Five integrator sites on streams draining mixed land-use watersheds were sampled monthly from July 2016 to June 2017. Two sites were sampled in the San Joaquin River watershed and one site was sampled in each of the Mokelumne River, Sacramento River, and Ulatis Creek watersheds.
A total of 53 out of 154 pesticides (18 herbicides, 14 insecticides, 13 fungicides, 7 breakdown products, and 1 synergist) were detected in surface-water samples and 95 percent of samples contained mixtures of 2 or more pesticides. The most frequently detected pesticides were the herbicides hexazinone, metolachlor, and diuron (present in 83 percent, 72 percent, and 67 percent of water samples, respectively), the insecticide methoxyfenozide (present in 83 percent of samples), and the fungicides boscalid and azoxystrobin (present in 67 percent and 58 percent of samples, respectively). Pesticide concentrations detected in water samples ranged from below method detection limits to 1,300 nanograms per liter (ng/L) for the insecticide chlorantraniliprole. A total of 4 pesticides (2 herbicides and 2 insecticides) were detected in suspended-sediment samples and 13 percent of suspended-sediment samples contained at least 1 pesticide. Pesticide concentrations detected in suspended-sediment samples ranged from 4.1 to 750 ng/L, both for the herbicide pendimethalin.
Six samples contained the insecticide imidacloprid at concentrations above the U.S. Environmental Protection Agency (EPA) Aquatic Life Benchmark (10 ng/L) for chronic toxicity to aquatic invertebrates. Three samples contained bifenthrin at concentrations above the EPA Aquatic Life Benchmark (1.3 ng/L) for chronic toxicity to invertebrates. One sample contained cyhalothrin at a concentration above the U.S. Aquatic Life Benchmark (3.5 ng/L) for acute toxicity to invertebrates.
Director, California Water Science Center
U.S. Geological Survey
6000 J Street, Placer Hall
Sacramento, California 95819
Identifying sources of sediment to streams in the Sprague River Basin, in south-central Oregon, is important for restoration efforts that are focused on reducing sediment erosion and transport. Reducing sediment loads in these streams also contributes to compliance with the total maximum daily load reduction requirements for total phosphorus in this basin. In the Sprague River Basin, phosphorus occurs in surface waters in both dissolved phase and particulate phase, and particulate phosphorus is readily transported in streams on fine-grained suspended sediments, which eventually deposit in Upper Klamath Lake. The lake has seasonal blooms of cyanobacteria that require phosphorus for growth and degrade water-quality conditions, violating State water-quality standards and creating conditions that are stressful to two endangered suckers that reside in the lake. Identifying sources of sediment to the Sprague River could help inform restoration actions by determining the principal locations in the basin contributing fine sediment to the river. The U.S. Geological Survey, in cooperation with the U.S. Fish and Wildlife Service, conducted a proof-of-concept study to determine if sediment fingerprinting can differentiate sources of bank erosion by source material, basin, river reach, and soil horizon. The sediment fingerprinting approach uses properties of streambank and streambed sediment to differentiate between multiple sediment sources by determining a composite signature, or fingerprint. The composite fingerprint is established by combining fingerprint properties from laboratory results of elemental analysis, stable isotopes, and total carbon and nitrogen. The methods for differentiating sediment samples for this study include grouping bank and bed samples by basin, river reach, and soil horizon, and using non-parametric statistics to determine which fingerprint properties could be used to differentiate the sample groups. Results indicate that fingerprint properties differentiated source material, river reach, and basin, and were more successful at differentiating samples grouped by geographic location (basin and reach) compared to source material. Source material (banks, bed, levees) were differentiated with three fingerprint properties—Antimony (Sb), copper (Cu), and manganese (Mn). The basin category (South Fork and main-stem Sprague River) differentiated the South Fork and main stem with stable nitrogen isotopes (δ15N), aluminum (Al), silicon (Si), and vanadium (V). Specific river reaches within the study area were differentiated with 11 different fingerprint properties. These results can be used for apportionment studies using suspended sediment samples and mixing models to determine sediment source contributions within the basin.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20191120","collaboration":"Prepared in cooperation with U.S. Fish and Wildlife Service","usgsCitation":"Schenk, L.N., Harden, T.M., and Kelson, J.K., 2019, Differentiating sediment sources using sediment fingerprinting techniques, in the Sprague River Basin, south-central Oregon: U.S. Geological Survey Open-File Report 2019-1120, 25 p., https://doi.org/10.3133/ofr20191120.","productDescription":"Report: vi, 25 p.; 2 Tables; Appendix","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-106755","costCenters":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"links":[{"id":369299,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2019/1120/ofr20191120.pdf","text":"Report","size":"7.4 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2019-1120"},{"id":369302,"rank":5,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2019/1120/ofr20191120_appendix1.xlsx","text":"Appendix 1 –","size":"41 KB","linkFileType":{"id":3,"text":"xlsx"},"description":"OFR 2019-1120 Appendix 1","linkHelpText":" Analytical Results and Site Characteristics"},{"id":369298,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2019/1120/coverthb.jpg"},{"id":369300,"rank":3,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/of/2019/1120/ofr20191120_table03.xlsx","text":"Table 3","size":"21 KB","linkFileType":{"id":3,"text":"xlsx"},"description":"OFR 2019-1120 Table 3"},{"id":369301,"rank":4,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/of/2019/1120/ofr20191120_table05.xlsx","text":"Table 5","size":"28 KB","linkFileType":{"id":3,"text":"xlsx"},"description":"OFR 2019-1120 Table 5"}],"country":"United States","state":"Oregon","otherGeospatial":"Sprague River Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.947998046875,\n 41.95949009892467\n ],\n [\n -119.21264648437499,\n 41.95949009892467\n ],\n [\n -119.21264648437499,\n 44.04811573082351\n ],\n [\n -122.947998046875,\n 44.04811573082351\n ],\n [\n -122.947998046875,\n 41.95949009892467\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Oregon Water Science Center
U.S. Geological Survey
2130 SW 5th Avenue
Portland, Oregon 97201
Trace-metal concentrations in sediment and in the clam Macoma petalum (formerly reported as Macoma balthica), clam reproductive activity, and benthic macroinvertebrate community structure were investigated in a mudflat 1 kilometer south of the discharge of the Palo Alto Regional Water Quality Control Plant (PARWQCP) in south San Francisco Bay, Calif. This report includes the data collected by U.S. Geological Survey (USGS) scientists for the period January 2018 to December 2018. These append to long-term datasets extending back to 1974. A major focus of the report is an integrated description of the 2018 data within the context of the longer, multi-decadal dataset. This dataset supports the City of Palo Alto’s Near-Field Receiving-Water Monitoring Program, initiated in 1994.
