Dataset Information

Modeling Magnetic Fields from a DC Power Cable Buried Beneath San Francisco Bay Based on Empirical Measurements.

ABSTRACT: The Trans Bay Cable (TBC) is a ±200-kilovolt (kV), 400 MW 85-km long High Voltage Direct Current (DC) buried transmission line linking Pittsburg, CA with San Francisco, CA (SF) beneath the San Francisco Estuary. The TBC runs parallel to the migratory route of various marine species, including green sturgeon, Chinook salmon, and steelhead trout. In July and August 2014, an extensive series of magnetic field measurements were taken using a pair of submerged Geometrics magnetometers towed behind a survey vessel in four locations in the San Francisco estuary along profiles that cross the cable's path; these included the San Francisco-Oakland Bay Bridge (BB), the Richmond-San Rafael Bridge (RSR), the Benicia-Martinez Bridge (Ben) and an area in San Pablo Bay (SP) in which a bridge is not present. In this paper, we apply basic formulas that ideally describe the magnetic field from a DC cable summed vectorially with the background geomagnetic field (in the absence of other sources that would perturb the ambient field) to derive characteristics of the cable that are otherwise not immediately observable. Magnetic field profiles from measurements taken along 170 survey lines were inspected visually for evidence of a distinct pattern representing the presence of the cable. Many profiles were dominated by field distortions unrelated to the cable caused by bridge structures or other submerged objects, and the cable's contribution to the field was not detectable. BB, with 40 of the survey lines, did not yield usable data for these reasons. The unrelated anomalies could be up to 100 times greater than those from the cable. In total, discernible magnetic field profiles measured from 76 survey lines were regressed against the equations, representing eight days of measurement. The modeled field anomalies due to the cable (the difference between the maximum and minimum field along the survey line at the cable crossing) were virtually identical to the measured values. The modeling yielded a pooled cable depth below the bay floor of 2.06 m (±1.46 std dev), and estimated the angle to the horizontal of the imaginary line connecting the cross-sectional center of the cable's two conductors (0.1143 m apart) as 178.9° ±61.9° (std dev) for Ben, 78.6°±37.0° (std dev) for RSR, and 139.9°±27.4° (std dev) for SP. The mean of the eight daily average currents derived from the regressions was 986 ±185 amperes (A) (std dev), as compared to 722 ±95 A (std dev) provided by Trans Bay Cable LLC. Overall, the regressions based on fundamental principles (Biot Savart law) and the vectorial summation of cable and geomagnetic fields provide estimates of cable characteristics consistent with plausible expectations.

SUBMITTER: Kavet R

PROVIDER: S-EPMC4767330 | biostudies-literature | 2016

REPOSITORIES: biostudies-literature

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Modeling Magnetic Fields from a DC Power Cable Buried Beneath San Francisco Bay Based on Empirical Measurements.

Kavet Robert R Wyman Megan T MT Klimley A Peter AP

PloS one 20160225 2

The Trans Bay Cable (TBC) is a ±200-kilovolt (kV), 400 MW 85-km long High Voltage Direct Current (DC) buried transmission line linking Pittsburg, CA with San Francisco, CA (SF) beneath the San Francisco Estuary. The TBC runs parallel to the migratory route of various marine species, including green sturgeon, Chinook salmon, and steelhead trout. In July and August 2014, an extensive series of magnetic field measurements were taken using a pair of submerged Geometrics magnetometers towed behind a ...[more]

PMID: 26915084

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Project description:Understanding habitat associations is vital for conservation of at-risk marsh-endemic wildlife species, particularly those under threat from sea level rise. We modeled environmental and habitat associations of the marsh-endemic, Federally endangered salt marsh harvest mouse (Reithrodontomys raviventris, RERA) and co-occurrence with eight associated small mammal species from annual trap data, 1998-2014, in six estuarine marshes in North San Francisco Bay, California. Covariates included microhabitat metrics of elevation and vegetation species and cover; and landscape metrics of latitude-longitude, distance to anthropogenic features, and habitat patch size. The dominant cover was pickleweed (Salicornia pacifica) with 86% mean cover and 37 cm mean height, and bare ground with about 10% mean cover. We tested 38 variants of Bayesian network (BN) models to determine covariates that best account for presence of RERA and of all nine small mammal species. Best models had lowest complexity and highest classification accuracy. Among RERA presence models, three best BN models used covariates of latitude-longitude, distance to paved roads, and habitat patch size, with 0% error of false presence, 20% error of false nonpresence, and 20% overall error. The all-species presence models suggested that within the pickleweed marsh environment, RERA are mostly habitat generalists. Accounting for presence of other species did not improve prediction of RERA. Habitat attributes compared between RERA and the next most frequently captured species, California vole (Microtus californicus), suggested substantial habitat overlap, with RERA habitat being somewhat higher in marsh elevation, greater in percent cover of the dominant plant species, closer to urban areas, further from agricultural areas, and, perhaps most significant, larger in continuous size of marsh patch. Findings will inform conservation management of the marsh environment for RERA by identifying best microhabitat elements, landscape attributes, and adverse interspecific interactions.

Project description:BackgroundPolycyclic aromatic hydrocarbon (PAH) exposures from tobacco smoke, automobile exhaust, grilled or smoked meat and other sources are widespread and are a public health concern, as many are classified as probable carcinogens and suspected endocrine-disrupting chemicals. PAH exposures can be quantified using urinary biomarkers.MethodsSeven urinary metabolites of naphthalene, fluorene, phenanthrene, and pyrene were measured in two samples collected from girls aged 6-16 years from the San Francisco Bay Area. We used Spearman correlation coefficients (SCC) to assess correlations among metabolite concentrations (corrected for specific gravity) separately in first (n = 359) and last (N = 349) samples, and to assess consistency of measurements in samples collected up to 72 months apart. Using multivariable linear regression, we assessed variation in mean metabolites across categories of participant characteristics and potential outdoor, indoor, and dietary sources of PAH exposures.ResultsThe detection rate of PAH metabolites was high (4 metabolites in ≥98% of first samples; 5 metabolites in ≥95% of last samples). Correlations were moderate to strong between fluorene, phenanthrene and pyrene metabolites (SCC 0.43-0.82), but weaker between naphthalene and the other metabolites (SCC 0.18-0.36). SCC between metabolites in first and last samples ranged from 0.15 to 0.49. When classifying metabolite concentrations into tertiles based on single samples (first or last samples) vs. the average of the two samples, agreement was moderate to substantial (weighted kappa statistics 0.52-0.65). For specific metabolites, concentrations varied by age, race/ethnicity, and body mass index percentile, as well as by outdoor sources (season of sample collection, street traffic), indoor sources (heating with gas, cigarette smoke), and dietary sources (frequent use of grill, consumption of smoked meat or fish) of PAH exposures.ConclusionsUrinary PAH exposure was widespread in girls aged 6-16 years and associated with several sources of exposure. Tertile classification of a single urine sample provides reliable PAH exposure ranking.

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Modeling Magnetic Fields from a DC Power Cable Buried Beneath San Francisco Bay Based on Empirical Measurements.

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Modeling Magnetic Fields from a DC Power Cable Buried Beneath San Francisco Bay Based on Empirical Measurements.

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