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At least 55 records · Page 3Linked to original sources
USGS1996

Material flow analysis for an industry - A case study in packaging

The basic materials used in packaging are glass, metals (primarily aluminum and steel), an ever-growing range of plastics, paper and paperboard, wood, textiles for bags, and miscellaneous other materials (such as glues, inks, and other supplies). They are fabricated into rigid, semirigid, or flexible containers. The most common forms of these containers include cans, drums, bottles, cartons, boxes, bags, pouches, and wraps. Packaging products are, for the most part, low cost, bulky products that are manufactured close to their customers. There is virtually no import or export of packaging products. A material flow analysis can be developed that looks at all inputs to an industrial sector, inventories the losses in processing, and tracks the fate of the material after its useful life. An example is presented that identifies the material inputs to the packaging industry, and addresses the ultimate fate of the materials used.

Natural Resources Research↗
USGS1996

The solid waste dilemma

In 1976, the U.S. Congress enacted the Resource Conservation and Recovery Act (RCRA) to further address the problem of increasing industrial and municipal waste. The main objectives of RCRA were to responsibly manage hazardous and solid waste and to procure materials made from recovered wastes. To fulfill these objectives, four main programs of waste management were developed. These programs were defined under Subtitle C, the Hazardous Waste Program; Subtitle D, the Solid Waste Program; Subtitle I, the Underground Storage Tank Program; and Subtitle J, the Medical Waste Program. Subtitle D illustrates the solid waste dilemma occurring in the United States. Under this program, states are encouraged to develop and implement their own waste management plans. These plans include the promotion of recycling solid wastes and the closing and upgrading of all environmentally unsound dumps.

Natural Resources Research↗
USGS1996

Recycling of nonmetallics

The first factor determining recyclability is the composition of the material itself. Metals, for example, can be reused with little or no loss in quality. Paper and rubber, by this criterion, are less recyclable. Each time paper is recycled, some cellulose fibers are broken. Shorter fibers can mean weaker paper of perceived lower quality and value. Vulcanizing is an irreversible chemical process that precludes recycling rubber in its original form. Both materials may be reused in other applications often of lower value than the original one. To be recyclable, the discarded material must have a collection infrastructure at the source of waste generation, at a central collection site, or at curbside. The recovered material must also have a market. If it is priced noncompetitively or no market exists, if it does not meet specifications, or if it requires special technology investments which cannot be recovered through future sales, the recovered material may be stockpiled or discarded rather than recycled.

Natural Resources Research↗
USGS1996

Sustainability in a materials world

Many adverse impacts on the environment can be directly related to the materials dispersed to the environment during processing or use, or after use as refuse and waste. Some materials, such as toxic wastes, are a major concern because they create immediate problems with longer-term effects. Gases released by major manufacturing industries can contribute to long-term regional and global problems such as acid rain or increased carbon dioxide in the atmosphere. The use of other materials, however, appears to be more benign or strictly localized in their impacts. If the current per capita level of material consumption in the United States was achieved worldwide, it would create major stresses on both resource adequacy and the environment. In fact, stresses have been created and will continue from this consumption style (developed countries) even if others don't achieve them.

Natural Resources Research↗
USGS2005

A new reserve growth model for United States oil and gas fields

Reserve (or field) growth, which is an appreciation of total ultimate reserves through time, is a well-recognized phenomenon, particularly in mature petroleum provinces. The importance of forecasting reserve growth accurately in a mature petroleum province made it necessary to develop improved growth functions, and a critical review of the original Arrington method was undertaken. During a five-year (1992-1996), the original Arrington method gave 1.03% higher than the actual oil reserve growth, whereas the proposed modified method gave a value within 0.3% of the actual growth, and therefore it was accepted for the development for reserve growth models. During a five-year (1992-1996), the USGS 1995 National Assessment gave 39.3% higher oil and 33.6% lower gas than the actual growths, whereas the new model based on Modified Arrington method gave 11.9% higher oil and 29.8% lower gas than the actual growths. The new models forecast predict reserve growths of 4.2 billion barrels of oil (2.7%) and 30.2 trillion cubic feet of gas (5.4%) for the conterminous U.S. for the next five years (1997-2001). ?? 2005 International Association for Mathematical Geology.