Significant reductions in silver and copper concentrations in both sediment and M. petalum occurred at the site in the 1980s following the implementation by PARWQCP of advanced wastewater treatment and source control measures. Since the 1990s, concentrations of these elements appear to have stabilized at concentrations somewhat above (silver [Ag]) or near (copper [Cu]) regional background concentrations. Data for other metals, including chromium (Cr), mercury (Hg), nickel (Ni), selenium (Se), and zinc (Zn), have been collected since 1994. Over this period, concentrations of these elements have remained relatively constant, aside from seasonal variation that is common to all elements. In 2018, concentrations of silver and copper in M. petalum varied seasonally in response to a combination of site-specific metal exposures and annual growth and reproduction, as reported previously. Seasonal patterns for other elements, including Cr, Ni, Zn, Hg, and Se, were generally similar in timing and magnitude as those for Ag and Cu. This record suggests that legacy contamination and regional-scale factors now largely control sedimentary and bioavailable concentrations of silver and copper, as well as other elements of regulatory interest, at the Palo Alto site.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20191084","collaboration":"Prepared in cooperation with the City of Palo Alto, California","usgsCitation":"Cain, D.J., Thompson, J.K., Parchaso, F., Pearson, S., Stewart, R., Turner, M., Shrader, K.H., Zierdt Smith, E.L., and Luoma, S.N., 2019, Near-field receiving-water monitoring of trace metals and a benthic community near the Palo Alto Regional Water Quality Control Plant in south San Francisco Bay, California—2018: U.S. Geological Survey Open-File Report 2019–1084, 41 p., https://doi.org/10.3133/ofr20191084.","productDescription":"vi, 41 p.","numberOfPages":"41","onlineOnly":"Y","ipdsId":"IP-109149","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":37464,"text":"WMA - Laboratory & Analytical Services Division","active":true,"usgs":true}],"links":[{"id":416180,"rank":3,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/ofr20161118","text":"Open-File Report 2016-1118","linkHelpText":"- Near-field receiving water monitoring of trace metals and a benthic community near the Palo Alto Regional Water Quality Control Plant in south San Francisco Bay, California; 2015"},{"id":416181,"rank":4,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/ofr20171135","text":"Open-File Report 2017-1135","linkHelpText":"- Near-field receiving water monitoring of trace metals and a benthic community near the Palo Alto Regional Water Quality Control Plant in south San Francisco Bay, California; 2016"},{"id":416182,"rank":5,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/ofr20181107","text":"Open-File Report 2018-1107","linkHelpText":"- Near-field receiving-water monitoring of trace metals and a benthic community near the Palo Alto Regional Water Quality Control Plant in south San Francisco Bay, California—2017"},{"id":416184,"rank":6,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/ofr20211079","text":"Open-File Report 2021-1079","linkHelpText":"- Near-Field Receiving-Water Monitoring of Trace Metals and a Benthic Community Near the Palo Alto Regional Water Quality Control Plant in South San Francisco Bay, California—2019"},{"id":368964,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2019/1084/ofr20191084.pdf","text":"Report","size":"6 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Open-FIle Report 2019-1084"},{"id":368963,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2019/1084/coverthb.jpg"},{"id":416185,"rank":7,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/ofr20231017","text":"Open-File Report 2023-1017","linkHelpText":"- Near-Field Receiving-Water Monitoring of Trace Metals and a Benthic Community Near the Palo Alto Regional Water Quality Control Plant in South San Francisco Bay, California—2020"}],"country":"United States","state":"California","otherGeospatial":"Palo Alto Regional Water Quality Control Plant","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.14187622070311,\n 37.43179575348695\n ],\n [\n -122.08419799804689,\n 37.43179575348695\n ],\n [\n -122.08419799804689,\n 37.48085213924346\n ],\n [\n -122.14187622070311,\n 37.48085213924346\n ],\n [\n -122.14187622070311,\n 37.43179575348695\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director,
Earth System Processes Division
U.S. Geological Survey
411 National Center
12201 Sunrise Valley Drive
Reston, VA 20192
Caged mussels used as biomonitors can provide insights about ambient contaminant assemblages and spatial patterns, sources of contaminants, and contaminant exposure risks for consumers of wild and farmed mussels. This study explored the potential role of ambient sediment in the uptake of polycyclic aromatic hydrocarbons (PAHs), polychlorinated biphenyls (PCBs), and potentially toxic inorganic elements by caged mussels and complements findings from a Puget Sound-wide stormwater-contaminant mussel-monitoring survey in Washington State. In summary, ambient sediment appeared to be related to mussel uptake of lead and possibly copper at all sites, PCBs at industrial sites, and PAHs at Liberty Bay, Eagle Harbor, and, to a lesser extent, Smith Cove. These findings indicate that resuspended bed sediment is one, but not the only, pathway that filter-feeding mussels are exposed to contaminants. Overall, PAHs, PCBs, arsenic, and potentially toxic metals were low in intertidal bed sediment at the nine sites measured in Puget Sound in February 2016 and signify a low risk of sediment-bound contaminant exposure to mussels at those locations.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20191087","usgsCitation":"Takesue, R.K., Campbell, P.L., and Conn, K.E., 2019, Polycyclic aromatic hydrocarbons, polychlorinated biphenyls, and metals in ambient sediment at mussel biomonitoring sites, Puget Sound, Washington: U.S. Geological Survey Open-File Report 2019–1087, 15 p., https://doi.org/10.3133/ofr20191087.","productDescription":"Report: vi, 15 p.","numberOfPages":"15","onlineOnly":"Y","ipdsId":"IP-102107","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true},{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"links":[{"id":366767,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2019/1087/ofr20191087.pdf","text":"Report","size":"10 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Open-File Report 2019-1087"},{"id":366766,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2019/1087/coverthb.jpg"}],"country":"United States","state":"Washington","otherGeospatial":"Puget Sound","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -125.3759765625,\n 47.03269459852135\n ],\n [\n -121.83837890625,\n 47.03269459852135\n ],\n [\n -121.83837890625,\n 48.98382212608503\n ],\n [\n -125.3759765625,\n 48.98382212608503\n ],\n [\n -125.3759765625,\n 47.03269459852135\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Contact Information
Pacific Coastal & Marine Science Center
U.S. Geological Survey
Pacific Science Center
2885 Mission St.
Santa Cruz, CA 95060
The Stochastic Empirical Loading and Dilution Model (SELDM) was developed by the U.S. Geological Survey (USGS) in cooperation with the Federal Highway Administration to simulate stormwater quality. To assess the effects of runoff, SELDM uses a stochastic mass-balance approach to estimate combinations of pre-storm streamflow, stormflow, highway runoff, event mean concentrations (EMCs) and stormwater constituent loads from a site of interest. In addition, SELDM can be used to assess the effects of stormwater Best Management Practices (BMPs), which are designed to mitigate the adverse effects of runoff into a waterbody.
Adverse effects of stormwater on receiving waters are one of the greatest unsolved water-quality problems Nationwide. State DOTs, municipalities, Federal facilities, and private property owners who manage impervious surfaces need information about the potential magnitude of their contributions and the potential effectiveness of methods to mitigate the adverse effects of runoff. Because the efficacy of at-site controls are limited, information about the potential effectiveness of alternative strategies is needed.
The USGS, in cooperation with the Oregon Department of Transportation (ODOT), conducted a study to research methods in which SELDM can be used to enhance the efficiency of ODOT’s stormwater program, support the development of a stormwater banking program, and meet environmental goals. Results can be used to develop a strategic, systems-level approach to stormwater management by considering entire watersheds instead of individual road crossings. Two watersheds, Bear Creek and Mill Creek, in western Oregon were selected for analysis. Within each watershed, seven road crossings were selected for demonstrating the utility of SELDM in nested basins.
Precipitation statistics, pre-storm streamflow, runoff coefficients, and hydrograph recession factors were calculated for each location and used in SELDM to simulate flow, water-quality concentrations, and constituent loads in the upstream basin, from the highway (or developed area), and downstream from the road crossing. Three water-quality constituents were selected for modeling: suspended-sediment concentration (SSC), total phosphorus (TP), and total copper (TCu). Using water-quality transport curves, the relations between streamflow and SSC and between streamflow and TP were simulated. Concentrations of TCu were simulated by configuring a linear relation between SSC and TCu. A generic BMP was simulated using the median treatment statistics for flow reductions, hydrograph extensions, concentration reductions, and minimum irreducible concentrations from nine BMP categories with data from the 2012 International BMP database.
Five simulation scenarios were modeled for demonstrative purposes. These simulations were used to evaluate potential effects of different watershed properties, water-quality inputs, and stormwater mitigation measures. Instream EMCs were compared to hypothetical water-quality criteria for suspended sediment, total phosphorus, and total copper to demonstrate the concept of water-quality risk analysis. For all five scenarios, it was assumed that highway runoff concentrations were independent of location or average annual daily traffic. These five scenarios are as follows:
• Simulation Scenario 1—Natural Conditions (hereafter Simulation Scenario 1) represents conditions in an undeveloped watershed. This scenario demonstrates that the strategic placement of a hypothetical road crossing within a watershed could be used to avoid exceeding water-quality standards of TP and SSC, but that no location choice results in meeting TCu standards. Implementation of BMP had the most pronounced effects on downstream water-quality constituent EMCs at road crossings with the highest ratio of highway catchment area to upstream drainage area, but the largest effect of BMP treatment on mean annual load is based on highway catchment area alone.
• Simulation Scenario 2—Current Conditions (hereafter Simulation Scenario 2) represents current watershed conditions, where all developed area upstream from the road crossing was modeled as a highway and combined with the undeveloped part of the upstream drainage area (scenario 2A) and where the output from scenario 2A is used for the upstream area (developed area and the undeveloped area), and where the road crossing is added as usual (scenario 2B). Scenario 2 results indicate that attaining water-quality standards is more difficult with upstream developed areas. Specific road-crossing sites can be selected to achieve the fewest water-quality exceedances per year, but water-quality targets are not met without BMP implementation, and in some instances are not achievable even with BMP implementation. Results from this scenario also serve to quantify the upper limit of constituent reduction if funding were available to implement BMPs to large areas of development, and to quantify how much area would need BMP implementation to achieve water-quality targets.
• Simulation Scenario 3—Alternative Road Layouts (hereafter Simulation Scenario 3) was designed to assess the sensitivity of SELDM to various road layouts. In this scenario, different highway configurations were superimposed at one road crossing. Results indicate that downstream waterquality constituent EMCs did not exhibit much variation, but annual water-quality constituent loads varied considerably.
• Simulation Scenario 4—Varying Road Width (hereafter Simulation Scenario 4) was designed to assess the sensitivity of SELDM to road width. Similar to scenario 3, the results indicate little variation in downstream water-quality constituent EMCs, but annual water-quality constituent loads increased in proportion to road width.
• Simulation scenario 5—Changes to Impervious Area (hereafter Simulation Scenario 5) was designed to investigate the effects of changing amounts of imperviousness upstream from the road crossing. Results indicate that the downstream water-quality constituent EMCs are highly correlated with the percentage of impervious area upstream.
Director, Oregon Water Science Center
U.S. Geological Survey
2130 SW 5th Avenue
Portland, Oregon 97201
The San Juan-Silverton caldera complex located near Silverton, Colorado, in the Southern Rocky Mountains volcanic field is an ideal natural laboratory for furthering the understanding of shallow-to-deep volcanic-related mineral systems. Recent advances in geophysical data processing and three-dimensional (3D) model construction will help to characterize shallow properties important for understanding surface water and groundwater quality issues and will also improve knowledge of deep geological structures that may have been conduits for hydrothermal fluids that formed mineral deposits. The study has general applications to mineral resource assessments in other areas of the world and to identifying possible groundwater flow paths and associated geochemistry important in abandoned mine lands cleanup.
