High resolution vertical profiles of wind, temperature and humidity obtained by computer processing and digital filtering of radiosonde and radar tracking data from the ITCZ experiment of 1977

Results are presented from computer processing and digital filtering of radiosonde and radar tracking data obtained during the ITCZ experiment when coordinated measurements were taken daily over a 16 day period across the Panama Canal Zone. The temperature relative humidity and wind velocity profiles are discussed

Protocol Requirements for Self-organizing Artifacts: Towards an Ambient Intelligence

We discuss which properties common-use artifacts should have to collaborate without human intervention. We conceive how devices, such as mobile phones, PDAs, and home appliances, could be seamlessly integrated to provide an "ambient intelligence" that responds to the user's desires without requiring explicit programming or commands. While the hardware and software technology to build such systems already exists, as yet there is no standard protocol that can learn new meanings. We propose the first steps in the development of such a protocol, which would need to be adaptive, extensible, and open to the community, while promoting self-organization. We argue that devices, interacting through "game-like" moves, can learn to agree about how to communicate, with whom to cooperate, and how to delegate and coordinate specialized tasks. Thus, they may evolve a distributed cognition or collective intelligence capable of tackling complex tasks.Comment: To be presented at 5th International Conference on Complex System

Data analysis and archival

The purpose of this task is the acquisition, distribution, archival, and analysis of data collected during and in support of the Upper Atmospheric Research Program (UARP) field experiments. Meteorological and U2 data from the 1984 Stratosphere-Troposphere Exchange Project (STEP) was analyzed to determine characteristics of internal atmospheric waves. CDROM's containing data from the 1987 STEP, 1987 Airborne Antarctic Ozone Expedition (AAOE), and the 1989 Airborne Arctic Stratospheric Expedition (AASE) were produced for archival and distribution of those data sets. The AASE CDROM contains preliminary data and a final release is planned for February 1990. Comparisons of data from the NASA ER-2 Meteorological Measurement System (MMS) with radar tracking and radiosonde data show good agreement. Planning for a Meteorological Support Facility continues. We are investigating existing and proposed hardware and software to receive, manipulate, and display satellite imagery and standard meteorological analyses, forecasts, and radiosonde data

Exposure and Exposure Modeling

Exposure to contaminants in the environment is quantified through the ecological risk assessment (ERA) process which provides a framework for the development and implementation of environmental management decisions. The ERA uses available toxicological and ecological information to estimate the probability of occurrence for a specified undesired ecological event or endpoint. The level for these endpoints depends on the objectives and the constraints imposed upon the risk assessment process; therefore, multiple endpoints at different scales may be necessary. ERAs Ecotoxicology | Exposure and Exposure Assessment 1527Author\u27s personal copy often rely on the link between these undesired endpoints to a threshold of exposure to specific toxicants and toxicant mixtures. Oral reference doses (RfD), inhalation reference concentrations (RfC), and carcinogenicity assessments are the usual way these links are expressed in the ERA, and unfortunately most of these thresholds have been developed for human health assessments and not ecosystem integrity. However, since these studies often use animal models, in many cases the original empirical data can be used when trying to apply these findings to ecological consequences or to establish ecological screening values (ESVs). The ecological exposure assessment often begins by comparing constituent concentrations in media (surface water, sediment, soil) to ESVs. The ESVs are derived from ecologically relevant criteria and standards. For example, in the United States the United States Environmental Protection Agency (USEPA) Screening Values and National Ambient Water Quality Criteria (NAWQC) are often used based on ‘no observed adverse effect levels’ (NOAELs) or ‘lowest observed adverse effect levels’ (LOAELs) derived from literature to assess exposure. Radionuclide comparisons for ecological screening are typically dose-based for population level effects. In addition to the ecological threshold comparison, constituents that may bioaccumulate/bioconcentrate are identified during initial screening processes. This is done to account for toxicants that may not be present at levels exceeding ESVs, but must be considered due to trophic transfer of toxicants that may concentrate in higher-trophic-level organisms. Constituents that exceed ESV comparisons (present with means, maximums, or 95% upper confidence levels (UCLs)) are evaluated using a lines-of-evidence approach based on (1) a background evaluation, (2) a bioaccumulation/ bioconcentration potential and ecotoxicity evaluation, (3) a frequency and pattern-of-exceedances evaluation based on review of exceedances to the ESVs, and (4) an evaluation of existing biological data. From this information, ecosystems can be prioritized in terms of risk and focused for proper exposure assessments. This article presents a scientific overview and review of how toxicant exposure is estimated and applied to assess ecosystem integrity

The development of a spatially explicit model to estimate

A spatially explicit model of raccoon (Procyon lotor) distribution for the U.S. Department of Energy’s (DOE) Savannah River Site (SRS) in west-central South Carolina was developed using data from a raccoon radio-telemetry study and visualized within a Geographic Information System (GIS). An inductive approach was employed to develop three sub-models using the ecological requirements of raccoons studied in the following habitats: (1) man-made reservoirs, (2) bottomland hardwood/ riverine systems, and (3) isolated wetland systems. Logistic regression was used to derive probabilistic resource selection functions using habitat compositional data and landscape metrics. The final distribution model provides a spatially explicit probability (likelihood of being in an area) surface for male raccoons. The model is a stand-alone tool consisting of algorithms independent of the specific GIS data layers to which they were derived. The model was then used to predict contaminant burdens in raccoons inhabiting a riverine system contaminated with radiocaesium (137Cs). The predicted 137Cs burdens were less than if one would assume homogeneous use of the contaminated areas. This modelling effort provides a template for DOE managed lands and other large government facilities to establish a framework for site-specific ecological assessments that use wildlife species as endpoints