Natural Resources Research↗
USGS2005

Discovery sequence and the nature of low permeability gas accumulations

There is an ongoing discussion regarding the geologic nature of accumulations that host gas in low-permeability sandstone environments. This note examines the discovery sequence of the accumulations in low permeability sandstone plays that were classified as continuous-type by the U.S. Geological Survey for the 1995 National Oil and Gas Assessment. It compares the statistical character of historical discovery sequences of accumulations associated with continuous-type sandstone gas plays to those of conventional plays. The seven sandstone plays with sufficient data exhibit declining size with sequence order, on average, and in three of the seven the trend is statistically significant. Simulation experiments show that both a skewed endowment size distribution and a discovery process that mimics sampling proportional to size are necessary to generate a discovery sequence that consistently produces a statistically significant negative size order relationship. The empirical findings suggest that discovery sequence could be used to constrain assessed gas in untested areas. The plays examined represent 134 of the 265 trillion cubic feet of recoverable gas assessed in undeveloped areas of continuous-type gas plays in low permeability sandstone environments reported in the 1995 National Assessment. ?? 2005 International Association for Mathematical Geology.

Natural Resources Research↗
USGS2006

Specific storage volumes: A useful tool for CO2 storage capacity assessment

Subsurface geologic strata have the potential to store billions of tons of anthropogenic CO2; therefore, geologic carbon sequestration can be an effective mitigation tool used to slow the rate at which levels of atmospheric CO2 are increasing. Oil and gas reservoirs, coal beds, and saline reservoirs can be used for CO2 storage; however, it is difficult to assess and compare the relative storage capacities of these different settings. Typically, CO2 emissions are reported in units of mass, which are not directly applicable to comparing the CO2 storage capacities of the various storage targets. However, if the emission values are recalculated to volumes per unit mass (specific volume) then the volumes of geologic reservoirs necessary to store CO2 emissions from large point sources can be estimated. The factors necessary to convert the mass of CO2 emissions to geologic storage volume (referred to here as Specific Storage Volume or 'SSV') can be reported in units of cubic meters, cubic feet, and petroleum barrels. The SSVs can be used to estimate the reservoir volume needed to store CO2 produced over the lifetime of an individual point source, and to identify CO2 storage targets of sufficient size to meet the demand from that given point source. These storage volumes also can then be projected onto the land surface to outline a representative "footprint," which marks the areal extent of storage. This footprint can be compared with the terrestrial carbon sequestration capacity of the same land area. The overall utility of this application is that the total storage capacity of any given parcel of land (from surface to basement) can be determined, and may assist in making land management decisions. ?? Springer Science+Business Media, LLC 2006.

Natural Resources Research↗
USGS2006

Estimated sand and gravel resources of the South Merrimack, Hillsborough County, New Hampshire, 7.5-minute quadrangle

A computer methodology is presented that allows natural aggregate producers, local governmental, and nongovernmental planners to define specific locations that may have sand and gravel deposits meeting user-specified minimum size, thickness, and geographic and geologic criteria, in areas where the surficial geology has been mapped. As an example, the surficial geologic map of the South Merrimack quadrangle was digitized and several digital geographic information system databases were downloaded from the internet and used to estimate the sand and gravel resources in the quadrangle. More than 41 percent of the South Merrimack quadrangle has been mapped as having sand and (or) gravel deposited by glacial meltwaters. These glaciofluvial areas are estimated to contain a total of 10 million m3 of material mapped as gravel, 60 million m3 of material mapped as mixed sand and gravel, and another 50 million m3 of material mapped as sand with minor silt. The mean thickness of these areas is about 1.95 meters. Twenty tracts were selected, each having individual areas of more than about 14 acres4 (5.67 hectares) of stratified glacial-meltwater sand and gravel deposits, at least 10-feet (3.0 m) of material above the watertable, and not sterilized by the proximity of buildings, roads, streams and other bodies of water, or railroads. The 20 tracts are estimated to contain between about 4 and 10 million short tons (st) of gravel and 20 and 30 million st of sand. The five most gravel-rich tracts contain about 71 to 82 percent of the gravel resources in all 20 tracts and about 54-56 percent of the sand. Using this methodology, and the above criteria, a group of four tracts, divided by narrow areas sterilized by a small stream and secondary roads, may have the highest potential in the quadrangle for sand and gravel resources. ?? Springer Science+Business Media, LLC 2006.

