estimates were then combined with the selected grade and tonnage models using Monte Carlo simulation to generate quantitative probabilistic estimates of undiscovered resources. Additional resources in extensions of deposits with identified resources were not specifically evaluated.

\n

Assessment results, presented in tables and graphs, show mean expected amounts of metal and rock in undiscovered deposits at different quantile levels, as well as the arithmetic mean for each tract. This assessment estimated a mean of 39 undiscovered porphyry copper deposits within the assessed permissive tracts on the Tibetan Plateau. This represents nearly four times the number of known deposits (11) already discovered. Predicted mean (arithmetic) resources that could be associated with the undiscovered deposits are about 145,000,000 t of copper and about 4,900 t of gold, as well as byproduct molybdenum and silver. Reliable reports of the identified resources in the 11 known deposits total about 27,000,000 t of copper and about 800 t of gold. Therefore, based on the assessments of undiscovered Tibetan Plateau resources in this report, about six times as much copper may occur in undiscovered porphyry copper deposits as has been identified to date.

","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"Global mineral resource assessment (Scientific Investigations Report 2010-5090)","largerWorkSubtype":{"id":5,"text":"USGS Numbered Series"},"language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20105090F","collaboration":"Prepared in cooperation with the China Geological Survey and the Chinese Academy of Geological Sciences","usgsCitation":"Ludington, S., Hammarstrom, J.M., Robinson, G.R., Mars, J.L., and Miller, R.J., 2012, Porphyry copper assessment of the Tibetan Plateau, China: Chapter F in Global mineral resource assessment: U.S. Geological Survey Scientific Investigations Report 2010-5090, Report: viii, 63 p.; Metadata folder; GIS data zip package, https://doi.org/10.3133/sir20105090F.","productDescription":"Report: viii, 63 p.; Metadata folder; GIS data zip package","numberOfPages":"74","onlineOnly":"Y","additionalOnlineFiles":"Y","costCenters":[{"id":245,"text":"Eastern Mineral and Environmental Resources Science Center","active":true,"usgs":true},{"id":387,"text":"Mineral Resources Program","active":true,"usgs":true}],"links":[{"id":263953,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir_2010_5090_f.gif"},{"id":263952,"type":{"id":23,"text":"Spatial Data"},"url":"https://pubs.usgs.gov/sir/2010/5090/f/sir2010-5090f_gis.zip"},{"id":263951,"type":{"id":16,"text":"Metadata"},"url":"https://pubs.usgs.gov/sir/2010/5090/f/sir2010-5090f_metadata"},{"id":263949,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2010/5090/f/"},{"id":263950,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2010/5090/f/sir2010-5090f_text.pdf"}],"projection":"Asia North Albers Equal Area","country":"China","otherGeospatial":"Tibetan Plateau","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n 84.990234375,\n 28.92163128242129\n ],\n [\n 90.17578124999999,\n 28.69058765425071\n ],\n [\n 92.8125,\n 28.76765910569123\n ],\n [\n 97.20703125,\n 28.92163128242129\n ],\n [\n 98.61328125,\n 27.916766641249065\n ],\n [\n 101.25,\n 22.836945920943855\n ],\n [\n 104.150390625,\n 23.241346102386135\n ],\n [\n 103.71093749999999,\n 26.27371402440643\n ],\n [\n 101.42578124999999,\n 30.751277776257812\n ],\n [\n 97.646484375,\n 31.50362930577303\n ],\n [\n 90.703125,\n 33.43144133557529\n ],\n [\n 85.166015625,\n 34.23451236236987\n ],\n [\n 82.177734375,\n 31.653381399664\n ],\n [\n 84.990234375,\n 28.92163128242129\n ]\n ]\n ]\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"50c85619e4b03bc63bd679aa","contributors":{"authors":[{"text":"Ludington, Steve","contributorId":106848,"corporation":false,"usgs":true,"family":"Ludington","given":"Steve","affiliations":[],"preferred":false,"id":470120,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hammarstrom, Jane M. 0000-0003-2742-3460 jhammars@usgs.gov","orcid":"https://orcid.org/0000-0003-2742-3460","contributorId":1226,"corporation":false,"usgs":true,"family":"Hammarstrom","given":"Jane","email":"jhammars@usgs.gov","middleInitial":"M.","affiliations":[{"id":387,"text":"Mineral Resources Program","active":true,"usgs":true},{"id":245,"text":"Eastern Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":470116,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Robinson, Gilpin R. Jr. grobinso@usgs.gov","contributorId":3083,"corporation":false,"usgs":true,"family":"Robinson","given":"Gilpin","suffix":"Jr.","email":"grobinso@usgs.gov","middleInitial":"R.","affiliations":[{"id":245,"text":"Eastern Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":false,"id":470118,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Mars, John L. jmars@usgs.gov","contributorId":3428,"corporation":false,"usgs":true,"family":"Mars","given":"John","email":"jmars@usgs.gov","middleInitial":"L.","affiliations":[],"preferred":false,"id":470119,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Miller, Robert J. rjmiller@usgs.gov","contributorId":2516,"corporation":false,"usgs":true,"family":"Miller","given":"Robert","email":"rjmiller@usgs.gov","middleInitial":"J.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":470117,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70040860,"text":"sir20125164 - 2012 - Global exploration and production capacity for platinum-group metals from 1995 through 2015","interactions":[],"lastModifiedDate":"2012-12-20T08:59:45","indexId":"sir20125164","displayToPublicDate":"2012-11-26T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2012-5164","title":"Global exploration and production capacity for platinum-group metals from 1995 through 2015","docAbstract":"Platinum-group metals (PGMs) are required in a variety of commercial, industrial, and military applications for many existing and emerging technologies, yet the United States is highly dependent on foreign sources of PGMs. Information on global exploration for PGMs since 1995 has been used in this study as a basis for identifying locations where the industry has determined that exploration has provided data sufficient to warrant development of a new mine or expansion of an existing operation or where a significant increase in capacity for PGMs is anticipated by 2015. Discussions include an overview of the industry and the selected sites, factors affecting mineral supply, and circumstances leading to the development of mineral properties with the potential to affect mineral supply. Of the 52 sites or regional operations that were considered in this analysis, 16 sites were producing before 1995, 28 sites commenced production from 1995 through 2010, and 8 sites were expected to begin production from 2011 through 2015 if development plans came to fruition. The United States imports PGMs primarily from Canada, Russia, South Africa, and Zimbabwe to meet increasing demand for these materials in a variety of specialized and high-tech applications. Feed sources of PGMs are changing in South Africa and Russia, which together accounted for about 89 percent of platinum production and 82 percent of palladium production in 2009. A greater amount of South African PGM capacity is likely to come from deeper, higher cost Upper Group Reef seam 2 deposits and deposits in the Eastern Bushveld area. Future Russian PGM capacity is likely to come from ore zones with generally lower PGM content and different platinum-to-palladium ratios than the nickel-rich ore that dominated PGM supply in the 1990s. Because PGM supply from Canada and Russia is derived as a byproduct of copper and nickel mining, the PGM supply from these countries is influenced by economic, environmental, political, and technological factors affecting exploration for and development of copper and nickel, as well as factors affecting the PGM industry. The recovery of PGMs from mill tailings since 2004 and the recycling of PGMs from catalytic converters, electrical components, and jewelry has increased since 1995 so that recycled PGMs recovered from these products accounted for about 30 percent of the supply of platinum worldwide and 29 percent of the supply of palladium worldwide in 2010. Economic and geopolitical conditions have influenced PGM supply and demand. The global recession of 2008 and 2009 temporarily decreased demand for PGMs and constrained PGM mine exploration and development, at least through 2010. Legislation regulating the structure of the mining sector has affected mining in Russia, South Africa, and Zimbabwe. Stricter vehicle emissions standards in established markets since the 1980s have led to mandatory use of pollution control devices, such as catalytic converters, that contain PGMs and are required on vehicles in expanding markets, such as China and India. It is expected that South Africa, Russia, Canada, and Zimbabwe will continue to be the principal sources of PGM at least for the next decade. Based on this review of the PGM industry, the world’s platinum capacity, expressed in terms of recoverable platinum metal, increased from 1995 through 2010 by 77,000 kilograms (kg) in South Africa, 9,000 kg in Zimbabwe, 6,000 kg in Russia, 2,000 kg in Botswana, and 2,000 kg in Canada. For the same period, palladium capacity worldwide increased by 44,000 kg in South Africa, 22,000 kg in Russia, 8,000 kg in Canada, 8,000 kg in the United States, 7,000 kg in Zimbabwe, and 3,000 kg in Botswana. Platinum capacity worldwide is expected to further increase by 24,000 kg in South Africa, 9,000 kg in Russia, 3,000 kg in Canada, and 2,000 kg in Zimbabwe from 2011 through 2015. Palladium capacity worldwide is likewise expected to increase an additional 16,000 kg in Russia, 14,000 kg in South Africa, 4,000 kg in Zimbabwe, and 1,000 kg in Canada if new or expanded mine and associated processing capacity comes into production as planned. It is likely that the magnitude of these changes in PGM capacity has been influenced by such factors as the global economy, electrical capacity shortages and mine safety concerns in South Africa, and geopolitical conditions in the major PGM producing countries.