Silverton, Colorado, is the site of a spectacular succession of igneous rocks that formed beginning about 35 million years ago (Ma). Base metals (copper, lead, and zinc) and precious metals (silver and gold) mined from the late 1870s to 1991 owe their existence to a 25-million-year cycle of igneous activity. The presence of economic, base, and precious metal deposits within a complex geological setting were largely responsible for stimulating studies by the U.S. Geological Survey (USGS) conducted during the early 20th century. The focus of investigations in the late 20th and 21st centuries have broadened in scope to include abandoned mine lands (AML) investigations. The legacy of hard rock mining in headwater catchment areas caused environmental challenges for local communities and downstream water resource users. The Gold King Mine, located a few kilometers north of Silverton, illustrates the potential environmental effects of abandoned mines. On August 5, 2015, during reclamation efforts at the Gold King Mine, a breach of collapsed workings sent approximately 3 million gallons of acidic and metal-rich mine water into the upper Animas River, a tributary to the Colorado River Basin. Mining-related sources of metals and acidity add to geological sources of metals in surface water and groundwater. Weathering processes of altered and mineralized rock have been a source of acid rock drainage that have been ongoing for millennia.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston VA","doi":"10.3133/fs20193026","collaboration":"Prepared in collaboration with U.S. Forest Service, Bureau of Land Management, U.S. Environmental Protection Agency, Colorado Division of Reclamation Mining and Safety, Colorado Department of Public Health and Environment, and Animas River Stakeholders Group","usgsCitation":"Yager, D.B., Anderson, E.D., Rodriguez, B.D., Deszcz-Pan, M., and Smith, B.D., 2019, Geological and geophysical data for a three-dimensional view—Inside the San Juan and Silverton calderas, Southern Rocky Mountains volcanic field, Silverton, Colorado: U.S. Geological Survey Fact Sheet 2019-3026, 4 p., https://doi.org/10.3133/fs20193026.","productDescription":"4 p.","onlineOnly":"N","ipdsId":"IP-103569","costCenters":[{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"links":[{"id":364304,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2019/3026/coverthb.jpg"},{"id":364305,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2019/3026/fs20193026.pdf","text":"Report","size":"8.83 MB","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2019-3026"}],"country":"United States","state":"Colorado","county":"San Juan County","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"Polygon\",\"coordinates\":[[[-107.5857,37.9702],[-107.5786,37.9667],[-107.5721,37.9636],[-107.5632,37.9573],[-107.5584,37.9524],[-107.5549,37.9493],[-107.5502,37.9475],[-107.5361,37.9445],[-107.5319,37.9414],[-107.5324,37.9378],[-107.5347,37.9337],[-107.5352,37.9291],[-107.5351,37.9237],[-107.532,37.9178],[-107.5278,37.9088],[-107.5247,37.9039],[-107.5212,37.9007],[-107.5211,37.8967],[-107.5279,37.8875],[-107.5324,37.8806],[-107.5329,37.8748],[-107.5317,37.8734],[-107.5305,37.8716],[-107.5204,37.8618],[-107.5179,37.8554],[-107.5184,37.8486],[-107.5176,37.84],[-107.5146,37.8342],[-107.5127,37.8288],[-107.5121,37.8265],[-107.5109,37.8256],[-107.5068,37.8243],[-107.491,37.8236],[-107.4828,37.8223],[-107.4757,37.817],[-107.4705,37.8143],[-107.4669,37.8107],[-107.4627,37.8044],[-107.4578,37.7918],[-107.457,37.785],[-107.4581,37.7791],[-107.4666,37.7668],[-107.4677,37.7645],[-107.4695,37.7645],[-107.4777,37.768],[-107.4812,37.7684],[-107.4829,37.7675],[-107.484,37.7648],[-107.4824,37.7407],[-107.4832,37.6374],[-107.6698,37.6372],[-107.6849,37.6375],[-107.6867,37.6375],[-107.9686,37.6377],[-107.9628,37.6401],[-107.96,37.6415],[-107.9583,37.6429],[-107.9572,37.6456],[-107.9572,37.6479],[-107.9579,37.6524],[-107.9604,37.6592],[-107.9629,37.6646],[-107.966,37.6718],[-107.9685,37.6777],[-107.9698,37.6822],[-107.9699,37.6867],[-107.9688,37.6899],[-107.966,37.6936],[-107.9615,37.6977],[-107.9575,37.7005],[-107.9534,37.7024],[-107.9505,37.7029],[-107.9471,37.7029],[-107.9389,37.7017],[-107.936,37.7017],[-107.9331,37.7027],[-107.9274,37.706],[-107.9239,37.7074],[-107.9181,37.7079],[-107.9135,37.7098],[-107.9094,37.7112],[-107.9049,37.7154],[-107.9014,37.7168],[-107.8968,37.7173],[-107.8904,37.717],[-107.8817,37.7162],[-107.8764,37.7163],[-107.8747,37.7172],[-107.873,37.7213],[-107.8726,37.7259],[-107.8733,37.7317],[-107.8717,37.7368],[-107.8684,37.7431],[-107.8644,37.7477],[-107.8627,37.7509],[-107.8622,37.7537],[-107.8629,37.7559],[-107.8641,37.7582],[-107.8659,37.76],[-107.8677,37.7617],[-107.8683,37.7635],[-107.8672,37.7663],[-107.8615,37.7732],[-107.8592,37.7737],[-107.854,37.7742],[-107.8493,37.7734],[-107.8446,37.7721],[-107.8423,37.7721],[-107.84,37.7726],[-107.8354,37.7767],[-107.8275,37.7859],[-107.8224,37.7915],[-107.8213,37.7928],[-107.8225,37.7955],[-107.8268,37.8063],[-107.8263,37.8082],[-107.8258,37.81],[-107.8085,37.8207],[-107.8056,37.8212],[-107.8004,37.8212],[-107.7975,37.8213],[-107.7952,37.8222],[-107.7935,37.8236],[-107.7918,37.8277],[-107.7885,37.8332],[-107.7868,37.8355],[-107.7845,37.8378],[-107.7812,37.8451],[-107.7762,37.8556],[-107.7756,37.857],[-107.7768,37.8592],[-107.7781,37.8615],[-107.7741,37.8656],[-107.7655,37.8739],[-107.7553,37.8845],[-107.7479,37.8923],[-107.7422,37.8982],[-107.7359,37.9038],[-107.7188,37.8977],[-107.7077,37.8955],[-107.7024,37.892],[-107.6977,37.8912],[-107.6942,37.8917],[-107.6897,37.8967],[-107.6879,37.8976],[-107.6862,37.899],[-107.6839,37.9],[-107.681,37.9],[-107.6682,37.9011],[-107.6595,37.9039],[-107.6514,37.9081],[-107.6422,37.9146],[-107.6394,37.9187],[-107.6389,37.9237],[-107.6404,37.9368],[-107.6405,37.9404],[-107.6407,37.9491],[-107.6385,37.9545],[-107.635,37.9586],[-107.6263,37.9588],[-107.6216,37.9588],[-107.6077,37.9636],[-107.5961,37.9669],[-107.588,37.9688],[-107.5857,37.9702]]]},\"properties\":{\"name\":\"San Juan\",\"state\":\"CO\"}}]}","contact":"Director, Geology, Geophysics, and Geochemistry Science Center
U.S. Geological Survey
Box 25046, MS-964
Denver, CO 80225-0046
The Cornwall and Devon vein- and greisen-type copper and tin deposits of southwest England are spatially and genetically related to shallow-seated granitic intrusions. These late Variscan intrusions, collectively known as the Cornubian Batholith, extend over 200 km and form a continuous granitic spine from the Isles of Scilly Granite in the west to the Dartmoor Granite in the east. The granitic plutons of the Cornubian Batholith were intruded from ~ 295 to 270 Ma without a major hiatus. Twelve samples of cassiterite (SnO2) were obtained from tin deposits associated with seven different plutons within the Cornubian Batholith for in situ LA-ICPMS U–Pb dating. This study of cassiterite was undertaken to obtain the first results of direct dating of ore mineral to refine the geochronology of tin mineralization in this region. Of the cassiterite samples analyzed, the oldest ages were determined within the Kit Hill and Hingston–Gunnislake Granites in the central part of the Cornubian Batholith. The Hingston–Gunnislake cassiterite, from Drakewalls Mine, was the oldest sample dated at 291.8 ± 3.4 Ma. The next oldest dates, 290.5 ± 2.8 and 288.5 ± 2.9 Ma, were from two cassiterite samples extracted from the adjacent Kit Hill Consolidated Mines within the Kit Hill Granite. At the eastern end of the study area, two cassiterite samples within the Dartmoor Granite produced ages of 286.0 ± 1.8 and 284.1 ± 1.3 Ma. The youngest sample from this study, 275.4 ± 1.6 Ma, is from the Balleswidden Mine within the westernmost Land’s End Granite. The cassiterite dates do not reveal any readily observable relationship between ore ages and geographic relationship from west to east throughout the Cornubian Batholith. Incorporating the associated errors, the geochronology does indicate continuous mineralization within the granites for ~ 21 million years, from ca. 295 to 274 Ma. This span falls within the established period of granitic magmatism of ca. 295 to 270 Ma for the Cornubian Batholith and further confirms the reliability of in situ LA-ICPMS U–Pb dating of cassiterite.
