Evaluations of sediment quality conditions are commonly conducted using whole-sediment chemistry analyses but can be enhanced by evaluating multiple lines of evidence, including measures of the bioavailable forms of contaminants. In particular, porewater chemistry data provide information that is directly relevant for interpreting sediment toxicity data. Various methods for sampling porewater for trace metals and dissolved organic carbon (DOC), which is an important moderator of metal bioavailability, have been employed. The present study compares the peeper, push point, centrifugation, and diffusive gradients in thin films (DGT) methods for the quantification of 6 metals and DOC. The methods were evaluated at low and high concentrations of metals in 3 sediments having different concentrations of total organic carbon and acid volatile sulfide and different particle-size distributions. At low metal concentrations, centrifugation and push point sampling resulted in up to 100 times higher concentrations of metals and DOC in porewater compared with peepers and DGTs. At elevated metal levels, the measured concentrations were in better agreement among the 4 sampling techniques. The results indicate that there can be marked differences among operationally different porewater sampling methods, and it is unclear if there is a definitive best method for sampling metals and DOC in porewater.
","language":"English","publisher":"Wiley","doi":"10.1002/etc.3884","usgsCitation":"Cleveland, D.M., Brumbaugh, W.G., and MacDonald, D.D., 2017, A comparison of four porewater sampling methods for metal mixtures and dissolved organic carbon and the implications for sediment toxicity evaluations: Environmental Toxicology and Chemistry, v. 36, no. 11, p. 2906-2915, https://doi.org/10.1002/etc.3884.","productDescription":"10 p.","startPage":"2906","endPage":"2915","ipdsId":"IP-085651","costCenters":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"links":[{"id":438184,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7HD7SVS","text":"USGS data release","linkHelpText":"A comparison of four pore water sampling methods for mixed metals and dissolved organic carbon, and implications for toxicity evaluations-Data"},{"id":346950,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"36","issue":"11","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationDate":"2017-06-09","publicationStatus":"PW","scienceBaseUri":"59e9b990e4b05fe04cd65c39","contributors":{"authors":[{"text":"Cleveland, Danielle M. 0000-0003-3880-4584 dcleveland@usgs.gov","orcid":"https://orcid.org/0000-0003-3880-4584","contributorId":187471,"corporation":false,"usgs":true,"family":"Cleveland","given":"Danielle","email":"dcleveland@usgs.gov","middleInitial":"M.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":713847,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Brumbaugh, William G.","contributorId":187473,"corporation":false,"usgs":false,"family":"Brumbaugh","given":"William","email":"","middleInitial":"G.","affiliations":[],"preferred":false,"id":713848,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"MacDonald, Donald D.","contributorId":176179,"corporation":false,"usgs":false,"family":"MacDonald","given":"Donald","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":713849,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70190557,"text":"ds1063 - 2017 - Groundwater-quality data from the National Water-Quality Assessment Project, January through December 2014 and select quality-control data from May 2012 through December 2014","interactions":[],"lastModifiedDate":"2018-04-03T11:33:14","indexId":"ds1063","displayToPublicDate":"2017-10-05T09:00:00","publicationYear":"2017","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":"1063","title":"Groundwater-quality data from the National Water-Quality Assessment Project, January through December 2014 and select quality-control data from May 2012 through December 2014","docAbstract":"Groundwater-quality data were collected from 559 wells as part of the National Water-Quality Assessment Project of the U.S. Geological Survey National Water-Quality Program from January through December 2014. The data were collected from four types of well networks: principal aquifer study networks, which are used to assess the quality of groundwater used for public water supply; land-use study networks, which are used to assess land-use effects on shallow groundwater quality; major aquifer study networks, which are used to assess the quality of groundwater used for domestic supply; and enhanced trends networks, which are used to evaluate the time scales during which groundwater quality changes. Groundwater samples were analyzed for a large number of water-quality indicators and constituents, including major ions, nutrients, trace elements, volatile organic compounds, pesticides, radionuclides, and some constituents of special interest (arsenic speciation, chromium [VI] and perchlorate). These groundwater-quality data, along with data from quality-control samples, are tabulated in this report and in an associated data release.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds1063","collaboration":"National Water-Quality Assessment Project","usgsCitation":"Arnold, T.L., Bexfield, L.M., Musgrove, MaryLynn, Lindsey, B.D., Stackelberg, P.E., Barlow, J.R., DeSimone, L.A., Kulongoski, J.T., Kingsbury, J.A., Ayotte, J.D., Fleming, B.J., and Belitz, Kenneth, 2017, Groundwater-quality data from the National Water-Quality Assessment Project, January through December 2014 and select quality-control data from May 2012 through December 2014: U.S. Geological Survey Data Series 1063, 83 p., https://doi.org/10.3133/ds1063.","productDescription":"Report: viii, 83 p.; Data Release","numberOfPages":"96","onlineOnly":"Y","ipdsId":"IP-079602","costCenters":[{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true}],"links":[{"id":346378,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7W0942N","text":"USGS 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\"}}]}\n","contact":"Director, Illinois Water Science Center
U.S. Geological Survey
405 North Goodwin Avenue
Urbana, IL 61801-2347
https://il.water.usgs.gov/
The U.S. Geological Survey, in cooperation with the New York City Department of Environmental Protection, sampled 37 sites in the reservoir area for nutrients, major ions, metals, pesticides and their degradates, volatile organic compounds, temperature, pH, and specific conductance during fall 2015. Data collection was done to characterize the local groundwater-flow system and identify potential sources of seeps from the southern embankment at the Hillview Reservoir. Water-quality samples were collected in accordance with standard U.S. Geological Survey methods at 37 sites in and adjacent to Hillview Reservoir. These 37 sites were sampled to determine (1) baseline water-quality conditions of the saturated, low-permeability sediments that compose the earthen embankment that surrounds the reservoir, (2) water-quality conditions in the southwestern part of the study area in relation to the seeps on the embankment, and (3) temporal variation of water-quality conditions between 2006 and 2015 (not included in this report). The physical parameters and the results of the water-quality analysis from the 37 sites are included in this report and can be downloaded from the U.S. Geological Survey National Water Information System website.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds1057","issn":"2327-0271","isbn":"978-1-4113-4179-1","collaboration":" Prepared in cooperation with the New York City Department of Environmental Protection","usgsCitation":"Chu, Anthony, and Noll, M.L., 2017, Water-quality data from an earthen dam site in southern Westchester County, New York, 2015: U.S. Geological Survey Data Series 1057, 83 p., https://doi.org/10.3133/ds1057.","productDescription":"Report: vi, 83 p.; Table 2","numberOfPages":"94","onlineOnly":"N","ipdsId":"IP-084827","costCenters":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"links":[{"id":346167,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/ds/ds1057/coverthb.jpg"},{"id":346486,"rank":3,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/ds/ds1057/ds1057_table02.csv","text":"Table 2","size":"114 KB","linkFileType":{"id":7,"text":"csv"},"description":"DS 1057, Table 2","linkHelpText":"Concentrations of water-quality constituents"},{"id":346168,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/ds/ds1057/ds1057.pdf","text":"Report","size":"2.58 MB","linkFileType":{"id":1,"text":"pdf"},"description":"DS 1057"}],"country":"United States","state":"New York","county":"Westchester County","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -73.87413024902342,\n 40.9055340480462\n ],\n [\n -73.86451721191406,\n 40.9055340480462\n ],\n [\n -73.86451721191406,\n 40.91818248731055\n ],\n [\n -73.87413024902342,\n 40.91818248731055\n ],\n [\n -73.87413024902342,\n 40.9055340480462\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, New York Water Science Center
U.S. Geological Survey
2045 Route 112, Building 4
Coram, NY 11727
(518) 285–5602
or visit our website at
https://ny.water.usgs.gov
Ceres, the largest body in the asteroid belt (940 km diameter), provides a unique opportunity to study the interior structure of a volatile-rich dwarf planet. Variations in a planetary body's subsurface rheology and density affect the rate of topographic relaxation. Preferential attenuation of long wavelength topography (≥150 km) on Ceres suggests that the viscosity of its crust decreases with increasing depth. We present finite element (FE) geodynamical simulations of Ceres to identify the internal structures and compositions that best reproduce its topography as observed by the NASA Dawn mission. We infer that Ceres has a mechanically strong crust with maximum effective viscosity ∼1025 Pa s. Combined with density constraints, this rheology suggests a crustal composition of carbonates or phyllosilicates, water ice, and at least 30 volume percent (vol.%) low-density, high-strength phases most consistent with salt and/or clathrate hydrates. The inference of these crustal materials supports the past existence of a global ocean, consistent with the observed surface composition. Meanwhile, we infer that the uppermost ≥60 km of the silicate-rich mantle is mechanically weak with viscosity <1021 Pa s, suggesting the presence of liquid pore fluids in this region and a low temperature history that avoided igneous differentiation due to late accretion or efficient heat loss through hydrothermal processes.
Industrial activities causing extensive groundwater contamination led to the listing of the Tucson International Airport Area (TIAA) as a Superfund Site in 1983. Early groundwater investigations identified volatile organic compounds (VOCs), including the chlorinated solvents trichloroethylene (TCE) and perchloroethylene (PCE), in wells in the area. Several responsible parties were identified and cleanup activities began in the late 1980s. In 2002, the compound 1,4-dioxane was discovered in wells in the area and has since been detected in measurable concentrations throughout the site. The U.S. Environmental Protection Agency (USEPA) classifies 1,4-dioxane as a likely human carcinogen.
The purpose of this map is to present 1,4-dioxane concentrations in wells sampled from 2002 through mid-2017 in the TIAA Superfund Site area to indicate both the current status and trends in 1,4-dioxane groundwater contamination. This map includes data from wells in the commercial and residential community in the TIAA and does not include data from wells in suspected or confirmed source areas, such as Air Force Plant 44 and Tucson International Airport, or from wells within treatment facilities.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sim3385","collaboration":"Prepared in cooperation with the U.S. Air Force Civil Engineer Center","usgsCitation":"Tillman, Fred, 2017, Concentration and trend of 1,4-dioxane in wells sampled during 2002–2017 in the vicinity of the Tucson International Airport Area Superfund Site: U.S. Geological Survey Scientific Investigations Map 3385, scale 1:7,500, 1 sheet, https://doi.org/10.3133/sim3385.","productDescription":"Map: 30 x 40 inches; Appendix A","onlineOnly":"N","ipdsId":"IP-087761","costCenters":[{"id":128,"text":"Arizona Water Science Center","active":true,"usgs":true}],"links":[{"id":345617,"rank":3,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sim/3385/sim3385_appendixA.xlsx","text":"Appendix A","size":"128 KB","linkFileType":{"id":3,"text":"xlsx"},"description":"SIM 3385"},{"id":345615,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sim/3385/sim.3385.pdf","text":"Map","size":"5.5 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3385"},{"id":345614,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sim/3385/coverthb_.jpg"}],"country":"United States","state":"Arizona","city":"Tucson","otherGeospatial":"Tucson International Airport Area Superfund Site","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -111.236572265625,\n 31.813396010784928\n ],\n [\n -110.71197509765624,\n 31.813396010784928\n ],\n [\n -110.71197509765624,\n 32.127942397192314\n ],\n [\n -111.236572265625,\n 32.127942397192314\n ],\n [\n -111.236572265625,\n 31.813396010784928\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director,
Arizona Water Science Center
U.S. Geological Survey
520 N. Park Avenue
Tucson, AZ 85719
Prior to the arrival of the Dawn spacecraft at Ceres, the dwarf planet was anticipated to be ice-rich. Searches for morphological features related to ice have been ongoing during Dawn's mission at Ceres. Here we report the identification of pitted terrains associated with fresh Cerean impact craters. The Cerean pitted terrains exhibit strong morphological similarities to pitted materials previously identified on Mars (where ice is implicated in pit development) and Vesta (where the presence of ice is debated). We employ numerical models to investigate the formation of pitted materials on Ceres and discuss the relative importance of water ice and other volatiles in pit development there. We conclude that water ice likely plays an important role in pit development on Ceres. Similar pitted terrains may be common in the asteroid belt and may be of interest to future missions motivated by both astrobiology and in situ resource utilization.
