Coal combustion, one of the principal energy sources of electricity in the United States, produces over 100 million tons of coal combustion products (CCPs) per year in the U.S. The reuse and disposal of CCPs has the potential to release toxic trace elements, including cadmium (Cd), into the environment. In this study, we investigated CCPs, including bottom ash (BA), economizer fly ash (EFA), and fly ash (FA), as well as feed coal (FC) and pulverized coal (PC) collected from two U.S. coal-fired power plants in New Mexico and Ohio with different coal supplies. The New Mexico plant uses high volatile C bituminous, low-sulfur coals mined from the San Juan Basin (Cretaceous Fruitland Formation) and the Ohio plant uses high volatile A bituminous, high-sulfur central Appalachian Basin coals (Upper Pennsylvanian Monongahela Formation). Mineralogical and elemental analysis showed that these CCP samples consist of ∼70% amorphous Al-Si-rich glasses and ∼30% mineral phases of quartz (SiO2) and mullite (Ai6Si2O13). The Cd isotope compositions (δ114Cd, normalized to NIST Cd standard 3108) of FA and EFA samples (ranging from −0.51 to +0.47‰) are distinctively heavier than those of BA samples (−0.75 to −0.52‰) in both power plants. We interpret this Cd isotope difference as a result of Cd condensation from the gas phase during flue gas cooling, instead of evaporation of Cd phase during coal combustion. Cd condensation is the main process to generate the isotopically heavy Cd signatures that preferentially partition on the fine FA particles. We also investigated Cd isotope compositions in different leachate products from a series of batch-leaching experiments with these CCPs, using diluted acetic acid, hydroxyl ammonium chloride, hydrogen peroxide followed by ammonium acetate, and 5% nitric acid, as a possible means to identify CCP-released Cd in the environment. Unusually and significantly heavier Cd isotope compositions were observed in each leachate of FA samples (+1.10 to +7.09‰), which fall far outside from the range of Cd isotope ratios observed in natural soils and rocks, but less so for the EFA samples (−0.43 to +1.18‰). Such an observation is consistent with the interpretation that isotopically heavy Cd preferentially partitions on the fine FA particles after coal combustion and is readily to be released during these leaching experiments. This study demonstrates that high-temperature coal combustion can lead to a very large degree of fractionation of Cd isotopes that can be used as a unique tracer for identifying anthropogenic metal inputs in the environment. The major Cd isotope fractionation process occurs as the Cd gas phase condenses on fine FA particles during the flue gas cooling stage after coal combustion.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.apgeochem.2018.06.007","usgsCitation":"Fouskas, F., Lin, M., Engle, M.A., Ruppert, L.F., Geboy, N., and Costa, M.A., 2018, Cadmium isotope fractionation during coal combustion: Insights from two U.S. coal-fired power plants: Applied Geochemistry, v. 96, p. 100-112, https://doi.org/10.1016/j.apgeochem.2018.06.007.","productDescription":"13 p.","startPage":"100","endPage":"112","ipdsId":"IP-087791","costCenters":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":468576,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.apgeochem.2018.06.007","text":"Publisher Index Page"},{"id":369496,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"New Mexico, Ohio","volume":"96","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Fouskas, Fotio","contributorId":220837,"corporation":false,"usgs":false,"family":"Fouskas","given":"Fotio","email":"","affiliations":[],"preferred":false,"id":775910,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lin, Ma","contributorId":57896,"corporation":false,"usgs":true,"family":"Lin","given":"Ma","email":"","affiliations":[],"preferred":false,"id":775911,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Engle, Mark A. 0000-0001-5258-7374 engle@usgs.gov","orcid":"https://orcid.org/0000-0001-5258-7374","contributorId":584,"corporation":false,"usgs":true,"family":"Engle","given":"Mark","email":"engle@usgs.gov","middleInitial":"A.","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":775912,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ruppert, Leslie F. 0000-0002-7453-1061 lruppert@usgs.gov","orcid":"https://orcid.org/0000-0002-7453-1061","contributorId":660,"corporation":false,"usgs":true,"family":"Ruppert","given":"Leslie","email":"lruppert@usgs.gov","middleInitial":"F.","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true},{"id":245,"text":"Eastern Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":775913,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Geboy, Nicholas J. ngeboy@usgs.gov","contributorId":3860,"corporation":false,"usgs":true,"family":"Geboy","given":"Nicholas J.","email":"ngeboy@usgs.gov","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":775914,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Costa, Matthew A.","contributorId":220838,"corporation":false,"usgs":false,"family":"Costa","given":"Matthew","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":775915,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70196994,"text":"ds1087 - 2018 - Groundwater-quality and select quality-control data from the National Water-Quality Assessment Project, January through December 2015, and previously unpublished data from 2013 to 2014","interactions":[],"lastModifiedDate":"2018-07-03T12:45:49","indexId":"ds1087","displayToPublicDate":"2018-07-03T00:00:00","publicationYear":"2018","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":"1087","title":"Groundwater-quality and select quality-control data from the National Water-Quality Assessment Project, January through December 2015, and previously unpublished data from 2013 to 2014","docAbstract":"Groundwater-quality data were collected from 502 wells as part of the National Water-Quality Assessment Project of the U.S. Geological Survey National Water-Quality Program and are included in this report. Most of the wells (500) were sampled from January through December 2015, and 2 of them were sampled in 2013. The data were collected from five 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; enhanced trends networks, which are used to evaluate the time scales during which groundwater quality changes; and vertical flow-path study networks, which are used to evaluate changes in groundwater quality from shallow to deeper depths. 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. Some data from environmental samples collected in 2013 and quality-control samples collected in 2014 also are included in the associated data release; these data are associated with networks described in this report and have not been published previously.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds1087","usgsCitation":"Arnold, T.L., Bexfield, L.M., Musgrove, M., Stackelberg, P.E., Lindsey, B.D., Kingsbury, J.A., Kulongoski, J.T., and Belitz, K., 2018, Groundwater-quality and select quality-control data from the National Water-Quality Assessment Project, January through December 2015, and previously unpublished data from 2013 to 2014: U.S. Geological Survey Data Series 1087, 68 p., https://doi.org/10.3133/ds1087.","productDescription":"Report: ix, 67 p.; Data Release","numberOfPages":"82","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-091701","costCenters":[{"id":35680,"text":"Illinois-Iowa-Missouri Water Science Center","active":true,"usgs":true}],"links":[{"id":355481,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/ds/1087/coverthb.jpg"},{"id":355482,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/ds/1087/ds1087.pdf","text":"Report","size":"16.3 MB","linkFileType":{"id":1,"text":"pdf"},"description":"DS 1087"},{"id":355483,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7XK8DHK","text":"USGS data release","description":"USGS Data Release","linkHelpText":"Datasets from Groundwater-Quality and Select Quality-Control Data from the National Water-Quality Assessment Project, January through December 2015 and Previously Unpublished Data from 2013–2014"}],"country":"United States","contact":"Director, Central Midwest Water Science Center
U.S. Geological Survey
405 N. Goodwin
Urbana, IL 61801
Sustaining the quality of the Nation’s water resources and the health of our diverse ecosystems depends on the availability of sound water-resources data and information to develop effective, science-based policies. Effective management of water resources also brings more certainty and efficiency to important economic sectors. Taken together, these actions lead to immediate and longterm economic, social, and environmental benefits that make a difference to the lives of the almost 400 million people projected to live in the United States by 2050.
In 1991, Congress established the U.S. Geological Survey National Water-Quality Assessment (NAWQA) to address where, when, why, and how the Nation’s water quality has changed, or is likely to change in the future, in response to human activities and natural factors. Since then, NAWQA has been a leading source of scientific data and knowledge used by national, regional, state, and local agencies to develop science-based policies and management strategies to improve and protect water resources used for drinking water, recreation, irrigation, energy development, and ecosystem needs. Plans for the third decade of NAWQA (2013–23) address priority water-quality issues and science needs identified by NAWQA stakeholders, such as the Advisory Committee on Water Information and the National Research Council, and are designed to meet increasing challenges related to population growth, increasing needs for clean water, and changing land-use and weather patterns.
This report is one of a series of publications, The Quality of Our Nation’s Waters, which describes major findings of the NAWQA Project on water-quality issues of regional and national concern and provides science-based information for assessing and managing the quality of our groundwater resources. Other reports in this series focus on occurrence and distribution of nutrients, pesticides, and volatile organic compounds in streams and groundwater, the effects of contaminants and stream-flow alteration on the condition of aquatic communities in streams, and on the quality of groundwater from private domestic and public supply wells. Each reports builds toward a more comprehensive understanding of the quality of regional and national water resources. All NAWQA reports are available online (https://water.usgs.gov/nawqa/bib/).
We hope this publication will provide you with insights and information to meet your water-resource needs and will foster increased citizen awareness and involvement in the protection and restoration of our Nation’s waters. The information in this report is intended primarily for those interested or involved in resource management and protection, conservation, regulation, and policymaking at the regional and national levels.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/cir1433","collaboration":"National Water-Quality ProgramNational Water-Quality Program
U.S. Geological Survey
413 National Center
12201 Sunrise Valley Drive
Reston, VA 20192
Groundwater quality in the approximately 7,820-square-kilometer (km2) Monterey-Salinas Shallow Aquifer (MS-SA) study unit was investigated from October 2012 to May 2013 as part of the second phase of the Priority Basin Project of the Groundwater Ambient Monitoring and Assessment (GAMA) Program. The study unit is in the central coast region of California in the counties of Santa Cruz, Monterey, and San Luis Obispo. The GAMA Priority Basin Project is being conducted by the California State Water Resources Control Board in cooperation with the U.S. Geological Survey and the Lawrence Livermore National Laboratory.
The MS-SA study was designed to provide a statistically robust assessment of untreated-groundwater quality in the shallow aquifer systems. The assessment was based on water-quality samples collected by the U.S. Geological Survey from 100 groundwater sites and 70 household tap sites, along with ancillary data such as land use and well-construction information. The shallow aquifer systems were defined by the depth interval of wells associated with domestic supply. The MS-SA study unit consisted of four study areas—Santa Cruz (210 km2), Pajaro Valley (360 km2), Salinas Valley (2,000 km2), and Highlands (5,250 km2).
This study had two primary components: the status assessment and the understanding assessment. The first primary component of this study—the status assessment—assessed the quality of the groundwater resource indicated by data from samples analyzed for volatile organic compounds (VOCs), pesticides, and naturally present inorganic constituents, such as major ions and trace elements. The status assessment is intended to characterize the quality of groundwater resources in the shallow aquifer system of the MS-SA study unit, not the treated drinking water delivered to consumers by water purveyors. As opposed to the public wells, however, water from private wells, which often tap the shallow aquifer, is usually consumed without any treatment. The second component of this study—the understanding assessment—identified the natural and human factors that potentially affect groundwater quality by evaluating land-use characteristics, measures of location, geologic factors, groundwater age, and geochemical conditions of the shallow aquifer. An additional component of this study was a comparison of MS-SA water-quality results to those of the GAMA Monterey Bay and Salinas Valley Groundwater Basins study unit. This study unit covered much of the same areal extent as the MS-SA, but assessed the deeper, public drinking-water aquifer system.
Relative concentrations (sample concentration divided by the benchmark concentration) were used to evaluate concentrations of constituents in groundwater samples relative to water-quality benchmarks for those constituents that have Federal or California benchmarks, such as maximum contaminant levels. For organic and special-interest constituents, relative concentrations were classified as high, greater than 1.0; moderate, greater than 0.1 and less than or equal to 1.0; or low, less than or equal to 0.1. For inorganic constituents, relative concentrations were classified as high, greater than 1.0; moderate, greater than 0.5 and less than or equal to 1.0; or low, less than or equal to 0.5. A relative concentration greater than 1.0 indicates that the concentration was greater than a benchmark. Aquifer-scale proportions were used to quantify regional-scale groundwater quality. The aquifer-scale proportions are the areal percentages of the shallow aquifer system where relative concentrations for a given constituent or class of constituents were high, moderate, or low.
Inorganic constituents were measured at high and moderate relative concentrations more frequently than organic constituents. In the MS-SA study unit, inorganic constituents with benchmarks were detected at high relative concentrations in 51 percent of the study unit. The greatest proportions of high relative concentrations of trace elements and radioactive constituents were in the Highlands and Santa Cruz study areas, whereas high relative concentrations of nutrients were most often detected in the Salinas Valley and Pajaro Valley study areas and salinity indicators were most often detected in the Highlands and Salinas Valley study areas. The trace elements detected at high relative concentrations were arsenic, boron, iron, manganese, molybdenum, selenium, and strontium. The radioactive constituents detected at high relative concentrations were adjusted gross alpha radioactivity and uranium. The nutrient detected at high relative concentrations was nitrate plus nitrite. The salinity indicators detected at high relative concentrations were chloride, sulfate, and total dissolved solids.
Organic constituents (VOCs and pesticides) were not detected at high relative concentrations in any of the study areas. The fumigant 1,2-dichloropropane was detected at moderate relative concentrations. The VOC chloroform and the pesticide simazine were the only organic constituents detected in more than 10 percent of samples. The constituents of special interest NDMA (N-nitrosodimethylamine) and perchlorate were detected at high relative concentrations in the MS-SA study unit.
Selected constituents were evaluated with explanatory factors to identify potential sources or processes that could explain their presence and distribution. Trace elements and radioactive constituents came from natural sources and were not elevated by anthropogenic sources or processes, except for selenium and the radioactive constituent uranium. Arsenic, manganese, iron, selenium, and uranium concentrations were all influenced by oxidation-reduction conditions.