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rmoscati@usgs.gov","orcid":"https://orcid.org/0000-0002-0818-4401","contributorId":2462,"corporation":false,"usgs":true,"family":"Moscati","given":"Richard","email":"rmoscati@usgs.gov","middleInitial":"J.","affiliations":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":761521,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Neymark, Leonid A. 0000-0003-4190-0278 lneymark@usgs.gov","orcid":"https://orcid.org/0000-0003-4190-0278","contributorId":140338,"corporation":false,"usgs":true,"family":"Neymark","given":"Leonid A.","email":"lneymark@usgs.gov","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true},{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":761522,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70202880,"text":"70202880 - 2019 - Sources, timing, and fate of sediment and contaminants in the nearshore: insights from geochemistry","interactions":[],"lastModifiedDate":"2019-04-10T09:17:17","indexId":"70202880","displayToPublicDate":"2019-03-31T09:16:17","publicationYear":"2019","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":18,"text":"Abstract or summary"},"title":"Sources, timing, and fate of sediment and contaminants in the nearshore: insights from geochemistry","docAbstract":"Rivers in Cascade watersheds carry sediment with a volcanic composition that is distinct from the plutonic composition of the Puget lowlands. Compositional properties (signatures) allow discrimination of river-sourced Cascade from lowland sediment, and inferences about transport pathways. Surface sediment on land contains atmospheric radionuclides whose known decay rates define monthly (7Be) and decadal (210Pb) timescales of sediment inputs from land to nearshore regions. We used geochemical signatures to source river-borne sediment in two urban embayments in Cascade watersheds: Commencement Bay (CB) and Bellingham Bay (BB). We concurrently determined sediment contaminant levels and, in CB, used geochemical aging to distinguish contaminants in recent winter outflow from those that were pre-existing. Methods are described in Takesue et al. (2017). Geochemical signatures showed that Puyallup River (PU)-sourced fine sediment (<63 µm) accumulated more along the northeast (NE) shore of CB than the southwest: median 91% and 69%, respectively. River-sourced sediment from recent winter storms, containing higher 7Be activities (open circles, Fig. 1A), also accumulated on the NE shore and had lower contents of PAHs, fecal sterols, PCBs, and potentially toxic metals (TM) compared to the south shore; only PBDEs were higher (column graphs, Fig. 1A). Lower 7Be and 210Pb activities in south shore sediment indicated that contaminants there were associated with older sediment. Existing sediment in CB contained higher levels of urban contaminants than new PU material. No PAH, PCB, or TM levels in CB exceeded Washington State marine sediment quality standards (WAMSQS). Geochemical signatures were not distinct in the Nooksack River watershed and lowlands, precluding sediment sourcing in BB. PAH ratios in BB sediments were ubiquitous (open circles, Fig. 1B), suggesting atmospheric rather than riverine transport, and had values indicating biomass/coal combustion sources, except for three sites along the urban waterfront that had values indicative of vehicle emissions (closed circles, Fig. 1B). Elevated TM occurred offshore of Fairhaven (cadmium, Cd; copper, Cu; lead, Pb; zinc, Zn), Whatcom Creek Waterway (Pb, Zn), and the marina (Cu, Zn). No PAH or TM concentrations in BB exceeded WAMSQS. Insights gained from sediment geochemistry about the sources, timing, transport, and fate of riverborne fine sediment and contaminants in nearshore regions are valuable components of monitoring programs that can help guide habitat restoration and resource management decisions toward effective and sustainable outcomes.","largerWorkTitle":"2018 Salish Sea Toxics Monitoring Synthesis: A Selection of Research","conferenceTitle":"2018 Salish Sea Ecosystem Conference","conferenceDate":"April 3-6, 2018","conferenceLocation":"Seattle, Washington","language":"English","publisher":"Puget Sound Ecosystem Monitoring Program","usgsCitation":"Takesue, R.K., Conn, K., and Dutch, M., 2019, Sources, timing, and fate of sediment and contaminants in the nearshore: insights from geochemistry, in 2018 Salish Sea Toxics Monitoring Synthesis: A Selection of Research, Seattle, Washington, April 3-6, 2018, p. 62-62.","productDescription":"1 p.","startPage":"62","endPage":"62","ipdsId":"IP-099363","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":362876,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":362653,"type":{"id":15,"text":"Index Page"},"url":"https://www.eopugetsound.org/articles/2018-salish-sea-toxics-monitoring-synthesis"}],"country":"United States","state":"Washington","otherGeospatial":"Puget Sound","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.71393775939941,\n 47.06579564376744\n ],\n [\n -122.67788887023924,\n 47.06579564376744\n ],\n [\n -122.67788887023924,\n 47.09694798930915\n ],\n [\n -122.71393775939941,\n 47.09694798930915\n ],\n [\n -122.71393775939941,\n 47.06579564376744\n ]\n ]\n ]\n }\n }\n ]\n}","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Takesue, Renee K. 0000-0003-1205-0825 rtakesue@usgs.gov","orcid":"https://orcid.org/0000-0003-1205-0825","contributorId":2159,"corporation":false,"usgs":true,"family":"Takesue","given":"Renee","email":"rtakesue@usgs.gov","middleInitial":"K.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":760370,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Conn, Kathleen E. 0000-0002-2334-6536 kconn@usgs.gov","orcid":"https://orcid.org/0000-0002-2334-6536","contributorId":3923,"corporation":false,"usgs":true,"family":"Conn","given":"Kathleen E.","email":"kconn@usgs.gov","affiliations":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"preferred":true,"id":760371,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Dutch, Margaret","contributorId":214606,"corporation":false,"usgs":false,"family":"Dutch","given":"Margaret","email":"","affiliations":[{"id":25353,"text":"Washington State Department of Ecology","active":true,"usgs":false}],"preferred":false,"id":760372,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70204108,"text":"70204108 - 2019 - Emerging investigator series: Atmospheric cycling of indium in the northeastern United States","interactions":[],"lastModifiedDate":"2019-07-05T16:44:46","indexId":"70204108","displayToPublicDate":"2019-03-28T16:35:21","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1566,"text":"Environmental Science: Processes and Impacts","active":true,"publicationSubtype":{"id":10}},"title":"Emerging investigator series: Atmospheric cycling of indium in the northeastern United States","docAbstract":"Indium is critical to the global economy and is used in an increasing number of electronics and new energy technologies. However, little is known about its environmental behavior or impacts, including its concentrations or cycling in the atmosphere. This study determined indium concentrations in air particulate matter at five locations across the northeastern United States over the course of one year, in 1995. Historical records from a Massachusetts bog core showed that indium atmospheric concentrations in this region changed only modestly between 1995 and 2010. Atmospheric indium concentrations varied significantly both geographically and temporally, with average concentrations in PM3 of 2.1 ± 1.6 pg m−3 (1 standard deviation), and average particle-normalized concentrations of 0.2 ± 0.2 μg In per g PM3. Peaks in the particle-normalized concentrations in two New York sites were correlated with wind direction; air coming from the north contributed higher concentrations of indium than air coming from the west. This correlation, along with measurements of indium in zinc smelter emissions and coal fly ash, suggests that indium in the atmosphere in the northeastern United States comes from a relatively constant low-level input from coal combustion in the midwest, and higher but more sporadic contributions from the smelting of lead, zinc, copper, tin, and nickel north of the New York sample sites. Understanding the industrial sources of indium to the atmosphere and how they compare with natural sources can lead to a better understanding of the impact of human activities on the indium cycle, and may help to establish a baseline for monitoring future impacts as indium use grows.
","language":"English","publisher":"Royal Society of Chemistry","doi":"10.1039/c8em00485d","usgsCitation":"White, S.J., and Hemond, H.F., 2019, Emerging investigator series: Atmospheric cycling of indium in the northeastern United States: Environmental Science: Processes and Impacts, v. 21, no. 4, p. 623-634, https://doi.org/10.1039/c8em00485d.","productDescription":"12 p.","startPage":"623","endPage":"634","ipdsId":"IP-104440","costCenters":[{"id":245,"text":"Eastern Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"links":[{"id":365317,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Massachusetts, New York","city":"Boston, Brockport, Reading, Rochester, Thoreau's Bog","otherGeospatial":"Quabbin Reservoir","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -78.31054687499999,\n 42.89206418807337\n ],\n [\n -77.18994140625,\n 42.89206418807337\n ],\n [\n -77.18994140625,\n 43.389081939117496\n ],\n [\n -78.31054687499999,\n 43.389081939117496\n ],\n [\n -78.31054687499999,\n 42.89206418807337\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -72.4658203125,\n 42.049292638686836\n ],\n [\n -71.015625,\n 42.049292638686836\n ],\n [\n -71.015625,\n 42.68243539838623\n ],\n [\n -72.4658203125,\n 42.68243539838623\n ],\n [\n -72.4658203125,\n 42.049292638686836\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"21","issue":"4","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"White, Sarah Jane 0000-0002-4055-8207","orcid":"https://orcid.org/0000-0002-4055-8207","contributorId":216796,"corporation":false,"usgs":true,"family":"White","given":"Sarah","email":"","middleInitial":"Jane","affiliations":[{"id":245,"text":"Eastern Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":765551,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hemond, Harold F.","contributorId":34673,"corporation":false,"usgs":false,"family":"Hemond","given":"Harold","email":"","middleInitial":"F.","affiliations":[{"id":13299,"text":"Department of Civil and Environmental Engineering, Massachusetts Institute of Technology, Cambridge, MA","active":true,"usgs":false}],"preferred":false,"id":765552,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70212534,"text":"70212534 - 2019 - Tectono-magmatic evolution of porphyry belts in the central Tethys region of Turkey, the Caucasus, Iran, western Pakistan, and southern Afghanistan","interactions":[],"lastModifiedDate":"2020-08-19T17:20:59.562078","indexId":"70212534","displayToPublicDate":"2019-03-19T11:38:30","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2954,"text":"Ore Geology Reviews","active":true,"publicationSubtype":{"id":10}},"title":"Tectono-magmatic evolution of porphyry belts in the central Tethys region of Turkey, the Caucasus, Iran, western Pakistan, and southern Afghanistan","docAbstract":"Exploration in the central Tethys region of Turkey, Armenia, Azerbaijan, Georgia, Iran, and western Pakistan has led to the identification of the giant Reko Diq (24 Mt Cu and 1300 t Au), Sar Cheshmeh (8.9 Mt Cu and 0.46 Mt Mo), Sungun (5.1 Mt Cu and 0.20 Mt Mo), and Kadjaran (4.6 Mt Cu, 0.94 Mt Mo, and 1100 t Au), and 10 other large (1–2 Mt Cu) porphyry deposits including Saindak, Cevizlidere, Teghout, Meiduk, and Halilağa. Continued exploration efforts have also resulted in the development of porphyry-related gold deposits such as Kişladağ (9.6 Moz Au), Çöpler (3.7 Moz Au), Aği Daği (1.7 Moz Au), and Sary Gunay (3.0 Moz Au), and in the generation of several other promising exploration projects.