Natural Resources Research↗
USGS2007

Quantitative analysis of scale of aeromagnetic data raises questions about geologic-map scale

A recently published study has shown that small-scale geologic map data can reproduce mineral assessments made with considerably larger scale data. This result contradicts conventional wisdom about the importance of scale in mineral exploration, at least for regional studies. In order to formally investigate aspects of scale, a weights-of-evidence analysis using known gold occurrences and deposits in the Central Lapland Greenstone Belt of Finland as training sites provided a test of the predictive power of the aeromagnetic data. These orogenic-mesothermal-type gold occurrences and deposits have strong lithologic and structural controls associated with long (up to several kilometers), narrow (up to hundreds of meters) hydrothermal alteration zones with associated magnetic lows. The aeromagnetic data were processed using conventional geophysical methods of successive upward continuation simulating terrane clearance or 'flight height' from the original 30 m to an artificial 2000 m. The analyses show, as expected, that the predictive power of aeromagnetic data, as measured by the weights-of-evidence contrast, decreases with increasing flight height. Interestingly, the Moran autocorrelation of aeromagnetic data representing differing flight height, that is spatial scales, decreases with decreasing resolution of source data. The Moran autocorrelation coefficient scems to be another measure of the quality of the aeromagnetic data for predicting exploration targets. ?? Springer Science+Business Media, LLC 2007.

Natural Resources Research↗
USGS2007

Net energy payback and CO2 emissions from three midwestern wind farms: An update

This paper updates a life-cycle net energy analysis and carbon dioxide emissions analysis of three Midwestern utility-scale wind systems. Both the Energy Payback Ratio (EPR) and CO2 analysis results provide useful data for policy discussions regarding an efficient and low-carbon energy mix. The EPR is the amount of electrical energy produced for the lifetime of the power plant divided by the total amount of energy required to procure and transport the materials, build, operate, and decommission the power plants. The CO2 analysis for each power plant was calculated from the life-cycle energy input data. A previous study also analyzed coal and nuclear fission power plants. At the time of that study, two of the three wind systems had less than a full year of generation data to project the life-cycle energy production. This study updates the analysis of three wind systems with an additional four to eight years of operating data. The EPR for the utility-scale wind systems ranges from a low of 11 for a two-turbine system in Wisconsin to 28 for a 143-turbine system in southwestern Minnesota. The EPR is 11 for coal, 25 for fission with gas centrifuge enriched uranium and 7 for gaseous diffusion enriched uranium. The normalized CO2 emissions, in tonnes of CO2 per GW eh, ranges from 14 to 33 for the wind systems, 974 for coal, and 10 and 34 for nuclear fission using gas centrifuge and gaseous diffusion enriched uranium, respectively. ?? Springer Science+Business Media, LLC 2007.

Natural Resources Research↗
USGS2007

Prediction of resource volumes at untested locations using simple local prediction models

This paper shows how local spatial nonparametric prediction models can be applied to estimate volumes of recoverable gas resources at individual undrilled sites, at multiple sites on a regional scale, and to compute confidence bounds for regional volumes based on the distribution of those estimates. An approach that combines cross-validation, the jackknife, and bootstrap procedures is used to accomplish this task. Simulation experiments show that cross-validation can be applied beneficially to select an appropriate prediction model. The cross-validation procedure worked well for a wide range of different states of nature and levels of information. Jackknife procedures are used to compute individual prediction estimation errors at undrilled locations. The jackknife replicates also are used with a bootstrap resampling procedure to compute confidence bounds for the total volume. The method was applied to data (partitioned into a training set and target set) from the Devonian Antrim Shale continuous-type gas play in the Michigan Basin in Otsego County, Michigan. The analysis showed that the model estimate of total recoverable volumes at prediction sites is within 4 percent of the total observed volume. The model predictions also provide frequency distributions of the cell volumes at the production unit scale. Such distributions are the basis for subsequent economic analyses. ?? Springer Science+Business Media, LLC 2007.

Natural Resources Research↗
USGS2007

Wellsite, laboratory, and mathematical techniques for determining sorbed gas content of coals and gas shales utilizing well cuttings

Drill cuttings can be used for desorption analyses but with more uncertainty than desorption analyses done with cores. Drill cuttings are not recommended to take the place of core, but in some circumstances, desorption work with cuttings can provide a timely and economic supplement to that of cores. The mixed lithologic nature of drill cuttings is primarily the source of uncertainty in their analysis for gas content, for it is unclear how to apportion the gas generated from both the coal and the dark-colored shale that is mixed in usually with the coal. In the Western Interior Basin Coal Basin in eastern Kansas (Pennsylvanian-age coals), dark-colored shales with normal (??? 100 API units) gamma-ray levels seem to give off minimal amounts of gas on the order of less than five standard cubic feet per ton (scf/ton). In some cuttings analyses this rule of thumb for gas content of the shale is adequate for inferring the gas content of coals, but shales with high-gamma-ray values (>150 API units) may yield several times this amount of gas. The uncertainty in desorption analysis of drill cuttings can be depicted graphically on a diagram identified as a "lithologic component sensitivity analysis diagram." Comparison of cuttings desorption results from nearby wells on this diagram, can sometimes yield an unique solution for the gas content of both a dark shale and coal mixed in a cuttings sample. A mathematical solution, based on equating the dry, ash-free gas-contents of the admixed coal and dark-colored shale, also yields results that are correlative to data from nearby cores. ?? 2007 International Association for Mathematical Geology.