Unlike other trace elements and radioactive constituents, uranium and selenium can be affected by agricultural practices. Uranium and selenium can be released from aquifer sediments as a result of irrigation recharge water interacting with bicarbonate systems.
Nitrate can be strongly affected by anthropogenic sources. Nitrate concentrations were significantly higher in modern groundwater, indicating recent inputs of nitrate to the shallow aquifer system. Nitrate was positively correlated with agricultural land use, indicating that irrigation-return water could be leaching nitrogen fertilizer and naturally present nitrate to elevate nitrate concentrations in shallow groundwater.
The salinity indicators total dissolved solids, chloride, and sulfate all had natural sources in the MS-SA study unit, primarily marine sediments. Concentrations of the constituents were elevated as a result of evaporative concentration of irrigation water or precipitation. Sulfate concentrations were significantly correlated to agricultural land use, indicating that agricultural land-use practices are a contributing source of sulfate to groundwater.
The samples with most of the detections of VOCs were from sites in the Pajaro Valley and northern part of the Salinas Valley. Most of the samples with pesticide detections were from sites in the Salinas Valley study area. The herbicide simazine was positively correlated to the percentage of agricultural land use, and its concentrations were higher in modern groundwater than in pre-modern groundwater.
Perchlorate, similar to nitrate, has natural and anthropogenic sources. Correlations of perchlorate to dissolved oxygen, nitrate, and percentage of agricultural land use indicated that the irrigation-return water could be leaching naturally present perchlorate, as well as perchlorate from historical applications of Chilean nitrate fertilizer, to increase perchlorate concentrations in groundwater.
The quality of the water in the shallow aquifer system from this study was compared with the quality of water in the public drinking-water aquifer in a previous GAMA (MS-PA) study in the same area. The shallow system was more oxic and had more sites with modern groundwater than the public drinking-water aquifer, which was more anoxic and had sites with more pre-modern groundwater. Arsenic and selenium were found at high relative concentrations in a greater proportion of the shallow system. Manganese and iron were found at high relative concentrations in a greater proportion of the public drinking-water aquifer. Uranium was found at higher relative concentrations in a greater proportion of the shallow system. Concentrations of arsenic, iron, manganese, and molybdenum are not likely to change much as groundwater percolates from the shallow system to the public drinking-water aquifer because there are no anthropogenic sources affecting these constituents. Uranium and selenium concentrations in the public drinking-water aquifer could be affected by the higher concentrations in the shallow system because of irrigation-return water, however.
Nitrate and salinity indicators had concentrations that were much higher in the shallow system than the deeper public drinking-water aquifer. High concentrations of these constituents in the shallow system could lead to increased concentrations in the public drinking-water aquifer in parts of the study units because of land-use practices, such as irrigated agriculture.
Organic constituents were detected more frequently in the public drinking-water aquifer than in the shallow system, possibly because more of the sites sampled in the public drinking-water aquifer were in urban areas compared to the sites sampled for the shallow system or because sources of contamination have decreased as a result of changes in use at the land surface.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20185057","collaboration":"Prepared in cooperation with the California State Water Resources Control Board","usgsCitation":"Burton, C.A., and Wright, M.T., 2018, Status and understanding of groundwater quality in the Monterey-Salinas Shallow Aquifer study unit, 2012–13: California GAMA Priority Basin Project (ver. 1.1, September 2018): U.S. Geological Survey Scientific Investigations Report 2018–5057, 116 p., https://doi.org/10.3133/sir20185057.","productDescription":"Report: x, 116 p.","numberOfPages":"132","onlineOnly":"Y","ipdsId":"IP-056428","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":357554,"rank":3,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/sir/2018/5057/sir20185057_versionhist.txt","size":"1 KB","linkFileType":{"id":2,"text":"txt"},"description":"SIR 2018-5057"},{"id":354600,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2018/5057/coverthb.jpg"},{"id":354601,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2018/5057/sir20185057_v1.1.pdf","text":"Report","size":"38.5 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2018-5057"}],"country":"United States","state":"California","otherGeospatial":"Monterey-Salinas 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 -121.904296875,\n 36.53170884914869\n ],\n [\n -121.761474609375,\n 36.527294814546245\n ],\n [\n -121.58569335937501,\n 36.49638952000399\n ],\n [\n -121.5142822265625,\n 36.40359962073253\n ],\n [\n -121.4813232421875,\n 36.363798554158635\n ],\n [\n -121.33300781249999,\n 36.33282808737917\n ],\n [\n -121.234130859375,\n 36.27085020723902\n ],\n [\n -121.17370605468749,\n 36.19995805932895\n ],\n [\n -121.08581542968751,\n 36.10237644873644\n ],\n [\n -121.01989746093749,\n 36.02688935430189\n ],\n [\n -120.94299316406249,\n 35.96911507577482\n ],\n [\n -120.88256835937499,\n 35.89795019335754\n ],\n [\n -120.80566406250001,\n 35.79999392988527\n ],\n [\n -120.89080810546875,\n 35.66622234103479\n ],\n [\n -120.8551025390625,\n 35.61488368245436\n ],\n [\n -120.6683349609375,\n 35.46961797120201\n ],\n [\n -120.56945800781249,\n 35.37113502280101\n ],\n [\n -120.465087890625,\n 35.37113502280101\n ],\n [\n -120.2838134765625,\n 35.37113502280101\n ],\n [\n -120.12451171875,\n 35.37561413174875\n ],\n [\n -120.0146484375,\n 35.44277092585766\n ],\n [\n -119.94323730468749,\n 35.46514408578589\n ],\n [\n -119.99267578124999,\n 35.53222622770337\n ],\n [\n -120.10253906249999,\n 35.59925232772949\n ],\n [\n -120.2838134765625,\n 35.755428369259626\n ],\n [\n -120.421142578125,\n 35.88905007936091\n ],\n [\n -120.50903320312501,\n 35.97356075349624\n ],\n [\n -120.673828125,\n 36.09349937380574\n ],\n [\n -120.80566406250001,\n 36.22211876039103\n ],\n [\n -120.94299316406249,\n 36.359374956015856\n ],\n [\n -121.06933593749999,\n 36.46988944681576\n ],\n [\n -121.55273437499999,\n 36.83127162140714\n ],\n [\n -121.61315917968749,\n 36.88840804313823\n ],\n [\n -121.72302246093749,\n 36.9806150652861\n ],\n [\n -121.84936523437499,\n 37.020098201368114\n ],\n [\n -121.9976806640625,\n 37.03325468997236\n ],\n [\n -122.06909179687501,\n 37.01132594307015\n ],\n [\n -122.1075439453125,\n 36.96306042436515\n ],\n [\n -122.0855712890625,\n 36.92793899776678\n ],\n [\n -121.9976806640625,\n 36.94989178681327\n ],\n [\n -121.92626953124999,\n 36.96306042436515\n ],\n [\n -121.86584472656251,\n 36.94989178681327\n ],\n [\n -121.8438720703125,\n 36.88401445049676\n ],\n [\n -121.8109130859375,\n 36.80928470205937\n ],\n [\n -121.8109130859375,\n 36.760891249565624\n ],\n [\n -121.83288574218749,\n 36.69044623523481\n ],\n [\n -121.8438720703125,\n 36.641977814705946\n ],\n [\n -121.8878173828125,\n 36.602299135790446\n ],\n [\n -121.9317626953125,\n 36.602299135790446\n ],\n [\n -121.915283203125,\n 36.56260003738545\n ],\n [\n -121.904296875,\n 36.53170884914869\n ]\n ]\n ]\n }\n }\n ]\n}","edition":"Version 1.1: September 2018; Version 1.0: May 2018","contact":"Director,
California Water Science Center
U.S. Geological Survey
6000 J Street, Placer Hall
Sacramento, California 95819
Operable Unit 2, Area 8, at Naval Base Kitsap, Keyport is the site of a former chrome-plating facility that released metals (primarily chromium and cadmium), chlorinated volatile organic compounds, and petroleum compounds into the local environment. To ensure long-term protectiveness, as stipulated in the Fourth Five-Year Review for the site, Naval Facilities Engineering Command Northwest collaborated with the U.S. Environmental Protection Agency, the Washington State Department of Ecology, and the Suquamish Tribe, to collect data to monitor the contamination left in place and to ensure the site does not pose a risk to human health or the environment. To support these efforts, refined information was needed on the interaction of fresh groundwater with seawater in response to the up-to 13-ft tidal fluctuations at this nearshore site adjacent to Port Orchard Bay. The information was analyzed to meet the primary objective of this investigation, which was to determine the optimal time during the semi-diurnal and the neap-spring tidal cycles to sample groundwater for freshwater contaminants in Area 8 monitoring wells.
Groundwater levels and specific conductance in five monitoring wells, along with marine water-levels (tidal levels) in Port Orchard Bay, were monitored every 15 minutes during a 3-week duration to determine how nearshore groundwater responds to tidal forcing. Time series data were collected from October 24, 2017, to November 16, 2017, a period that included neap and spring tides. Vertical profiles of specific conductance were also measured once in the screened interval of each well prior to instrument deployment to determine if a freshwater/saltwater interface was present in the well during that particular time.
The vertical profiles of specific conductance were measured only one time during an ebbing tide at approximately the top, middle, and bottom of the saturated thickness within the screened interval of each well. The landward-most well, MW8-8, was completely freshwater, while one of the most seaward wells, MW8-9, was completely saline. A distinct saltwater interface was measured in the three other shallow wells (MW8-11, MW8-12, and MW8-14), with the topmost groundwater occurring fresh underlain by higher conductivity water.
Lag times between minimum spring-tide level and minimum groundwater levels in wells ranged from about 2 to 4.5 hours in the less-than 20-ft deep wells screened across the water table, and was about 7 hours for the single 48-ft deep well screened below the water table. Those lag times were surprisingly long considering the wells are all located within 200-ft of the shoreline and the local geology is largely coarse-grained glacial outwash deposits. Various manmade subsurface features, such as slurry walls and backfilled excavations, likely influence and confuse the connectivity between seawater and groundwater.
The specific-conductance time-series data showed clear evidence of substantial saltwater intrusion into the screened intervals of most shallow wells. Unexpectedly, the intrusion was associated with the neap part of the tidal cycle around November 13–16, when relatively low barometric pressure and high southerly winds led to the highest high and low tides measured during the monitoring period. The data consistently indicated that the groundwater had the lowest specific conductance (was least mixed with seawater) during the prior neap tides around October 30, the same period when the shallow groundwater levels were lowest. Although the specific conductance response is somewhat different between wells, the data do suggest that it is the heights of the actual high-high and low-low tides, regardless of whether or not they occur during the neap or spring part of the cycle, that allows seawater intrusion into the nearshore aquifer at Area 8.
With all the data taken into consideration, the optimal time for sampling the shallow monitoring wells at Area 8 would be centered on a 2–5-hour period following the predicted low-low tide during neap tide, with due consideration of local atmospheric pressure and wind conditions that have the potential to generate tides that can be substantially higher than those predicted from lunar-solar tidal forces. The optimal time for sampling the deeper monitoring wells at Area 8 would be during the 6–8-hour period following a predicted low-low tide, also during the neap tide part of the tidal cycle. The specific time window to sample each well following a low tide can be found in table 5. Those periods are when groundwater in the wells is most fresh and least diluted by seawater intrusion. In addition to timing, consideration should be given to collecting undisturbed samples from the top of the screened interval (or top of the water table if below the top of the interval) to best characterize contaminant concentrations in freshwater. A downhole conductivity probe could be used to identify the saltwater interface, above which would be the ideal depth for sampling.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20181082","collaboration":"Prepared in cooperation with the Department of the Navy, Naval Facilities Engineering Command, Northwest","usgsCitation":"Opatz, C.C., and Dinicola, R.S., 2018, Analysis of groundwater response to tidal fluctuations, Operable Unit 2, Area 8, Naval Base Kitsap, Keyport, Washington: U.S. Geological Survey Open-File Report 2018-1082, 20 p., https://doi.org/10.3133/ofr20181082.","productDescription":"Report: iv, 20 p.","onlineOnly":"Y","ipdsId":"IP-095017","costCenters":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"links":[{"id":354378,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2018/1082/coverthb.jpg"},{"id":354379,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2018/1082/ofr20181082.pdf","text":"Report","size":"3.1 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2018-1082"},{"id":358998,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7JW8D5S","text":"USGS data release","description":"USGS Data Release","linkHelpText":"Groundwater and Tidal Time Series Data, Operable Unit 2, Area 8, Naval Base Kitsap, Keyport, Washington"}],"country":"United States","state":"Washington","city":"Keyport","otherGeospatial":"Naval Base Kitsap","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.64913558959962,\n 47.683072220525\n ],\n [\n -122.59180068969725,\n 47.683072220525\n ],\n [\n -122.59180068969725,\n 47.72627665811123\n ],\n [\n -122.64913558959962,\n 47.72627665811123\n ],\n [\n -122.64913558959962,\n 47.683072220525\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Washington Water Science Center
U.S. Geological Survey
934 Broadway, Suite 300
Tacoma, Washington 98402
The magmatic degassing history of newly erupted volcanic glass is recorded in its remaining volatile content. However, this history is subsequently overprinted by post-depositional (secondary) hydration, the rates and origins of which are not yet adequately constrained. Here, we present the results of a natural experiment using products of the 1980 eruptions of Mount St. Helens. We measured water concentration, δDglass, and δ18OBSG (δ18O of the bulk silicate glass) of samples collected during the dry summer months of 1980 and compared them with material resampled in 2015 from the same deposits. Samples collected from the subsurface near gas escape pipes show elevated water concentrations (near 2.0 wt%), and these are associated with lower δDglass (− 110 to − 130‰) and δ18OBSG (6.0 to 6.6‰) values than the 1980 glass (− 70 to − 100‰ and 6.8 to 6.9‰, respectively). Samples collected in 2015 from the surface to 10-cm subsurface of the 1980 summer deposits have a small increase in average water contents of 0.1–0.2 wt% but similar δ18OBSG (6.8–6.9‰) values compared to the 1980 glass values. These samples, however, show 15‰ higher δDglass values; exchange with meteoric water is expected to yield lower δDglass values. We attribute higher δDglass values in the upper portion of the 1980 deposits collected in 2015 to rehydration by higher δD waters that were degassed for several months to a year from the hot underlying deposits, which hydrated the overlying deposits with relatively high δD gases. Our data also contribute to magmatic degassing of crystal-rich volcanoes. Using the 1980 samples, our reconstructed δD-H2O trends for the dacitic Mount St. Helens deposits with rhyolitic groundmass yield a trend that overlaps with the degassing trend for crystal-poor rhyolitic eruptions studied previously elsewhere, suggesting similar behavior of volatiles upon exsolution from magma. Furthermore, our data support previous studies proposing that exsolved volatiles were trapped within a rapidly rising magma and started degassing only at shallow depths during the 1980 eruptions.