The distribution in space and time of porphyry deposits in the central Tethys region was shaped by complex pre- to post-mineral tectonic, igneous, collisional, uplift and burial events. These events are represented by a partially-overlapping and variably exhumed and covered collage of twenty-six Early Jurassic to Holocene magmatic belts permissive for the occurrence of porphyry deposits (porphyry tracts and sub-tracts). Twelve tracts or sub-tracts are characterized by compressional continental arcs that formed on drifting terranes or continental margins, 10 developed in compressional to extensional intra-oceanic arc and backarc-rift settings, and 4 formed in extensional post-collisional environments over amalgamated terranes. Eight of these belts were variably affected by coeval and younger metamorphic, fold-and-thrust, and extensional faulting events.
Fifty-four porphyry Au-(Cu), Cu-Au, Cu-Mo, Mo-Cu deposits, 15 porphyry-related Au, Au-(Mo) and W-(Mo-Au) deposits, 239 porphyry prospects, and 68 other porphyry-related mineral sites were identified in the study region. Of the 376 porphyry and porphyry-related sites, about 11% formed in island arc, 42% in continental arc, 20% in backarc, and 27% in post-collisional settings. Of the 69 porphyry and porphyry-related deposits, 7% developed in intra-oceanic arc, 41% in continental arc, 27% in backarc, and 25% in post-collisional settings. The largest occur in either compressional continental arc (18 deposits including the Reko Diq and Sar Cheshmeh giants) or post-collisional (13 deposits including the Kadjaran and Sungun giants) environments. Ninety percent of the largest porphyry or porphyry-related deposits occur in only 9 of the 26 permissive porphyry tracts or sub-tracts. Moreover, 88, 90, and 77% of the identified Cu, Mo, and Au resources are contained in porphyry deposits that occur in only 4 of these 9 tracts. Of these 4 tracts, 3 outline arc settings, and one delimits a post-collisional environment.
The compositional diversity of porphyry intrusions in these tectono-magmatic environments generally varies from island arc settings with the most restricted range (partly alkaline but mainly calc-alkaline dioritic to granodioritic-tonalitic), to continental arc (calc-alkaline dioritic-quartz dioritic, granodioritic, quartz monzonitic-granitic, and less commonly mildly alkaline), to backarc (mildly alkaline and calc-alkaline dioritic to granitic), to post-collisional settings with the most expansive range (alkaline and calc-alkaline mafic to felsic, and weakly peraluminous). Metal associations also vary broadly as a function of porphyry intrusion composition from weakly peraluminous to metaluminous felsic (Mo[±W ± Cu]; <2% of porphyry-related systems [i.e., Tyrnyauz]), to metaluminous felsic and intermediate (Cu-Mo[±Au]; 85% [i.e., Cevizlidere, Haft Cheshmeh, Kahang, Sar Cheshmeh, Sungun, Teghout, Reko Diq, Saindak]), to mildly alkaline felsic and intermediate (Cu-Au[±Mo] [i.e., Agarak, Kadjaran, Kale Kafi]) and mafic (Au-Cu; 12% [i.e., Çöpler]), and to alkaline felsic (Au-Mo; 1% of porphyry-related systems [i.e., Kişladağ).
Tectonic changes were critical in triggering the formation of large porphyry deposits in the region. Large porphyry deposits were preferentially emplaced in continental arc settings shortly before major collisional events (Dar Alu, Kahang, Meiduk, Now Chun, and the giant Sar Cheshmeh and Reko Diq deposits), or in post-subduction environments shortly after collision (Bakirçay, Güzelyayla, Haft Cheshmeh, Masjed Daghi, and the giant Kadjaran and Sungun deposits) or during periods of prominent extension (Aği Daği, Halilağa, Kişladağ, Sari Gunay, and Zarshuran porphyry-related deposits). Collision-induced uplift, erosion, and removal of coeval volcanic rocks favorably exposed the hypabyssal level of subduction-related porphyry deposits. Extensional structures that developed parallel and orthogonal to the compressional principal stress component along transtensional or transpressional strike-slip faults or in pull-apart basins commonly controlled porphyry-related deposits in post-collisional settings. The latter deposits typically exhibit shallow epithermal levels of emplacement because of preservation by burial.
Seventeen porphyry deposits and one porphyry-related deposit in the study region are reported to contain significant supergene resources. Relatively mature levels of secondary copper enrichment in dominantly granodioritic to granitic porphyry deposits occur in areas where large pyrite-rich quartz-sericite alteration zones have been preserved and exposed to surface oxidation (Güzelyayla and Ulutaş in northeastern Turkey; Agarak, Ankavan, Dastakert, Kadjaran, and Teghout in Armenia; Ali Javad in northern Iran; Kale Kafi in central Iran; Darreh Zar, Meiduk, Now Chun, and Sar Cheshmeh in southeastern Iran; and Tanjeel in southwestern Pakistan). Chalcocite blankets also developed over porphyry deposits in regions where significant post-mineral faulting has occurred (Muratdere and Sarıçayıryayla in western Turkey). Normal faulting also enhanced secondary enrichment of gold in the Halilağa porphyry and Sary Gunay porphyry-related deposits located respectively in western Turkey and northern Iran.
Evaluation of provincial as well as local controls strongly suggests that continued exploration in the region will lead to the identification of additional porphyry and porphyry-related deposits. These deposits will likely be found under younger cover formations in porphyry belts that are already known, and in association with superjacent high- and intermediate-sulfidation epithermal deposits, or increasingly peripheral skarn, carbonate-replacement, and sediment-hosted deposits. Application of suitable exploration techniques to detect concealed and/or deformed deposits in porphyry belts that remain under-explored may also prove productive.
In 2013, the U.S. Geological Survey, in cooperation with the Keweenaw Bay Indian Community, began monitoring the water quality of springs and seeps within the Yellow Dog and Salmon Trout watersheds in Marquette County, Michigan. The objectives of this study were to (1) monitor streamflow and analyze the hydrology of the watersheds and (2) characterize the water quality in the watersheds prior to development of mineral resources within the watershed. Three continuous-record streamgages (U.S. Geological Survey stations 04043238, 04043244, and 04043275) were examined to identify runoff and baseflow components of streamflow and the relative magnitudes of those components. Streamflow at each station was dominated by groundwater discharge with about 70 to 80 percent of the annual streamflow being groundwater-derived baseflow.
From May 2013 to October 2016, 239 water-quality samples were collected at 15 stations within the Yellow Dog and Salmon Trout watersheds. Of the 15 stations sampled, 8 of the stations were springs and 7 of the stations were streams. Samples were analyzed for nutrient, trace metal, and major-ion species at all stations with additional suspended-sediment samples collected at the 7 stream stations. Where applicable, water-quality results were compared to aquatic health guidelines used by the Michigan Department of Environmental Quality. Copper concentrations exceeded the final chronic value five times and the aquatic maximum value once, whereas silver concentrations exceeded the final chronic value twice and the aquatic maximum value once. Results indicate that chloride concentrations may be increasing at some stations, but values are generally low with a median concentration of 0.25 milligram per liter.