Natural Resources Research↗
USGS2007

Assessment of exploration bias in data-driven predictive models and the estimation of undiscovered resources

The spatial distribution of discovered resources may not fully mimic the distribution of all such resources, discovered and undiscovered, because the process of discovery is biased by accessibility factors (e.g., outcrops, roads, and lakes) and by exploration criteria. In data-driven predictive models, the use of training sites (resource occurrences) biased by exploration criteria and accessibility does not necessarily translate to a biased predictive map. However, problems occur when evidence layers correlate with these same exploration factors. These biases then can produce a data-driven model that predicts known occurrences well, but poorly predicts undiscovered resources. Statistical assessment of correlation between evidence layers and map-based exploration factors is difficult because it is difficult to quantify the "degree of exploration." However, if such a degree-of-exploration map can be produced, the benefits can be enormous. Not only does it become possible to assess this correlation, but it becomes possible to predict undiscovered, instead of discovered, resources. Using geothermal systems in Nevada, USA, as an example, a degree-of-exploration model is created, which then is resolved into purely explored and unexplored equivalents, each occurring within coextensive study areas. A weights-of-evidence (WofE) model is built first without regard to the degree of exploration, and then a revised WofE model is calculated for the "explored fraction" only. Differences in the weights between the two models provide a correlation measure between the evidence and the degree of exploration. The data used to build the geothermal evidence layers are perceived to be independent of degree of exploration. Nevertheless, the evidence layers correlate with exploration because exploration has preferred the same favorable areas identified by the evidence patterns. In this circumstance, however, the weights for the "explored" WofE model minimize this bias. Using these revised weights, posterior probability is extrapolated into unexplored areas to estimate undiscovered deposits. ?? International Association for Mathematical Geology 2007.

Natural Resources Research↗
USGS2007

Development and implementation of a Bayesian-based aquifer vulnerability assessment in Florida

The Florida Aquifer Vulnerability Assessment (FAVA) was designed to provide a tool for environmental, regulatory, resource management, and planning professionals to facilitate protection of groundwater resources from surface sources of contamination. The FAVA project implements weights-of-evidence (WofE), a data-driven, Bayesian-probabilistic model to generate a series of maps reflecting relative aquifer vulnerability of Florida's principal aquifer systems. The vulnerability assessment process, from project design to map implementation is described herein in reference to the Floridan aquifer system (FAS). The WofE model calculates weighted relationships between hydrogeologic data layers that influence aquifer vulnerability and ambient groundwater parameters in wells that reflect relative degrees of vulnerability. Statewide model input data layers (evidential themes) include soil hydraulic conductivity, density of karst features, thickness of aquifer confinement, and hydraulic head difference between the FAS and the watertable. Wells with median dissolved nitrogen concentrations exceeding statistically established thresholds serve as training points in the WofE model. The resulting vulnerability map (response theme) reflects classified posterior probabilities based on spatial relationships between the evidential themes and training points. The response theme is subjected to extensive sensitivity and validation testing. Among the model validation techniques is calculation of a response theme based on a different water-quality indicator of relative recharge or vulnerability: dissolved oxygen. Successful implementation of the FAVA maps was facilitated by the overall project design, which included a needs assessment and iterative technical advisory committee input and review. Ongoing programs to protect Florida's springsheds have led to development of larger-scale WofE-based vulnerability assessments. Additional applications of the maps include land-use planning amendments and prioritization of land purchases to protect groundwater resources. ?? International Association for Mathematical Geology 2007.