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20125164","usgsCitation":"Wilburn, D.R., 2012, Global exploration and production capacity for platinum-group metals from 1995 through 2015 (Originally posted November 26, 2012; Revised December 14, 2012): U.S. Geological Survey Scientific Investigations Report 2012-5164, iv, 26 p., https://doi.org/10.3133/sir20125164.","productDescription":"iv, 26 p.","numberOfPages":"34","onlineOnly":"Y","additionalOnlineFiles":"N","temporalStart":"1995-01-01","temporalEnd":"2015-12-31","costCenters":[{"id":432,"text":"National Minerals Information Center","active":true,"usgs":true}],"links":[{"id":264658,"type":{"id":18,"text":"Project Site"},"url":"https://minerals.usgs.gov/minerals/"},{"id":263371,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2012/5164/"},{"id":263372,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2012/5164/pdf/sir2012-5164.pdf"},{"id":263373,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir_2012_5164.gif"}],"geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -180.0,-90.0 ], [ -180.0,90.0 ], [ 180.0,90.0 ], [ 180.0,-90.0 ], [ -180.0,-90.0 ] ] ] } } ] }","edition":"Originally posted November 26, 2012; Revised December 14, 2012","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"50b48f8ae4b0b3fb1a229140","contributors":{"authors":[{"text":"Wilburn, David R. 0000-0002-5371-7617 wilburn@usgs.gov","orcid":"https://orcid.org/0000-0002-5371-7617","contributorId":1755,"corporation":false,"usgs":true,"family":"Wilburn","given":"David","email":"wilburn@usgs.gov","middleInitial":"R.","affiliations":[{"id":432,"text":"National Minerals Information Center","active":true,"usgs":true}],"preferred":true,"id":469151,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70040865,"text":"sir20125215 - 2012 - Byproduct metals and rare-earth elements used in the production of light-emitting diodes—Overview of principal sources of supply and material requirements for selected markets","interactions":[],"lastModifiedDate":"2012-11-26T14:51:43","indexId":"sir20125215","displayToPublicDate":"2012-11-26T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2012-5215","title":"Byproduct metals and rare-earth elements used in the production of light-emitting diodes—Overview of principal sources of supply and material requirements for selected markets","docAbstract":"The use of light-emitting diodes (LEDs) is expanding because of environmental issues and the efficiency and cost savings achieved compared with use of traditional incandescent lighting. The longer life and reduced power consumption of some LEDs have led to annual energy savings, reduced maintenance costs, and lower emissions of carbon dioxide, sulfur dioxide, and nitrogen oxides from powerplants because of the resulting decrease in energy consumption required for lighting applications when LEDs are used to replace less-energy-efficient sources. Metals such as arsenic, gallium, indium, and the rare-earth elements (REEs) cerium, europium, gadolinium, lanthanum, terbium, and yttrium are important mineral materials used in LED semiconductor technology. Most of the world's supply of these materials is produced as byproducts from the production of aluminum, copper, lead, and zinc. Most of the rare earths required for LED production in 2011 came from China, and most LED production facilities were located in Asia. The LED manufacturing process is complex and is undergoing much change with the growth of the industry and the changes in demand patterns of associated commodities. In many respects, the continued growth of the LED industry, particularly in the general lighting sector, is tied to its ability to increase LED efficiency and color uniformity while decreasing the costs of producing, purchasing, and operating LEDs. Research is supported by governments of China, the European Union, Japan, the Republic of Korea, and the United States. Because of the volume of ongoing research in this sector, it is likely that the material requirements of future LEDs may be quite different than LEDs currently (2011) in use as industry attempts to cut costs by reducing material requirements of expensive heavy rare-earth phosphors and increasing the sizes of wafers for economies of scale. Improved LED performance will allow customers to reduce the number of LEDs in automotive, electronic, and lighting applications, which could reduce the overall demand for material components. Non-Chinese sources for rare earths are being developed, and some of these new sources are likely to be operational in time to meet increasing demand for rare earths from the LED sector. Because most LED component production and manufacturing occurs in Asia and many LED producers have established supply contracts with Chinese producers of rare earths, a significant amount of the metallic gallium, indium, and the rare earths used for LED production will likely continue to come from Chinese sources at least for the next 5 years; however, a greater amount of these materials are now being processed in Japan, the Republic of Korea, and Taiwan. As non-Chinese sources of rare earths come into production, these new mines are likely to be sources of light REEs, but China will likely remain the leading source of supply for the heavy REEs suitable for use as LED dopants and phosphors at least for the next few years. Increased research in the development of phosphors that use smaller amounts of or different REEs is intended to reduce dependence on rare earths from China. Supply disruption of rare earths and other specialty metals could take place if China's specialty metal exports are redirected to domestic markets. The cost of recovery is high and the lifespan for LEDs is comparatively long; thus, the LED waste volume was low in 2010, and few LEDs were recycled. The minute metal content of LEDs leads to a high cost for recovery, so recycling of LEDs outside of electronic waste is unlikely in the near term, although some LED producers are evaluating recycling options. Recycling of metals from LEDs in electronic waste is possible if the costs of recovering metals are justified by demand and metal prices.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20125215","usgsCitation":"Wilburn, D.R., 2012, Byproduct metals and rare-earth elements used in the production of light-emitting diodes—Overview of principal sources of supply and material requirements for selected markets: U.S. Geological Survey Scientific Investigations Report 2012-5215, iv, 15 p., https://doi.org/10.3133/sir20125215.","productDescription":"iv, 15 p.","numberOfPages":"24","onlineOnly":"Y","additionalOnlineFiles":"N","costCenters":[{"id":432,"text":"National Minerals Information Center","active":true,"usgs":true}],"links":[{"id":263378,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2012/5215/pdf/sir2012-5215.pdf"},{"id":263379,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir_2012_5215.gif"},{"id":263377,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2012/5215/"}],"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"50b48f86e4b0b3fb1a22913c","contributors":{"authors":[{"text":"Wilburn, David R. 0000-0002-5371-7617 wilburn@usgs.gov","orcid":"https://orcid.org/0000-0002-5371-7617","contributorId":1755,"corporation":false,"usgs":true,"family":"Wilburn","given":"David","email":"wilburn@usgs.gov","middleInitial":"R.","affiliations":[{"id":432,"text":"National Minerals Information Center","active":true,"usgs":true}],"preferred":true,"id":469159,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70041250,"text":"ds709E - 2012 - Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Aynak mineral district in Afghanistan: Chapter E in Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan","interactions":[],"lastModifiedDate":"2013-02-01T11:14:45","indexId":"ds709E","displayToPublicDate":"2012-11-21T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":310,"text":"Data Series","code":"DS","onlineIssn":"2327-638X","printIssn":"2327-0271","active":false,"publicationSubtype":{"id":5}},"seriesNumber":"709","chapter":"E","title":"Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Aynak mineral district in Afghanistan: Chapter E in Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan","docAbstract":"The U.S. Geological Survey (USGS), in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations, prepared databases for mineral-resource target areas in Afghanistan. The purpose of the databases is to (1) provide useful data to ground-survey crews for use in performing detailed assessments of the areas and (2) provide useful information to private investors who are considering investment in a particular area for development of its natural resources. The set of satellite-image mosaics provided in this Data Series (DS) is one such database. Although airborne digital color-infrared imagery was acquired for parts of Afghanistan in 2006, the image data have radiometric variations that preclude their use in creating a consistent image mosaic for geologic analysis. Consequently, image mosaics were created using ALOS (Advanced Land Observation Satellite; renamed Daichi) satellite images, whose radiometry has been well determined (Saunier, 2007a,b). This part of the DS consists of the locally enhanced ALOS image mosaics for the Aynak mineral district, which has copper deposits. ALOS was launched on January 24, 2006, and provides multispectral images from the AVNIR (Advanced Visible and Near-Infrared Radiometer) sensor in blue (420–500 nanometer, nm), green (520–600 nm), red (610–690 nm), and near-infrared (760–890 nm) wavelength bands with an 