","language":"English","publisher":"AGU Publications","doi":"10.1002/2017GL073970","usgsCitation":"Sizemore, H., Platz, T., Schorghofer, N., Prettyman, T., De Sanctis, M., Crown, D.A., Schmedemann, N., Nessemann, A., Kneissl, T., Marchi, S., Schenk, P.M., Bland, M.T., Schmidt, B., Hughson, K.H., Tosi, F., Zambon, F., Mest, S., Yingst, R., Williams, D., Russell, C., and Raymond, C., 2017, Pitted terrains on (1) Ceres and implications for shallow subsurface volatile distribution: Geophysical Research Letters, v. 44, no. 13, p. 6570-6578, https://doi.org/10.1002/2017GL073970.","productDescription":"9 p.","startPage":"6570","endPage":"6578","ipdsId":"IP-082076","costCenters":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"links":[{"id":469505,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doaj.org/article/9ec60cdecbc24e7faac0fa4f772ddd6c","text":"Publisher Index Page"},{"id":345992,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"Ceres","volume":"44","issue":"13","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2017-07-15","publicationStatus":"PW","scienceBaseUri":"59c4cf96e4b017cf313d3cb3","contributors":{"authors":[{"text":"Sizemore, H.G.","contributorId":86195,"corporation":false,"usgs":false,"family":"Sizemore","given":"H.G.","email":"","affiliations":[{"id":13179,"text":"Planetary Science Institute","active":true,"usgs":false}],"preferred":false,"id":710937,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Platz, Thomas","contributorId":128459,"corporation":false,"usgs":false,"family":"Platz","given":"Thomas","affiliations":[{"id":7175,"text":"Institute of Geological Sciences, Planetary Sciences and Remote Sensing, Freie Universitat Berlin","active":true,"usgs":false},{"id":34668,"text":"Max Planck Institute for Solar System Research, Göttingen, Germany","active":true,"usgs":false}],"preferred":false,"id":710938,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Schorghofer, Norbert","contributorId":196619,"corporation":false,"usgs":false,"family":"Schorghofer","given":"Norbert","email":"","affiliations":[{"id":24732,"text":"Planetary Science Institute, Tucson","active":true,"usgs":false}],"preferred":false,"id":710939,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Prettyman, Thomas","contributorId":196620,"corporation":false,"usgs":false,"family":"Prettyman","given":"Thomas","affiliations":[{"id":13179,"text":"Planetary Science Institute","active":true,"usgs":false}],"preferred":false,"id":710940,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"De Sanctis, Maria Christina","contributorId":196621,"corporation":false,"usgs":false,"family":"De Sanctis","given":"Maria Christina","affiliations":[{"id":34654,"text":"Istituto di Astrofisica e Planetologia Spaziali, INAF","active":true,"usgs":false}],"preferred":false,"id":710941,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Crown, David A.","contributorId":196622,"corporation":false,"usgs":false,"family":"Crown","given":"David","email":"","middleInitial":"A.","affiliations":[{"id":24732,"text":"Planetary Science Institute, Tucson","active":true,"usgs":false}],"preferred":false,"id":710942,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Schmedemann, Nico","contributorId":196623,"corporation":false,"usgs":false,"family":"Schmedemann","given":"Nico","email":"","affiliations":[{"id":34669,"text":"Department of Earth Sciences, Freie Universität Berlin, Berlin, Germany","active":true,"usgs":false}],"preferred":false,"id":710943,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Nessemann, Andeas","contributorId":196624,"corporation":false,"usgs":false,"family":"Nessemann","given":"Andeas","email":"","affiliations":[{"id":34669,"text":"Department of Earth Sciences, Freie Universität Berlin, Berlin, Germany","active":true,"usgs":false}],"preferred":false,"id":710944,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Kneissl, Thomas","contributorId":196625,"corporation":false,"usgs":false,"family":"Kneissl","given":"Thomas","email":"","affiliations":[{"id":34669,"text":"Department of Earth Sciences, Freie Universität Berlin, Berlin, Germany","active":true,"usgs":false}],"preferred":false,"id":710945,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Marchi, Simone","contributorId":172689,"corporation":false,"usgs":false,"family":"Marchi","given":"Simone","email":"","affiliations":[{"id":27081,"text":"Southwest Research Inst.","active":true,"usgs":false}],"preferred":false,"id":710946,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Schenk, Paul M.","contributorId":196626,"corporation":false,"usgs":false,"family":"Schenk","given":"Paul","email":"","middleInitial":"M.","affiliations":[{"id":12445,"text":"Lunar and Planetary Institute","active":true,"usgs":false}],"preferred":false,"id":710947,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Bland, Michael T. 0000-0001-5543-1519 mbland@usgs.gov","orcid":"https://orcid.org/0000-0001-5543-1519","contributorId":146287,"corporation":false,"usgs":true,"family":"Bland","given":"Michael","email":"mbland@usgs.gov","middleInitial":"T.","affiliations":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"preferred":true,"id":710936,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Schmidt, B.E.","contributorId":177354,"corporation":false,"usgs":false,"family":"Schmidt","given":"B.E.","email":"","affiliations":[{"id":27526,"text":"Georgia Institute of Technology","active":true,"usgs":false}],"preferred":false,"id":710948,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Hughson, Kynan H.G.","contributorId":192186,"corporation":false,"usgs":false,"family":"Hughson","given":"Kynan","email":"","middleInitial":"H.G.","affiliations":[{"id":32998,"text":"Department of Earth, Planetary, and Space Sciences, University of California, Los Angeles, CA, USA","active":true,"usgs":false}],"preferred":false,"id":710987,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Tosi, F.","contributorId":9472,"corporation":false,"usgs":false,"family":"Tosi","given":"F.","email":"","affiliations":[{"id":34654,"text":"Istituto di Astrofisica e Planetologia Spaziali, INAF","active":true,"usgs":false}],"preferred":false,"id":710988,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Zambon, F","contributorId":145548,"corporation":false,"usgs":false,"family":"Zambon","given":"F","affiliations":[{"id":16145,"text":"Italian Space Agency","active":true,"usgs":false},{"id":34654,"text":"Istituto di Astrofisica e Planetologia Spaziali, INAF","active":true,"usgs":false}],"preferred":false,"id":710989,"contributorType":{"id":1,"text":"Authors"},"rank":16},{"text":"Mest, S.C.","contributorId":177355,"corporation":false,"usgs":false,"family":"Mest","given":"S.C.","affiliations":[{"id":24732,"text":"Planetary Science Institute, Tucson","active":true,"usgs":false}],"preferred":false,"id":710990,"contributorType":{"id":1,"text":"Authors"},"rank":17},{"text":"Yingst, R.A.","contributorId":101370,"corporation":false,"usgs":false,"family":"Yingst","given":"R.A.","email":"","affiliations":[{"id":24732,"text":"Planetary Science Institute, Tucson","active":true,"usgs":false}],"preferred":false,"id":710991,"contributorType":{"id":1,"text":"Authors"},"rank":18},{"text":"Williams, D.A.","contributorId":98048,"corporation":false,"usgs":false,"family":"Williams","given":"D.A.","email":"","affiliations":[{"id":7114,"text":"Arizona State Unviersity","active":true,"usgs":false}],"preferred":false,"id":710992,"contributorType":{"id":1,"text":"Authors"},"rank":19},{"text":"Russell, C.T.","contributorId":32275,"corporation":false,"usgs":false,"family":"Russell","given":"C.T.","email":"","affiliations":[{"id":33607,"text":"University of California Los Angeles","active":true,"usgs":false}],"preferred":false,"id":710993,"contributorType":{"id":1,"text":"Authors"},"rank":20},{"text":"Raymond, C.A.","contributorId":50301,"corporation":false,"usgs":false,"family":"Raymond","given":"C.A.","email":"","affiliations":[{"id":18954,"text":"Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA","active":true,"usgs":false}],"preferred":false,"id":710994,"contributorType":{"id":1,"text":"Authors"},"rank":21}]}} ,{"id":70191019,"text":"70191019 - 2017 - Assessment of critical minerals: Updated application of an early-warning screening methodology","interactions":[],"lastModifiedDate":"2018-02-21T13:15:12","indexId":"70191019","displayToPublicDate":"2017-09-21T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5502,"text":"Mineral Economics","onlineIssn":"2191-2211","printIssn":"2191-2203","active":true,"publicationSubtype":{"id":10}},"title":"Assessment of critical minerals: Updated application of an early-warning screening methodology","docAbstract":"Increasing reliance on non-renewable mineral resources reinforces the need for identifying potential supply constraints before they occur. The US National Science and Technology Council recently released a report that outlines a methodology for screening potentially critical minerals based on three indicators: supply risk (R), production growth (G), and market dynamics (M). This early-warning screening was initially applied to 78 minerals across the years 1996 to 2013 and identified a subset of minerals as “potentially critical” based on the geometric average of these indicators—designated as criticality potential (C). In this study, the screening methodology has been updated to include data for 2014, as well as to incorporate revisions and modifications to the data, where applicable. Overall, C declined in 2014 for the majority of minerals examined largely due to decreases in production concentration and price volatility. However, the results vary considerably across minerals, with some minerals, such as gallium, recording increases for all three indicators. In addition to assessing magnitudinal changes, this analysis also examines the significance of the change relative to historical variation for each mineral. For example, although mined nickel’s R declined modestly in 2014 in comparison to that of other minerals, it was by far the largest annual change recorded for mined nickel across all years examined and is attributable to Indonesia’s ban on the export of unprocessed minerals. Based on the 2014 results, 20 minerals with the highest C values have been identified for further study including the rare earths, gallium, germanium, rhodium, tantalum, and tungsten.
","language":"English","publisher":"Springer","doi":"10.1007/s13563-017-0119-6","usgsCitation":"McCullough, E.A., and Nassar, N., 2017, Assessment of critical minerals: Updated application of an early-warning screening methodology: Mineral Economics, v. 30, no. 3, p. 257-272, https://doi.org/10.1007/s13563-017-0119-6.","productDescription":"16 p.","startPage":"257","endPage":"272","ipdsId":"IP-090603","costCenters":[{"id":432,"text":"National Minerals Information Center","active":true,"usgs":true}],"links":[{"id":469507,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1007/s13563-017-0119-6","text":"External Repository"},{"id":345990,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"30","issue":"3","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2017-09-19","publicationStatus":"PW","scienceBaseUri":"59c4cf95e4b017cf313d3cab","contributors":{"authors":[{"text":"McCullough, Erin A. 0000-0002-9072-7021 emccullough@usgs.gov","orcid":"https://orcid.org/0000-0002-9072-7021","contributorId":196629,"corporation":false,"usgs":true,"family":"McCullough","given":"Erin","email":"emccullough@usgs.gov","middleInitial":"A.","affiliations":[{"id":432,"text":"National Minerals Information Center","active":true,"usgs":true}],"preferred":false,"id":710953,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Nassar, Nedal 0000-0001-8758-9732 nnassar@usgs.gov","orcid":"https://orcid.org/0000-0001-8758-9732","contributorId":196630,"corporation":false,"usgs":true,"family":"Nassar","given":"Nedal","email":"nnassar@usgs.gov","affiliations":[{"id":432,"text":"National Minerals Information Center","active":true,"usgs":true}],"preferred":false,"id":710954,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70190806,"text":"70190806 - 2017 - Holistic assessment of occurrence and fate of metolachlor within environmental compartments of agricultural watersheds","interactions":[],"lastModifiedDate":"2017-09-20T10:04:44","indexId":"70190806","displayToPublicDate":"2017-09-14T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3352,"text":"Science of the Total Environment","active":true,"publicationSubtype":{"id":10}},"title":"Holistic assessment of occurrence and fate of metolachlor within environmental compartments of agricultural watersheds","docAbstract":"Background: Metolachlor [(RS)-2-Chloro-N-(2-ethyl-6-methyl-phenyl)-N-(1-methoxypropan-2-yl)acetamide] and two degradates (metolachlor ethane-sulfonic acid and metolachlor oxanilic acid) are commonly observed in surface and groundwater. The behavior and fate of these compounds were examined over a 12-year period in seven agricultural watersheds in the United States. They were quantified in air, rain, streams, overland flow, groundwater, soil water, subsurface drain water, and water at the stream/groundwater interface. The compounds were frequently detected in surface and groundwater associated with agricultural areas. A mass budget approach, based on all available data from the study and literature, was used to determine a percentage-wise generalized distribution and fate of applied parent metolachlor in typical agricultural environments.
Results: In these watersheds, about 90% of applied metolachlor was taken up by plants or degraded, 10% volatilized, and 0.3% returned as rainfall. One percent was transported to surface water, while an equal amount infiltrated into the unsaturated zone soil water. < 0.02% reached the groundwater. Subsurface flow paths resulted in greater degradation of metolachlor because degradation reactions had more time to proceed.