Thermal evolution modeling has yielded a variety of interior structures for Ceres, ranging from a modestly differentiated interior to more advanced evolution with a dry silicate core, a hydrated silicate mantle, and a volatile‐rich crust. Here we compute the mass and hydrostatic flattening from more than one hundred billion three‐layer density models for Ceres and describe the characteristics of the population of density structures that are consistent with the Dawn observations. We show that the mass and hydrostatic flattening constraints from Ceres indicate the presence of a high‐density core with greater than a 1σ probability, but provide little constraint on the density, allowing for core compositions that range from hydrous and/or anhydrous silicates to a mixture of metal and silicates. The crustal densities are consistent with surface observations of salts, water ice, carbonates, and ammoniated clays, which indicate hydrothermal alteration, partial fractionation, and the possible settling of heavy sulfide and metallic particles, which provide a potential process for increasing mass with depth.
","language":"English","publisher":"Wiley","doi":"10.1111/maps.13063","usgsCitation":"King, S., Castillo-Rogez, J.C., Toplis, M.J., Bland, M.T., Raymond, C.A., and Russell, C.T., 2018, Ceres internal structure from geophysical constraints: Meteoritics and Planetary Science, v. 53, no. 9, p. 1999-2007, https://doi.org/10.1111/maps.13063.","productDescription":"9 p.","startPage":"1999","endPage":"2007","ipdsId":"IP-092685","costCenters":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"links":[{"id":468914,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1111/maps.13063","text":"External Repository"},{"id":377531,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"Ceres","volume":"53","issue":"9","noUsgsAuthors":false,"publicationDate":"2018-03-14","publicationStatus":"PW","contributors":{"authors":[{"text":"King, S.J.","contributorId":197182,"corporation":false,"usgs":false,"family":"King","given":"S.J.","email":"","affiliations":[],"preferred":false,"id":796241,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Castillo-Rogez, J. C.","contributorId":177375,"corporation":false,"usgs":false,"family":"Castillo-Rogez","given":"J.","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":796242,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Toplis, M. J.","contributorId":238461,"corporation":false,"usgs":false,"family":"Toplis","given":"M.","email":"","middleInitial":"J.","affiliations":[{"id":47711,"text":"University of Toulouse","active":true,"usgs":false}],"preferred":false,"id":796243,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"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":796244,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Raymond, C. A.","contributorId":238463,"corporation":false,"usgs":false,"family":"Raymond","given":"C.","email":"","middleInitial":"A.","affiliations":[{"id":36392,"text":"Jet Propulsion Laboratory","active":true,"usgs":false}],"preferred":false,"id":796245,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Russell, C. T.","contributorId":238465,"corporation":false,"usgs":false,"family":"Russell","given":"C.","email":"","middleInitial":"T.","affiliations":[{"id":13399,"text":"UCLA","active":true,"usgs":false}],"preferred":false,"id":796246,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70195937,"text":"70195937 - 2018 - Fungal disease prevention in seedlings of rice (Oryza sativa) and other grasses by growth-promoting seed-associated endophytic bacteria from invasive Phragmites australis","interactions":[],"lastModifiedDate":"2018-03-12T12:54:23","indexId":"70195937","displayToPublicDate":"2018-03-08T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5020,"text":"Microorganisms","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Fungal disease prevention in seedlings of rice (Oryza sativa) and other grasses by growth-promoting seed-associated endophytic bacteria from invasive Phragmites australis","title":"Fungal disease prevention in seedlings of rice (Oryza sativa) and other grasses by growth-promoting seed-associated endophytic bacteria from invasive Phragmites australis","docAbstract":"Non-cultivated plants carry microbial endophytes that may be used to enhance development and disease resistance of crop species where growth-promoting and protective microbes may have been lost. During seedling establishment, seedlings may be infected by several fungal pathogens that are seed or soil borne. Several species of Fusarium, Pythium and other water moulds cause seed rots during germination. Fusariumblights of seedlings are also very common and significantly affect seedling development. In the present study we screened nine endophytic bacteria isolated from the seeds of invasive Phragmites australis by inoculating onto rice, Bermuda grass (Cynodon dactylon), or annual bluegrass (Poa annua) seeds to evaluate plant growth promotion and protection from disease caused by Fusarium oxysporum. We found that three bacteria belonging to genus Pseudomonas spp. (SLB4-P. fluorescens, SLB6-Pseudomonas sp. and SY1-Pseudomonassp.) promoted seedling development, including enhancement of root and shoot growth, and stimulation of root hair formation. These bacteria were also found to increase phosphate solubilization in in vitro experiments. Pseudomonas sp. (SY1) significantly protected grass seedlings from Fusarium infection. In co-culture experiments, strain SY1 strongly inhibited fungal pathogens with 85.71% growth inhibition of F. oxysporum, 86.33% growth inhibition of Curvularia sp. and 82.14% growth inhibition of Alternaria sp. Seedlings previously treated with bacteria were found much less infected by F. oxysporum in comparison to non-treated controls. On microscopic observation we found that bacteria appeared to degrade fungal mycelia actively. Metabolite products of strain SY1 in agar were also found to inhibit fungal growth on nutrient media. Pseudomonas sp. (SY1) was found to produce antifungal volatiles. Polymerase chain reaction (PCR) amplification using specific primers for pyrrolnitirin synthesis and HCN (hydrogen cyanide) production suggested presence of genes for both compounds in the genome of SY1. HCN was detected in cultures of SY1. We conclude that microbes from non-cultivated plants may provide disease protection and promote growth of crop plants.
","language":"English","publisher":"MDPI","doi":"10.3390/microorganisms6010021","usgsCitation":"Verma, S.K., Kingsley, K.L., Bergen, M.S., Kowalski, K., and White, J., 2018, Fungal disease prevention in seedlings of rice (Oryza sativa) and other grasses by growth-promoting seed-associated endophytic bacteria from invasive Phragmites australis: Microorganisms, v. 6, no. 1, p. 1-13, https://doi.org/10.3390/microorganisms6010021.","productDescription":"Article 21; 13 p.","startPage":"1","endPage":"13","ipdsId":"IP-094472","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":468929,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/microorganisms6010021","text":"Publisher Index Page"},{"id":352330,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"6","issue":"1","publishingServiceCenter":{"id":15,"text":"Madison PSC"},"noUsgsAuthors":false,"publicationDate":"2018-03-08","publicationStatus":"PW","scienceBaseUri":"5afee701e4b0da30c1bfc05c","contributors":{"authors":[{"text":"Verma, Satish Kumar","contributorId":203175,"corporation":false,"usgs":false,"family":"Verma","given":"Satish","email":"","middleInitial":"Kumar","affiliations":[{"id":12727,"text":"Rutgers University","active":true,"usgs":false}],"preferred":false,"id":730554,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kingsley, Kathryn L.","contributorId":203176,"corporation":false,"usgs":false,"family":"Kingsley","given":"Kathryn","email":"","middleInitial":"L.","affiliations":[{"id":12727,"text":"Rutgers University","active":true,"usgs":false}],"preferred":false,"id":730555,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bergen, Marshall S.","contributorId":178394,"corporation":false,"usgs":false,"family":"Bergen","given":"Marshall","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":730556,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kowalski, Kurt P. 0000-0002-8424-4701 kkowalski@usgs.gov","orcid":"https://orcid.org/0000-0002-8424-4701","contributorId":3768,"corporation":false,"usgs":true,"family":"Kowalski","given":"Kurt P.","email":"kkowalski@usgs.gov","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":730553,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"White, James F.","contributorId":152046,"corporation":false,"usgs":false,"family":"White","given":"James F.","affiliations":[],"preferred":false,"id":730557,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70195485,"text":"70195485 - 2018 - Phytoforensics: Trees as bioindicators of potential indoor exposure via vapor intrusion","interactions":[],"lastModifiedDate":"2018-02-16T15:40:38","indexId":"70195485","displayToPublicDate":"2018-02-16T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2980,"text":"PLoS ONE","active":true,"publicationSubtype":{"id":10}},"title":"Phytoforensics: Trees as bioindicators of potential indoor exposure via vapor intrusion","docAbstract":"Human exposure to volatile organic compounds (VOCs) via vapor intrusion (VI) is an emerging public health concern with notable detrimental impacts on public health. Phytoforensics, plant sampling to semi-quantitatively delineate subsurface contamination, provides a potential non-invasive screening approach to detect VI potential, and plant sampling is effective and also time- and cost-efficient. Existing VI assessment methods are time- and resource-intensive, invasive, and require access into residential and commercial buildings to drill holes through basement slabs to install sampling ports or require substantial equipment to install groundwater or soil vapor sampling outside the home. Tree-core samples collected in 2 days at the PCE Southeast Contamination Site in York, Nebraska were analyzed for tetrachloroethene (PCE) and results demonstrated positive correlations with groundwater, soil, soil-gas, sub-slab, and indoor-air samples collected over a 2-year period. Because tree-core samples were not collocated with other samples, interpolated surfaces of PCE concentrations were estimated so that comparisons could be made between pairs of data. Results indicate moderate to high correlation with average indoor-air and sub-slab PCE concentrations over long periods of time (months to years) to an interpolated tree-core PCE concentration surface, with Spearman’s correlation coefficients (ρ) ranging from 0.31 to 0.53 that are comparable to the pairwise correlation between sub-slab and indoor-air PCE concentrations (ρ = 0.55, n = 89). Strong correlations between soil-gas, sub-slab, and indoor-air PCE concentrations and an interpolated tree-core PCE concentration surface indicate that trees are valid indicators of potential VI and human exposure to subsurface environment pollutants. The rapid and non-invasive nature of tree sampling are notable advantages: even with less than 60 trees in the vicinity of the source area, roughly 12 hours of tree-core sampling with minimal equipment at the PCE Southeast Contamination Site was sufficient to delineate vapor intrusion potential in the study area and offered comparable delineation to traditional sub-slab sampling performed at 140 properties over a period of approximately 2 years.