8-bit dynamic range and a 10-meter (m) ground resolution. The satellite also provides a panchromatic band image from the PRISM (Panchromatic Remote-sensing Instrument for Stereo Mapping) sensor (520–770 nm) with the same dynamic range but a 2.5-m ground resolution. The image products in this DS incorporate copyrighted data provided by the Japan Aerospace Exploration Agency ((c)JAXA,2008,2010), but the image processing has altered the original pixel structure and all image values of the JAXA ALOS data, such that original image values cannot be recreated from this DS. As such, the DS products match JAXA criteria for value added products, which are not copyrighted, according to the ALOS end-user license agreement. The selection criteria for the satellite imagery used in our mosaics were images having (1) the highest solar-elevation angles (near summer solstice) and (2) the least cloud, cloud-shadow, and snow cover. The multispectral and panchromatic data were orthorectified with ALOS satellite ephemeris data, a process which is not as accurate as orthorectification using digital elevation models (DEMs); however, the ALOS processing center did not have a precise DEM. As a result, the multispectral and panchromatic image pairs were generally not well registered to the surface and not coregistered well enough to perform resolution enhancement on the multispectral data. For this particular area, PRISM image orthorectification was performed by the Alaska Satellite Facility, applying its photogrammetric software to PRISM stereo images with vertical control points obtained from the digital elevation database produced by the Shuttle Radar Topography Mission (Farr and others, 2007) and horizontal adjustments based on a controlled Landsat image base (Davis, 2006). The 10-m AVNIR multispectral imagery was then coregistered to the orthorectified PRISM images and individual multispectral and panchromatic images were mosaicked into single images of the entire area of interest. The image coregistration was facilitated using an automated control-point algorithm developed by the USGS that allows image coregistration to within one picture element. Before rectification, the multispectral and panchromatic images were converted to radiance values and then to relative-reflectance values using the methods described in Davis (2006). Mosaicking the multispectral or panchromatic images started with the image with the highest sun-elevation angle and the least atmospheric scattering, which was treated as the standard image. The band-reflectance values of all other multispectral or panchromatic images within the area were sequentially adjusted to that of the standard image by determining band-reflectance correspondence between overlapping images using linear least-squares analysis. The resolution of the multispectral image mosaic was then increased to that of the panchromatic image mosaic using the SPARKLE logic, which is described in Davis (2006). Each of the four-band images within the resolution-enhanced image mosaic was individually subjected to a local-area histogram stretch algorithm (described in Davis, 2007), which stretches each band’s picture element based on the digital values of all picture elements within a 315-m radius. The final databases, which are provided in this DS, are three-band, color-composite images of the local-area-enhanced, natural-color data (the blue, green, and red wavelength bands) and color-infrared data (the green, red, and near-infrared wavelength bands). All image data were initially projected and maintained in Universal Transverse Mercator (UTM) map projection using the target area’s local zone (42 for Aynak) and the WGS84 datum. The final image mosaics were subdivided into four overlapping tiles or quadrants because of the large size of the target area. The four image tiles (or quadrants) for the Aynak area are provided as embedded geotiff images, which can be read and used by most geographic information system (GIS) and image-processing software. The tiff world files (tfw) are provided, even though they are generally not needed for most software to read an embedded geotiff image. Within the Aynak study area, five subareas were designated for detailed field investigations (that is, the Bakhel-Charwaz, Kelaghey-Kakhay, Kharuti-Dawrankhel, Logar Valley, and Yagh-Darra/Gul-Darra subareas); these subareas were extracted from the area’s image mosaic and are provided as separate embedded geotiff images.","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan (DS 709)","largerWorkSubtype":{"id":5,"text":"USGS Numbered Series"},"language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds709E","collaboration":"Prepared in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations and the Afghanistan Geological Survey. This report is Chapter E in Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan. For more information, see: Data Series 709.","usgsCitation":"Davis, P.A., Cagney, L.E., Arko, S.A., and Harbin, M., 2012, Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Aynak mineral district in Afghanistan: Chapter E in Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan: U.S. Geological Survey Data Series 709, Readme; 3 Maps: 11 x 8.5 inches and 42.79 x 29.78 inches; 18 Image Files; 18 Metadata Files; Shapefiles; DS 709, https://doi.org/10.3133/ds709E.","productDescription":"Readme; 3 Maps: 11 x 8.5 inches and 42.79 x 29.78 inches; 18 Image Files; 18 Metadata Files; Shapefiles; DS 709","onlineOnly":"Y","additionalOnlineFiles":"Y","costCenters":[{"id":387,"text":"Mineral Resources Program","active":true,"usgs":true}],"links":[{"id":263605,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ds_709_E.jpg"},{"id":263595,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/ds/709/e/"},{"id":263600,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/ds/709/e/index_maps/Aynak_Subarea_Image_Index_Map.pdf"},{"id":263601,"type":{"id":14,"text":"Image"},"url":"https://pubs.usgs.gov/ds/709/e/image_files/image_files.html"},{"id":263597,"type":{"id":20,"text":"Read Me"},"url":"https://pubs.usgs.gov/ds/709/e/1_readme.txt"},{"id":263598,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/ds/709/e/index_maps/Aynak_Area-of-Interest_Index_Map.pdf"},{"id":263599,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/ds/709/e/index_maps/Aynak_Image_Index_Map.pdf"},{"id":263602,"type":{"id":16,"text":"Metadata"},"url":"https://pubs.usgs.gov/ds/709/e/metadata/metadata.html"},{"id":263603,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/ds/709/e/shapefiles/shapefiles.html"},{"id":263604,"type":{"id":22,"text":"Related Work"},"url":"https://pubs.usgs.gov/ds/709/"}],"country":"Afghanistan","state":"Kabul;Logar;Paktya;Wardak","otherGeospatial":"Aynak Mineral District","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ 68.633333,34.083333 ], [ 68.633333,34.533333 ], [ 69.5,34.533333 ], [ 69.5,34.083333 ], [ 68.633333,34.083333 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"50bd1396e4b069d93eefc4ec","contributors":{"authors":[{"text":"Davis, Philip A. pdavis@usgs.gov","contributorId":692,"corporation":false,"usgs":true,"family":"Davis","given":"Philip","email":"pdavis@usgs.gov","middleInitial":"A.","affiliations":[],"preferred":true,"id":469455,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Cagney, Laura E. 0000-0003-3282-2458 lcagney@usgs.gov","orcid":"https://orcid.org/0000-0003-3282-2458","contributorId":4744,"corporation":false,"usgs":true,"family":"Cagney","given":"Laura","email":"lcagney@usgs.gov","middleInitial":"E.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":469456,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Arko, Scott A.","contributorId":101929,"corporation":false,"usgs":true,"family":"Arko","given":"Scott","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":469458,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Harbin, Michelle L.","contributorId":20590,"corporation":false,"usgs":true,"family":"Harbin","given":"Michelle L.","affiliations":[],"preferred":false,"id":469457,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70040593,"text":"sir20105090H - 2012 - Economic filters for evaluating porphyry copper deposit resource assessments using grade-tonnage deposit models, with examples from the U.S. Geological Survey global mineral resource assessment: Chapter H in Global mineral resource assessment","interactions":[{"subject":{"id":70040593,"text":"sir20105090H - 2012 - Economic filters for evaluating porphyry copper deposit resource assessments using grade-tonnage deposit models, with examples from the U.S. Geological Survey global mineral resource assessment: Chapter H in Global mineral resource assessment","indexId":"sir20105090H","publicationYear":"2012","noYear":false,"chapter":"H","title":"Economic filters for evaluating porphyry copper deposit resource assessments using grade-tonnage deposit models, with examples from the U.S. Geological Survey global mineral resource assessment: Chapter H in Global mineral resource assessment"},"predicate":"IS_PART_OF","object":{"id":70040436,"text":"sir20105090 - 2010 - Global mineral resource assessment","indexId":"sir20105090","publicationYear":"2010","noYear":false,"title":"Global mineral resource assessment"},"id":1}],"isPartOf":{"id":70040436,"text":"sir20105090 - 2010 - Global mineral resource assessment","indexId":"sir20105090","publicationYear":"2010","noYear":false,"title":"Global mineral resource assessment"},"lastModifiedDate":"2018-11-19T10:28:53","indexId":"sir20105090H","displayToPublicDate":"2012-11-02T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2010-5090","chapter":"H","title":"Economic filters for evaluating porphyry copper deposit resource assessments using grade-tonnage deposit models, with examples from the U.S. Geological Survey global mineral resource assessment: Chapter H in Global mineral resource assessment","docAbstract":"