Conclusions: An understanding of the residence times of water in the different environmental compartments, and the important processes affecting metolachlor as it is transported along flowpaths among the environmental compartments allows for a degree of predictability of metolachlor's fate. Degradates with long half-lives can be used (in a limited capacity) as tracers of metolachlor, because of their persistence and widespread occurrence in the environment.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.scitotenv.2017.08.154","usgsCitation":"Rose, C.E., Coupe, R.H., Capel, P.D., and Webb, R.M., 2017, Holistic assessment of occurrence and fate of metolachlor within environmental compartments of agricultural watersheds: Science of the Total Environment, v. 612, p. 708-719, https://doi.org/10.1016/j.scitotenv.2017.08.154.","productDescription":"12 p.","startPage":"708","endPage":"719","ipdsId":"IP-077291","costCenters":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"links":[{"id":345776,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"612","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"59bb952ce4b091459a578170","contributors":{"authors":[{"text":"Rose, Claire E. 0000-0002-5519-3538 cerose@usgs.gov","orcid":"https://orcid.org/0000-0002-5519-3538","contributorId":2317,"corporation":false,"usgs":true,"family":"Rose","given":"Claire","email":"cerose@usgs.gov","middleInitial":"E.","affiliations":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"preferred":true,"id":710480,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Coupe, Richard H. 0000-0001-8679-1015 rhcoupe@usgs.gov","orcid":"https://orcid.org/0000-0001-8679-1015","contributorId":551,"corporation":false,"usgs":true,"family":"Coupe","given":"Richard","email":"rhcoupe@usgs.gov","middleInitial":"H.","affiliations":[{"id":394,"text":"Mississippi Water Science Center","active":true,"usgs":true}],"preferred":true,"id":710481,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Capel, Paul D. 0000-0003-1620-5185 capel@usgs.gov","orcid":"https://orcid.org/0000-0003-1620-5185","contributorId":1002,"corporation":false,"usgs":true,"family":"Capel","given":"Paul","email":"capel@usgs.gov","middleInitial":"D.","affiliations":[{"id":392,"text":"Minnesota Water Science Center","active":true,"usgs":true},{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true},{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"preferred":true,"id":710482,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Webb, Richard M. 0000-0001-9531-2207 rmwebb@usgs.gov","orcid":"https://orcid.org/0000-0001-9531-2207","contributorId":1570,"corporation":false,"usgs":true,"family":"Webb","given":"Richard","email":"rmwebb@usgs.gov","middleInitial":"M.","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":710483,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70190319,"text":"70190319 - 2017 - Evidence for degassing of fresh magma during the 2004-2008 eruption of Mount St. Helens: Subtle signals from the hydrothermal system","interactions":[],"lastModifiedDate":"2017-08-27T11:55:21","indexId":"70190319","displayToPublicDate":"2017-08-27T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2499,"text":"Journal of Volcanology and Geothermal Research","active":true,"publicationSubtype":{"id":10}},"title":"Evidence for degassing of fresh magma during the 2004-2008 eruption of Mount St. Helens: Subtle signals from the hydrothermal system","docAbstract":"Results from chemical and isotopic analyses of water and gas collected between 2002 and 2016 from sites on and around Mount St. Helens are used to assess magmatic degassing related to the 2004-2008 eruption. During 2005 the chemistry of hot springs in The Breach of Mount St. Helens showed no obvious response to the eruption, and over the next few years, changes were subtle, giving only slight indications of perturbations in the system. By 2010 however, water chemistry, temperatures, and isotope compositions (δD and δ18O) clearly indicated some inputs of volatiles and heat associated with the eruption, but the changes were such that they could be attributed to a pre-existing, gas depleted magma. An increase of ~ 1.5‰ in the δ13C values of dissolved carbon in the springs was noted in 2006 and continued through 2009, a change that was mirrored by a similar shift in δ13C-CO2 in bubble gas emissions. These changes require input of a new source of carbon to the hydrothermal system and provide clear evidence of CO2 from an undegassed body of magma. Rising trends in 3He/4He ratios in gas also accompanied the increases in δ13C. Since 2011 maximum RC/RA values are ≥ 6.4 and are distinctly higher than 5 samples collected between 1986 and 2002, and provide additional evidence for some involvement of new magma as early as 2006, and possibly earlier, given the unknown time needed for CO2 and He to traverse the system and arrive at the springs.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.jvolgeores.2017.06.020","usgsCitation":"Bergfeld, D., Evans, W.C., Spicer, K.R., Hunt, A.G., and Kelly, P.J., 2017, Evidence for degassing of fresh magma during the 2004-2008 eruption of Mount St. Helens: Subtle signals from the hydrothermal system: Journal of Volcanology and Geothermal Research, v. 343, p. 109-121, https://doi.org/10.1016/j.jvolgeores.2017.06.020.","productDescription":"13 p.","startPage":"109","endPage":"121","ipdsId":"IP-087110","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":461426,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.jvolgeores.2017.06.020","text":"Publisher Index Page"},{"id":345181,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Washington","otherGeospatial":"Mount St. Helens","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.42202758789061,\n 46.06465561687544\n ],\n [\n -121.97158813476561,\n 46.06465561687544\n ],\n [\n -121.97158813476561,\n 46.326068311712596\n ],\n [\n -122.42202758789061,\n 46.326068311712596\n ],\n [\n -122.42202758789061,\n 46.06465561687544\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"343","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"59a3da2fe4b077f00567321f","contributors":{"authors":[{"text":"Bergfeld, Deborah 0000-0003-4570-7627 dbergfel@usgs.gov","orcid":"https://orcid.org/0000-0003-4570-7627","contributorId":152531,"corporation":false,"usgs":true,"family":"Bergfeld","given":"Deborah","email":"dbergfel@usgs.gov","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":708430,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Evans, William C. 0000-0001-5942-3102 wcevans@usgs.gov","orcid":"https://orcid.org/0000-0001-5942-3102","contributorId":2353,"corporation":false,"usgs":true,"family":"Evans","given":"William","email":"wcevans@usgs.gov","middleInitial":"C.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":708431,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Spicer, Kurt R. 0000-0001-5030-3198 krspicer@usgs.gov","orcid":"https://orcid.org/0000-0001-5030-3198","contributorId":2684,"corporation":false,"usgs":true,"family":"Spicer","given":"Kurt","email":"krspicer@usgs.gov","middleInitial":"R.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":708432,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hunt, Andrew G. 0000-0002-3810-8610 ahunt@usgs.gov","orcid":"https://orcid.org/0000-0002-3810-8610","contributorId":1582,"corporation":false,"usgs":true,"family":"Hunt","given":"Andrew","email":"ahunt@usgs.gov","middleInitial":"G.","affiliations":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":708433,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Kelly, Peter J. 0000-0002-3868-1046 pkelly@usgs.gov","orcid":"https://orcid.org/0000-0002-3868-1046","contributorId":5931,"corporation":false,"usgs":true,"family":"Kelly","given":"Peter","email":"pkelly@usgs.gov","middleInitial":"J.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":708434,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70227369,"text":"70227369 - 2017 - Initial pulse of Siberian Traps sills as the trigger of the end-Permian mass extinction","interactions":[],"lastModifiedDate":"2022-01-11T19:15:20.919633","indexId":"70227369","displayToPublicDate":"2017-07-31T13:04:21","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2842,"text":"Nature Communications","active":true,"publicationSubtype":{"id":10}},"title":"Initial pulse of Siberian Traps sills as the trigger of the end-Permian mass extinction","docAbstract":"Mass extinction events are short-lived and characterized by catastrophic biosphere collapse and subsequent reorganization. Their abrupt nature necessitates a similarly short-lived trigger, and large igneous province magmatism is often implicated. However, large igneous provinces are long-lived compared to mass extinctions. Therefore, if large igneous provinces are an effective trigger, a subinterval of magmatism must be responsible for driving deleterious environmental effects. The onset of Earth’s most severe extinction, the end-Permian, coincided with an abrupt change in the emplacement style of the contemporaneous Siberian Traps large igneous province, from dominantly flood lavas to sill intrusions. Here we identify the initial emplacement pulse of laterally extensive sills as the critical deadly interval. Heat from these sills exposed untapped volatile-fertile sediments to contact metamorphism, likely liberating the massive greenhouse gas volumes needed to drive extinction. These observations suggest that large igneous provinces characterized by sill complexes are more likely to trigger catastrophic global environmental change than their flood basalt- and/or dike-dominated counterparts.","language":"English","publisher":"Nature Publishing Group","doi":"10.1038/s41467-017-00083-9","usgsCitation":"Burgess, S.D., James D. 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Muirhead","contributorId":271057,"corporation":false,"usgs":false,"family":"James D. Muirhead","affiliations":[{"id":5082,"text":"Syracuse University","active":true,"usgs":false}],"preferred":false,"id":830621,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bowring, Samuel A.","contributorId":271058,"corporation":false,"usgs":false,"family":"Bowring","given":"Samuel","email":"","middleInitial":"A.","affiliations":[{"id":12444,"text":"Massachusetts Institute of Technology","active":true,"usgs":false}],"preferred":false,"id":830622,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70189810,"text":"70189810 - 2017 - Noble gas data from Goldfield and Tonopah epithermal Au-Ag deposits, ancestral Cascades Arc, USA: Evidence for a primitive mantle volatile source","interactions":[],"lastModifiedDate":"2017-07-26T15:37:17","indexId":"70189810","displayToPublicDate":"2017-07-26T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2954,"text":"Ore Geology Reviews","active":true,"publicationSubtype":{"id":10}},"title":"Noble gas data from Goldfield and Tonopah epithermal Au-Ag deposits, ancestral Cascades Arc, USA: Evidence for a primitive mantle volatile source","docAbstract":"The He, Ne, and Ar isotopic composition of fluid inclusions in ore and gangue minerals were analyzed to determine the source of volatiles in the high-grade Goldfield and Tonopah epithermal Au-Ag deposits in southwestern Nevada, USA. Ar and Ne are mainly atmospheric, whereas He has only a minor atmospheric component. Corrected 3He/4He ratios (with atmospheric He removed) range widely from 0.05 to 35.8 times the air 3He/4He ratio (RA), with a median of 1.43 RA. Forty-one percent of measured 3He/4He ratios are ≥4 RA, corresponding to ≥50% mantle He assuming a mantle ratio of 8 RA. These results suggest that mafic magmas were part of the magmatic-hydrothermal system underlying Goldfield and Tonopah, and that associated mantle-sourced volatiles may have played a role in ore formation. The three highest corrected 3He/4He ratios of 17.0, 23.7, and 35.8 RAindicate a primitive mantle He source and are the highest yet reported for any epithermal-porphyry system and for the Cascades arc region. Compiled 3He/4He measurements from epithermal-porphyry systems in subduction-related magmatic arcs around the world (n = 209) display a statistically significant correlation between 3He/4He and Au-Ag grade. The correlation suggests that conditions which promote higher fluid inclusion 3He/4He ratios (abundance of mantle volatiles and focused upward volatile transport) have some relation to conditions that promote higher Au-Ag grades (focused flow of metal-bearing fluids and efficient chemical traps). Results of this and previous investigations of He isotopes in epithermal-porphyry systems are consistent with the hypothesis posed in recent studies that mafic magmas serve an important function in the formation of these deposits.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.oregeorev.2017.06.023","usgsCitation":"Manning, A.H., and Hofstra, A.H., 2017, Noble gas data from Goldfield and Tonopah epithermal Au-Ag deposits, ancestral Cascades Arc, USA: Evidence for a primitive mantle volatile source: Ore Geology Reviews, v. 89, p. 683-700, https://doi.org/10.1016/j.oregeorev.2017.06.023.","productDescription":"18 p.","startPage":"683","endPage":"700","ipdsId":"IP-079179","costCenters":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"links":[{"id":469663,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.oregeorev.2017.06.023","text":"Publisher Index Page"},{"id":344344,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Cascades Arc","volume":"89","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5979aa4fe4b0ec1a488b8bcf","contributors":{"authors":[{"text":"Manning, Andrew H. 0000-0002-6404-1237 amanning@usgs.gov","orcid":"https://orcid.org/0000-0002-6404-1237","contributorId":1305,"corporation":false,"usgs":true,"family":"Manning","given":"Andrew","email":"amanning@usgs.gov","middleInitial":"H.","affiliations":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":706437,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hofstra, Albert H. 0000-0002-2450-1593 ahofstra@usgs.gov","orcid":"https://orcid.org/0000-0002-2450-1593","contributorId":1302,"corporation":false,"usgs":true,"family":"Hofstra","given":"Albert","email":"ahofstra@usgs.gov","middleInitial":"H.","affiliations":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":706438,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70189747,"text":"70189747 - 2017 - Volcano geodesy in the Cascade arc, USA","interactions":[],"lastModifiedDate":"2018-10-25T15:58:17","indexId":"70189747","displayToPublicDate":"2017-07-24T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1109,"text":"Bulletin of Volcanology","active":true,"publicationSubtype":{"id":10}},"title":"Volcano geodesy in the Cascade arc, USA","docAbstract":"Experience during historical time throughout the Cascade arc and the lack of deep-seated deformation prior to the two most recent eruptions of Mount St. Helens might lead one to infer that Cascade volcanoes are generally quiescent and, specifically, show no signs of geodetic change until they are about to erupt. Several decades of geodetic data, however, tell a different story. Ground- and space-based deformation studies have identified surface displacements at five of the 13 major Cascade arc volcanoes that lie in the USA (Mount Baker, Mount St. Helens, South Sister, Medicine Lake, and Lassen volcanic center). No deformation has been detected at five volcanoes (Mount Rainier, Mount Hood, Newberry Volcano, Crater Lake, and Mount Shasta), and there are not sufficient data at the remaining three (Glacier Peak, Mount Adams, and Mount Jefferson) for a rigorous assessment. In addition, gravity change has been measured at two of the three locations where surveys have been repeated (Mount St. Helens and Mount Baker show changes, while South Sister does not). Broad deformation patterns associated with heavily forested and ice-clad Cascade volcanoes are generally characterized by low displacement rates, in the range of millimeters to a few centimeters per year, and are overprinted by larger tectonic motions of several centimeters per year. Continuous GPS is therefore the best means of tracking temporal changes in deformation of Cascade volcanoes and also for characterizing tectonic signals so that they may be distinguished from volcanic sources. Better spatial resolution of volcano deformation can be obtained through the use of campaign GPS, semipermanent GPS, and interferometric synthetic aperture radar observations, which leverage the accumulation of displacements over time to improve signal to noise. Deformation source mechanisms in the Cascades are diverse and include magma accumulation and withdrawal, post-emplacement cooling of recent volcanic deposits, magmatic-tectonic interactions, and loss of volatiles plus densification of magma. The Cascade Range thus offers an outstanding opportunity for investigating a wide range of volcanic processes. Indeed, there may be areas of geodetic change that have yet to be discovered, and there is good potential for addressing a number of important questions about how arc volcanoes work before, during, and after eruptions by continuing geodetic research in the Cascade Range.