","language":"English","publisher":"PLOS","doi":"10.1371/journal.pone.0193247","usgsCitation":"Wilson, J.L., Samaranayake, V., Limmer, M.A., and Burken, J.G., 2018, Phytoforensics: Trees as bioindicators of potential indoor exposure via vapor intrusion: PLoS ONE, v. 13, no. 2, p. 1-17, https://doi.org/10.1371/journal.pone.0193247.","productDescription":"e0193247; 17 p.","startPage":"1","endPage":"17","ipdsId":"IP-085495","costCenters":[{"id":396,"text":"Missouri Water Science Center","active":true,"usgs":true}],"links":[{"id":468991,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0193247","text":"Publisher Index Page"},{"id":438010,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7CF9P06","text":"USGS data release","linkHelpText":"Concentrations of tetrachloroethylene in tree-core, groundwater, soil, soil-gas, indoor-air, and sub-slab samples from the Tetrachloroethene Southeast Contamination Site in York, Nebraska, 2014-2016."},{"id":351746,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Nebraska","city":"York","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -97.595,\n 40.87\n ],\n [\n -97.575,\n 40.87\n ],\n [\n -97.575,\n 40.8639\n ],\n [\n -97.595,\n 40.8639\n ],\n [\n -97.595,\n 40.87\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"13","issue":"2","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationDate":"2018-02-16","publicationStatus":"PW","scienceBaseUri":"5afee72be4b0da30c1bfc168","contributors":{"authors":[{"text":"Wilson, Jordan L. 0000-0003-0490-9062 jlwilson@usgs.gov","orcid":"https://orcid.org/0000-0003-0490-9062","contributorId":5416,"corporation":false,"usgs":true,"family":"Wilson","given":"Jordan","email":"jlwilson@usgs.gov","middleInitial":"L.","affiliations":[{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true},{"id":396,"text":"Missouri Water Science Center","active":true,"usgs":true}],"preferred":true,"id":728825,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Samaranayake, V.A. 0000-0002-1892-8363","orcid":"https://orcid.org/0000-0002-1892-8363","contributorId":201176,"corporation":false,"usgs":false,"family":"Samaranayake","given":"V.A.","email":"","affiliations":[],"preferred":false,"id":728826,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Limmer, Matthew A.","contributorId":200927,"corporation":false,"usgs":false,"family":"Limmer","given":"Matthew","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":728827,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Burken, Joel G.","contributorId":21218,"corporation":false,"usgs":true,"family":"Burken","given":"Joel","email":"","middleInitial":"G.","affiliations":[],"preferred":false,"id":728828,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70195031,"text":"70195031 - 2018 - Regional variability of nitrate fluxes in the unsaturated zone and groundwater, Wisconsin, USA","interactions":[],"lastModifiedDate":"2018-02-22T12:49:24","indexId":"70195031","displayToPublicDate":"2018-02-06T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3722,"text":"Water Resources Research","onlineIssn":"1944-7973","printIssn":"0043-1397","active":true,"publicationSubtype":{"id":10}},"title":"Regional variability of nitrate fluxes in the unsaturated zone and groundwater, Wisconsin, USA","docAbstract":"Process-based modeling of regional NO3− fluxes to groundwater is critical for understanding and managing water quality, but the complexity of NO3− reactive transport processes make implementation a challenge. This study introduces a regional vertical flux method (VFM) for efficient estimation of reactive transport of NO3− in the vadose zone and groundwater. The regional VFM was applied to 443 well samples in central-eastern Wisconsin. Chemical measurements included O2, NO3−, N2 from denitrification, and atmospheric tracers of groundwater age including carbon-14, chlorofluorocarbons, tritium, and tritiogenic helium. VFM results were consistent with observed chemistry, and calibrated parameters were in-line with estimates from previous studies. Results indicated that (1) unsaturated zone travel times were a substantial portion of the transit time to wells and streams (2) since 1945 fractions of applied N leached to groundwater have increased for manure-N, possibly due to increased injection of liquid manure, and decreased for fertilizer-N, and (3) under current practices and conditions, approximately 60% of the shallow aquifer will eventually be affected by downward migration of NO3−, with denitrification protecting the remaining 40%. Recharge variability strongly affected the unsaturated zone lag times and the eventual depth of the NO3− front. Principal components regression demonstrated that VFM parameters and predictions were significantly correlated with hydrogeochemical landscape features. The diverse and sometimes conflicting aspects of N management (e.g. limiting N volatilization versus limiting N losses to groundwater) warrant continued development of large-scale holistic strategies to manage water quality and quantity.","language":"English","publisher":"AGU","doi":"10.1002/2017WR022012","usgsCitation":"Green, C., Liao, L., Nolan, B.T., Juckem, P.F., Shope, C.L., Tesoriero, A.J., and Jurgens, B.C., 2018, Regional variability of nitrate fluxes in the unsaturated zone and groundwater, Wisconsin, USA: Water Resources Research, v. 54, no. 1, p. 301-322, https://doi.org/10.1002/2017WR022012.","productDescription":"22 p.","startPage":"301","endPage":"322","ipdsId":"IP-086033","costCenters":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"links":[{"id":469026,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/2017wr022012","text":"Publisher Index Page"},{"id":351039,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Wisconsin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -92.3291015625,\n 46.13417004624326\n ],\n [\n -92.59277343749999,\n 45.98169518512228\n ],\n [\n -92.85644531250001,\n 45.72152152227956\n ],\n [\n -92.85644531250001,\n 45.5679096098613\n ],\n [\n -92.6806640625,\n 45.47554027158593\n ],\n [\n -92.8125,\n 45.213003555993964\n ],\n [\n -92.83447265624999,\n 44.74673324024678\n ],\n [\n -92.48291015625,\n 44.5435052132082\n ],\n [\n -92.21923828124999,\n 44.402391829093915\n ],\n [\n -91.99951171875,\n 44.33956524809713\n ],\n [\n -91.7138671875,\n 44.11914151643737\n ],\n [\n -91.2744140625,\n 43.88205730390537\n ],\n [\n -91.2744140625,\n 43.48481212891603\n ],\n [\n -91.0546875,\n 43.34116005412307\n ],\n [\n -91.25244140624999,\n 43.068887774169625\n ],\n [\n -91.16455078125,\n 42.71473218539458\n ],\n [\n -90.76904296874999,\n 42.66628070564928\n ],\n [\n -90.65917968749999,\n 42.48830197960227\n ],\n [\n -87.7587890625,\n 42.52069952914966\n ],\n [\n -87.71484375,\n 42.71473218539461\n ],\n [\n -87.802734375,\n 42.90816007196054\n ],\n [\n -87.802734375,\n 43.16512263158296\n ],\n [\n -87.8466796875,\n 43.29320031385285\n ],\n [\n -87.71484375,\n 43.42100882994726\n ],\n [\n -87.6708984375,\n 43.61221676817573\n ],\n [\n -87.6708984375,\n 43.739352079154706\n ],\n [\n -87.62695312499999,\n 43.89789239125797\n ],\n [\n -87.5390625,\n 43.99281450048989\n ],\n [\n -87.5390625,\n 44.15068115978094\n ],\n [\n -87.3193359375,\n 44.465151013519616\n ],\n [\n -87.14355468749999,\n 44.77793589631623\n ],\n [\n -86.9677734375,\n 45.089035564831036\n ],\n [\n -86.8359375,\n 45.24395342262324\n ],\n [\n -86.7041015625,\n 45.460130637921004\n ],\n [\n -87.099609375,\n 45.521743896993634\n ],\n [\n -87.3193359375,\n 45.24395342262324\n ],\n [\n -87.6708984375,\n 44.84029065139799\n ],\n [\n -88.02246093750001,\n 44.49650533109348\n ],\n [\n -87.890625,\n 44.809121700077355\n ],\n [\n -87.802734375,\n 44.902577996288876\n ],\n [\n -87.5830078125,\n 45.058001435398246\n ],\n [\n -87.71484375,\n 45.182036837015886\n ],\n [\n -87.62695312499999,\n 45.398449976304086\n ],\n [\n -87.890625,\n 45.336701909968134\n ],\n [\n -87.802734375,\n 45.49094569262732\n ],\n [\n -87.802734375,\n 45.67548217560647\n ],\n [\n -87.802734375,\n 45.79816953017263\n ],\n [\n -88.11035156249999,\n 45.79816953017263\n ],\n [\n -88.11035156249999,\n 45.98169518512228\n ],\n [\n -88.6376953125,\n 46.10370875598026\n ],\n [\n -88.9013671875,\n 46.13417004624326\n ],\n [\n -90.087890625,\n 46.34692761055673\n ],\n [\n -90.263671875,\n 46.498392258597654\n ],\n [\n -90.43945312500001,\n 46.58906908309182\n ],\n [\n -90.2197265625,\n 47.07012182383309\n ],\n [\n -90.3515625,\n 47.279229002570794\n ],\n [\n -90.966796875,\n 47.18971246448421\n ],\n [\n -91.4501953125,\n 47.010225655683485\n ],\n [\n -91.93359375,\n 46.830133640447386\n ],\n [\n -92.3291015625,\n 46.73986059969267\n ],\n [\n -92.3291015625,\n 46.13417004624326\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"54","issue":"1","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2018-01-23","publicationStatus":"PW","scienceBaseUri":"5a7acd1de4b00f54eb20c589","contributors":{"authors":[{"text":"Green, Christopher T. ctgreen@usgs.gov","contributorId":146339,"corporation":false,"usgs":true,"family":"Green","given":"Christopher T.","email":"ctgreen@usgs.gov","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":false,"id":726652,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Liao, Lixia 0000-0003-2513-0680","orcid":"https://orcid.org/0000-0003-2513-0680","contributorId":201643,"corporation":false,"usgs":true,"family":"Liao","given":"Lixia","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":726653,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Nolan, Bernard T. 0000-0002-6945-9659 btnolan@usgs.gov","orcid":"https://orcid.org/0000-0002-6945-9659","contributorId":2190,"corporation":false,"usgs":true,"family":"Nolan","given":"Bernard","email":"btnolan@usgs.gov","middleInitial":"T.","affiliations":[{"id":27111,"text":"National Water Quality Program","active":true,"usgs":true},{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true}],"preferred":true,"id":726654,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Juckem, Paul F. 0000-0002-3613-1761 pfjuckem@usgs.gov","orcid":"https://orcid.org/0000-0002-3613-1761","contributorId":1905,"corporation":false,"usgs":true,"family":"Juckem","given":"Paul","email":"pfjuckem@usgs.gov","middleInitial":"F.","affiliations":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true},{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":726655,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Shope, Christopher L. cshope@usgs.gov","contributorId":5016,"corporation":false,"usgs":true,"family":"Shope","given":"Christopher","email":"cshope@usgs.gov","middleInitial":"L.","affiliations":[{"id":610,"text":"Utah Water Science Center","active":true,"usgs":true}],"preferred":true,"id":726656,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Tesoriero, Anthony J. 0000-0003-4674-7364 tesorier@usgs.gov","orcid":"https://orcid.org/0000-0003-4674-7364","contributorId":195265,"corporation":false,"usgs":true,"family":"Tesoriero","given":"Anthony","email":"tesorier@usgs.gov","middleInitial":"J.","affiliations":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"preferred":false,"id":726657,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Jurgens, Bryant C. 0000-0002-1572-113X bjurgens@usgs.gov","orcid":"https://orcid.org/0000-0002-1572-113X","contributorId":127842,"corporation":false,"usgs":true,"family":"Jurgens","given":"Bryant","email":"bjurgens@usgs.gov","middleInitial":"C.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":726658,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70196295,"text":"70196295 - 2018 - Morphological indicators of a mascon beneath Ceres' largest crater, Kerwan","interactions":[],"lastModifiedDate":"2018-04-02T10:41:05","indexId":"70196295","displayToPublicDate":"2018-02-01T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1807,"text":"Geophysical Research Letters","active":true,"publicationSubtype":{"id":10}},"title":"Morphological indicators of a mascon beneath Ceres' largest crater, Kerwan","docAbstract":"Gravity data of Ceres returned by the National Aeronautics and Space Administration's Dawn spacecraft is consistent with a lower density crust of variable thickness overlying a higher density mantle. Crustal thickness variations can affect the long‐term, postimpact modification of impact craters on Ceres. Here we show that the unusual morphology of the 280 km diameter crater Kerwan may result from viscous relaxation in an outer layer that thins substantially beneath the crater floor. We propose that such a structure is consistent with either impact‐induced uplift of the high‐density mantle beneath the crater or from volatile loss during the impact event. In either case, the subsurface structure inferred from the crater morphology is superisostatic, and the mass excess would result in a positive Bouguer anomaly beneath the crater, consistent with the highest‐degree gravity data from Dawn. Ceres joins the Moon, Mars, and Mercury in having basin‐associated gravity anomalies, although their origin may differ substantially.
The U.S. Geological Survey National Minerals Information Center (NMIC) is the U.S. Government agency tasked with the collection, analysis, and dissemination of information on the production, consumption, import, export, and other measures of the flows of non-fuel mineral commodities of importance to the U.S. economy and national security. The NMIC and its agency predecessors have maintained a database of this information, collected and published annually, dating back to the beginning of the twentieth century. Time series analysis of annual information from the NMIC provides the opportunity to identify trends in the supply chains of the minerals and metals which are increasingly in demand for advanced technologies. The identification of trends in data for net import reliance, country concentration of production, global demand, price volatility, and other measures, when combined with world governance indicators, can be used to focus attention on individual mineral commodities where supply chain restrictions may develop. Specific examples for U.S. net import reliance, global tantalum primary mining, and mineral criticality screening are presented to illustrate the utility of time series analysis of trends in mineral commodity supply and demand, the types of data required, and the limitations of currently available information.
","language":"English","publisher":"Springer","doi":"10.1007/s11053-017-9340-9","usgsCitation":"Fortier, S.M., Thomas, C.L., McCullough, E.A., and Tolcin, A., 2018, Global trends in mineral commodities for advanced technologies: Natural Resources Research, v. 27, p. 191-200, https://doi.org/10.1007/s11053-017-9340-9.","productDescription":"10 p.","startPage":"191","endPage":"200","ipdsId":"IP-086414","costCenters":[{"id":432,"text":"National Minerals Information Center","active":true,"usgs":true}],"links":[{"id":386023,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"27","noUsgsAuthors":false,"publicationDate":"2017-05-03","publicationStatus":"PW","contributors":{"authors":[{"text":"Fortier, Steven M. 0000-0001-8123-5749","orcid":"https://orcid.org/0000-0001-8123-5749","contributorId":202406,"corporation":false,"usgs":true,"family":"Fortier","given":"Steven","email":"","middleInitial":"M.","affiliations":[{"id":432,"text":"National Minerals Information Center","active":true,"usgs":true}],"preferred":true,"id":816551,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Thomas, Christine Lyn 0000-0002-1391-6072","orcid":"https://orcid.org/0000-0002-1391-6072","contributorId":258823,"corporation":false,"usgs":true,"family":"Thomas","given":"Christine","email":"","middleInitial":"Lyn","affiliations":[{"id":432,"text":"National Minerals Information Center","active":true,"usgs":true}],"preferred":true,"id":816552,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"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":816553,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Tolcin, Amy 0000-0001-9447-2444 atolcin@usgs.gov","orcid":"https://orcid.org/0000-0001-9447-2444","contributorId":213768,"corporation":false,"usgs":true,"family":"Tolcin","given":"Amy","email":"atolcin@usgs.gov","affiliations":[{"id":432,"text":"National Minerals Information Center","active":true,"usgs":true}],"preferred":true,"id":816554,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70038826,"text":"sir20115220 - 2018 - Quality of water from crystalline rock aquifers in New England, New Jersey, and New York, 1995-2007","interactions":[],"lastModifiedDate":"2018-11-19T10:34:21","indexId":"sir20115220","displayToPublicDate":"2012-06-25T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2011-5220","title":"Quality of water from crystalline rock aquifers in New England, New Jersey, and New York, 1995-2007","docAbstract":"Crystalline bedrock aquifers in New England and parts of New Jersey and New York (NECR aquifers) are a major source of drinking water. Because the quality of water in these aquifers is highly variable, the U.S. Geological Survey (USGS) statistically analyzed chemical data on samples of untreated groundwater collected from 117 domestic bedrock wells in New England, New York, and New Jersey, and from 4,775 public-supply bedrock wells in New England to characterize the quality of the groundwater. The domestic-well data were from samples collected by the USGS National Water-Quality Assessment (NAWQA) Program from 1995 through 2007. The public-supply-well data were from samples collected for the U.S. Environmental Protection Agency (USEPA) Safe Drinking Water Act (SDWA) Program from 1997 through 2007. Chemical data compiled from the domestic wells include pH, specific conductance, dissolved oxygen, alkalinity, and turbidity; 6 nitrogen and phosphorus compounds, 14 major ions, 23 trace elements, 222radon gas (radon), 48 pesticide compounds, and 82 volatile organic compounds (VOCs). Additional samples were collected from the domestic wells for the analysis of gross alpha- and gross beta-particle radioactivity, radium isotopes, chlorofluorocarbon isotopes, and the dissolved gases methane, carbon dioxide, nitrogen, and argon. Chemical data compiled from the public-supply wells include pH, specific conductance, nitrate, iron, manganese, sodium, chloride, fluoride, arsenic, uranium, radon, combined radium (226radium plus 228radium), gross alpha-particle radioactivity, and methyl tert-butyl ether (MtBE).