An analysis of the amount and location of undiscovered mineral resources that are likely to be economically recoverable is important for assessing the long-term adequacy and availability of mineral supplies. This requires an economic evaluation of estimates of undiscovered resources generated by traditional resource assessments (Singer and Menzie, 2010). In this study, simplified engineering cost models were used to estimate the economic fraction of resources contained in undiscovered porphyry copper deposits, predicted in a global assessment of copper resources. The cost models of Camm (1991) were updated with a cost index to reflect increases in mining and milling costs since 1989. The updated cost models were used to perform an economic analysis of undiscovered resources estimated in porphyry copper deposits in six tracts located in North America. The assessment estimated undiscovered porphyry copper deposits within 1 kilometer of the land surface in three depth intervals.

\n

The results of the updated engineering cost model analysis for open-pit porphyry copper deposits are in agreement with the grade-tonnage boundary defining positive economic returns for copper deposits developed between 1989 and 2008. This correspondence demonstrates that the updated engineering cost equations are performing well and appear to be appropriate to evaluate the economic status of open-pit porphyry copper mines under current, and potentially future, economic conditions. Economic filters based on these simplified engineering cost models provide a method for estimating potential tonnages of undiscovered metals that may be economic in individual assessment areas.

\n

One implication of the economic filter results for undiscovered copper resources is that global copper supply will continue to be dominated by production from a small number of giant deposits. This domination of resource supply by a small number of producers may increase in the future, because an increasing proportion of new deposit discoveries are likely to occur in remote areas and be concealed deep beneath covering rock and sediments. Extensive mineral exploration activity will be required to meet future resource demand, because these deposits will be harder to find and more costly to mine than near-surface deposits located in more accessible areas. Relatively few of the new deposit discoveries in these high-cost settings will have sufficient tonnage and grade characteristics to assure positive economic returns on development and exploration costs.

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Jr. grobinso@usgs.gov","contributorId":3083,"corporation":false,"usgs":true,"family":"Robinson","given":"Gilpin","suffix":"Jr.","email":"grobinso@usgs.gov","middleInitial":"R.","affiliations":[{"id":245,"text":"Eastern Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":false,"id":468634,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Menzie, W. David","contributorId":15645,"corporation":false,"usgs":true,"family":"Menzie","given":"W.","email":"","middleInitial":"David","affiliations":[{"id":432,"text":"National Minerals Information Center","active":true,"usgs":true}],"preferred":false,"id":468635,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70040432,"text":"sir20105090E - 2012 - Sandstone copper assessment of the Chu-Sarysu Basin, Central Kazakhstan: Chapter E in Global mineral resource assessment","interactions":[{"subject":{"id":70040432,"text":"sir20105090E - 2012 - Sandstone copper assessment of the Chu-Sarysu Basin, Central Kazakhstan: Chapter E in Global mineral resource assessment","indexId":"sir20105090E","publicationYear":"2012","noYear":false,"chapter":"E","title":"Sandstone copper assessment of the Chu-Sarysu Basin, Central Kazakhstan: Chapter E in Global mineral resource assessment"},"predicate":"IS_PART_OF","object":{"id":70040436,"text":"sir20105090 - 2010 - Global mineral resource assessment","indexId":"sir20105090","publicationYear":"2010","noYear":false,"title":"Global mineral resource assessment"},"id":1}],"isPartOf":{"id":70040436,"text":"sir20105090 - 2010 - Global mineral resource assessment","indexId":"sir20105090","publicationYear":"2010","noYear":false,"title":"Global mineral resource assessment"},"lastModifiedDate":"2015-06-19T11:13:59","indexId":"sir20105090E","displayToPublicDate":"2012-10-19T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2010-5090","chapter":"E","title":"Sandstone copper assessment of the Chu-Sarysu Basin, Central Kazakhstan: Chapter E in Global mineral resource assessment","docAbstract":"

Mineral resource assessments represent a synthesis of available information to estimate the location, quality, and quantity of undiscovered mineral resources in the upper part of the Earth’s crust. This report presents a probabilistic mineral resource assessment of undiscovered sandstone copper deposits within the late Paleozoic Chu-Sarysu Basin in central Kazakhstan by the U.S. Geological Survey as a contribution to a global assessment of mineral resources. The purposes of this study are to: (1) provide a database of known sandstone copper deposits and significant prospects in this area, (2) delineate permissive areas (tracts) for undiscovered sandstone copper deposits within 2 km of the surface at a scale of 1:1,000,000, (3) estimate numbers of undiscovered deposits within these permissive tracts at several levels of confidence, and (4) provide probabilistic estimates of amounts of copper (Cu), silver (Ag), and mineralized rock that could be contained in undiscovered deposits within each tract. The assessment uses the three-part form of mineral resource assessment based on mineral deposit models (Singer, 1993; Singer and Menzie, 2010).