","language":"English","publisher":"Springer","doi":"10.1007/s00445-017-1140-x","usgsCitation":"Poland, M.P., Lisowski, M., Dzurisin, D., Kramer, R., McLay, M., and Pauk, B., 2017, Volcano geodesy in the Cascade arc, USA: Bulletin of Volcanology, v. 79, p. 1-33, https://doi.org/10.1007/s00445-017-1140-x.","productDescription":"Article 59; 33 p.","startPage":"1","endPage":"33","ipdsId":"IP-084861","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":344270,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Cascade Arc","volume":"79","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2017-07-12","publicationStatus":"PW","scienceBaseUri":"59770749e4b0ec1a48889f2e","contributors":{"authors":[{"text":"Poland, Michael P. 0000-0001-5240-6123 mpoland@usgs.gov","orcid":"https://orcid.org/0000-0001-5240-6123","contributorId":146118,"corporation":false,"usgs":true,"family":"Poland","given":"Michael","email":"mpoland@usgs.gov","middleInitial":"P.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":706175,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lisowski, Michael 0000-0003-4818-2504 mlisowski@usgs.gov","orcid":"https://orcid.org/0000-0003-4818-2504","contributorId":637,"corporation":false,"usgs":true,"family":"Lisowski","given":"Michael","email":"mlisowski@usgs.gov","affiliations":[{"id":615,"text":"Volcano Hazards Program","active":true,"usgs":true},{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":706179,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Dzurisin, Daniel 0000-0002-0138-5067 dzurisin@usgs.gov","orcid":"https://orcid.org/0000-0002-0138-5067","contributorId":538,"corporation":false,"usgs":true,"family":"Dzurisin","given":"Daniel","email":"dzurisin@usgs.gov","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":706178,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kramer, Rebecca 0000-0002-4873-1983 rkramer@usgs.gov","orcid":"https://orcid.org/0000-0002-4873-1983","contributorId":195070,"corporation":false,"usgs":true,"family":"Kramer","given":"Rebecca","email":"rkramer@usgs.gov","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":706180,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"McLay, Megan 0000-0002-7527-1820 mmclay@usgs.gov","orcid":"https://orcid.org/0000-0002-7527-1820","contributorId":5095,"corporation":false,"usgs":true,"family":"McLay","given":"Megan","email":"mmclay@usgs.gov","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":706176,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Pauk, Benjamin 0000-0003-3036-5927 bpauk@usgs.gov","orcid":"https://orcid.org/0000-0003-3036-5927","contributorId":195069,"corporation":false,"usgs":true,"family":"Pauk","given":"Benjamin","email":"bpauk@usgs.gov","affiliations":[],"preferred":true,"id":706177,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70189150,"text":"70189150 - 2017 - Remote measurement of high preeruptive water vapor emissions at Sabancaya volcano by passive differential optical absorption spectroscopy","interactions":[],"lastModifiedDate":"2017-07-03T09:29:03","indexId":"70189150","displayToPublicDate":"2017-07-03T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2314,"text":"Journal of Geophysical Research B: Solid Earth","active":true,"publicationSubtype":{"id":10}},"title":"Remote measurement of high preeruptive water vapor emissions at Sabancaya volcano by passive differential optical absorption spectroscopy","docAbstract":"Water (H2O) is by far the most abundant volcanic volatile species and plays a predominant role in driving volcanic eruptions. However, numerous difficulties associated with making accurate measurements of water vapor in volcanic plumes have limited their use as a diagnostic tool. Here we present the first detection of water vapor in a volcanic plume using passive visible-light differential optical absorption spectroscopy (DOAS). Ultraviolet and visible-light DOAS measurements were made on 21 May 2016 at Sabancaya Volcano, Peru. We find that Sabancaya's plume contained an exceptionally high relative water vapor abundance 6 months prior to its November 2016 eruption. Our measurements yielded average sulfur dioxide (SO2) emission rates of 800–900 t/d, H2O emission rates of around 250,000 t/d, and an H2O/SO2 molecular ratio of 1000 which is about an order of magnitude larger than typically found in high-temperature volcanic gases. We attribute the high water vapor emissions to a boiling-off of Sabancaya's hydrothermal system caused by intrusion of magma to shallow depths. This hypothesis is supported by a significant increase in the thermal output of the volcanic edifice detected in infrared satellite imagery leading up to and after our measurements. Though the measurement conditions encountered at Sabancaya were very favorable for our experiment, we show that visible-light DOAS systems could be used to measure water vapor emissions at numerous other high-elevation volcanoes. Such measurements would provide observatories with additional information particularly useful for forecasting eruptions at volcanoes harboring significant hydrothermal systems.
","language":"English","publisher":"American Geophysical Union","doi":"10.1002/2017JB014020","usgsCitation":"Kern, C., Masias, P., Apaza, F., Reath, K., and Platt, U., 2017, Remote measurement of high preeruptive water vapor emissions at Sabancaya volcano by passive differential optical absorption spectroscopy: Journal of Geophysical Research B: Solid Earth, v. 122, no. 5, p. 3540-3564, https://doi.org/10.1002/2017JB014020.","productDescription":"25 p.","startPage":"3540","endPage":"3564","ipdsId":"IP-083524","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":469701,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1002/2017jb014020","text":"External Repository"},{"id":343266,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"122","issue":"5","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2017-05-21","publicationStatus":"PW","scienceBaseUri":"595b5797e4b0d1f9f0536da9","contributors":{"authors":[{"text":"Kern, Christoph 0000-0002-8920-5701 ckern@usgs.gov","orcid":"https://orcid.org/0000-0002-8920-5701","contributorId":3387,"corporation":false,"usgs":true,"family":"Kern","given":"Christoph","email":"ckern@usgs.gov","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":703175,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Masias, Pablo","contributorId":190934,"corporation":false,"usgs":false,"family":"Masias","given":"Pablo","email":"","affiliations":[],"preferred":false,"id":703176,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Apaza, Fredy","contributorId":190927,"corporation":false,"usgs":false,"family":"Apaza","given":"Fredy","email":"","affiliations":[],"preferred":false,"id":703177,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Reath, Kevin","contributorId":194091,"corporation":false,"usgs":false,"family":"Reath","given":"Kevin","email":"","affiliations":[{"id":12722,"text":"Cornell University","active":true,"usgs":false}],"preferred":false,"id":703178,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Platt, Ulrich","contributorId":194092,"corporation":false,"usgs":false,"family":"Platt","given":"Ulrich","email":"","affiliations":[],"preferred":false,"id":703179,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70187493,"text":"sir20175043 - 2017 - Status and understanding of groundwater quality in the Bear Valley and Lake Arrowhead Watershed Study Unit, 2010: California GAMA Priority Basin Project","interactions":[],"lastModifiedDate":"2017-06-22T16:21:33","indexId":"sir20175043","displayToPublicDate":"2017-06-20T00:00:00","publicationYear":"2017","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":"2017-5043","title":"Status and understanding of groundwater quality in the Bear Valley and Lake Arrowhead Watershed Study Unit, 2010: California GAMA Priority Basin Project","docAbstract":"Groundwater quality in the 112-square-mile Bear Valley and Lake Arrowhead Watershed (BEAR) study unit was investigated as part of the Priority Basin Project (PBP) of the Groundwater Ambient Monitoring and Assessment (GAMA) Program. The study unit comprises two study areas (Bear Valley and Lake Arrowhead Watershed) in southern California in San Bernardino County. The GAMA-PBP is conducted by the California State Water Resources Control Board (SWRCB) in cooperation with the U.S. Geological Survey (USGS) and the Lawrence Livermore National Laboratory.
The GAMA BEAR study was designed to provide a spatially balanced, robust assessment of the quality of untreated (raw) groundwater from the primary aquifer systems in the two study areas of the BEAR study unit. The assessment is based on water-quality collected by the USGS from 38 sites (27 grid and 11 understanding) during 2010 and on water-quality data from the SWRCB-Division of Drinking Water (DDW) database. The primary aquifer system is defined by springs and the perforation intervals of wells listed in the SWRCB-DDW water-quality database for the BEAR study unit.
This study included two types of assessments: (1) a status assessment, which characterized the status of the quality of the groundwater resource as of 2010 by using data from samples analyzed for volatile organic compounds, pesticides, and naturally present inorganic constituents, such as major ions and trace elements, and (2) an understanding assessment, which evaluated the natural and human factors potentially affecting the groundwater quality. The assessments were intended to characterize the quality of groundwater resources in the primary aquifer system of the BEAR study unit, not the treated drinking water delivered to consumers. Bear Valley study area and the Lake Arrowhead Watershed study area were also compared statistically on the basis of water-quality results and factors potentially affecting the groundwater quality.
Relative concentrations (RCs), which are sample concentration of a particular constituent divided by its associated health- or aesthetic-based benchmark concentrations, were used for evaluating the groundwater quality for those constituents that have Federal or California regulatory or non-regulatory benchmarks for drinking-water quality. An RC greater than 1.0 indicates a concentration greater than a benchmark. Organic (volatile organic compounds and pesticides) and special-interest (perchlorate) constituent RCs were classified as “high” (RC greater than 1.0), “moderate” (RC less than or equal to 1.0 and greater than 0.1), or “low” (RC less than or equal to 0.1). For inorganic (radioactive, trace element, major ion, and nutrient) constituents, the boundary between low and moderate RCs was set at 0.5.
Aquifer-scale proportion was used as the primary metric in the status assessment for evaluating groundwater quality at the study-unit scale or for its component areas. High aquifer-scale proportion was defined as the percentage of the area of the primary aquifer system with a RC greater than 1.0 for a particular constituent or class of constituents; the percentage is based on area rather than volume. Moderate and low aquifer-scale proportions were defined as the percentage of the primary aquifer system with moderate and low RCs, respectively. A spatially weighted statistical approach was used to evaluate aquifer-scale proportions for individual constituents and classes of constituents.
The status assessment for the Bear Valley study area found that inorganic constituents with health-based benchmarks were detected at high RCs in 9.0 percent of the primary aquifer system and at moderate RCs in 13 percent. The high RCs of inorganic constituents primarily reflected high aquifer-scale proportions of fluoride (in 5.4 percent of the primary aquifer system) and arsenic (3.6 percent). The RCs of organic constituents with health-based benchmarks were high in 1.0 percent of the primary aquifer system, moderate in 8.1 percent, and low in 70 percent. Organic constituents were detected in 79 percent of the primary aquifer system. Two groups of organic constituents and two individual organic constituents were detected at frequencies greater than 10 percent of samples from the USGS grid sites: trihalomethanes (THMs), solvents, methyl tert-butyl ether (MTBE), and simazine. The special-interest constituent perchlorate was detected in 93 percent of the primary aquifer system; it was detected at moderate RCs in 7.1 percent and at low RCs in 86 percent.