Patterns in fluoride, arsenic, uranium, and radon distributions were discernable when the data were compared to lithology groupings of the bedrock, indicating that the type of bedrock has an effect on the quality of groundwater from NECR aquifers. Fluoride concentrations were significantly higher in groundwater samples from the alkali granite, peraluminous granite, and metaluminous granite lithology groups than from samples in the other lithology groups. Water samples from 1.4 percent of 2,167 studied wells had fluoride concentrations that were equal to or greater than the maximum contaminant level (MCL) of 4 milligrams per liter (mg/L) and 7.5 percent of the wells had fluoride concentrations that were equal to or greater than the secondary MCL of 2 mg/L. For arsenic, groundwater samples from the calcareous metasedimentary rocks in the New Hampshire-Maine geologic province, peraluminous granite, and pelitic rocks lithology groups had higher concentrations than did samples from the other lithology groups. Water samples from 13.3 percent of 2,054 studied wells had arsenic concentrations that were equal to or greater than the MCL of 10 micrograms per liter (μg/L), about double the national rate of occurrence in community-supply systems and in domestic wells of the United States. Uranium concentrations were significantly higher in groundwater samples from the peraluminous granite, alkali granite, and calcareous metasedimentary rocks in the New Hampshire-Maine geologic province lithology groups than from samples in the other lithology groups. Water samples from 14.2 percent of 556 studied wells had uranium concentrations equal to or greater than the MCL of 30 μg/L. Radon activities were equal to or greater than the proposed MCL of 300 picocuries per liter (pCi/L) in 95 percent of 943 studied wells, and 33 percent of the wells had radon activities were equal to or greater than the proposed alternative maximum contaminant level (AMCL) of 4,000 pCi/L. Radon activities exceeded the proposed AMCL in 20 percent or more of groundwater samples in each of the studied lithology groups with a minimum of 9 samples, but radon activities were significantly higher in groundwater samples from the alkali granite, peraluminous granite, and Narragansett basin metasedimentary rocks lithology groups. Water samples from 3.2 percent of 564 studied wells had combined radium activities equal to or greater than the MCL of 5 pCi/L; however, combined radium activities were not significantly different among the studied lithology groups.
Land use and population density also were evaluated to explain patterns in water quality. Concentrations of nitrate, sodium, chloride, and MtBE from the studied wells were significantly greater in areas of high population density (≥50 persons per square kilometer) than in areas of low population density (<50 persons per square kilometer). Concentrations of sodium, chloride, and MtBE from the studied wells were significantly greater in areas classified as developed (urban lands) than in areas classified as undeveloped (forested), agricultural, or mixed (no dominant land use). Nitrate concentrations from the public-supply wells were not significantly different among the four land use categories, but nitrate concentrations from the domestic wells were significantly greater in areas classified as developed than in areas classified as undeveloped, agricultural, or mixed.
Chloride to bromide mass ratios in the domestic well samples indicate that the groundwater was probably affected by at least three halogen sources: local precipitation and recharge waters, remnant seawater and connate waters evolved from seawater, and recharge waters affected by road salt. The groundwater in the NECR aquifers generally contained low concentrations of nitrate, VOCs, and pesticides. Less than 1 percent of water samples from 4,781 studied wells had concentrations of nitrate greater than the MCL of 10 mg/L. Less than 1 percent of water samples from 1,299 studied wells exceeded the USEPA advisory level of 20 to 40 μg/L for MtBE. None of the other studied VOCs exceeded a human health benchmark. MtBE (36 percent frequency detection) and chloroform (32.9 percent frequency detection) were the most frequently detected (>0.02 μg/L) VOCs in the domestic wells. MtBE was detected more often in water samples with apparent ages of less than 25 years than in water samples with apparent ages greater than 25 years. This finding is consistent with the time period of high MtBE use in areas in the United States where reformulated gasoline was mandated. The largest pesticide concentration was an estimated concentration of 0.06 μg/L for the herbicide metolachlor. Deethylatrazine, a degradate of atrazine, (18 percent frequency detection) and atrazine (8 percent frequency detection) were the only pesticide compounds detected (>0.001 μg/L) in more than 3 percent of the domestic wells. None of the detected pesticide compounds exceeded human health benchmarks.
Concentrations of nitrate and gross alpha-particle activities were significantly greater in the water samples from the domestic wells than in samples from the public-supply wells. Concentrations of sodium, chloride, iron, manganese, and uranium were significantly greater in the water samples from the public-supply wells than in the samples from the domestic wells. One possible explanation may be related to differences in field processing (filtered samples from the domestic wells compared to unfiltered samples from the public-supply wells).
The high frequency of detections for a wide variety of manmade and naturally occurring contaminants in both domestic and public-supply wells shows the vulnerability of NECR aquifers to contamination. The highly variable water quality and the association with highly variable lithology of crystalline bedrock underscores the importance of testing individual wells to determine if concentrations for the most commonly detected contaminants exceed human health benchmarks.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20115220","isbn":"ISBN 978-1-411-33417-5","collaboration":"National Water-Quality Assessment Program","usgsCitation":"Flanagan, S.M., Ayotte, J.D., Robinson, G.R., Jr., 2018, Quality of water from crystalline rock aquifers in New England, New Jersey, and New York, 1995–2007 (ver.1.1, April 2018): U.S. Geological Survey 2011–5220, 104 p., https://doi.org/10.3133/sir20115220.\n","productDescription":"Report: xiv, 104 p.","numberOfPages":"122","onlineOnly":"N","additionalOnlineFiles":"Y","temporalStart":"1995-01-01","temporalEnd":"2007-12-31","costCenters":[{"id":245,"text":"Eastern Mineral and Environmental Resources Science Center","active":true,"usgs":true},{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"links":[{"id":353386,"rank":3,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2011/5220/pdf/sir20115220.pdf","text":"Report","size":"9.15 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2011-5220"},{"id":353387,"rank":4,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/sir/2011/5220/versionHist.txt","size":"1.33 KB","linkFileType":{"id":2,"text":"txt"}},{"id":257873,"rank":100,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2011/5220/index.html","text":"Index Page","linkFileType":{"id":5,"text":"html"}},{"id":257884,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2011/5220/images/coverthb.jpg"}],"country":"United States","state":"Connecticut, Maine, Massachusetts, New Hampshire, New Jersey, New York, Rhode Island, and Vermont","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -75.03662109375,\n 40.56389453066509\n ],\n [\n -66.90673828125,\n 40.56389453066509\n ],\n [\n -66.90673828125,\n 47.39834920035926\n ],\n [\n -75.03662109375,\n 47.39834920035926\n ],\n [\n -75.03662109375,\n 40.56389453066509\n ]\n ]\n ]\n }\n }\n ]\n}","edition":"Version 1.0: Originally released June 25, 2012; Version 1.1: April 13, 2018","contact":"Director, New England Water Science Center
U.S. Geological Survey
331 Commerce Way, Suite 2
Pembroke, NH 03275
The Devonian-age Marcellus Shale and the Ordovician-age Utica Shale, which have the potential for natural gas development, underlie Pike County and neighboring counties in northeastern Pennsylvania. In 2015, the U.S. Geological Survey, in cooperation with the Pike County Conservation District, conducted a study that expanded on a previous more limited 2012 study to assess baseline shallow groundwater quality in bedrock aquifers in Pike County prior to possible extensive shale-gas development. Seventy-nine water wells ranging in depths from 80 to 610 feet were sampled during June through September 2015 to provide data on the presence of methane and other aspects of existing groundwater quality in the various bedrock geologic units throughout the county, including concentrations of inorganic constituents commonly present at low values in shallow, fresh groundwater but elevated in brines associated with fluids extracted from geologic formations during shale-gas development. All groundwater samples collected in 2015 were analyzed for bacteria, dissolved and total major ions, nutrients, selected dissolved and total inorganic trace constituents (including metals and other elements), radon-222, gross alpha- and gross beta-particle activity, dissolved gases (methane, ethane, and propane), and, if sufficient methane was present, the isotopic composition of methane. Additionally, samples from 20 wells distributed throughout the county were analyzed for selected man-made volatile organic compounds, and samples from 13 wells where waters had detectable gross alpha activity were analyzed for radium-226 on the basis of relatively elevated gross alpha-particle activity.
Results of the 2015 study show that groundwater quality generally met most drinking-water standards for constituents and properties included in analyses, but groundwater samples from some wells had one or more constituents or properties, including arsenic, iron, manganese, pH, bacteria, sodium, chloride, sulfate, total dissolved solids, and radon-222, that did not meet (commonly termed failed or exceeded) primary or secondary maximum contaminant levels (MCLs) or Health Advisories (HA) for drinking water. Except for iron, dissolved and total concentrations of major ions and most trace constituents generally were similar. Only 1 of 79 well-water samples had any constituent that exceeded a MCL, with an arsenic concentration of about 30 micrograms per liter (µg/L) that was higher than the MCL of 10 µg/L. However, total arsenic concentrations were higher than the HA of 2 µg/L in samples from another 12 of 79 wells (about 15 percent). Secondary maximum contaminant levels (SMCLs) were exceeded most frequently by pH and concentrations of iron and manganese. The pH was outside of the SMCL range of 6.5–8.5 in samples from 24 of 79 wells (30 percent), ranging from 5.5 to 9.2; more samples had pH values less than 6.5 than had pH values greater than 8.5. Total iron concentrations typically were much greater than dissolved iron concentrations, indicating substantial presence of iron in particulate phase, and exceeded the SMCL of 300 µg/L more often [35 of 79 samples (44 percent)] than dissolved iron concentrations [samples from 8 of 79 wells (10 percent)]. Total manganese concentrations exceeded the SMCL of 50 µg/L in samples from 31 of 79 wells (39 percent) and the HA of 300 µg/L in samples from 13 of 79 wells (about 16 percent). A few (1–2) samples had concentrations of sodium, chloride, sulfate, or TDS higher than the SMCLs of 60, 250, 250, and 500 mg/L, respectively. However, dissolved sodium concentrations were higher than the HA of 20 mg/L in samples from 15 of 79 wells (nearly 20 percent). Total coliform bacteria were detected in samples from 25 of 79 wells (32 percent) but Escherichia coli were not detected in any sample. Radon-222 activities ranged from 11 to 5,100 picocuries per liter (pCi/L), with a median of 1,440 pCi/L, and exceeded the proposed and the alternate proposed drinking-water standards of 300 and 4,000 pCi/L, respectively, in samples from 60 of 79 wells (75 percent) and in samples from 2 of 79 wells (3 percent), respectively.
Groundwater samples from all wells were analyzed for dissolved methane by one contract laboratory that determined water from 19 of the 79 wells (24 percent) had concentrations of methane greater than the reporting level of 0.010 milligrams per liter (mg/L) with a maximum methane concentration of 2.5 mg/L. Methane concentrations in 18 replicate samples submitted to a second laboratory for dissolved gas and isotopic analysis generally were higher by as much as a factor of 2.7 from those determined by the first laboratory, indicating potential bias related to combined sampling and analytical methods, and therefore, caution needs to be used when comparing methane results determined by different methods. The isotopic composition of methane in 9 of 10 samples with sufficient dissolved methane (about 0.3 mg/L) for isotopic analysis is consistent with values reported for methane of microbial origin produced through carbon dioxide reduction; an isotopic shift in 1 or 2 samples may indicate subsequent methane oxidation. The low concentrations of ethane relative to methane in these samples further indicate that the methane may be of microbial origin. Groundwater samples with relatively elevated methane concentrations (near or greater than 0.3 mg/L) also had chemical compositions that differed in some respects from groundwater with relatively low methane concentrations (less than 0.3 mg/L) by having higher pH (greater than 8) and higher concentrations of sodium, lithium, boron, fluoride, arsenic, and bromide and chloride/bromide ratios indicative of mixing with a small amount of brine of probable natural occurrence.