\n

Delineation of permissive tracts for resources is based on the distribution of a Carboniferous oxidized nonmarine clastic (red bed) stratigraphic sequence that lies between overlying Permian and underlying Devonian evaporite-bearing sequences. Subsurface information on the extent and depth of this red bed sequence and structural features that divide the basin into sub-basins was used to define four permissive tracts. Structure contour maps, mineral occurrence databases, drill hole lithologic logs, geophysical maps, soil geochemical maps, locations of producing gas fields, and evidence for former gas accumulations were considered in conjunction with descriptive deposit models and grade and tonnage models to guide the assessment team’s estimates of undiscovered deposits in each tract.

\n

The four permissive tracts are structural sub-basins of the Chu-Sarysu Basin and range in size from 750 to 65,000 km². Probabilistic estimates of numbers of undiscovered sandstone copper deposits were made for the four tracts by a group of experts. Using these probabilistic estimates, Monte Carlo simulation was used to estimate the amount of metal contained within each tract. The results of the simulation serve as the basis for estimates of the metal endowment.

\n

The team estimates that 26 undiscovered deposits occur within the Chu-Sarysu Basin, and that these deposits contain an arithmetic mean of at least 21.5 million metric tons (Mt) of copper and 21,900 metric tons (t) of silver. The undiscovered deposits are in addition to the 7 known deposits that contain identified resources of 27.6 Mt of copper. Sixty percent of the estimated mean undiscovered copper resources are associated with the two permissive tracts that contain the identified resources; the remaining estimated resources are associated with the two tracts that have no known deposits. For the three tracts that contain 95 percent of the estimated undiscovered copper resources, the probability that each tract contains its estimated mean or more is about 40 percent. For the tract with 5 percent of the estimated undiscovered cop-per resources, the probability that it contains that amount or more is 25 percent.