The status assessment in the Lake Arrowhead Watershed study area showed that inorganic constituents with human-health benchmarks were detected at high RCs in 25 percent of the primary aquifer system and at moderate RCs in 41 percent. The high aquifer-scale proportion of inorganic constituents primarily reflected high aquifer-scale proportions of radon‑222 (in 62 percent of the primary aquifer system) and uranium (26 percent). RCs of organic constituents with health-based benchmarks were moderate in 7.7 percent of the primary aquifer system and low in 46 percent. Organic constituents were detected in 54 percent of the primary aquifer system. The only organic constituents that were detected at frequencies greater than 10 percent of samples from the USGS grid sites were THMs. Perchlorate was detected in 62 percent of the primary aquifer system at uniformly low RCs.
The second component of this study, the understanding assessment, identified the natural and human factors that could have affected the groundwater quality in the BEAR study unit by evaluating statistical correlations between water-quality constituents and potential explanatory factors. The potential explanatory factors evaluated were land use (including density of septic tanks and leaking or formerly leaking underground fuel tanks), site type, aquifer lithology, well construction (well depth and depth to the top-of-perforated interval), elevation, aridity index, groundwater-age distribution, and oxidation-reduction condition (including pH and dissolved oxygen concentration). Results of the statistical evaluations were used to explain the distribution of constituents in groundwater of the BEAR study unit.
In the Bear Valley study area, high and moderate RCs of fluoride were found in sites known to be influenced by hydrothermic conditions or that had high concentrations of fluoride historically. The high RC of arsenic can likely be attributed to desorption of arsenic from aquifer sediments saturated in old groundwater with high pH under reducing conditions. The THMs were detected more frequently at USGS grid sites that were wells, part of a large urban water system, and surrounded by urban land use. Solvents, MTBE, and simazine were all detected more frequently at USGS grid sites that were wells with a greater urban percentage of surrounding land use and that accessed older groundwater than other USGS grid sites. Comparison between the observed and predicted detection frequencies of perchlorate at USGS grid sites indicated that anthropogenic sources could have contributed to low levels of perchlorate in the groundwater of the Bear Valley study area.
In the Lake Arrowhead Watershed study area, high and moderate RCs of radon-222 and uranium can be attributed to older groundwater from the granitic fractured-rock primary aquifer system. Low RCs of THMs were detected at USGS grid sites that were wells and part of small water systems. The similarities between the observed and predicted detection frequencies of perchlorate in samples from USGS grid sites indicated that the source and distribution of perchlorate were most likely attributable to precipitation (rain and snow), with minimal, if any, contribution from anthropogenic sources.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20175043","collaboration":"Prepared in cooperation with the California State Water Resources Control Board","usgsCitation":"Mathany, T.M., and Burton, C.A., 2017, Status and understanding of groundwater quality in the Bear Valley and Lake Arrowhead Watershed Study Unit, 2010: California GAMA Priority Basin Project: U.S. Geological Survey Scientific Investigations Report 2017–5043, 71 p., https://doi.org/10.3133/sir20175043.","productDescription":"xii, 71 p.","onlineOnly":"Y","ipdsId":"IP-051454","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":342654,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2017/5043/coverthb2.jpg"},{"id":342655,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2017/5043/sir20175043.pdf","text":"Report","size":"10 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California GAMA
U.S. Geological Survey
6000 J Street, Placer Hall
Sacramento, California 95819
During two seasonal sampling events in spring (June) and fall (August) of 2015, the U.S. Geological Survey collected benthos (benthic invertebrates) and plankton (zooplankton and phytoplankton) at three sites each in the Waukegan Harbor Area of Concern (AOC) in Illinois and in Burns Harbor-Port of Indiana, a non-AOC comparison site in Indiana. The study was done in cooperation with the U.S. Environmental Protection Agency and the Illinois Department of Natural Resources. Samples were collected concurrently for physical and chemical parameters (specific conductance, temperature, pH, dissolved oxygen, chlorophyll-a, total and volatile suspended solids in water samples; particle size and volatile-on-ignition solids of sediment in dredge samples). The purpose of the study was to assess whether or not aquatic communities at the AOC were degraded in comparison to communities at the non-AOC, which was presumed to be less impaired than the AOC. Benthos were collected by using Hester-Dendy artificial substrate samplers and a Ponar® dredge sampler to collect composited grabs of bottom sediment; zooplankton were collected by using tows from depth to the surface with a 63-micrometer mesh plankton net; phytoplankton were collected by using whole water samples composited from set depth intervals. Aquatic communities at the AOC and the non-AOC were compared by use of univariate statistical analyses with metrics such as taxa richness (number of unique taxa), diversity, and a multimetric Index of Biotic Integrity (IBI, for artificial-substrate samples only) as well as by use of multivariate statistical analyses of taxa relative abundances.
Although benthos communities at Waukegan Harbor AOC were not rated as degraded in comparison to the non-AOC, metrics for zooplankton and phytoplankton communities did show some impairment for the 2015 sampling. Across seasons, benthos richness and diversity were significantly higher and rated as less degraded at the AOC compared to the non-AOC; however, benthos IBIs were not significantly different. Multivariate comparisons revealed that the benthos communities in the AOC and non-AOC were significantly different, but these comparisons do not address current degradation in either harbor. The dominant taxa in dredge samples were oligochaete worms in both harbors, but there were differences in the relative abundances of Dreissena as well as oligochaete and midge taxa. Although zooplankton richness and diversity in the AOC were lower and rated as more degraded in spring, these metrics were rated as less degraded in fall compared to the non-AOC, effectively balancing out so that there was no difference across seasons. Multivariate comparisons also indicated that zooplankton communities in the AOC were significantly different from those in the non-AOC for spring only but not across seasons, possibly because of lower water temperatures in spring at Waukegan Harbor than at the non-AOC site. The spring zooplankton community in Waukegan Harbor was dominated in density and biomass by the rotifer Synchaeta. Across seasons, diatom richness was significantly higher and rated as less degraded in the AOC than the non-AOC because of spring values, whereas soft algae richness was significantly lower and rated as more degraded in the AOC because of fall values. Spring richness of combined phytoplankton (soft algae and diatoms) was significantly higher in the AOC than in the non-AOC. Neither diatom diversity nor soft algae diversity differed significantly between the harbors, but combined phytoplankton diversity across seasons, if replicates were included, was significantly lower and rated as more degraded in the AOC than in the non-AOC. Multivariate tests indicated that the combined phytoplankton communities in the harbors were not significantly different across seasons. Significant differences were not found between harbors for chlorophyll-a, suspended solids, algal densities, or biomass.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20175039","collaboration":"Prepared in cooperation with the Illinois Department of Natural Resources and the U.S. Environmental Protection Agency-Great Lakes National Program Office","usgsCitation":"Scudder Eikenberry, B.C., Templar, H.A., Burns, D.J., Dobrowolski, E.G., and Schmude, K.L., 2017, Comparison of benthos and plankton for Waukegan Harbor Area of Concern, Illinois, and Burns Harbor-Port of Indiana non-Area of Concern, Indiana, in 2015: U.S. Geological Survey Scientific Investigations Report 2017–5039, 29 p., https://doi.org/10.3133/sir20175039.","productDescription":"Report: viii, 29 p.; Data Release","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-077261","costCenters":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"links":[{"id":342062,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7CN7259","text":"USGS data release","description":"USGS data release","linkHelpText":"Benthos and Plankton data for Waukegan Harbor Area of Concern, Illinois, and Burns Harbor-Port of Indiana Non-Area of Concern, Indiana, in 2015"},{"id":342020,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2017/5039/coverthb.jpg"},{"id":342021,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2017/5039/sir20175039.pdf","text":"Report","size":"4.72 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2017-5039"}],"country":"United States","state":"Illinois, Indiana","otherGeospatial":"Burns Harbor-Port of Indiana non-Area of Concern, Waukegon Harbor Area of Concern","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -87.827083,\n 42.374\n ],\n [\n -87.827083,\n 42.355\n ],\n [\n -87.808333,\n 42.355\n ],\n [\n -87.808333,\n 42.374\n ],\n [\n -87.827083,\n 42.374\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -87.163889,\n 41.649\n ],\n [\n -87.144444,\n 41.649\n ],\n [\n -87.144444,\n 41.627778\n ],\n [\n -87.163889,\n 41.627778\n ],\n [\n -87.163889,\n 41.649\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Wisconsin Water Science Center
U.S. Geological Survey
8505 Research Way
Middleton, WI 53562
Increased nutrient and sediment loading in rivers have caused observable changes in algal community composition, and thereby, altered the quality and quantity of food resources available to native freshwater mussels. Our objective was to characterize the relationship between nutrient conditions and mussel food quality and examine the effects on fatty acid composition, growth and survival of juvenile mussels. Juvenile Lampsilis cardium and L. siliquoidea were deployed in cages for 28 d at four riverine and four lacustrine sites in the lower St. Croix River, Minnesota/Wisconsin, USA. Mussel foot tissue and food resources (four seston fractions and surficial sediment) were analyzed for quantitative fatty acid (FA) composition. Green algae were abundant in riverine sites, whereas cyanobacteria were most abundant in the lacustrine sites. Mussel survival was high (95%) for both species. Lampsilis cardium exhibited lower growth relative to L. siliquoidea (p <0.0001), but growth of L. cardium was not significantly different across sites (p = 0.13). In contrast, growth of L. siliquoidea was significantly greater at the most upstream riverine site compared to the lower three lacustrine sites (p = 0.002). In situ growth of Lampsilis siliquoidea was positively related to volatile solids (10 – 32 μm fraction), total phosphorus (<10 and 10 – 32 μm fractions), and select FA in the seston (docosapentaeonic acid, DPA, 22:5n3; 4,7,10,13,16-docosapentaenoic, 22:5n6; arachidonic acid, ARA, 20:4n6; and 24:0 in the <10 and 10 – 32 μm fractions). Our laboratory feeding experiment also indicated high accumulation ratios for 22:5n3, 22:5n6, and 20:4n6 in mussel tissue relative to supplied algal diet. In contrast, growth of L. siliquiodea was negatively related to nearly all FAs in the largest size fraction (i.e., >63 μm) of seston, including the bacterial FAs, and several of the FAs associated with sediments. Reduced mussel growth was observed in L. siliquoidea when the abundance of cyanobacteria exceeded 9% of the total phytoplankton biovolume. Areas dominated by cyanobacteria may not provide sufficient food quality to promote or sustain mussel growth.
","language":"English","publisher":"Public Library of Science","doi":"10.1371/journal.pone.0173419","usgsCitation":"Bartsch, M.R., Bartsch, L., Richardson, W.B., Vallazza, J.M., and Moraska Lafrancois, B., 2017, Effects of food resources on the fatty acid composition, growth and survival of freshwater mussels: PLoS ONE, v. 12, no. 3, e0173419; 26 p., https://doi.org/10.1371/journal.pone.0173419.","productDescription":"e0173419; 26 p.","ipdsId":"IP-080604","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":461682,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0173419","text":"Publisher Index Page"},{"id":338773,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Minnesota, Wisconsin","otherGeospatial":"St. Croix River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -93.328857421875,\n 44.68818283842486\n ],\n [\n -91.4227294921875,\n 44.68818283842486\n ],\n [\n -91.4227294921875,\n 46.426499019253\n ],\n [\n -93.328857421875,\n 46.426499019253\n ],\n [\n -93.328857421875,\n 44.68818283842486\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"12","issue":"3","publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"noUsgsAuthors":false,"publicationDate":"2017-03-07","publicationStatus":"PW","scienceBaseUri":"58de194ce4b02ff32c699c8b","contributors":{"authors":[{"text":"Bartsch, Michelle R. 0000-0002-9571-5564 mbartsch@usgs.gov","orcid":"https://orcid.org/0000-0002-9571-5564","contributorId":149359,"corporation":false,"usgs":true,"family":"Bartsch","given":"Michelle","email":"mbartsch@usgs.gov","middleInitial":"R.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":687345,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bartsch, Lynn A. 0000-0002-1483-4845 lbartsch@usgs.gov","orcid":"https://orcid.org/0000-0002-1483-4845","contributorId":149360,"corporation":false,"usgs":true,"family":"Bartsch","given":"Lynn A.","email":"lbartsch@usgs.gov","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":687346,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Richardson, William B. 0000-0002-7471-4394 wrichardson@usgs.gov","orcid":"https://orcid.org/0000-0002-7471-4394","contributorId":3277,"corporation":false,"usgs":true,"family":"Richardson","given":"William","email":"wrichardson@usgs.gov","middleInitial":"B.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":687347,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Vallazza, Jonathan M. 0000-0003-2367-4887 jvallazza@usgs.gov","orcid":"https://orcid.org/0000-0003-2367-4887","contributorId":149362,"corporation":false,"usgs":true,"family":"Vallazza","given":"Jonathan","email":"jvallazza@usgs.gov","middleInitial":"M.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":687348,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Moraska Lafrancois, Brenda","contributorId":190133,"corporation":false,"usgs":false,"family":"Moraska Lafrancois","given":"Brenda","email":"","affiliations":[],"preferred":false,"id":687349,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70186031,"text":"70186031 - 2017 - Spatial and temporal dynamics of suspended particle characteristics and composition in Navigation Pool 19 of the Upper Mississippi River","interactions":[],"lastModifiedDate":"2017-07-10T16:20:01","indexId":"70186031","displayToPublicDate":"2017-03-30T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3301,"text":"River Research and Applications","active":true,"publicationSubtype":{"id":10}},"title":"Spatial and temporal dynamics of suspended particle characteristics and composition in Navigation Pool 19 of the Upper Mississippi River","docAbstract":"Suspended particles are an essential component of large rivers influencing channel geomorphology, biogeochemical cycling of nutrients, and food web resources. The Upper Mississippi River is a large floodplain river that exhibits pronounced spatiotemporal variation in environmental conditions and biota, providing an ideal environment for investigating dynamics of suspended particles in large river ecosystems. Here we investigated two questions: (i) How do suspended particle characteristics (e.g. size and morphology) vary temporally and spatially? and (ii) What environmental variables have the strongest association with particle characteristics? Water sampling was conducted in June, August, and September of 2013 and 2014 in Navigation Pool 19 of the Upper Mississippi River. A FlowCAM® (Flow Cytometer and Microscope) particle imaging system was used to enumerate and measure particles 53–300 μm in diameter for size and shape characteristics (e.g. volume, elongation, and symmetry). Suspended particle characteristics varied considerably over space and time and were strongly associated with discharge and concentrations of nitrate + nitrite (NO3−) and soluble reactive phosphorus. Particle characteristics in backwaters were distinct from those in other habitats for most of the study period, likely due to reduced hydrologic connectivity and higher biotic production in backwaters. During low discharge, phytoplankton and zooplankton made up relatively greater proportions of the observed particles. Concurrently during low discharge, concentrations of chlorophyll, volatile suspended solids, and total phosphorus were higher. Our results suggest that there are complex interactions among space, time, discharge, and other environmental variables (e.g. water nutrients), which drive suspended particle dynamics in large rivers.