The spatial distribution of groundwater compositions differs by topographic setting and lithology and generally shows that (1) relatively dilute, slightly acidic, oxygenated, calcium-carbonate type waters tend to occur in the uplands underlain by the undivided Poplar Gap and Packerton members of the Catskill Formation in southwestern Pike County; (2) waters of near neutral pH with the highest amounts of hardness (calcium and magnesium) generally occur in areas of intermediate altitudes underlain by other members of the Catskill Formation; and (3) waters with pH values greater than 8, low oxygen concentrations, and the highest arsenic, sodium, lithium, bromide, and methane concentrations can be present in deep wells in uplands but most frequently occur in stream valleys, especially at low altitudes (less than about 1,200 feet above North American Vertical Datum of 1988) where groundwater may be discharging regionally, such as to the Delaware River in northern and eastern Pike County. Thus, the baseline assessment of groundwater quality in Pike County prior to gas-well development shows that shallow (less than about 1,000 feet deep) groundwater generally meets primary drinking-water standards for inorganic constituents but varies spatially, with methane and some constituents present in high concentrations in brine (and connate waters from gas and oil reservoirs) present at low to moderate concentrations in some parts of Pike County.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20175110","collaboration":"Prepared in cooperation with the Pike County Conservation District","usgsCitation":"Senior, L.A., and Cravotta, C.A., III, 2017: Baseline assessment of groundwater quality in Pike County, Pennsylvania, 2015: U.S. Geological Survey Scientific Investigations Report 2017–5110, 181 p., https://doi.org/10.3133/sir20175110.","productDescription":"Report: xii, 181 p.; Data Release","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-088156","costCenters":[{"id":532,"text":"Pennsylvania Water Science Center","active":true,"usgs":true}],"links":[{"id":350196,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://www.sciencebase.gov/catalog/item/5980c3c0e4b0a38ca278a8c9","text":"USGS Data Release","linkHelpText":"Field properties and results of laboratory analysis of groundwater samples collected from 79 wells in Pike County, Pennsylvania, 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Pennsylvania Water Science Center
U.S. Geological Survey
215 Limekiln Road
New Cumberland, PA 17070-2424
http://pa.water.usgs.gov
The Great Lakes Areas of Concern (AOCs) are considered to be the most severely degraded areas within the Great Lakes basin, as defined in the Great Lakes Water Quality Agreement and amendments. Among the 43 designated AOCs are four Lake Michigan AOCs in the State of Wisconsin. The smallest of these AOCs is the Sheboygan River AOC, which was designated as an AOC because of sediment contamination from polychlorinated biphenyl compounds (PCBs), polycyclic aromatic hydrocarbons (PAHs), volatile organic compounds (VOCs), and heavy metals. The Sheboygan River AOC has 9 of 14 possible Beneficial Use Impairments (BUIs), which must be addressed to improve overall water-quality, and to ultimately delist the AOC. One of the BUIs associated with this AOC is the “degradation of phytoplankton and zooplankton populations,” which can be removed from the list of impairments when it has been determined that zooplankton community composition and structure at the AOC do not differ significantly from communities at non-AOC comparison sites. In 2012 and 2014, the U.S. Geological Survey collected plankton (phytoplankton and zooplankton) community samples at the Sheboygan River AOC and selected non-AOC sites as part of a larger Great Lakes Restoration Initiative study evaluating both the benthos and plankton communities in all four of Wisconsin’s Lake Michigan AOCs. Although neither richness nor diversity of phytoplankton or zooplankton in the Sheboygan River AOC were found to differ significantly from the non-AOC sites in 2012, results from the 2014 data indicated that zooplankton diversity was significantly lower, and so rated as degraded, when compared to the Manitowoc and Kewaunee Rivers, two non-AOC sites of similar size, land use, and close geographic proximity.
As a follow-up to the 2014 results, zooplankton samples were collected at the same locations in the AOC and non-AOC sites during three sampling trips in spring, summer, and fall 2016. An analysis of similarity indicated no significant difference between the zooplankton community composition and structure in the AOC and non-AOC sites. Zooplankton taxa richness in the AOC was rated as “not degraded” in 2016 because of significantly higher taxa richness values in samples collected from the Sheboygan River AOC, compared with the non-AOC sites as a group (that is, data pooled from both non-AOC sites). Zooplankton diversity in 2016, however, was characterized as “degraded” in the AOC on the basis of significantly lower (p<0.05) values in samples collected from the AOC compared with those collected from the non-AOC sites as a group. Annual variation in zooplankton community composition and structure at the Sheboygan River AOC was significantly different among all 3 years sampled, as indicated by an analysis of similarity test. Zooplankton richness was significantly higher in 2014 than in both 2012 and 2016, and diversity was significantly higher in 2012 than in both 2014 and 2016. Postremediation recovery can often be complicated by non-AOC-related stressors such as nutrients, invasive species, and extremes in flow, which could affect the recovery of zooplankton communities in the Sheboygan River AOC. The effect of the stressors on postremediation recovery underscores the importance of sampling multiple years when assessing the effectiveness of remediation activities. The results from this study will be used by the Wisconsin Department of Natural Resources and the U.S. Environmental Protection Agency to determine if restoration efforts have been effective in removing the plankton BUI and to monitor future conditions in the AOC.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20175131","collaboration":"Prepared in cooperation with the Wisconsin Department of Natural Resources and the U.S. Environmental Protection Agency","usgsCitation":"Olds, H.T., Scudder Eikenberry, B.C., Burns, D.J., and Bell, A.H., 2017, An evaluation of the zooplankton community at the Sheboygan River Area of Concern and non-Area of Concern comparison sites in western Lake Michigan rivers and harbors in 2016: U.S. Geological Survey Scientific Investigations Report 2017–5131, 15 p., https://doi.org/10.3133/sir20175131.\n","productDescription":"Report: vii, 15 p.; Data Release","numberOfPages":"28","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-090820","costCenters":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"links":[{"id":349967,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2017/5131/sir20175131.pdf","text":"Report","size":"2.36 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2017-5131"},{"id":349966,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2017/5131/coverthb.jpg"},{"id":349968,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7QV3KD9","text":"USGS data release","linkHelpText":"Zooplankton Community Data at the Sheboygan River Area of Concern and Non-Areas of Concern Comparison Sites in Western Lake Michigan Rivers and Harbors in 2016"}],"country":"United States","state":"Wisconsin","otherGeospatial":"Lake Michigan","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -87.7313232421875,\n 43.74530493763506\n ],\n [\n -87.4676513671875,\n 43.74530493763506\n ],\n [\n -87.4676513671875,\n 44.484749436619964\n ],\n [\n -87.7313232421875,\n 44.484749436619964\n ],\n [\n -87.7313232421875,\n 43.74530493763506\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Upper Midwest Water Science Center
U.S. Geological Survey
8505 Research Way
Middleton, WI 53562
Low-temperature hydrous pyrolysis (LTHP) at 300°C (572°F) for 24 h released retained oils from 12- to 20-meshsize samples of mature Niobrara marly chalk and marlstone cores. The released oil accumulated on the water surface of the reactor, and is compositionally similar to oil produced from the same well. The quantities of oil released from the marly chalk and marlstone by LTHP are respectively 3.4 and 1.6 times greater than those determined by tight rock analyses (TRA) on aliquots of the same samples. Gas chromatograms indicated this difference is a result of TRA oils losing more volatiles and volatilizing less heavy hydrocarbons during collection than LTHP oils. Characterization of the rocks before and after LTPH by programmable open-system pyrolysis (HAWK) indicate that under LTHP conditions no significant oil is generated and only preexisting retained oil is released. Although LTHP appears to provide better predictions of quantity and quality of retained oil in a mature source rock, it is not expected to replace the more time and sample-size efficacy of TRA. However, LTHP can be applied to composited samples from key intervals or lithologies originally recognized by TRA. Additional studies on duration, temperature, and sample size used in LTHP may further optimize its utility.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":" Unconventional Resources Technology Conference","largerWorkSubtype":{"id":12,"text":"Conference publication"},"language":"English","publisher":" Unconventional Resources Technology Conference","usgsCitation":"Lewan, M., and Sonnenfeld, M.D., 2017, Determining quantity and quality of retained oil in mature marly chalk and marlstone of the Cretaceous Niobrara Formation by low-temperature hydrous pyrolysis, in Unconventional Resources Technology Conference, 8 p.","productDescription":"8 p.","ipdsId":"IP-085370","costCenters":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":350077,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":347665,"type":{"id":15,"text":"Index Page"},"url":"https://archives.datapages.com/data/urtec/2017/2670700.htm"}],"publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5a60faf9e4b06e28e9c22a57","contributors":{"authors":[{"text":"Lewan, Michael 0000-0001-6347-1553 mlewan@usgs.gov","orcid":"https://orcid.org/0000-0001-6347-1553","contributorId":173938,"corporation":false,"usgs":true,"family":"Lewan","given":"Michael","email":"mlewan@usgs.gov","affiliations":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true},{"id":255,"text":"Energy Resources Program","active":true,"usgs":true}],"preferred":true,"id":717546,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Sonnenfeld, Mark D.","contributorId":198886,"corporation":false,"usgs":false,"family":"Sonnenfeld","given":"Mark","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":717547,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70197329,"text":"70197329 - 2017 - A new sulfur and carbon degassing inventory for the Southern Central American Volcanic Arc: The importance of accurate time-series datasets and possible tectonic processes responsible for temporal variations in arc-scale volatile emissions","interactions":[],"lastModifiedDate":"2018-05-29T15:54:39","indexId":"70197329","displayToPublicDate":"2017-12-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1757,"text":"Geochemistry, Geophysics, Geosystems","active":true,"publicationSubtype":{"id":10}},"title":"A new sulfur and carbon degassing inventory for the Southern Central American Volcanic Arc: The importance of accurate time-series datasets and possible tectonic processes responsible for temporal variations in arc-scale volatile emissions","docAbstract":"This work presents a new database of SO2 and CO2 fluxes from the Southern Central American Volcanic Arc (SCAVA) for the period 2015–2016. We report ∼300 SO2 flux measurements from 10 volcanoes and gas ratios from 11 volcanoes in Costa Rica and Nicaragua representing the most extensive available assessment of this ∼500 km arc segment. The SO2 flux from SCAVA is estimated at 6,240 ± 1,150 T/d, about a factor of three higher than previous estimations (1972–2013). We attribute this increase in part to our more complete assessment of the arc. Another consideration in interpreting the difference is the context of increased volcanic activity, as there were more eruptions in 2015–2016 than in any period since ∼1980. A potential explanation for increased degassing and volcanic activity is a change in crustal stress regime (from compression to extension, opening volcanic conduits) following two large (Mw > 7) earthquakes in the region in 2012. The CO2 flux from the arc is estimated at 22,500 ± 4,900 T/d, which is equal to or greater than estimates of C input into the SCAVA subduction zone. Time‐series data sets for arc degassing need to be improved in temporal and spatial coverage to robustly constrain volatile budgets and tectonic controls. Arc volatile budgets are strongly influenced by short‐lived degassing events and arc systems likely display significant short‐term variations in volatile output, calling for expansion of nascent geochemical monitoring networks to achieve spatial and temporal coverage similar to traditional geophysical networks.
","language":"English","publisher":"American Geophysical Union","doi":"10.1002/2017GC007141","usgsCitation":"de Moor, M., Kern, C., Avard, G., Muller, C., Aiuppa, S., Saballos, A., Ibarra, M., LaFemina, P., Protti, M., and Fischer, T., 2017, A new sulfur and carbon degassing inventory for the Southern Central American Volcanic Arc: The importance of accurate time-series datasets and possible tectonic processes responsible for temporal variations in arc-scale volatile emissions: Geochemistry, Geophysics, Geosystems, v. 18, no. 12, p. 4437-4468, https://doi.org/10.1002/2017GC007141.","productDescription":"32 p.","startPage":"4437","endPage":"4468","ipdsId":"IP-092011","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":469272,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/2017gc007141","text":"Publisher Index Page"},{"id":354550,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"18","issue":"12","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2017-12-12","publicationStatus":"PW","scienceBaseUri":"5b155e00e4b092d9651e1b9e","contributors":{"authors":[{"text":"de Moor, Maarten","contributorId":173676,"corporation":false,"usgs":false,"family":"de Moor","given":"Maarten","email":"","affiliations":[{"id":27271,"text":"Observatorio Volcanológico y Sismológico de Costa Rica, Universidad Nacional, Heredia, Costa Rica","active":true,"usgs":false}],"preferred":false,"id":736690,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"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":617,"text":"Volcano Science Center","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":736689,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Avard, Geoffroy","contributorId":173679,"corporation":false,"usgs":false,"family":"Avard","given":"Geoffroy","email":"","affiliations":[{"id":27271,"text":"Observatorio Volcanológico y Sismológico de Costa Rica, Universidad Nacional, Heredia, Costa Rica","active":true,"usgs":false}],"preferred":false,"id":736691,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Muller, Cyril","contributorId":205255,"corporation":false,"usgs":false,"family":"Muller","given":"Cyril","email":"","affiliations":[{"id":37066,"text":"OVSICORI","active":true,"usgs":false}],"preferred":false,"id":736692,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Aiuppa, Sandro","contributorId":205256,"corporation":false,"usgs":false,"family":"Aiuppa","given":"Sandro","email":"","affiliations":[{"id":25431,"text":"University of Palermo","active":true,"usgs":false}],"preferred":false,"id":736693,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Saballos, Armando","contributorId":205257,"corporation":false,"usgs":false,"family":"Saballos","given":"Armando","email":"","affiliations":[{"id":37067,"text":"INETER","active":true,"usgs":false}],"preferred":false,"id":736694,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Ibarra, Martha","contributorId":205258,"corporation":false,"usgs":false,"family":"Ibarra","given":"Martha","email":"","affiliations":[{"id":37067,"text":"INETER","active":true,"usgs":false}],"preferred":false,"id":736695,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"LaFemina, Peter","contributorId":205259,"corporation":false,"usgs":false,"family":"LaFemina","given":"Peter","affiliations":[{"id":7260,"text":"Pennsylvania State University","active":true,"usgs":false}],"preferred":false,"id":736696,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Protti, Mario","contributorId":205260,"corporation":false,"usgs":false,"family":"Protti","given":"Mario","affiliations":[{"id":37066,"text":"OVSICORI","active":true,"usgs":false}],"preferred":false,"id":736697,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Fischer, Tobias","contributorId":205261,"corporation":false,"usgs":false,"family":"Fischer","given":"Tobias","affiliations":[{"id":36307,"text":"University of New Mexico","active":true,"usgs":false}],"preferred":false,"id":736698,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}} ,{"id":70194473,"text":"70194473 - 2017 - Constraining the magmatic system at Mount St. Helens (2004–2008) using Bayesian inversion with physics-based models including gas escape and crystallization","interactions":[],"lastModifiedDate":"2017-11-29T10:34:41","indexId":"70194473","displayToPublicDate":"2017-11-29T00:00:00","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":"Constraining the magmatic system at Mount St. Helens (2004–2008) using Bayesian inversion with physics-based models including gas escape and crystallization","docAbstract":"Physics-based models of volcanic eruptions track conduit processes as functions of depth and time. When used in inversions, these models permit integration of diverse geological and geophysical data sets to constrain important parameters of magmatic systems. We develop a 1-D steady state conduit model for effusive eruptions including equilibrium crystallization and gas transport through the conduit and compare with the quasi-steady dome growth phase of Mount St. Helens in 2005. Viscosity increase resulting from pressure-dependent crystallization leads to a natural transition from viscous flow to frictional sliding on the conduit margin. Erupted mass flux depends strongly on wall rock and magma permeabilities due to their impact on magma density. Including both lateral and vertical gas transport reveals competing effects that produce nonmonotonic behavior in the mass flux when increasing magma permeability. Using this physics-based model in a Bayesian inversion, we link data sets from Mount St. Helens such as extrusion flux and earthquake depths with petrological data to estimate unknown model parameters, including magma chamber pressure and water content, magma permeability constants, conduit radius, and friction along the conduit walls. Even with this relatively simple model and limited data, we obtain improved constraints on important model parameters. We find that the magma chamber had low (<5wt%) total volatiles and that the magma permeability scale is well constrained at ~10-11.4 m2 to reproduce observed dome rock porosities. Compared with previous results, higher magma overpressure and lower wall friction are required to compensate for increased viscous resistance while keeping extrusion rate at the observed value.