","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"Global mineral resource assessment (Scientific Investigations Report 2010-5090)","largerWorkSubtype":{"id":5,"text":"USGS Numbered Series"},"language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20105090E","collaboration":"Prepared in cooperation with the Centre for Russian and Central EurAsian Mineral Studies—Natural History Museum, London, United Kingdom, and Mining and Economic Consulting, Ltd., Almaty, Kazakhstan","usgsCitation":"Box, S.E., Syusyura, B., Hayes, T.S., Taylor, C.D., Zientek, M.L., Hitzman, M., Seltmann, R., Chechetkin, V., Dolgopolova, A., Cossette, P.M., and Wallis, J., 2012, Sandstone copper assessment of the Chu-Sarysu Basin, Central Kazakhstan: Chapter E in Global mineral resource assessment: U.S. Geological Survey Scientific Investigations Report 2010-5090, Report: vi, 63 p.; Metadata Folder; GIS Data, https://doi.org/10.3133/sir20105090E.","productDescription":"Report: vi, 63 p.; Metadata Folder; GIS Data","numberOfPages":"74","onlineOnly":"Y","additionalOnlineFiles":"Y","costCenters":[{"id":387,"text":"Mineral Resources Program","active":true,"usgs":true}],"links":[{"id":262731,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir_2010_5090_e.gif"},{"id":301359,"type":{"id":16,"text":"Metadata"},"url":"https://pubs.usgs.gov/sir/2010/5090/e/sir2010-5090e_metadata","size":"193 kB"},{"id":262724,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2010/5090/e/"},{"id":262725,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2010/5090/e/sir2010-5090e_text.pdf","text":"Report","size":"3.3 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Report"},{"id":301360,"type":{"id":23,"text":"Spatial Data"},"url":"https://pubs.usgs.gov/sir/2010/5090/e/sir2010-5090e_gis.zip","text":"GIS data zip package","size":"1.7 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Timothy S. thayes@usgs.gov","contributorId":1547,"corporation":false,"usgs":true,"family":"Hayes","given":"Timothy","email":"thayes@usgs.gov","middleInitial":"S.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true},{"id":662,"text":"Western Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":514668,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Taylor, Cliff D. 0000-0001-6376-6298 ctaylor@usgs.gov","orcid":"https://orcid.org/0000-0001-6376-6298","contributorId":1283,"corporation":false,"usgs":true,"family":"Taylor","given":"Cliff","email":"ctaylor@usgs.gov","middleInitial":"D.","affiliations":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":514666,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Zientek, Michael L. 0000-0002-8522-9626 mzientek@usgs.gov","orcid":"https://orcid.org/0000-0002-8522-9626","contributorId":2420,"corporation":false,"usgs":true,"family":"Zientek","given":"Michael","email":"mzientek@usgs.gov","middleInitial":"L.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":514670,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Hitzman, Murray W.","contributorId":14682,"corporation":false,"usgs":true,"family":"Hitzman","given":"Murray W.","affiliations":[],"preferred":false,"id":514671,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Seltmann, Reimar","contributorId":73450,"corporation":false,"usgs":true,"family":"Seltmann","given":"Reimar","email":"","affiliations":[],"preferred":false,"id":514675,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Chechetkin, Vladimir","contributorId":71821,"corporation":false,"usgs":true,"family":"Chechetkin","given":"Vladimir","affiliations":[],"preferred":false,"id":514673,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Dolgopolova, Alla","contributorId":96943,"corporation":false,"usgs":true,"family":"Dolgopolova","given":"Alla","email":"","affiliations":[],"preferred":false,"id":514676,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Cossette, Pamela M. 0000-0002-9608-6595 pcossette@usgs.gov","orcid":"https://orcid.org/0000-0002-9608-6595","contributorId":1458,"corporation":false,"usgs":true,"family":"Cossette","given":"Pamela","email":"pcossette@usgs.gov","middleInitial":"M.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":514667,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Wallis, John C.","contributorId":45755,"corporation":false,"usgs":true,"family":"Wallis","given":"John C.","affiliations":[],"preferred":false,"id":514672,"contributorType":{"id":1,"text":"Authors"},"rank":11}]}} ,{"id":70040204,"text":"sir20115145 - 2012 - Parking lot runoff quality and treatment efficiencies of a hydrodynamic-settling device in Madison, Wisconsin, 2005-6","interactions":[],"lastModifiedDate":"2012-10-05T17:16:22","indexId":"sir20115145","displayToPublicDate":"2012-10-05T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2011-5145","title":"Parking lot runoff quality and treatment efficiencies of a hydrodynamic-settling device in Madison, Wisconsin, 2005-6","docAbstract":"A hydrodynamic-settling device was installed in 2004 to treat stormwater runoff from a roof and parking lot located at the Water Utility Administration Building in Madison, Wis. The U.S. Geological Survey, in cooperation with the Wisconsin Department of Natural Resources, the City of Madison, cities in the Waukesha Permit Group, Hydro International, Earth Tech, Inc., National Sanitation Foundation International, and the U.S. Environmental Protection Agency, monitored the device from November 2005 through September 2006 to evaluate it as part of the U.S. Environmental Protection Agency's Environmental Technology Verification Program. Twenty-three runoff events monitored for flow volume and water quality at the device's inlet and outlet were used to calculate the percentage of pollutant reduction for the device. The geometric mean concentrations of suspended sediment (SS), \"adjusted\" total suspended solids (TSS), total phosphorus (TP), dissolved phosphorus (DP), total recoverable zinc (TZn), and total recoverable copper (TCu) measured at the inlet were 107 mg/L (milligrams per liter), 92 mg/L, 0.17 mg/L, 0.05 mg/L, 38 μg/L (micrograms per liter), and 12 μg/L, respectively, and these concentrations are in the range of values observed in stormwater runoff from other parking lots in Wisconsin and Michigan. Efficiency of the settling device was calculated using the efficiency ratio and summation of loads (SOL) methods. Using the efficiency ratio method, the device reduced concentrations of SS, and DP, by 19, and 15, percent, respectively. Using the efficiency ratio method, the device increased \"adjusted\" TSS and TZn concentrations by 5 and 19, respectively. Bypass occurred for 3 of the 23 runoff events used in this assessment, and the bypass flow and water-quality concentrations were used to determine the efficiency of the bypass system. Concentrations of SS, \"adjusted\" TSS, and DP were reduced for the system by 18, 5, and 18, respectively; however, TZn increased by 5 percent. Some of the TSS concentrations were \"adjusted\" to add the particles that remained on the sieves during sample processing. The loads of SS, \"adjusted\" TSS, and DP were reduced using the SOL method for the settling device by 38, 9, and 19 percent, respectively, and TZn increased by 13 percent. For the bypass system, the loads of SS, \"adjusted\" TSS, and DP had percentage reductions of 39, 12, 22, respectively, however TZn increased by 4 percent. The SOL method produced percentage reductions for SS and 'adjusted\" TSS that were twice those for the efficiency ratio method. Removing the two large runoff events on August 23 and 24, 2006, from the SOL calculation brought the reduction for SS down to 16 and increased \"adjusted\" TSS by 4 percent. The two large runoff events were anomalies in that the runoff volumes and dissolved solids concentrations were greatly increased by overflow from an adjacent recycling facility. The SOL method was used to determine the percentage of SS load reduction for six different particle sizes for both the settling device and bypass system. Essentially no load reduction was observed for particles less than 125 micrometers (μm) in diameter, and about a 90-percent reduction occurred for particle sizes greater than 250 μm in diameter. The large removal efficiencies for particle sizes greater than 250 μm in diameter were further supported by the fact that more than 80 percent of the particle sizes trapped in the sump were greater than 250 μm in diameter. These results support the claim by the manufacturer of achieving a large percentage load reduction for particle sizes greater than 250 μm in diameter.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20115145","collaboration":"Prepared in cooperation with the Wisconsin Department of Natural Resources, the City of Madison, Cities in the Waukesha Permit Group, Hydro International, Earth Tech Incorporated, National Sanitation Foundation International, and the U.S. Environmental Protection Agency","usgsCitation":"Horwatich, J.A., and Bannerman, R.T., 2012, Parking lot runoff quality and treatment efficiencies of a hydrodynamic-settling device in Madison, Wisconsin, 2005-6: U.S. Geological Survey Scientific Investigations Report 2011-5145, viii, 60 p.; col. ill., https://doi.org/10.3133/sir20115145.","productDescription":"viii, 60 p.; col. ill.","startPage":"i","endPage":"60","numberOfPages":"72","onlineOnly":"Y","additionalOnlineFiles":"N","temporalStart":"2005-01-01","temporalEnd":"2006-12-31","costCenters":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"links":[{"id":262308,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir_2011_5145.jpg"},{"id":262298,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2011/5145/","linkFileType":{"id":5,"text":"html"}},{"id":262297,"rank":300,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2011/5145/pdf/sir2011_5145.pdf","linkFileType":{"id":1,"text":"pdf"}}],"country":"United States","state":"Wisconsin","city":"Madison","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -89.55,42.983333333333334 ], [ -89.55,43.166666666666664 ], [ -89.23333333333333,43.166666666666664 ], [ -89.23333333333333,42.983333333333334 ], [ -89.55,42.983333333333334 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"50e0ec21e4b0fec3206f1904","contributors":{"authors":[{"text":"Horwatich, Judy A. 0000-0003-0582-0836 jahorwat@usgs.gov","orcid":"https://orcid.org/0000-0003-0582-0836","contributorId":1388,"corporation":false,"usgs":true,"family":"Horwatich","given":"Judy","email":"jahorwat@usgs.gov","middleInitial":"A.