Bed-sediment chemistry was evaluated twice for each stream sampling station. Samples were collected in the first and last year of the study and analyzed for trace metals. Sediment chemistry results were compared to consensus-based sediment quality guidelines. None of the metal constituents analyzed exceeded the threshold effect concentration or probable effect concentration thresholds, indicating a healthy aquatic environment in relation to bed-sediment quality.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20185152","collaboration":"Prepared in cooperation with the Keweenaw Bay Indian Community","usgsCitation":"Hoard, C.J., and Weaver, T.L., 2019, Water quality and hydrology of the Yellow Dog and Salmon Trout watersheds, Marquette County, Michigan, 2013–16: U.S. Geological Survey Scientific Investigations Report 2018–5152, 24 p., https://doi.org/10.3133/sir20185152.","productDescription":"viii, 24 p.","numberOfPages":"36","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-098434","costCenters":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":361778,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2018/5152/coverthb.jpg"},{"id":361779,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2018/5152/sir20185152.pdf","text":"Report","size":"9.83 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2018-5152"}],"country":"United States","state":"Michigan","county":"Marquette County","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -88.07464599609375,\n 46.64283679198892\n ],\n [\n -87.60017395019531,\n 46.64283679198892\n ],\n [\n -87.60017395019531,\n 46.91884832811514\n ],\n [\n -88.07464599609375,\n 46.91884832811514\n ],\n [\n -88.07464599609375,\n 46.64283679198892\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Upper Midwest Water Science Center
U.S. Geological Survey
6520 Mercantile Way, Suite 5
Lansing, MI 48911
The transport of coal and oil can result in contaminated soil, water, and organisms from unintended releases. Trains carrying coal and crude oil regularly pass through Puget Sound, Washington, and an increase in the number of coal and oil trains is expected in the future. This study characterized levels of potentially toxic contaminants in sediment in September 2015: arsenic, metals, and polycyclic aromatic hydrocarbons (PAHs) at four sites with fine-grained sediment (Chuckanut Bay, Padilla Bay, Snohomish River Delta, Nisqually River Delta) adjacent to the Burlington Northern Santa Fe (BNSF) rail line in the Puget Sound region. Arsenic (As) and metals levels were compared to those measured at a fifth site, urban Saltwater State Park, which was expected to show contaminants associated with urbanization but not rail transport of coal and oil because it is not adjacent to the BNSF rail line. Knowledge about current properties of soil and sediment is essential for quantifying impacts of spills and other releases, and for setting remediation or restoration targets. For the sampling effort and timing of this study, all five sites had fine sediment contents of cadmium (Cd), mercury (Hg), lead (Pb), and zinc (Zn) below minimal effects levels. Pb and Zn appeared to be urban sourced. Median As, chromium (Cr), copper (Cu), and nickel (Ni) levels were in the range where adverse biological effects would possibly occur; however, Cr and Ni were geologically sourced and unlikely to be bioavailable to organisms. As, Cu, and antimony (Sb) levels were highly correlated, an association that is characteristic of legacy smelting operations; however, total sediment contents of these three elements, along with Hg and As/Sb ratios, were near natural levels and could indicate river-borne inputs. Median total PAH concentrations were highest at Snohomish River Delta, but were below minimal effects levels at all sites. Diagnostic PAH ratios were indicative of PAHs sourced from petroleum combustion and coal/biomass burning, rather than from spilled petroleum or coal. Rare earth element patterns were distinct among watersheds with Cascade volcanoes, granitic rocks, or non-volcanic sediments, making them promising sediment provenance indicators. Knowledge about sediment sources and contaminant distributions could provide unique insights about sediment-bound contaminant sourcing, delivery, and dispersal in nearshore regions.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20181196","usgsCitation":"Takesue, R.K., and Campbell, P.L., 2019, Contaminant baselines and sediment provenance along the Puget Sound Energy Transport Corridor, 2015: U.S. Geological Survey Open-File Report 2018–1196, 10 p., https://doi.org/10.3133/ofr20181196.","productDescription":"iv, 10 p.","onlineOnly":"Y","ipdsId":"IP-101826","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":437594,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9JCJ4EQ","text":"USGS data release","linkHelpText":"Inorganic compositional data for fine-grained Puget Sound sediment along the Burlington Northern Santa Fe rail line, September 2015"},{"id":360807,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2018/1196/coverthb.jpg"},{"id":360808,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2018/1196/ofr20181196.pdf","text":"Report","size":"2.6 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2018-1196"}],"country":"United States","state":"Washington","otherGeospatial":"Puget Sound","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -123.5,\n 47\n ],\n [\n -121.5,\n 47\n ],\n [\n -121.5,\n 49\n ],\n [\n -123.5,\n 49\n ],\n [\n -123.5,\n 47\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Contact Information
Pacific Coastal & Marine Science Center
U.S. Geological Survey
Pacific Science Center
2885 Mission St.
Santa Cruz, CA 95060
Early–life stage white sturgeon are sensitive to copper (Cu), with adverse behavioral responses observed during previous studies. The objectives of the present study were to quantify the effects of Cu exposure on white sturgeon swimming and feeding behaviors and determine their time to response. Larval sturgeon (1–2, 28, or 35 d posthatch [dph]) were exposed to Cu (0.5–8 μg/L) for 4 to 14 d. Abnormal behavioral changes were observed within the first few days of exposure including loss of equilibrium and immobilization. Digital video tracking software revealed decreased swimming activity with increasing Cu concentration. Significant changes in behavior and mortality occurred at concentrations of Cu between 1 and 8 μg/L. Juvenile white sturgeon, 58 dph, exposed to 12 μg/L Cu consumed 37 to 60% less food than controls after 3 d of exposure. The present results indicate that behavioral endpoints were more sensitive than some standard toxicity test endpoints and can effectively expand the sensitivity of standard toxicity tests for white sturgeon. Swimming behavior was impaired to the extent that survival in the field would likely be jeopardized. Such data would provide managers a useful metric for characterizing the risks of Cu contamination to white sturgeon.
","language":"English","publisher":"Society of Environmental Toxicology and Chemistry","doi":"10.1002/etc.4293","usgsCitation":"Puglis, H.J., Calfee, R.D., and Little, E.E., 2019, Behavioral effects of copper on larval white sturgeon: Environmental Toxicology and Chemistry, v. 38, no. 1, p. 132-144, https://doi.org/10.1002/etc.4293.","productDescription":"13 p.","startPage":"132","endPage":"144","ipdsId":"IP-095133","costCenters":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"links":[{"id":437598,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9QB60EV","text":"USGS data release","linkHelpText":"Behavioral Effects of Copper on Larval White Sturgeon"},{"id":437597,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9QB60EV","text":"USGS data release","linkHelpText":"Behavioral Effects of Copper on Larval White Sturgeon"},{"id":360782,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"38","issue":"1","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationDate":"2018-10-09","publicationStatus":"PW","contributors":{"authors":[{"text":"Puglis, Holly J. 0000-0002-3090-6597 hpuglis@usgs.gov","orcid":"https://orcid.org/0000-0002-3090-6597","contributorId":4686,"corporation":false,"usgs":true,"family":"Puglis","given":"Holly","email":"hpuglis@usgs.gov","middleInitial":"J.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":755264,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Calfee, Robin D. 0000-0001-6056-7023 rcalfee@usgs.gov","orcid":"https://orcid.org/0000-0001-6056-7023","contributorId":1841,"corporation":false,"usgs":true,"family":"Calfee","given":"Robin","email":"rcalfee@usgs.gov","middleInitial":"D.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":755265,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Little, Edward E. 0000-0003-0034-3639 elittle@usgs.gov","orcid":"https://orcid.org/0000-0003-0034-3639","contributorId":1746,"corporation":false,"usgs":true,"family":"Little","given":"Edward","email":"elittle@usgs.gov","middleInitial":"E.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":755266,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70199204,"text":"70199204 - 2019 - Selected trace-elements in alluvium and rocks, western Mojave Desert, southern California","interactions":[],"lastModifiedDate":"2019-03-15T12:47:39","indexId":"70199204","displayToPublicDate":"2018-09-10T13:54:34","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2302,"text":"Journal of Geochemical Exploration","active":true,"publicationSubtype":{"id":10}},"title":"Selected trace-elements in alluvium and rocks, western Mojave Desert, southern California","docAbstract":"Concentrations of twenty-seven elements, including naturally-occurring water-quality contaminants arsenic, chromium, and uranium, were measured in 217 samples of alluvium and rock from the western Mojave Desert, southern California, using portable (pXRF) and laboratory (LXRF) X-ray fluorescence. Comparison of measurements with NIST-traceable standards was good, although pXRF overestimated iron compared to LXRF. Results suggest pXRF survey data are sufficiently accurate to assess regional geochemical differences in geologic-source terrains. Principal component analysis showed rubidium and potassium were associated with alluvium eroded from felsic terrain, while iron, copper, chromium, and to a lesser extent titanium, manganese, and nickel were associated with alluvium eroded from mafic terrain. Zinc, vanadium, and arsenic were associated with alluvium eroded from hydrothermal terrain. Elemental assemblages associated with different source terrains were traced spatially to identify the source and composition of alluvium composing aquifers pumped for water supply. Changes in geologic source terrain to the Mojave River, associated with movement along the San Andreas Fault over the past one to five million years, reduced the mafic fraction and increased the felsic fraction of alluvium deposited to the regionally important floodplain aquifer along the Mojave River—lowering chromium concentrations in alluvium through geologic time. Comparison of pXRF and sequential extraction data from 40 samples showed arsenic and uranium were more abundant on the surfaces of mineral grains, while chromium and vanadium remained mostly within unweathered mineral grains—suggesting arsenic and uranium may be more readily mobilized into groundwater with changes in pH, redox, or ionic strength than chromium or vanadium.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.gexplo.2018.09.005","usgsCitation":"Groover, K., and Izbicki, J.A., 2019, Selected trace-elements in alluvium and rocks, western Mojave Desert, southern California: Journal of Geochemical Exploration, v. 200, p. 234-248, https://doi.org/10.1016/j.gexplo.2018.09.005.","productDescription":"15 p.","startPage":"234","endPage":"248","ipdsId":"IP-069818","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":468095,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.gexplo.2018.09.005","text":"Publisher Index Page"},{"id":357205,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Mojave Desert","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -117.5,\n 34\n ],\n [\n -116,\n 34\n ],\n [\n -116,\n 35.5\n ],\n [\n -117.5,\n 35.5\n ],\n [\n -117.5,\n 34\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"200","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5b98a262e4b0702d0e842e4a","contributors":{"authors":[{"text":"Groover, Krishangi D. 0000-0002-5805-8913","orcid":"https://orcid.org/0000-0002-5805-8913","contributorId":203450,"corporation":false,"usgs":true,"family":"Groover","given":"Krishangi D.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":false,"id":744652,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Izbicki, John A. 0000-0003-0816-4408 jaizbick@usgs.gov","orcid":"https://orcid.org/0000-0003-0816-4408","contributorId":152474,"corporation":false,"usgs":true,"family":"Izbicki","given":"John","email":"jaizbick@usgs.gov","middleInitial":"A.","affiliations":[{"id":493,"text":"Office of Ground Water","active":true,"usgs":true},{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":744653,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70198482,"text":"70198482 - 2019 - Phenology of hatching, emergence, and end-of-season body size in young-of-year Coho Salmon in thermally contrasting streams draining the Copper River Delta, Alaska ","interactions":[],"lastModifiedDate":"2019-02-11T15:15:35","indexId":"70198482","displayToPublicDate":"2018-08-06T12:33:38","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1169,"text":"Canadian Journal of Fisheries and Aquatic Sciences","active":true,"publicationSubtype":{"id":10}},"title":"Phenology of hatching, emergence, and end-of-season body size in young-of-year Coho Salmon in thermally contrasting streams draining the Copper River Delta, Alaska ","docAbstract":"Phenology can be linked to individual fitness, particularly in strongly seasonal environments where the timing of events have important consequences for growth, condition, and survival. We studied the phenology of Coho Salmon hatching and emergence in streams with contrasting thermal variability, but in close geographic proximity. Following emergence, we tracked body sizes of cohorts of young-of-year fish until the end of the growing season. Hatch and emergence timing occurred at the same time among streams with marked variability in thermal regimes. We demonstrate that this can be explained in part by the thermal units accumulated during embryo development. At the end of the first growing season there were some differences in body size, however overall fish size among streams were similar despite strong differences in thermal regimes. Collectively these results provide novel insights into the interactions between environmental variability and the early life-history stages of Coho Salmon furthering our understanding of the consequences of phenology on growth and survival for individuals within the critical first summer of life.