","language":"English","publisher":"American Geophysical Union","doi":"10.1002/2017JB014343","usgsCitation":"Wong, Y., Segall, P., Bradley, A., and Anderson, K.R., 2017, Constraining the magmatic system at Mount St. Helens (2004–2008) using Bayesian inversion with physics-based models including gas escape and crystallization: Journal of Geophysical Research B: Solid Earth, v. 122, no. 10, p. 7789-7812, https://doi.org/10.1002/2017JB014343.","productDescription":"34 p.","startPage":"7789","endPage":"7812","ipdsId":"IP-086340","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":469293,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://www.osti.gov/biblio/1411224","text":"External Repository"},{"id":349506,"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 -122.63214111328125,\n 45.94160076422081\n ],\n [\n -121.77246093750001,\n 45.94160076422081\n ],\n [\n -121.77246093750001,\n 46.494610770689384\n ],\n [\n -122.63214111328125,\n 46.494610770689384\n ],\n [\n -122.63214111328125,\n 45.94160076422081\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"122","issue":"10","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2017-10-30","publicationStatus":"PW","scienceBaseUri":"5a60fafce4b06e28e9c22a90","contributors":{"authors":[{"text":"Wong, Ying-Qi","contributorId":200978,"corporation":false,"usgs":false,"family":"Wong","given":"Ying-Qi","email":"","affiliations":[],"preferred":false,"id":723991,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Segall, Paul","contributorId":75942,"corporation":false,"usgs":true,"family":"Segall","given":"Paul","affiliations":[],"preferred":false,"id":723992,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bradley, Andrew","contributorId":200980,"corporation":false,"usgs":false,"family":"Bradley","given":"Andrew","affiliations":[],"preferred":false,"id":723993,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Anderson, Kyle R. 0000-0001-8041-3996 kranderson@usgs.gov","orcid":"https://orcid.org/0000-0001-8041-3996","contributorId":3522,"corporation":false,"usgs":true,"family":"Anderson","given":"Kyle","email":"kranderson@usgs.gov","middleInitial":"R.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":723990,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70209685,"text":"70209685 - 2017 - Magnetotelluric imaging of lower crustal melt and lithospheric hydration in the Rocky Mountain Front transition zone, Colorado, USA","interactions":[],"lastModifiedDate":"2020-04-21T16:08:17.708545","indexId":"70209685","displayToPublicDate":"2017-11-06T11:01:32","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":"Magnetotelluric imaging of lower crustal melt and lithospheric hydration in the Rocky Mountain Front transition zone, Colorado, USA","docAbstract":"We present an electrical resistivity model of the crust and upper mantle from two‐dimensional (2‐D) anisotropic inversion of magnetotelluric data collected along a 450 km transect of the Rio Grande rift, southern Rocky Mountains, and High Plains in Colorado, USA. Our model provides a window into the modern‐day lithosphere beneath the Rocky Mountain Front to depths in excess of 150 km. Two key features of the 2‐D resistivity model are (1) a broad zone (~200 km wide) of enhanced electrical conductivity (<20 Ωm) in the midcrust to lower crust that is centered beneath the highest elevations of the southern Rocky Mountains and (2) hydrated lithospheric mantle beneath the Great Plains with water content in excess of 100 ppm. We interpret the high conductivity region of the lower crust as a zone of partially molten basalt and associated deep‐crustal fluids that is the result of recent (less than 10 Ma) tectonic activity in the region. The recent supply of volatiles and/or heat to the base of the crust in the late Cenozoic implies that modern‐day tectonic activity in the western United States extends to at least the western margin of the Great Plains. The transition from conductive to resistive upper mantle is caused by a gradient in lithospheric modification, likely including hydration of nominally anhydrous minerals, with maximum hydration occurring beneath the Rocky Mountain Front. This lithospheric “hydration front” has implications for the tectonic evolution of the continental interior and the mechanisms by which water infiltrates the lithosphere.
","language":"English","publisher":"American Geophysical Union","doi":"10.1002/2017JB014474","collaboration":"","usgsCitation":"Feucht, D., Sheehan, A.F., and Bedrosian, P.A., 2017, Magnetotelluric imaging of lower crustal melt and lithospheric hydration in the Rocky Mountain Front transition zone, Colorado, USA: Journal of Geophysical Research B: Solid Earth, v. 122, no. 12, p. 9489-9510, https://doi.org/10.1002/2017JB014474.","productDescription":"22 p.","startPage":"9489","endPage":"9510","ipdsId":"IP-091898","costCenters":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"links":[{"id":469344,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/2017jb014474","text":"Publisher Index Page"},{"id":374159,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Colorado","otherGeospatial":"Rocky Mountains ","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -109.061279296875,\n 37.01132594307015\n ],\n [\n -102.052001953125,\n 37.01132594307015\n ],\n [\n -102.052001953125,\n 40.98819156349393\n ],\n [\n -109.061279296875,\n 40.98819156349393\n ],\n [\n -109.061279296875,\n 37.01132594307015\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"122","issue":"12","noUsgsAuthors":false,"publicationDate":"2017-12-04","publicationStatus":"PW","contributors":{"authors":[{"text":"Feucht, D. W. 0000-0002-3672-4719","orcid":"https://orcid.org/0000-0002-3672-4719","contributorId":224277,"corporation":false,"usgs":false,"family":"Feucht","given":"D. W.","affiliations":[],"preferred":false,"id":787515,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Sheehan, Anne F 0000-0002-9629-1687","orcid":"https://orcid.org/0000-0002-9629-1687","contributorId":224234,"corporation":false,"usgs":false,"family":"Sheehan","given":"Anne","email":"","middleInitial":"F","affiliations":[{"id":36621,"text":"University of Colorado","active":true,"usgs":false}],"preferred":false,"id":787516,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bedrosian, Paul A. 0000-0002-6786-1038 pbedrosian@usgs.gov","orcid":"https://orcid.org/0000-0002-6786-1038","contributorId":839,"corporation":false,"usgs":true,"family":"Bedrosian","given":"Paul","email":"pbedrosian@usgs.gov","middleInitial":"A.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true},{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":787517,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70196515,"text":"70196515 - 2017 - Organic chemical characterization and mass balance of a hydraulically fractured well: From fracturing fluid to produced water over 405 days","interactions":[],"lastModifiedDate":"2018-04-12T16:04:25","indexId":"70196515","displayToPublicDate":"2017-11-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1565,"text":"Environmental Science & Technology","onlineIssn":"1520-5851","printIssn":"0013-936X","active":true,"publicationSubtype":{"id":10}},"title":"Organic chemical characterization and mass balance of a hydraulically fractured well: From fracturing fluid to produced water over 405 days","docAbstract":"A long-term field study (405 days) of a hydraulically fractured well from the Niobrara Formation in the Denver-Julesburg Basin was completed. Characterization of organic chemicals used in hydraulic fracturing and their changes through time, from the preinjected fracturing fluid to the produced water, was conducted. The characterization consisted of a mass balance by dissolved organic carbon (DOC), volatile organic analysis by gas chromatography/mass spectrometry, and nonvolatile organic analysis by liquid chromatography/mass spectrometry. DOC decreased from 1500 mg/L in initial flowback to 200 mg/L in the final produced water. Only ∼11% of the injected DOC returned by the end of the study, with this 11% representing a maximum fraction returned since the formation itself contributes DOC. Furthermore, the majority of returning DOC was of the hydrophilic fraction (60–85%). Volatile organic compound analysis revealed substantial concentrations of individual BTEX compounds (0.1–11 mg/L) over the 405-day study. Nonvolatile organic compounds identified were polyethylene glycols (PEGs), polypropylene glycols (PPG), linear alkyl-ethoxylates, and triisopropanolamine (TIPA). The distribution of PEGs, PPGs, and TIPA and their ubiquitous presence in our samples and the literature illustrate their potential as organic tracers for treatment operations or in the event of an environmental spill.
","language":"English","publisher":"ACS","doi":"10.1021/acs.est.7b03362","usgsCitation":"Rosenblum, J., Thurman, E.M., Ferrer, I., Aiken, G.R., and Linden, K.G., 2017, Organic chemical characterization and mass balance of a hydraulically fractured well: From fracturing fluid to produced water over 405 days: Environmental Science & Technology, v. 51, no. 23, p. 14006-14015, https://doi.org/10.1021/acs.est.7b03362.","productDescription":"10 p.","startPage":"14006","endPage":"14015","ipdsId":"IP-090640","costCenters":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"links":[{"id":353385,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"51","issue":"23","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2017-11-22","publicationStatus":"PW","scienceBaseUri":"5afee7c6e4b0da30c1bfc36e","contributors":{"authors":[{"text":"Rosenblum, James","contributorId":204203,"corporation":false,"usgs":false,"family":"Rosenblum","given":"James","email":"","affiliations":[{"id":30224,"text":"Univeristy of Colorado Boulder","active":true,"usgs":false}],"preferred":false,"id":733354,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Thurman, E. Michael","contributorId":9636,"corporation":false,"usgs":true,"family":"Thurman","given":"E.","email":"","middleInitial":"Michael","affiliations":[],"preferred":false,"id":733355,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ferrer, Imma","contributorId":169362,"corporation":false,"usgs":false,"family":"Ferrer","given":"Imma","email":"","affiliations":[{"id":25480,"text":"Univ of Colorado, Boulder","active":true,"usgs":false}],"preferred":false,"id":733356,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Aiken, George R. 0000-0001-8454-0984 graiken@usgs.gov","orcid":"https://orcid.org/0000-0001-8454-0984","contributorId":1322,"corporation":false,"usgs":true,"family":"Aiken","given":"George","email":"graiken@usgs.gov","middleInitial":"R.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":733353,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Linden, Karl G.","contributorId":194690,"corporation":false,"usgs":false,"family":"Linden","given":"Karl","email":"","middleInitial":"G.","affiliations":[],"preferred":false,"id":733357,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70194076,"text":"70194076 - 2017 - Updated polychlorinated biphenyl mass budget for Lake Michigan","interactions":[],"lastModifiedDate":"2017-11-17T10:39:46","indexId":"70194076","displayToPublicDate":"2017-11-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1565,"text":"Environmental Science & Technology","onlineIssn":"1520-5851","printIssn":"0013-936X","active":true,"publicationSubtype":{"id":10}},"title":"Updated polychlorinated biphenyl mass budget for Lake Michigan","docAbstract":"This study revisits and updates the Lake Michigan Mass Balance Project (LMMBP) for polychlorinated biphenyls (PCBs) that was conducted in 1994–1995. This work uses recent concentrations of PCBs in tributary and open lake water, air, and sediment to calculate an updated mass budget. Five of the 11 LMMBP tributaries were revisited in 2015. In these five tributaries, the geometric mean concentrations of ∑PCBs (sum of 85 congeners) ranged from 1.52 to 22.4 ng L–1. The highest concentrations of PCBs were generally found in the Lower Fox River and in the Indiana Harbor and Ship Canal. The input flows of ∑PCBs from wet deposition, dry deposition, tributary loading, and air to water exchange, and the output flows due to sediment burial, volatilization from water to air, and transport to Lake Huron and through the Chicago Diversion were calculated, as well as flows related to the internal processes of settling, resuspension, and sediment–water diffusion. The net transfer of ∑PCBs is 1240 ± 531 kg yr–1 out of the lake. This net transfer is 46% lower than that estimated in 1994–1995. PCB concentrations in most matrices in the lake are decreasing, which drove the decline of all the individual input and output flows. Atmospheric deposition has become negligible, while volatilization from the water surface is still a major route of loss, releasing PCBs from the lake into the air. Large masses of PCBs remain in the water column and surface sediments and are likely to contribute to the future efflux of PCBs from the lake to the air.