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":467891,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bannerman, Roger T. 0000-0001-9221-2905 rbannerman@usgs.gov","orcid":"https://orcid.org/0000-0001-9221-2905","contributorId":5560,"corporation":false,"usgs":true,"family":"Bannerman","given":"Roger","email":"rbannerman@usgs.gov","middleInitial":"T.","affiliations":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"preferred":true,"id":467892,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70040058,"text":"70040058 - 2012 - Toxicity of copper to early-life stage Kootenai River white sturgeon, Columbia River white sturgeon, and rainbow trout","interactions":[],"lastModifiedDate":"2016-12-31T12:24:42","indexId":"70040058","displayToPublicDate":"2012-09-28T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":887,"text":"Archives of Environmental Contamination and Toxicology","active":true,"publicationSubtype":{"id":10}},"title":"Toxicity of copper to early-life stage Kootenai River white sturgeon, Columbia River white sturgeon, and rainbow trout","docAbstract":"White sturgeon (Acipenser transmontanus) populations throughout western North America are in decline, likely as a result of overharvest, operation of dams, and agricultural and mineral extraction activities in their watersheds. Recruitment failure may reflect the loss of early-life stage fish in spawning areas of the upper Columbia River, which are contaminated with metals from effluents associated with mineral-extraction activities. Early-life stage white sturgeon (A. transmontanus) from the Columbia River and Kootenai River populations were exposed to copper during 96-h flow-through toxicity tests to determine their sensitivity to the metal. Similar tests were conducted with rainbow trout (RBT [Oncorhynchus mykiss]) to assess the comparative sensitivity of this species as a surrogate for white sturgeon. Exposures were conducted with a water quality pH 8.1-8.3, hardness 81-119 mg/L as CaCO2, and dissolved organic carbon 0.2-0.4 mg/L. At approximately 30 days posthatch (dph), sturgeon were highly sensitive to copper with median lethal concentration (LC50) values ranging from 4.1 to 6.8 μg/L compared with 36.5 μg/L for 30 dph RBT. White sturgeon at 123-167 dph were less sensitive to copper with LC50 values ranging from 103.7 to 268.9 μg/L. RBT trout, however, remained more sensitive to copper at 160 dph with an LC50 value of 30.9 μg/L. The results indicate that high sensitivity to copper in early-life stage white sturgeon may be a factor in recruitment failure occurring in the upper Columbia and Kootenai rivers. When site-specific water-quality criteria were estimated using the biotic ligand model (BLM), derived values were not protective of early-life stage fish, nor were estimates derived by water-hardness adjustment.","language":"English","publisher":"Springer","publisherLocation":"Amsterdam, Netherlands","doi":"10.1007/s00244-012-9782-3","usgsCitation":"Little, E.E., Calfee, R., and Linder, G., 2012, Toxicity of copper to early-life stage Kootenai River white sturgeon, Columbia River white sturgeon, and rainbow trout: Archives of Environmental Contamination and Toxicology, v. 63, no. 3, p. 400-408, https://doi.org/10.1007/s00244-012-9782-3.","productDescription":"9 p.","startPage":"400","endPage":"408","costCenters":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"links":[{"id":262156,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"63","issue":"3","noUsgsAuthors":false,"publicationDate":"2012-08-14","publicationStatus":"PW","scienceBaseUri":"50662515e4b053bff18e1c13","contributors":{"authors":[{"text":"Little, E. E.","contributorId":13187,"corporation":false,"usgs":true,"family":"Little","given":"E.","email":"","middleInitial":"E.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":false,"id":467582,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Calfee, R.D.","contributorId":85130,"corporation":false,"usgs":true,"family":"Calfee","given":"R.D.","affiliations":[],"preferred":false,"id":467584,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Linder, G.","contributorId":43070,"corporation":false,"usgs":true,"family":"Linder","given":"G.","email":"","affiliations":[],"preferred":false,"id":467583,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70039893,"text":"ofr20121160 - 2012 - Assessment of groundwater, soil-gas, and soil contamination at the Vietnam Armor Training Facility, Fort Gordon, Georgia, 2009-2011","interactions":[],"lastModifiedDate":"2018-08-15T14:58:11","indexId":"ofr20121160","displayToPublicDate":"2012-09-13T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2012-1160","title":"Assessment of groundwater, soil-gas, and soil contamination at the Vietnam Armor Training Facility, Fort Gordon, Georgia, 2009-2011","docAbstract":"The U.S. Geological Survey, in cooperation with the U.S. Department of the Army Environmental and Natural Resources Management Office of the U.S. Army Signal Center and Fort Gordon, Georgia, assessed the groundwater, soil gas, and soil for contaminants at the Vietnam Armor Training Facility (VATF) at Fort Gordon, from October 2009 to September 2011. The assessment included the detection of organic compounds in the groundwater and soil gas, and inorganic compounds in the soil. In addition, organic contaminant assessment included organic compounds classified as explosives and chemical agents in selected areas. The assessment was conducted to provide environmental contamination data to the U.S. Army at Fort Gordon pursuant to requirements of the Resource Conservation and Recovery Act Part B Hazardous Waste Permit process. This report is a revision of \"Assessment of soil-gas, surface-water, and soil contamination at the Vietnam Armor Training Facility, Fort Gordon, Georgia, 2009-2010,\" Open-File Report 2011-1200, and supersedes that report to include results of additional samples collected in July 2011. Four passive samplers were deployed in groundwater wells at the VATF in Fort Gordon. Total petroleum hydrocarbons and benzene and octane were detected above the method detection level at all four wells. The only other volatile organic compounds detected above their method detection level were undecane and pentadecane, which were detected in two of the four wells. Soil-gas samplers were deployed at 72 locations in a grid pattern across the VATF on June 3, 2010, and then later retrieved on June 9, 2010. Total petroleum hydrocarbons were detected in 71 of the 72 samplers (one sampler was destroyed in the field and not analyzed) at levels above the method detection level, and the combined mass of benzene, toluene, ethylbenzene, and total xylene (BTEX) was detected above the detection level in 31 of the 71 samplers that were analyzed. Other volatile organic compounds detected above their respective method detection levels were naphthalene, 2-methyl-naphthalene, tridecane, 1,2,4-trimethylbenzene, and perchloroethylene. After the results of the 71 soil-gas samplers were received, 31 additional passive soil-gas samplers were deployed on July 14, 2011, and retrieved on July 18, 2011. These 31 samplers were deployed on a larger areal scale to better define the extent of the contamination. Total petroleum hydrocarbons were detected above their method detection level at all 31 samplers, whereas BTEX was detected above its method detection level at 17 of the 31 samplers. Other organic compounds detected above their method detection levels were naphthalene, 2-methyl-naphthalene, octane, undecane, tridecane, pentadecane, 1,2,4-trimethylbenzene, 1,3,5-trimethylbenzene, chloroform, and perchloroethylene. Subsequent to the 2010 soil-gas survey, four areas determined to have elevated contaminant mass were selected and sampled for explosives and chemical agents. No detections of explosives or chemical agents above their respective method detection levels were found at any of the sampling locations. The same four locations that were sampled for explosives and chemical agents were selected for the collection of soil samples. A fifth location also was selected on the basis of the elevated contaminant mass of the soil-gas survey. No metals that exceeded the Regional Screening Levels for Industrial Soils, as classified by the U.S. Environmental Protection Agency, were detected at any of the five VATF locations. The soil samples also were compared to values from the ambient, uncontaminated (background) levels for soils in South Carolina, as classified by the South Carolina Department of Health and Environmental Control. Because South Carolina is adjacent to Georgia and the soils in the Coastal Plain are similar, these comparisons are valid. No similar values are available for Georgia to use for comparison purposes. The metals that were detected above the ambient background levels for South Carolina, as classified by the South Carolina Department of Health and Environmental Control, include aluminum, arsenic, barium, beryllium, calcium, chromium, copper, iron, lead, magnesium, manganese, nickel, potassium, sodium, and zinc.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20121160","collaboration":"Prepared in cooperation with the U.S. Department of the Army Environmental and Natural Resources Management Office of the U.S. Army Signal Center and Fort Gordon","usgsCitation":"Guimaraes, W.B., Falls, W.F., Caldwell, A.W., Ratliff, W.H., Wellborn, J.B., and Landmeyer, J., 2012, Assessment of groundwater, soil-gas, and soil contamination at the Vietnam Armor Training Facility, Fort Gordon, Georgia, 2009-2011: U.S. Geological Survey Open-File Report 2012-1160, vi, 56 p., https://doi.org/10.3133/ofr20121160.","productDescription":"vi, 56 p.","numberOfPages":"66","onlineOnly":"Y","costCenters":[{"id":589,"text":"Toxic Substances Hydrology Program","active":true,"usgs":true},{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"links":[{"id":261872,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr_2012_1160.gif"},{"id":261863,"rank":300,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2012/1160/pdf/ofr2012-1160.pdf","linkFileType":{"id":1,"text":"pdf"}},{"id":261862,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2012/1160/","linkFileType":{"id":5,"text":"html"}}],"scale":"100000","country":"United States","state":"Georgia","city":"Fort Gordon","otherGeospatial":"Vietnam Armor Training Facility","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -82.40295410156249,\n 33.23868752757414\n ],\n [\n -82.4036407470703,\n 33.46638955379554\n ],\n [\n -82.08333333333333,\n 33.46666666666667\n ],\n [\n -82.08572387695312,\n 33.23409295522519\n ],\n [\n -82.40295410156249,\n 33.23868752757414\n ]\n ]\n ]\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5059ee37e4b0c8380cd49c22","contributors":{"authors":[{"text":"Guimaraes, Wladmir B. wbguimar@usgs.gov","contributorId":3818,"corporation":false,"usgs":true,"family":"Guimaraes","given":"Wladmir","email":"wbguimar@usgs.gov","middleInitial":"B.","affiliations":[{"id":559,"text":"South Carolina Water Science Center","active":true,"usgs":true}],"preferred":true,"id":467156,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Falls, W. 