","language":"English","publisher":"Canadian Science Publishing","doi":"10.1139/cjfas-2018-0003","usgsCitation":"Campbell, E.Y., Dunham, J.B., Reeves, G.H., and Wondzell, S.M., 2019, Phenology of hatching, emergence, and end-of-season body size in young-of-year Coho Salmon in thermally contrasting streams draining the Copper River Delta, Alaska : Canadian Journal of Fisheries and Aquatic Sciences, v. 76, no. 2, p. 185-191, https://doi.org/10.1139/cjfas-2018-0003.","productDescription":"7 p.","startPage":"185","endPage":"191","ipdsId":"IP-084964","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":501355,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"http://hdl.handle.net/1807/90589","text":"External Repository"},{"id":356192,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"Copper River Delta","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -145.67,\n 60.33\n ],\n [\n -145,\n 60.33\n ],\n [\n -145,\n 60.67\n ],\n [\n -145.67,\n 60.67\n ],\n [\n -145.67,\n 60.33\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"76","issue":"2","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5b6fc3dbe4b0f5d57878e909","contributors":{"authors":[{"text":"Campbell, Emily Y.","contributorId":206748,"corporation":false,"usgs":false,"family":"Campbell","given":"Emily","email":"","middleInitial":"Y.","affiliations":[{"id":6680,"text":"Oregon State University","active":true,"usgs":false}],"preferred":false,"id":741623,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Dunham, Jason B. 0000-0002-6268-0633 jdunham@usgs.gov","orcid":"https://orcid.org/0000-0002-6268-0633","contributorId":147808,"corporation":false,"usgs":true,"family":"Dunham","given":"Jason","email":"jdunham@usgs.gov","middleInitial":"B.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true},{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true},{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":741622,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Reeves, Gordon H.","contributorId":101521,"corporation":false,"usgs":false,"family":"Reeves","given":"Gordon","email":"","middleInitial":"H.","affiliations":[{"id":527,"text":"Pacific Northwest Research Station","active":false,"usgs":true}],"preferred":false,"id":741624,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Wondzell, Steve M.","contributorId":206749,"corporation":false,"usgs":false,"family":"Wondzell","given":"Steve","email":"","middleInitial":"M.","affiliations":[{"id":37389,"text":"U.S. Forest Service","active":true,"usgs":false}],"preferred":false,"id":741625,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70195971,"text":"sir20185033 - 2018 - Characterization of stormwater runoff from bridge decks in eastern Massachusetts, 2014–16","interactions":[],"lastModifiedDate":"2020-05-19T13:33:40.660565","indexId":"sir20185033","displayToPublicDate":"2020-05-19T09:40:00","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":"2018-5033","title":"Characterization of stormwater runoff from bridge decks in eastern Massachusetts, 2014–16","docAbstract":"The quality of stormwater runoff from bridge decks (hereafter referred to as “bridge-deck runoff”) was characterized in a field study from August 2014 through August 2016 in which concentrations of suspended sediment (SS) and total nutrients were monitored. These new data were collected to supplement existing highway-runoff data collected in Massachusetts which were deficient in bridge-deck runoff concentration data. Monitoring stations were installed at three bridges maintained by the Massachusetts Department of Transportation in eastern Massachusetts (State Route 2A in the city of Boston, Interstate 90 in the town of Weston, and State Route 20 near Quinsigamond Village in the city of Worcester). The bridges had annual average daily traffic volumes from 21,200 to 124,000 vehicles per day; the land use surrounding the monitoring stations was 25 to 67 percent impervious.
Automatic-monitoring techniques were used to collect more than 160 flow-proportional composite samples of bridge-deck runoff. Samples were analyzed for concentrations of SS, loss on ignition of suspended solids (LOI), particulate carbon (PC), total phosphorus (TP), total dissolved nitrogen (DN), and particulate nitrogen (PN). The distribution of particle size of SS also was determined for composite samples. Samples of bridge-deck runoff were collected year round during rain, mixed precipitation, and snowmelt runoff and with different dry antecedent periods throughout the 2-year sampling period.
At the three bridge-deck-monitoring stations, median concentrations of SS in composite samples of bridge-deck runoff ranged from 1,490 to 2,020 milligrams per liter (mg/L); however, the range of SS in individual composites was vast at 44 to 142,000 mg/L. Median concentrations of SS were similar in composite samples collected from the State Route 2A and Interstate 90 bridge (2,010 and 2,020 mg/L, respectively), and lowest at the State Route 20 bridge (1,490 mg/L). Concentrations of coarse sediment (greater than 0.25 millimeters in diameter) dominated the SS matrix by more than an order of magnitude. Concentrations of LOI and PC in composite samples ranged from 15 to 1,740 mg/L and 6.68 to 1,360 mg/L, respectively, and generally represented less than 10 and 3 percent of the median mass of SS, respectively. Concentrations of TP in composite samples ranged from 0.09 to 7.02 mg/L; median concentrations of TP ranged from 0.505 to 0.69 mg/L and were highest on the bridge on State Route 2A in Boston. Concentrations of total nitrogen (TN) (sum DN and PN) in composite samples were variable (0.36 to 29 mg/L). Median DN (0.64 to 0.90 mg/L) concentrations generally represented about 40 percent of the TN concentration at each bridge and were similar to annual volume-weighted mean concentrations of nitrogen in precipitation in Massachusetts.
Nonparametric statistical methods were used to test for differences between sample constituent concentrations among the three bridges. These results indicated that there are no statistically significant differences for concentrations of SS, LOI, PC, and TP among the three bridges (one-way analysis of variance test on rank-transformed data, 95-percent confidence level). Test results for concentrations of TN in composite samples indicated that concentrations of TN collected on State Route 20 near Quinsigamond Village were significantly higher than those concentrations collected on State Route 2A in Boston and Interstate 90 near Weston. Median concentrations of TN were about 93 and 55 percent lower at State Route 2A and at Interstate 90, respectively, compared to the median concentrations of TN at State Route 20.
Samples of sediment were collected from five fixed locations on each bridge on three occasions during dry weather to calculate semiquantitative distributions of sediment yields on the bridge surface relative to the monitoring location. Mean yields of bridge-deck sediment during this study for State Route 2A in Boston, Interstate 90 near Weston, and State Route 20 near Quinsigamond Village were 1,500, 250, and 5,700 pounds per curb-mile, respectively. Sediment yields at each sampling location varied widely (26 to 25,000 pounds per curb-mile) but were similar to yields reported elsewhere in Massachusetts and the United States. Yields calculated for each sampling location indicated that the sediment was not evenly distributed across each bridge in this study for plausible reasons such as bridge slope, vehicular tracking, and bridge deterioration.