","language":"English","publisher":"Wiley","doi":"10.1002/rra.3131","usgsCitation":"Milde, A.S., Richardson, W.B., Strauss, E.A., Larson, J.H., Vallazza, J.M., and Knights, B.C., 2017, Spatial and temporal dynamics of suspended particle characteristics and composition in Navigation Pool 19 of the Upper Mississippi River: River Research and Applications, v. 33, no. 5, p. 740-752, https://doi.org/10.1002/rra.3131.","productDescription":"13 p.","startPage":"740","endPage":"752","ipdsId":"IP-076602","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":338814,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":343530,"rank":2,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F70Z7250","text":"Spatial and temporal dynamics of suspended particle characteristics and composition in Navigation Pool 19 of the Upper Mississippi River"}],"country":"United 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A.","contributorId":190148,"corporation":false,"usgs":false,"family":"Strauss","given":"Eric","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":687404,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Larson, James H. 0000-0002-6414-9758 jhlarson@usgs.gov","orcid":"https://orcid.org/0000-0002-6414-9758","contributorId":4250,"corporation":false,"usgs":true,"family":"Larson","given":"James","email":"jhlarson@usgs.gov","middleInitial":"H.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":687405,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Vallazza, Jonathan M. 0000-0003-2367-4887 jvallazza@usgs.gov","orcid":"https://orcid.org/0000-0003-2367-4887","contributorId":149362,"corporation":false,"usgs":true,"family":"Vallazza","given":"Jonathan","email":"jvallazza@usgs.gov","middleInitial":"M.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":687406,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Knights, Brent C. 0000-0001-8526-8468 bknights@usgs.gov","orcid":"https://orcid.org/0000-0001-8526-8468","contributorId":2906,"corporation":false,"usgs":true,"family":"Knights","given":"Brent","email":"bknights@usgs.gov","middleInitial":"C.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":687407,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70259478,"text":"70259478 - 2017 - Early postcaldera rhyolite and structural resurgence at Long Valley Caldera, California","interactions":[],"lastModifiedDate":"2024-10-09T15:08:30.497692","indexId":"70259478","displayToPublicDate":"2017-03-20T09:58:20","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2499,"text":"Journal of Volcanology and Geothermal Research","active":true,"publicationSubtype":{"id":10}},"title":"Early postcaldera rhyolite and structural resurgence at Long Valley Caldera, California","docAbstract":"The Southeast Missouri Barite District and the Valles Mines are located in Washington, Jefferson, and St. Francois Counties, Missouri, where barite and lead ore are present together in surficial and near-surface deposits. Lead mining in the area began in the early 1700’s and extended into the early 1900’s. Hand mining of lead in the residuum resulted in widespread pits (also called shafts or diggings), and there was some underground mining of lead in bedrock. By the 1860’s barite was recovered from the residuum by hand mining, also resulting in widespread diggings, but generally not underground mines in bedrock. Mechanized open-pit mining of the residuum for barite began in the 1920’s. Barite production slowed by the 1980’s, and there has not been any barite mining since 1998. Mechanized barite mining resulted in large mined areas and tailings ponds containing waste from barite mills.
The U.S. Environmental Protection Agency (EPA) has determined that lead is present in surface soils in Washington and Jefferson Counties at concentrations exceeding health-based screening levels. Also, elevated concentrations of barium, arsenic, and cadmium have been identified in surface soils, and lead concentrations exceeding the Federal drinking-water standard of 15 micrograms per liter have been identified in private drinking-water wells. Potential sources of these contaminants are wastes associated with barite mining, wastes associated with lead mining, or unmined natural deposits of barium, lead, and other metals. As a first step in helping EPA determine the source of soil and groundwater contamination, the U.S. Geological Survey (USGS), in cooperation with the EPA, investigated the geology and mining history of the Southeast Missouri Barite District and the Valles Mines.
Ore minerals are barite (barium sulfate), galena (lead sulfide), cerussite (lead carbonate), anglesite (lead sulfate), sphalerite (zinc sulfide), smithsonite (zinc carbonate), and chalcopyrite (copper-iron sulfide). The Cambrian Potosi Dolomite is the most important formation for the ore deposits, followed by the Eminence Dolomite. Because galena, sphalerite, and barite are less soluble than dolomite, chemical weathering of the ore-bearing dolomite bedrock resulted in the concentration of ore minerals in the residuum. Most of the barite and lead mining was in the residuum, which averages 10 to 15 feet thick.
Lead mining by French explorers may have begun in 1719 along Old Mines Creek at Cabanage de Renaudiere, which was followed shortly by the discovery of lead and the development of lead mines at Mine Renault (also called Forche a Renault Mine), Old Mines, and at other places along the Big River, Mineral Fork, and Forche a Renault Creek. Lead mining began sometime between 1775 and 1780 at Mine a Breton, the name of which was later changed to Potosi. Other mining areas were developed in the early part of the 19th century, including Fourche a Courtois (Palmer Mines), the French Diggings, and the Richwoods Mines. Zinc became a valuable resource after the Civil War, and the Valles Mines was an important supplier of zinc as well as lead, with at least some production up until the 1920’s. Lead mining declined in the early part of the 20th century as mining in the Old Lead Belt, Mine La Motte, and the Tri-State District expanded.
The earliest lead mines were diggings in the residuum and were round holes (shafts) about 4 feet in diameter dug with pick and shovel about 15–20 feet deep, with drifts dug a short distance laterally from the bottom of the shafts. This mining process was repeated a short distance away until a large area was covered with pits. Some mining in bedrock began by about 1800, with shafts as deep as 170 feet and as much as several hundred feet of lateral drifts.
Smelting of the lead ore to elemental lead was first done using a log furnace, which was inefficient; estimates have been made that only about 50 percent of the lead was recovered, and the remainder was lost to the ashes (slags) and to volatilization. Starting in 1798, ash furnaces were used to smelt the ashes from the log furnaces. These two furnaces were worked in tandem for many years but were gradually replaced by other furnaces, including the Scotch hearth. Estimates of lead recovery as high as 80–90 percent have been made for the Scotch hearth. By the mid-1870’s the air furnace was being used, also with estimated lead recovery as high as 80–90 percent. Zinc furnaces were built when zinc became a valuable commodity, but much of the zinc ore was shipped out of the area, either to a smelter in St. Louis, Missouri, or to other smelters.
The total lead and zinc production from the Southeast Missouri Barite District and the Valles Mines is estimated at 180,000 tons of lead and 60,000 tons of zinc. An estimated 97,000 tons of lead and an estimated 120,000 tons of zinc were lost during smelting. The estimated losses do not include losses at the mine site during mining and preparation for smelting, such as the loss of fine-grained galena during hand cleaning or the discarding of zinc ore before its value was known, for which no estimates are available.
Hand mining for barite in the residuum was active by at least the 1860’s and peaked from 1905 to the 1930’s when several thousand people were engaged in barite mining. Hand mining (diggings) and cleaning of the ore was done in much the same way as earlier lead mining, with the additional use of a rattle box to further clean the barite. Mechanized open-pit mining of old barite diggings began in 1924 to recover barite left behind by hand mining, and washing plants were used to clean the clay from the barite. Hand mining, however, continued to thrive, and washer plants began to close temporarily in 1931; nearly all of the barite produced before 1937 was by hand mining. By the 1940’s, however, all barite mining was mechanized.
Mechanized mining used shovels powered by steam, gasoline, or electricity (and by the 1950’s draglines and front-end loaders) to mine the residuum. The ore was loaded onto rail cars (and by the 1940’s, trucks) for shipment to washer plants. Clay was removed from the barite using a log washer, and a jig was used to concentrate the barite. Overflow from the log washers was waste and went to a mud (tailings) pond. The coarse jig tailings went to tailings piles or were used as railroad ballast and, later, to create roads within the mine pit. Some barite was ground, depending on its final use, and some ground barite was bleached using a hot solution of sulfuric acid to remove impurities such as iron minerals and lead sulfide (galena). An earlier bleaching process used lead-lined tanks.
Large quantities of water were required for milling the barite; some was recirculated water and the remainder came from dammed streams or was pumped from wells. Tailings and wastewater were impounded behind dikes that were built across small valleys and were increased in height as necessary using washer waste and any overburden that had been stripped. In some cases, dikes were built across valleys that had already been mined for barite.
The total production of barite from the Southeast Missouri Barite District and the Valles Mines is estimated to have been about 13.1 million tons. Most of the barite production was from Washington County. Hand mining and processing of barite was inefficient. Estimates of barite recovery range from less than one-fourth to about one-half because pillars between the shafts in the residuum needed to be left unmined for stability. With mechanized mining, large amounts of barite were lost during the milling process. It has been estimated that about 30 percent of the barite was lost and that about two-thirds of the lost barite was fine-grained and was discharged to the tailings ponds. Some galena was lost to the tailings ponds.
A 1972 inventory of tailings ponds by the Missouri Geological Survey identified 67 ponds in the Southeast Missouri Barite District (there are more than this currently documented). Results from samples from four ponds that were drilled were used to estimate that the 67 ponds contained almost 39 million tons (or cubic yards) of tailings averaging about 5 percent barite, for a potential reserve of 1.935 million tons of barite.
It is not known how much lead was removed during barite mining, either by hand or mechanized mining and processing, how much lead was recovered, or how much lead went as fines to the tailing ponds or as coarse material to mine roads or was otherwise lost.
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Rolla, MO 65401
The Priority Basin Project (PBP) of the Groundwater Ambient Monitoring and Assessment (GAMA) program was developed in response to the Groundwater Quality Monitoring Act of 2001 and is being conducted by the U.S. Geological Survey in cooperation with the California State Water Resources Control Board. From 2004 through 2012, the GAMA-PBP collected samples and assessed the quality of groundwater resources that supply public drinking water in 35 study units across the State. Selected sites in each study unit were sampled again approximately 3 years after initial sampling as part of an assessment of temporal trends in water quality by the GAMA-PBP. Twelve of the study units, initially sampled during 2006–11 (initial sampling period) and sampled a second time during 2008–13 (trend sampling period) to assess temporal trends, are the subject of this report.
The initial sampling was designed to provide a spatially unbiased assessment of the quality of untreated groundwater used for public water supplies in the 12 study units. In these study units, 550 sampling sites were selected by using a spatially distributed, randomized, grid-based method to provide spatially unbiased representation of the areas assessed (grid sites, also called “status sites”). After the initial sampling period, 76 of the previously sampled status sites (approximately 10 percent in each study unit) were randomly selected for trend sampling (“trend sites”). The 12 study units sampled both during the initial sampling and during the trend sampling period were distributed among 6 hydrogeologic provinces: Coastal (Northern and Southern), Transverse Ranges and Selected Peninsular Ranges, Klamath, Modoc Plateau and Cascades, and Sierra Nevada Hydrogeologic Provinces. For the purposes of this trend report, the six hydrogeologic provinces were grouped into two hydrogeologic regions based on location: Coastal and Mountain.