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Water-quality sampling of Fourmile Creek began within a month after the wildfire to assess its effects on surface-water chemistry. Water samples were collected from five sites along Fourmile Creek (above, within, and below the burned area) monthly during base flow, twice weekly during snowmelt runoff, and at higher frequencies during storm events. Stream discharge was also monitored. Water-quality samples were collected less frequently from an additional 6 sites on Fourmile Creek, from 11 tributaries or other inputs, and from 3 sites along Boulder Creek. The pH, electrical conductivity, temperature, specific ultraviolet absorbance, total suspended solids, and concentrations (dissolved and total) of major cations (calcium, magnesium, sodium, and potassium), anions (chloride, sulfate, alkalinity, fluoride, and bromide), nutrients (nitrate, ammonium, and phosphorus), trace metals (aluminum, arsenic, boron, barium, beryllium, cadmium, cobalt, chromium, copper, iron, mercury, lithium, manganese, molybdenum, nickel, lead, rubidium, antimony, selenium, strontium, vanadium, and zinc), and dissolved organic carbon are here reported for 436 samples collected during 2010 and 2011.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20121104","usgsCitation":"McCleskey, R.B., Writer, J.H., and Murphy, S.F., 2012, Water chemistry of surface waters affected by the Fourmile Canyon wildfire, Colorado, 2010-2011: U.S. Geological Survey Open-File Report 2012-1104, iv, 11 p.; 4 Appendices, https://doi.org/10.3133/ofr20121104.","productDescription":"iv, 11 p.; 4 Appendices","numberOfPages":"15","onlineOnly":"Y","additionalOnlineFiles":"Y","costCenters":[{"id":145,"text":"Branch of Regional Research-Central Region","active":false,"usgs":true}],"links":[{"id":261700,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr_2012_1104.gif"},{"id":261694,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2012/1104/","linkFileType":{"id":5,"text":"html"}},{"id":261695,"rank":300,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2012/1104/OF12-1104.pdf","linkFileType":{"id":1,"text":"pdf"}},{"id":277520,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2012/1104/Appendixes2-4.xlsx"},{"id":277519,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2012/1104/Appendix1.xlsx"}],"country":"United States","state":"Colorado","otherGeospatial":"Fourmile Creek","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -105.43416666666667,40 ], [ -105.43416666666667,40.083333333333336 ], [ -105.3,40.083333333333336 ], [ -105.3,40 ], [ -105.43416666666667,40 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"505bc7d1e4b08c986b32c648","contributors":{"authors":[{"text":"McCleskey, R. 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The purpose of the databases is to (1) provide useful data to ground-survey crews for use in performing detailed assessments of the areas and (2) provide useful information to private investors who are considering investment in a particular area for development of its natural resources. The set of satellite-image mosaics provided in this Data Series (DS) is one such database. Although airborne digital color-infrared imagery was acquired for parts of Afghanistan in 2006, the image data have radiometric variations that preclude their use in creating a consistent image mosaic for geologic analysis. Consequently, image mosaics were created using ALOS (Advanced Land Observation Satellite; renamed Daichi) satellite images, whose radiometry has been well determined (Saunier, 2007a,b). This part of the DS consists of the locally enhanced ALOS image mosaics for the Balkhab mineral district, which has copper deposits. ALOS was launched on January 24, 2006, and provides multispectral images from the AVNIR (Advanced Visible and Near-Infrared Radiometer) sensor in blue (420-500 nanometer, nm), green (520-600 nm), red (610-690 nm), and near-infrared (760-890 nm) wavelength bands with an 8-bit dynamic range and a 10-meter (m) ground resolution. The satellite also provides a panchromatic band image from the PRISM (Panchromatic Remote-sensing Instrument for Stereo Mapping) sensor (520-770 nm) with the same dynamic range but a 2.5-m ground resolution. The image products in this DS incorporate copyrighted data provided by the Japan Aerospace Exploration Agency (©JAXA,2007,2008), but the image processing has altered the original pixel structure and all image values of the JAXA ALOS data, such that original image values cannot be recreated from this DS. As such, the DS products match JAXA criteria for value added products, which are not copyrighted, according to the ALOS end-user license agreement. The selection criteria for the satellite imagery used in our mosaics were images having (1) the highest solar-elevation angles (near summer solstice) and (2) the least cloud, cloud-shadow, and snow cover. The multispectral and panchromatic data were orthorectified with ALOS satellite ephemeris data, a process which is not as accurate as orthorectification using digital elevation models (DEMs); however, the ALOS processing center did not have a precise DEM. As a result, the multispectral and panchromatic image pairs were generally not well registered to the surface and not coregistered well enough to perform resolution enhancement on the multispectral data. Therefore, it was necessary to (1) register the 10-m AVNIR multispectral imagery to a well-controlled Landsat image base, (2) mosaic the individual multispectral images into a single image of the entire area of interest, (3) register each panchromatic image to the registered multispectral image base, and (4) mosaic the individual panchromatic images into a single image of the entire area of interest. The two image-registration steps were facilitated using an automated control-point algorithm developed by the USGS that allows image coregistration to within one picture element. Before rectification, the multispectral and panchromatic images were converted to radiance values and then to relative-reflectance values using the methods described in Davis (2006). Mosaicking the multispectral or panchromatic images started with the image with the highest sun-elevation angle and the least atmospheric scattering, which was treated as the standard image. The band-reflectance values of all other multispectral or panchromatic images within the area were sequentially adjusted to that of the standard image by determining band-reflectance correspondence between overlapping images using linear least-squares analysis. The resolution of the multispectral image mosaic was then increased to that of the panchromatic image mosaic using the SPARKLE logic, which is described in Davis (2006). Each of the four-band images within the resolution-enhanced image mosaic was individually subjected to a local-area histogram stretch algorithm (described in Davis, 2007), which stretches each band's picture element based on the digital values of all picture elements within a 315-m radius. The final databases, which are provided in this DS, are three-band, color-composite images of the local-area-enhanced, natural-color data (the blue, green, and red wavelength bands) and color-infrared data (the green, red, and near-infrared wavelength bands). All image data were initially projected and maintained in Universal Transverse Mercator (UTM) map projection using the target area's local zone (42 for Balkhab) and the WGS84 datum. The final image mosaics were subdivided into two overlapping tiles or quadrants because of the large size of the target area. The two image tiles (or quadrants) for the Balkhab area are provided as embedded geotiff images, which can be read and used by most geographic information system (GIS) and image-processing software. The tiff world files (tfw) are provided, even though they are generally not needed for most software to read an embedded geotiff image. Within the Balkhab study area, one subarea was designated for detailed field investigations (that is, the Balkhab Prospect subarea); this subarea was extracted from the area's image mosaic and is provided as separate embedded geotiff images.","largerWorkTitle":"Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan (DS 709)","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds709B","collaboration":"Prepared in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations and the Afghanistan Geological Survey. This report is Chapter B in Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan. For more information, see: DS 709.","usgsCitation":"Davis, P.A., and Cagney, L.E., 2012, Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Balkhab mineral district in Afghanistan: Chapter B in Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan: U.S. Geological Survey Data Series 709, Readme; 2 Maps: 11 x 8.5 inches and 46.68 x 35.61 inches; 6 Image Files; 6 Metadata Files; Shapefiles; DS 709, https://doi.org/10.3133/ds709B.","productDescription":"Readme; 2 Maps: 11 x 8.5 inches and 46.68 x 35.61 inches; 6 Image Files; 6 Metadata Files; Shapefiles; DS 709","onlineOnly":"Y","additionalOnlineFiles":"Y","costCenters":[{"id":387,"text":"Mineral Resources Program","active":true,"usgs":true}],"links":[{"id":262587,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ds_709_B.jpg"},{"id":262584,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/ds/709/b/","linkFileType":{"id":5,"text":"html"}},{"id":262586,"rank":400,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/ds/709/b/index_maps/Balkhab_Image_Index_Map.pdf","linkFileType":{"id":1,"text":"pdf"}},{"id":262585,"rank":400,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/ds/709/b/index_maps/Balkhab_Area-of-Interest_Index_Map.pdf","linkFileType":{"id":1,"text":"pdf"}},{"id":263621,"type":{"id":14,"text":"Image"},"url":"https://pubs.usgs.gov/ds/709/b/image_files/image_files.html"},{"id":263620,"type":{"id":20,"text":"Read Me"},"url":"https://pubs.usgs.gov/ds/709/b/1_readme.txt"},{"id":263622,"type":{"id":16,"text":"Metadata"},"url":"https://pubs.usgs.gov/ds/709/b/metadata/metadata.html"},{"id":263623,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/ds/709/b/shapefiles/shapefiles.html"},{"id":263624,"type":{"id":22,"text":"Related Work"},"url":"https://pubs.usgs.gov/ds/709/"}],"country":"Afghanistan","state":"Balkh;Samangan;Sari-Pul","otherGeospatial":"Balkhab Mineral District","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ 66.25,35.25 ], [ 66.25,35.916667 ], [ 67.25,35.916667 ], [ 67.25,35.25 ], [ 66.25,35.25 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"507d2378e4b0905c2a76c025","contributors":{"authors":[{"text":"Davis, Philip A. pdavis@usgs.gov","contributorId":692,"corporation":false,"usgs":true,"family":"Davis","given":"Philip","email":"pdavis@usgs.gov","middleInitial":"A.","affiliations":[],"preferred":true,"id":468095,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Cagney, Laura E. 0000-0003-3282-2458 lcagney@usgs.gov","orcid":"https://orcid.org/0000-0003-3282-2458","contributorId":4744,"corporation":false,"usgs":true,"family":"Cagney","given":"Laura","email":"lcagney@usgs.gov","middleInitial":"E.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":468096,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ]}