Bridge-deck sediment quality was largely affected by the distribution of sediment particle size. Concentrations of TP in the fine sediment-size fraction (less than 0.0625 millimeter in diameter) of samples of bridge-deck sediment were about 6 times greater than in the coarse size fraction. Concentrations for many total-recoverable metals were 2 to 17 times greater in the fine size fraction compared to concentrations in the coarse size fraction (greater than or equal to 0.25 millimeter in diameter), and concentrations of total-recoverable copper and lead in the fine size fraction were 2 to 65 times higher compared to concentrations in the intermediate (greater than or equal to 0.0625 to 0.25 millimeter in diameter) or the coarse size fraction. However, the proportion of sediment particles less than 0.0625 millimeter in diameter in composite samples of bridge-deck runoff was small (median values range from 4 to 8 percent at each bridge) compared to the larger sediment particle-size mass. As a result, more than 50 percent of the sediment-associated TP, aluminum, chromium, manganese, and nickel was estimated to be associated with the coarse size fraction of the SS load. In contrast, about 95 percent of the estimated sediment-associated copper concentration was associated with the fine size fraction of the SS load.
Version 1.0.2 of the Stochastic Empirical Loading and Dilution Model was used to simulate long-term (29–30-year) concentrations and annual yields of SS, TP, and TN in bridge-deck runoff and in discharges from a hypothetical stormwater treatment best-management practice structure. Three methods (traditional statistics, robust statistics, and L-moments) were used to calculate statistics for stochastic simulations because the high variability in measured concentration values during the field study resulted in extreme simulated concentrations. Statistics of each dataset, including the average, standard deviation, and skew of the common (base 10) logarithms, for each of the three bridges, and for a lumped dataset, were calculated and used for simulations; statistics representing the median of statistics calculated for the three bridges also were used for simulations. These median statistics were selected for the interpretive simulations so that the simulations could be used to estimate concentrations and yields from other, unmonitored bridges in Massachusetts. Comparisons of the standard and robust statistics indicated that simulation results with either method would be similar, which indicated that the large variability in simulated results was not caused by a few outliers. Comparison to statistics calculated by the L-moments methods indicated that L-moments do not produce extreme concentrations; however, they also do not produce results that represent the bulk of concentration data.
The runoff-quality risk analysis indicated that bridge-deck runoff would exceed discharge standards commonly used for large, advanced wastewater treatment plants, but that commonly used stormwater best-management practices may reduce the percentage of exceedances by one-half. Results of simulations indicated that long-term average yields of TN, TP, and SS may be about 21.4, 6.44, and 40,600 pounds per acre per year, respectively. These yields are about 1.3, 3.4, and 16 times simulated ultra-urban highway yields in Massachusetts; however, simulations indicated that use of a best-management practice structure to treat bridge-deck runoff may reduce discharge yields to about 10, 2.8, and 4,300, pounds per acre per year, respectively.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20185033","isbn":"978-1-4113-4222-4","usgsCitation":"Smith, K.P., Sorenson, J.R., and Granato, G.E., 2018, Characterization of stormwater runoff from bridge decks in eastern Massachusetts, 2014–16: U.S. Geological Survey Scientific Investigations Report 2018–5033, 73 p., https://doi.org/10.3133/sir20185033.","productDescription":"xiii, 73 p.","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-088034","costCenters":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"links":[{"id":374915,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2018/5033/sir20185033.pdf","text":"Report","size":"4.01 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2018-5033"},{"id":353906,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2018/5033/coverthb.jpg"}],"country":"United States","state":"Massachusetts","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -71.98516845703125,\n 41.97582726102573\n ],\n [\n -70.7904052734375,\n 41.97582726102573\n ],\n [\n -70.7904052734375,\n 42.827638636242284\n ],\n [\n -71.98516845703125,\n 42.827638636242284\n ],\n [\n -71.98516845703125,\n 41.97582726102573\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, New England Water Science Center
U.S. Geological Survey
10 Bearfoot Road
Northborough, MA 01532
Sediments from the Upper Columbia River, Washington, USA, are contaminated with metals from smelting operations. We conducted short‐term and long‐term tests with the midge Chironomus dilutus and the amphipod Hyalella azteca and short‐term tests with the freshwater mussel Lampsilis siliquoidea with 54 sediments from the Upper Columbia River to characterize thresholds for toxicity of metals to benthic invertebrates. Test sediments were screened for toxicity by comparisons with low‐metal reference sediments. Toxic effects on amphipods occurred primarily in sediments from the upstream (riverine) reach, and toxic effects on midges occurred in sediments from both the upstream reach and the downstream (reservoir) reach. Little toxicity was observed in mussel tests. Toxicity thresholds (20% effect concentrations [EC20s]) for metals in sediment and porewater were estimated from logistic concentration–response models. Copper (Cu) concentrations in the simultaneously extracted metal fraction of sediments and bioavailable Cu in porewater, as characterized by biotic ligand models, had consistent associations with toxicity endpoints. Concentration–response models for sediment Cu produced EC20s for 6 endpoints, with long‐term amphipod survival and reproduction being the most sensitive. A logistic regression model fitted to an endpoint sensitivity distribution for sediment Cu predicted that approximately one‐half of the sediments tested would be toxic to at least one endpoint and that approximately 20% of test sediments would be toxic to more than half of the endpoints. These results indicate that sediments from the upstream reach of the Upper Columbia River, which contain high concentrations of metals associated with slags, cause a wide range of toxic effects in laboratory tests and are likely to have adverse effects on benthic invertebrate communities.
","language":"English","publisher":"Society of Environmental Toxicology and Chemistry","doi":"10.1002/etc.4276","usgsCitation":"Besser, J.M., Steevens, J.A., Kunz, J.L., Brumbaugh, W., Ingersoll, C.G., Cox, S.E., Mebane, C.A., Balistrieri, L.S., Sinclair, J.A., and MacDonald, D.D., 2018, Characterizing toxicity of metal‐contaminated sediments from the Upper Columbia River, Washington, USA, to benthic invertebrates: Environmental Toxicology and Chemistry, v. 37, no. 12, p. 3102-3114, https://doi.org/10.1002/etc.4276.","productDescription":"13 p.","startPage":"3102","endPage":"3114","ipdsId":"IP-097897","costCenters":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"links":[{"id":360059,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Washington","otherGeospatial":"Upper Columbia River","volume":"37","issue":"12","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationDate":"2018-09-21","publicationStatus":"PW","scienceBaseUri":"5c0b957de4b0c53ecb2aca84","contributors":{"authors":[{"text":"Besser, John M. 0000-0002-9464-2244 jbesser@usgs.gov","orcid":"https://orcid.org/0000-0002-9464-2244","contributorId":2073,"corporation":false,"usgs":true,"family":"Besser","given":"John","email":"jbesser@usgs.gov","middleInitial":"M.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":753284,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Steevens, Jeffery A. 0000-0003-3946-1229","orcid":"https://orcid.org/0000-0003-3946-1229","contributorId":207511,"corporation":false,"usgs":true,"family":"Steevens","given":"Jeffery","middleInitial":"A.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":753285,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kunz, James L. 0000-0002-1027-158X jkunz@usgs.gov","orcid":"https://orcid.org/0000-0002-1027-158X","contributorId":3309,"corporation":false,"usgs":true,"family":"Kunz","given":"James","email":"jkunz@usgs.gov","middleInitial":"L.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":753286,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Brumbaugh, William G. 0000-0003-0081-375X","orcid":"https://orcid.org/0000-0003-0081-375X","contributorId":202358,"corporation":false,"usgs":true,"family":"Brumbaugh","given":"William G.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":753287,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Ingersoll, Christopher G. 0000-0003-4531-5949 cingersoll@usgs.gov","orcid":"https://orcid.org/0000-0003-4531-5949","contributorId":2071,"corporation":false,"usgs":true,"family":"Ingersoll","given":"Christopher","email":"cingersoll@usgs.gov","middleInitial":"G.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":753288,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Cox, Stephen E. 0000-0001-6614-8225 secox@usgs.gov","orcid":"https://orcid.org/0000-0001-6614-8225","contributorId":1642,"corporation":false,"usgs":true,"family":"Cox","given":"Stephen","email":"secox@usgs.gov","middleInitial":"E.","affiliations":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"preferred":true,"id":753289,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Mebane, Christopher A. 0000-0002-9089-0267 cmebane@usgs.gov","orcid":"https://orcid.org/0000-0002-9089-0267","contributorId":110,"corporation":false,"usgs":true,"family":"Mebane","given":"Christopher","email":"cmebane@usgs.gov","middleInitial":"A.","affiliations":[{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"preferred":true,"id":753290,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Balistrieri, Laurie S. 0000-0002-6359-3849 balistri@usgs.gov","orcid":"https://orcid.org/0000-0002-6359-3849","contributorId":1406,"corporation":false,"usgs":true,"family":"Balistrieri","given":"Laurie","email":"balistri@usgs.gov","middleInitial":"S.","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true},{"id":662,"text":"Western Mineral and Environmental Resources Science Center","active":true,"usgs":true},{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true},{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":753291,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Sinclair, Jesse A.","contributorId":176180,"corporation":false,"usgs":false,"family":"Sinclair","given":"Jesse","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":753292,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"MacDonald, Donald D.","contributorId":176179,"corporation":false,"usgs":false,"family":"MacDonald","given":"Donald","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":753293,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}} ]}