Major and trace elements in igneous rocks from apollo 15

The concentrations of major and trace elements have been determined in igneous rocks from Apollo 15. All materials analyzed have typical depletions of Eu except for minerals separated from sample 15085. Four samples have concentrations of trace elements that are similar to those of KREEP. The samples of mare basalt from Apollo 15 have higher concentrations of FeO, MgO, Mn, and Cr and lower concentrations of CaO, Na₂O, K₂O, and rare-earth elements (REE) as compared to the samples of mare basalt from Apollos 11, 12, and 14. The samples can be divided into two groups on the basis of their normative compositions. One group is quartz normative and has low concentrations of FeO while the other is olivine normative and has high concentrations of FeO. The trace element data indicate that the samples of olivine normative basalt could be from different portions of a single lava flow. At least two and possible three parent magmas can be identified from the samples of the quartz normative group on the basis of their concentration ratios of Sm to Eu. Within each group, the compositions of the samples appear to be related by crystallization of olivine or pyroxene. Significant variations of the ratio of concentration of Sm to Eu cannot be produced without plagioclase-liquid equilibrium. The source material of mare basalt may be depleted in Eu. Alternatively, the magmas may have assimilated a small volume of material similar to KREEP.Paper dedicated to Prof. Harold C. Urey on the occasion of his 80th birthday on 29 April 1973.     

On redshifts and number counts of extragalactic objects in two cosmological models

Observed redshifts and magnitudes of seven classes of extragalactic objects, and number counts of QSRS are compared with predictions made by cosmological models. The uniform model U 1 and the proposed non-expanding model RHL 5 represent the observations very well. The latter offers numerous advantages. Absolute magnitudes and colors are determined.     

MAROS: a decision support system for optimizing monitoring plans

The Monitoring and Remediation Optimization System (MAROS), a decision-support software, was developed to assist in formulating cost-effective ground water long-term monitoring plans. MAROS optimizes an existing ground water monitoring program using both temporal and spatial data analyses to determine the general monitoring system category and the locations and frequency of sampling for future compliance monitoring at the site. The objective of the MAROS optimization is to minimize monitoring locations in the sampling network and reduce sampling frequency without significant loss of information, ensuring adequate future characterization of the contaminant plume. The interpretive trend analysis approach recommends the general monitoring system category for a site based on plume stability and site-specific hydrogeologic information. Plume stability is characterized using primary lines of evidence (i.e., Mann-Kendall analysis and linear regression analysis) based on concentration trends, and secondary lines of evidence based on modeling results and empirical data. The sampling optimization approach, consisting of a two-dimensional spatial sampling reduction method (Delaunay method) and a temporal sampling analysis method (Modified CES method), provides detailed sampling location and frequency results. The Delaunay method is designed to identify and eliminate redundant sampling locations without causing significant information loss in characterizing the plume. The Modified CES method determines the optimal sampling frequency for a sampling location based on the direction, magnitude, and uncertainty in its concentration trend. MAROS addresses a variety of ground water contaminants (fuels, solvents, and metals), allows import of various data formats, and is designed for continual modification of long-term monitoring plans as the plume or site conditions change over time.     

An evaluation of the role played by remote sensing technology following the World Trade Center attack

Remote sensing technology has been widely recognized for contributing to emergency response efforts after the World Trade Center attack on September 11th, 2001. The need to coordinate activities in the midst of a dense, yet relatively small area, made the combination of imagery and mapped data strategically useful. This paper reviews the role played by aerial photography, satellite imagery, and LIDAR data at Ground Zero. It examines how emergency managers utilized these datasets, and identifies significant problems that were encountered. It goes on to explore additional ways in which imagery could have been used, while presenting recommendations for more effective use in future disasters and Homeland Security applications. To plan adequately for future events, it was important to capture knowledge from individuals who responded to the World Trade Center attack. In recognition, interviews with key emergency management and geographic information system (GIS) personnel provide the basis of this paper. Successful techniques should not be forgotten, or serious problems dismissed. Although widely used after September 11th, it is important to recognize that with better planning, remote sensing and GIS could have played an even greater role. Together with a data acquisition timeline, an expanded discussion of these issues is available in the MCEER/NSF report “Emergency Response in the Wake of the World Trade Center Attack; The Remote Sensing Perspective” (Huyck and Adams, 2002)     

Sediment magnetic properties reveal holocene climate change along the Minnesota prairie-forest ecotone

We propose a model that explains variations in magnetic parameters of lake sediments as a record of Holocene climate change. Our model is based on records from 4 lakes and incorporates the effects of erosion, dust deposition, and the authigenesis and diagenesis of the magnetic component of the sediment. Once checked against high resolution multi proxy climate records, which are currently being established for some of our study sites, it will allow us to use magnetic proxies to establish high-resolution climate reconstructions on a regional scale.Our model utilizes a combination of concentration-dependent parameters (magnetic susceptibility, IRM) and grain-size-dependent parameters (ARM/IRM, hysteresis parameters). Magnetic mineralogy is characterized by a combination of low-temperature measurements and S-ratios, and our magnetic measurements are complemented by XRD, LOI and smearslide analyses.During periods of forest growth within the watershed, deposition of terrigenous material is low and the sediment magnetic properties are characterized by low concentrations of mainly authigenic minerals (low values of IRM, high ratios of ARM/IRM). During the early to mid-Holocene dry period, deposition of terrigenous material increased due to intensified dust deposition and the erosion of lake margins caused by lowered water levels. Concentration of magnetic minerals increases (high IRM, ) and so does the grain-size of the magnetic fraction (low ARM/IRM). During the late-Holocene, sediment magnetic properties depend on the varied position of the site with respect to the prairie–forest ecotone.     

The Northern North Atlantic: A Changing Environment, edited by P. Schäfer, W. Ritzrau, M. Schläter and J. Thiede (Book Review)

Volume Contents

Volume contents     

SEDIMENT YIELD AND HYDROLOGY IN NORTHWESTERN RANGELANDS

lINTRODUCTIONRangeandforestlandsofnorthwesternNorthAmericahavebeenutilizedforres0urceextracti0nandproductionsinceinitialhuman0ccupationofthecontinent.Intensive"managed"utilizati0nofec0systemsforspecificbenefitsincludingcattle,sheep,t1sh,w00dandagriculturalpr0ductshasbeenong0ingfornearly0ne-and-haIfcenturies.Intensiveresourceproducti0nhasto0oftenbeenacc0mpaniedbyunwanted"sideeffects"includingacceleratederosion,s0illossandsedimentdeliveredoffsitetod0wnstreamlocati0ns,estuariesandoceanicsin…     

Maximal Overlap Wavelet Statistical Analysis With Application to Atmospheric Turbulence

Statistical tools based on the maximal overlap discrete wavelet transform (MODWT) are reviewed, and then applied to a dataset of aircraft observations of the atmospheric boundary layer from the tropical eastern Pacific, which includes quasi-stationary and non-stationary segments. The wavelet methods provide decompositions of variances and covariances, e.g. fluxes, between time scales that effectively describe a broadband process like atmospheric turbulence. Easily understood statistical confidence bounds are discussed and applied to these scale decompositions, and results are compared to Fourier methods for quasi-stationary turbulence. The least asymmetric LA(8) wavelet filter yields coefficients that exhibit better uncorrelatedness across scales than the Haar filter and is better suited for decomposition of broadband turbulent signals. An application to a non-stationary segment of our dataset, namely vertical profiles of the turbulent dissipation rate, highlights the flexibility of wavelet methods.