","language":"English","publisher":"ACS Publications","doi":"10.1021/acs.est.7b02904","usgsCitation":"Guo, J., Romanak, K., Westenbroek, S.M., Li, A., Kreis, R., Hites, R.A., and Venier, M., 2017, Updated polychlorinated biphenyl mass budget for Lake Michigan: Environmental Science & Technology, v. 51, no. 21, p. 12455-12465, https://doi.org/10.1021/acs.est.7b02904.","productDescription":"11 p.","startPage":"12455","endPage":"12465","ipdsId":"IP-087835","costCenters":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"links":[{"id":349052,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Lake Michigan","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -88.13232421875,\n 41.52502957323801\n ],\n [\n -84.7705078125,\n 41.52502957323801\n ],\n [\n -84.7705078125,\n 46.118941506107056\n ],\n [\n -88.13232421875,\n 46.118941506107056\n ],\n [\n -88.13232421875,\n 41.52502957323801\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"51","issue":"21","publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"noUsgsAuthors":false,"publicationDate":"2017-10-17","publicationStatus":"PW","scienceBaseUri":"5a60fb22e4b06e28e9c22d11","contributors":{"authors":[{"text":"Guo, Jiehong","contributorId":191232,"corporation":false,"usgs":false,"family":"Guo","given":"Jiehong","email":"","affiliations":[],"preferred":false,"id":722008,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Romanak, Kevin","contributorId":191234,"corporation":false,"usgs":false,"family":"Romanak","given":"Kevin","affiliations":[],"preferred":false,"id":722009,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Westenbroek, Stephen M. 0000-0002-6284-8643 smwesten@usgs.gov","orcid":"https://orcid.org/0000-0002-6284-8643","contributorId":2210,"corporation":false,"usgs":true,"family":"Westenbroek","given":"Stephen","email":"smwesten@usgs.gov","middleInitial":"M.","affiliations":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true},{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":722007,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Li, An","contributorId":200536,"corporation":false,"usgs":false,"family":"Li","given":"An","email":"","affiliations":[],"preferred":false,"id":722010,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Kreis, Russell","contributorId":200345,"corporation":false,"usgs":false,"family":"Kreis","given":"Russell","email":"","affiliations":[],"preferred":false,"id":722011,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Hites, Ronald A.","contributorId":191235,"corporation":false,"usgs":false,"family":"Hites","given":"Ronald","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":722012,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Venier, Marta","contributorId":191233,"corporation":false,"usgs":false,"family":"Venier","given":"Marta","email":"","affiliations":[],"preferred":false,"id":722013,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70194442,"text":"70194442 - 2017 - Tree sampling as a method to assess vapor intrusion potential at a site characterized by VOC-contaminated groundwater and soil","interactions":[],"lastModifiedDate":"2017-11-29T13:19:10","indexId":"70194442","displayToPublicDate":"2017-11-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1565,"text":"Environmental Science & Technology","onlineIssn":"1520-5851","printIssn":"0013-936X","active":true,"publicationSubtype":{"id":10}},"title":"Tree sampling as a method to assess vapor intrusion potential at a site characterized by VOC-contaminated groundwater and soil","docAbstract":"Vapor intrusion (VI) by volatile organic compounds (VOCs) in the built environment presents a threat to human health. Traditional VI assessments are often time-, cost-, and labor-intensive; whereas traditional subsurface methods sample a relatively small volume in the subsurface and are difficult to collect within and near structures. Trees could provide a similar subsurface sample where roots act as the “sampler’ and are already onsite. Regression models were developed to assess the relation between PCE concentrations in over 500 tree-core samples with PCE concentrations in over 50 groundwater and 1000 soil samples collected from a tetrachloroethylene- (PCE-) contaminated Superfund site and analyzed using gas chromatography. Results indicate that in planta concentrations are significantly and positively related to PCE concentrations in groundwater samples collected at depths less than 20 m (adjusted R2 values greater than 0.80) and in soil samples (adjusted R2 values greater than 0.90). Results indicate that a 30 cm diameter tree characterizes soil concentrations at depths less than 6 m over an area of 700–1600 m2, the volume of a typical basement. These findings indicate that tree sampling may be an appropriate method to detect contamination at shallow depths at sites with VI.
","language":"English","publisher":"ACS Publications","doi":"10.1021/acs.est.7b02667","usgsCitation":"Wilson, J.L., Limmer, M.A., Samaranayake, V., Schumacher, J., and Burken, J.G., 2017, Tree sampling as a method to assess vapor intrusion potential at a site characterized by VOC-contaminated groundwater and soil: Environmental Science & Technology, v. 51, no. 18, p. 10369-10378, https://doi.org/10.1021/acs.est.7b02667.","productDescription":"10 p.","startPage":"10369","endPage":"10378","ipdsId":"IP-083556","costCenters":[{"id":396,"text":"Missouri Water Science Center","active":true,"usgs":true}],"links":[{"id":438169,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F71835D8","text":"USGS data release","linkHelpText":"Tetrachloroethylene, trichloroethylene, and 1,1,2-Trichloro-1,2,2-trifluoroethane concentrations in tree-core, groundwater, and soil samples at the Vienna Wells Site: Maries County, Missouri, 2011-2016"},{"id":349537,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Missouri","city":"Vienna","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -91.9442,\n 38.1883\n ],\n [\n -91.9417,\n 38.1883\n ],\n [\n -91.9417,\n 38.19\n ],\n [\n -91.9442,\n 38.19\n ],\n [\n -91.9442,\n 38.1883\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"51","issue":"18","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationDate":"2017-08-31","publicationStatus":"PW","scienceBaseUri":"5a60fb21e4b06e28e9c22d02","contributors":{"authors":[{"text":"Wilson, Jordan L. 0000-0003-0490-9062 jlwilson@usgs.gov","orcid":"https://orcid.org/0000-0003-0490-9062","contributorId":5416,"corporation":false,"usgs":true,"family":"Wilson","given":"Jordan","email":"jlwilson@usgs.gov","middleInitial":"L.","affiliations":[{"id":396,"text":"Missouri Water Science Center","active":true,"usgs":true},{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":723833,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Limmer, Matthew A.","contributorId":200927,"corporation":false,"usgs":false,"family":"Limmer","given":"Matthew","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":723834,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Samaranayake, V.A.","contributorId":200928,"corporation":false,"usgs":false,"family":"Samaranayake","given":"V.A.","affiliations":[],"preferred":false,"id":723835,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Schumacher, John G. jschu@usgs.gov","contributorId":2055,"corporation":false,"usgs":true,"family":"Schumacher","given":"John G.","email":"jschu@usgs.gov","affiliations":[{"id":396,"text":"Missouri Water Science Center","active":true,"usgs":true}],"preferred":true,"id":723836,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Burken, Joel G.","contributorId":21218,"corporation":false,"usgs":true,"family":"Burken","given":"Joel","email":"","middleInitial":"G.","affiliations":[],"preferred":false,"id":723837,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70191270,"text":"sir20175112 - 2017 - Hydrogeology and water quality of sand and gravel aquifers in McHenry County, Illinois, 2009–14, and comparison to conditions in 1979","interactions":[],"lastModifiedDate":"2026-04-01T15:55:08.73","indexId":"sir20175112","displayToPublicDate":"2017-10-26T00:00:00","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":"2017-5112","displayTitle":"Hydrogeology and Water Quality of Sand and Gravel Aquifers in McHenry County, Illinois, 2009–14, and Comparison to Conditions in 1979","title":"Hydrogeology and water quality of sand and gravel aquifers in McHenry County, Illinois, 2009–14, and comparison to conditions in 1979","docAbstract":"Baseline conditions for the sand and gravel aquifers (groundwater) in McHenry County, Illinois, were assessed using data from a countywide network of 44 monitoring wells collecting continuous water-level data from 2009–14. In 2010, water-quality data were collected from 41 of the monitoring wells, along with five additional monitoring wells available from the U.S. Geological Survey National Water Quality Assessment Program. Periodic water-quality data were collected from 2010–14 from selected monitoring wells. The continuous water-level data were used to identify the natural and anthropogenic factors that influenced the water levels at each well. The water-level responses to natural influences such as precipitation, seasonal and annual variations, barometric pressure, and geology, and to anthropogenic influences such as pumping were used to determine (1) likely hydrogeologic setting (degree of aquifer confinement and interconnections) that, in part, are related to lithostratigraphy; and (2) areas of recharge and discharge related to vertical flow directions. Water-level trends generally were determined from the 6 years of data collection (2009–14) to infer effects of weather variability (drought) on recharge.
Precipitation adds an estimated 2.4 inches per year of recharge to the aquifer. Some of this recharge is subsequently discharged to streams and some is discharged to supply wells. A few areas in the eastern half of the county had higher average recharge rates, indicating a need for adequate protection of these recharge areas. Downward vertical flow gradients in upland areas indicate that recharge to the confined aquifer units occurs near upland areas. Upward vertical flow gradients in lowland areas indicate discharge at locations of surface water and groundwater interaction (wetlands, ponds, and streams).
Monitoring wells were sampled for major and minor ions, metals, and nutrients and a subset of wells was sampled for trace elements, dissolved gases, pesticides, and volatile organic compounds. The results were compared to health‑based and aesthetically based standards, which include the U.S. Environmental Protection Agency Maximum Contaminant Level (EPA MCL), and EPA Secondary Maximum Contaminant Levels (SMCL), as well as EPA Health-based Standards Drinking Water Advisories. Health‑based standards were exceeded for arsenic in 22 percent, sodium in 20 percent, and nitrates in 2 percent of the monitoring wells sampled. Aesthetically based standards were exceeded for total dissolved solids in 33 percent, chloride in 11 percent, iron in 85 percent, and manganese in 30 percent of the wells sampled. Many of these same constituents, such as arsenic, iron, and manganese, are naturally occurring but become elevated in areas that have anoxic, mixed, and suboxic conditions. Some areas of potential vulnerability to anthropogenic-sourced constituents in the sand and gravel aquifers were evidenced by trace amounts of volatile organic compounds and pesticides detected in water-quality samples from shallow wells (total depth less of than 46 feet below land surface) near urban settings, and by the detection of elevated major ions (chloride, sodium, magnesium, and calcium) associated, in part, with road-salt applications. Source analysis for chloride indicates mixtures of road salt, water softeners, and sewage.
Continuously measured specific conductance values were used as a surrogate for continuously measured chloride concentrations in the groundwater. The estimated chloride concentrations generally were highest in spring and lowest in summer, and occasionally peak during spring melt. Overall, the range of concentrations varied depending on the local thickness and hydraulic conductivity of the aquifer.
Water levels and water quality from the countywide groundwater monitoring network were compared to water levels and water-quality results in 1979 from a previous U.S. Geological Survey study. Potentiometric surface maps show areas with inferred decreases of water levels near the southern and southeastern areas of McHenry County. Significant increases were noted for total dissolved solids and specific conductance. Chloride concentrations increased as much as 521 percent in three of six wells resampled in 2015 from the previous study.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20175112","collaboration":"Prepared in cooperation with McHenry County, Illinois","usgsCitation":"Gahala, A.M., 2017, Hydrogeology and water quality of sand and gravel aquifers in McHenry County, Illinois, 2009–14, and comparison to conditions in 1979 (ver. 1.1, August 2022): U.S. Geological Survey Scientific Investigations Report 2017–5112, 91 p., https://doi.org/10.3133/sir20175112.","productDescription":"ix, 91 p.","numberOfPages":"106","onlineOnly":"Y","ipdsId":"IP-067438","costCenters":[{"id":344,"text":"Illinois Water Science Center","active":true,"usgs":true}],"links":[{"id":404906,"rank":3,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/sir/2017/5112/versionHist.txt","text":"Version History","size":"1.36 kB","linkFileType":{"id":2,"text":"txt"}},{"id":404904,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2017/5112/coverthb2.jpg"},{"id":347422,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2017/5112/sir20175112.pdf","text":"Report","size":"6.67 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2017-5112"},{"id":501947,"rank":4,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_106395.htm","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"Illinois","county":"McHenry County","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"Polygon\",\"coordinates\":[[[-88.3016,42.4979],[-88.1971,42.4981],[-88.1979,42.4562],[-88.1974,42.4167],[-88.1966,42.3286],[-88.1994,42.2432],[-88.1992,42.1555],[-88.2382,42.155],[-88.3539,42.1547],[-88.4703,42.1552],[-88.5891,42.1556],[-88.7061,42.1564],[-88.7057,42.2418],[-88.7041,42.329],[-88.705,42.4167],[-88.7059,42.4972],[-88.6737,42.4977],[-88.6288,42.4985],[-88.5047,42.4981],[-88.4099,42.4977],[-88.3016,42.4979]]]},\"properties\":{\"name\":\"McHenry\",\"state\":\"IL\"}}]}","edition":"Version 1.0: October 26, 2017; Version 1.1: August 17, 2022","contact":"Director, Illinois Water Science Center
U.S. Geological Survey
405 N Goodwin
Urbana, IL 61801