Measurement techniques and instruments suitable for life-prediction testing of photovoltaic arrays

Array failure modes, relevant materials property changes, and primary degradation mechanisms are discussed as a prerequisite to identifying suitable measurement techniques and instruments. Candidate techniques and instruments are identified on the basis of extensive reviews of published and unpublished information. These methods are organized in six measurement categories - chemical, electrical, optical, thermal, mechanical, and other physicals. Using specified evaluation criteria, the most promising techniques and instruments for use in life prediction tests of arrays were selected

Habitat and exposure modelling for ecological risk assessment: A

Contamination has a dramatic impact on the health of ecosystem and habitat suitability for the inhabited flora and fauna. The Environmental Protection Agency (EPA) mandates an ecological risk assessment (ERA) that evaluates the potential adverse impact of any anthropogenic activities on the ecosystem (US Environmental Protection Agency, 1997. Ecological Risk Assessment Guidance for Superfund: Process for Designing and Conducting Ecological Risk Assessment. EPA/630/R-021011, Washington, DC). This study provides a general framework and specific procedures to predict the contaminant exposure of midsized mammals using a geographical information system (GIS)-based Monte Carlo simulation model. The model was applied to the raccoons (Procyon lotor) on the Savannah River Site (SRS), a former nuclear production and current research facility. Habitat behavioral data of 13 radiocollared male raccoons were used to determine home range and core areas. Combined with other geographic data layers, such as distance to water, number of wetlands, and class landscape metrics, a logistic regression model was used to inductively derive the resource selection functions that define the occurrence of raccoon. The cross validation consistently revealed a high accuracy. A Monte Carlo simulation was then performed to estimate the likelihood of exposure and contaminant uptake of the species weighted by the resource selection probability. This model adopted conservative assumptions and spatial parameters. The proposed model served the purpose of assessing ecological risk and supporting decision-making. Implementation issues for a GIS-based ecological risk assessment model are discussed

Habitat and exposure modelling for ecological risk assessment: A

Contamination has a dramatic impact on the health of ecosystem and habitat suitability for the inhabited flora and fauna. The Environmental Protection Agency (EPA) mandates an ecological risk assessment (ERA) that evaluates the potential adverse impact of any anthropogenic activities on the ecosystem (US Environmental Protection Agency, 1997. Ecological Risk Assessment Guidance for Superfund: Process for Designing and Conducting Ecological Risk Assessment. EPA/630/R-021011, Washington, DC). This study provides a general framework and specific procedures to predict the contaminant exposure of midsized mammals using a geographical information system (GIS)-based Monte Carlo simulation model. The model was applied to the raccoons (Procyon lotor) on the Savannah River Site (SRS), a former nuclear production and current research facility. Habitat behavioral data of 13 radiocollared male raccoons were used to determine home range and core areas. Combined with other geographic data layers, such as distance to water, number of wetlands, and class landscape metrics, a logistic regression model was used to inductively derive the resource selection functions that define the occurrence of raccoon. The cross validation consistently revealed a high accuracy. A Monte Carlo simulation was then performed to estimate the likelihood of exposure and contaminant uptake of the species weighted by the resource selection probability. This model adopted conservative assumptions and spatial parameters. The proposed model served the purpose of assessing ecological risk and supporting decision-making. Implementation issues for a GIS-based ecological risk assessment model are discussed

A Spatially Explicit Model of the Wild Hog for Ecological Risk Assessment Activities at the Department of Energy\u27s Savannah River Site

In North America, wild hogs (Sus scrofa) are both sought after as prime game and despised due to their detrimental impacts to the environment from their digging and rooting behavior. They are also a potentially useful indicator species for environmental health for both ecological- and human-based risk assessments. An inductive approach was used to develop probabilistic resource selection models using logistic regression to quantify the likelihood of hogs being in any area of the Department of Energy’s 805 km2 Savannah River Site (SRS) in west-central South Carolina. These models were derived by using available SRS hog hunt data from 1993–2000 and a Geographic Information System database describing the habitat structure of the SRS. The model’s significant parameters indicated that wild hogs preferred hardwoods and avoided pine and shrubby areas. Further, landscape metric analyses revealed that hogs preferred areas with large complex patch areas and low size variation. These resource selection models were then utilized to better estimate exposure of wild hogs to radionuclides and metals in a disturbed riparian ecosystem on the SRS using two different possible diets based on food availability. Contaminant exposure can be better estimated using these resource selection models than has been previously possible, because past practices did not consider home range and habitat utilization probability in heterogeneously contaminated habitats. Had these models not been used, risk calculations would assume that contaminated areas were utilized 100% of the time, thus overestimating exposure by a factor of up to 25