The groundwater samples were analyzed for a number of synthetic organic constituents (volatile organic compounds, pesticides, and pesticide degradates), constituents of special interest (perchlorate and 1,2,3-trichloropropane), and natural inorganic constituents (nutrients, major and minor ions, and trace elements). Isotopic tracers (tritium, carbon-14, and stable isotopes of hydrogen and oxygen in water) also were measured to help identify processes affecting groundwater quality and the sources and ages of the sampled groundwater. More than 200 constituents and water-quality indicators were measured during the trend sampling period.
Quality-control samples (blanks, replicates, matrix-spikes, and surrogate compounds) were collected at about one-third of the trend sites, and the results for these samples were used to evaluate the quality of the data for the groundwater samples. On the basis of detections in laboratory and field blank samples collected by GAMA-PBP study units, including the 12 study units presented here, reporting levels for some groundwater results were adjusted in this report. Differences between replicate samples were mostly within acceptable ranges, indicating low variability in analytical results. Matrix-spike recoveries were largely within the acceptable range (70 to 130 percent).
This study did not attempt to evaluate the quality of water delivered to consumers. After withdrawal, groundwater used for drinking water typically is treated, disinfected, and blended with other waters to achieve acceptable water quality. The comparison benchmarks used in this report apply to treated water that is served to the consumer, not to untreated groundwater. To provide some context for the results, however, concentrations of constituents measured in these groundwater samples were compared with benchmarks established by the U.S. Environmental Protection Agency and the State of California. Comparisons between data collected for this study and benchmarks for drinking water are for illustrative purposes only and are not indicative of compliance or non-compliance with those benchmarks.
Most organic constituents that were detected in groundwater samples from the trend sites were found at concentrations less than health-based benchmarks. One volatile organic compound—perchloroethene—was detected at a concentration greater than the health-based benchmark in samples from one trend site during the initial and trend sampling periods. Chloroform was detected in at least 10 percent of the samples at trend sites in both sampling periods. Methyl tert-butyl ether was detected in samples from more than 10 percent of the trend sites during the initial sampling period. No pesticide or pesticide degradate was detected in greater than 10 percent of the samples from trend sites or at concentrations greater than their health-based benchmarks during either sampling period. Nutrients were not detected at concentrations greater than their health-based benchmarks during either sampling period.
Most detections of major ions and trace elements in samples from trend sites were less than health-based benchmarks during both sampling periods. Arsenic and boron each were detected at concentrations greater than the health-based benchmark in samples from four trend sites during the initial and trend sampling periods. Molybdenum was detected in samples from four trend sites at concentrations greater than the health-based benchmark during both sampling periods. Samples from two of these trend sites had similar molybdenum concentrations, and two had substantially different concentrations during the initial and trend sampling periods. Uranium was detected at a concentration greater than the health-based benchmark only at two trend sites.
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\"}}]}","contact":"Director, California Water Science Center
U.S. Geological Survey
6000 J Street, Placer Hall
Sacramento, California 95819
http://ca.water.usgs.gov
Groundwater is a major source of drinking water in Lycoming County and adjacent counties in north-central and northeastern Pennsylvania, which are largely forested and rural and are currently undergoing development for hydrocarbon gases. Water-quality data are needed for assessing the natural characteristics of the groundwater resource and the potential effects from energy and mineral extraction, timber harvesting, agriculture, sewage and septic systems, and other human influences.
This report, prepared in cooperation with Lycoming County, presents analytical data for groundwater samples from 75 domestic wells sampled throughout Lycoming County in June, July, and August 2014. The samples were collected using existing pumps and plumbing prior to any treatment and analyzed for physical and chemical characteristics, including nutrients, major ions, metals and trace elements, volatile organic compounds, gross-alpha particle and gross beta-particle activity, uranium, and dissolved gases, including methane and radon-222.
Results indicate groundwater quality generally met most drinking-water standards, but that some samples exceeded primary or secondary maximum contaminant levels (MCLs) for arsenic, iron, manganese, total dissolved solids (TDS), chloride, pH, bacteria, or radon-222. Arsenic concentrations were higher than the MCL of 10 micrograms per liter (µg/L) in 9 of the 75 (12 percent) well-water samples, with concentrations as high as 23.6 μg/L; arsenic concentrations were higher than the health advisory level (HAL) of 2 μg/L in 23 samples (31 percent). Total iron concentrations exceeded the secondary maximum contaminant level (SMCL) of 300 μg/L in 20 of the 75 samples. Total manganese concentrations exceeded the SMCL of 50 μg/L in 20 samples and the HAL of 300 μg/L in 2 of those samples. Three samples had chloride concentrations that exceeded the SMCL of 250 milligrams per liter (mg/L); two of those samples exceeded the SMCL of 500 mg/L for TDS. The pH ranged from 5.3 to 9.15 and did not meet the SMCL range of 6.5 to 8.5 in 22 samples, with 17 samples having a pH less than 6.5 and 8 samples having pH greater than 8.5. Generally, the samples that had elevated TDS, chloride, or arsenic concentrations had high pH.
Total coliform bacteria were detected in 39 of 75 samples (52 percent), with Escherichia coli detected in 10 of those 39 samples. Radon-222 activities ranged from non-detect to 7,420 picocuries per liter (pCi/L), with a median of 863 pCi/L, and exceeded the proposed drinking-water standard of 300 pCi/L in 50 (67 percent) of the 75 samples; radon-222 activities were higher than the alternative proposed standard of 4,000 pCi/L in 3 samples.
Water from 15 of 75 (20 percent) wells had concentrations of methane greater than the reporting level of 0.01 mg/L; detectable methane concentrations ranged from 0.04 to 16.8 mg/L. Two samples had methane concentrations (13.1 and 16.8 mg/L) exceeding the action level of 7 mg/L. Low levels of ethane (up to 0.12 mg/L) were present in the five samples with the highest methane concentrations (near or above 1 mg/L) that were analyzed for hydrocarbon compounds and isotopic composition. The isotopic composition of methane in four of these groundwater samples, from the Catskill and Lock Haven Formations and the Hamilton Group, have sample carbon isotopic ratio delta values (carbon-13/carbon-12) ranging from –42.36 to –36.08 parts per thousand (‰) and hydrogen isotopic ratio delta values (deuterium/protium) ranging from –212.0 to –188.4 ‰, which are consistent with the isotopic compositions reported for mud-gas logging samples from these geologic units and a thermogenic source of the methane. However, the isotopic composition and ratios of methane to ethane in a fifth sample indicate the methane in that sample may be of microbial origin that subsequently underwent oxidation. The fifth sample had the highest concentration of methane, 16.8 mg/L, with an carbon isotopic ratio delta values of -50.59 ‰ and a hydrogen isotopic ratio delta values of -209.7 ‰.
The six well-water samples with the highest methane concentrations also had among the highest pH values (8.25 to 9.15) and elevated concentrations of sodium, lithium, boron, fluoride, arsenic, and bromide. Relatively elevated concentrations of some other constituents, such as barium, strontium, and chloride, commonly were present in, but not limited to, those well-water samples with elevated methane.
Three of the six groundwater samples with the highest methane concentrations had chloride/bromide ratios that indicate mixing with a small amount of brine (0.02 percent or less) similar in composition to those reported at undetermined depth below the freshwater aquifer and for gas and oil well brines in Pennsylvania. The sample with the highest methane concentration and most other samples with low methane concentrations (less than about 1 mg/L) have chloride/bromide ratios that indicate predominantly anthropogenic sources of chloride, such as road-deicing salt, septic systems, and (or) animal waste. Brines that are naturally present may originate from deeper parts of the aquifer system, while anthropogenic sources are more likely to affect shallow groundwater because they occur on or near the land-surface.
The spatial distribution of groundwater compositions generally indicate that (1) uplands along the western border of Lycoming County usually have dilute, slightly acidic oxygenated, calcium-bicarbonate type waters; (2) intermediate altitudes or areas of carbonate bedrock usually have water of near neutral pH, with highest amounts of hardness (calcium and magnesium); (3) stream valleys, low elevations where groundwater may be discharging, and deep wells in uplands usually have water with pH values greater than 8 and highest arsenic, sodium, lithium, bromide concentrations. Geochemical modeling indicated that for samples with elevated pH, sodium, lithium, bromide, and alkalinity, the water chemistry could have resulted by dissolution of calcite (calcium carbonate) combined with cation-exchange and mixing with a small amount of brine. Through cation-exchange reactions between water and bedrock, which are equivalent to processes in a water softener, calcium ions released by calcite dissolution are exchanged for sodium ions on clay minerals. Thus, the assessment of groundwater quality in Lycoming County indicates groundwater is generally of good quality, but various parts of Lycoming County can have groundwater with low to moderate concentrations of methane and other constituents that appear in naturally present brine and produced waters from gas and oil wells at high concentrations.\"
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20165143","collaboration":"Prepared in cooperation with the County of Lycoming, Pennsylvania","usgsCitation":"Gross, E.L., and Cravotta, C.A., III, 2017, Groundwater quality for 75 domestic wells in Lycoming County, Pennsylvania, 2014: U.S. Geological Survey Scientific Investigations Report 2016–5143, 74 p., https://doi.org/10.3133/sir20165143.","productDescription":"Report: xi, 74 p.; Appendixes 1-2","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-076071","costCenters":[{"id":532,"text":"Pennsylvania Water Science Center","active":true,"usgs":true}],"links":[{"id":336804,"rank":4,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2016/5143/sir20165143_appendix2.xlsx","text":"Appendix 2 - Table 2-1 - ","size":"27.3 KB","linkFileType":{"id":3,"text":"xlsx"},"description":"SIR 2016-5143","linkHelpText":"Spearman rank correlation coefficient (r) matrix 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Excess ice is widespread throughout the martian mid-latitudes, particularly in Arcadia Planitia, where double-layer ejecta (DLE) craters also tend to be abundant. In this region, we observe the presence of thermokarstically-expanded secondary craters that likely form from impacts that destabilize a subsurface layer of excess ice, which subsequently sublimates. The presence of these expanded craters shows that excess ice is still preserved within the adjacent terrain. Here, we focus on a 15-km DLE crater that contains abundant superposed expanded craters in order to study the distribution of subsurface volatiles both at the time when the secondary craters formed and, by extension, remaining today. To do this, we measure the size distribution of the superposed expanded craters and use topographic data to calculate crater volumes as a proxy for the volumes of ice lost to sublimation during the expansion process. The inner ejecta layer contains craters that appear to have undergone more expansion, suggesting that excess ice was most abundant in that region. However, both of the ejecta layers had more expanded craters than the surrounding terrain. We extrapolate that the total volume of ice remaining within the entire ejecta deposit is as much as 74 km3 or more. The variation in ice content between the ejecta layers could be the result of (1) volatile preservation from the formation of the DLE crater, (2) post-impact deposition in the form of ice lenses; or (3) preferential accumulation or preservation of subsequent snowfall. We have ruled out (2) as the primary mode for ice deposition in this location based on inconsistencies with our observations, though it may operate in concert with other processes. Although none of the existing DLE formation hypotheses are completely consistent with our observations, which may merit a new or modified mechanism, we can conclude that DLE craters contain a significant quantity of excess ice today.