Natural Resources Research↗
USGS2007

Probabilistic prediction models for aggregate quarry siting

Weights-of-evidence (WofE) and logistic regression techniques were used in a GIS framework to predict the spatial likelihood (prospectivity) of crushed-stone aggregate quarry development. The joint conditional probability models, based on geology, transportation network, and population density variables, were defined using quarry location and time of development data for the New England States, North Carolina, and South Carolina, USA. The Quarry Operation models describe the distribution of active aggregate quarries, independent of the date of opening. The New Quarry models describe the distribution of aggregate quarries when they open. Because of the small number of new quarries developed in the study areas during the last decade, independent New Quarry models have low parameter estimate reliability. The performance of parameter estimates derived for Quarry Operation models, defined by a larger number of active quarries in the study areas, were tested and evaluated to predict the spatial likelihood of new quarry development. Population density conditions at the time of new quarry development were used to modify the population density variable in the Quarry Operation models to apply to new quarry development sites. The Quarry Operation parameters derived for the New England study area, Carolina study area, and the combined New England and Carolina study areas were all similar in magnitude and relative strength. The Quarry Operation model parameters, using the modified population density variables, were found to be a good predictor of new quarry locations. Both the aggregate industry and the land management community can use the model approach to target areas for more detailed site evaluation for quarry location. The models can be revised easily to reflect actual or anticipated changes in transportation and population features. ?? International Association for Mathematical Geology 2007.

Natural Resources Research↗
USGS2008

Are fractal dimensions of the spatial distribution of mineral deposits meaningful?

It has been proposed that the spatial distribution of mineral deposits is bifractal. An implication of this property is that the number of deposits in a permissive area is a function of the shape of the area. This is because the fractal density functions of deposits are dependent on the distance from known deposits. A long thin permissive area with most of the deposits in one end, such as the Alaskan porphyry permissive area, has a major portion of the area far from known deposits and consequently a low density of deposits associated with most of the permissive area. On the other hand, a more equi-dimensioned permissive area, such as the Arizona porphyry permissive area, has a more uniform density of deposits. Another implication of the fractal distribution is that the Poisson assumption typically used for estimating deposit numbers is invalid. Based on datasets of mineral deposits classified by type as inputs, the distributions of many different deposit types are found to have characteristically two fractal dimensions over separate non-overlapping spatial scales in the range of 5-1000 km. In particular, one typically observes a local dimension at spatial scales less than 30-60 km, and a regional dimension at larger spatial scales. The deposit type, geologic setting, and sample size influence the fractal dimensions. The consequence of the geologic setting can be diminished by using deposits classified by type. The crossover point between the two fractal domains is proportional to the median size of the deposit type. A plot of the crossover points for porphyry copper deposits from different geologic domains against median deposit sizes defines linear relationships and identifies regions that are significantly underexplored. Plots of the fractal dimension can also be used to define density functions from which the number of undiscovered deposits can be estimated. This density function is only dependent on the distribution of deposits and is independent of the definition of the permissive area. Density functions for porphyry copper deposits appear to be significantly different for regions in the Andes, Mexico, United States, and western Canada. Consequently, depending on which regional density function is used, quite different estimates of numbers of undiscovered deposits can be obtained. These fractal properties suggest that geologic studies based on mapping at scales of 1:24,000 to 1:100,000 may not recognize processes that are important in the formation of mineral deposits at scales larger than the crossover points at 30-60 km. ?? 2008 International Association for Mathematical Geology.

Natural Resources Research↗
USGS2008

Map scale effects on estimating the number of undiscovered mineral deposits

Estimates of numbers of undiscovered mineral deposits, fundamental to assessing mineral resources, are affected by map scale. Where consistently defined deposits of a particular type are estimated, spatial and frequency distributions of deposits are linked in that some frequency distributions can be generated by processes randomly in space whereas others are generated by processes suggesting clustering in space. Possible spatial distributions of mineral deposits and their related frequency distributions are affected by map scale and associated inclusions of non-permissive or covered geological settings. More generalized map scales are more likely to cause inclusion of geologic settings that are not really permissive for the deposit type, or that include unreported cover over permissive areas, resulting in the appearance of deposit clustering. Thus, overly generalized map scales can cause deposits to appear clustered. We propose a model that captures the effects of map scale and the related inclusion of non-permissive geologic settings on numbers of deposits estimates, the zero-inflated Poisson distribution. Effects of map scale as represented by the zero-inflated Poisson distribution suggest that the appearance of deposit clustering should diminish as mapping becomes more detailed because the number of inflated zeros would decrease with more detailed maps. Based on observed worldwide relationships between map scale and areas permissive for deposit types, mapping at a scale with twice the detail should cut permissive area size of a porphyry copper tract to 29% and a volcanic-hosted massive sulfide tract to 50% of their original sizes. Thus some direct benefits of mapping an area at a more detailed scale are indicated by significant reductions in areas permissive for deposit types, increased deposit density and, as a consequence, reduced uncertainty in the estimate of number of undiscovered deposits. Exploration enterprises benefit from reduced areas requiring detailed and expensive exploration, and land-use planners benefit from reduced areas of concern. ?? 2008 International Association for Mathematical Geology.

Natural Resources Research↗