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.icarus.2016.11.031","usgsCitation":"Viola, D., McEwen, A.S., Dundas, C.M., and Byrne, S., 2017, Subsurface volatile content of martian double-layer ejecta (DLE) craters: Icarus, v. 284, p. 325-343, https://doi.org/10.1016/j.icarus.2016.11.031.","productDescription":"19 p.","startPage":"325","endPage":"343","ipdsId":"IP-077824","costCenters":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"links":[{"id":342216,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"Mars","volume":"284","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"593910abe4b0764e6c5e8850","contributors":{"authors":[{"text":"Viola, Donna","contributorId":127526,"corporation":false,"usgs":false,"family":"Viola","given":"Donna","email":"","affiliations":[{"id":7042,"text":"University of Arizona","active":true,"usgs":false}],"preferred":false,"id":697430,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"McEwen, Alfred S.","contributorId":61657,"corporation":false,"usgs":false,"family":"McEwen","given":"Alfred","email":"","middleInitial":"S.","affiliations":[{"id":7042,"text":"University of Arizona","active":true,"usgs":false}],"preferred":false,"id":697431,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Dundas, Colin M. 0000-0003-2343-7224 cdundas@usgs.gov","orcid":"https://orcid.org/0000-0003-2343-7224","contributorId":2937,"corporation":false,"usgs":true,"family":"Dundas","given":"Colin","email":"cdundas@usgs.gov","middleInitial":"M.","affiliations":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"preferred":true,"id":697429,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Byrne, Shane","contributorId":192609,"corporation":false,"usgs":false,"family":"Byrne","given":"Shane","email":"","affiliations":[],"preferred":false,"id":697432,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70182459,"text":"70182459 - 2017 - Environmental signatures and effects of an oil and gas wastewater spill in the Williston Basin, North Dakota","interactions":[],"lastModifiedDate":"2017-04-25T16:37:44","indexId":"70182459","displayToPublicDate":"2017-02-23T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3352,"text":"Science of the Total Environment","active":true,"publicationSubtype":{"id":10}},"title":"Environmental signatures and effects of an oil and gas wastewater spill in the Williston Basin, North Dakota","docAbstract":"Wastewaters from oil and gas development pose largely unknown risks to environmental resources. In January 2015, 11.4 M L (million liters) of wastewater (300 g/L TDS) from oil production in the Williston Basin was reported to have leaked from a pipeline, spilling into Blacktail Creek, North Dakota. Geochemical and biological samples were collected in February and June 2015 to identify geochemical signatures of spilled wastewaters as well as biological responses along a 44-km river reach. February water samples had elevated chloride (1030 mg/L) and bromide (7.8 mg/L) downstream from the spill, compared to upstream levels (11 mg/L and < 0.4 mg/L, respectively). Lithium (0.25 mg/L), boron (1.75 mg/L) and strontium (7.1 mg/L) were present downstream at 5–10 times upstream concentrations. Light hydrocarbon measurements indicated a persistent thermogenic source of methane in the stream. Semi-volatile hydrocarbons indicative of oil were not detected in filtered samples but low levels, including tetramethylbenzenes and di-methylnaphthalenes, were detected in unfiltered water samples downstream from the spill. Labile sediment-bound barium and strontium concentrations (June 2015) were higher downstream from the Spill Site. Radium activities in sediment downstream from the Spill Site were up to 15 times the upstream activities and, combined with Sr isotope ratios, suggest contributions from the pipeline fluid and support the conclusion that elevated concentrations in Blacktail Creek water are from the leaking pipeline. Results from June 2015 demonstrate the persistence of wastewater effects in Blacktail Creek several months after remediation efforts started. Aquatic health effects were observed in June 2015; fish bioassays showed only 2.5% survival at 7.1 km downstream from the spill compared to 89% at the upstream reference site. Additional potential biological impacts were indicated by estrogenic inhibition in downstream waters. Our findings demonstrate that environmental signatures from wastewater spills are persistent and create the potential for long-term environmental health effects.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.scitotenv.2016.11.157","usgsCitation":"Cozzarelli, I.M., Skalak, K., Kent, D., Engle, M.A., Benthem, A.J., Mumford, A.C., Haase, K.B., Farag, A.M., Harper, D., Nagel, S.C., Iwanowicz, L., Orem, W.H., Akob, D.M., Jaeschke, J.B., Galloway, J.M., Kohler, M., Stoliker, D., and Jolly, G., 2017, Environmental signatures and effects of an oil and gas wastewater spill in the Williston Basin, North Dakota: Science of the Total Environment, v. 579, p. 1781-1793, https://doi.org/10.1016/j.scitotenv.2016.11.157.","productDescription":"13 p.","startPage":"1781","endPage":"1793","ipdsId":"IP-080154","costCenters":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"links":[{"id":461719,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.scitotenv.2016.11.157","text":"Publisher Index Page"},{"id":336062,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"North Dakota","otherGeospatial":"Williston Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -104.03778076171874,\n 48.09275716032736\n ],\n [\n -103.282470703125,\n 48.09275716032736\n ],\n [\n -103.282470703125,\n 48.963990624864145\n ],\n [\n -104.03778076171874,\n 48.963990624864145\n ],\n [\n -104.03778076171874,\n 48.09275716032736\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"579","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"58b002c4e4b01ccd54fb27bd","chorus":{"doi":"10.1016/j.scitotenv.2016.11.157","url":"http://dx.doi.org/10.1016/j.scitotenv.2016.11.157","publisher":"Elsevier BV","authors":"Cozzarelli I.M., Skalak K.J., Kent D.B., Engle M.A., Benthem A., Mumford A.C., Haase K., Farag A., Harper D., Nagel S.C., Iwanowicz L.R., Orem W.H., Akob D.M., Jaeschke J.B., Galloway J., Kohler M., Stoliker D.L., Jolly G.D.","journalName":"Science of The Total Environment","publicationDate":"2/2017","publiclyAccessibleDate":"12/1/2016"},"contributors":{"authors":[{"text":"Cozzarelli, Isabelle M. 0000-0002-5123-1007 icozzare@usgs.gov","orcid":"https://orcid.org/0000-0002-5123-1007","contributorId":1693,"corporation":false,"usgs":true,"family":"Cozzarelli","given":"Isabelle","email":"icozzare@usgs.gov","middleInitial":"M.","affiliations":[{"id":436,"text":"National Research Program - 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The study was designed to provide a statistically unbiased, spatially distributed assessment of untreated groundwater quality in the shallow aquifer systems of the Madera, Chowchilla, and Kings subbasins of the San Joaquin Valley groundwater basin. The shallow aquifer system corresponds to the part of the aquifer system generally used by domestic wells and is shallower than the part of the aquifer system generally used by public-supply wells. This report presents the data collected for the study and a brief preliminary description of the results.
Groundwater samples were collected from 77 wells and were analyzed for organic constituents, inorganic constituents, selected isotopic and age-dating tracers, and microbial indicators. Most of the wells sampled for this study were private domestic wells. Unlike groundwater from public-supply wells, the groundwater from private domestic wells is not regulated for quality in California and is rarely analyzed for water-quality constituents. To provide context for the sampling results, however, concentrations of constituents measured in the untreated groundwater were compared with regulatory and non-regulatory benchmarks established for drinking-water quality by the U.S. Environmental Protection Agency, the State of California, and the U.S. Geological Survey.
Of the 319 organic constituents assessed in this study (90 volatile organic compounds and 229 pesticides and pesticide degradates), 17 volatile organic compounds and 23 pesticides and pesticide degradates were detected in groundwater samples; concentrations of all but 2 were less than the respective benchmarks. The fumigants 1,2-dibromo-3-chloropropane (DBCP) and 1,2-dibromoethane (EDB) were detected at concentrations above their respective regulatory benchmarks in samples from a total of four wells.
Most detections of inorganic constituents were at concentrations or activities less than the respective benchmark levels. Five inorganic constituents were detected in groundwater samples from one or more wells at concentrations or activities greater than their respective regulatory, health-based benchmarks: arsenic, uranium, nitrate, adjusted gross alpha particle activity, and gross beta particle activity. Four inorganic constituents were detected in samples from one or more wells at concentrations or activities greater than their respective non-regulatory, health-based benchmarks: manganese, molybdenum, vanadium, and radon-222. Three inorganic constituents were detected in groundwater samples from one or more wells at concentrations greater than their respective non-regulatory, aesthetic-based benchmarks: iron, sulfate, and total dissolved solids.
Microbial indicators (Escherichia coli, total coliform, and enterococci) were analyzed for presence or absence. The presence of Escherichia coli (E. coli) was not detected; the presence of total coliform was detected in samples from 10 of the 72 grid wells for which it was analyzed, and the presence of enterococci was detected in samples from 5 of the 73 grid wells analyzed.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds1019","collaboration":"Prepared in cooperation with the California State Water Resources Control Board","usgsCitation":"Shelton, J.L., and Fram, M.S., 2017, Groundwater-quality data for the Madera/Chowchilla–Kings shallow aquifer study unit, 2013–14: Results from the California GAMA Program: U.S. Geological Survey Data Series 1019, 115 p., https://doi.org/10.3133/ds1019.","productDescription":"Report: viii, 115 p.","numberOfPages":"128","onlineOnly":"N","ipdsId":"IP-056132","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":334554,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/ds/1019/ds1019.pdf","text":"Report","size":"3.67 MB","linkFileType":{"id":1,"text":"pdf"},"description":"DS 1019"},{"id":334553,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/ds/1019/coverthb2.jpg"}],"country":"United States","state":"California","otherGeospatial":"Madera/Chowchilla-Kings Shallow Aquifer study unit","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -120.666667,\n 37.416667\n ],\n [\n -120.666667,\n 36\n ],\n [\n -119.166667,\n 36\n ],\n [\n -119.166667,\n 37.416667\n ],\n [\n -120.666667,\n 37.416667\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, California Water Science Center
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6000 J Street, Placer Hall
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Previously reported whole-rock δ18O values (5.6–7.8‰) for primitive quaternary mafic lavas from the southernmost Cascades (SMC) are often elevated (up to 1‰) relative to δ18O values expected for mafic magmas in equilibrium with mantle peridotite. Olivine, clinopyroxene, and plagioclase crystals were separated from 29 geochemically well-characterized mafic lavas for δ18O measurements by laser fluorination to assess modification of the mantle sources by ancient and modern subducted components. Oxygen isotope values of olivine phenocrysts in calc-alkaline lavas and contemporaneous high alumina olivine tholeiitic (HAOT) lavas generally exceed depleted mantle olivine values (~4.9–5.3‰). Modern addition of up to 6 wt% slab-derived fluid from Gorda serpentinized peridotite dehydration (~15‰) or chlorite dehydration (~10‰) within the serpentinized peridotite can provide the 18O enrichment detected in olivine phenocrysts (δ18Oolivine = 5.3–6.3‰) in calc-alkaline mafic lavas, and elevate 18O in overlying mantle lithosphere, as well. Specifically, although HAOT δ18Oolivine values (5.5–5.7‰) may reflect partial melting in heterogeneous 18O enriched mantle source domains that developed during multiple subduction events associated with terrane accretion (e.g., <1 wt% of ~15‰ materials), an additional 18O enrichment of up to 2 wt% of 10–15‰ slab-derived hydrous fluids might be accommodated. The calc-alkaline primitive magmas appear to have experienced a continuous range of open system processes, which operate in the mantle and during rapid magma ascent to eruption, and occasionally post quench. Textural relationships and geochemistry of these lava samples are consistent with blends of mafic phenocrysts and degassed melts in varying states of 18O disequilibrium. In lenses of accumulated melt within peridotite near the base of the crust, coexisting olivine and clinopyroxene δ18O values probably are not at isotopic equilibrium because fluids introduced into the system perturbed the δ18Omelt values. A “sudden” melt extraction event interrupts 18O equilibration in phenocrysts and poorly mixed melt(s). Rapid ascent of volatile oversaturated primitive mafic magma through the crust appears to be accompanied by devolatilization and crystallization of anorthite-rich plagioclase with elevated δ18Oplag values. The (Sr/P)N values for the whole rock geochemistry are consistent with a 87Sr/86Sr ~0.7027 slab-derived fluid addition into the infertile peridotite source of magmas, and melt devolatilization is recorded in the mixture of disequilibrium δ18O values for the constituent phases of lavas. Morbidity of the Gorda Plate as it undergoes intense deformation from the spreading ridge to the trench is likely a key factor to developing the carrying capacity of hydrous fluids and mineral phases in the slab subducting into the SMC mantle.
","language":"English","publisher":"Mineralogical Society of America","doi":"10.2138/am-2017-5588","usgsCitation":"Underwood, S.J., and Clynne, M.A., 2017, Oxygen isotope geochemistry of mafic phenocrysts in primitive mafic lavas from the southernmost Cascade Range, California: American Mineralogist, v. 102, no. 2, p. 251-261, https://doi.org/10.2138/am-2017-5588.","productDescription":"11 p.","startPage":"251","endPage":"261","ipdsId":"IP-075965","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":352601,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Cascade Range","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.4920654296875,\n 39.9434364619742\n ],\n [\n -120.794677734375,\n 39.9434364619742\n ],\n [\n -120.794677734375,\n 40.990264773996884\n ],\n [\n -122.4920654296875,\n 40.990264773996884\n ],\n [\n -122.4920654296875,\n 39.9434364619742\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"102","issue":"2","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2017-02-01","publicationStatus":"PW","scienceBaseUri":"5afee8d3e4b0da30c1bfc4be","contributors":{"authors":[{"text":"Underwood, Sandra J.","contributorId":192684,"corporation":false,"usgs":false,"family":"Underwood","given":"Sandra","email":"","middleInitial":"J.","affiliations":[{"id":13628,"text":"Department of Earth Sciences, P.O. Box 173480, Montana State University, Bozeman, MT, USA. 59717.","active":true,"usgs":false}],"preferred":false,"id":697361,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Clynne, Michael A. 0000-0002-4220-2968 mclynne@usgs.gov","orcid":"https://orcid.org/0000-0002-4220-2968","contributorId":2032,"corporation":false,"usgs":true,"family":"Clynne","given":"Michael","email":"mclynne@usgs.gov","middleInitial":"A.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":697360,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ]}